From e064b394c5d70463342111dd35cfbfd109fe8396 Mon Sep 17 00:00:00 2001 From: alessandrozocca Date: Thu, 26 Oct 2023 09:11:11 +0000 Subject: [PATCH] deploy: aba3d3a215543a57824bd0e5e41a76f0c963a31c --- ...08020d2d0d8956166b1c2a0f4249e483bb05b6.png | Bin 23879 -> 0 bytes ...06a158d8db082511c4cea0e4da68e13694f8f2.png | Bin 0 -> 24269 bytes ...fcc66bff62565f31fb07f17c7eb445a15bcd61.png | Bin 0 -> 155671 bytes ...c6a3432a0a14b7f0dd44b84e807b42a82bb443.png | Bin 0 -> 27297 bytes ...8ea294a5a37b812824dd1cffab7845b1aed61c.png | Bin 26399 -> 0 bytes ...ca562e1f9f7c0666d018f3afdba61ab61253c3.png | Bin 0 -> 159809 bytes ...9e5f9ddc764fe94eb3cfc6f5154678d1b51bfa.png | Bin 149756 -> 0 bytes ...ea168b29d2ba3be8955fc81e9bd4beba2661f2.png | Bin 148060 -> 0 bytes _sources/notebooks/04/graph-coloring.ipynb | 118 +++--- _sources/notebooks/04/power-network.ipynb | 284 +++++++-------- genindex.html | 1 - intro.html | 1 - notebooks/01/01.00.html | 1 - .../01/production-planning-advanced.html | 1 - notebooks/01/production-planning-basic.html | 1 - notebooks/01/production-planning.html | 1 - notebooks/02/02.00.html | 1 - notebooks/02/L1-regression-wine-quality.html | 1 - notebooks/02/bim-dual.html | 1 - notebooks/02/bim-fractional.html | 1 - notebooks/02/bim-maxmin.html | 1 - notebooks/02/bim-rawmaterialplanning.html | 1 - notebooks/02/bim.html | 1 - notebooks/02/lad-regression.html | 1 - notebooks/02/mad-portfolio-optimization.html | 1 - .../multiproductionfaciliity_worstcase.html | 1 - notebooks/03/03.00.html | 1 - notebooks/03/bim-perturbed.html | 1 - notebooks/03/bim-production-revisited.html | 1 - notebooks/03/cryptarithms.html | 1 - notebooks/03/facility-location.html | 1 - notebooks/03/job-shop-scheduling.html | 1 - notebooks/03/machine-scheduling.html | 1 - notebooks/03/maintenance-planning.html | 1 - notebooks/03/recharging-electric-vehicle.html | 1 - notebooks/03/shift-scheduling.html | 1 - notebooks/03/simple-production-model-gdp.html | 1 - notebooks/03/strip-packing.html | 1 - notebooks/04/04.00.html | 1 - notebooks/04/cryptocurrency-arbitrage.html | 1 - notebooks/04/dinner-seat-allocation.html | 1 - notebooks/04/forex-arbitrage.html | 1 - notebooks/04/gasoline-distribution.html | 1 - notebooks/04/graph-coloring.html | 99 +++-- notebooks/04/mincost-flow.html | 1 - notebooks/04/power-network.html | 344 +++++++++++------- notebooks/05/05.00.html | 1 - notebooks/05/cutting-stock.html | 1 - notebooks/05/markowitz_portfolio.html | 1 - notebooks/05/milk-pooling.html | 1 - notebooks/05/ols-regression.html | 1 - notebooks/05/refinery-production.html | 1 - notebooks/05/svm.html | 1 - notebooks/06/06.00.html | 1 - notebooks/06/building-insulation.html | 1 - notebooks/06/economic-order-quantity.html | 1 - notebooks/06/investment-wheel.html | 1 - notebooks/06/kelly-criterion.html | 1 - .../06/markowitz_portfolio_revisited.html | 1 - notebooks/06/optimal-growth-portfolios.html | 1 - notebooks/06/svm-conic.html | 1 - notebooks/07/07.00.html | 1 - notebooks/07/bim-robustness-analysis.html | 1 - notebooks/07/fleet-assignment.html | 1 - notebooks/08/08.00.html | 1 - notebooks/08/bim-robust-optimization.html | 1 - notebooks/09/09.00.html | 1 - notebooks/09/economicdispatch.html | 1 - ...witz_portfolio_with_chance_constraint.html | 1 - notebooks/09/pop-up_shop.html | 1 - notebooks/09/seafood.html | 1 - notebooks/10/10.00.html | 1 - notebooks/10/airline-seating.html | 1 - notebooks/10/ccg.html | 1 - notebooks/10/farmer.html | 1 - notebooks/10/opf-ldr.html | 1 - notebooks/10/opf-wind-curtailment.html | 1 - notebooks/appendix/appendix.html | 1 - .../functional-programming-pyomo.html | 1 - notebooks/appendix/pyomo-style-guide.html | 1 - search.html | 1 - searchindex.js | 2 +- 82 files changed, 445 insertions(+), 471 deletions(-) delete mode 100644 _images/012c0ac7fc1ef68266b235563008020d2d0d8956166b1c2a0f4249e483bb05b6.png create mode 100644 _images/4a958f6164537dc50c0238eafd06a158d8db082511c4cea0e4da68e13694f8f2.png create mode 100644 _images/65af28bac15dc33c59e44d5c77fcc66bff62565f31fb07f17c7eb445a15bcd61.png create mode 100644 _images/7b5ab8c778114aa5f3811e14abc6a3432a0a14b7f0dd44b84e807b42a82bb443.png delete mode 100644 _images/8b81c2a184c076c22ffa803d1d8ea294a5a37b812824dd1cffab7845b1aed61c.png create mode 100644 _images/a14d32935b261690016cda1f27ca562e1f9f7c0666d018f3afdba61ab61253c3.png delete mode 100644 _images/d122e190c38f57c64f87900ee69e5f9ddc764fe94eb3cfc6f5154678d1b51bfa.png delete mode 100644 _images/eea2e649c26e8415e05af2dc7aea168b29d2ba3be8955fc81e9bd4beba2661f2.png diff --git a/_images/012c0ac7fc1ef68266b235563008020d2d0d8956166b1c2a0f4249e483bb05b6.png b/_images/012c0ac7fc1ef68266b235563008020d2d0d8956166b1c2a0f4249e483bb05b6.png deleted file mode 100644 index 937fbd0ca3d287950bfbfdf8b5776e3e09b9f791..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 23879 zcmdqJhdO_%Z`LlMlwovsFa1C@ed4wM-}! znj{Kk(G2=WUsKVMU zYuCxHbn*6f_fnFRJMzyL*1CB*%WW*XRfvl)y6akcQ7CM7Ujq#6swy%v@}fp zE`ELQZ)Litf62Hr&(^v%E3Hhr*iC48wcIrZ*A(Y(IO4U&tEJ0Cf2aTB6TDsxomO7a zn;+A8o!Dv0rNPCkb%4=BmxYFl!`s$rbc`)%Qm?YEtM$_0>`Ao~vV86S>jZ_KR1aB& zuVkQ!B!3?1O8Zho@JHTFHc1PA9JzS(sQ=HzEY5*HeBt2<aCOr{u@d zilS`$>^DT}wuMRLQR*FpcT?PbZt7%4Fwf0YW*dKd*&|+uS(&!hqdVVzCOM26`PmY=D z(RJ$4UG@2bFBqNnR4vf>{fg+V8$eb$P7}n&gQV_ap(j_-5 z;=N>1opS$n!9?;r7cE`044yP^bJQ~{*wj&$~EtPU#h# zb97BMIrX@sDut{chSDBQzW7w>xsd_UfY9K`D+W6rN|5o`%ws7vcF^akZk302;{M>k z;$6=a@%_lQQ`>nSeSR~0Zq9w@qOE(6-G6X{oxG}Av}{ti(zePruT^S`-n@BJ8giqT zEWixCHNF(-*VkI}B!4Vikvk(_lBJg{~S|YCefH>o7{j@J z>g}z=6#?I5zJGle(bl%`mA%BGtZ$k5rq6h&xo@8v>gqJg+fU(Yx=WerG~Fl{S7Ze5 zT>na3QAsz~H1o2}euJ+gmRD_p#=2Fl?j2)!b$$P8Vb?fk+dnOvG9{9EjvZ&mMjC>w*@ zu3WR`YgA!+K|w)<@0j((VL?H`%N2JmYfhf1xO=z$;Y027?RC!v5Buo0KGDf~LfLnV z^V>y%9$V*l-xN&XqSA5Aw2a-suXqJR%^o;}ed*K_5PHtxBk*-Q|8Cikl`EB%e@3k) zSAXiVVcl|}d26X;JzQAL=f=6j#ATbAlQliHg>FA^VUJH`+__65ip7qJay|At!?e4G zu)6t%Yis8pZNd`1D0|n4W~)Wfl4ZvpL~rV@60)9o{c6w6iATGQjX9n@e}38TgVUiy zGM=8EXKeOWdJg6t<+)~FA|zv)zp~%iUg?<^6FW9QytJi}Gy}hao@o&dfACHUYfZ2Gn&zzT#F8^t3|z`Dm!7I`5jr)xcKGv{OiRbs zm)h)MK?32^eiKz5{n`^#Pmj2|8r?biKF@kriCOW5qRY{@j!a{r1#p;IN(ncKS`Yl_ zsatGSbMkkA&Z@z|LGGIGxhd8GBTlQ#&COrGeXDoj1!r6~+3M$C@aoAQ!5m9U4i(T> zAKtKH_*(#lEl%^=?z|_v%{O1VbSdVotmE~F!DSpAJ7U5U+TP~moXhyWy!FeMFMY3+ zwro-HIB-KFbV)v$DYK%Pwn~Fpj|{Sx?X$$9&!?yF%XU?pA3J#Ppp>kv?8zg=dv9gj zwanL!S;1iCxAc`4lUVECS1m$K50~g|Qo|xKwUBB#q^iX9>0n`c(EP0P#NpMZ*UpSI zY+lTnQBpv0KRCi)6@jqU#>y<-v3p=>NOa8_7A(!kUB4FZE6-Jb>pa%{eY|MTo=Ja< z>VpTl?Adwl?(V^Pd6Fuss>b);9C5Ye5TCsmE+V9Zr!=)r@}yrWPk(!4a<M6xtbD7rfg1dXiM? zikKyo@sYxk^HQnbMqVh4D1OA#wF7RL>e-d8FnG-&_tx*my^R`f3v=0Lb30tlv>tGD z6yxONq)@P`^`b)F+&s8jD!D5WW87z(B_y@2|OT_SgV$6}oxU$AS>P<8kAPFlC#$jB)8d7dG!jfA?- z2p5t^1QWMRrqAb>jmjg?zLU?4PEIqS$JjegW7TNQ0YC=69&%SwIeP%38 z<;2{EkdP3g8%{d~RQ%X)9eN>CGV}D4cZGYerbpe`vu7XJ1pTJVHHpIgxp~_#MV5;>Rpp8-G+<)IJ;^vn?u92ms zdsZ7Gak3s88JfR4J?-uN=^34(qT&|!9?IUEF2<|}FOPkEoZk4uHe-ti4ewg3;FS#d z*3|(~+y-uLZuu|T7gVrrCxIW+&J`8O($dlOj=U&jU}MwC+jVImcABlSvNH0_8JV?d zd4`uyn-y*!e3aaAb!U2CjM~YQC-W`Jvb#K@BJ%~v1yZZ3RHlbJ7RSfOGcYqZ93QKe z^u6L7fJOY|qT+6=b%q%#QC(eDuV25;+*4@QNOxoZy<-V(N?6POdB{)}}66v?$-E=Kl6Bo~>GryYSX+Z3VmY#=pOFYk2X3o1Rsm^sSD_)x12cIIKk) zO6Rpbg<5s4Z*NMQ$|ScPjEa=yCwJ7-)!mBEjmqq|3n+Oru&mf{PC4NVayC0R_a3Wt z?H3h8v$I7^i}!LLd3SrweYWSXUh!fRdp3!Sl#_bINe1zH|6OklYil7^Ar%HJze>@x zq@O>=`lmlVZ=_R@kzx8V`abm1CBeWGC!(31uvv>gzFZ_CQa}c~tgX$U>f6hGGrxa) znD|^$lYQdncTXL8OQlP!ymHpE-NVZeXV0EpD#gX*clCyN6y}i8_ca93G%?>QX`{eGsbCg?nHy0j;nRjh1f_`IT?o4VnHt+_w z?k=%*nw?LY8_q9h5#dzGYLTw(cN_g*$YgDKJypx`6sAcwY*$_buT9{oTZdou-5a~# zkhaJpw5~d8 z^R+Y+} z{ms2=o@A)*tLhjUXi2Q_8e(;Ib?xcz#~yxn>oC2fWS(aW7f)eb(m3t#(t3sHfe!`$ z0Z{j^b4rNGDBs_l#zyWj{oeOOFXroEPhDu4ed8I)jE3gcoQDd_m+I>3Vs#=|RCx3+ zp=9nzlxX~6w**P<#hzc!cvi%pJ-2O#cAUcPXk~5MO`NMZ;wNUh9W%(lbUuvXC*i^S z^GlX}w_P>DnYbzAlle)s8nxd(zlv@hj9Mn?KKO{6vh|XZkDlxF!Dm+(lk^Ux4Kbm3 ztB>_7%XYA4lM8H1)=S{{klsd?H{H7%&TMLP!=eZ-OYR-}T7Un6a+S*7Cx``d7ghYr zD{M1VkMjgn3&qC9x&Zil)J;!JoGLE<${h0#f_7$KlXq!vRD*-kB(p+G$ep99>SP3X zu@-zkoZ!8s#J2U+yTjUXO?dy7_I4d_Z|@21%Lo)%nVA&s)n;LrFWY$3xjw(jB4d7X za19U@vU%(FZI&frkK3YDl&RIhEqarXT-=$w z{CtL?_RDe}X)3E%Gs`41Jx<>&*FF3kD8Ll8QVXB|aMetOqd#lhC(35t?iB68&^t#h zs4D@F^l>}#j)cVd*TaeD&o804`}#Juy0JE}{5;LRa$e&zlJ4(cBld^P4Lh17<}kgM zJmlrb569xv=cVpz-8UShuhY0I8a1NyrvLTptt}5F1H#63p3nWVZ)sHXfVlI(DtU4J z&dsirr~I^7o2$eX3_CqOwH$hNJqCko-|eeUVQdwnxRf)WD|xX)i5_z!%VtO~UT%w8 zzFqZXP7%uOO*)7D{HLX9HMXL5xViU8R1gz0^TLFe+}wq;n*0phZ*|l8x3<@b8t<&2 zzqOYI0Xyd;m%~{d^%Y)ioM}9GZr~;nW*(HkE&Q9t-NjdmNH5#HY9amhN(Mt&yN5}e z*IVy4V+yB1>{^)7+5et};oNN_n%b{jDg%S_rx4!w;u$V7n*&o zEb))`$oRJ6*52O_betr*+8W=r?pi)o^Cdj2EuDG6{BX*rS4<(4YU_ozddu?(G9TmU z=;*ZLR&j@Gt|E6H{i&2?)twF|MD1#sz=ZFGX3hQWPa-;%M`(_`zcc)a^?=bc3PJHbMvQn4)acb zeaBnd5c;aWzaNRk+k3;y>-(93dCzdK&OXq3UffKce}l{TgVt}3Cxw!ol$Di@n|4;D zMY9aLf7bS|rhm3gB_g3&6LqwU(znbjDLUMgwL4FQ{*X=<-R)=cr26;|_t7rJi)ttC zR=8N-`#ye~UPngNPS$c_{K8=k)3KJD>oHee%7tj(G*%>#=gz5OkVO>K|)mdGyzI6FI6&3;Vx zn|i!?kxExZLPmzQJ-64#wlr`DLR?IADk>^^Rx)lci_(Tu%v!v0<;n4c&GB>!;jKAh z*T=`*r$=5ev)r3*cyIoJ`$(6+YSnmINuf)>YLs<}j=jA-FmX&wD=Vd0CuzQ$-wPKk9jh&rPJ6Y-gunIx$+fce3z!pwC)BwA6KIQ9a>kI!X0JU!zV zcKS~M&W_Egc5!(2{L{C9z;7?iE$(_tKa3TO1~lYWHx`#Q3zhC=e99MQa>C9`n%ihK zcWU>G-IK{J&+Z=ov6f^$d-2^l9TbZ7$=N{+Hg<+w&9Cydr~+A}AWQ7@qJP*7Ykw=D z+=$7ksg8TTZohyWE$#;@-k<4<4yuwsu?4b@BQ4=u*N~|CoL_Ldf|KtL`EXfiqt2`U^O<4PUf$qFwv=J>Q#`1{wrd}%iNdYV?dX7g`#MYs1W5hM%kzYH4x zTwT-maN-DRQti+sEMf+F6B84DKfm6wTerLvloOd_(;79K!fl8EOg>9qUrWv(8nB&c z${+StvbrBwi3QLY&71Y=vz@bZ1S*jfixyX4=859PVkPDGH!}tZx^~L6jf_4{-jP;j z#A(Urur}^3^AFS*{Gidawr}qRfg#g0@Us7D*0!1P1~y}mTV$N`_usn>`1bPm&mSJZ z?VPLAT3T8t!NAzR`q{sOC2Z{5^gFe6Gw%U^w`<>fc#eKys(YazN$`B^!B1mk5=|}T z;v^&`bAX=4zkh#tYB9YZpRps}sE)v{&E0;B?d4EKhpoxJX1`u^tp+2oJa1?5J;<~Ap| z$7&YTUKUx3nmf{f(a)M*y`0qShfAtYqb9Qhr@(V3Ta+G=324X;JAb*7x77Ky`Y?eF3hJou7YSpQr!PqiZR(j~^FnwYYX<(|!56(@P;S_sG+L_#aonM%WKO&Dw$* z0(__BZWHh^+48fW@-9Ec5^YOezZkQgpd4#?9F^JJkFmJRLGyg8R;^mD;Ivf#Zrjo& zi%m>S^tjq8Dz>=X+KWlpaOCaH2ftG@GBV187TbPNefIorKz1HqcZAEjW z)t%*ybhT4EdSsYgyV0%Y_i14NR>77cF>&!#Qc?_{R8Y`H zTo%4OYIhVnm4lbp++JK^<3?^u&+u?0iiG4XVbv(&vz>b^W7%SaR96(5mpsHc_KX}l zIr~@;Q^l8CTFUNre^z3xRYmadu*-%+jwcKGJtIK^pw6Y|<>meI?hYH!XNodslo;Tb z^OK9xWeI6%X^a%C)MI!-H8r*Ty|)gf4fQ>Dnjb z(CfH;WFIyU%E+mi*rC^VeO9ae{GtG6gtg|^By*fixjR@pRn_VW+lR=UZD|V4t*whG zRdXYS;%k#PAAY%%TgKEct87-~OTz6V?@q_5%`x2b9n%JA9gKC@gLSXV1!iIV$B&4J z2zpjwwWY{+s9Xdz*w-C?DI18rO$yqH1~&Ea*W#-WtXqCAHPynNd#XO18BAVSObkm^ zb+tYc1s>m2W>3`m1ck|`{u3T8@%L^KfY-c~@yRQmM8!jsQvLak0E645u4eYUEU{@5&;0y6p#^tcQfidnkqs(G zX~iAZ;G_eb6k5u`H?s*(R&irK0~db(AOYayuL&KjEjp|%&P$qEwUdLb9R<53N!CTq zA(X-Kn=9UAYAnWTYiMY|mUPr$+O8te%=Iz8zGnWL9L9|v+R3(K$8L9d$bx#{*a2B# z32O6gU{*M|xJ(0CFXt|!T?E)zk2#3*?e?dy`TdUzD{}^pV6z?eBx4Ek($YxYG;n^qe<%*tS_vc1dpA}XY zB2kzyO=ZnAFT6a@&4m1DU>^B)vF+#UOCX9I5GO6}9b2<2Lq*zGAo}4>MJ=&P1fa}q z5v+bgmwefIc%0%lH-EV2%cgq#`vXMzQu{`xr9vtec-vm3wUM>oF4D9-+&r|uJMQ`C zZ!Tajn3$N@d3osx+aqcz)_UArQY7*DwLPm{-{0j%9%!mr`0ZBNA32ItfJnPIR#-h2 zAh6uPq!QA{DLv`OO1UPBXz$+Bl|SacyTH_<(o=k`&Hc0D`sbSko9vP1j4KHfQ3@il z?UFJtqRn~bSQmsAin_Y`uWzqx$lP`N^|N4cCJ*-y$+TpBq}Z|ti>ezm)P>U9G4jgq zyXkT&UR1~aQId4ykY7Rt_H};OS%j{J(<}{0l@lKp=FLa9Xe)yVe0#?&4y+pA`t|FP z=gup0TE_puo|e;l^q>oBC;LdvC~%YTc44zyEXu~5{CwR`|3~jI{l=hW&#u_0H!8(L z4Ye^?MhW8j;}7}WdP3RMYC(bx#F{!GDAy~GRfS?<_RdW7=kF;zk5$j~cyyHRR&%%s zKg+PV$=+tCmAV^UL>13X}v%C*_9v+a8jm8u@3rhRt#Dg16*u1Skvbdklsbf#Mm z+8djiM8(8tu_3qT>Lsu99ySV`9ZYfh=F98nSM+M1TXi^QKxEabMXanJtE1m1xs#N# zA5149nl$sC_kzRNe)7J*N=!c}y_uQ*xH8*18uH{|CJ&^Ez4m?Yt#F6*oQ(VeKwY0OAyct*qECo7W<-H6pI2;N&zJAFOF zP&U!fbLfd+(cW83(Y$gGk<+7aM?1t2LRVP!rxfxjIN8okf7%i>uL3~?(U61W0yFHs z?f3=(57lckopJB(j}WrwAs%N_b)p7B=!A! zX6S|bs+SS7&#&3X&dC`9B_R_ra=H3RmAl8j9(p$P_|UDrAmwtPaBeyFWjPm9L0r_G zK#~#e4YsB@Jc#5Vpcy$p!uKL)tf2B~B*z@&meeZ{he^!}pF66CX5*4Fmh z40BVgE`8w`9u2uaf8E`yz;!xsN$4UHN71a2d4Q7Rcm_w#hiCah36%>80bFc?GAqRvQs44*wiG4r;b3Is9Hebe9TAyZ zfyJzdu~MCUwuNTd8HtMpzH}x$<`oo-p=0K;MXY!C@TkK^i^|#-(FfR?;QFL|=NWhxaew#09k0;N?$1h@IV+)+=jo|rK zOQ#67G`^)7{8Ce_;Kb17AQ1_PB}AL4bVmAqKxjBfiKLdStE;Q3In&I5VuXQ(r4hNo zt=~OMlo@Y*9u-;tBY)HmBY3(m;|TiJqTdu9=ygt!rsv1bLTlT3}N7 z7-Z}bl2nY1jbE4AEyhIeIqJ2{66MsW9cq=C(R*X=(C~>kfonHl79>7zJ_0%o&=LWS z&HeiqOXvd4=Nm7kjq=Eflonte*taa6Ld^=#|^Vv6z zbFFeUnQkBMk55e0UEhDN=gSvavp|sm4KQ{(y1ESY_4P)#4((aWziBBVWLR{xe&qoI zORP_P+k??2NMdkPNiG2$iJMOT@(T+KBP$LOV&6nN@8ugQP~e{|d-BHXzici+88;*u zXn59IMNafL^<(iogv(*)_bL^U!^BZR0vL*&Q`RL-7_c)4Ju6~XY?Mivz4I4r1hwt= zxGG)n00I>g$u@5@7 zwkw|<+28v#OMRN=(R5MY!TqWe-wWk>$s1s6l|qPHDzL?6W|E1TFmb^$Q5FN1#nraE=x8vJfHnVD|cPvEfmEdhkk$w!nImRiA1q zeEd{zyM2g#a!ENl^<3nY>{p*TgoI+Tt9!5;2~H>Mf!c|=+9ywTP0u>DrJh3V-v4WM zYJ7T{>qMab12Q~v;1w8^`?m9s>8tAmezWH9cqp1Z=`}g9qYWq#gPCu6LjwAD_^NHE zBj;R9i_MrJf)HvJJGH-o#hT)_LPR9-JRBLIC$eKJN4^ODvjHuR&2tq@}g<}-eH)7y$Hm6vWumS&sW(D!K{n1ajU z=8>MTor`m;>n=xL@x?xt-G7&h{OsgOwSXU^G0?#3k!^>|AW=szre|FV-E7ycT_RU* zSy8W+3@b}>lB{v7*tq*P!~b}V9@#v;uyMWf6M-vvc@EuG{#!f;7*Het9){)U#I5*d z8y3#Yi$rQyAI7*aV*yWc90I&RF2+kOX6eGA$HDEeeFIVQ9A6}uh)ULt3?*U^)g+IT~ ze6hF#dHWY08noB-{Yo76OCA^C=a+gj17ik6!SNmqS&LE%5&{eiEaL!NBq5aExf9gu zF&&_~m;QdZ@~Fnsny&n|p$~hNtS2Qz61@!zL$&*26fS(BDXcNr?pOfEtUGXO=Pw9p zTf9ClMJ2c1b3nJVcpvZct2?)unZ0C=xv^$+$s~=o#*l?@?Nod1iRp>_PS>jY!^`XK zi~Ha7knEFi-Fax+NUJ1GF!bCg=T#z=vokX*Wo4Iw%^<-K5R)F>jithB0yPWsKX(W1 zchQoU_!6m;wa6&HGxx%7H}=dIeCzCVR5V2sVt#WO5R9I7Me|Z!_QzEsvm0HWQd-Zi z3DwT23u9bHxT1#l?*)ZVOmo;fIOtbx!jgr|lHJDdDaE)@HlD0UHpmW`BK(ibl=w$B zd&58AFgegtaq_p4=C*Apog)x&MAxljhj14mp=>ift)Bkz@hT>cKv0O*$GH7bwld$dasfa?l6TkP1^QA|&nQPf!y)vfE zu_GmpKc_!;>cNIT?M{2pyu*A--BJ#&o7H)q5 zRBLvf2F!$qtOH6AMdgl#+T6_Vn^P8Z4_mF$#Il|HX73zmLL73+jm=SoQq&Nn<4Y>! z{LhXHaolut!FP9kA09I2rPsc_?Uq-1nd5gy#XipXv|ju!hn-eqgk`6eR>GrKBj?Uv ziqpKb==LG;5k6=X^ynJ17}sdtplyfC)naX*~aUf zC#a?ob>RK`_kmg(VeH5<(mjy^we-dx9c#_Vq9F|IKmN51;#C7XwRjA(jBHVrZ-H0i z`G+HvukD!9pKYzXq_j~|9 z$3W~hEvJ?L0ly4OwoXhlSK(D)o%~}FJ+Lv({{R+Rp@QGI?U%Q=n8B}rHk^zdTPZTJ zzdC@s`|G`)&?tTPZTU-x6GYC4Nk!$R%G38`Ij)&>$#f<@-ohzV4B+%w00N$;lK z*cK_16t_pas~DA)?+s-H9X>)HQU+8YD}eR`Fp8|aysd$rbR1Er+87`fYlAN@^_#G- z>`xUNMd&KrU{_BI=Uy9#ZR+5h{Qb?`(aFiar}mVm&U#A{+6y-x|L$s#zKI1$2y}Et zmq%o?R`u`i@0uSy(ljtQ+huIPV~+bC0zzPttDfe(y6cjRFPDhC@#dplwWz5plx77; zJi8?zAV9K{YgYva>;gd39BG*>{F^f2m_t0v!-ZB5khEvDtgIFickkd}IQTK@)JE3X z2B)XMJ;d zjszkDAf-b>4b{v#r_9Nb7TjHZTom*qyf(c*>%FLpBEzKM!9_(clnGJDa?NB}ZQZqt z_1Kr!r;rfJ4DM5|!%)45opuofWKD3b#0z3N`SXa#;oGine(Lf9xu7FhFfhHLP<~SmOwy4T8D0-4+<;1hXwxv`JtALo|JcSiGdE{H z)?H04K4L9}NMtTrDM4OF$t?2o17jnp}Z-IetF|knsRYm$fX{!XhwzLhufF!M+>qYKh8c zEPGYqI5%8}DzM0=MhFYo-P4myUUDJ|GD7)8unC_h-y=`AjFz6h0R=cVE*>u1Ga)G{ ztiLJF;m?9n#yZe4?CI+ZA&?T;r$IRA*DCC68T!vJiyQRis>1*VTLl}xkS9}Z1Th{C zl#pobEIs;O$*MYF57vQL77CA5 zqN1TG_gW*n7|2=*V6C=h132p}vP{&8Vz#@TXV}-B?7vm(K+ZI1ai^ z6r=@;YqBN6Kui(COX{X0D;~xP%i$3pl1DTl&j)B+dh&NbWe$6M{OzOf&p^fwoNSTA z);UgIS0)#mgpiML!e}&};U2`e9q7bfA{Z0oz<<7nF%wl#SeBKQMJ8VUOmuWZrPt6p zm!~T$b1Z1du1T&N?`@cPZm7Nr1pA9?dlJbadWL^1^BUUavSCFx+Zvib-@{x&@LeA? zABg8NmVRFoBn%0x&iV3*hw{>-8pxKXBIY=u7|=WYSk#_PtFldqP<$>uJ$ljNCC!43 z_K+w!jQQSIdeOtXvlTV`1RO%G*jm;`s3QQuo~kUQL`hmA=|0g{WfSTr+;YMa8qRLsZ(Z$&^psgW_r0vH$(4v^wDHZ~}kSHd>M6s|d{ zt2Ld9FJ|FaMD3)KDFV?A$I%d?m1!hJ1QT$)qADs@&tsUJa|cW`$zn~YB^(As6M-|8k?&JH|CrAg2?aIm z`9EDA;^h{kHfW9)jnBx4#YTGchkxbR(K9{xq2q|t@-HKsBEX_`k5Auut0TEkQ2+KB=ckXYNMvb4m;R)o)zz#_vSO`mn}B zV(q$)EKe@0$K7yl_f*)WXw)hg9NC-@rY$BqVDzkE!6<3;__1n@;O>>ggXH-Bxjh;~ z7&$pDpkjS=< z`kBE|8>veRWjgEllj?-rTm=S(Zoaski+`hSq?uF9dB9Hp?8gF0seB;@m$^?HGWA$0 zMfP$NBq47CORJKc+S)fW5l!B~>CAClA~ZtQEadmiNku~$nVDgf#at>HSpwriSW==# zqB^$bCVi}R{JZ;v!O!pVTjpIh&dCtb9s5BfNRT4xbRsyAM7v>?ICN5mESOc{Z}e7sOA}(s9C@ zz!A^k`eJZu(_Z+&(-Hu2VN;4a8CTxDa;3aDvvit&cI@HDGpySYZP9ad&MD}}g4BGF zkjUYNWn690>+yR~g6_#PuFCLuY(C!F2s_z3?_ zY{K|=^h)e7H=dijrzgKDUb>%==_54=>HbrZB!yVh=Vcq1mPn11YB`<4`|*4aaMLKMUuMf0Zicoh3HHM9)F-S7z6+1T=0xh|BCYjsLs=X9vXD)OQWc z#||AR7%MQ9<}Tg6dVNU*?`itG+zVB}T8RE06MfqOLFiANIz^T2IlOkN*FWP@XvM*qBQ9TdFYuU}(;JfitC zbe%$0+5$znyeStynWntL=$cqsgrrntG+FI5sLsj`W(vFiXAZPT0{PLwFIKy;F zE=_uaWrX3(-sH<%iXNrA z8*Z5Gx#@m_G2_;?71exO3ry`n#1bS5H~A@GH^P2NNuB%tNkq$j2hux+sH4i?3l?)x zunYufKmef&@9VvGg-cS(U~HsCURs_^gu<(QV^IO+V@u%;APN?dh7u(W9|=Ye7ZA84 zcYlTkRmek-Mud?Q6BFw}mO5=R+kQx-k&#J^I-AUysNi3i+w_7fb3b-W8#>PY`MJYX zozF$95%%Hn$D2Qpst1x{12FlygoKcG^#uXA3EF?%GP#(!wT}u-d9+JjIdo)iPu*~k zbL3@lG$|<{GI%zLtUiDFavbPgTev{r&L_+`Ve62s&j%DuU!ceU@Ak1E*N(5tt#c; zqJ04(9Ry*ObIL0$S8A}A9{+I^7M!J|2!P%H)Xa>Z>+4dDa(Twcpb(m5!Ue^1yTJaM zot;h8eZok?lcDA6S_CyUgjDn(W*YypFaRJppmM_Zqq;h%o_-EX##?)17?(*9g9p6D za1H2S1a9sv?&@ehdkL0Ux2lOH0J2%nKe?lYfskQUx9T4ed}PUIXlO_-3Ea%U$apF) zjtw=EsIRQN0*Xw6atMzHMCkhAz96~_v_WS_vx!T7CS0>)c;}&w*e4!D7tT5iT4^I76^`pc*bPQyTg=Qbdd-Jx*H^$jOXFN9`X2cyKy&!3`dYSyC`Vj&Q1 ztG>TIJls{OfJsGYB>XF6nr6Y6wx#6ZRa5?|@Zk@E

|yqIAYy_SDIdhd{6u#5ZYz zg1w)xD-fB6I|~xYt-(5RbTA)&ag7_Uy=b&{*kS0fNSmmt^maKZ^c=ui5OL?uW`fKR zuKJ*(5m^-rjoLMBT!7_ehugv7_7Gp~?e7o83UR;nEDVl~9%OG1$dZz=4PDp=zM~Oq{1=DFMn)#V zq7KEQ*ApTl@=+0J5oi;v*q>x&p%$>k%C#y^dV^;nD)R;qxWt^L7P!S^_ihdWfj0Ra z38b*(i0Z>?A^`*uh5^L@HvXcL`*YX2%8K;hjec2T6Gy5wQPIWVxa)}<3$xlH7$Yk{ zK)fy&Y(lk&${x@sx==k~i8etxMa#=ztkVQsU{IubK7ERUSV59rh36oXS&>DZ{Eop8 z^5j~Bm=K88c2I9;KBl`7nNTO73v@@p2MajNw2p)+^U$X1HrPR%t41J&?dQh#9;**;S9D6p1p{j{CLMz1TCUt zpJo+2gGq-b#Hy>Om!N#!@}A#>NcV{!`)|5^5Q6cn5deqO*!W-TQ5VNXP-l_4CJ1Cy zMG_x?2Fr%{YH`zr!+f>AG)h*m0Nb&bJiyTqy9YuqaCu+WfEb~9MPzuP2RA{@Ao^b5 z?{BZL5|^QX9Ed$I3B5fW#09CCh|~;oF(G=0X;x3X=4|4@p37Rez-HXtqRMYQVX)FS zyVbvY#}A1tyw3KV@`aYl6F)bRkU~HXvNLQ!ntFOnrzeZB@${`s~quY*;?zW z$ab}#M5lZ}fFx+D7Qw zX9B|JU=8Z(>nAFoA12NL()EMq0eMxAgj$L!5geH*-u(de$OMU8&%s9)W%hLNy`4=; z;(||us)fe5UPoah2E{fSnWUOFv#yHss6r#=uhxbE)`VbLN`+# z(DY#J9*Muy8dw*j2x|v06B!e;9R#SKl%gdq^}#I(e+5)Rq937{TU(i7JK2=};*t9N z%wn+IiYqoBJqv_o56%y!NKUnxp2a*n%B5gFN82l*AqlS8c=%-|77R%~R{Qt2s#rr! z`&TRAA>(osKT8zwlx5TmeTVwHyDY&kkOEXo}jUHR$l`=0o9JiPp>fm!(H-9AL;ZNOE#E~~{rgC_9b<;AsR z7gV95WH8H@-*Nl!5Or6X&kv1Gp>n1WlZ*S`QEYQ)4_(?9-T%`!8`+tpk@;^WK~bC3 z;uVQrB@#XLvCGC|@b)66T)ms?>8e?;eK8IEar6Z6L(Gsar>b_9+k5m%8*D{YfBmD3 z)|y00rcr^NyNAy6+kzGnQS+w>r`nwDO0D9rj-$)VHTI=0iqyZZ&l#U;IU@L8P7mQf zK1sUewbsY8Bss`F{O?8>o5DnIRuL~k;%f2q2OLwo(tS{df+Go1{CGsBsQZ!!CwY|S z`$x9Xk-4>8y3c1e&~h~d$TqqKZFY|MMwrSe1#HvCzZO)qrqv0-?6{tk+CDc^yjlO$ z+RL4@n+P6=-wq$~YxGA>a^|dBKAq5(Wg^2qJSy_f)3xozR^pMfUJBO?vW&)MZ-eQ) z0hR2{4Aidszh9!wL{pQ7WEgnKiED*SEYh_5{Ogmn6^haGHw8dyKme+!H0ANJ64B3O zhlVD44+E+NG+gT3E);h9bRVcE#J?rz2w)DJpB)0B=``{AKMf02aep@~Jow?lnI=m3 zv-pccNqzZZcjr>HL6;kFs?yylK-+N( z_}FbOE>fU)nJB~W?`#obQr@6)#)hm)7HwQ5mOGs?h&? zg^P#B9>|}B3%nwFOazG$1-K#P#tpB6Cg#5nJy{gc5FOOAY-xbhD%?4aMDSo3)mvn^P z`mWRq7oJ|ZTB6Eeiqmo#_5EGZ$cO07zGB50WZMS7aZ=ylT^1P{dW@Z-4F)rVHAy%SqCNw;gE2 zZf3l9_(P34g0k6KzJDJnv*1Vb;-Kv};jmjO#Y(}d*;TCb9c$}3$ zA_qx`{BBi?a-VG&t5@d-mpI$aPt6x*zsZ{>;k5VZrH$uAVtbLV!XM3;%7E;s%O(` zZuCmOvOZ2uML>qMuiSrLQl6LW6|rl`b+R`11#r@d4*GBJ`g}f({F{wPXe9OEgn+&O zGnWmd1%mjNQ6Cb<_6qf$9RPyp){T7n)Ck$0&Rc+axKGSY*I`ge zcL5Zrw58P1zJX3}LU6RE$msyWkm8iw5qtyH$~z%Ok|^=aqkA{3aP{SkZM5Wu#(bnY z0Umi>;US7PRH8c*ixqrg>p!=?mFq)-cX?UFw_<}!@Q0H>S!9y+Kz)}hJXTnNNHqZ8 zJgE>!o(AJi6bIq~#7q(ICzA4-`vx?%M1UeiSyP;F6XZEbh%AY<1Q`WfMGHI;+5mf0 zQI#5% z*ETijjJik=Q3}1e=yiZmS985dB{pI(_^P4H8~!Y$olB(9mgpawgB;PG9@Wzyg}^r`&@j-9dzA;rY0}(lp;=q zcn9g@#RT3c=%he7FhFRIWOT!*2n=m7KsP9R0 zF(~eb5Oz*uw>W@-0$Q&}I;qeL8VtV0m!$kE|I5P&{R zN&(`?#8*y(DsK^N?;{N#gfv2RK>{U~UNUuXqW+Bye zOn-jGMow_?K6>~($}dzQRFmq-Ut2bBh<`y?+XRvv|2g6YDnrh{Rfg=x>ENsga7Kx~ z?XTU1$zQo{-MJs%k`wdur6BRy0y)os9l??@T}vikD+$bA&!ve-gO-rL1c=xFa8pEp zxT=U_f`IPBNTgVp|LylFH)S0R1_XH`-LLtar>RZKKd1JL7~JFL(f33LOdy$`a|d(^ z$O4%P4DGTBL3udS%1mZmaiL_u+}-=*C9MEe7|7DVSx?Y_IY4rRk`4I&r6uona}i7g zAXOR=c|Fk8*zL5HCk}B-m-c_pwCcIBx%FRL6>#;efFdWhYVUy~%ZMgSuske}7Pk&1 z!%!fGLr%0DuasJ_z`w+Mq>3~UPJA$v`4*r`fInWd_pfY;f+vL3ohbUUAMfn@+fVtW zyP6+sAz7I<-jNL9*?-7UXZ9lo%C|TnN@xk{9Crlx1%{r1e>AJZg|sM<=OVpVu1Ah+ zPfxtEih+iNK!m?lYHC6o4|T#R5HCi(h>TGum`YXh=qDdM!#-%6rCy|2;|P9Ing-})~I zfjH}>0X>z_phb+SV(?ju#+N?80T;HC&q$`>Wi?cRNf@tu@^X)Q zGR)|A?mBhF>z^L$WMO)Gde=AQbO^%_(ECn8j0_@LwtPj#CANYwUQPf_he z?P4+4Ilg1aomj*!?R}=Gt45FkDU_D-$o+rd=ht9bk=QZj^{*n@a>vi$D?j{{VXlpGY4MC>e5s z41C`?fJ?+=&P`SUUlu%EI986!r|r{zRZEFt1A?W{H%Ch9XIFM$Y-Ki*#3TCOtq1gK z-v_G`UlNQ-M1R6OBS-E;RLHH@?}qDu@oyZLWt#2-Lc9}a*ZF>POuOlcGLEz!5DTra za2$?|+JUqx7e+R|)+a@}KLVd@e$p9dp4NY&R8`wfN-)lxA>Mur5)OR{)m-(BV@~TK z2}1vgoPW;0LFDY|%^LjEkNW6+*EHM0Y$_9#~0`= ztnX<9YE33@2kKP|&TDio6Wb8-hbjlDKH?c+O$vh>oG7l)a_hS@@)n)@)GJQCp3~vO zq^l7JudzUPO2H#9Bah6HRskWKbeRC~Gy#&48?h0Go0j7e99Cdt#Eu0L0e+s8u?v1I zarq*Z1n_XAMX4|RqK1)I*9DJ_b}@!)PSk9hUWVgA{OecE{nu$~Pqt0(AboUNT27Ae z4v-@CV^9q%?~(NJ^_Lwv$rg!hYuhL4)aSX~F#m{amRzH`N3zKx*cIWR?s)!c&)r~0 zp9<*+HHBgQU2$W4MV&H0nj< zxigUj$TrKuoQ$&&L-HMVu^Mg-*mWx3A;IU*lq{yI%MTx>mp>&Y&$GNf2Iae`k1nwm zXEWj`xAv}<{XB5c!A^X|@ne+IT1#QFo<)}35!YUv{H)@*#AWSVQ(LbMW4U7ee+H@| z@_|8zxukFhj*k#K0Ik%LoG^l)9Q%(oci^y3!V``2IIj#37)Cu0!EhzVUop&*s%wcX zGs{=7=u~k`qmGzCD$WkLZ<_K7|1gtB#wH9+X2BbN-doTiF4kl!zaG!%1*z>thxIc> zw4LmM*~68}ssjUAVuIXq*`-8(oVhy;0g7|TRUgdBK6J*|>#_#}#Jryf<{+mZce znzsGlt$n9OudY{dvGJ=)6GaK}!+&n`5G|hn=`0_g;q{>t651;?JW9jnBN0&ZTkhAd zsdl3144%>FIYS+LP0YmqoI0qdvPcrmxM3>(G78i=K_S2i+-eKI zyej+8(NRw}Ef*oR1yEr8#fwXi9~a`&>gy@fz>AqVqLZn)txe0tCBMtKIfP24H$NhR z3PJj4yRr`WBu=hFrOM-z(;yq-pb)~SSLU1xC&*5uTpnE71H!7HSn9g#qd&UEaS^qW zZDtz$_%Rz2&&+U69O)LsmC}gf3N`K8-di$%JBSn&E%BR=1g~m2=8|{;Y)aa=)PGOI zF4KILD(N)q?J2V0AgmLrPecKPE_nxP3@W#WumcryJIQ$9%*k!~{@iAF;fvIbhk1zb z01G{=f^A%cwvQ~jxRSx;{oReGGTcDhbT|vdS4>{v&(%C}PzLId?a*+JjdicVZMIQA z5TR@Zy9uJ41(2TFCKu7hK)o6RWgT4mR+XM~>6?xuC^Mz;k?g}^Tt>QvaRME1I;r9j z%$!1qHl}6jN?dUMQxd{Wy1DhFXcCd>g{vIof$}-D=zwfQt}jq z;o^+c?JARnUIqdU?Aek>m-9$O*mEzFhK)soQIs4MitW7)m_{^>FMa z(wSo)HHe`n4c7)+O_Zfgpy}|!cGMTnmh^OYuf^F#W&Tr6cxTwb43<+LX}I9bnKMr- zJRCM0d`63Gf<(HE%8H8w$be!eZBejh5mf^3EOCbV&eI0Sj(~hPO_20ga506Wv+)6S z$wg-DfZz_XZ;St=7)nzzwHkjOVThA<5vc0smX#6(2&byj>?nwg$Ko&QT`X{OX@jew) zQMYCXGogMaNA;ibe9APsW^=qw#D)V&a5oOH8qO%2xGL-Y z_mQ^))G(=K_@@h{$a!>NE%SdLc{@OaV>nN5kqlz8s^vA1UwV%J|1^4$TtEaI1@e5Z@Dg07UlaycAnl>B1w>1Z zL2L*CS0E~&E&IT}zY=h?@=D96S?x;>|8E95;EM~WHGB5oyZ@l!%9MNHYUV{J>Tu;s z)w#_}z;h}t{-Q4)Dgo;XNGtUzXu%3_LUvXE{MAdI2YmZlJ~bsrD;|;;LJ&)WfSvBCJ{l+?KFFY-hl#sa(LNL8`B2s6Z;!s%5b8Lc`_dUtMH7&Hn`a1edUj zp1*qex@%+X9aqV0*r=dxC%6V#1@wxGm=fZ!l-z59u)|U&r(R+L2T|ZkU?Tu=bn?7N z9r;=t;Gs5~cUONj+TIGTW)>NFqHf-7bwV1iD=&_=0EeSd6xvKiqyK@8N??Bj55fj5 pKLdghb<#C>Xq@;{zEAyURNlw&ic3;b-Pys(-NDX+<<1RPH#;XsQ2|K- zA$}HHcXwwuX+gnT|9n8e$<;>iZ0V~4xX3YQRYNxnhRhuO4<}Flxg7>$Dy@c9)bmVT z8uhvwKf8~=>T~j>qB4%ljh3TD$PTDMth|!@v9Uc}I)^VCR9{t+t1im`@ zwFnU|C;Xa%E+jA(ejOI|_W#d+ZjTlz>q3{{AnRFf=2mIk#gFQq)l$vFfoApL9loo4 zloT;^>b)J!zq5^6())tND>3JjD|s-s*U~1&M{t{#&aS>Rx%g5fJPd;&QX~&kI{@3U2|sPtkETK<~{F34*$x)lkAoCPy@Rm zgl<^GFhK8kf-Y<45IotBht7hW6v_C9e`wKX6CrobD|(EDW$XMi4ofNu*)RwpRs70G z_kML>XO)!8cmJ@Z<@B+z9YLXI6_Xf8mY;$-j?r~nEvWpS(Vz`E1rDZRkeos-Cohk%;b8w8OODZb~Fcm!=&23blIr5t^NBvVpPu>zfSzNb8e}c%4K97n52Q8pV zjpt8`1^$^pT!PHcKL%c!oYPE~p$iNQT;1F}Bhl~m`6YhCv*oZ|z6&1=)f03BZASE} zmaZ#g$ocg@RU+tqa`yQC{(hG1y|6s~5Eeq+%Jb}OWxV+JaM~X-@{z=-si`?TJ1cyC zX+l9u8}`}Mhh+2n$AbQ=3)M&GUtedAz&flVUe7o% zFd*qVLx`DZr7^=^zs_<57k8l6%dIoL0q%QYK&_uHSbZs9@9^mD$n<}!Pwoum5fEs5 zm%#TE{)B~(@3>MZX{$|!-~BhYf6!l+qZk%~pewVJP9t@3ami&B;p9B3rKL4LkWB#B z{`tM2I7|P``&Z*?eP`fsv61FjDdp`I<) zZbac(E}I$iJ)JWaf>!5KE<2B>NfV9SGFl$*#>G8n+y5c^iB2Ef`pNqJ-#2~Ndn908 zA4|HhomW!QDSF~EO&POv9b!Di`PbSFw9jD=AGSF)?A@Q5ve^0kn+@XI@Arn{*Vnh6 z>OJ{3YyL}FI%jSs`>M^|I-_HP5;kg%jh)@yEsMkDrBFd!E2mgaxiu z-L-rF%zS;W2O_DB#>_Xca?HES!NxUQRSpiH)qvwjRiIhG9`)Bsr}o~ob3eDo1C+7{ zGB0Jw5fT$)zxAeR6ierDyZzp<^ZmW>e5llt!045INV2F+mO-&;ZEsANx-jfY>#rZh z4Xa&(4cB+KmWCPvOwVTg+M%m=#5Rx9tr^Y;|NqixgJ>kC(FVYAXu~gq>I4o(Y`}bdJtvW3SPHfS8eipxVy$iMz z4kik^$B$`GoH&sQtD37Z3=ue^W+|Heexby1R5~~`lwDSqk(HH|kc=!eDJf|rmm=mE ztj{pv<*`OxI#^9U*#t%!8Ul>xWC)G=u9CRZSn4k883i333jM;Xfr1TxD66ZhcUGIp zes*$aWNM{JyC$h%xzNqwM%A%rFhIkLX`;m-O9nwhOCuo;>nGFF)w+-MfQ( zkC>R4vScDP1?AaL z6%E@|bz56YU&F$~o8bT8)1)&qGnsdmzT}d$)!bR)-MtdZ@sdHp@%sLsUjTsarlm1* zT}qDf&0N)GaTpf)kf(#2;k$NB?$4@{q@-kr2|YzP6v__u+;1l{zXti8 z9;CxEyjLu0Np~@MH+q?e@CYRpm4@-|DS7`>ya_~U=R8y(iJAH=ofWei#8wz}l;z~+ znzu#KU9GuuhF;9}?&_*@aB%SIBkGt0bf3Dce9>&n#i{B`$-bwcpgepqO8!gH2cw{- z*6C-!_$)W~Da82va5*27M+Nb+rIZ`EEj-*I9wY5gl3_QEYfOquhfX!D$i1JZz-owpWs@6a3%nJ(%zjcidHs?R``gy zxp}Qxcn7htc5LV4_nQHUs>PqDzr4Dsdg)TAe!<@76{Dh)!^6WR>$bt(_h{5i$!tz{ z>N$?rKL|NaGgVMrA7om5!PfRPmsV;R{aJeydVBW*V>RENdU+sf6T~tx*OQXlR8rgT zIs1-!-u>Wf<<%miv$kUNu&ZO+H5X(r5s&jNF{vNDTRtf}vDoV;1^;<(+ZXo+w%^ecReJzlt$s{BsP&%WPc0awF zLD>mMhU3Qf9|tplqFnZVZ@MOBuIx$i@%^a(?CI$lkKep@-g4>7tEam8=~Y}jyV@_} ziGnMf!d4ZS2imz_L}?@mu*%4siiwG_9V%gc+uSVdJfV;+=MgsFDWn~nqv^7j5x;y! zS>Aqp>Ym2Hl>+^}&kh#DB}18txRTP+>PD3xBxV=sKGR*4_57XQt)#0<`RroK{aasO zPcA&qXiGBl53l#zjrigq-=G@$A=UT958@I7zRB6S?la8T8}JQQ{H!0)1}6!c`P*LA zymYC3>1(CNxLJ`tDgv_tisQTGk&%&xBlMOF=IME5Q`6Hw;mT}WT=;#m+o#Y$S{|*D z|M`vmYYN4cQ@EUJD$6$v?ln1&>$-bA6&4j;KU@bH*YT`Uje%!Y$G?(`fudHsWgy{*3ns$l3tF;a|FR36t8xEt06ae56B~ zI6)Non}bII}c*`)1egH zCuNL?k3Z3!B0;93qk~|^&d+HV=~)rfYW=RY8&FeCa_%CFsfM;e4Ye6 zorN%4pV%YhGagocN{w;w-E!bGZdzcB4KBY&PakgcTFg<4SU#b|dGh>+B4Zk-x=sCs zajA28lb8FB_SxINeV%^&;D95geEQFLuCYwZGhN=2d+jsyuB1J zRgu?c-}UyYSXptXJfLsgeHi{OOg4i@t@s+Ip8>DMw8Qt$IZ8tueDzpOXP*b~Hw1Sk z6k{TO@9(bQV3_@Po^~gYCr5u(mbT@Tlg#enQSgsh{<)%x3XGb_*sFr3;{2NV@_6Vo z{V$GI3+4w!L`IfE^904MadgyV*)^>LG8`zPm1jZ+?ZTTA5pfStE${;jtb{U%A9EEJaUs+FhobWj*8jDEvZYo z&yzo7mVbD#zukZ?f2VdN^(ltK$!QLH)JdwaZrlI|wm4|pA4u)_PG;)sdtb`c#i4a? zwdKAxVKSI-f`TFtGH>>UXr{wIhY(klA&$2a*?xKOV`zv3!^FV9Qn%O2we0!%42gU% zV>Ce6D{In4%J%lWSy@>^cNVXnPWYq8%}WN!ApD-h>?3|?<4gAQPL|S$JniABa_UqI ztdak?E3w|#NJ=lZnTHQ23;{+tIi}~AGE^Xc&hn00Xg(IgDKIEj@%ENZO{<WwjaZ;64eL| z&5S^3M`1{zOhi?KD|RWRK$o|_w3LBO-d6C-W9(eikLw&Y5vB*|MK%kj~?BH-shc3tYP@Whp4-B zp6Q^daO#^C&x$ZQmEv&Cr#wKD$hP<42`e|+)17QLtgW-)={&#ZKQHmwcFfb`t=14> z0IVtkb=qZT)x27RwM-I$Kc+OiG{w9R>CmR*ywVNq!}S~DOLCx0s_kU+^7Opke4k{f z(uo=MHPv0h3}~Gl9QfNFFmQYDU{B_kE%mUB)ajR6T1r462{Dg#I0@A{%MYFs@N|2+ ztj{X+VqGQ=7smn){1!)RXae>&X)ZNU(Ji#-@m4c~;gS}$d zsLlu<_{)zkO&ETBE^ddw68710sP2ks1+-cMjb1HaAL2MH7qk+=qctAv+}szIb;GP$ z71Z>f!nxd8EbkNY`|S?>-KAw$O-DeU9ngY27Pg!b28t zXG-CHc+N`4QRm6GM^oke=wI1?jIH57EKreg<$ZXl{q>B44inOto`o;3_@LXgu&{tj zsfwpQ40AW}jhFj%1koB3@fjLbfUG=XPSVH*ey`a2V%n2S(Fm@yO2GyG$#DcOEOmH&8* zkg)MX{$*6UrzV>2xhApaL-9aOHX#W~$oZd-@w>4c$2>ed+?T#k1IkQ<2OM@L<22+< z(+UL?K?h~}?ZW%#lXG)i9%`|)qSnOXjw6Ic`jNa>UK~CkV0Y^K#B@QZRy&TqaZOUP zaz#&>qhC;J-i!}DqD6nEqJDM88tma!^kFjQULiG(a=<6&i}a`4nFHd{s-nBK@6W_x zV`oP#k?-E-XSmxp348`wRaLa?7apQdr5Kc3U&O=1a~@7{I0?t{6-24U+DzwT>D#=d z%yRr5Qdt8F?pG^pDe#GD8)wh5iBiChqi$GM)&zE3^I>3Y;TS?k(0N%l-o@$Y=}D+L zrGsc1J3BiEYOIyY?~Mgq0s;bu(KlBP|02}2gUj}nQHA3uJ8c z!|p;~-khtEgaRxF!rr=e>&s1Ad4CzX{T<6w=k91OyQUAl4LLrLr^Akij}O~RA)D#3 zG6wjE=(WQz8w3egD`Xm;*4Eb5^>rm{Yc6PCLk>~3Ztk^e*Q2JUrjI3@m~2jmck3PO z@45V(QifLIJbI@4qVZOj7nhbwz1FQqYQ3lco!rmelX(U7iC(_$QTR_32i{@(d%M#> zO9BRpLC*zE;|aH2%z;m!5HB>L7gLCzsUcxa7 z!ps7&%hlHo$s@BeAA*h^Uxl2I<@T)?Dk7G8Vq)U%XR`oCI3eOcnDxV3&{M7SNQ}31 z#IOrHjz~fhFj{uqpY4-BXo0LnK~Hc0Q{oT#aBOBK3+iRV!^7c198&OnM-bVD*u{>% zzV>h`Zf$6Bsx^4eTC@m+JU5R4h-*O{G}xem<+l&urZ95ErKm6aD7{P(IBZ{@BHLjPaozCcO#$uRTcPb1A}t)N~O84*=E)m%M=BE9Q~=&5+GdiALnFc!S+ zzt+DE0G+n+<1-mlhqJ#Va1_b=>-~HX?dP+#D7;V}u6nJswA2&Y4VS}eK5n|~nn!uE zoy*d{`)GE1GHpL`_FkQGUWe~bZBiYnClXE%XSVW1~j)uP*h3Z zCW5EBr`wsa8^%9+f!QxOFYh!YDt|5GyBi}%+>J}fl%?<4T1w|742iys{J5My(_o)< zVQ1^B(?E_I)yB#=GawxYorcDGBLea2S*<}+rsU|Aqrpy zzm-)URR#SjFn&>;u`!>pPO&jC-XX_oE?oL$H7vGw6qGA^jYR$?C~p*WbUX{?h%cb# z)4x97|FkSkfSc_nPl7tSTlxJR_6_g4k=cIsLiraV>O4J)n!qRBzEJ2U$cf9Ta}>Ut z@E$(N+b{}t#JzW>m)}`3nwgz72MRM56pI;D3;-ZlLOO)g7)|aYcX?yD(`N%82XHDU zov|ZuwA34;9^;C@$p#$kpXTR3;pYob73hmBvj+cu+rkDLx|kv_z(|v`v#mFrMDIX* zdCM^{r>}qR#MRle56~5678j$=7{6u#THdn#A+_Hh#Q1i0cG5~Xrp{YZ#r!!zboBT3 zN_2+*?_<(wn@5RmK0;EI@i-w!QJQWY@8f~u;(e+dc@kAJ#8g69M@Vm>tn_ESFB|F^ z62#`R;TAi3dl6U81zYvdg5oP)aq~`V9M{DXNF>!7PhFu?q>9wsJaxIOJ~~X*f+*w&Fciw5OZ7Jd1OQRc zJ}*ooa4qcj=8tJedncZrXA?1i4=E}t4!yp`0G-jSKqwPvV#N6YIR<~$Pu*-*P}{%* zh;|=VVgfDzwXIgi62Ps+=$qTLvfg5gi;LJ7kHWgIXls)rS{(3lhY68vh!R8<>mR_Y_6yPRy93(-D(C06Ew6S+{yz1y!t&=rHu zKWzly77Yv-+Kbb?yu90c|C4d`?a0c2NtlLp1MC#V)5XP>d=wbGm4<^hKy5Put=7O| z0LcxYCKJHjAz=Ugoi8U%>IleiS>uV>y1WygKQLaDeSuDlHenFU?JiEX0*~(>c--gv zai9RO*6(c@V?0*wnFQ!X4y`Bm&z&6k{8baD5gJRn=UZ9+O=dew-$=?nT*R)~4VQ5u z#7M%h^UFycu)|P=9o1Z4Ms!OHw!-c`J{7lCONvvy;hSh#*-Fgl$wj4@uqD4!AJm~m zIGRqmG7x_pmorASes}p?6q79dxYN$D-Q(Y<71YJ`)LYq$S1F0TPsj7_{FSWrcSG)n z?cbW~PJS%wBQ7E;IyuwQ=a)YUh+{n9K=vfW6Lfn>*+6QLsrN#z>(^JeB0gKZdyO4P zm#@qa4EkdD%~b;Ucn*3+@(KAFs%x&d2wtVhZY1n<|4XaZ|8q1nY@b_7imvC$S;QF+ zi)fw)Ja@IqnH3!$kZzDjH{Bi`8XetdX;yP6XGg6_$na!Jsr-^S>wU@%R6CB?K|z@y z4DCRwuZ4nW)YkUNQV|IAZTd8)Lois_3*~whu#6>?vpmx}X_YA2z=7-w*?@Z!=xzS1 zq+fIK?yn0Ef`+Wn+j@3JNL#v^!Go zXS}Ri7}RvVG2md=4C!i~%hlgdr^tV`1Ou!pu#koBzzu^g583=UkV3e3+nGL9Z*Kvg zjyR(f!Z-|Iy{NXHuh@+o0h2eu(CJx159qnOR5>fqZb3~=Z4Q0*4j`tV0J;#sUevF|4#qaCA;NNsJ0@y9q+P16n?I&!5R%A z`LAx;D*a2PQ#2qxR$gB9WnF$PP^uHp7~hAibTT$ zsKt4n<*?1pO{oZ+K4_JZaxceNCLp48Mb;gbpI>7$rh-EYGV!0i?QvN3HzTuGgB$jL z9|v50wc3>vv@ekAWTO})Na3VO7?Sjo+V6aD6CPggX57}Mqyt^DXubz{HXiD$9>G35 z;f15dPIVyw8vyk~Q_wvITQ~q&&eO*St=D5QJ4%oP;SsC{h13opF06v#RAmX=PRf-a z46A#@(>a8-l9Q2@MbEV6xDtwbLul=x8V`U(jtcX*-!>y$18CjJN%J%hOJjO`^(=1p zf7Ob3)Ay>_Pk@~Xg@uKyT&C}juYXZA-P=H#WF0C|ElXC_mpG z7wj-$k_D5+09Bbm%G~>QWQXvAEM^W$Q^&h^&=ki};NgUlGM*o=_xt(b@+EW73U_AW zE*;*P zFiSa1Nk&G7j*foaVp>K<^h*6MDar?s&yGPyfSO)ab@jK8Sd}K`=TCctZv;b`jRG5u z(x6=Ye$No;y^cgsSIprds{HrfjO2##va{o6_-)aN(UX9_br0B#NswfBAPxtBY(AY3 z#h&=^;AnUh`G_gI9rL?DMzPqai`cn*fC}2Y3260Z1(Z(&?Em6MtnGag28*VkqlCwf zHNm2k+P&whxcOOYc}*1yyP^U<9unXgl{0d|39x$ed+$w}aEGXZ0=_pMD-WTDc9^`Q zqQb)g!M7Qy?>6aP_~-5{B5h~z{d+hHID&$L)fybfK;Naa(>F8AQznhK&plH9`*#HR zZVc}OWJHl*@bX$rO}sjE$wReXqR4JhyD_Mtdhuc_u+`2BgPfYlB1g~O{1jh15;I zSsn?8jCCD4f3Sl*s=Q6E@rC>aeHq=_`nvG-MhxNzfn-Un5sSrve1}~t^y6~%5C}42)dN~n9Y?|J z$ads8;aWF#J0cFYNCf$SJYYF<=HjyMJ|}>nmAY-F+S=L@Xm*JirB5JI3pfWlu3NP5 zxP%CN0v>p(oX}8e<4fc2;9JSFG95HqSLxv}_3+oefaI@fkH_acUe0V%#(4QGz4{En zWGf!(1_6vHGvo%i(Umw<;~{9>m;PX5!yPg8>FMbZwIb885;24-4^M>yGcW}n17Pp* zF&zK4PTVcau>F^HLj96kz}B!0DxajMBpYjPhC7TfIMoJLRER;(bL};~y1IG^H1XXT z^32DM9kU&Ma~5f9(6=}D_G-O;)A8pp9Kep_Ih$ax3dq)crXyyy{*r$TX};92)1TZu-KaCVnwM64P#Jd<#1&Mq!7Z+zKAE`y^$5fEBzT-*Qv1fl>&ie^~;5{p(M z{%cj_ARo2y71stqVVs%;UL{L*%4!cCE9dDp5+n%7$;l19x|wv^%=Yr-%L6a2@NFy( zQ-QcWL*vB8kN~Ij%_Z664cpDmHAYIdZe4~8&i`s9fBM~g|Nea`2nD_ed)rlR-$;Y* z-4h1m!p`rq2XwOZuwfMN6T}y#%KDrnp%){+HG+g22t!0QA>wkNjgzhGQM&Qnl057w z)lPh3Z-spC`CX9X=1GqHdGf|m-)x-QUg{3uDa1LUQ}IH-C<2Fj8^^MHV(ehGEl zhjo;F3J;zIIPWU(7x1;p%m??#Df}4+C#N|`Sg|tq z!n)g^c@~{Er^JBcsd3J8$uGbIHWCzI0%+Xdf_xVZU>Idc$vca*(8Kfzsi{mhFlDJD z8t~5IP#_$J4==804BE)3~U9Mp0XZFosmAqm{O&5 z;K2p9&((l~?Et7^p4+1yh)|K)+jyTP7wy0ROakxZV6KKOAXn5hL2LSCCOL=&kzrxc z(TFtFey+tBCzBMW$!#^O)3TRvIbSv|I$IC(ajkf2acUAJB)IDku=+fO6b|0Cc_t{w zL?X1rtJ~WbjEv}eQ>E@f`0HN;6IR%BO;%FrXN|i7K0X z7tnAbC--5!3<}u0saS~tOJI&Op$7yO5%FU>x$4xz_Q)^>4!1C1sHT9jTco~VHR(vR zFu_oNT-TpnA0x>yrc`#5J{;2vf&2+JGzN5ujt*7BW)95I*RPhK`9aZ>2I>6F%`-rn zRHXWjJ9LAMoZtrHQLa4fwTOvobL`8CW^)&j5`JV#qEvA~2DbV`@@euK;TU83&0mLbtw%Rd=ywaYJi)zwM*ipbfN{o-CmpAlq%+ zZ8+FxK-B@PVL^~n-kJ2WL!u@{1^@#yzmUTQ6>b&hV2&wv>*>Z}XNkRm9+E{&>;xDQ zu9jOrP##eg1)3A_>EKK{gh!{?UgUtaNo`kKzf1B#Y%HZ(8~2;`KMlr|$=dGjVn_f9 z3nTRO^6E6v3OSvijvg8v1;}|#pUSX_tu=SfR=k|X&~9WsEYQPTSsxU38B#!S_2*P8 zL;?9G9d;WM)E@g^RzYRJWr&Wg?#hn`>B$0^LF6PmdB%tXC{jH|5T}lxP_iGuDbiYY)>!7Xad$!Phjh=>RhntdUyp!$JNLLUrg zCfn})+IU7D8xZevCiT8_XN)Qu!JcAIEzyVIHrOay&#lzn0~QK24vGYq-K|@}_wQTG zzDt<@S}6!EC60td_%6~^`;|MH*QQ8 zRgS%dwkrx;0Ivs`X~1keEC#G%_60IXzms5I%rh*1Ho_T>zJyl9iV(4DU>?)}KAo@; zqLKX6DO8)yL2{&(@my7^{0x?A7VuFM=$1XzQ{E=N$B70n9p|?bl%^?KuST)yoW_(E!f|HEQDc4a>00 zu2_%txr-=Y0DssHGEt`f`ZHp-%NiFiDyymzPEAdbgEIjffwDiZy!^lIB$z>=7lHPW z55X^}tZ&=f2`)d=1Pt@Y&{Rod4pd5qSgq&xGBTJ!TmyCX`m0a_xF%Yd;E<5X^*;He znp12kWgyW-osy!2#NGmjs6YQQceTcg3b-PA7<8VH{~BDKZAUT7qfLpaIn}wa>5cLYji4#^ z{P`o-OiX44!aMAj#v7O+1yzCZHc`MN0`jKuax50;ivV+Q79xBE5|A*+4iMT|hti#j z2(Vfyx}d*6oy5U_=Vx+ag2hewnF}~`E9^fKnY?jtg5=*4mx5*E6A(~A%4~NsE{NkO zXX*RVE<*`GtP7&mpu(lZBsV!K zGV=H{&1A%D^PASvUU+z_sk~1v5;C1Rkj4{ic}o+q62rk@-$f3D)z#HTz}mN7hiE~S z0~U}VV)DSV1;4vq?%{sKiHoIXzDW8O^5nj%w1%`N8BldaOV33tCx>*K)TX*f{p+%AP+2- z!Q@w-LPM~xt^%)ny)%{*DV&hYJ1kJXefsn%>Kyt3xN~rEWr0uGHR(no@Yl$M4;Tck zO24fb^t6GMl@e&zfy00{GzN*}Ux2pm&r&|Vv$Jy@zEEcL54hs{i_PR0Au>_B(w`YP z0`nWMfPAc7?>(ogrPYSg74R``$0}nX&V@XduQ`m>(k(A9gI?VVq=t633JDndC_pa0 za-5X34c5+iYtiujGlH49xh&Xp+rgY;Ff(xTGQqJh-gno9t`B4>@4yhi0K`h6SpyRw zYj}hK0n^$ruk|@|7*B9^cjsTaVF(}+F3i5#&R1px(+I85u9tw@=YFSa)tfhnv<9Pf z!$mPq?iYoyD^CH>=8D>Zifj4!#37Lm*4mtB&n$LUC$E-S9fJ;22#(gZT2GzjwfSQ% z_hSnO0ZbrHCdt(M7<|F3?l!w-ia1HRb{kX5d}g0$hmXpka`Aw zYS$#ISB_(~;hY+YFi~|xN=gc8G*C<&;+97F=|Bf(R3u;ha@;v+%CO;JC@oxY zmj>JSQE2&_pgvb;ggY4d`^zCf4ux$3X|iw(CYF~4JPgI3mXwee=oh`M^;&-fR0|4t z2+5N^WN(TlVtY@p1SCpA_XyffIJB)`qkVe$xz_)`qcvrW6__U=h*cV4<_F|vC_)({oCB7~LW1fmpd%gFgh8qu z0RaKmBG8vjHDYBn39rLmt#8!;hZ;vPK8W2(5766 z+KBQ$*b+EA?8KqH?biAaX7J^zs0PeHriY_2{T&Z5HKAj1pvRIuG9RHP16Z4h>Tl_B z1r7zS#hZfwf&Q^lQO4*1@qxUR-RZInsK9~;5MpLVAQJ1kLJ$mSdZfw)7sRQ@A~%Q_ z22y~@N`3&MXs|Np)S*^!bmM;L!TZ|ntwg3fLz}ZckADvc!8}3A%c~5J5)wjy{LKRS z4Z)z5GhC4gsi{ayLqP}hY9pMy?gEt}J-EJ|paythAZbwp#)!#Dx}mJ!?{EyhE#%)a z^M0fv86kf6;%A~J#;O+9*U(9@u&`jjUC;{f7gjS*7itpB`+#pC0+@8f)7yT23Beb0 z46P#gkx;GJ-hW7+P6CLvZk`FF*)PQ>Ua{@qle?f!JF8 zWbC9^^m4~xDy}f|*FX9@<+PHp57?>;&=U?Pp8n$Lw)=}MFHNQ5=lt@e--7i!Y+&wi z0X{{qz}i^;cHHbRxGxa!1{nq!4gduu)NsTmvk;=u6$H~vYVJIR0-amO&&bHg{Ob$1 ziQ?t|P9lo0`h}-tsfxo48Cc#pzCV7S6$gY4%lF5xdwY9Hp|!&TV+hBR6S^C++u*K1 z&GI^zvj$RwaFW~ z!;kU4cb6><2Yz7T;!sA*eBThT(J%zid4tYN{p|yEc)`ly64PoPXYB^@kX8yI2pYf>G zucerO%m1+woorI;YDp9EQOc zxLMb1jdGL7dC%wSvE=wE1rz)ZlY3p%)zzhxB7RF7{8xxZ-rCwa@MeBJ$a1+FSc5}@ zAUq>LpH?tmGSx6YoHvIcK=W9LC4BMHa&rD7k#<<+qyKSY&IJd?S`FMVdMA5|KI}mV8&62oQNyZcXC7G0*CuX2nUVD>`7~RckeE z{DX-8IZ4M1a2}ZnI}=gj&oR&%^hT+n9MTN7PK2l`yi57~dtAM&_(*URj2v;;qMw=f zOzNfF%vGFv2X36;V^k%+zg%HorVjR34zvsO&s2A@@loF9`cYaGm>#d5-}r{zsNkC7 z^wU!!)j*M`%AOIxsP=Rw?eM(52?fB@U*YsKrj83EtqvH^MVfIRr|4Zi0+3Ogx%kF2 zwWiKN?4bcsz`jW6L8ZQ#BV1t1_Zf#dW!3I&p~K15t_Ls^@$zcR#olOFp=Cm?47mr$ zT~}2##L-tlt+8c-y>B3)aD%{)vtjv*5iCx+X>mKOJ8F{k3iL_9tkVKochsAo!Fe*z zt|^v_UnAp)D+lf7+hgGG6x8N&2M?B}rhl)k@UMR z;W*x{sIRYI-2fv)G0Dl{g@ybx-wu4dYGH6GnmCng-}TOQ!qDSAEg=fqvUrK|r= zf@)?Cpb6=zz}+A@3R+G+n-|n#mu1_*3DL;`eHwDYwzRacfcG(?k*=hG$K<{FgA}TC zyH9uut=^m`Po7LzL0Br88|p_xY~+Q8+)JO_Vs8H? zF#$oSde7ZARaG7I3UP;%&c+)qoA@};#K*)Y+awf;<++kFN(aMqE*m#D0gQ(bl9Ilz zVy^9Q^{SRq!cl#*ShVv^>Jv;hU|9)|^k&FMgLwdP%J4+zh=_;~Lw5Hr2DNm6G4qTo z1@6{N&Paqiz8he`BVJ@#N|ymG>_f2`Gc?!5{ku@=S{&-G{o%ph-*Rjs$s;4zp!0g}eo_Rc^&oM8U9lOM1PXHUyHIBn8SHCs8r*~7bYO1T z?G>s$r~<2d+`+r|6nfI!z~3$)Oh7JSmcsR3`f?U}W2ABd1{R`S9*@h`%?AK$I!UK( zU|^7^_agL@RfInMOTd2L1d;JPA%J_6ruG;LuOzLudCoF2C}eFDwVf$=-E}pxZ}m9IiZwzI1o$x zCT$NNJWz(&Z|Ly{>U=!VY$o`bFM#VQeTVKp1A$MzZLQxp{)7nZ$biuKCEOEf)SVjX zm{tTH)xL!Ju(CJ$^q;WZeBy3^2pool9KOCLVfJ0c0UBQWmHid9AKWkU9wl7hG*&GC zgd0X2@1B8JW#A9^(n4y%MF%}5QfFb14xyMnx!pzfBo#iGlXkT;Q?djv`$L`mi^_Rn zOzyfqxO<6hYWu0hX8DlE!-rCXuqVF8ZEPxa{@YNZ>H%QLRY(~!lycJQMX*3waS>a}&>LcAm zyXZ-U52ZxwO<`H-W77Au^D_vqs2}~HepHTZW3oFZ_`l)ZR!cdLzPtuj5H->Pa+i1RTl(h)#2mm#O83RIKc;DHfc9 zyNZAE#E6~+c>G9MF_cl};gWV?8*6JKUM3cOL61Da9b`*Uud&9!p}$!em@-V)(NT5q z8P1}{!Jq3?-U;eg@>hB07T>(0y198Bu-uN%33f?ITBIQ(qy*&bK8u2NG@mVXyMi4q zQeGJtVD2|AE)HzvPyj*)F~3IK`jUI{-wpa19Zp}^WF)3g{W&D%9t@|=y|y-)YgPZE zp8Yh1YU|=gz~b)gw{Hi0R&xBlV?egmf96e42MMQOWa8KL9d{3p%7s;)t;O!5Q4Q^4 zA!=kpgcb$Mkfe$pnigN3F9!zTz=I732u5vz?}NuqSiZNhyz+3Tt znH8mGrG8D(M+UwrCOzHM`_&}qtdHX2?!o6LL331rg9>mUkn1Av9THX@FPJ>(H_5Wz zznW@0u26kTG1(7=-x|`eBaC_uiDbtEA^YZf-I`7m1|KnGD<@5MeUL8y*aGZRZIodaeo16RR9{56l+B1#Cg37;)C<08JgaLT&+0z^=57wE|=Du8lRQ&XYA zG=r-EopJia;Hc^O4VKq~kF7CC%Mn^`Ne1_&tcPc6?1uOC0q_|^;#dveca>K3X`uuXBoeVstY*q zN9++`UcOO+;UZ%RqzQibMj0MhB*uRMURqE+x!yF9d}RvrT%!I_Et6@fnw6gen|8!- zsz*gbrH-W)_ynQF$z@%G#|MH23v&qSN;%QdWJ#r+Y>#&f<*)SeERk%SZK6)mVV9mV zym%2NUa`+CH*b$oh!2(ptW)HB{xrSD$=9Eh5PE^acA@1H&Viua$Pn#$!KqzL3vu&Z2xu zRlOO~%L0`B&-!#PC}6OsPIh51dKp?*Ckqp)XaWV<0Kq;`TbbwpFAkxX+q^bmTue_? z%+;)YjZjG22+xM#tk_Gf*z~neRZ_y5l!mMYdxctu{#u8D_KysBAaS=nGYe=RR`S?B z&jdgk$P3WHnviP%5_Tr^oX)OOOu}U*aPTm9p-Lgs{+xYY7OIP1LI)d?L+9a*41Ws6 zwO`7=@LOaJbMziG%A0Lwown064(4`C4z8Jk#eDDkv_7 z*T%&BDtV`noERs#z@v;I$H0prH2$1m>zbXP4}%;gqHV+i``S(Zt9}WMNBP8eL>S)4 z!uX_r02$b2g{X z4A}-aRT&#yG+t`#_EPl5)SX69}Hk@>W#CLIu~>@R!BECA=WxOj)PALY!1vlmr3O zN*D07-tw65_i7>vE0_mu}?86M-%Bn=7f#(W>fdRsfgyxaZi&DGWv7 zLm0S5XV2&;BM3dfCV`_X_AUz{lKGCPVG|o);G!?-jQlKUBmr+8dD9L*Xq>CXx>{sb z_=9-~@9IyUl``}UOvLe@G{~3z8E?P~JsROAafkVL{WX(1MHUL03Yd77;io4ce@ZA^e1c2d1~7fVd07 zYh}=Da5#i}wT&b|3#R~cDVEaB!{Y+j7LmI=_fZ(IZiljNOwP#YD4=X4gL?3Au)(AA zM#3wFI9h+u6v5~wMFI?vVPjzt{{5}7VI9BWdt-9!KNTJeIp3sUcS90x4(Y@(IRKsD z$DO;iMa2L7y``Y~4{-MV^$D;B6p{V+SD6)Zwcasd@6ZdCI)BPJ{b;3AKYV>r2cD#o zo!>uq`oDh$kJAn|7#&?*m=ofl{O7(sR$iw98c*h9EnU?HUGwnvr#B-%g~C|LU#s>o zaL^m>^l(|=MHqH||J?hG{f9i9T-{CuJLSVAhpWb>>gERnNCIXF=9sWRME&&;Y9%ze zwBu%b+TdbnQb6+bcIkkkJ4D~O&DSm49Qjf343kcn6N`;t{~ zQUwLcl$Djiy3aO2{P*f}xvacCwUt$Yg6OX+uKrg3@fKF;aH}+f0ter~7ybR!|8srR zal(G!<|a)1bF1f{YB%=uJP36y!~=6#9zQ&!2pwD=y}jk|^6-8UBeH*G+O_{I8wR#KxxenK>rmw2+F_)l9gmxYz4<@apZz;F z|IhV-34=F4*<@B6fjiYpG+I6q)^X?b38Jdc`O(J>k4om&;rP6wGCckADXV7kI;AE=2NC zED4OB)+u6`2w9HYtr$6iWxCi51pw@e4-NhNCKtYQTpG}0JzNtPGB}gyZDYt(K4RwK zqxGF6nv`XGjA`3|^v#)}P@oe#Z{~2fA8s9d6~~*_(oQJili{WX5`-|(4P;~3;#Xz# z`Z3qr9QcP(jXw9{;?FPKq;X_Vpx~!SUAFrK;YkScHX8+W57)ijWAiMvBDKzY3#{ym zO91JeRR$kW6+?q9vev~`Hx|%f3#Bq+TvWRf*dtK#2uGY7^yJJwJI~5sJmjzTocnu~ z)v5pNJx2r#L22{k9-{$U4|)+3&e%-8+PGFSZyq}v*T%4P2n)(MZmzUOZ zPXp_RqFzH`y7;V-D+3RWop!{HRR88PNOj z3Ukx)9enhb79eCZq08Fd^Iz$M_t96@$YOK7kw%E#9K9BC>zu=7+dhOU9E++fSv*W z-edql3=HNmzsXo1Te=doQk!1W6^VSxDir=ne0-eOZ(c>Tw_otWX?03|j`8uak@ z%Z(4%36DS$W|DgEh2EhB24#4z(b2sa?jZ))YuFnN-SSu6B2+O8s0`(aLuY)$ILmgr zXX)F`kGm_-N2*_XANLNVVP47 z-*JG=5}gZnHvH$E8D$QTn5$sis=Dj@wts{7Ca?ROgVC#&PEKZyKXS?fUS57q3Ijjt zX76v97S3>QZeQF;a`0t~MWs&d?GV%b41(WRH@kC&z|9YB$Kfhw96x?s!wlYn1OC3W zn#sZU$8BoIk8;Qqy~H?+*Ak>M4qXrK_=2j4m1kFk7i=(MJ3I_!Ilqw#oMmS5A~`4b z9WTRMAXYv!O!KgC8+em#glO8j5iQr~Tmao^4)4I4iFQb_S&2bJDz`4MUSpagK<3l+Zi&-9P zf2phP_HNf@yOb*C1_}%|i~_u{g5zQjjsluC!u_g1VaNyRj_ru^_G&yZWdk-mKxcq? zbsbOsuUN{`1(NFg8P`lbczxr?&jufa!#iqWX()7f{*8b0(mURvY%}18uqx0CI&Du* z^rsrwQVwIrpwwb#r{L)8>HNQP&NV2iGK}Mbw-p6kL>p3>IJ2N3CW|I&IT;?1W$;3R zMkXrk;3djiUeFRUpk+XCSIig^sj*3#p?o4r4p;Y_y`7M3^@HHQb@G$z%5aWk#hW~&io7Z5&F8OB_V%XcNR>e^z5 zWoBlgx+D4NKd4m-k+;+^F|(J^K1ax6FuGbmnT|_IDFX>2;Q<1e%ywLxg79!>3B%a@(grbo^?+DSC2U?B*5Hw2j^O>^j!CI!eP6)vyb zgRLL;vS+psMzAZ9xfeVuiB}W6YKaYbtBG|;s8VE>TCQ!*k|MODCqaQN){nFWT%vJc z_b6-&?#%=rLDwAt^hokZlv|*(87-neX*2!8S%d_sB#T^ib>MY0hd~TwnMc}@9390Y zp^ZBXzE^r0?Uw}=3APO^0eVIWz`tUxY+9OD2b#hMd@9O=A0v5SCjjJ~A*azQL?h=S zDb|elCs~-mn$^8o{PyuCtCs>GFli1&`+-3QYIt`reqm)pIZ)_?q z)I*Z0S1b`WA~Ft--D{8`;kqpD1yPg6vLpV|E^h6IzoOBR0hhIQ)21H#-V$!NwUhEo zSV;V5+2C`iW7c8hfP7*A-PAWLD+{fGOTZD16xm&?)kv@k60_gv75<$5<;gJ;HX7@W z%?z&r6(%$rUi%B zF&q&3q$vTQw3g&iRMcu_R6=KEn1(our5m6uPpn4jZ3C14Ygc<|w;4YdMl-6za?x(-gK4}vZ{lWeW#OaAX;@XInVB{7M zkn4Jmm~*5WlQ)vkK>&g9EsGN6kU=s=l+tUJfvY*x+mJlCf~x{+)K{7DTpp0w&J`6E zit*A0Mr=qLm_SVG(b=V-fw&1Q3Ke0<51>z?aDa8Oad-n6qX@M4)g!;58}SQoMj zi(Zf5bckREKe$hVLDJ!5(@fK=b5Y1GO!8~?QAUmiHP#2Bn=xXZ-@NKmzJ#?~PYfQ@ zJb#{7hv%mbxEtBZM&(VeVx9AC%_+L4dY>0L8_aKbU@VP`EcefTXuNQO*pCnzZj;%$ zdkA!*_^AW!-fD;x>}^*-{nh(l>cfq_W36e*7u&*$#vemnIHq{0c}qad{gnlij7Dhn zMq_dzhlYfsrVhv}W}o2SV_MY`*}JU9#>L&kM~|}nVBQ`*AZYY~F>Ht#BJgWW&VdMW zy~m}Sjg0}6@GD1-vRArY9z6SU3*eADTGzOzSn4m?cM{h#{0|^!6#8Y9qmr$+seemK zoR+4RyXFE!r|uyj2w>n`_fi;O)zb+eVUE{vB8R4#-^~4laF>N=3cso)~J?5TV_Ne&M=4(Aqixh`kdKLeQNV1v&HoB&`dw=^G-dWLCfoJvp z8(dB5=V*e7e`r}*tOcrv+VaDrX2onNE>Bw(c)jDqd|$*aJY_yriHKRac}wZQwDDAe zwk$pWipA7L*k2dsAQ~;FwRZi5#NYN5#Z_dZk_A2-bskNQyjnrY6Ru8PT*Y$ho+GVG zVM5c74a6UsijN9DZP%cvUfT`h)~}j8`Qm$L7PZH6XU^+>%05o}Gw7zP-XoN{C%QR$ sjN~Wy`+w<;%j95s{8z2@w%117eeS}pZ{7?>TE2rNdV;1`%k*+SVXqcTd_WK>4Ts7TRJHkpYK2_Z6)tn3{n8D%Ci zGk?#c>wEw1`;Xt_{`>ypz8=@-Q@QeXp2zt*Ua#jmPG1c*`K_B7H&anjZB2e@9$SE2QD%Jm_?tjdOk2W^V`h1 zd85K?jd-!tBA?+C#yuMC^)BZ_+qr9YnJ489MA~=fssvCrN$*%o{;i~>#Yj;7_lKTh z)wMyl4{jv?%AGvH@$WYWEl&RbU;O{nf()2%Ke1zNkNMml#!~6)hHkf?-Fpxkc=qgF z{&kZL&2QG0ZM9z-?b&qu;Npu)ieiAr%t1V958B+^lD7t)_eZMhE2$V_AD_@)Ph+?e zewMF1#YKcML})(GYxi2|IsYB25)N)$*+o(O@MB(|E^^|ezOs)@_hXdscWczqiX(F@?b@E) zfth1re_t4y41dM{U#SoizAsPNczgWDPV&==B|=B+8rwd7&CJdTd7#=}#)U7+=#dKi zVE4<|g8CJY)QfjDQH*yqd!Lz8#mE?EI-B6bi?{F8*nE3jUu(XcxZF%&`uLsq<81mm|9_7FANT#&cV)G{E-hN$ygSeOO#~az# zNzbMIXl<3&FXd3OVHh0oEjPkXN&fE|v$49dmb2?OvD*Z(9q~DgtJkObclFuPi7bNK z*nM}x(Tx_1-n)2(;4)F4dfSXt$jE39??tNV z;nr%uOPg^w=DzIrbpVZOnM#w0kTdkS;_Ux!w(Ze=v3tJ0C7qp&H%Hpj zC;$9V<~n-x?;e_mW#aTHLe`2WBlo#W>^EB7-JGJWHt%2?+B=PFdR%4l`Sa)JH-5i; zE4*#L=*QqAXOpyEY+JKo8^!Khf$sbw*&@6Dt5t{5&wN;{vbl-ATj^O3&YU@uYFHe- zPvqJ-uFmOKXPNh=UD^XDPo8{zv1BzJw?Wvj6cu)aDG$2P67YzOyU;@>Y@gR zhyT<|t!U(3Gp&t|Bx@uWw3PDR6m65Ag9+sP#Y`YO{jz3hM}!xU`})I;b`iO%fH^63`} z_lR7hWMpJm`PWuf-n-gY&Y~-7nD4+*Qc_}ND2ttRmJ&j$(nj2KIWqfld!|_}>)~|j>gsen7aqjNAO8F2M|De> zAr`bPP2cz7L(}i?Z?&Z9AJ=N%iN_lLk(zXXb#``kXHw6Vr0Bd1SR1(c&h1@nY7Ncesm-j|iJD4uW`X*(+EHuu;{wF;$n(b`(2I^<|8 zle~k2pp%mm?u4_fFg(0xWTg6M?bA)v)X&eRUwC8DDD&@;hEmK(ORD$t^ZW4aTXceQ zDC-v1RXMg@pQKh61GzTdSe&~WA#M2dn9bWOJu*J!0bhcQaznNgWv@&z%^jp`pfN zPfr5_gQT6~8JfK4CsJH#MZ?Q<0dEQ1&&?-evOVR{b37s`0-=$@tutXVQ%D&FHWX zdP?uw|LIpe-Hi4cqx7%yyif@Eh#i~p`gN>TYYGR`E(QkQ(9pAfEY7r>Pvw_TPTbwL zU)XcmEwN(g`}dnUImeVkxmm<=Qs}wPJ)Y>R=UZEe}wP*bv8=udZN|~wa*;sp zvr@E^KlGN}4;L_hlp?$kEpa1rsR(21UoVroRO+)8g&SEHCHBH461y=cCns5Qtfxo1 zHbSU1-`s2c*0()?ZjQ~3P57KQ9+^Hp74QTxT5USIp6l-;@Y(ca^a6a!gL<1@AWMXrzSLw8e) z5>1wPq@Qcs)7K|k?6K4$DZd|$>j8s+kF?kN#-!8nT!l_@>(;N&#N00^EFAipCxA~p zsjOUc92-hcOk3F9qbUT5-mTHu*RoQz7O@DnujfX9z-;y#lsIX24p{ObpXpRjJ{GEFv- zjyX7(^MnzqwXF8(@r=w& zqu<{OpCw|5aQp|yyc-%c%KZ=2e+oX*%005?wQZMZHvjwh`1mRe{lxONBKI5E4WY^Q ztwPqHc`;7QQ+2aEk^>|$sEo1yg~i0Qk~9vD{`wV;hMG7Zx#jlwf~K8>B0A>YQ}Xi0 zc6RmHZyXx2H#-Nq-d*=cyLrN<9_`@oK0lS*xvsYOZ0fm;12iY5M>_&nuiO0n`}g-v z3CgV({;cdY;b-{y^Jm!8r<2P|H;&nUtqkQc9Bh8EUG?d)+LoGh3_^dyf%IVf8tfm( zx6fg=jE&u|(pkjC(UDz?ce{kDvc}i(6|>EKeSI0(*{0Z&c+`Wvy&ockF1Luz;4zS{ zE!(~la_iQrLx&Fa*T+aTw`<%D4`*1vemxM-_rbxiA>G!|pmWXq$Bu0YMv?Sm#9|8IO@IGF!qTU*G^!*Uw&au2Dy22dgeE|WfSvUgJ)7e8kh z>lQd)O*CJ6WsoPMp|L~a#!OAiUxpt)ev~c#oz%^?+U?`xBh?=r@%F|nHy|prdbBw8 ze$k-KyEzv}4{f?VzUCj;<2s~B!`-~Lqv7uyosq4QjbHzw`ngK@5 z&CN9=DARZ5+VNQFZT_%AHKEVFQ6}WGL+R6X=HjcGs9B5MzskN_txoemz%4z?yuK;N zMnBt25gmPkN$ULh^E5Ox9u^-|8lRogEp!zMWK%D%t{%DDb#_;Ic{$lyLYLci?A=>^ zZ|C828Aj{yD5P#!U{w#3ULVVcwXKm_V%8d{16dOLR$_I4N0Da3wtcaHZ&opr00UgQ zx6^d9Sg|i!=R_GUSy)ugPmk#4STg`z&c)5Pc|Urz4aG-*iNj#SEevjcr_pmvQXY$0 zcUd>e9Q#M(813_x>1@(!YN>$fKRa~k|LWU*KvE^wwu}GGgL!mvlx}c%4@)DSTTD|c zEBdyuh)9NU#WsWU=RN0^gmlvMghIG(xLYoslo~oykyi@+%GgYPpO>z)(+-Gb8KTAbLgPu!e!C6cIX%SCTn^&1;5009BlwQYoY)hqMn^}(j@vPLczFCCnrlg zI{v9KuynUA=`M zEt}4h4h~cGOc4h+GW>(0f;0>~@^P0`;vZAoB-ec(8dAj8*nEe%gAX9*^t+$^xwmiM z26<|-zS(Wj_-q|+tU7bV^vufgQu6tC#{yYZl_o}}4Fivy<@TXwxSf?HfFd)&H2`V^ z=h}5IkH&4f9lO4f0}S|KKjE=Ha?%NO{BQcN8Wg$)$HpEka{GH*Gg(`LJG43v=qyUq zu@|LA3j}m~-4;zWz1EchV8yb8@e2O~TG*I1+sDL2?0-^@9ixMg;QFov>?=UZ(?iam zsTTdUvAKC6xvy$7h=9-5y-lw#$*x|#`g5k~7PRDeH1Ic<+tmPNy$yr@6^cUmZI=dz zMjZ~t{xfoom<~!IT;Zb=Xv;>IE=dP->TKM$jg_7K9?NrUd3E%E6 z{t4(mI5J{vYpaGm>Fe)rj@3@Zv)C0H3>*Y#% z@?>Xze!jDd%hll)4h#|@=O*0|d=`07KdM79UgBaTBCRJ!I|OoUzW4xlj(;!F4JhQ< zc>CwS0xajs>F)dV^1Vv%wx+g##?;6|j?80!dds#D)`p@5Qes4T^a1X_vH21L2&I8% zOKm6>f0RC0iRIFzODVCFU#JAx*%freCP2X6*mlj2*f+G5S5~s?Qt7?EDE()k-ajYD z$)_TU0c1~DSeO^6320_gcIEp0DA|6E5YjrWQ!fql}(*9*Lc z`bI;N?M>fb7?Bg?x(xK(kG-%@!Zj#>ML9(@je75~2WXsse%9{2_T$qjT(xCuicY?A z8|WsP{SZG)tgI~=KxXZK)*M3bsr+#bcM)JjHNWK1aMIP)m1BLZ<*yAo@(?nBTR(sK zLdc+M%ugQmWbJDcy{8^ANhnS9mJ!Ua@Ps+M=o>oGw)}gMT0oP?n0em zw+%b8MV@}71wGnlqE-{7_}A{WY*ufaYMj){NksOqxZA3g;XO1rC9@a z?%rL7!pd{|%g@Kh7sO*24c$N^K`Gco`ZKzf^Pm1r_@!=YQmGcT)!5dS2r?8dDutM<3EFzSKCs;BH1(V~ss7A%dp5tlYMi~s z{{Jy^=jP?)58cY4rW7p;q#HfZnY<>*_0&;k&Dx&p|EPYZH$~Apzo&Mwndh;h5=D2o z)n=wzZjH0Ev*zfn&;g#hFU(w>{HaQ~1%`aUTJ?0p;-A<(1u>jJ}$);$A^XOnHlS<2B5e2`j*dgW$Ad{wFL2ZkRSf{_|6o}wV_Bxx7DW|TulE5 z)O4+Ci?Sj;c9q`0x6h)=grjci4OdLeXZaT$@60Zww1*2?(tsn=9@W#H&I2ON1kboO zP*>X!Cz}lT8enf^Y@BzsZ#|e5c>L<^+qXkMxRso2nNu+54`QuVB_ri06L)cW@o&nB zg@uEH2^Tu?4@ce2<-w&`UFiS{w1iT0m4^2AiVq)d18K90u)Z{JTi4?mOxjf?zfuB? zva&K7xp%@ZXDi18b??5jLogg18Pe!v-(IMqtWm>Dzp}i*gPD&Ze5k|mTd}AA{rg+& z2kKNOByZiiW!;fUlnv4AV=ADZn$!+H+x9B~F^!LppOBZo%c>gD09=8s7{gM39Z$gF z_qV8PKRkZDH$uO`ChYnC{qb1FwLEb}OIF7jFE9~-)`QxCxPFd<2X6xZPWF^;z$}x) zF3lU+C1V&`^J{6{=h>CnWe9`>YG*d!7I_5)pQAGZqTdG-NpMZ2D4siajv(V}_{jbY zOniPY83(bi?6jNJqQ$E~Cefo-uPjdb5ARb90Bt{O>dZ!=T!Eg!ZSeMlg$4U5KiW7{ z7O9u~b2F0z^?BERY(94ESh(nlyr}CGI}`*IpIG&MuZoW!pEG(VzBxd9!q8Bv^`KzZ zv~=r}$B*CR$AXcIr{52sj%}buDVhR(sSGYs}p8PNv6Gf_d;Db z_s;34&6gZ(LQc!*$^NQcBLO_`D4^w&?yG{){)F%VT-IyIK`|?FUJJ$yKEi_N5(%E!_JbsWTe0~5Z{WTQOaC^Es zZqx7RCVc(V<3qB0_)Ru~E|T*1SaMyxW(^;-)${M11g$^s*dNuhqVmav-@(yQtFR(H z(X={b4Vm?9W166{yug;%B8Hv@Z=7UUH^6YCr_S;yU){N^#M(q&ZjK5ee~T0F>>|Z zW7h9WOTEBr0-=?t__IJor9L3J4=aqDAiWM(`T^StbUeZN5ojVHT_W^Fs)m%>ODE};thv8`0X9xRfV1d)!-0uU#wNHa&`In>nCEk-A%utmTd|*h z_OYI+Zo7GQpCoy2&6T_E*B? z_E%xy;ilF6))_`+VUq5mz@vo9Lju!^m)p92J5%JCby7$OU1DM)Hsk6YjEtYk?$Z+r zgr#XoI=#lwu$$|Ez0(ncx4ihUvbwrQAVi7px~H$x(9_FnTk!HzDEu+EUL9TIE-}H+ zx$!@+`UdKSj!4A4dmAyqpZ4(cVaq`N0PhK4G2XmsQ%OSuZ^wY6qazt=V7?_N2SCMx zfmNhvv5C%(bb{qgfdr!iF)Px5%KU&p2i)ZioIo%Yiafyd)rueRNd?#qgMb+|I?nd3 zjDm9=vY+U#;R*j^*l)0l5b^hGY7O zp-(?gq0jSN@xYcQP{ZdH5!!(y$0sH(y}!9iJ2go+pcGfOY1_6$d4HxMroC9JnO|RA zW=0vHQpIC+80v1~QSSsn!K0TnC~^zO7kBR3B@1*q*buj7H>dU-ixpp@T$~0koDl-Y z0Fymtt_UV-usbi#Weg7}p|L|GY)sKP;z!T3%|tcic)-bbZ%3#{C)hCj7ZQpqZa?lK zFi$42pqq}KoM~|FIRS*!EzY##WWNBGd{%|kE^0JbWTi7{PQ@x{ug97CNq2 z)cDk|FSF*`*<>k-z36Oj^Yi}d>z^M z-#F7Z-cyQw>V=63G3-5UU@kDpKV66a2cS@-*!4%)=&KB86M&?A0np6`MPH~zF>`YI z!FpJ81&xksd442a#lIG^HlTz_{>@x}|LtHwhbR)kD95d zP(vC2fkFWiIh|vzODw5ut5%QX@HEGfwpEKwWt}XFy^z4jBZC-2rBUeWsF!Q2idoUL z=qe{KpJma=4E&%v$+XhoIkHr`$v68c&st}-dWLM=w}Az&^{9qk3i?i?!>>Sg$(ot+Uds!Uy3e}AF2Q~g+8o@v)D zY5Vmpl)SBj?dgUo#+~o3^I%WDfS_%4e&N@bT(U+O`hkb#w?Vn_$;%UgJj3X(uZ5rA zhYH0U`xUy$sT*+O<;x>zHz$*|HREK~)zs7^T`0`&wA)t~BUO*pB-?i`o_ul z58_ewQ(8)6%3;$Lg+}T@qI8KPy+~!T%`kvKgPP=jeaY93J5ugrJ#Hn zVA!{hI6Z*zRpZ%xy}fT;CRyouE>Oh9BcYTv$H{IWLcJupxV}96EFha$wKI+V$)Cua6nvJIjdQ(SMm!kp@Pyz{=E?H`yla zP3KlZfP2H~w8V7EGIe#)n261Ti!c4~fw}Cv7%%T*j8#IKh`bde=?P`?w%tXl1_t{GkU|Z&q#H^#SCJe^B2o2e$j|7{P=~DZ z$7-Rfn7AF)d-b>|WPQNge7fb3n?+%MO>wn3MPwG^mbft(ZHbIrN&z1WZ_IwqwL1Xh zfYzIm9W1kB`N+Ro_96Cko5pe`ZU72quh@sW;^6c-s zHTwveJ9VEf1CNmF{G;t#w)COPLraMo9JJU>%YFiaKKR1bkhSSxBxXGy?qJAzNiEOG z{+fh>bme_l==GA*CqGs-wl~MUInCr69ugaNiMuV`P#sU1Pe4HV+BYDhFh1k;+qP|M zLBFlNaZ+C19{q*vK60(XR}SI=YFj3uLEIsrUgN1u-1|?TI6G2%pDPB25x@56E~u#t zut6cETQXgTsrD>BUVt`94Jsab=t_g=W0+t@;6@M)HSh$@>LSB!W;bu#_#I;A*LT;q z-z4oGvhrqn?ns;2#kq;Y1h-TLu!L_5iGTKt>;`P5!(3bs&~>30ZizT%qx7x7CCfS$ zBRW+t+Ygd8t9o=~Lc34;g2z!Vt}EBBDV_0_l9Y^wxvBZ=o~>iKOVzM5PnOJ_1?sywRSLm#zufCEplUq3*tO2yT(me-T$13?MlSnG=26d zlqY6v0yf3lyu7QJthc?qs-nb>W2VKUv2oBv)o+I5a0zxb*$=X5QUafvn*)JXlZVqi zegmchKKP(UQW(}#%M1U+4?SR5sM}>79U@f&2gIG< zgJ-{f^G16_w6U=fLIpg-_1TYR!JnZA5h&ed%%TW~bos@)pmEP^VdC5(qELnZLLv&> z=S9E#-oI~O4LWe1`@%863XE+urMp}st^4=ye+cRLu>7OvxLrjiWd#Kd$M}iaS$TDJ zf2?I=rl~Si=^&O_b=8w6*OJKz^7*;5(=2J5mD$k?1z`ks ztbc(2n_{KcxXz9prE&2#jQ&@D)sW2yILV~10NlL(4DkAEkybbkI> zdb&D+rERGUkWs>mY+*|GRrtREF@+^?;OyD6m>qW^A!A~`@Uz_YYJv6p|4}rF={XB2 zZ~&-ZC7hq7mHB4}r0i8kjvN6^(Tv)vrl4>Ug-irCcmXDJ3*5NVm4Alj<5#a=^O7EB zL^lg>ul2&%w(Z-^u{aE$*56IfipP?h;LPwPyesLQ>(as7rX)NuckMaT4+qOTDMbyHwk70YLEGO6$tPr zZk$W+4SRF-N4nvkvZ>IHWoO{Mcp|gV9=)O$P8r0imyS`u zRn0HY@_?xX_3%YX+z5dmBVf@GtL+~ST^rtP^$bhf)bq2Fg8)v}-9`Iv5-AS?!2uz` z@0YL4VR+R=ig@Mb9>;YiVmlKkhqX$61ZdX_I3#{!hI+2pRuK5)Bx_&>F#FW>WL#>C zA6$&)w7#%8XQTZUHEVA{%AlvG7nhI-N4;+6Nti0MY)<5Zm8laq)q;ZIx9NPt)zKXu zR=I1>9tD)#5UN_NZw6_YFDoCg8UP$DV*s( z%wud31)=0VbJl*hBUgVLxR$6vEI>A90KF8j&Ic8{67>Ecz#tg5eecIj1qB5#wu3lz z{O}M6EdW8*+PdtM_O(8*p5eEJV78V{YQ)R#%lp4$Il0c~2Z7XIw6%@yxnXt}PX)WQ z470WQs0>eNb-0wLq@0`_;xw9lx;l9VuZAlFp;xb`-g6L@86!s~|8q;U=m&d`bC+cb zLa<2rRzDQZXY5m6#qqnl*t{#>kv#FT3eVu1e*nUA4NQL*^x^2sC?qF@VMAZQ<6$^!xgWzl-bh zpXgP0qmANLX!8u}P+~e+NyUE11rV(iLV9A`1dx6ob`6QQV91zP?UD3ct^sgzfwTc@ z^*I2O?gf6u9ZdmC$yZ1e3^{}+VB)l1RsIL0G~vEwzv>$pkau${C=ahg+xUQZ&xY+x z8t{H7{&())UEvRZ{g6?J1S+gH1nKGN5gi#w;18G-nXn298-XGc(W7*8qN(~_)ZwW9XMt~;7h$cosdkngccZj~DYPn4IGtb*tW zqY&mbU~p5Gxq5`4B{LqUH5&=YD73;ZKL~xA@o<}Sy4oYOwf~c15P5` zQxDS8fsG!(Qoi@N?KrG#^yRb(iOdg!jqz6<9BLeR#y)>O2U(&Xz>UOM(9uC89vnRi z`AK zP#}0ba6giCDkx_G120|{6sa*DQvavm`5aa#D5zfzk+TekEvn_d(6kH zaZ32YpAQpFNBH?flAp1x5t~%{9KO;$`Gn$&Ak+8Z;ZJyI9J-k%bPr}Kgq_C^Dkboj z+F3yxd|%?VLHF&IL+duvR)%DtEQy^6QHHQ*kStnXahVVrWIFV@rnZ(r!c`E)M9RldP$&VUJGct{S>e~#L(79Vhe)0zdORB{6I_*S z98t$%ZxAWmXdhFAFtP#alsNMpN?No@=eI?2wJtUS67_LFggXf)XRW-0OJ`Ao^+OM z{+4yp`;B}ML^8qM-$Zf|3#2kJ0fL|fhUzfuQ3x0;dv_Zj6jrVSn8F8i^RBUArPp{w zc}LnMoRwsc2YDfO7qskNY;xS}s$IKwVIC$rY3zVTk|Esfvn~x=>QNO-BG=h z(7iLVvZ|+?HaWUKt!z#@eHi$a1^Y>5mjK!$1xNzDdOP57GLt==JZ-O9yR`G~&ZLF- zhMz`ffvQml>p59JcZ?^m0&b`quFTXmMJBG9Pf*(?xDBN}=3KF}l%5 z&!p}Fd>B9{g(Jx=J79JBvVh~THcV~?NjKpw^xQRVqEEY7|KPFSg$i|0k%pvCL8Mpm z7>s%bX#Oor23S4ntonfG;*;J!WTe22?<16#=n{ozYLDr#Z{NO5t;oF^>`6gEVb1lDiX0{ta7_W{ zcNGrHQFBesU}6v;WTR3)_jh4I!1NO>L~TpN`sn<59dYyfgsrx* zJ9Xb|q3Nm;@XO~Mo2PODQ{daE2e3ykFR#+=o=k)`Vmd(aZp<*27j+uN&7J#9s|niH zlRF)MW6R1mlE*|am(bvp3ebv7DB*&J=e~aZ>Wn-atm?`~msqvZFGyekgD6)t*=fD+ z-er5bZc*~!17F|MQIkv2(r5?B*=SO)FJ3xF3>Nx@)A4c{2s7y&wL0Ip(F|!FsigP`YhyGmFfpBVPobWt zTr`9#iXrv#b}cd5!Wn9<&;jF7(~Rxm1#pg_q8dQ~Ko)`bzT68*;3AYg^kizx5u#l& zKap1edi!7}A3%Y9yL74Wjwe0p5IF7;Au+BhZf@ecSXC5`_kiDTW@BT6FCrkm4Hb3& zzOtk4+?NF7J2JOaSo_cg5Cm?5T%dCz2{#OtLi0Sc+M+O&(vEp|L(DF;*13fR_C`#qyLmXoxs5B(W z4vV|Z?Lc;sj25IH!}~{e?cSZhY1f=oO*L;*6q-Eo>1N?dvDPE#+feL!L0X~U^IJAi zJ_T2w)0ZRS$~b~zIWou zOu2|Dd^gg2!*aV098d>o@x6cF7!r(bz&U9DP!v)q;m|Q*4V`OUydJmB}fDPK5A1Ebg>aFS>(P(s!*&7}x)M8cTK@c!U`0a6Ddw3tz)A0mkFD zsji1qEq&+EQIJB4L24by!wJOlINd`+{FNMpq6c>rw=`lUw=eUFbI|cG33!G z$T14QmqhfxlpifMA=~{PKKy|@!oV9}{7WqERqUG2?^&fABgxIbn7#Pt#}+hgGfZU& z;f*iU4`9q_MxENSb*m}Hx^{~8rXxpQQf}3NyY4Bl*l@wcDyfjUA>sMHik;^*_g{yO zjnxLhcpoeg`~(Hw$Ca1J%6#~+2yh^BNQs#7)O&bOQ2s0u2X|aQGx@l^hD}Q=GyVTd738V&LKj26Q>SfgHo=4d-Q;8rWJ6RO<#=H#)dBc^n3^>@UPlx~r zYcls%XrpLlL?=Py8}{8Hlw)&qyk52yA>f{Rxz?;ZY+yTP{^RI&rVEL^;1WL2&L?q}CiLQ-x7uRFJARl&d z__pcVes1MPKUTNRi!uhXn&M-3JdIAYb^Nr{DD^88sN*3kMXMm~!q-@+^>m(M(zO9s~u>#S4VZJNRm}-MbI5!Px+FG0nfM z23Zf!h4^A{zaI;jtDzy0BPIgcCVBxBVttN}zegG!-`rT>Vo!2dApHPAariAG+hsQ% zSTvv{_Q-W$W(^|44fj<;tTL41dsIK?HI4@O(Q?ROI1R#!%Is)GUm@-mHapax&9=6- zj3&)V9Qsxm1XyUh^H6?$^q=p)6-){^N-toGeIH-?PfgGz-rsZ zjTb8(?MJ>YnZ_kEKeu3f5~kLi&4Z5Fdob^wHJJF&`1*;+B(r(G;$#bKqTzGvdLDCz zBmARjuc2kz_Z!%4eOO@RbopxgaI^!nI#oZHyQ~7c5u%)OmWQd6V)73{j*~SL{PdJ> z0ovW&exMg#bb2}u=AWQN!%g6*WHX88T}(`MNDYvt0sxRQI*BMv(&pRsU zR2N#%6`<3p>FFV?F`mJvE03pv<{@0kgO>k=k+$kB8W~`a43uX=(Sg=L5?<%zm_a@u zhT;47C&=SP95hfu>c)))?U$M%Q^1*L^U+(8ZVasx-iEn=kfQb1 zx2Mx$)+A{9#>5x~oQ(UJc4RzzmzL3M$Ymb5jZ?^lHKpxb$U>JxM->5ygxe2^xEYa7 zG?1rA6OVs+-FY=;OZ^(b0>6`G27C{a;#9#|v{xDR7I)k5G?1h-jM@CGbqM?SLghQB zum56h4h6t*_SM(z-POAhs6)>7+}kUc0_u;@Zca^2{fyLG<`3Bf%_=M)@d43bVxf zjAWvj{uqL{=2Nlt`>$WMkS7t*IEm{c`2|zcQ`iFhj)kL6Q-h~5%eA^h19pO@S6SKS zzk7$nP8KamI}ys!Sr-XL`!`upwfp{q2mSAFtpUt9ji(FVG*|uW;cotaxc2Z7Gxltg zhE#7RFU}{=zg_B;f_f=>EP;9e^o64PVfok|)kWcqueJ3~zz#@erkr{A0RWlT`txhr z&}Nj%9w;Vg*;P!{W89~(H37#b;p4I07zMB-5oW|35e&EkLI4?B9zhz&Z5PeVRVOF!}%qxTN;XYr}7#uhwF}}p; zHEwCmZxL>Cb9X17h>eDh-w1Qg&~|-IdASd6(M12rA5?i3svGL493d9p3Q8&}?gEgv z^1)G3%M1dKS+-`lFG{n^1v@|n&XPrUQK6jY;ZxV&#K``efAV8-DvCxq)48h#XIBl) zuFEUluCPn0?&)#6lvP8yUAp{x6##34gLmUx>DeQz-j|oNw*IgMlR%;==K0=A|6$EH zxC9KdXfA!oKTk0uvT$Sx_U0X67VrdZZ~@&bhd?~1hl5kLUNU;9f_A49pn??^{1(rq zNJD_imA|ntKmn0U;oJj$pk*x+cF$;+05(pJ)?qyIfdypinRvkC;Xa?=0Cy1!6fWw> z31v#F_H9DTPP5*Rz9eB+OFfN`lY6kI1Y1V%n?5}g(<5XMc`g)?P%P#`1E>xVZSao; z9f9iZ?wEC3=w9Q`*6%9d*oGlyNrYYqHHu7u6kk*Zo37IKty^`LmavulIU5K91bCi1 zbVGX=4UI4;88~ezrrlSiHb%*Elg3`v^2P zZl*UvRFIe+AhU<*3hroxf(01XzCqt}`GZ<-Y9H|MW6CBNd2m_0i3S4Z$~ScAC1Hld zHQ8HG_VFW`$&hpPmKNK!`RF$#P+2mlAR=AKJOVK<0I_+d|T25Pe2<6;^DV#DBjD#xsN6Mrb zB_5=*BhQ}g!i5WhmQCI;@)PIHWU<&nIHfh0W}$aC^SRR=!$;g7;h+LpAviH&z2}EN z)Vsi%FxK_)P>G13iZsHGojavrUP7X6?a+jpj5EfnLrn>RwINL4_Qd8znFtf4}J2>FD-31~Uw2eBzDZ-R5MU56O z&)-Kn_BE^~#Co5Me*PGd2%KEn(6D36mM!qHRzXje&7T!TeiWBm@$H*rY5h?lbPo_b zdpvA%+7MtxgPoQfEW+_5^A2}@rGF=e{-rRAd{@1-AJ~Q*BS{D=T0JoH0U$nOFL3PG zndw=$CG1t2t|hnE3C&9^9D72VB^igY(q5Ey+O9^Atpw8@`4@tZ%u^HTo}u%A0044I zj9`R9d{J0S$4t3%?7G!Ztq`!zj?BR#eT_qICRy>2L>3o*7ZWIKIBR*z;_6ZPE*1aF zs=3$RBxzE+yDynkU&iwz$2QQOX!h<^#-&)|Ob9F-6L|e8x)_L3t7BijBzz3{bi$~K ze1zT^6CH#HUIHen`^IADxZ}zY;Bubx1T!`rvX-j^1hTj+8|MmNo=wlR`Em@WAQiyl zn8sAx*Ibw2jda9i5b zAK{;%z9HJPZJ+Q7*mpQ7LDVvG4iNFWm7q*nC_(V^b*CpEN73v`&cFU!4No)c2NU8h zm@O3LAp|&6E&@D9D$?A+y#&V{S3&qR#WkAb$DscdJZz!Ey6+_GE~fj}RtVV$%$wH$ zqnqitDp70}U@2#|PTz$IX^J2Tax6)XizopS-~_x-pTTb?2fyT|b3Ty??6|~0W9o3& zl4FtrbcO@ak{*kdSW}&)*Y{~TZo^(qDKdwmglm8#lXANPco~N~6fj#VpB_)=RB%QY zLkzR~O%U^e5hH)i;temDT!?63W(;pv--b-2PIkH*raKP2YOshRI1C*> z+Qdm9jYb1Ou+gu1fs+|OHhwz2$CR~v((u=#nU{pTe}Ut(Nx$yu_iSe6*=D3&{E;X7 zgBKy7-IT)v(z3~(eF^@&o2dP^=cmnRVArUFFeG6I1k`U>w+^gM2B&einVb$~j=fta z+bg>UyK>Loz46+do3?L+BC3WME*Lc5VT9q(jTV{;?Q8@qU9h@AQ89x4tgNi$ zcqo4kPE|CkdMKrpYRG-8s35{SNt9vVk!aGI_0*L!lqYENR{_f~*5uIXnk6p8X^^-( z^7-|+Xg)zf6YP38j!arwT6hKsmfQH~pI{By<~l#c0jwdPtj&)Hpe@z~Ie{1U4}{vs zM;9h(3UO!x?>hjHhf&6X@?wSm0jR5$X`-0@D$Y_a11YkmrU0nc%dZ)x5c}@w@BfI( z3&?I>)J1j}j*JrjI|c}W5nVVsM1q(pH?uIQ-8SD(=rB4fxXH-F;rg5Ia3ZFw!El5S z^}%(R=2-XC>1jH(nz_IUPieW@)%=MwHJ=0IdnMl>NudEyO{fI^ZsxDQCc*zjFUrZO zP|1q&^7U+NFHCODAeMmhvYNFAO;7nq1O)uyOHV4fK{ng-t(TM%)uKKDb+vr+L};cQ zzti4y6796IveF?i27FIv(U&Hw`b`6eW=05YyA3W*^&9g^*L%zvaNn=omq{RbBG zf&ijPcO)JMBG+gZ(Ohpm@X=t9#z03MMeWnrMdYO%-rj2onM8xzw0ZM0&z0rmWm|Jo zxeQ3O*v#e_Nn!6G61>Hj-DCe-QHw|uRXrTDYK$9$J;I3AVx~9Om=w_kWA*+Bl z34E|K$1sAFXBezA&mriuW~``S%OhrHwYn|-cc+FM{ECNZjmzJrR~LsLEx86Ho~Rz9 zhD@O6(lk9tUQHXrZdJ%rcZqCqeuM{p1tu)2Kdnz|_;Fw~!iqTac#F$sd$I=my?gf#f|^6`xPnRi>O!HCwRLJrzY+vIw50d# z;bHLO|8b-$bzlZXGbOE;rV*fk+H1HJ13tgIo<2OF8FkDJi7BoN1$!{3%OCB38NqV@ z-o5uYxC^uwr@_7l<`>3Go%WSby{q;x*%7mmf3z?CZHlG@sb$din>8+sz8^T@iIJzBtgn}q9BEa+6nM2jX~KQ#PT4Tm!H zXU5Fv!Se>YW<@5&HR6wFGAzA2{CsTS>{&W*t|>q+WOJjQpH$>4HBkKK-r4c%ecjj1 zH;Y%6pF;W(K+IUBD;?f2Qpz+Sc`)jdVF06BkoZx{%h{39YFIREII1CgCmvUpY*jpa zR9?QqgvFb=?+4?$z;Q<>HfFWxjt^j+QB!{pi0Yf+epqQ^vuGK(|GkkwUvQP0(+MJ_uZ&1mOS&r4)1AR&1`| z2{3VAD5wPCA*Un|3s&VXhoi`Qxs402O(AHLcsf%mm(YGdxD?Nb>tkFbs_sRpmLh$G z)69pVGQ;S5N-`}tqWrTyrXI7D*z$>EQ9Chv5e|L`8is}c2z!QP9C0K7!(S8hd&euxc%CN;W*8P%7Isa0HwG_hy7~-O-DS5$0>xJR=AkAbl0pXcla+H(Pj1qtrg45%cw6S6O)q=Xs$RpsnJBby13vFIyvJ7^aRcP4&Xh~lObFuYO!DQ zZ9pMQ9+#k9Qst}0?NG&rN+;P7U+4=oW|Km+_dyn<(19U5}B;h!&_@RdJ){5bAE zxqECqyHKZW_>*EWnNFOZ82>^JsG}hy;F6Jl1$L$=YW~`L?fUfrJTho=rbEtfugU9S z5NwKtOH>mjcJ`M^Sn9txD&B`gPNhk*fxMy8Uqhy)#2kQ-DS!kY-JV4-IegneZf>{WNG9$(encc*@`30Lq+@B&cK+bq`_Qk^s{?J=D%p8>c%U*XK=f+m zT!XU=*k>Ca=I;FJ9KoAZD7TJT9@aa#6 zA6P2gN(Pg}hrljIl~zDp^-#*)i_Qc_6Mp^ZJs#In8UYgwe2xNsY${=RHHK==EVH_b z^TIJI>P?$^5Eg=M0KQa8QRM6Pw8IM>AQBN;vS!ViYyFkCWa17=N?yn=J1i)u-8we$ zC2c=+6eT(e&IIw+rrJX*2HPf$7UQSCF6wDzQ>{qfkp;`HM(^h*&v7r(p`XcKym%3B ztZ{QcJ~ld}{A!MNr@g|F zAb#7g!UX309F0Ki0_`Uf!AwXC5IpMeh?}|0pKXJjfm2=l?nOX3(A^$C-qDt-8-GS) z0f_?K;t5QDl3kwIgB8X1=oYz&;Cf)DYC+)bgiSt_fmhp%qwokVccE*XT}61X-A zlPa069j7Nt+uK9&^d|>mJW=esbX<~tdo^S0nYz&UBUV4HpUpOB`|}6`dk_u1#F{x; z#y~T<2_y@zT)9GCy3`d@`+LoYH)b2PT-AJ6UFt2yX)%&110En09aVV{9R^p#_LrWK z(NBd{t7}8ivWn*c3hGR_*>m8(<1hyK4x3PW4h{}U7&Mp{DU3;Wi?YH$oOki>{Qh#x zYu@v^_ZuQR*F!adr1JdjkQ56Jf)elXuYu8Rd8KJOA(p_Z!Ot0o!FeeND#1Y2gq4rD zN>L72dgXCk~s3;4h#jeGJge`aBwZ zc+!!bg~fFG8OLL-Li+XC-UPZsLxAzSDMI}a3 zqWWFJwl>WKu zimUUz#)>LWWYGw{Uv=GZwB|@6!wwJ-V(y}UY89R_I$?3~V(jLPm}lzviq3%-EtC^+ z8awckAIga-yuG2cR92^!3h-z(oW+|&AI7;^VoiYla%eu^h)q}>QnLVu`3go2WQ}_i zMeUbo9wID8ehg(cu=)oW;cF1y2NCCXM7(rP%=tp8W4s?AtxMEF&u_S&p^mH0FRu2;P&K4RtOOgz+D(b*^rA4R|%o? z;YjXXL{e5AIB`KoykV*>z5xr@Zp||B7h!1)1nAHov9C0q2%i=l5>ea^E5J zn2@{lNY}gL@DE8A6BPnTv>!Jh2kizYsV;%)>53XhDd^a;=8JxvkX2??*0eQiO*qRD z@|3(+4LL8omAE%0WIfVfF=#@WP#f<@d=#C;se`<)2c z0DI#_HYUgea&TwqrGKvf`~Jaij+Pr9ezkoIjj6f2t*u<**SGzNTej|e;|sMVxz$q?kPMf8(ZmEf zi}U$E5SKL~a2@VF!YkyZO?XiO!S0zM-pRq+KC$N+Ji=FCdVl!*ISftP>GwB+P{_el z9L}r?X*z#KY|OsLY`QerPMsK( z;W(^{hKQ~P%8f$wLd$3Q>n3+u$czQ34f63h;9+1_YDU40h%KlT9)$i5TRhRqn!Gd% z%Ktd75NX+ZU^;%qqh2YILEG$=% zbtUf)gcFl;d>>>nSgYtQckx0d#PV9%=l*^RbN3gXnTwa(bdaASs&nMyR8B(RI$xOi ziXo9bmu1f5J$M!nUIR|>y$gwKCVU6%7124Z!j6B3)L`hMa(WQ&M(&F|VeD${cM&Bh zSHds=co0~<2PK{LMk%t4I5g+E^e*sDwlsDLB%K(DMjW_Gq;0PF)K5=N8beZ2i4f$d z8rYSk2RHJmPH9aLd}Thc790smMwSy}leB-U7|-$V((u9md#%sY&m14$zo)_w;>6ii zoCLrJDcgsP;C_iO3~`q^uBG5P=yxViPPYqh*!8Ye>*$CFa6OnZ z-i;=W25=JC2cQN+APchI^5UdAxPKk?vt>i9bc)SF5eyW({^&a%8&s1!@Z&J*&f+8) z)d{>IWM*b2rAeftY=X1KB=gsrte&M>Q|Nr;sGW_7f%M9MDl0P6Ev-0x%ctsjIXEjZgLEWUvpiHOA7<f){7UTZ)ikGy~Z#l z@GsZR;l#@?pv;AMHx=|~qY$EAHt$iq*#g~z;dd<84KW-899kcY|3w!A7mG^=0$fc` zJoM!s1F+nH(s;PQO_#AsMzCIg{_Kw#2I{n0sAku@v#7!b@hy4kv6W9WQ4|PW$GM=o z~ z|7X;|TNHmK+pKepGM>bQ|ji$cL;l+GYpup5C|8^oio?i^qhOF2p~WqQz7FDek}kF$7;sn#LFU8 z_o{CTK!Zj5llnOVVFxA~{R;dWcxQWijT6~O5<+NR@YJ+Unw#6)rVP8mpD>4oxeEn) zowK%wdivYdPF+7oTYTC(j zM|nkRAb?*(EDv3%<%=s16g33R8n4>9^DV|3R=B(8JMFf=%kd!;mV=}TtxC}wv}Rai zSoFR^dYwa5m$@O5EoH1vgudTwKsL z*G_GV7*nPU&8cZ+9+U}iCweZKj03z+zQy-Kve8oHc?_uD`!w+t2P%=*U98ByW3v2u=eX@_U=ky_hzs@;C zF?Z~lz6_v?kqkbF`s1G3j^6llx4?LA6Z`0at;K@xeY`t!+@?x@L<+&wpomDe;kCp) zm038dmml9=Pasof2ls0W>=p;X%z%_XnZg>3LI8-IZ^|!z?8&vAl+xPgai~&?b9RIC zJ25sPticbWmmEwdW&Zun8xDISPESBD_p0`!&7^jsZFo(YDJTFBhseQ zMT>ktv3}n4V>46K1Z|+g5nVJo5F)4;Dll*+qx=+~@*NAxoz1{xMG#3912WzM$Kd}> zFD!!lNOpXJKkzGfWs{1wHGnR*&zq)4>5Zmry_B|v2J|KZHiC3N`@JC;BO|}TNkV`o zKy>@l^S5c=!2Katj8HjB3-RVcQUuEJj>s%JIsUfu`e`RDG#A2t2uCX%{f8Gnoz`4b zt*VJ%LkVG!r5^-H4Pw#X7#KSd^h{SzmE$}B|)U*2?fdk?3G1Gk2j&yrVbsH zmh=nCD-l%{b%Xc1|3q#{K{E%_03uZD zHf`3%b<6X=1CpcL1t1X&)N-t)gHtFmwYX^rYzHjWP;NyD%$8|k-^pBk?C65_& zk#qyxx2_JyFg6kOFJzn3KG>bMqyk}tbn}KDV=hc?2vUZd^zZwbSOeHT3W9;EZ#U02 zZvDJBt*3w~BLRe1*45RuO*;gpY2_TQ6KaO%RW2#f=E`*79_<{pxCbMlh(BsxTMvZuc#MQM(=Q7TrZ$EswTkjCgZb$9zMGEa4Gu2S2!w}ANh zhSYvM?W3e3nQch6Kg0oGZg)Ktm!QzAk94HEC%fpMX&5r5)AO$@a|{O6HGP<$Y}8mW zeYi2LAhXFiKdt8@GXw!aXk-|w$LKbR*Zehpc5#cs-4N{g^F;8J#+hfP6Yxm&=@;Enwt<1f&dI19rLZ#b3YmKd! zV7sv0=wHUe+EZRQauIx#KdlS!Ash0$hk$cs4cqO*F+gtjhT|`=F%@+_)#RnsAA?Fv z-HGn=32thMwT7Z?S;Q|39T=Kr`)4>u+!5w(5B`i z=e>c~;4Ej{tt=k$ddKtyd(w8S89O#+;$O?<4bg&1&PGhE`d1?q)e{L|HYVBHa zuRbt!Kb1J7fXbo{8FN>rGoitFI;3qsCFMQ-{zIM(q!uSKUPpxmx#@@v62c@QDN>_0 z0CI9(3#lf=vK@3p_-f9c$O{mTamB@W-(qN&i?jyEuRi(S`d(mc(6&xnKR4+6mcCc& z_vX$7=&FNDukbV9;z8r8X#<=kiYekkB58y!z*3{Ha~OjYGBbz14dXKOKgJBbC!*NA zY4{(&3F6oJV4$X9?=z+x|BcM*0^|P#p2BClXz5d!zx^3L+qp&@QL3iVUm|OE*_biY z&D#97Y4N*vH;MkZJm#b_XUuIn4fO?ze2tHQpBk2!qH#w2xi=+c@Pu8hUsDxL9XzUr zGv9sW>fMBZv<*L8Wb)gw$-l%HX7TNPpEpz1Xc4c9&-NVx0XAzQ@992zeE>h-5=kJA zBS{fj9~qUT`Bx|3^BIQ}Y?)5>0fVCB!zbv(vun#@z?jlN6^59fl^GF61w{VL%SK-< zft?>NLqnKc`GSD&4ZpJD%1^VSHC`rW+F2RbQmqEd7vbY?V91D1U=kGTwtQy7)E>z* zP96Sqa2JRygMVWPiMCPHG7D*VMIT%E{nLOEP3cO;WnF((RDVV6eZVwb>|cKeE3#W@ z!XPl9W(g6OoIB6X=ErR8c5h-h1$36rpdMA;LASG8Gyk13V@9~hC9+Bj31-eOt^XQR zn~A&L*yg+1sdhDfKItqG;2tz8?LODO++qtUfZ59ll;dRe;wC*iX2 zhgw3Rc;Z*P`h8N4H-jqzuHAR>;)bw!>u5jtUSscc+Qis6bx(2l+`r+Stt;w=4jn3v zFp|-54AizwJd*p4QK1oI$BvbW9!eJN87Gflx=Hyc`d@@AVxJ7KqIr2=aBv5q2v&{A z<1UdC46qe#J;s~SQ?Zg`3d5BD`vYC8@6h*fM_u6ihzewm!Av9%IX?~oD}#DnY1~ey zrJ0}K```I{nB5-W05x)0bOv4IUKkIO(8K}Zc)m^GIu0H>G>&Fo>+whND)D}vqK~;2wbD`B@(Wi|}hg;x^&>_U=LQ4^^Av zwovmQ17RO3zJd@;9?qB#wV3(&=?R!?;U9*oQotd8;eq1c?P;udWA1C#Xu#2nFAFM3 z<}V`RmS;bNOxppP24*Tf2a_G!shJ&@EsKn6{^OxqliXhB6nq1}as=gm&aNNCj9iz# zXe1imgpes#!j}&*e^t8}^alu+#&-hv1h9-0c+^0+-3GdK_J!Pkg*JpTfwjyTB-iVVP?9T`Gbx{6sPH2yRu-BE+N(3U1uIyEpN z#A95*ZJ~P?02ZwZZ+wdT#oF1ZtWa(VdH$0UMW(u$%X)e9M%9gp^)f&z#T%UW!tk) zLs12X1O_~cAtj(i-jtQ?Ay&d*(;55lGmoA+b&mvzZ}Q2T=664d7bF@_(QgKP^ zPGl7mFaTYqM0nm39#dxW^THQVu_g^D;KMjBT6BvnE|b%AO7S3oM9`)fUNAt&z^ekE zaC*mY4S~$s-hm;3tGSXKc9J%N&Sl){>Ovgaz?N%I|E~KpDwZcwFv67i+5TrWc{?&P zL}6q4;{r!oX8XiWretCEZZ4RBw45xF5K!x**Fy4WEJp0}(u34}L|)7>!2X|yk9tmZ z(W3WG=1~}H6%)FWoxIOb3C3Pn9r1xKO*m&-LF;%6RkXcvienwFtdDk6-544o2 zwZ+y`23EAuxFSdKyTwBJi*+&?^nX78^A|0eysb%dd0nJa8JPt&L9-x;2@NL2U!Ms+ z+Q@a;*`NT~IcabAq?!#Ej~ZT7-KsjJA}6YyKQ<-YZ5*6i0ULwE07q;F;1i{yCCX^K zBMX-<^*?;LCvpixRP>y$@Axo4)?@=W$376?*m#R+QD6lh1K=c3!3^Q?Gzq9{@_Nfa}ezBOjUje}^1E>cMq&Vd$ zQx?jIj>uk!%NTGdA?)diLlQAWBJ!mt2>hn_o;4KAi7YJh&v<{tVDO~%r7oE_2`Y_> zC!wm&19eAGt!+ zOcki=JDEh>tD`{^9To!-_!#;-Z5q`rY^bBPcdqWp-}-k-V`H7u=l@(7qct-ui0x@l`d1bW#v=A{I8HF}&;*5Qi(Mu@s6VC3K4W_`{ zfjkvJp0|X5s+zsPMhOw7k@i9AvcpDn^rX0_AdaNxsn$Ek$!Ze;Rq$LLbZ4ruRP;3I zc*N|cMSBagOw zJ#?@ma%>?cD1u|C+Nm|jJqsw;Bz^JbtwTLcmn;08|Nr}9k6yDXD?hzgx3GanASDDOL*OO3+t zuxyMRxfJnLX)E5{RwV{E7AHm7S|WBx#1jTuncwt=zn8zp&3|;uwu$Fp>WYI znz{cO`QX(h>~B=e9mnHdekDB)z*j%>`DnBny?S?Ic5!lD%dyp^Y7@*1N=K!31pR5jc(%m{+9bGNP5+4DT7Og7JfCyAjTP zqqgC5c^O4p-g)^r$;O-E7$@yf!`vVD$7&g%W+h{3P@KZekuoN~^pZOvLVuYjw zrh1caA=jm_!{27{i&n2^qvE-C{kl=8ZP0~j8#tXD7;nJ%xSE@qDXkxa;yi5qps$*m zuxp62kb{hpMQuE5Dc%ddZUR@O5jAnQlL18zUOCYLTIAl4gDOtIKSPiQp??tt2;2*Q z5KEqdWo>x$H_*sPa{TQvHKn+2p>#OToaeu0&z^m@gO>ghLZujb{TF)>2?sV0anrvg z`ACz)z8S2BEI3e{(YFwHILPjh)3*IEUy^p`@R#GQwmyG8pK0=}ijqZ6n{D10S5{- z!%Uvp8pec&cV@t^FPckc%mVZMg;K}czN1I{@0OhEN7M(w(Qn&ag*Czy%HrxOwAk+T7==wgf@0Ib%m_q-5L|}7fbrT8{0XqM@yx230#!2$_n#i9@h~h@&cM?yUH&dvtxtEKDsoy#5|Aug9#U+&hroL~CA@dD`ZD zSzl9#X#k*69L%WHPdpQi5t_J!)AUPVAWBW-gMEaiBX#FJGTW+dDzknBF!?^v5RG77 zQ4 z-4rA;l`D4MfElv5O3)k_L{k@s&Wr}ZQsZEA^VY4FpvDACWAIj+|9(^xgJg0D#hzWq zfy%${542BJFL1hIEGG&)hbY&LY)k+Oj(&dHQ2C zeURr!{)r(;kr`95$)ri{GGuW(=J~Y_pI`NUsyKH3bIP6dqXq?<|JXis^#5((`nsIE zEz<(*x}1vWLmno!`JiszG%~QrTUX~rCN80^Lnhv9EA<0PyAgcqqNqh$xCuK%WHgHiLsrD=qVx2L=SsCwLMf@zi_ZrPgT9qpdHk*2%$UK*T zv{|;%!L?BP@m;AMd(tbM{d$UnaK^O*psi)ulRF>onL73`rvcg4AWo zgHpoozb%3UA|L58VrA^4!XJ`4fkjb=^fq@1$k6zI{rMuWKNc#?EtoO#vT0Bz22|E} zZr8pvXkFKM+g`8|D17Tn+ltNsB4*LN#NF^E=&V0wkR@3WtzUl4*-VT3R1Tdy#xD-iZ`PlTbff%XDk<&7ECfInbAOHCxh8UC}Dc}+%dpulJ{L* zlO9(y+Du$9;F>U=xRXOBmWEsQ3O4)l<-DQC&Ok%jDc?RX`BBKUhw*!!i5hG)gYHME z0X{!J-xhx=K_1OEn;kz@eU&+LA(;rxvNwVtVXD91hJ{Mk$l0=Z2Hm=_fB>xVPtOe` z4^g7E12M5qLR3qyz~qmnK+Akd)5=oXyZuxmta-ZyC~S9aor@lfA@6HZ%}9O{Ah_5} z+3u?bilX#%0g@7|0Ean}0`ss(kSC)(LkhSX$`5w}8ITp1^BaxJA%_nD9wfK<$j?Kj zGHX};fGh|bYzxG#kC1BfId;wO%4MV=fre$(8Xc^Nwh<2-6}+^wA(<@TI9co;)W=>m z{x0t})ilM_=uB^CJA9?q)V)U{yj(pitUy5uhU|4o5LFu8n)7$d_Zw0`m# znV>LP)nXtpz62Ne08}_IIZFIK?xS>~fC$F0oMIV3RKA9#70w`ul@B{goPp&wd zfjEA}>1$q|*@>-x=9%br|5bxaNJHW00LG_Smgr?e~rM#oMZba;vz9!lerV=TmOC1(T94f zoa6>jg{jbu|NiSiA4jv|pO%*9_P3pl&+lI7#v_sne-Z@I*#Imr^4&Li(xjDGxe91Z zXVKp_F+h7o?cbK>y3f~8C1B_wEF}8N0~^N@Kr#yoLMepwx74hL4-S7lRqVugG-4-) zT!A2`Mi)TdL|w2QVLrqd9j6NJjZj+QC3||JxflOA;AKZrWY?C-$mOWGd<7rRZ{_t< zhIXAHDPVI!o+g~DSUcqoH55T<*E4%>*suv`U$}Cs_f?>f;KiY|mBm0dab_Js2yPN? zKGOO#X=OP|s}Hm$@&7b0ZpgmhUAj(4(>S@f^10sY2Nzo{>v}N0`W6Ed)iOjPb|h4( zH0{z(gX8cKh~?X{DFi~LtU5|?mjP8qNNJWr7-y!QVY|jQbq6t570m>9%RuFu=T|@) zd<8qg<8qy3*Q(8-y6M`X5(Q}u{^+&oQPkgpy>WGANh6YiX>=0Sb(hpD=ZRM^VN%Pb z)}xo@uAMtsMVQS!4(cJ=aeB6yXBJyU+#AYc7Re<1xzobSoMEUQ2?2)~62KaK2f_MS zMOyfUQxz1GCPBs=m@X`0jSo7Bs?&C8r;Lhavoqx{ViGIsK)`T}$l>44eztThpEfD& zS_dyQ1nh2O`{MrB83sIZ7l_^DVJ!$o^k*%Jg&Yn+Wc6m9c}2E!JKw7g8)ku#2+M!0 zZ#Ev?%h4Ugc$=NkGq@f7)%E9@(aI%di-!TVX98DCsz1)WK9j+%&kw$n$n*O%R?T)0 ztNS$wbjZawkW!|uSk1EY9%iq@Q=phQARg-nDOetxt~Yx0XgnkWXWd%&@j-KV1>q(g zO(R9k)MM05LPnx(k}@R;1|u?)NT$6t4yXJiRUe3uV`p1_W>KF0_~7-{=9+Ka*AK|u zw22lPO4{=32Mw1vUQQH0ryRvM4?ByRJqNQNAh>HZ^T7Eo{VxwebwHyYOk`N{P4@`G z9bmw1G(h>3?@(yl;KSYa#Um^Oq(=WFcGL+Yf9N7vfu$hX(*$fM0150)Rtqm)|G%}X z*;3mKS#0V1qz39LRjrx?fe1%E>pg4CHjwCUl1ptqr~Kv6^d;4A3gx)dFI(+Um>%TK z76iTzOlc9wGMTjGYa`FP=kz;@VjFc1mF5O#}x6@A?|^|Z(ECNoMSzE!-ZbM=#@Xedt& zz><&&-jT`3`Yo&yZA1lL42nkbQKczVFA07m>Rh|iGyoewVMSvGXX-?r0kitzz51e* z|76((#Bv$ZMy}-YX(WSc8A~s}C<@<>U2|cE%_H$1Tgq;qul0;$_~& zgU#hNtJCjdb|3~VLH800oHbI`#s&x5_!@i^ISstFmZn?Ti;Erl_C4zK%iQ9e0Q{)A z5(p+}y{Tsm>CdJ4B!QY%lrm(W$1#Kuni!;xRL2$i;nH%&va&Lo3ahgdIo?{F%4t6i zJ)%BI9@zj|+t{JVUrHeXtBI;AO`|#NuhF?PAN1f#I_AJcKiN+!f&g|+@natzUvl8_ zufan_$BH%*d$V9L;#53xnI5_Z&Y*8QLbjk#%m^IGlX`HXPd8X*N_y=hWad8unY4dk zaP4_WQVNq}M5@L^s_C5-1lhvWwnPTA=&OUW-J}Z0SVu4FLA3-wQ>BvJB(J3 z+xpJ=N6MPT3+V#f*R8t+>ciaetJ2%KB5T6DD#AR|z?KBtSZ$iQm3&>X2qeb7}$@C;}T~EUqm)wPZS2W=t7hMo_>`L0mSw5%gRHS?rWQ z51&R+(Xc+lw0r}-i1jWyl4Ed<4RPBPD3zgS$gO0qW0O58NLT{xsPx+e7qAA5mPI zQ-FBR8l-R}F3!t3>Gu5*lxz&!+b4xU3$7NZ%t5pI9-|S$JJAd(NI1noHbh&L)~)PLatDhNpkztd?mko z>B}nzXhMY;eRn)AI=T<-5*65<^e`?T|EGPyn0G`^bb;F`WJUFj6ZEOdvoe}Sh=6Zx zDmHG!8{`UOH&^}3Ulukab!nL(Kz*y28;EXC;st>to z9fPAz+E|cRf?LVO8}OkFLn%=k9Hp!@b=gXShh%C)3=oq~w}H;3xQJq~$L#x7ETKso zqGMzgB3k%t{`LA_UwVL{I1{o_QjUI}yZvKn=|f~egzESjPGWa4F5%K}!V*VzVHK2! z$1#NAHD+aJw}KmIA}w*_7pa5^T5b)sRF}Ry8K(=H$08$pz(0zKCY#WtN@vS9tspm# zd8fq~AIqY|hZe1uum_w6EEeQagH!GZ2MML+#b>6H&jLCm&#}}RLq-ATs3$m12c3>x zJCAw-;yCNxy|(NQ5L6gU#}z#I+!}*YYEi0T7yd*CmpHfSa7M55^4cl5;vs!~T1VDx zpiZ6%mwB(JA_K_tIV&IUs^h;91yC4$>{uS-WvH5?;n$%q8=+1{@5DAOm%?Yy^bx+S zR_feu<&|Quw{bI^)UM5*Xx?J&yU^3WJwHdTnPcnoyRK+La(`dPVZMq_-#k0%>sb11 zNz3T|t@gL__1d=0cYY(sThGdpcP`QK-QJ{y+Md|e20wo982IbG$Amznpd}m&m8oYAi67N>g1!L*ZGDzkh4+?ez#4Y3X!VHcGq@_JK#8NJr+=$?)RE zi?o1vO6-h@Q3I%8ZX?O$ggu}iyL)QO^9B;?yQ`|I($D*xJo!)HhL1&WfbV#-w)@LZ zn0N`|LDju0Gt+p;(4puy`#>J|qo1JYuIt-{6wxTQD^ z(9>%J+9Ui7cSD*}Zk!;TBrwItrc@zFk>zaA80AiEZJ@6&W8Fj(!^xAqQ5S?=PMtg5 zY0)Av0;7Ypj`#ny-KS#tv3sFao2*Rx>wF*R1w_Cawf?J0%D!guwe#=a@Bd(LzcFJX zr6u6{KfJnW9a_;{K|#XT-Jt73^-n!9`_sfrYQh#{7hUq8UA@27^1xO-PjoRpI&0$W z0HHY1)2JL%m||+$hp3O6G(#6+(!gA^@9Nx~94q2Jr<<9Q-Ghpm-|cNN=^&UROG`mS zm?a;u%1&p*hyw(K_9SzL(F5P*j~FpR29}OaZY#tmwrsq@EX~mI9ye?Gj5656rIJw| z00xz=vrNp*7ZP^y3+JS&1q8;%s;~X>!oFDj3&~p+Bp_VY{(e~iQ4upzqJur@3{BMN zb#KjOQSE4^byf(q>tmB(Y$_R$tSRI7PmvG zusMfcs$y<}2!t&yEyZU7F1c?fzvfd?E?%r|TjFM}u1wz~S`zv<7LGP7AJN&UK3!&2 zSum%S-{do!AQmrKGGl#Wf^x}Zjp*Z<8LgZ5yX<>-wddbr3q9>|6nU^@de|qz^W&^tU-%gPM zJax%84<0_GNbUD@A|wP2cT?sIfW#?rjF6}VhS|tboH;W@>$}hZVz@{*6Ljbh zlT+(tT*onGKRu$9?hMU)A2?v2RI05+i|YkJ3n1wT+Tit5xK1>8!wmt$b z#g!D>0G`PYxCOk^8WRh($(n*qCLTMcv~!Gxh8LYf#|M|fS|aXezBS>|+Zk$s-{4D0 zJQJ9;WEIEZBd@n$j|(ZgfO1W2QS9yQqm7b|AHPjN&O6a-fOsP@Lq4&K+VA}Sk7L>) zDI{6@7I+(_JA6ebO+8pLt)bRTWsjMWy^p5?Pj)abbf{lVlrcAlCTkH<&8Wq4IuK&o zUkJHaLi-oJ`Trc>6puYFuWCdoC0Vn$N<77uI*fEdE55##eLSlM_DpC~% z=|(pFQi$jb#!diW0f6vX6+jD7I06C7pXk zFYtl2-_)3K&qie3xZM5GRvfEAqzxtS;Y0tT5HKoh zj$(=8dd@2SUhk13J$)~8`-oY%>z_C3cdyO+o^LC6|W6wD{74D@hdGcs(M z=aOT}(d47#{cKQv$+0HL(`#(05ChelX zQ+jrH`((q*V)-ww1E>YwaN-C6LWc5C&|A*RwRm1o(9zl18P~XMq#^d$92RPRYtwpX z*d?MuwBH8zo%%zEc4RJ0Oz(*;LQYY1qIDQXfHBcS`(=-=>pH+^?uCTBmOjSU|F7Ie z*hO09lFBiTJ8Dc-V#AVMWw$#rVT4+J?ch3>VU z=85QejwUDj&eXlh2s8&XbVCoq8U~m`0MnuyPoLgNEwB|@-D@FNk3Y;sRZ>Ez;3|f= zR+G`8<}IzP45v)lL;3O$e}PQL!O*bI*tFnBru04-lM*lq6MzBENoA4#%;19u^Wb;I zNDvbydifvT&q|Bl@@2)CmzQN`mwDp&@zbfPHAzu+K0#I^O6K}_c4ztqZ-TO-?G~Mk zkIY2_#D}9=Z;2dGZ~yOk;AkK*!ire8bi}vK%PBl+o1kdKa{L7E^43IGn$jbo*K)3ev#3%!!Zz=p55x*UYavCn9JC8Rt^+BO0W`q>mq9cSB5xaxz zgwB8)`i7Q9*&1dL(_7FtVJhNh??C6HG<3Az~)cY1*!9#iIlFryVPqX2R%j; zM?${Mfiv&^4YR{V90`I>3KGEA=P}J%4~VeVrj$}%iXT8nzA z78V@5kf|f8cOURUM(nov`YPhPz-&sD_mgpsnXTlrFcZV2-riy?7}ksSA)!@+ZKqS_ z?o%5!tTTiOPrzfN&dJdx78b=~Ov9cQVlR_U`?hayf*gq1cH9*^%S;n!eO~eJ>02Q= zAMoi>vfG?2LrwKBHnu1P+NrAg7^}Ue6ct7mRs((Q%##&yv9a@)F1467tE=!GvoicH zM?1cFIdR9#?f(9|M=NCej@J#`YLfYCZAJdqCqX^+N&|v|uG4x$muRbWt0G$?aQwb+ zv4fxQoGXlwkedmh;x>A%=H2-skKbCiY$r`>!MMSDE;RwNsh*x5+@miKgKXgBF zix*dB`t0WM&?!NIeSdwUrIWLB{^Q5-au5;95+oQ>7(-n=jJHkvV_LvCJAJ@k)V9~ZO@mr*gnC59#ARE$JIcbf zY#C$6I2n%t%f%aVH?W{=?IZm5uh?X2YAVTy8hF9drE@fsOpF~{ym#2up?mlwx3vQb zIu5BPRC3tR8?5ofBR0zPOmI z*o6Mh_iFZ*x|)s{rqzwc zfj+9Y)7&Th2(OQIDzTnmwfFqA(IZmV8b-T*p)-acotf&S5D^h^{YP`hsvym1&lc&u zETzt&K{*P31{$9Rct#^C%4>*jcGB&FC>u;osm9u?CV*lR?`XyIA3c&a?sO(VRWe#s z1qaO=qA+Pnj$3dfaem?lx&@(f&CVwzCu;}Xt*Tm2G{}GQr1QMC_(2ish0jGj$&JY- zvHGfirp;IY=;P%vj@I=x;e~1-l2{S$nwan>EN~5I^%uCfOpiZD>(w7SwCudRg^rHa zOEtD2>7k=h${aF!bay@~&%M207Jo~ewFz&2wYRBY#1R>ES@3^&3o3(#AuB(A{`_af zDKZzYml-?)M!c=Q^f^kWzn}_srCIi=;~7-;6aj)o_c412u)`NmDoUVwA}_Zu|B&%t zFJ3AlL}g;6n4kb}QCr6UWWy_Y( zX4m-mLg&Lf>jw3|!g@IR0J(g<8@?jo8+hjFw8)XNs6ljoZ~>n`FJ;`{5LjF23X$Bh z#)8+Vk3R>CCYoKZAe>V$i?MNF(KXyy=qqWzJQrsh>2_KL{|m&+vOnKf3+?BDYhj1A z)mRPDK&<7aRirLra(fCbf(}KW3rkjM&EsBFP9n9+usiie3_TJV27{#cZQImJ$pYgm z1Kw&^jm?FBpmdm+a$`n`A>kZA;RQG!(2K9~%ImS$hkWA!h%q2EyC9Yt$|qA}{_S0e?E-j!Oi%IRcjhj1 zeYvJNv{OqY#wP+ipMk81M+%Ajk4}8aV}Ho`R;NHB=y>ANi}<$+FpPj^6Hgip8y3zD z8pJ|1%HZw$_D%D#c|T4GVh%}S1SN|;x>ciFcL-1R%*ppD7n42Wl`Ovl4FXi%1k;F9fUok6$3UFe>hgXMzjn3r6;DVDT?H=%5(|uR6-Xmdzyl_nRP(#X^xhSnR#fG-DzN77hJ- z1{Xw=&A8SBlJLr4TLO~QW*``aKy?QuG*|qF+l92xqc^O)_;QAdy0U^)QXFy+xj~-w zn`xt@6P1(;p(aMMln9il<2l(V&{qZ4JODG7A@L-`sN=_V32XmydE_byPe%3>{mH0N zqhtXJ{#$q3ZhyMk;K+;T%ZC~@-Ql5eE3i}V-n|=9CexXth;#lsxS=ORGD))~Spx2$ z_Pj>5?VE<9f5Mre;oa{9tGwF7zGv)Ku39AniF{yV+6p>Y#Y;!I0ub1|`L+ZhC(4eA z^PJ%0eA(~mb0VBu1Fn(zsTON&N=0wE@V7-`rnE$6)mbOU8&)R5HnQOln&sJ-kofltmW^`o|z1GEDfW zzXDA%Vd!Ejzw=TVTX$mERVK0lrtnN}x(jlV+LC$kfopng-emKGc*WBux{sv#=sR-c ztU-SJ{QXsweOY|BbM!lECex3jzzFAlZa$Q9j7d&38M1MP)H!aVUqpDgH^W9Ck0f`s zPJYOOB=rM6S?un>PT%_1_q6|__r z3^(LWe1ylGNViBszoWlO-T7CqvA5-);blor{2s2JquP<2jF-$_?3{qN4b=h}dc2J> zr(nlm8sqD~P1!a8WN?>Em{QTGl+W_2?Uu^B>Z_xZ$8ki@(1wIxWgPdmPx6HUzxF9F z&GrR_8;!M>VBz50vP@)v^#ulgXi0^U<)86!OO}sWZWr_Ckc~$oPRMYM*y`nb*3P14 zXrCViZMY;zVN}rdb;x$4=Hi>H137b1!}q7OUO{yAs4nRoZ3OVA-8x1k;1-!wz7|29xS;yk@PIYy4 zC==oz{h&=jcpJX{nu=eR)bT(XSf9>4S*D{T^GOszq!cB>gEQ2rM$nw>C#yb{mWD6B zs~cz{mhuAlLD2@981p3D+}wD2S2NGF$v(B7hE&)NT2Y=Fb+_b6t*^QKS*CnQLkg{0 z9f4Gqmw!JZ?ADnVSkFF4;sdQ&*IRJPJXyjnxA0 zy8+z?%*x>BYH4Ya%6VOWunBzRx;|&@%vO-iFloJ)^pk!FoRC^@}n8#$@N_Cf|;l@oLHJ{A=wn9eW#hCrln4N%W>s4f6E(~aU?!|`iJh76{R!e ztkNBc1Nx$jNAK(xD=J%6A1jJ$t`V}6KAD)uU{yDM4{cTiJm@(bM-SFgw*>QSG@vxS)GLMlBQ-6-`L1w{M$igp>>o`NeuG zgyW*Wpz33KeJ`9>$}DpLO6I+1p8qHE(Rbcp4}8+DqftTdp(rjs*u*-EeEUQGgvC$F ziZUE}>*BD$+(~po!i-OA!E!`)PNqRKdObhi>e~Ze`vA`90>ZVZZK%jdvi)t3+E`oT z+*LxD@Y-AO;>8?(sw~`0PEH0gI*KvS`nB(hi(BRSQhFZw@Z9bF`3F0QIs$uxp72zW zVRi!dpn09~>8twS!GV$r`2%&G;(xWZksK8nrxERBc(^#J^NJH+*)Mi-%A_@mO&1+B zJi67zD`RxjqL@Z^1k)XYJQbycSzrRm2979)_=Owa#uWX~)K_5L6b{OC+EBXw#%jPE zjrjv5vl$g;KzR6MYQ~z}sF`CrynmlEyBlY!9@XlTNO8_NF;OkdZYv)Do1 zkUFm6?`>ThrX>D^N-6SXX7I>~6LVektB3SYH*!**-|%p8&5|tTkE^1j_5fRW-OO6$ z!Gi}9F+~8%73P)FZcC|XW@bhu{oZ@^Fd$PY`qecx!%RKlKTjI9D2Ri5GirCQ^uveV zfhL&7SftpU=EOV%DKfg(7HJigR=7!je(G)NCptNivhm*_M_#O4w!ATKl&0bh#YOAx z!vlat%}rZ_(B>6e&A|MC$t2l`Yv!M5K4pqC;ZLMJNUi(y>nGa(HSz$hF6ANaT7Uhje5Y<^Z&4mdk<-d0MS zH^_vjgON%ltmw}10MtP4--?_!VcN8|gcwf1PG_i?{fL zirjjiY069sw!Gh;*8q1dO$iV}Un*b@Bllq{;FBN~u)9D@UFgBpl}(c}BB9Xosjm=) zbEH~6J-@scN2FnLYB+yGl>uhbdhdSyyeZ%Cs+a6%Ppj#uz(=1eZuk%u z-&_XHfdR#Bl>sG_x-C3qTDqGogaR8)WrCUTkco0+*6YMvKK5I7`_UqNd!Cb<`-Zky z9J)Y=gW#QM@CR31>eJW8PdQ>@oKdqwn^gBE?cM10B>&iqfmFE@X_jg8`)XOC8Jdk`tCUmrrcDDt$6@c%q@8Ce|3h z^%^DpMqHfpfhUnrWHgBZ!NE8F{dX%#M(QOn65kU&BMu%^dY17OWX2!Qq`*SX;hxIO$4*G}zajdj-y8MOql3Nx2;p5D$At5S&J$9eZ6;Z^X1em{I zL7%D-9wIQ2@)2GPQjW=ccEI?Nv@nMTrr6ExYp1NdJvCLIIk#wfn*RO!2ZV%Vg4JW= zaD>w=tGQ54wo=f?u10ieF%y+ApSeqkpZjRK2gJO%2O!$vikyC0LMW! zQ(QuM_qH9O)WVlEBT^5qdY>pv{aK18o}%cE>>}4tMa-%I|!JenWcf-3gUTBg<)wI7ySD19E8U;n8Bao@ac!Ps3N~a7l=?$P=ur0_jkIKc{~lzXOei zOz66IMKl}^=(TM{O;wdNG5nm^2bv3nFFI3zA!@DKeN#T0jEOc)O{;mX@r+S@7=?E*5*0_tI2^3}0`@vjN0^%AA@Qcra)Xs`o8w zYpx>bYp2m$YHX{b!#ZwyF)sC1-Hm-`?bMZrX!No88nRr4_&G1SLl%|b$0w(Xrsc0; z#hFM3xs_JMrPACH%A8OB?6`gk<;Nhb3h{dtdWUSeh#@YGe^!}>KA~V_A+?>;npFZi z&YY>@IzdJz#OQ*0#P8AP$gx`@NCAW0-xveJPuE;&X=^mqH2d~#Cq^iTV~X9$54~&_ zhV7u)AzEtX}nwFn0X(u;#NIEt(?A{ci zzF48ajm%QMO2Nf`#3>{XD?7W6hx6{}MO@g@@I08Z3WkfLFRmh-Y6=~%o@@8Lz4-fk zY1_zy4SN-xt=2P%$pwB3BZl_m!lQs4GOG^C$W(S%#+c);GkS#XOjRD&16G{K&B%%M z$>1x62WHHv@EKpb{Qh(-nVXaTabi#%cjj;tv6H5q?DSxssk$<8gf#DP;Mfeh5DkzZ zuqG)qC7EEQL1xff*)E|GC8=DGnOmHvPW=lMVxaNxEXTnNjxeFz>GBtpNUvVMz6KZo z;n-)?sDtFZA82%Bdk}1_nR-xBXkY41h<*{|5n9D<4})XSimX#jNI&iAityQ*|#{dN( z?$8@zY1?jweRndPfOS5V`W!Nf(NxDQ#p2>((6vE)y(46}Cec3>t8*{4G%YFW)6nun z;;1uLIT`Jz+uG^|6?YsBh%MYE@-JpU+iGaUtqd;Ztjd-XuDDWCdp)oW>&TQ5bDYM5?naH?kUIa_JQV;`?D?GNLrU)cb1JjpkHBf#EuH`- zGI~E6Ng9K@edoAzuA|DQ8*SSGtVZN+c0S~$i)2~5+zL$0dUhdQHzI&evu8i|U7k10 z1fuEs^_X^Azfpw?g@n(W^Q?O?ChHN9Q5rf!Vl`16YGAMsUlNT^mzX!AT;A+s_crG9 z4wNUx_!AHt2D(2NG(d(@X*KXxk@2j!!-xESbnO^eRH?IM=WJ9~fHQBAQ^Bj8HhCi& z9EkMwEH0z>W8gMQJRQo?cpvv+F|c5n^`VXyMy6R&pYzm_BFdDqe~(eqldpCnT`)d8 z^XkT-4Kv-CJrzc}Y?T0+AEZt%%;tl@MEgPfPk#*9tQ6I^A3D5P#U+8v>)@u9neIzsVfVy%=y4bKUxqDmFof;$w(CA(9yW z>tfWreDmUgJ}r7#7i+IxHK)Cw(A}tW99+)th>?k4Y6&(+%Nn*@*nlCsk+wVA)L?j* zf}OqkD2-c~d--^)R;^wUNRgieL`L2LmlV+}je0Euds*?VI<5|6N_Ki-lT(d^3G~n= zDc_=5FOL=aML|C!v)Q)ucB?yfeZOUaZRC3KXM!)|YjciY z2Zn^8kD6CsK5UA0Gz6vO@ zh_);1AEn~pClDFb+Kr26cyxn^;%HdfMw3*B%81($pCUc*Yf0wEIO~D~d3Fb$FR-C`^ zylhP6mu$Y2ZRN5@@isKQ+Jfoo0KS$WW*XHkQR%AooUQCkAZ-2;x|Hv2kkISR7Pmx zXeb-8u3g!Cs-g^03PM7S?K@YKR)$Ziv>`w4>}3!jsWlmP<2K#LkD)WS|ykq9E1yTD(+nqZzyXd&CHrQoXpJxf*6ja4~)(B zMGo5@Tl3Z+CpM?rUW~H#SoZkQTHn<+W=E zB2JEy@3K-vcUSMPLZI~;ofx>Cw^*66R;8C);X$0K$b?3>mj3e(tn}vg&q|vsOeD*X zuXq1YRwi0K5i*}z*>&ZZ;a|NqV|1SN91yT1#OY_-hN906pbz9|poUvi54>|_8jSD< z12fPta~nJKvr%f;<)!n>d0VUDHg{tW_1eaG5BO}>#$7F1wtUMhAleiJowDlN`qV8( zzj^IqZ7y&_@ks5i3bjT4qScII1!6zmzt`TqQ=^}tOB+rZ${~fiG^^V>!N^Gd92KK{ zAz}0f@2Q!+7Z~5|V65sRo)0J%6hhBZJ_uZf-WkV9Ea@6o7yMzxjMD)0xoxM}SU>|Z z=cI1oas^kbebm;dlEqIPB|Yv>vG*r_+hi0G9K3^yh-(V0*q&>CZGh~xkNfM5%6umE zq;-4bw4WYTp;wjoTzp9r75T@aDa%N*MLv~nE~)ty5;X`SIf~EqsHm2 z+2nUab;n`j^m;#H$^utcQ*I%pzLe2~qRYUL`${LpDra#(Z)1AB`UWpuf zBl<7OY=XB*cy#cfjGnWi*EIQ=x6#n-zK#$uydStIsEFnar%35U!KxOxo3SKd0`ca| zp#=l?YN<5jTMw(G=P!DMu7z7heL$o$DD^J*NuC`&~7_)~h8WJal&(wVfQpa-g zNHQl2s4lELuS24>M@{c#vrJ}cDgF_2&ObW4e~$JtZQC53@e|L!BK85@O95>1I2g`~ z>QU}9h@Z$=IpG*QsQ@YNEaBH0)AD`93S8=5Vj{FW_1Xp%hmz&@%Ij4{aZdZQ5XFYZ zfN*{mA4Dn>FjZ^!D~>5$xO_sTrEk9YZSzF6Z4ER2(8)GPrg9*t!ep|A)U1Fe*ZAZ12LEM=aZ`PjDFGS}Dm%<-T}d8bF!Rz6?eUq?r#F`1AcFt(&_ z*GjcUu1}xPdAAE-7blb|Xz#^7;FWae@d;x|d)XlT=t4&5-DRID!a!`<< zD2q)Xs~|R0NMpU z14!XC)^y4_YoVLbv4X`;&W)|URe#e`r|`IxlSmo}^zZ=jNU&%$djf8O2XM_s^j3sg5YY+V%- zQA$pHlBPy?3kupbT(R|?$$Pqb(fmW*0Czy%ZB0sYJ)rr<^KWR;)AjVLqB=BEd&JGfr==BnwV#1O2W08=qSO!5Qhv|Y?PS0&BbXae zz7j+o$rqGu&3O`eH|{OHq-vSG`RI_O+#(-F7a(VD4$P>vjxYI9UVZ^b11d7vBP}fO zvrkfo;Bf)!cA=(ESwi;e`q_U*SZwCA@`o`qx~13LQDza#p?5@XOGwi`bchg}BlR;` zfn$A?KF7LX=c1^$2j1AGe6ll~9XI=7#2oY)jBFdA373Be#CQSX1BnbmAp?$qwVoQv zb^D7eHOOM*(kOU}=za(G@&j^VUvaI~$(U!LAw z{D6pG7y^Xyv^#gr)JifE0S5&!azxz}XSO_f^VgBEm7oZexd1{aJWP|~86m##Yt zCQ{7)o8#r>m9pqw&ydhi`z!0+4+KT}?wF|?rnY2a`wPn(t`ZNrcI^tBJ!SpLBaw4d zeAPBKx3sl2CN|Pwpxx#k#`4^y0|3iI#bLx;-p+;rRqK$Ne*W)rxcC+MJ&i{^i8C9z z2ZYSBg=6=|JJ-tIKI!#f`;0S2G*~{^!Z5?f*RVuA*rIipe@U&)w=6fs`QDLqE@i)r zEsMjE+K{67b%miUFG~-5kDD)IBUH^wiMab4Ta<4IxOy36bM1f@MONpj6l5#oQX$ z;T!v~m=hB3)RYrh$UEl`H9BgvtYcpLuGe#x;N^gPRUi#SdG{YYU<;HYntI?8?onF? zOk@o@OnyhLyCk_z|MoL^spA+FF+5 zbt0~M-S$^r%(awu@LEAblQ*V@9G||Gs@~ zc3;>s?G2gA($0|nTZYz4(ZOk5;IO4GOk1Rb#IUw2Ee!$G6A@4B{50ORodbb734vpLr?U=U+zWU#6|b$x6hCvAp||K zriKml?UDLhmC~eyYKIl_Uzh*(Z}Q_4dNzYil}nSlF~&OCqppI<=z)=gXmG?su_ucV znWmNzPaY9)-Vel76oKBeS}uE>-mY$$%}by!xr!9fuj#xCs`a5S`OX{^ zR`x1GlIZ^EefNCPiC1bfm8pQ;SFbMSr%+sgw8ZtQd0C`J$K)_0O6{cC_x2&q6YVRU znZlIlZ5@i1X^x<-@bpCy{tH&rHeXkF)N_TN^2lSkG3Av@eKzEk%qwkB{q(%BFm(9t zVy11NN1K<;b?;cw%Mj)gAWSDeq+wC?k)tA36>BX<*RiZdrR)2vk*vnR5IV)4b515rn8i0k561+Oo2 zvSEX;RM^JxM~7nn;VdNjY5eEKbDhg*50y>nPbf5>iRGU+Cv>5+v&QIfm@>|j-_I+2 zI(03rB;zHio=s#3gwkl-|KaJq<9goz|9_(#m64|1&@NK;Oeq>@C?z9O)^Y3=Dk4-y z6Il&~>}0Ph*d)ACLRE-EX(sy=rk?8`~Y> zr7OP#L=|mXWL&h4siu&xDM`fViug|f)Kk1iIOY{qRZe_mx|Lt%_2UNk-%T4@+}F`$ zvh#7D>1IW@&u!4S{OE3A`G( z4qN`w^7{1=LXhV%Itz9%tQRGR4Xf(Bbo2QLpo=vp3lI4C#tt5m-}3mmU`GfJ1G9&@ zf85iybBv=QG`h>Yt_MgqvWpkIyC26}evThDf&71jq2RU)Ei8o{?CM(NJ|@6L7>pnb z1;xc`u;v)qj-1}(J*8tM4ThjvxTwtezm4)myw>cToP>wEG}PRSJ3g6x;@W8UyHHb; zKdfY*P!MJAfmlgce8;AZ6c!&?Wzn**9Z1^1!7_=tdBf+Re547`@7h%z)>lWnuysf< z7$Zg=%YoHXNfn7xipml(W!mL;>k&EUD8VMYPZ}&9tIdbb8*LA7Q-9gEL#x>zf`8h@ zYkWQIh>p%NOCVpsRv9Ewp9t%E$dD!!tV5X=2p&j>#~9+r$zeG?_W2yYub0ly8)Po> zYec3!qZg=6yum)pes<-^>bChK&20B4hv)Y{G(NF|fJv?L` zI~@PWv{-=q&jBwh5$Bs$O6AwWt} zE7RQIPugmq4;L!&sK&2WP@b9mis$dg(zp8iN?#U^xM^!UtgUT>gcVDG{Q$r^IjTEc zSe>&xXy5+*n&5YcePI-VH8xqW;G6B9-gQm=_gd85_gSlOTc%ROE&7#dJ$3}FpZ3gc zQ9rvL_pN5)Mc5Y)qt(vP0i|ZUQp$$yc^i%sAW5@54WT$9>%zva30}85`!-)~GQeLKmIt z=YFpgPDK;wQ5XnIE-wJ-!0DNHB{uuw!UU1;%FeS8v7*S46P#EM)eSp_F)xlXMKm(c zs*Fpp)3kf*uho9@_my9M|5{~hH1PeD88>r#2pAnLGCm|r`FHMU62NKYX(YrDO%@o^ z`O@*AGImKG@UFfE-@Jl~k#A-3wVuiiBPm0na)W0M`1AXBDXeRUt-F}`Vv;WeIXI#+1IWAP5384aFb{`7$`W~}p!3ok zKzg2yeH<8^(l&7^SM|BeVRCV4&SWHW*a5mYIIC)CoG=L+9^GHZ@y@@P-t$pZL%O}J zs*+R3mPr@TEqS)wHRHj%EkaL*)T-Z(cQ#u0@iFj28){0Aks~K@{_@^Rs|}5rY8-r* z4lIaDlP?GvB#-=KQC|`4$S-RX)^V-z`tTV=?L3CJz&gK~kB^Ty!%!=1QCQw{2A){ru&e#(8r!+ih*bXRT(C+!lVtRuY9v8w1$16@70{=l|?JSCS zJZ{WSSZrasz|;2_HA=Q134(>C04>z%xVnyZktZA)d3|ozsYzV3_30@!e~%o!aQs=5 z*KHOoSP(u{VPS4=!=eXiizsTT%iO z76(7#ny_XW&EUrKth(Aopd)S)MN;OFvO3MF_+{|m=`W6#bx({J+!9LZmi{5OpnO&= z9pIugUD-(4^eV@F(#)AHUQFp3K-o$}7I$H!dG3U?nEuIZMc0}3^zo6218ugFykQ)A z{egkJl9op7R*7_6k5*0QNYxI1G~=#zyLK_8DQHe`D$t#hWZ~GbfJ5l@tU@G2$}oYr z>-4nQ;w4LLQHjyuvTx8bC~IVU)RRQ3XIyyBn3ykFP2=#chMEgftVyoNZo$}9U z?-pkRdLW(B*A|wRU>A>@rHtnHJ7{OpC_41W!Mww6*g9CpESffil0~05 z=U2;sz^b>tug?~(P0coodv_pc;_LTFC0Hf_QK^_D6n^TPRi{oXGc%2az})e^MwFvm zM6e19u}AhS4$Cmj{UUaJztSRO>2H8RVrp7E>5vJ%J{^h zDPa`+irEh$O?9?Y5c@#K>8UG$GglZDu-jOape4_Lo{2NLRejSqR&eP7umN(&$O|38rMR)v#)^LMk}@ z##UAb9-9wSDDhX7kG5{#ei+al$Am|%PW1Nj5;c|JL?Ezmt{uM=d~e$APK>~J z&{T8<78w=5DHD*x(QI10*e~2-Ikn_?UUw#6mj2iaT9SFpu85vbWh6z34}uJRByn*= z7kBsnicna*eUZX z?|LqkmBD1h`v~)yZaqG~bTiyhPY@=FbK;Qly^UfGv1-@BgTq19EsrE?Ft-p!$QJYk z_@q~vY=S6&dFEM%!bMKm0HyST1+(O<*m1}4hqtlrytDMU#T>s~ z7vp4ES=H}9;vS429F)L|w9BGx;8!t?KjGIr$VIFQfu<1)ohdWBL3(vv(7fIpIbkaz zJ(aj{NFfDq^qL+nE-t2ea%ZGYcHq4kQc8iVf^M-Z(&fQ z+st1nt6d#_*{zdZZF&QT;bKEsE^B{)CFa$Bh#hd-(Bc1;|Q7^{m;oT{5Da1QJz2gA>e=I%rg1W`rYVg~uIU%y^9 z9dZg}iz}j-#HFgE$S^-XjI00oyd@$s&f;pVYF9V6grmJ(hYxqM(t-QhiI%to1*dSY z-$lhIB%riet=_FS96OSR$L{H)VX1S_O^0PQpKm^<>dP3dV2!a8RPI0}B!Kx$wZqXY znT`uPcUh&2Q^A6$6lj4%`QF?Z9F|oZcY@U;I0qw+Qp$LPyB()WXfbqO*MNVDYRB_GnB}*@-86FG+5YfCWvK%LPZ2nJ`}jyx5Lf5~ zHx=L>FcPNeFd#rVAmFoNEXYUAneo8(z<~owPFaETg_j3em*B0%2U!<@o8veUO z`}Tycy?gg+_31HwxtJ2YyZ`ylp6|vQDsZMKXw`fQ&?DN{H2(D@3ht}aMQHwz%}W@{ zn{|r93`$%Jin;FHyGNJh!B_)071McM#*{NFY?em&SnfGjyj;#^69(ZVraqy+yTh3f zV-xBs*|H^u&x|(^z4^x_MX=QZ1)A%2)jHn_Qls#I!s~D8jTg9!=APlv+-DaX3S)zi zQ`G&wfF-O-8$q0-6rREjBLK7mv*6*$RGV=(FMySMfxKC9rJ`J9Wl$?V4MGDF+|abU zbLPNAqZnIBxn=_wsY#3W;$N9zvLoiQPzzjK(tyjj-BK>1q!>>8z(HSzWAu34=w~j? zJ9a=O1)#!kUgxkbV#K+%MZJzF?CSjHnC-v!ng`Zr;k(xSnqXoDe6+btk0>ceV}?lh zq>B?K$jg7~b2wq+zr}bJmF)V1?T8&V1 zwPOnp#)ta#_@FDm0?FD1B0S%Sp^~gO;tQGeaM`wbv#EDy3diJri)NnQzX>c?&_h}> z?+G7k!!e1PE65XDGkCNaGp0rl=7=(NF}u6@+faiz=TCT1QD{oY($W$g4wNCJp=o75 z)~sG#Nx4pQ4Re~c7fmMEfNaN)%Wb)Tq=qd+6tEn3^b0@EP=rL@e1ydrXST!D@d zI}yMY4}Yp)`X+n7AwR{;Hy2$e80lnCU14AX&WI8fKm~$0IdAs!g63!eU`dY@ zLPH9{{QLLC2S&s627eG#+x_%~ZA>ibjJ-Nn14SBWgTbWj+b13+)1IE|BaTx(K1qyI z#M0`|_k;Su=BLcN90{^?+kENClMXNe;AfSv&FkSq|5(pDkFhf{Tf+5x6uWh65p@?Q zEuAleD|;k2MpU14eiAWS+oa!rGsHgV5m&l6@!Y4wgI3_~Y7;UY&F)nFJEf&kpa7AI zp9FJbU6;AEIW{<}5*$$>NpNJW0mt+u0D}0sfm*1&2k_k}IbrkW%^v5ad8w|h4xa9b z6&?zye1aDS`$iNYgCQ#enQCJ4O`LQcS14&8DwH6UkUKF4q;$K24;4GQj0l*Nr0VMG zXw)tg2Cg{aJ$Uec?J*RH<94#N6cc+&a^C;vS1I9AOOWpK+y2?*Xz{mt{GRQzZWzSr z$Gu2drRF`kYW-}yD$GIOcY{ZQL%0n;@&R=|B3BRPtJzjA}dj-oM{h@;HYyq4Xmwi<=pyw!0t=z@}NGB>54yx)+z<~sFWO9(!%2Q z)7G_{Qf|I@^{S9dIqlJjgA;lg$2lWVH?Xp5#$j;C7>K%pD9F-Ufl!Kljz6Z-6pb?z z;Hsx~<(>NVYezpJGEUC9+qs4e&n}gg*6b-i5JrMyG^pOO;|Pv7-LC{E2h-gL?%Hx; z1%$x{hRqddKTV*+P-Oz2=<@o&siiie_kr8l>E8#Zi4q83B{fl(-KHO+%^Edxk?K{& z0N7QkG~D*4?I{VUU0#>x+EI`=8EK&ME`r%>V{2=XIPIT_6E6WN6t(Y(UUe{kRA`Q3 zxB2)~9Q}&U*>l*B&yy6~ZdC@D;W5)-nnKsrFix&DWFx+_r6Qq)qw} z0ee0|cils+*l3QG{&KEY@V*8^9UYG>`8HiVSx6?b$~msE`c`bUw@HM@ZCgR{@GoNgQE6s3zrPsZAz;%qR(Vu}N z`aGx>tH6(4$35nZc#a%tS@!!Z3S4H{K;|2lFK@t9r8S!-#cY_fAU-lAHr~XF?Cd#N zQN7Dgv@OK*oWd(}lO1wUt~3;y_~Xmq++I(yOW^{3VQJm}+#bl@c4Xfx7u>CMG?CB) z4f0K(ZK!D;V;~a56e(#HK3J+g{V_hID8mZKaLkA(nXE*+6nwco@=camx8L_VYHyg0 z=%@;2+a6#Cj`2ilg=S$)9aeF&5~mHIB_SZmb}d@Mh!rdBqb|1+ni32Z%z8z3!k8L# z*U2zWggdBX-R{kJG46!wkMoW9?mOV{e93~TnJyS=l z(}oynV5#N?^fe9F6%^~4CeIQb&A?KH7>41)pz-5(^6hOg%<%fF22TPXGmW3&=EY~@ zJ?eE0K@P|cB5~pj1N~LfX+RF?NI}e)(&&ZlW@U;ZB=cv=x<`fgP)*M((sc0~C1PRe zyGMIcLf|no2m2xdoY~Jgs9Xfy&I*>^4xYC7*O)kCjVT&aMlB6$tUdU!lSqZeEm$!9 zVm5WUkZi#vlv>{Sn9ZCEEW$Tve4iI5`y!IR3XCG#fY7pdEwSYxQsERmp1Y>jK8rqu z_fjDVBr;T7BejW(Fk5Ew?-b+Ft z#xsbt5c79{%2xHchGH@+=@Zt`WfWobx3N2SZa{HO@e)LrYFxh%4q-9Z1>o5H^E|kh za`q?+9TwQI`G~bN^3dxrary+#L16-rIyw2acZPEi8)KXuH-yY8AS^Q zx9w>wo--^GYAT~8k*pbvX#o=qp1MKOoVt(EJSj}da^^NyN>m1^%GkZz7BZg3=B0Fi zLOQ2#M_dpA*HrZ|Bn%r;I5n8s=z1BufH37?)JA?A42FoR`yzw_g1GrX9}r(K$t%Uh zF@%#ZJibkf^K5(dD#RwtZwNMzXrp14I6!x!w-tRZPjbTFe~($)`w8PP`WLo|k9iZu zd6r^Rs##P^$T*fm^9D*z>>F}xdmouZ%OGXp!V_JiMx*nE=XY-%_s*-sWXZtzuVwL(PBZ-6NJy%L zdImHO?(XjUj{g%BCHH|8}LO@)^IXdfylCm<(wgj9K zB>)}0Qxm;qZd(AIuJbkSvw7jP=_3YP0t|6tF2g|qPq6oW%b^3H@btBQ)SV~xhvYno zvY$H8rTICnVa~bS8+y5_F|TU_`kf&-BhTWg8ZKC;n>uLG1!f8~I?9!;J9cdG;^e6@ ztXpG)3;`O%@6(>RLn04C%}T6;k}?G*4svcxX<`D$JPa1w3zAFfko{eZhcxna-2J6I zLJ>A8Lot_O494n~i&JH(CNldupDUe&H2^#nW@cM*<3{t&oewIS+NvO5@y3fUyl>h& z5DbgiaXkIzU!5!d)lkDdGI07I%%KCo?5)SZ-qq2~FZcOAO{@ zM^oxBd>xMOC9}#2=ruB5&ecs#t*a%rQum2-ow!Ew6&#fHEiKhjuUd@7e_OciNghCU zTbR2CPM$o30}VH^kGNkFV!eXEAQOm=NxVSqwy`cFMzGa6mj3Sxx>fPx!MGbxN4xu0 zuF92BZWM}uL*|Yq2IYU3T)NaSJUpDkRdVkhmrEG_8gMEIhe96@2*|yz8-!0>tP1Jy z#Eb`dbciUsBIj=nulu&y`(HTzJ87$AV;q>ZaL&+Or}2a`GBUbODrhE5NZ4V}2 zEoHi41|)(w%gN9R@zcUP5)_eQ7#^{u9L})waZ^@bJBa`z@&`B_gz>5uBp4yFxn-n=<$LoB;5_H6I%?JZ=#J4a~~CUe*E z25H5dg1~~AiFmm>pIt9gZXUtdQ&^h*k4DFNDkXtYN{gsuFLMl#5DaV*g(G}__01bM zs$^nKBa2Dz7Fvd*_|+R)kEb>69KXsw%xeg_FuPh8Lse_M; zM2C9O$s|W>i^{F!ZbKK#e6x4ozUf(6E_5kq>@{Z$;;9QJV$w(P^Z7=v%r;CE9-mnd zLm41^8tlDg2{V7FYWj+*sw$PFH1JzNZp4Zi;~T2+#Oe0%d?BdnXJ#j{dF}cuuJT$6 zt4}9I#X%W^E-?^uR}Q@>cL)-)E|G*vNwDU`iJmmj_9I6ofM;ie(-9f2qg8g@A~a4jpa~Q;-9QU76F%GlRo?aNPbZcs$Sn^M!*;v%6BzmXwXx5p}G zLU_AUT6#3^d)F&zR&5Uh=HjPjnX!QcC9@G~L2&4NYC#IyR5XOnMwOgxK|Xb(BJ8(A zlakH!`$ipf_4C_O=44J6BjOmE9#j{vALN({4~9Sk>Pnxq8gdn{Li|eksif%@lFp9} zkBK1i@NBKT=g5GXU;^PX8a!2BCq`-uU^vLajEB)*`FMOT!62W*`?N1OIJw^*c(c<>OJ{B``%3|-`m-=1RYtR=mD~P46PNG=rijL3r zN=&^O5M?yB7=neOMy4xe*+?5EGoluNl@U4rBJqKgxCTot$;KUKDN8BGg9{|a!9`W4 z;QK!at zhC^bn!oOSm=~+XrY~<4v+!m;VB&sn({7*A#i*EfB>6f{eh}!W|NJZiy)Kz*hDkTR- zA;rf&K6(6D_99@VlsAuhUJ5SeeE>7cxrG=`H$C`d|Iwh#OLU3$JCPL2ogX){NCBZz0{bS+fbMu z5L!|npoOoXx`nIFJ}!5{w#kB5XIZjJCoe=}2HKZko|ZTvKiNe6cZbObS(4)*C_em5 zv6rWO6Rj!=?-wNIh-c?}^J0NzN2W&>k)+sR6+g&|ku%R{B8#O(gRT+9_`$*F#-B@9Y9WFCS3WqB^TG4+pbwEO@^=QfPVZ-ttKi)3z8-yXiM_B-x`S1aE z*Q-M#s%lP#`SG0*n|^>tMX!rh5)mphZ>oP8f@a-=D$gqDov8zAN3}DFa~2a8{-Ti6 zsF(F~ACB#+1U_-rA$%p_N!WJYo#}KLaJ1zb)EZO|YY1t+x59S&vs2x@a^__n(jThk zV{EeUZwESB*?=yx7O1PTR~8Z{##yBfZ?7TVr;KFMrox^v2aQOoduepYO|*kD*{4`b zMG8RiA@wH;HR+dlo&r36J39c62x`qhMyE~-mr#+D+eSp)?Gu}_>pX^K+>2Gwr?Rtc zSYfH&)IT?@PNsi+Eh!CvBYB9Bh)k@khOIqw9$b#2yN4SLVq5~-Ko)TX1<#`^;2{A5 z<#;VP4lXKl4#d{XXS!$^!_yVep2~3O@ZksjZapB>vQ{t2VO$z0G?5@CWrP`UY;rlxyx-*>B@nV+9ebdWO|{;;o_?Y`XOML%_9SsW)nZ~i;ZFRQSK zFa09BxCUnXecJaHA{7d?3bGd>h-Ua7abcWM36<7gh+RAqDQuf=V(Hhx*D-~VZ$)_|+}aUQ)) zS6iiQJ2hi`6m=FYgXl6q;7~U?hyoe0B2}UY9~fP`1pgCW_dAImStuXGB;j*2AxV8};YboMs6&f?esdxzmO4g&0)T86#JmbnUFZx$MYPYSF=(?IjjR^rQJp1#| zaSQ36dWzQ*n2s|S@p{OBbvT1+F3JRE&du}&j_o}}6>~G$#X+lpXchFYp(wMN+@^xB zF&YqBoD}C&Rb(94L47hurO@_ZTv{_SBFNF%=$F#b1`4|#&W`5-8`m6rRns@8#lz(o zVoGviKX`U+rwxNyTSsabSV&k@c09wS1|<==D@R}9#+E~ujnoIRN#~l z4@xO9Xt}HZ-LH!sP?wt83#2F^>Jov)N=Y+$RqgcMXdgIBS0FlGy*F5Q>JH0jBwVsW z1WA@qCy4=>8rAS9^;(qEcjOfm?9Oj@-c@UeG55h94^51AU@hLpX#$N7yi(a$M#QL_ zl=qSnqLr>LCHjE+xLbevi8hy~;j#PbrK1dieVnKM>_~|$qh>f?vzg_~)?5N=%yk_F zHf_v_q`QS5LwU232P;|N!m?y&H1ey&{_xl}z{V`!!yWmYg1(eJw>Q$bjbkUHfwcgG zOi?MY)e7&Sh>KL+fQlq4;T%W`$rCrVV$sQ&yq-6AE^);Gi==k#wgnn%fKUUsuLXJ8 zy!HM_|2r9g_Tp#6=tLY!DZnG|!G0DAB$FChFDhz-vWo7o>VyVN#@QQ?dm-^(%@@AE zgzm(!M_58MmI9`g=UO{A2iG)JA4mYq`kr(4?9w=shYUTat&+Bmk}u2QryPS*wC8HB z4}Sg-^vfh{o*M=3%6*tUe?CUOt4T91?=|r?Ans4Sd!P+DS!btpY*P`efcMdS z3D87x+e6<-EeIHNQLO#fSIiIjnSA5q(}sy{$M}9)vLa;uiZ)*v{sZ~QC1RAiT6$!P zULxR1ZiXi%_wrdQg!nVS?Kg?&^Ofx3T}pnSx!y7|^aMukF|> zs?E8Ck(X;X-t+o>SY=$h=Xh)Y1A&LIf(y5wlZKCMAkiZD^g5+)J^H8;RLCsH?ev%o zI-MC*;B;gO3l_X!zr)D4zCN2Tu==XH;?m-lLRhuoKr1el^Z#LxvA; z9_Q>G)Z;ZyL{1~R>qd$y{=k8Cq;fz#%eifU?ZJX?NPLQpj<-$HiE@-Rt5h6JZV^9q zwpIH*h6fKTqh-ZQU|da36;gr~8#iw3di(=oVM60nHj*N!nn3RZL+G#zn8zG2Uc^)Y#3v7q3h2+vcG_+1*Rx~+y5CC~(@7uFf7C?|@4jxPp z#^ZE@@ItcFl|_xno0oe62q>V!+_O_gD(ml#}%-((l;kOiln)Jb-SF0xG zfP%zs-@cBfi`O_POnLO+!SW`%O)JgNxHShIDC1A@bkni&yGR`!)8QFzGF^D8)+ee0 zG#E#A1#7q&3?!s)WR&6E9J3{S&myT9{pWj*FhAq9C+(5P9N+VidQ)O0da6|-rJv}6ju~a z{)x%_8c=d#NKdz+^9vRib;ZPMTtg?IG z^&ySW-I14}V3;Rr*LJ3INajx?X<_1G1I(v!^0ZO&;D$UP`Bl{ALO3T?Que>m_-nUo z9xqRLAuK?QT~ZGxO^7~dn$-S;5uAlvNue`|A(>BgL~Uqy{F#J_&lHx|L}-)b%&lHe zwBc4SUc8v`lh2!avx_`79#%^!Yrgds1e;GN9$_U%`G4U3!mO*EyU0*XB>66?tyYn$ zQIPcJ?vSCxkm1OtPFMG4HnG({Vx6$o)3sT;UPB>v0B6X9q&8jUIvpqzZZ8_fHJl$U zw@(-+UL#nt(?A=p9blSl4|Fy%G%*o|a2QMZc!Zsj4DcJBuwqvA#@^Gk{HnDUXL1f1 z0N)jal%uw4?_=&m8iP_u1bF48boDuymG$d#LXz8>wyc^K!~(xA&^YuLEa@&kRA70lX+|sQCB;!kQt9LPCqaa3RdVA!zz^ zSL%2MQ8L8fy>*+Iw<=}sIXbD4C=f2aF=2vC_MJ^bP0C^kT<0M5a`;06V9+Fkr9cTy zb+m26f^3+>(58ZDXM;6PZCDa1YyGeIgOT2d;2yW-)<3F#5;@ z`(*2#;-87XBLCd&{2qQ&vyT0@;MGUH;y!G8i#8Sq)6#W=~8Op;J>c{`v1|^pr=M9KScvoyFi67R+%ikA`rNIde*q?92go+ zRakc5*Vi)*8a8O);%M((UIPp!d4q|Kq!XxkMaSy_Foc^b&;dxSJO(Y1*9B2R!_7S7 z(D{8S6hnW5(j9;UK-(E!S1ddSqJGJ3!(EqouQ&}-S&$N6^MGkmEss}ybq@rf&1~^k z?VdoK;)j*zsjCq>Yceb*^F3uj85Q-_5 zlDKKHKBJfgEDb>w#OjP^BI`e8Nu%R>_i3hgX+3N)>8nt{7^cnV%fZdRA(k$<(nyEH zq~h4D@|}<>*it%(S=1KsoNwUiY1Xx%1y(5!lQPpTM!f!`HVpCz_;Wr&Wip{l@Mhtt zgOBxtJ;5M z?w22!9Xk-}v^$U|xXkehzAvh)qi{4OzKPNcIFGtk+3N|TDB%ZS5J6{(xr?j@7d4>8 zX>7aA_%5=;3B1dt!z6+ed_Q46$=pZs;EW&P;?W}lHbfk>j6$V_1TVT6UJZ3?FsR$R zZ?*Y<|7e+5lVje>(DB&a9hV|5+yLwm^I}vsuo7A1virz()&nywzzJ(LD1yyD54*F& z^co<8ppf8)ax}a$2tsiHeR!&jvIxPoHI+WR>JXjjOVwWLP->0Q)d`;oX)+=#$jUmE zhHB3~e7Gs(l$@M|t=;e4yEhc^7Y#NWJzYp4(p|wD%kY23AeBGwl^Yf+6JhEI!6d2i zs{C^yyKn@sh4<9|L0*{%g9+Y38hZ~aHZ7cHHsXv|TRzij#!JawF&3WPEmW$?SBcaG z8!o{ufI1{FG31Nf=c{NTohyZob&zgNc|?R!T73TN^5;Xp1uRm`PTRO7R7TZQDKgJv z$S3=?rcH}NEh-ZT1m?!^*BVhw*@*F8w{Bu{2GNAP`Jexqm7m9pD0-t?kq@&`_~mKq9`{4IV^T3R~h%z`nXHXWHU02_(&QFVBr?i#QH4x{}9oilC6Gt>(gnmvQo!i!US9O=Tt(G{B5`)7o@oIH)jVXM^T|vy3&Yi8ra+UVWZIhMwS_722`e^zd^cS%i zgqf;+zq8n-2>c9>7&N4gfLXZHmC!W>P_7mhG3rGI!)2Mf&?G{t>|d0Vg54m8Hs(q32KiFgQ_G z6y&LHV4t(Q^*8H|3=##Dq)5y#yrZfyM>YR#@Csy>7{P-8RRn4LXeX(gCp8e+Mm+(7L0~k|Mk{$ieP=1)d-i+@xI^(H_nesZj|>Ah7f+Obl+H3z;WG2(CM|0;Z0vt;^31n0u*qqv zs_Fn=mP-NzK=_Z3)}u_cq*h3yl0n}gYp$d+n|y2MdQOY5Otx*?#gd5K(|4iyf>}dF zpHA)NXNAJc@zdOO&@+yf!Ju`4a)$v;d}#nm8=_il|vpU-!rB$%_Bke_kDW zyf@eX2&)IgfEdu4uX6eB-BEiVE1sB@WNp$G;wfdj!;;&s&d5!;JU!fP!%?ny8u8Rz^;2DVz56DI(HW9S(63u0HjYtrO2WiBK z1~QtJkrF6fW|%N`QbY$IaH2;Tr1%1_S#q zKFrSx%^l7v$h85rt|#VAdS|j|(~^O`dik#1x(rVR;2#`nS}}4U1hnoxRb5moMjC>{@P&WDuB3?; zkD&a018TzqZc?@EV&<#flUMM<2X^*Oa0s2H-TYGR#n*|b+DcWGk2wf~EP@pC8p&cv zz9&;W8lRZP@~dGy@r;@Z#$@8{Qo^bm;k!M3m)HdDuKnO#YTc~6AL$mLnFTYuce=px zZs9A!4vjQ_Pdg_98NBMG@nx!BoA%z)vS_dw1*3o=9CYpP1qbsLg$k{-+OVtX8E-~j zdONC9_mYo~j+R6XW*DQQOCK#;6ruLe1^>{Sw^^1@f$fc*dHY+q1xdpVc2)HDi}gB7 zAKM*$_1CumTf?p$GB%Vy=m20h+SU3Gw0~5QW2Z+TTIv$tpfe~I!!Cm}A0G{cdP&_~ zN%j|0&WRHn>K|W+swVc^m zKF8{((MtnB<{*j(a&JWUOCb)XD%(h4D9E0qEu~!+Ykh0SLSRU9f(`Pg+{jm;?WO|; zbRcFkGrZ4clGs;hmSSj&F2{|=4@i2 zZ9=w&2MM>hF>?WN`6f(GrYHj5l7q(-82Mq&1i$x4?7>g~)(v|095uB(rti8J>oZj1 z^`VOkGe-qeI4X9^NfCqUHD}1 z+KA6Th2LA<8J31<-ng>b4-eI(TXkur48H9+Zd`|PD}7BI)x^V(d{NZ?(zlNh#5CYSsDr=E{kJQWKr6HPAT%+<34~z(^!d8K zKd!uxd~Tg)UC9;osMf#M-YZiq+eV0SiHl?NhYZ>!S{*nrBU{%J%+jbKU8X_Tu4Jdx zT5bpQbBjFSQOd3`*%C-~f$AZZa!ZD5pkNwNL^W07lT?i~JWzrx)y=`KIAhU|KM*SC z(X?QYPE*nyz6hO|cF6W$sDBBxLP}&03BOH%3kKUIStCtFfDTwpFMKH0NGS1?5P|>f zf|jrXOo4yAskG`Jw7M(@AuD=MzTwMc2B1Ksd{VqnwoKgd^yyRKu}~R-9kdg%H*ha@e8=!9D1QrI^%i_P!b=Ll=l(R(w7%quFEMu~%g1-5T;+xv=xeyqIbk|?4lc&RG^ovA4= zbW&dGR0qUiI`CZ8^G;EY>7P!vCq6(D^+0Bbx)`3GBW5NQv$EnX8kJi2GmBbP^Ki-a z4g)uHujYhJdjWG?}h1WAMwCjY@2*mJIsIq@R44YV zfZx(XQDh*Y9GU5=Elr>pmJ*4D5kNttdj8;$q#myWM}N!t6PsjIa(u(U)r#t1pmiIh zM@`hn1<2B90yL)dj_OKuMqMV41NkWC9LcMpz#~iTAXEUn+>WxJw{k(Z&z11=$Lpi$HZc^v?;uiDs7YY4S;K$v8O0+3$Vq zbq6jd_YVV?o77fCj=NDer zcL_9}hSg)zt$uhzqW+&ut9)5_{pL@%hH8duo_L~Se*F44t01pYJ3`ihH?iM95zuN? zs0wK8U~*klWPIFA2gmK$ zF&vgD30+3e9K<^WcFrHt%Vr#8Sr^XvJ9>3cXC`6rWaK(guS}%`r8{xLZi@qnzF{cY zf>5xFS~Rf1{K$_z)JYJ6_u5uv4^lLavNZHeDzd!tc0or*LE<`XrPNND`<4tYD@pLtE9zj zP-^k5346uCmL`tw)dqni<6`UIeKxN~QX8|Oe*-4(yZQC)`_5lWK^xt0(&ELZdaDz) zybq0SL%j`gGRq^a5px!4wK+>dnnf2PzGM_IragLSn>Bq*GB)=;)SiUQ#6&zN83PD) zi=QYgE_QpT8w%(p4Jx2Cy{>KA%0Bm=<|kD@uG6-)zj!9JVtgTANgzPduk55H34of# zgVRzjO6LxyCgZFuFJn|pZd6M`8g$6wDQu^omcobV;I#SzS|-XnDBaPcR%6vC(>mb| z1_fozJ`c$%Nvz{uzcy=f&WT!U6PHv#R}>)ww>is>CMY&n;IwGB-=n3n+v`~05&E86 zZ)#1^o!+i`;-pC<1GV1+GCTG48}08;Q@;jnFiltfj#+$40f|x_<$QG5?^Wl}m6nWZ1W& zFPWkG1edQLAFePTr)Im9vn)22#0)knFQZXf-l+57)13pEv=`5R%74tm0y8p9xE5{X zjT4G~!Zil*noCvEmQUygTng&N6!c0#K@+I=b4~+3c4OT(ayEM}ulT$kh9519kw-GA zWXA*q52Nu@hJ+DI@@%YYCd9^}S|Po9_ADqX(_&5w zpH-Ha5|q$hdm2ng`s-L`UEODee4V%VS`ucdubJZR`}rea4z(3yJI)*1ci1Ps#`dp7 zW(3THX4lt-5OkEZf)3wIu?q+?$zc8`+)toPX}lT17BV}KmB?x2_g=nM_kRESRe@X$ zytsGovrG_sSKjp zl5B-r0WnxaaFMFow5sN)AXGQ_lP^Vo%}jhQwtLv3#a;_4^UYe3JN>=wj@*s6(;ONd zygr}1RzU)Rqa@2lsfuJ!B<4lT5ShAmo%y)8O;?8P1=p@caZXr3?$3uo>OYYYm2;*S z?@UY~sju?D*@;JjhJhDfB)GF0vy$Vvz``T$&SGC5rv9j%eOk+Kp)u^2LC6b#GF zUBn9{t}{~oYWIP9dcvR;!VJ}m;hp`XZ7+H6*R1y6df&=#@Og{rP;GQdtwU)J$V$40 zPm2oee@m)-eW%dzK%Pm#Z159)HG%-aW8hS*a0pH_;-f}Dh(omY>Bgf2uKOp;kAj2M zhPyk~nSQcs<CKR;)MWSux>d$2tYF2<8T zlfPCW36Hz;@4x>Nz-Bx-lZ2lAO=sO#R- z*+0XfV*>F-o=9f63eyb*Trg>hN2z3g5vVcIK&H_(OQ1;vQYl3KjszFE#mtFFmEc?y z_nf0lNL)?LE3{eki@ZX{8nSDbsnTl>gfQ(kamYy$KG)}CtKA$Wh|S8^nC{Rn$u?xF z5wZ3KHQri8Ew0YPprt)&s>Q*n*8jvfxbQDB05NQVyNUL2!t%P3Wx zu$JGz{~uQWYYGl6S|3hAPbCgHeGVZr@!9AEgd~*NmTf(H;Q6@jTQ(Pd?`r(roYRy6!b|lTiSkAF?~1>ajrI_2 zr1s?aIC4>i@j-Ofc*QK@IaAu&&xLw{v)LKzNM{M}Psj@CO@D)=i=iyZLfl|j2U_#x z3odc`d@s@i196$>=ik-t)TvW;|HHgeUKp!JwmLi-GAFMtMZ83BU!K$Bl6Iw&?%|E) zv-Es@I}V*<@b8iIuyF&%>R1msJ2x27Qhqa8Sv>mK)K-!d@i1bS5vZOR*J?L;QWHYo zD4W2U(+4wm44ytzDhByc7+_-biQwbb!0*=f&^B2^Yu;_zt9}EUD>O5ReN+-N+7y%)rLy((CJg=H&K!!u%z2+qN-LPj4zLAxcl7V+;)U^z&;C zL~GAGr-&OnGe2yhV)N1XRb4juJm~p5H~AnfO6AL!qfBZx={Nl!!om0*|8Cu!0^(WV z5ZrL~iPi}sq8C$jfSK9s!7C|IM{NkLTJ3=$O0P}O#VXDXuZ+YaIDd)P6)qv$L zI}oUP^eJO0v5r8{6%%9vgyXFm_c;ffHg7H#c!|~l9XU#2KP&!{9^&ON=Q-R9;eiSI z$hnp>7BuUM)y~I1{15do*E8F_XOGA@Y^MJF`=W*74|GET5qN>XuHvbV?YxlZh{J|W z8_7*DHBH#M)s@4t-YLBplSNps)^Er@Fp`gf?D00 zwpYi!Lx*5tiEt`I=m4NDPox<#Zfng*_6SOHnMBf2V)@i1XPA)HB)##$)Adg?x)nfx z^b08g3@wBy4}$e|dUh9_*O>MBoBr*U;P9MD1nu1r{)%M+-N|m!qqzPu2k!ux%Kh%J z#OH2JciXjfo4sh!P?|urd{~Yy2f3#{;}&h&cN-?fC4S+RDJ3wIijVzsS~Ce)gBa7f zEWEA_TRT2f6M*b*9Se{+_BnQ zKb(**-!!G{PmRJ-o<4P;O!I)Rr~?qbTW+|jx5}hze(|fEyPX@h7(TW0bb0i$r95)? zk6SCo`i<^56`he(nNpz>go%ehDTz?z*H%8$E7s1;$oTIW9`H*$@)Xj8h!*IBy=l0cxKVP`~qP zUsBG%72iQpM|R*&Xw6^l&)kfA^BER5x(!q1$?ps8#VIMAT{u)=>3mqJR7n>?SB;*I zH_h6GA>0O}FJ`a176sWta*?KzWX2R~Vqjndk7sXJ{g&Poplg^FiI$1?%Qe#3wtjtd zwD2U-BQx6bW4I}7!VcpzAQW|)_&36^XmGW=McnwzhF-(Rc^4&_8uV=IHn>Ck@M%{L zs_g*|-_2o=G|EE&mr)I3jTJQ1Y}6A2ZdH~4%j*>%V;M^k^&uy)y(QYV_!VHBGFT;G zN<*!$8!q6XAQmz38Gs-h(T_7vnZP-zJl(m4SQ9}IfN|WKauVoZF&~V{(JRn>G1Nkq z0^=B}VN2mpl$0D9_D5A&=}y|Cfgc|z9hu^-`C-RXaVL*jyEc_HN~sc%_ARsf)g7VS zTXKfk$l1LyFcV~z2My1h{P}$UwrMhvq6{@Oen56Cq{Ydfa&ghJ&|3GzbH~fPJvM!E zYU3KL;_acxU3y0Rt^k&D|4LA>-ekl5#koP(;vJGNkD7eu`g@-rIY%2bo^BC!DF``YHy=dK1^<(kBtCwx7;=hi zk_ajM|LuJjsG5EHwUZ4;LM%YD;B-Nl5AIB9XcDVv|K2@39z#PFv;Id)%~5rw75u7a zl({&Fz#Mm=LqPyrwc-wxb zW>3uiQLwyWW0-{7r|vN`y#Nt&#Jk9(ghez4vf7K;tr)ZN2NQp_2UmxfmwB-WuN~26 z^0C~?QV;NBURjCUt7O<mwND(i{-pWax(*INWQUqU*%Z9Tds1Jq6MS%>^V9t68F&z%WcPLBgYwCsaM2Z!z>K zYOM9Ji9KzMBR@^CsZH*%7UBVL$P11gT&W}Y#{rk;FCR5}bTZ8p6stV`ASvbrl`}8N zmJXe>bY;Tf1D7%opP=xgxQ-of*MA|*ZWA|RT`+qn7tmwq4i_3Wlwk5C&T8n(IY-}zq^n&upRCzTB9@Pu0GhF4p!a_;FLkrMj)}`EyjPubH9$lAI9Q^Jlnaq zt14|bf?5wjW=5t#7J2p7EmMr}?Z*$TPj_d{5`_W;3{5V2SncPbn6wz!p6t+}gRE!} zXhou@p56HQ9n38`;Ihw^I?=$)tSJZr+5oN_G|g^ zJ#jn24TOeO=&>+BV4)x z+y=fSIsrtZ7o1f(oNm8q?D`29cpxrX!3>U&E@r$$W$L~T;o%CyrIS!+AjG$UmIN&P z8QUw6lmgxoX%903wdGQbasTKfsK>mf_KApC@f}DKLP?@S&z{6QP@Ox76jWqo<)da5NDc63w+)}ZmO&V|H`Lk!AT#VN%QuOZ)sbw)O zsV-*A?S$N)u3zrx{K{VeI8W4`GJ9hw8)7$((|D^s#X+_lwfqUp_*XJ^K=!sAlQ*Il#4NAt zjf#yIzIcRGu7DNVR}aKJ-dDo%R}Og`)W-wEcht5{p-zO)?|3?yD1Dn(iW|!Y?1k>X zYOASv89J)SPOupwiBdtjF(shoZQZslf7F3mS)9*hfPu&^rG1Hm{plZ6C2~^GYoY++ zC(?mVgknTC6+H3w73U3LCYAL04DO+P!2Hp|o?d|JH$C^@5(ht)SALnn5)bvv{OX9v zNT;~EWxxT1p_P)#m>YOb+{({!yoS)N*{ieLWymgFVQj#E>SQsM z)_xAtX(jtqawCX=O)BPNL&$V(GkMXX-=pl~-@?zN+G8q00idU@BytHPj$HwDRT4nh z#nF@|=JWrlGjP~)$}W-(-=dMAHO=`mr~R#(eFn=eHSlq1H1f<{lNZ+~6DUTTZEMG} zEz*Xt02u*BJ`Rh{Bl(J6f4DjUU2@4fE+a)@oDzf3}!v~m1!V^M_Sc|HEX-uHH5 z>p5xq^xt-EhOtCo4xC$%RN0fQ)+Ydt8HM5{vaz<2M}0I!)iK*U#(n$5>~c2@*&J){ zKVqPEna|=cKfAolKl)&a%B+Xg&v0zQ_*N+Rq-vpa1iW92le}z>1DPVqMCx85e27Am z*|?)ohUQ-X1iJFLo!d5U+N$c(YDKdTqdZJ_>#ukQvdEV_T*EWPI0jpv#%SPV-oOMt z`rT9lI`t03pNRk_fp%N4(dNGUOqiwc(L3Col0+sJk?&4#w;89ymmx4Yg4N_-&th91 zmFynKaJ_r?UfX6WQbYPXrY8WA;-?953PL*9u_Y2Q8;n>CyO}^`g9<0SENskDQ~zw< z9yfgNkV$1n6I`zAs2=al*?0!&l}U)SmL4Ttgo?zdDO&6H2z(m3rZ58=gocKSdm=nx zF*uMo3tyH2MmiP@n4EO&-d$jSVfVq^;qg%`Mo<0n)0ZTIFziaIXBWMU0|$ojzNNin z;+0N5k`?8=rEX|^0y9qto32-{DNrbD+06`dTn9K>RzpA=i>|AG(Kvzz?m2OY5Xs}H zUukN4vx~0rb-1+3Kv25uyWSv>ryzR)a{2v1w878^1hQ8)1$C&9=u}WhvKUmTg z>_OHd`yF2a7|mZA!W>QXPmqR~dZ+5UY5nJ?+np&R^Qxwl{@`k^3;v0d?Kn)~k091^ zXmhyo-5nl0IY>J+vy-8r*5e@*?<@w@tUGxA{CRxQaK=o8MlXq2wgiG0rd^-IL>4KR zIE^u&(m8!=rAfbC|5obGY+`H{wBJ}UZC|V9TdR&v-K!B})e~C)2bP9T1K6i*w>E0{ zZH`GF$O57$Vd4z=9g&S50aTD%$|;!u6L#zg^o%Sf0$q9U^L8mq>yMPhuJ%)7rg)At z1ccg(4iErAP_J$fj%&xe7gq+FDmz-?t zfSQqbG~`dF=ft$<_hrzBsoIW#nlG?D6+fxcV`?aglsYV}Y+xS>A(1UlE@JrQhjkh` zG@X}<8b<@g9mH(BAPhlqdCJ0*A(jA%-22lZ__AWyAeDf^;y;HM*St^xIe_1z4)6}Xvx;Jpz-o+KiLWQT zXPVUS|NeRHdYMT+!`blchF2A{z*eXw5|~hgDe8XMK6)9lWJxK|mxD$>V*^I&oH{II zukcU&$PYYzE)QN;F{r$`PlGIy0@;VH=I@OYcrxw)Bg} z$ECamDzjU>{A;&v?cvx!bC8wg7^4CAX7XSokM4#bf@7n@xye;kPxuiTW)*F=-Ux$O ze2fr@*A4{jxBJtFfj}f=eQ+%rxSqy0m$J$O_U?N05wv60TIXP-BvQp?W33|g^yphC z`2SLkC}jxW72%VtX#inkMz+28oCt7h!#HQHqLP|&kf02nq40^ozk@trBNozQ{jA=T zl0W`2H4uq~zJ+C4=dVs^p&IdqX%Bla)~z05Z+)J2pEE1uEdY3`7)^m@C?kGVZ4QVY zaIa>?s>h1+%!(uja+??%h~$M%n`@V2c=DNuM1 zGH=@G(Z|)BqJq+l8YX+F5A#3S&GMVUc2+mjZ8++#;{VqC`Ix)wz=7*P6)a42Vq+Np zkR6n-Y;)A@bfwUSzC{10*f#T3`EmwhFkz%(W2<_~yX>9t?13-QLR){a6@n>5MtK-i z{Ann2zITHf6E9HE)7uoQ5Q~#RP?JK+X^cVn#Y7JHn8CaEyK@1PQbpCq{DT|1n~uC$ z+wOZEcX*4i4SE};3v+4#UMVVZ^>b!wBQQONB~%~{lBXLuuymA5sv~;o>AmHE z3&aMvw2O+R@^rVJJ#`uv5-Ws93(`(0^fPGT{_VZLWDi;fUdK>NT7LpfX}XhI&k2n;XNK z5X}YE;_jHdnXB{d`p&)!EWjS6NGCKrd-lvDUHN?>jm-pxmu$osX?2omz3?~))xy#M z>uMS?h;a~10x>9IcCS@hk~rma0~%_>$!=9>_MUOqIq2e;18aabywY=b$HP9?Q&-tf zn�c%=Y?}{h{SvuR5#pEioN!#jj_~tF|K-z)l(y&(X33kL6<9>E@vZFp3CDtFMF- z>jj&`y60ojQ_7$a$$*^6{Tg8xcFnJKS5BOp=y+7!?C0%k(ScuH1WX&b|MkwaO8usd zc9y3IM@B#{u^3a zBBUuRB!%`sLRN(qrIbkBZS4}JRA^b1>b6R05n5UrWTdqBBxw&CWc^>){d@k;ar}2q<61y>nCF@}PBU?$ z853coc%_lgy_Cj#@gTpK{ zkMTdoXCre?7{4r?w6k=HTFABf*}Eu${&P!e)+{WS(tZjmYo5~?tNe*d3J?y2%0)BL zgApi_I|*!{^I$1MSN+^fbVdC&d9L#xuzk37I=^EIGWrGfx>ong%rfe?f#KToh^fhh zc+elnyL;^UzdiY41RW%sBLx1Y7G;ls!IIPhn^cSI+%nu*WiJ{7j;IyeAdnXj5gno~ z$ZjF*3@AtXd)=V;C50ziW@0CSGhTTsQvqf`+iAky4bs@?V{2K4Kv%Lgae zK*$-=q}SantGZhhc}A2@M-J}%?9jK&ag}~Mh52K?Z4P<4>sK{9($Z+Em~F~_`J8}> znX$*95kZ@hD?|r_p|~~g$ekz7iJ0iN%Slh=nf4{?CC}MahD#Yq#Nl&T{k8?`>+{#T zZcDUN>$l{FS#qYy@S<*^+9!%~h(HiF)kPj)7%h9P@W~!UQ4GE{bY=MlD)C6lej%g^ z-zu#{K&&^Ym%L_9*zq8XO+)$}7qD=Lgp3ap zOZ-{`Ab>pEq`v!~lPuAT^h-S1qNP#hM{QL6{yhlvs1QG0Kw1!GS{&8QP0F3_^6_nk zU4>V}REAcsj1|=-MC%O`zTLW^@TBbD8QxK2T8vnBZ#{Pqry8-EWGx9@AZYn)h`s>x zSm$7Tq0@8)I3k!70dzB20+4B9^XKfK+YlL)M`! z75Cn7=MG4sWOf1l*-q(i#OkT;jcg-y=AYkIb8LozBG-azAgo$36BXJH9{?93rO92O z0LyMw=JO1+67ABxFoxm?^^80>ViEimE5m5Dj{E#`U#+kIur|FfvxRg9Q@u~GiOlzw zxJjKRZocP+x9T!@oX2upPPwSw-`t}&z75?0wCyVNBB_j}DWrwa9q3dPEPG)PF_vlno`gg3>y_Z&%2kH7XpE|G4gZWl@jV zSA)#w-1VGY+0oBUxy6d2&q32m>o2_p__n$0i0LmP7Hq^CHhEMI`nG7{!g%^Vnl^lG zWzzzuVSISZ0qSFrNM@I^oMrj)KgvZW?cK(=>D0d!wVD`zJL!#3QV=yZX_wg&FR~A7 z;J_$cy_b!y`@^Fb`&!^Xe3w~Z*SqT&T0Wa1->R0A=SOzH8D)u|+UzMawW@-YwSz7% zJpSnC*P6xlSN?uhZLm-{yxk;jpaDV-xsL)Prth*}f;KZMZ|38Xvi8Z&%Z zx{wZw45K#L@QR&Pu=m_CmhRD_6T-~HBo zh02IJrNU-?1}ZC)^Syg4%+IiQoU?xLY+aq zNOgT39*OLlgKFZmxBv0S$BOBD*-2{rv(S-^Vw@Hkanb;p{t0(Ta=r6mCWIZ&fA7Pq zzDWv4mUy=E0?y`EbRv?Tr3hY)wd2&!cUrOPhcZDkx?|;0wcaITJKy*GcmJW7jx=C& zQ+JrODz8qmXjcCDBUhftJ)OC?V&gm>F;ILzHih);(Q>U@ z78|}b^f6$*obW#2d%y6wI9ZM^kFo#`_Bc{O{rHZt#`N#8nn6Nx0d^C>YmR3vFLJ-$b7K}090a- z+?v-S(=wKF5@X?Z4&k-5W~6i{eKcHi3|U1Xfb4{m$NmRV3c|GznK)cAXkGTxpMj_; zE?ZH)Mw}4{s>Ea3{dMCE#S@Cwy5!rpG30J;@wjB?hA~dIL^xTU2x_eOYPL(R`~CXK zu`?I;HdKG2zR%02#m{+O*-x*GQXEwsv6h`{zi?+hQ}{&@vV^p~z_Jr+K0~D-lwwh_ zmV6tMR2rcKDG*u*Z=gGa(6hjW5Lme-hx)t{r3(v-05~ZPOd%FCM-}sVJ~k7KGz{_# zCmhosd|jxxAOor&&#wV zU~Fp`T@C}I=u+IJk{dsU#Tzx@xQVS-cHO?-Hsml8sUD*sj1hRn9HW-P$H=?hBIq(v zl$Obwtar}uTLX6W{#hW{yvrJT&Oqs`SvwVAWZY--2|WrEqt37 zGLTmZ-k0qB8(MZ7NR=k5RXTO*>Clj5yBSJR`@7SPT3-LQx-fcTTHJ+wjT9P=ebCo- zuTR3ELz^fWtdy!=JyBFR&qo-;&^_k^hzipqq29@U2*qWAD7%{ruR6J#yI!Ph%<4LH zg(Yn&b}1PHXFbMAo5`8j*SWsMrk#-ipg)r zi-BbuR(rIYHo83mBaFRV&=Lzrl|G~y$iE!J|ID>+u7X;yn<+pz3R?bXnca{^IEi3+bxdy80okyKta~au1Bp!HT;6Vp-!#{vUDc1-UQ1zbpHhZYs z9dR_UhzO5G*2?}X&ZRG9jZ};9JlO{2daUU`E<045QZIxK*BX95c6>y8kK9J_b={R5 z-F4oKNtwa4ksF22VeHlA`+#1^e=9kTM19M3mopgyF|PGoVlG=+>7W|OUTVzy_S+Q> z!d3zQPG3I1;um#5C10Qmw@H%>cQ?=5+7V5F*@;XOq(+?C=};J$Kcy6UU;0+rzcOxN zL6!2jV{YLzQw#aSmE8|`HloTRoHD79@s6BnaD0Impz;=CxFlqD#zwrRkiRPdvxPwc zAhHO))xpvKIxJiEyWW20a^5HKr}+1A`^*yAWwXTIX zKcf3_^vt+c^O2+vPc1_{>4k%OS4qo-%ehyu7Y=i56#39WmVh$cW09tpmN zy?V8#4-wBw9StGXSPqYS#>90Ui(_Eyy#=$t%3D;@B1S^MNGO#Jb=dUEI+MBfMubux z`eHycEk{r2b1bFpNQo)2nVACE3h3j0%n_i?fZW@H^LM_fXLq~A(e_1wa&mm#uWqNv za*SHf6*f!?4OL`kjtm*eu%o6=;ugB|q^JUX7?3kHXaTuEtDjxif2fv4pgHy{L;Wjv z@RCp`Wwjsljg&0ll?9+PS=6* z5IId}HtUoAi|{d%M8)_ECzZPKaYOt(e^7H`uvLJUNe2W`j6Oku8}Lx6z?JM*0{gJB zG0FOHpFxviKDbU9wrOZwZSthkhphTlSSgI1_bY{}bkff@f#T?#I#spyaddPv(8M8T zgQ9Vws|2;BIV|PK2z`+G8AuaVp_*f<&%B}!507^OB}fXauiLP3qt}83LQ13D=2FWX zUvEsTQN;K7__#G^ORSbWYx8cErAPQbMxRof+|693s{F0X^!js2aX-HJ=RUgrXKi{b z`3i)pC2VQk`+H`d&p;Vr@)RFK?Id+}9=Nap16xs8)34-g@~5fL7_!U=9uw1jb*8kk zni|g)=2Mk=5!Rla0#&tlIsT}L>|o-hKr1$l={?hu2yBs)m-NVmG0GrKTUhHnMi@w` z&X%)jP+?Kh{hRU5)ut?M!1gzHIwSO)G6&1E{RQ+Vo(^Oj>rv-;TdpG>MW`RH3Vv5V zuIBdbphZ(ws}AbLcoAm;h9Se@eNw*U?ziWe z>%&j$H6F72&dJ%4T4h*d*x~>M3fbP&O%OWA+YBdk(DOgH;BC;OJ5nN2{AyuYK!M=L z6fUTG#1xTciE*UMlLURy2JvZS3IPT~Vq#rS>l8TEV6!}72ta^}>s`ME11LV6_u}Shx5yxsUzth@=X_qx zv@A-Y3mE^Vx;`RefPcq(leZD6gk5pykniC#O$Lfo3{;#!44WHe;)pilbN#8)r;Sgh zFqVBylm2^r0Jv@|936^izBI5zb6)t3>1PHGKrRp8my|G}y!PaY`{!LCGQ)(bP0ZWE zX0_*aH0p3gjqZ${s-z$u-q@BhbFMKQF9ZWw@(Zp<3qAv<7v1!0xHsMc@|G1;WSHRH zH;M1q*fvBnAua_s)r#QX!tcW`-BV|d1#<^-EwK5~_^p#Wa?;@h3dKkO4Gj&0rgMpb z`$fPR6GMAd2nn)^6dt6G5 zC?S+n)0z%79!xQ~z%fvrKY*&IC5$9bBip)Oi^|{HLx10X^yr+lD=EyVq^9ohV>KgN z@}I*4m~Yyn_oiwSkth>fi%v)a&nhG^_$Y1W-7 z2bn;UPCEf{o;x3_(`U-5?1MGM@yB!$!hFV`-fHZgID@c64z#(lREvU;p>_LJE3%-K z1COwJh2e^9z81h2(iUtGMiqD$$TlYOi0k2T>q?KOrb@{IWR?IbCxm{+Enp)u_NBZ9 z;IuC6Yin)Y{%2^5MtC13P#1`2JNqkTl6tg$LTtab&6|sF!TUWHDzTpJKKKqbEG>Jy zW|lTpyR33S%o{Xokb6Y(Qg`Pl%@yto-{!T0hh%;J+Fdrm=+1oj<;xeFszdZpyX@R9 zpkXIg0k8E-bhRYk5#CFmKd;3Ik*ni zO?BGIlW(CcHBdaR)vbgs*emYT#fxha{%pr7gKjdXjgiRxu{a@I1)p4G(JV+4Hk-C- z5g`E#!g9FY6C6{hIMHb%Y{dj;bN>XG0xCY|WN6ys1KO+in_rCc*w!X< z%;WPjhkq~&$Q^Ly&)Ra8@4dV?m^Y(;6SA+64HztmT}x=Fi~

XIbCzB5?BY8qQ)q z9HSF*sXfOR0ix=#VHZ>N}NcubjM^Wk8Y)#&W1qazVY50nJKPCG2cnYODoS`IKM zHZQafAROdrSp_5DE~pPLT6N@i8Xj3EN+@-~*B8jm9$+zh=@(XhU-s76RDATupdAf1 z)s+;xb{0epbNKECNpcw(goLjZ>sZb^`>$s*Ium0tdK!ufTc%|22v!~L?G6Nh7E&C~ zF`n)_?`aePkbx8@m3|yq$2v^QVeZC*u<&o$A*v#o7--_d?SyN-|F+a`zC>ooIA22l ztf}!QEZVyrEGYX_*P_w9#a$T#>#Z{HM9^o#Pno`wPL{f(=JUD-kTQ3Zj(fby3euF# zftc7&_TFo=2)UW;PG}x$Q=ne%*^a*L5UIEFCh-o3MhDwEc*RAB76 zKj|Q31{rSt+_N!78STNO;d92%FJXXB%}kAWmt~Q(HtuL5-@U8r=dVXzP9Dq4a>$5TD_{TZM|Il_o0#=9m;f5RUCpgi{!~3G zk*1R2G~HbrFisBBS;Wr})xq5p5)-W`Cuz+LUHvB-uSABU2ygW&j9iYzsDy8KF#H&< zlsx&2@qFL7a@V9KH}bL)2gZHaF4mCLb?x0^(bJ03hX;!XSTk9ZMTn8y0)D>*VSn0sXeul5_q1TrxG6Ozj^*gfm#)&qR6Zph$fWHej77a$D zCjDdm@{{38;0>^O%(;<#%#jpt7LLvTQaykL?Jv|gN~tS^gMa_+Lg<pHlZ!wAISh3ttB>c^n8+XzTIg$F26>dL^uUn%ir_24FP{a|a!u zSV$FY;6Rpj{ltXY-t*r;NE&c{PDrnzuYP>_J}kb*x~7Y%m5-Q-%zBja@B6qtXkt*; zK{JS_xt0=*o|(llH<|DrrVI=Dq@u767qrb0)>yJ9@R?DceU9vQDM(Yu8<0uLZ|3A> z^?%!cKI!*}?hLxRoyx1sQQ&nN+pA$OY zw=^5J`ltTGgdECw8S7C0fzmDo6o&mMmIgHl1p3atD;zZS8?yo_b1+EtdFWo#^Z)FR z98RXRS6D~KfLr@@PGNh~MM8HcL13{ZQ{*NV<=fLBhvM(S4$jMHlPRRagm1~Qn@0JE zk|>%$5>{4EZA&o}Ol@EC@uLHY3f1m@RCAP+4*R~zYSD6z~eY(?>}{? zYLKSbM$iSJ;1{_UW=(I7D$Ky7kVhzjB+;{S%`IlHWc(?-1?IHOczyBG3w{S>O$|_a z!h0W<-ZYYr&Rg*GZxt8DkrAetnEvygh~_iD-D`VcLjU02&c}B&Z?w(A9czI@ZBJwY z*Zx~t8&WyMdxOIW;vB!kdBs4;0I&cyIEgt#CuvWGGzjcK=CB4qhi4-^Gn?O|9dwkz zg?gHHDUGluklFqp=?bQZa^q`Rq2W09*J!WV<0*t?SrBL9Y}&71DLDixRx^FgV)@;a zRunPo5jIeA>KYqwV@xe#2vP4bR{U>~LMK{7c09L%BqB{NzdsqdI~_*$)#9wSZ1NtT zmODB&;TgR%!%g7*btKx?A3ug#Yr)}LtP}EPpZ~uFN5}an#I({4Q8umXnbEz$6r-bF zFJ879=H3O??lyKdP-4LhVvIy$xq=-K8ZE-2IC#RE%f(i+F!?FER7|%)u^HE)ohFoK zqyMt@-AA!4g$F_rdMYuyrg2d1*{}TXuQ}j-GDZdtv8GUfKcSq}lfed0?gn&Y5y=bb z`SIgvke~nuRCP|9U+33}?v@+xjS`BP<|4v|sJ4)1nVZ-5T5w~^3IuAiz2|PJPCYfS zYH;+N9J`q2jmF&y&7S8m=3L+8ZMUcQL%hUA-uyOlJ6M(jfQk6KX4U@gb@TOx^C?yEg;a z48XA%A}7D3Bo1Hr{rs`@Qul@S&+><)w||CTQaIiMW) zoM&jun{q}~Ee`(~#?({xx`3@y zJ>FnicjI%)xCz+2L_m|pkc2|G`fVw=paTPF>5CaKiY5fAThI3^5b~(qZT|(;Bvkxj zM9g)1tM>W~=WZW%OVbk5Y}Rf_6xrlZ)V#)Ze^Z5*y59cBU({?Hll`YvsV@{4Q$CDW zx2vy|{hIQ&KRJF`v#P#s7!`vSAB{S0KP@?T7MfH$n;AF6*fzy8ODs0SqI3$-_R|P5 zYb)#4PP=~6j`K_N<~@pE8!y|G1SkIU$Cqryi5_lL2K!!+KqezOKG2j{oHZ%UJA{Un z4WhO%9|&CgxkEWqM>5F}uRS`T48}@=Sp8>e5KCb1S$H1o2ee_+CHF3?Mo)D*ADb1? z+r{Pf0kdPr)@e5PYWo=AHv989iVV?>itj%Ckth^MJJ3M*9%6C_3?+OhW9@J|tbb*k z2`tAama78EaCq0lI?uBLX6T)6Zc97BTm!E0SpRjlHa2gtgk-X( zqUWU4tfBM5S0WIh)$;Q3$)REsz7x!DxO^FIH?!z&!mk+D(=&7*b;RmyXgdw%twD=D zMn`{q+OfvNb33MaXV0I{K=~KmrOisTL>yOyo6Nf?HvQy+*e%27h8o3d70fC8(3I_G`cbM= z6eN3Oni8Ul%S1Iv)aRK0fI`bWFONtkaa!D(`D0P?%AOQBprX{IXM~WG;Cvb3OAZML zoyzc-e)AYg2-8wpUM3IJR_XU$>vmby)dseCCb$KM1r}j1oZ+mwR~*&-RJ{<;Hb|63 zH%o+3?A3{!24o+$q}$)~3n9IUW#ix;Yg9SG0Y`kD4}_q}UhUsj-$JE6YRheoDOaO+ z#%`1L3YXQ5J!EA)lc@?McH*tZv{3v7A#oWlo^gr1z(JA)Z)`?X>e6Kt^*Bo|0GPWDs;;d3r82n0Fid`@XcoWSB{V7G4>B{oARu!3N&qDjOMEnl(>J9$^ z?}UK>|E>j%y7~(*NDIO%Bn?V};@(rL%5Ve5tuR!P#D+9(Obd-xc_8XtuF=@XWta=_ zt7Pe8PRSG$0}Rd$UHUh9O+l0W>{%xkItLHWBXi4RbFDWUG)SXavu3n|VHf6?23!L4 z6__72#A3F~i)IwkWgZtx{P4uh_O0?P7m9usjZEnN9$wB{GA%TZ(cb#G+1ZT&`m&D4AmtGvR4k@AXOoX49oB3v zx1SS1#30Pe!q32Gi$6Oya)AB|Ot=ySEZK>^od1CN?i(&T)T4!bTCZkD;S$HwMqnRO zIj3_$50;d*1QUfd-163yi6=k%+>*mV3%(o@ zG9PzAoVGzI#Lp;Jg&PQus0cCDa#N7~1~?^IV5WFl3!Kg$K}^ z(wc*ab+IJWp)A3(BAALpR#+=vT#giS6Yv0)8a0eE;5$li!@*sLUs<`&%y)E1?O94Y z3PG4~A~0s7YR<<`g9Z*1i)@Y*`@x1%MOkZwJ9Ckt@Qfz;v8J_sNFUw=ws~UuDRfwz ztw^NQjx!LnBzwmJO2F2$dN=+SL!)KKgZ#t5I4Di@vgvl9gb#N(Ow&5$PiahNH2Wftn{M~h!1LhvGwhJOa@Kcw!=4IuUW^91b z*FRODA(j(|Ft9+_z77_P$%^mOg!P2gkon$y>Z~^=R=BgIg6{Pi0ut12sW4y<`OqH4^W|9>En zYq_zA=CH!vbipVYaZ4yA$aFweCj?%?2%#Q<_W1X~UFhIwjzd+o>)j&kw8C#wd1l!} zydR6N!!>?X#6BEpB$4cr$d_Efc9!rp0h}V~Up)hB#bkBo}yNLLnCnioG#LX5CLf)4V+ZYr;mlH9(fWV+$+MH*;mvYCB z1uP@!Fl5=>n0Y0a+Qa06zGepa>Y`CholNr|%n{2#2jSv2SxEsoR?F}Z^SU}_s?^qA zw`W6*fHq>?BMKlw{jlP96J|m!TD8h1XdwWD#S4Dwfqso-1D(tket_eW0fucLHL5M` zVR7l5nW-tmMj2-j^TT?nKuRTZMN)44plI~#-glRe`pbBuglwm1|5Y=dOb$3cIV3Ld z>v{lR*6hqlTeXd0IgTTt`~+=oHaNizoz*{ki3E4C2}6%g0$Ip@s_O5Pud&O8>dKUeZ@cBpjJ&$by=Sb{Ubx`l@|}My zg6oIOJ`mXb?O%6d$}10BSSyRk1m#B+BAusI3}o*n^Sf-GHA`Sb%0}Ii03;6?oOBEM zYAeMDRPo=gIe9%XX#?>>ZPf=<7Ca^c8G%rrAAUUZ)!tB%A4sflqJ)D9FM}v_xuTj` zHA+2tysE-Feu;SF@B%hMlL~)^ou7CGfeST;rN>pb<1&R?Z`m%rfpod3`meV1P*RXx zCsgjRB@ROL7dkeW{N}&gg<3$uzVAf;&IFYC6`+eD^;HShLI(ZTr%-b9CM9;zYzn=) zXGCcYQ#5$HngPGDtfJCdujM$Cxjv*Mrnv1p6u_7#-QER9(ON%i5VisBKeuZrM8Muz zHLl)$*lfC)i5zGbj0jvc?TGDAw;0KCnL5($`xvCk%lsre-Y#QX$aB1d zlvsdAN*An@-j=C9_AMwK3z5sQFyK&95-emJ`cBwbnBOADfOqH()ej%CScLS1U3HSa z;mpCM%XagG71jLtFTMG?i9520|McRz=yCPWrj|Y_jOb8ClU4?F2TXU^`T9|2E7HNy zc5t;e@^2mOw5zP(C^J)H*W+l7B9W_gRcuv&m@FKP?iIby|MfzaEyiPuM3 zLvfT1&KnZgj1bsdQPGRH4Cc`wH<1c+R`sv%p&)0qOXIgnT>8#Y*(HPCuR*%?O zwTB*V2AK)Y{g=HvKR}w7G73;FNd})ZXDB|~QPXi$I#>kwhhKC~dNad5k#UlUu+hnw zJ4Ph;h1+#Uy^=6Nlh1HZBu0Q;hT|UY!HEu;0ZVW*Zl6OSim#ilnOP(Ny{tW=rBij7 z4H_&AJSYnM{h`~-nPnBwygRBo2M|ZaM}>h9+?NUnnw(nkt>M;*gp0%_G(=Eeniv7H zkq4PPqwtX^?glkW`f=u6M%E1sT2nX5AdKj(R`B}8g_V&cFL2Km?Y*CXrnx3=e8W&1 zH+7{J8hFIYd!?McM_Z-*r<5KO$%>uPH?nXi2A#+*j`#6IVTueEwRayhq>H94hul*gU~nWiuaS6!5{RSUk_|4Wi_r&A^_)HuWh6oOc{~JL`J!B-d!b({2`R$ zs;6$T8nBTvyNrXvF1s06MsWX4W1RMlw6O^$SKOI!2fHjZKL4Xf*DvkFP+8#TOyWI;;PPGiwg680uV=Z#;VbQWY~<4kWII zV2;8eXxgg7cl$WHBnWx0)vZf5`b8E^eRWc=;Bi}n!6RzB zyz0tWB6TgO6`*WNe9y{$a*IR{aP0cCM;n1>M0v|n5u%+bo4#?bxq_n-N~`^pmIw`g zW~?3wTt=of$k1_FRJnVo_MeR)0_L*FGiZ40(UrC;zq_yh`P~2H{c(LB^enpk?s|vu z4_^aYWas9puWIqGtW5UYL8R6oNg`Fbf-*)32kg{FoHg->hs?5==c*ZG{Q#DZHD5Dn zZnx=>UnoV(VEM{aO-yDE9I!?=1H`1mRigvEhq{Zq2^6H-tUatAWLYk)Ix?`!MB_w1 zF54VrG9Tq*(345ndi;Q)6>@8Ar+=pv^9~RGmlzotIX10pnIEW7I!zv$IxDy<&`5;Z zux`zi&IoTa;k82odPj&BkrfwB-{}vV$UHLrP*%FPdWz(aht--};SIAWsg2v)x)Smy zTGAhTR~6iNQqRD;T~0ZTsvV#uqno&XZjq_W`A~eCgLxlB(MUtV7!QJnFLlre27R)G zj+g-pBc$|~bY`@ZsE;^R;tI*vq%F@eJN}T0UE@a5EpOq22OwYc}HFk)$UOw4qi7ZH|U&rH@f+w#`DzNjES?0SDzM56e5{X$OZsT7D67Im@i-7 z4vvy-vXoOaVQTt$TUbT;FJayU$UVGy)Sf+|kU6PnAP%G#Ce5Y9VHmEu`;AY2d_WuM z2eOrg?n93qFjRCLhhSY)x$GNz)yYbE@0V+w~xsR1la&lcjE#FfonFxR7D{5o)i#_M>QbQ~fU=0R%H;7lS6406S%5I1k5<8HAi@0K zlF%?yYtH%4u0umhd!|-o9&UZu>Gk?a{c1++H}JeP6s!@++@A%zmQ;6^EXG5SNCrQm zptJL(l@(3lrNJ^zex1vH_9q`Lk8;N_s%U7UONR= zqb7G`pP4vi+^d(v9Y4i=390qWCHqgjO5K*Tu_84XypLQ| z1VDUAW6s}HueW>^-Bhw`!snIbMp!ex=3siw zpFf%e!&!k6A%4E(yfB?2aH7*gx;GhBn>2K@j#b0OOXjDZgHFc7jU;dE=e;oX;$8~U zrO>n~--KmML!}uG(qvj#$=XlVhr598xTY=Iw0Q?d8W~y;8cEsL5fajZhbUHPB+%(T zKI7jf^on*6IlXlCJP%AAcN)w%g;bVDhyR4kuAh_gDd*DQ{){Q8WPamZGrA#*b!B}P zyeL7`X@|UK&5{iakVGfPG){pgrHth*0+1dd`aMt*U^B!tR;WL@xtj!br2w5iZ(grZ zC&wgL>AQ)&XvCkY`yRjzMUja;bglUaF(;7el6`~%0QU#1# z|MI~Wr;Uu-Fxme7iJ>cYQ2XN&0&I_VDm=kB(8R|%_;0IKTvP-xgR+1vzW0xSeW z#qbcZhM@rfkOC&X173-f1_VZ|m~o_|Tg(1*=JkBPoZeo44DBy#_1Jx_BCv$hK=HSg zE5V?6gz&aeKH77RD&ngjR?&pgnazy%g-MkC8`*m7g}uG%r0< z__-@QS0E}ebKvqW!r+=8hI*2Qatp9;Br#?8n|C?e&SO5SQvE7>t&^p@y;jG5HEtuj zefmA~r0KmJa815(&8LjJ^%frq$L2s zU70n5&<%2Uq_on2BMgX&XK`KRtu<7dL?1=>QG^ERb+EnwrRVzju`3mbv!Jt+IoY17 zoO<do_D$OXe2cle#3}0gHFy7pjR0Y$vLDL#83JESXxp+K zmI%3~-^{ZZ?_x(wPbfPRY1V@9BLQ0!S~U!porl$b%-|!&f~R@C@L*_>O$uW~6=LV1 zfkGYRO&cO5^f#fr(q&wO`2Su8LOsSX7&H&IzPZNV|8eHx9&~%fzhzcNMX=^%li|~# zR!RLrPb#B32ZvBQy@+}SZr}Ax+r=DwxXb-(L%m;n#D!2ASx6r;31G@msrTevYHKv> z43-P}egm0eAl^jrR>siXTf)Njv*su6!QgQTR!v|%Zo?M@b%7>%m?hc%E!>AuYBE7c;{cNYO z4&{?rMv4507Y`jkAYkFir=&>A&Dm9$3wKH;-k%+#^1V?Ks5{2mj~b<_8?x3a!rHuh z3(x!a0~hX7jcB_-wyRJcF+jMT?4r#%v(XYi6|yE~ol>0&Fv_#G{&XR+AQQZY%qJGO zT4(m+Y61i&AR2(@RmyncW*Ri6F;DA3G8qMk^C$P_uTF~y`dqUa*IPC5oDW%x|6EAk z?9%883ezj2`5z*7CM+qjq|49$5P5QJMtVBxU3H=}e_lCz@eHGSU!x;jyjaFMjG({n z{U=s2NdAO@Xy$nEtWN!VG-628wq2c=AfgXcvv@{_0Zc&Uy1(#`SoF*W>F7S@D~}aS z$EaX<^yy1zSQfJzi)$zwBN$CgsQgNfyG|p6MXi0Bt`7`N^1Ez<3yc0<)xk5jdy{}8 zhsKnuZ;HXrkdD{JFd8|tAFl%}xAxH>;`PAj!C2G5PB@Kn9ALfU*VPhtW0z@E5ivB{GEo<7@E?Q%IiZP#cSz~r zhO*&ewc%EWUW?UR#zcjuoKMzR8cn+=sh#`7HouOZGoCeRnS zUy?JZd`&M#F$a*|mCV6bQR%2)RUKaENhQX26uT4@x|ScMn-DU3;>z_k z8YRWWVhJh#=9FhA#inDVLO&V!>c>)4gf#`b0cHRp4DZw)=qu?T>?0t0?+9aCj!NAq z_hV9|#txf&a%IhzGp~T?hmRb&2`OVcC8f3W;Ut8a2;L|Ver4=^H-6l>_h?e++kx2T zTl}8!D`fe1ji){h^bNGll1Gjx@hBf#B6sA7Ji0zgWk6r$qE7Exw zM2c;zd4Z7ML_11Ik+lxR%l7Tt#|X5StH%W$di*FtB@uCxX>SJ6*S%`}nVyW{O$+Yr zdido1P3JV53ojFJ&lL3FM+Nm2j#6U}__uBEz3AeF3$k{*p9x3k7M0Grpj}B9hDn6l zYntY0#S~WbWE2cS#N)FF`0#GpaeX)scT+tr?z~z<$JapE+oTvF+YY@IwjM$Us8Ul! z(;EoX8zcsNJ|zCtoDm+FDp1i)k}~5j8VA*LU#S4APvA-UD}VUb!&9qzx6d$sf9Pn! zDwvECVsBCMuUrLfhlN` z(g~DuU6~gMDoc&IE~sJbh3&PeIE&PGTyv*>yuU@Yrv~MV2y}_LB^f)nhlUpOA$!Jf7N5Gt+p_6<;uki4fJTnhPkFN(Ra zdUSqffFy#s^Yoseqq(|_+AEhU`UK!5=3yMfU8ubR?IKEtTf2}z?z(IB&-d-P?>VN4 zROxo$7z|Zqi@JZZdJ}|fP>FF6>8%rqQfq+8A@9v)>%udqm;TGG3uby{)2X*UK!T~s` z;`~82a?^nJkVc(2efk~6q7dahpSO`!hg@|bDiW@Q5hwEwhMwFb$tR4yMQ;q$wZ^Xx zoZzJoBE#3T(B2fZ*3Y@3(Z-Ye_s{4a6alcrkNLoCfC^9{By35zDqAO=o6d**RoVNN_1V6k%?|)nu8#q_S%_S8ev3_{El-4Sf7+<%XX0yY!?x0 zJ+ijc`mh7?d33Cr@9AQdedESayE)eSnjeA7rqe0!GM=)wk?C5GgYRbm28aF)wejgr zn@zjWzJ5FWMXDtLo4Ir6A{G;ZAorpVRK@sd)0UQ8Zw=XkL7Cy${7>IDa+(F_7&2rp zPerU;1)jV!;-V1_?z+8ux79y8k(s`#!waltd^ocx_CtELvl*_Wz}pgeHEOCV!v|a8 zc0ntU?f}R~JvD=|G_v?>!lI`XVn8k~^=J>@Mfh<)fU(qX{Or=Jqu&6Xs*Fh!qM~({ zq#ZLj7Pg8e5qLhtAoRO+$Mgtv#=-5e=K6|(;=ZlA_b?9J6$i{ux z+S9ZC=u2$|?!q-iaTR3#OB6SSbIhN4mc?&%NxNu48{ZE&w^WCEzgv}2!EN0LQO^@B*Rm0Pi z$7S_8kg^B?!4<&7oQAV$t;sawzbow0*3;X_5M1srXDdswDx2kkI8+P3b}1XDB-v&! zZt%eDvaDL)^lI=!v+ug@Q{zS+iEOY* z@8rSgCxPFd!9q9bV5|s^IE_~Z<>F-F)9tSm|Hu4|jEnO$jG50{1cOt@XBVhf&`}y4 z*%6e~X0C-QR7t5Iz@^oP6j5|B#I=N7%D|c}KOo{srk~IRKUk0;R9g)Z!R`L zR7SGr2pSec3@j7g@pLJvU2rOt4UALH_ot@Pu3M$!8#gl0Wo%YN#D;%XJ^ehT?v-hV zW^=6cHdnK-dL*bh)h_)u-86R<8}}&l6L4{jHicYX*$AmQ8PmuSl*l z>C@*mGcyL^>5r?B)WMc%?W}oIyw$-Gs5OAo5*cP{?l6wbmmUwSu&3V|x{k!iJD%$! z;ak1N)(hbpgIr!lV;tp`J!dk``Hv>)UzNV2YpKv=p|b!O2sFf#<45eM+wi0^{83Z$ zOtfTc8#X57Tkt%tzkJ!%(eZ|I%$sh$`lX1fh6xXb28F^!wDg2geiJ>KDb>@RJK|$0 z#R`P_G|a5gdR-c5`4^_1SZh%kdpQeE4GB;>S<;LzSW0n*G+YhbU)l2)mqFLwS$#T7%*sp<# zJSbhodx2XJWCk0ZKo+g1_wH!3$OZ@wn6rokmd_EoFPBLmQD`xni=k#X_MNd~gkB^@ zX|2dy62g(W%Akatrh0x0wP99Gc}v+q4K!qPt76!I-$g?6YArt@i5*#uY?XW*ndddH z0qLrMOi&Otg)&eG9umO zzP?>Tky!pQ0#+ez3G?cHayzi{3jwuzARb2o@yLQ~nZj=yC&fI^kT{emH2AKEVy2d> z5BP;!|Eguq{?0s77yrzGWwN_kf(->S;0c$>q!M(egc~bFHzJzYs>77#{?7m}qwT`i zc&vBRagL4{uW0RDEd}JHDn- z(iC56la}QZu^y+R)t&hY*f={jB`c+j+a=UN{(AvB(ZZ+(<@3VeW#9akRlkh}j4Gt| zUBIuvW;)6tb{$t^%0p8*f*KDvLDlP?dYPXn-|tLtjm>|E7Ze~U<%6<@Mm{+~DCJC; z`D4RB)ao`Yr8XC~)XkftYPue9l|oLJc{QB~o&&C*FS|m)6t)t)0FeM=7ShO)S18Ss z$@jGRzP7Bynm_SXK*Wg9rRNi0xbUiWWAVwkwi%r|?yxd{A#soC0>I9ez#J2j z+pc=Bsz+E56)H+y5nKnyszWQB&h4dGK}#;pAJa1qam+%S>ZS~AgB`$9Z=dRNygBk9}M<3Qo z$A(7h8N-0UUgNjaq{^2^JV2(Puv63=TqO3dg|*h`1Qmyuh(#qLJZVg53*T{E z1dO$_yUZ>*LN>AhM}S2cOVV(&PK`_}sH|)RqO;`hAhs8QT!GA5PoBJ&rr0oQXw&`! zX4am%Y#O&Iv3vKD(tfVb9_VMx>!#_@(#OX~_y+_LeuLMy2>>KO<0O_{M93d-Vtyp) zMmtD#XBJOqBRd9|V1UWwv|COoPbA*Y`FnfRh_BS>nMHYoMlPD6D z7`pPvjCVS}#hPBTdCtzO4H4tqxqH_N8@?wMhTS@g8Mm|E1mkW|d;^4CcUT`szLhf7 zIqN}vTa9Kb^^73RGaO|5cCIK2(@zm%9;?($WE8doG!N&Po_~iOO-}v}I448}(F6v6 z%Ln#`V!dX<=~19!YyeGDpCqbB=v5*L=X8k)6iHeAa4Y%MkQl^VO`d6|{!TwV+cKwM zJOoT3q;o>E;tOAlU-FKwcDpx6UwuTy*}r;f-i;g_B7#1ycM6S2H*It~C;iC#9j=`r z3W-e&MWf2ad-aNJB4BC+rOOMC6b2AS?#GrcXtMJ3xw8d1l;uLB7Qri&iNz3LQVn}g zyl=i0b>Nq0XK>24Ui6H1i&i+V z1lHEmCqsL*OS-GPvKipASo>`0V3Ihlbp5x=>K_+3m3MkGqmyOkP0t@@H(qOZx}4QC zB(A4zS85%SgEVEJtD=v+uyQf-qfJ(CW3se#b#1!OifR@N!H@GJdvPaB5Kb@<=AtQp zv;_C*|NP@XZzJn78edPhQc~!O0V`8EMyR4;^$MIyEiN{YKxr}s<6kjS%Q-u2`&o?+ z^-l&z9qHC6=23zoCAVx}?$l|o)+vp!s|*=d6050{T`PxTHAg9kAD$f;8+9cDbyb6( zQ#%qhu0kNghGIhA+UpdNf%O59?KdYRbO%aRtNy`D$-a!eT><*V#@t+4davVNM&teY z*_rJWKI((j2Bl2BSb(%ac3sHanJF-U3M)Yi;7pW)ojY8kxdkJHW z0n^yeD~;{5E9(uJv^_buv?l~?(Rea?fxh(~Kr8Kr*r8EW%0>-hqLlft!(=}^lP=T&G4;KERUJ)w6%a>E<8dRRwRDa8oApf-NqX-6NN)J;<&Iz1}9-IL} ze?UcT2Aee@Ys(0LSp-`lm^P-8pNVRd4j_tI)?Gy1JgsY-?k8D+fe902g9z`_ zE%6w7up*(`li9%94V|hX&ywah{&!q2E3da#>XrMpc0|cD^{9z-d$Od|(D2AO6F;`2 zNB9z1P+*CU2hE)9Wo!TBTJ+AHwhI@Y=+O6iP7b_N&{l#wWk-*uJNz0>K_q4}EvlZ2 z7x)0@9<2l(t(;3H+f2)DK-ZB~++NgvWbYPq38Nfu>A1(bD=PtvjQ## zX>X@W8alLd1CSP%r%e<)`OoU)cqx@*FL-pHZ)uV2$Zky?0gsVG<^nv;=XC~d&bU<2qDDpgO5j*#>kx8 z02!HoG{|PcDB`{bMvAO;Sif5%P6SEHle@`~-Nz>wku?>UY@_F~Kzjhwd`Ib8d|_jB zzge0g)7-OG32O8Gr{b}`y%-K!U8y(%s16AzDf@M^cvQ4v<%tdo0+X0o*PWgt`;^cu zM*u_5wba0-w9O@epdS?#Jyp7YpY!_9tH48K0oj;By+P7<=%+^8%iJ_l#?*8#Y|R-h zW9q?6W`(agPWN60omaPMl=y5gVUU&D=rx-3IQT6yEl`+V3mU}j*iiJ3@ur~oyKZ9( zE{X)ANvTGXsPb?VgaE(LjcO6#v1!ICP5YO|_Bjppw6FYe~^Wh<2;XWs3+c0IkNB4oi6IeiVyFX0KG@ z-TSxwyxpb8C)NGu#`t)jIS-5_v_2}k9DxyuLo`ItQ`M`KqV~fV5RD&P+;+rz9QCaq z$vmualTlyk%Ho!G0Z{u=-8LE$Aa?WJ2dD(g(q&3gHvI0rjVrtKWVxqfOX9^IrWPG(u6) zP|;A|YkGIXY0H0@`3iX?+DL(9fV#t{nHv0XWYBo|%Tw+#Hdu7O{GP_OH zOS8I_En27#eQeG@$E!0-&WUdklrnO+IE3+{dB7R97oc7=!UIsW-JG)E@+bAFQHJ9c zv6tbP%gA>(Y+&phrs4PF_rwxwL!z?mmf~v!ecC$L#e{8y0y2Q)JPiB%W9+eYzruZ= z{GMH32vjZYHw(j7Y=dWnUXOs z$!vS1EWB~2SC3)Crlhp50ae0K5wG&Pq+AL(@aMJw#FiKY!L%6epQVZAYg{Tfv?y^fgF}@Y%`ta5 zJ=Yz?WCT$sU13Ys5Ijkk(qcu@jDsd0n(~0Ox}I2OIJ?yIU5MT=^ndDgjc8?#T%4f zP%PJE{Le+dF%PbF4x`tWNo@y%#S8NsG&49}TT@dOJDCU8ZOO{Y>hq=6j2j}V8*IV& zrYJ2t!p{;8x|lpOu>n%J40QPRSf?ac0~sF|6v!%4CH4x^Z2@VJOJn)=3~8?L>V-W3 zZq#noKm6x30tB`M?mnF#oLF0yI#8;%&~Rptb?4qc2W5KIq_Wgh@JOCoF~1OdyseBw zSr>eZBrN3ty-z#iOAPI2(mEPVKD~w5)7aS|t6f}c(^+Nyox)v5y{z8o{o&qMkBNKj z=gnz8Y!j7xDJ3Np(R#W+4*y0w9WVMk_rG4A5WeBI3rUMtLHW%ja|8E)#^K4T$Lbph zsxB;4O}L2w0*{im1YPQS7}}~-L(nF1Z4FrWCpA9a5;3dbZ(tn-kJiYR0^%E96_?q# zZa3jvRRU2R8egB0yN<>kdI0Ed`14SmA<3McRst|1EWfYM2VH4>T=Q>%)Hv7_gxGZ%>fhZR7JXISbH8zIdH%f9Q3KA@1ECS7`u7UH?Xvrad5}>+r7-U#Y z#ZUpUnDw1TQS_-L8J$z1*U(ARV_1Dx-}!63+W3y2mKRe{I8lT4lhs{s2!=mcxBWNE2`T{=WVp-P5er;hv9wdhEKYp}3a01~<>CcH7CAm|@ z8=Q;PNi?5eoiW2!FKZXOvV~2O4yUs7pEkA%HW6vz4!V!OWNuz{xeMG^kb0Zp!yDoX zK(8hH$~Y^DL^L=w^+ip$tW4l)@i7F^qXHCk0vZ*^XZy3=DI0PQE-W0fdwIgE6`$%u z4(wiV|Nfn6Utgb|yTq*^v3`XQ-rmz$(!?YW6bo8j6B`>F#=O$yqEBl`B$4fVa9g&K zB>jGWb{BWa_r3vD<-wragfwwlOh47Gv507y2^uf4oIP{qbsjgQN8A5-5R!>zgP4i+ zOaI+bzuf9ND2PyHO(tol7_bnbhvnH}h`A&kLZwC%AgbZrLzd6q=IZK|wi_(Mgl-0t8MLv4U%DM>cscfscjKYqau2lw=7 z&m+zWR~LLp*DmpW5>IOt)qP z!WO)Dw_hI|xMVu-TwI>NZ;>QVd=-5ddEN|>67H{iO3Y84JSj6U{+UqooQndvb|eU& zP94DS0Ltwpx>7iR-qPZjLJyXR$bBvE!p+l?vW>2o#%b=Q?PIXOrhGv`jEdC&Eku=W z(gWz{5loe4I(C%p!H44ux*T2RSse?JeC4 z6#_=-r>FK^n=*aI=i{5$*0I&U#s2#GZBCcO?v36}z!!0~L?n3Ut4F82sAqz)-qYKX z2#_jmA$1ji<~0~s1KGfh`jiqb48SlkIoXa+F5OIE?JsrC*jp;7ne-cCfkJz+7;kS{ z^jyvwk9R+;&diSu3MRZXt=e~$J*78jFQwFFis4^V8BTh~aW7`>nOC@f@PKw!PX;WI z-zf(8o^%$qs5yY-(6!@Vq_ z=HrimJ%u3RWN2SdU{_JbIzE6`qSuwL^k-orE7PY8W`yxHT|@9n^90M}Y`K>VwJZxy8t|MPd; z%wuXp?S?^`=d|;=%za#7TTri8JfARp_&Tm0yb@cq6;~w*z-m7zT}rWod3 zV&>Gy-53KDZZqca>HsQN@7ytYrKr?oWh-*$+{O;>?OfC>dGEs<>!-Vf&)%-5s|%G+ z`Xl21)YHR1Q7tgWSel~PihCx=DLe(>o>t8(QidbnVx8dh-4aHDZcEIu}JDAvqWRCWRv- zA~ESOKnx`|MhshtSkg+y#&#u4C6FY7Bhn?2id*-Qh74=Pp@7B;|XSR4wDL~2B z!=nRHz6godW-xm)lac48eUjLbfBQ%8$_lK%1rkqD0%+4kbb5>`#OjYEAS(3dKL}FA zrKP&FK9+94&kDq^YNb7$-w01G+?5b80Au6Pw;Fx`g1g!v0wMUbsf-OUw=sG$27s7i zBrM9nb=)`|0|Wcr$+zY^Or=ua-Rc$8LW-OX4?cLlH=mc*{J_$|3t0jorxH|%QHt%l zt*taGPQ?saZY-7)K#WzFUQsiOp#(p;a{f`o!2=uQn+w|HLoLYkej!9e^MIPoC|^L| zik3e02fC!HHhWY!XY_8q2i*=1MjBv330YZ#$VEGj=gE@BWF~cMUq639=QM8hij05SRKe5+ixBES+6mm=Y*QIp3ET72+!&wVOj znTU)c2zZpcv1KJu-#_WM&<~5bTM(+hS$~qVLGj1eUBx;EHe*WYWb zm@|rsTHrh;fq-J28ADFLETa;Vu$h15Lg*^^Pgx+$qqY~0TU|}Xm`o>K?^rvwY7AUd ztiaGoOq8Id3jb7CyL25@7{oFen?XKcY^wiEC1dW11by`bqJ#mmW%TUq?5qjv?U_+A zMsS9!E5d4#IuU%spv-#g&|^~Vf8laP%e5Ef{izkhM{ za_CXvzLxGs#u*?uC?C2lNQ;W~_HBl{+MY4JU<@)3+ELpI!#-vJvaLl$B~o`rA_W3w zH*Xt_ao7A?(crGod8xBeapg_8`DP@wYYu_9va{-#A!U<;=N}EXd-Je*!IqD{d-lJa zHC!mMG-iCTvh(Bc-0_3vvM047hAAiTEETUz5a^6Fk0W~OnXI2zlSyn8k7uq!e!AvA zC>j`e+#fel#1wGbs`oknVRY%73!8@AHeRC*IyVjG)hHxn;6?q7v04?8DCppwMCSZk!lfzLZaqI)yACZ(g0n8`2T z(9BF3KA%z|**!xKYIwU z+a36(+o3};A&e7B`!qKv>Jmgf7oJz|Rsj{oO0tE@(3u^C5^jmAEDOt6}4& zB8BMg*dMh9s$@Nd#3uA4!k^>jNJoM;!*Iv>38TfzOWangs_Eo42F&lgV^Gu~Q2s;N z&K(54=VE^Vw&dVqI%Hhr^m@C#p`lz#AsJ%1{(U)j4!xQ1PeIh5w9$JPTxfC#O*E8? zD0oGHgi!q;2%9}CnuxlG#HBnoM1Y8fSx zO4_BAtg9XEov2VDQd%h5ldGXYL|N@ADui~51`+r3?E2pK{m1X|_+8(M&*%Mqz0PqQ z$9bF`!r!O4_5}0Mh~LXm>i*zu1E784aO|R#py1%QKp+?uiAoH(HUMjMRumOdGl{JL zTY;>H4wY|464J5vMH85Ydjf6|VCNZ(2Qrzb)o2pZZ{rCkH0ko1Py7S+;mS%)ddu)vm(?fTbsX7JBd7eRMkQjn&5nA>hZl!;egMRJ7$4gViJp1gFX#~sDc84Uje9cO?zoc8yQkXqqYkO7tgVZZ zFGLoS!9H(|j~22s6sSif)}`uAgIKUk#seIb&czSq7%|ErnsTO!q`>3@5B-l0eaL~M zjwa_CJFQ;9~geIet=hda-OFCB!`=E&$|V~2r1>MJfT_5FCe&$HkOH}|azbzZFzdU)V;W&gv& z`o7a~)NEs^cz)~X%`Ywo_qpSf$J;4*^9FysOZRh5$HmzYga}?8p-IsfaIZGxI2<_T z%t)Ac$JHfQ>0>iePR|tiWi* zkB88JMAs2UK|(X&8hsgUX5nHKA~`f%^%OicnX8s6jbFvTSRAU5)Ey*@9zGy2kcEWX zAfr{LL}5lNJH#Buv8>Y-l#n8f=jKUR#8XPvv-2aepv(OJfci!79>iCx!!$U+Ai5fU zE4ZNN$7>2-(T^ae>i(P=$+%hn{F8}Zy7;?_E>9J^Gq^?D9rwy8^Z+g%fX`Vc4^P$r z7GUhEf)j4F*#ub^aLPFd<~3!WsRwQISM2`Ndr|$SjRt>PzUo9{%w2tl_t@-9|@F5^-rnU#3{6{#C1dCT)aykBBDPK$`1_z|aSR08>o;Fd|jik-# zx_E8)1^t~mL93o<Tl4GM-(eXOK;l=)|X0 zP8&ANuen>+#2>(4GCdC1CW>He@VOu-M>a?P4G5i`|` zPZzlL4JP&+B7eaOi^4>>Y7)0h)>0E1(u$(_S62JZ1-OM_31lO~2Y0C-g@WgnTAz)` zX=ONg@BwN*8H&Mxmny(D=4fEU1`V*VYGFUvOzk3dxu|Ktqc%G9J0RR51Hv-3Mgk{< zvu|TB^6d=8u#m_OqA8+vaHDF&#+oy$ONSVCQmuqv%I4Lm{oP^!6tET2=-tgd>Lh5$ zV!9{ihFKV~V#Yu1*t62*82UFr*#L9grCc*ezBJ=AGA|7K>+5TswCOp-8kD(_ z=?l<1zdQ)C@?En|qHqCiX<)YH2_vokv#!z(>%3@zrGg?P8j2o4=5WU{8sF$V5GH6& zrm+D1!DLbOcI~!9rf{GY?{)&cQAA@ZY$SJ8Dp)v16YV|?sSU)ZmNO@(24VSMPTg@n ze#$(YyWf67RK6)F&|8uJ5f@P1vo}ia`!)^>F^+p;HzpyrW_puwh4ADJrH!VVewc99 z@n_J*>mRh<<7;wyRB-#j#e+sCultiltTl&4bV*uM-)!kUQWpC&l$jtYB)C>qRTYvg zxj6n#hbNoL3MA`u$IqUv3(h*BDRHSPYgmm}#R?f<(Y4rty$Qg%6-LO&&6Czt$#xKY z`#iy!sg~};tO%sSn*Y!D*7OGt@u0C0&X>wv zyHX!|rZdI6{23BGO#=&_ulNp8N&(jteg1rhuE&4f5zum$2FL~$(4*{SuL&tM2!22m z2~?qw2zx%BU-RepE-qBjhYx#8d?&$qfUn;I6cU2W^?XYpH>`-%0}O7f7MFodk0;G$ zb00*h7oom>Mr|I%9ZKH<91B4usKvXtRtwpADcots_XW?k6{=;iOF_KSxsJQ$_B5J) zr8n5{4aB{WTP%XweYUKYBY-P*%zhg$tYip4U|XXyygc08G89jkE1pJPZaZ#V7zhd3 zS-f8PGGTe$u3G2a^B!nXx4_LUjap8gEt%BF$Vi6lNetxU@f+hWBJ~mP4dS;9F)&n8 z5!e4~Mb8ZC=agPU!)ePQ$riC`e!c$aOG$FccL2xZ&LiQOFdwijF?i8$xc`lY6PMf zkSz(aKn&-}?i>op{1UDxZK0B)q9VygEV5~tq#gJ=TeqjHpL0m}Fny=7WATV@$WRDL zA%%4!6)y{-_U<*wXbnstBXBHQmicv_C;Eg(C~?>{n4E}1MW$;a&k=bs%xgLHgYFq z$bh(12MvzvR`nbj$=C_E3|$?srG7?}4_Fy7#@$kI6a)2dRnr=Le)=lbZg9AM&oN^b z%(m{enjyZOZ@x8FP#_J6MI2?Xc2adn6@R0rXc-mSb2(G47t@PDKe13kUy$v?Ygp$`6khPc_qI6~9%BU(MBA~Z6AUu3p$Xa`%NBp&?j8h21hA~B|TI2Fg!=1g_W!+u6bn>H1 zooLlfr^LtJ7VDz%dg4X;31Epofy1n4P+$ia^b@PZn}LvpCthi-b$!#fGUiR zXPDN$0R9y>SA?jezm(DIiOQS)K{lC+_9i-M%<=IicCSn)pVND0c43<OP;;EL*pD zaWe7CPryq6*FO!a9T5fMPb6mVpz3b>9*i0}QY^ag&=I3oP9O&)U{SX!^O4mZ;~nO% z`|asIWf;Xf@|*W)$f=+`3Dq{Odxwh^Fj!Ljog-gz6B>g#$M|QK{9fI6#*d*>{oFQB zR_HbG*({H@*Y3?SEOr>Nxm@Q_zGV>E+;4d2#gIs2#ww@9#f}?p(_(GcrJMJ@`_uQN zKBUxuCGYf})oCIlAw@{DMT$fMMe_8@zuc3PD|$dq$t7KO7m$5u-tckMfGLhyavWre zXXQULfr2IZlwT5O1C&&?odb_GjC9UY_`5`rDg>R+f%QS>Xuuv}n8r+?5MJ~HJQdNQ zQCLbz3Pd~e=IF$U2U~uRB*M~m! zSpZALR8JANK-9Ek0&ytI+yJSxm~|nex3k zrTD0+Q)RUV-BQN&ga4b#sA57`oV6s7a1Q~;W?ziAHmlukSjMo2nB5ZH&lS)p7tlU} z5y&B?MjY$pBrl$SCI(L65#ITp@THV%MI^!hnIL>K_}b>?OYdd6nQ8&!?cW#N4(~R9 z8&DjzqWZP)iXb}!*&%=)CV;xbqk4dV2!t_}+Mn^YHkh=b(-7A%v;F4o+3qyxD!F5M ztuP@$hS8_Uo^&{GfTF#l3S}gfYhRBCwA;9ouJ&+ht5*FN%{(}`lmv<-X%W|1I0Z)a zc5JeDJwI9LF=(}X3wF;S5D{}vfo8bwND;L(jpA3Io-J9jXa(#<8z2k_MV@&6klfgCs=zx1)9N+zMm>m-DEHU#&kVXFpi;OU%{zF2uEMnb z{FyVO7dcb&UQ?>vp=q2P_8|q`kDJj*qaMIo>>H6Xj_8QJBWj>P;3yd-1Sa-z4m}F8 zM+wNR*$QGUVgyFGkq6LSA119@CwnZ|p|i3D!^8w1B-8#^>Ubf-wosAIqP0NqvlzOR z3#{-moq9&_fATboFFK(|_tajW$H^nJ3&VrTQEYT5JmVR7B3j)B&{C`ljgrQh08S{P zkTlY{yk*OlM<5RH?G8jtAyrvW(;_WF$}0+18IBP?nwDCQHWx$eJP95>%*=!VmoSW) z=swTa*(FS7c6eR?(|T}ks4jZBWrQ@iev$A;gb{NDSt2Er`e+N%g>)$FaBlFqE;$_x zc`{Qhcx`o{5Fuyoq*U!0mPMhXA@Iv+Hynf8Iv)=Aze*U1K?>nof z*IEDgr~8Kq!AIu27LbWf11iA`&`1D6(yQvVZ;#{YfH!s?S>`ow-YLh?zkdDd z%;qPhmhLGZf=gtd3=$Ku(fr>;0)JgAZ*ezJU{UW~IY0r%?G$HC_GT3R$eL@_7R?R3 z&AEU7)pWZV-_c+|z}TREuycuH@&-H)m7V00Vfrly5Nr>$JhQ%UGT{&XpWW!uo%;6WiLGWp zai8IhwdesMAD~s4=G7cDWOw0ECu1Yms}r969&kB0bK3Mczx^Q7BaO6C7_0=NqgYMt zeUwF*Ow5q@Nz;4Y2J~av4vRXal+xg&i*Os>5Q>6oRKT6R{d@ z!1;?g5POLq$|t|lZ!d-qf}YMIHPd#@!g^Rddne0jNAxisU#m=Rj*uOc%whoyeu=wq z$jNyQfK)K)#e^rBoT4a_Nj64>@H%%Tq*I<800BY#=D<~X0pJ^9{`lX_Q2uaeEz(@%jxzOjg?_mg}~=YQ{wyNq>YGkIaPtyGg#bA$v_sphXH`Ppq4Ht>Y6<$$F36i&!CITIxdC!bBa| zvSmw0NHyy*UfJT<#Y4|@nx7fKZ(}MhgPhCw!c3Gp^h9s>_>ZJc0Qf^eI&;>n4wqhb ztTRGG=X0}rgUG4ZHCxyj*5!^K_I6dIb^exqr^BmHWz5rHz&@QiO@197Ny-1FzoXy8 zTVEomxZwbYh$1P(+{>N)FHEq7R`-G82;gKQnnU2d6CI&wfuO)`V1@4Q44c{8FFb4b z)-?aKON_Thub(~rX|uV`v9oLI4uD?!xrjRkBZoI`-)@Y(2;d>I{v)&S83Xd65ic3J zWV*>N^%gBUDD0*5X0EbThN*w6mMxW11k@DUKDx;6IH zSzJi8PBmgKA%i$1vIojA5unoa%hqa49Y?~`NQ#Gvy^)rtz^DYY2;V4${0I1ee|r;2 z)Nekv(AB+1=asnPn?529vHO6n5T209FXq2zqNb8nm|(9WJb{7XoXi5}u)bAEjHKjk z!XgVQ*Gb1rzj6=-XX>{g-{@iUiO?Nle9mOLx6@Dyl!`aWOR9fbrjOuH=z++~%A;)w z@F}-%i{TDP>TB!Ile8U^Q1f#!4j(yki|<;pWMBeom}yvbhUZM)pL_IAr?w&b+5sw$ zkG5;saw~5L<##c$gD_$KD=f7+lehRUp&(^x+&NHq{eZ1QJ#6$anMHRUDRDiK^&*Eowdin;;}ya^&ts*T{b(>H*K-6k=?)c2v0 zzWn;fZ3I?px+}FF`N#ais@9}IL3IHd2)x_*5FD%S<2}yl32TkRB5p^G0D)78wC{5h zj^_6zL(7Dwb~xAwynbv$>A7H<%!ks+i%KaZA*@#vM+KTr3_e8#z8rp_MLMdjc4QM4|4 zdX_Dls3<8F@LKTn@h8D4ZS(-*i|=}}HUq8~^=eBJkSqu`Z#0sO1%9Qhvp%D3s(8ZE z(dqbJqSKQFrxaHrMZh65RCPakx$_ALZzwdyFOYN##c86mCnM`1Lr>pz%@6Jla965q zeeZMQ;DGIc(Q6;AGPril>g9;8c)AjPR8#BEX7Q?{;uv)gDe;w8W!1C8+%bERam&p95$^oz+($3W2w9R z=8c%uvdiv z?LnfqySceR?#JtJ_#%({tbC_Cd$oLT&7;U|3&E|iW*2#?>uCXB90}~vplb%OjdIGcndHMGJ4kA z?#YuU{spfYfkT3htOyD1j)H%mz&e=zrXxt9pPLCn1;n;>w~5b$3-d$mU+K5Vk9zk0 zQlw|)B`0;qh_5cv_(BD$HdW@K0bx0!Sq06A|2!~TxpCvh;sc6~2|-8LK5GEPfgvkX zPBJc>ulXBUnq)*OE)9iLpEnRtQe9DDsOr3AmC&M3&wB#pc78UrHIa$SkxS=^#6?7E z-ksNz{&|J6mqNT>!Mh=fM0^72*tI&iB=xr2%7s${G((k!ZOsU=KX#_&mRmYwewurZ zUi6WH1CUMvLOOsMN|i2B)zJM*>sYt&ZnKOdX(-%9XTsfQF3jy?$@J#L3&tAwggx`} z)-AP+1gS@HL5rSRFa<>sCPnCGdyhQwl^=v2O)6#U-CK|z6U<8C9c40!M6P+v;XQN7 zLSnzVmiYA&r{g@#sQ#|?B5y%bYlkY)KwZeK1~|OXPohjQzo|&$Nkh2d_&*O;J$Bn6 z8)A&ZFGSJhnwmN&^>v@plibZ$hwGTdR(OG<1f)EBHp+ALsAU91S@MiTiQ4H1^@^;Q zooxDgokrH>wf+g66rMj$ZsfWA%xp3%Cgi8@S7&yIaAy!z^!d_A@NHV6ZRJpaWhti| zqW9rSGd@ehC`;Q#%z(PpiYwHv-GMc#3DuRAUu&v-Fp_HK)~VzFroM276lX$yg&J+% z)SSGLv931etJ7F;W#q8CZq1>4WqLc% z@yM6%eUBJSo_p}<(M?*I$vv}2`Dj4#Djd=1@x^T?U82k2Ex`LP{*rG_H+By& zNmODRPkkqv;>>A3-O)ht9? zcZdTF(8^wo%Sk)6UmTp|r+HwTUAMfZrcNHt!>ME8<>6p~0<2*Q`B?z=N-0J3Fh=8! zG@+y>&p&{aC;0>-C!n|)ijb8UoON9rw>?I2dj!pOTE`oA2c?ii1iy$7=iS3NRg#e_ z*~i;y%*)|pN~S+~mH4Tv=dc@vnO$o?#;>hY4bNz_>+3XBjtHtkofC;?4Jo$BdEzdG zkPg@km%*VtYp`-p?ZJtkLUvs@nRF(HPbYSd3OgP>e5jm1D#-P|Ic~G+{B!V1uKxjPS$PJtk?ZhwLc_zyADii!26SG zIPM-(lGd!e_}U7@n*lsOmLG@iACG3bk{<(p2`5y%dTXa-VY>+#CC8?>5pv>@E=m_K zuVc>U*CB|!OTHtlJ%rZ|G4(x*$C0{!8nPzv<3=sj>4$dd>pPF#H*CDozU*bZEdrvA zk~XFQRo~xh&?Z<%8zrn7&jVOT`(+6Vzycs!zV(VEE=L@?0UlFV+o;dFV!eUr^HrNuElB>!#v+CdOtr&*LL{Wm+$Q>E$q#x zn$T()kS%BI@jb(OML-z-rEs4>1p5zr1W4wuol z`%LePRE~d7jmwOo*+@sq`V4x+a|zku^(p6@Qq_pKlB$`Vp|&CdJ@4J?S>}hq2VF}0 zjx{KH(h&L$s>X!7eiT-MZdG%I3(?^yUz*p|_x60uVC?vZD!uPicZ6s1VDeKOYoWQ7 z8jdj^@u6lLJ@k?>Q5Ne*^K+1q&`j4u)WTjnmv=eO$$->zvuNIPvj&z7N4YN`7;3`w;`C0gzP5H!SxQYje-T6^ob+YSPd$`ul70n*3-5v4Hc7KunHoQIak(;2BqdWLtz=b zUocb^#CpaL-vF=lU_1pd^#;9t6brF+`;dBU{n14*C0G%f6Ih7frmIeZ zRl^!lwY+uyC2}Hq$mckr#O!#(ffJc10y#LTjZ+oNgT|X^#V!ndv_$B9u*_M@zjYj= zZ{S~kpf-6^c=WeB!7s)(^WPvba02%2BSfI?drm)8xl>oeQk zc<$Vfra@cz{5(NPkz*02`)26=N=8G1O!lCAkE2XX02b-;cHv9tjZYR_{;|;eXtm4X z*y8D_$p_(@d(3@mT9{_69V8A5sDISW`U2k35Tn45LI`jq4i_7Ub>*Ks{de_|0es#e zelhWQODAqC<~NJUGw`#lumC#!hW)whAY=y$35UU#-I!;h*a;2`d$j)A-i2eI?>cy` z-|0?_*Q2~_fX^ApI+MZ?s%qpxoxR*`=5S=KRQZp~;BvERy{W&l)!d4=04RwMI^f_f zZowWjD|&^j?+N5Oa4<>3^#E0t;t~e5|EzoD0yPpHQW*L&9j_1lFlm6$Ap!Zt#knW7 z^DEcy-+vD{WT{coA5=!J=dWcevmk;GzauWrkk2RcYBCR|+8@-?`QghGM)b-l+J!!d*)aV0=#$YIg_0tW+pG^0=0{brr; zt~7fM>?4(~Bk{dIl@%|B%bQmAOMLX_>{#hm&UT`gM)Xc?9R6_`VV(a+spJ$`+5@6B z|3-LQR(kVSVx5ln*#C$L-ZdjG*Aqk>Ewh+h_cIk^C14zUg${w=kp4vwN4~{qI6`kF zhSKKL9ikz!YOQ8a;pyrguTAtTu{b;?X%WPzuH&t)E*8_d*$C=@hr7F@{ z@?2HRZC3VVKvZTnDOpraZ**O~gP+u5e4BNO{38!ksNBA5mXYs468Y!;J1@Z%xg@P= z@mniw=gzHXp6QxA?y_^iAz!7eW3^YZFEN_II54GN2(m)i;)GejChO0@E>3i-JzyOm z>#dl%Wp00MlJ6sgCKx2w*Yjz4=gAW-Zfs)C60rY^uOFGXkKFanzV_x{kmDrU)zr*P zW0yQZZrS)HCSu`wEEk|s@I0Habboecx?n5- z=_SXPPHhRL)w16L=N&2EDRASzkFPaB7c1`U*!W0^hxU)8kqCK`^b6qtq;WSe4738^ zl%gE~C%K$wzKD&3Q&Bc7%)~cd`I|+ zzul|t?vG`GkB1s7e!t-TOQX9fAcX3q4bSJaXxhE8GP^)pNP59tATUF41Qe5j~J-N9et*ZLid2hBnao+-VIqvK4@Z|a+ui9TD1b8ncP zhouxPyvz^y_N7Q-j@!~Z;kV6|=a!`gUYj}{@q6WC%Z1_P%4T)QQlUYKBa}stP>fLa z$p|l8x@@A9)!)Eo*3Hh-e(-nYDWeJ%F%%6eP1j}uG<}lgk!(4S5+TVKG91FAAhamn z;Bq`?UXmv-UAxU{tMUTogAgS~(8s#HZ&uR^nHv`oPCpt*nQEt`f8~Vn{OIA}6=#|n zQHU7rY`NU3MZhp70=I}t6Zaub2ds-5+R((N3;x)VxX6;lw zoa~^>=1h6T@$NzUYwicDz9e+I{QT1;X6D~p--Y(3lu@`(udWY#_8DO~Y6Ykf-G2Qp zwOt!pafqHCWZHJY21I;q(Ie*P=d)5=58nh1WHho~x&RP@@NAPzUzv#ob8Efo=ci0G zVt)1PO|?5}2aO%4epv62qyBZXVRlumf4905t_i|7ntwa=rKwhn$$a-n3 zzyA0UM~T5sslm6+oWScwmB4!d$u#6(OGhx{`T%Cl#OFTMp!Ob<9@1|9xhS2H$L%V}br*XW?;svtv2ft%ebt?-=An54V z=PoWDMmr9NSjgkOoS29};TC8ca};BfrrLm?b!_rT%fLv$EP6?dsWGOEIBHW83{V6= z4fQ0W#S}N+01!G%_RCS9Pm96CMjGlOfL7O~haRvu5xKPg)0l9zms-npXYxn{-kREl zD4I=wgAza-HVJCQN2F3iz(Sa4#sAnrbuN4d zz)iXPuVXPWRt^r^LY7Ws{FdJiitgTGLU$8HoUWu-G%^Oy-tM7IN6~$G=|^p89sb?y zW<~pLPC2x)(P^57bh9TjnnRx}LHnkpSbd#O>o304()7XBP%xcyPL5)t#1(ZdV#uSG zsj`1fmJCS;fkwMSbU2L{+DWD-D%e%U54Zyp#DGE@N{ZA!^m8KtWsd{tQS3oe^?qh@ zn~PNP#igyof=Qb`F6^kX)Foh8R@%iz>8l3SzS=if5tl0mkM`5=N7 zZ#Dh(9<-R&iUysLeVCm#R#O9aJvnpO*V$2P7`LIDum*%9^tlf19`3lpzCo6H?b2e; z<}3yhzK9=%7g02Fi}ZDEDQUU!`w*GY6L=RMdJLf<9ULmy%PbZEV1Ri+NsPW|bZ{LTy2_~j5a)q6j?8W>h)g{mCA)N-n4yDl6b&sj zms}&^2q}eR9X#a##j8y83@KvzHw`9@fKpIWk}hISAQw}!J2^Qm2d`RkG36db`5r{S ze5&kT+0UsIxf`9_^4-+_(B9pA@nSComrmx?=4K5U-N)8`yv#oA(81Pwn8ZvO!9gC2 z*W3wty``T41)Hb1z?f9zOaahPS0z1F(U;bEOjO2K5{`DmCNo; zhnY>;Tcr0UNVm`IwN=N)E}Hezr9;|U@)V**c9Dx0i!{J@y9{Qp2dK<9HW*SMj6&g2 z-fmc}gmt)&LZVr2)6X!xfea#^WA@0Z;sUuJ!MMwUfixMsY;gB3|1So7%$O@@zzmB8 zBx2drq&{sA883Mr7c(=WJRx>dOw6nud15EUOUqUaCudTK zBv9D%hc{_mR1b7OebW`rB?sXUz?$3DQLJ+T<>*ZRCGtF3D*WMmdG3YnWPTty0EYmh0XtAzl z1>*XD7>sZJPBtRJ?2$ni`}l-SV;g{RC`a#7vniHS2nIXbXT9Dk)cJa?m1;$JT+&+! z5Qw7EwC~y1QG@qXk)RG&u+AK@h%7Wi zfxxUY#(T`*slfhG>7{X#WkncaI`db$4IhK9Yc`Y92=hbw+*xoHaZHSbJ#h^*La!oq z2)!)tW-<;U8)vAK?9h@ys33dyXww861Apnlp_TmoZO&|5xVZfAB|jQE6lD zDJ7*oq2BWH@{)O5V9`JvN+?;Ubjp8rdYUcR0&CneEz}+U=N%Bwv9~U}nU}YZTq-z2 zhjA9i=c_Gf|2imearXslw`R@QI!)zAw*9#_Pp>@h6$ZdNn{Y?nQ6EXva&ZPCIw0H- zTL=-fr@tubpdA!BWbKu&Q;DJ&Wn|-vK}DMLb4XxdAZWPqTW5knQBl!`oyKLa1O6Tc zwf_zS5Sk^j0XYm2s-g)bb(M0^*lT?0#vdQ}e7;x@Xe+c2+029%_f~-l!VaXbDC8jt zQReI**b$@Jt!njTwkX<%c$|DXVe79GHy+0AGhbKJU&i_%F2xRoegQgM6FG|#n~PIZ zebKU?W8Q{N&cD4$#^c9V*HoE-9lqg5qGrJ*Z3Cm{03Ezb*mb|i8zx(O)<@@|AOf!Nm=u>%4=$V)ox zMPCc7XgH}JV`&3L`>fQGeo2f$iF39|S&vvg2F##hm40^k)AjAzw%vd9Xw^NceNoKQ zL!wm*uRa5r+4Qh|+~oc-Hao2I-FIkug+-KuTHD*u}*K4b#}@+C;i!k*OdnMQ%A0a7w6q&?1k#L9ejdV27*z_c{EI zdKgw+tg)@@X7TD@{o@M9?Q({Nm8T6cze8}OO%zlMiUJ*#Eg~qj*1d1=w&`b`jySa9 z{RG46Uu^J*^O@?lngb|uCLX&?X_9DV)iNJqIOkqA`B5bvC1(KF7q9T01d+_85Gp`~5c(kT$a!#=KF4CjsTUN$!*IJB?+{acpDo3IF)q!e_a z&!HZI?eOO3ZF=>oa@Uze>d(Jii6+ZC1zlopM4)_LmmEZ7gYbvE0QeVwwEVC`f<>Ur z6ov?4v^7#)U+jg~Uu!fU!d88ooGYn`up=F6ed%c1@jU+2kG2#B#IBgS|j3i-x}9%r-8w$WWg zeA0dMP?%8fckgz%d1*$2ERmg@nF9Tz`0%1Bc2a)r1ui+L?)9;;WU(E~2Ie&4+=TpNt&xwPmP=_C_SaOu=yPI1_O^Ml^ZK zWg~fJ{-=(!x-}xl4?PdLxn6Fg@DTIRIqvQ@h=UWlMo|$8F+@e4@LWsO!61cBR3P9a z>w{`f@@fT=3~yhtDLHxlj?)bj$)m&J+?pG$W6ywWHHmba$Q%rVyCfs5OZ8m|1QZ>1|1mA}WoQS*s_U znjA`&6$1o#01LB{8AzQ_Bv&k5!;uu-KA^Md;EiUen2hOE4}KXFKlA!AQ5%C+#PqN9q6Kxuo9rvg#{G9R zj#};KTgf>VOFX3PDub39F+%7IW+0wb)JHvL?P((dF0MG35dH}_k*>3WI&1N2#sEYN zKR@scPi?VMcuC1%pylGNm^dntID{9!QlP5%x%c&B$ z28;?xpgQ|ZfaXjTR+0#09-8kG5+0sL*Z-c*;b88NjJA5nJOI-}~PXE=v>n~Wt< z4X?xDK;I{71MM;;c>A7r&5i}S_N;xdu z!b5lA%PZ-S&@_vQjt5!l<9vD1Mh0kP=$}LReVTh8hy@AGDw-|bJ9{16yBAXDn6pPu z#1!2ov$NFN)^-bLL%G!uvX#2J*`GKY{T9Rwz;9V#f`9g+B}>G)QE|YKP&+?RNoWms zNVe1>v`jrApaeYOtiWWsaTo9a!ps9>&ZS9R8qk^uPyDfZYFh~JO#+Qk-nP92iaMKv zfPnQOx}&z2@{r@u^VDf=F>VfT1ki@@sm!m5PZ5F(hCxInTu(e>U%VJF>HVo9RAvn! zgM}F2O0oCt{LGt?d7dBNrtH@p`O2_n$X_(!Cr(m5^Q`tW7a$vAxL=|Kh?#i&zsW;= z3KG~l&SUn{YT$p=jyE~$q6I}Lmx{ppbuhL!Ud&ecA>RNW^}d7%CxGP1J_j9HUX8si zIgKP+@b>K%{!UbsMd!hNwEmfAx)ktX&%Kx#*JDx@K7;uqI16vCnej=#L$6~H%i4Tl zor7CI&S{F=K#ZkG0*f8=x;Bd(E*{6=<Pm!9uwzeygOGb1Wk0V5utx4UzLhr~E*E z-jqT?R&b+f#mFEm+W7h9rJYMZUmdY+n15xlX18^#hyPId(4^;sp}#DA@A9)LEor$n z0n1a9$i`4cRk`~ug3{6P`XG~A@aozKz;23z+ZH?hjg<%`G(E;+&K47V1PZo%fL569 zrJ%5|!#o^@{D_*Qp&0ZVvRMxG5@Ba+U|<6?9crOjxCc+j=#jN~R=g}*0L#)Dpz4K6 zhRzOyC{JMR)a5pK8^FOWlFc@E?nvpzf5pNt%J3cS*4rzu$rX+)KS2gl6Re0pWiN-c zf^Tj5gc-tA?ytocH~A6k&&_ogoS!UNuj0uEJynxk;o-%bz3t<}lAGzj zx5)K#vQ}0!FgKsF=uzdjv`{wJ(){+|E|BLGha4BB28&RErJ#lF&v@%m(#Rd9q7oSp z+BhN6Vj6~#?$`*fFk+W3CXO=+@NHQnKsn!&WdlfWk7KOB@gs*YV@F+}4MVsAtl8$BWSQo3 zU&P1ptXdc1olhfMRtZoU{R7io(d+DY{~8y4b|cC=2tZe!m(98}l#XwC4rnbq1^GGB ztI8M=LK-?1KyYGK&V{yX!0dQH4oKwam`uyRmFxy!VH*ScQciyDhsIKZBTRhc$x%m| zF!={M+bz7>M<2eBM9y;R9Op|x%x`jRL|(uFkij3Bd&Vn*Tm{iKZkp26&F;PwlOhi&@*lXorTaY)z@%}hlNqVGU z1$}$SzfF9riCA#*mbI00Tfa5m5UZyi+F@7xu}On#=S|s8YsrZEP--o}V0GzdR?V#Y zXZx*BK!fV>f$_Ri&aEIG(1CChY+PJ)(L&*b5=aY7ibAy(069;!A#<_z&*GOg%C&iZ z<3>IDWY;@M$nJX3)0&25+K9xQPEl3_&a*hm5JxI>FIV9kosx6%Ylc5l4;9kOrF*Zb zk|9r??|nvt3B1JRp-G=xQC~2bF#XKbD`vGw4Vf@Ub)K`#f`(KU7!mKp^Yi@q#XEvF z10n%C+EX_{PvK3m6&lZdpy~LwfEuz&2_74Fo{X_uG|g5Y1mD5ms%~3OPd2wW_c#-x zHm7#a57WYA+Yy;p{a!~fcy79>KQmj1H+KO&#EZkmXTULU-ujOAg9EYTat{i<@bQUI(g~6&CJwEl7JeOsJ6h70X1Za1S2#-M~<){F&ycZkl${F`0IABLD*p~N>03-44^jp;Gh6%AzAss9p&@9qE!9@1u z0@NaV+Q|@RJt}8^uvD5$?}pv*yO6QL49ziYn(HCvN0hcQ&Ivx-i#ZJV?aP`Wfyo}F z3Z64uzqG2G((vq+%FSKzvN^hZ_Wu3*S-wZ5HIN%$s@r8FJZ_fSC56U~HCnYYzBG!C z+Al|DwJ?HcBQzP0zaPh+~Ip2bTgHN#-R>u4GFfvcS;nV|8{21Cd2Fx38)*K!Ap^ zXH%vkWi}l&C#g&pBRQ`=y}p>n(6>()x2AOmcrb*B!>3Q*f#hRwJEK=cjj%tbPC4*_ z>r2lIfm7w4QVe7RX4I3bkv-`aRZhGRh`gVy!LN0RuS3Lk(b1{2cDf8XRn8~)hfhmK zaC9FmP^MogK`X8$57RH?h^O8UK)x3-!J9xR!ertmaLWTK7#?e&bAv!!l=Jf1pgtkD zZ^$v0rz9bm>iN#S3!o`0wz+pAyq8kWHC?4}*xrK&yJ3jRO~1Gv z?_-Rscx6s}fe>N<@za~1?~B5KW|wFo%Y9h9l8r!iL(a2G;wB}!55s)`ufVn(C>C;9 z^R*cXX+o_P!wDr65{g?f4=sZ+aND<{SN3bVS?lgbgIm!W14p-$PFtqUNec3#ARmrV z*oSr-M7H(b=t^f#^52z*|MMs%?KS`~d{A7&8o=RF8B(hFHF?8s1?ZQEnb+UHeS4eA zKx7z5M8voAb<|bxChd&6E77n7?5x^*^7=osgg8JrHj6w-M`gcYmO^C7D%fu7;SpFN ziQ}uhz493*Mn+0&=1IYdR%Zh;v-InHv}PKu!O!n{Nr4W zp!COQrtjmkhzYD-g>M_CL(y`e@ax3dGddBPXJPqZ$c1$$IGv}v+L1KI@1c5gt!vI* ztnKg22& z0Znmg8sg!i!%rlmG14_Oc!|KL@(nA6X{LeBCNBAq#JdsimBxFM$(eO4imGK!r z7^|o`JT;v1Ssc^|mSWIQxO(sFvS%2OllB%io;b0avcdYH z!p5x|C`M|_KJ6*k3ivzA^Go~-)Wbt|K>HvvSxas1fSk`$&6H`l1g6^^gH@)Cq5B zDh1g=hk)$m+@(vquWn_aVJFN{=I34vZVEYEROF<$vMo0UH-Jo@QDl!<4TveCR~JPi z$8P5A*<9mxgjR?xA)iR*`&3r zD`QlDY}`EKETpb9z~W7@zP75fOfX`t^Wj4lz@eYnb;PJ-xPQGK_)@(-OkTg9&)xag zev}E!JJJ4rWq$yyq8(dRzrN^VWE6e!WDwXp)*^@2*VV3^qhjsh@|CRSr|7V3Mtb6q zw=SoyzGb&MO}qE!m0g-*hPesSfPJtyFAbPB@HWD~#jGr#NJ)d{xc~TZ+KU%cGwvb= z+D8%mjVjJG^+)<0;geVY>IO%Xni|Xf*l+H$nX6vBvW`xdSnBh*shYBKAs{fnX)_;M zvaq<59yl;PX2+!ewmXR)ZPFy_jfV-IV;GGKy0dfQEeInDY|YI@DkFt_A)N!jPtne( zN5>|1yzG}$$XK((aJF7@GsF7s%5_@Shr;@QY3ESzOrdDpBjeMjj51O``MfmhUnEr~ zry2Zp_u*|BaMQWW`w&7XRIJ|Rg|Xy*#W!E#Uh`J10w{IB@9+HbXD@?Td%l5oCmsmx zZe!yw{)d3s&_+S-O4g>@Z-6Rkq8Z|A%+R`+R)MITr^gT`j^Pyr-7nm~XuzNRI!54p zn{54b84gDbizjWU=taTlPR9CP_F9)n09Piv@I)4XdRr!Ox$8Z!dQS=K-yMjLFMSkt z#rkU(bc~C$+6=mx5k9xOfx5BA#4F?a4emAY6e<9cl+cPIQWjl7*J%@#Qr%KMb6kay zrM&M<(@DD)bK-=F!_c5%`b(B90o;z}eal<~FBx}PcLAxv;9fn6hDw)>{TNbKO zmb$vOSlc~j#ouPgc4e`yfA#eB3o30g5|fO!niR0n z__LB=&{tALoM#-pTRb(rbiWMULAdx~Q0ZJRq8-3EM~rh5fJ+USvyq936SAlO1bXw% zH|<=52Cfs)&<#AD_)(w0BF@_|%hdAJ?{p%>>94>)9=QdJeiF$DPfo5@5*npWA=yWJyJ92+jnBiMRMLLkxZUC{h}UaWIPU% z5IsU7B4I8Hz^FNWy!Pt5TudPn3V*5Vmc0&A&y7~EZ6QZ#`Jcs?zxUOR?@_0078NzC z`c%x6iI1u983|G2^O6SxL8ORE0v<7-39Q_TO+-7c2gNtph5inHSGJj|2Z*&jPt*G8 zo8%PIq%h9F-{9C-8JdYT1h|Rcj4WDTbuBF$FbwnzD7CGXQ1DK(B-W&Npw}YSg*&QCF7&479e&9GsWeszRB@Hi-R9k_#efCL_hToeQ@XM&U?&2AF5y>pDZu@QwW zh6sFsmu9nkcxBRE!p#vn79vQDrt^-_Sg~U^3C*tz*$JcYZ^Y%SJ>cJr6 zpZ~1t82@WE`G1O82=jTeg$6Remrtn!vn5^JmX53}bJ`hWTBtkg?e%(XyIof-@2JW? z$~HebJN~Gf_zspyET0KS=TVqQ-9j}g)oK4OHDx9oeY2M5}YCI?*i`?S-G zs=vSAL?Gcr9^yC)?E}}}^k7oj&CA}n^WUge>)m_a=o1EhI?G@Bzp)_SA%C6XI|4Zw zZ#6_K=lyHGSK>MYFd_KBcP}nYW{uws_|aIM|GWjC+@#nDBL~jMG{0k^TJrmFt270y=c< zI%-8%Y|QV!kTGAn3HYWCg9o=`D;7|h1K^Zc`STc3=YF5vtO(1Fe|W+eNU9u+sactt z-2XC{4<%jQlbPxT_blpUeY~WGIZsRqm+GJx-Pf-f4v1XxjX7oKK2m>_nRyYJdOUIuAfaaIcL`*U3iTv^AvuFLDWj^Kx zV!@jNr+n_>#Un&_Gm&Rvog=RaGZeLj;N7W*7(;%5Z!ACn=Stil zL4UQgHi&*!6tCQoHLC-%#YamJ2pn??#Y#g#fvMwr1p7qbWS|hmFRTAxKd^Dr4Sr}Z ztY``=J{K4Jfl=vIOwc64$Yv!jc(!Ys>MmZmbWx#aIsNX3wGPxNydU*m)igte+Vw|e zI;Z>Xn(kv3To20W)hn`{{&Bz7Cjy$B{yu$?pG@UYbQ-V~4yiB8iVDkCyy~N|N4)#kSx>z=L@%@6;=4L_Eu3PvPJVtfB=hqe?P>+mkZiHK zx7*^p-NxweH^wc-n`#i4D#?J z*_e>vbFenk1}OR~vp*zG{mYnQJXAzi&L|G)X2;j6t>7(iecaKpFcFD4{~*ndP<{&L z21hRT>YO3-h|liH*}q5l%%&7U+i?8;pH<0$QuTiN#B$@H=EJz8y%4D|(Qc@a2NvK7 z5b;01$MXmXPKE*2ob@-0so z?XdiCd#Bfel$o5qr-y3_N7OpEzx)36{(l?4WJ#LI$+>w6-NN#;7S7~!h(obV0bIPq z#gKLD3fq`=EF}Wb&S7<#invIY>J5rp3V-?P=}o;*~%_I>-gAu zy~2L+|92V;Nn-<#OG%K`)2M4!?BcP4I-(4B6~#bTe> zBgae#Vkr-&sx!`%#+Gt`Zi<+_W$It(3q+knT_$Ua5Zbi_d!W%Q|cpi+a1TWjH^K>H#qbb>8vjlQo7OyxBK^Jz5dg_tN3 zt6QWmdaM~C@ljUSxtL#6FE%z_x%=x#^DphTDFyaT@1l6=; z-Q8Mw{a#rxV(8Grj)qO7dP#|koPvznf-tPN(b*g1_ib;ej=7d z;@}8ID*e2TUptkk(CLp)whw#pw1C!t3RRviVbJ^fJ*W!C?mQSfQ(SkgMx6snyRmrr z@_Q8(%WxY4j?S(mT9SU*(B-MwU9!w0&X#xv+kBut0F6YEb9ndkkl9C~rNU%wjt5D&ZN0XB9m zl-1pwqQhePPI&WY>#FKKWGpi7|Chg-0rEO;dPzgGSYFSjO)?!S!+Ya)WK&i{8^X&B zhwoE$yJIARNrE)>>mKJzQr{qnU_eKC*%?Wfe4{tCG>Yq-Gfq7eog9@jYKgBSOCFYI z69&w2MqwdU2b|PKG`;G0cKm^RF8aq@j&{1$=R}XRVa;ATznEcP`QyKs+UfJJq7NUx zUh9{$>F#E&+&)9fb`~TbDDrC2yo39(EYTTYcTyy^eJh7)Z=K|DmyV1Ta9`kw4>K16tD97I5@iG9MUd)n{JA-b$!_^Zm$?}NfDi|27B5h(~?;-pY@&$0~5c*NYq`I?iKX+Yd#9Twg0hdkgrnj zC$+2BI@cMbKhUqYsM<#bT=Wq2w72#~)cPJbHq`g`zAplK_Mk9np!Kdnm&4pB8D|0L z0=3b_Rs0UY49`cZnx5!y+t29lFm?N~eAR8C8c8}G6+`VZ28^0FH>BiH4F1~y$18q* zYDEu_%E_EP`^~&ycl;y>AuZ8^T6rd1#(T%_ey_c{-eGEJCS+Lzk!vSDxIkr6hY5p2 zY7k_Xpd+@UOw)iC|8*+S>oj1%USgMcvmSdpDIfKckRfL~3;+q~akbqwhq~ZFj_qs9 z;wyH1JiMrPs#fOZ#b}bf@mx8U4!hAwG|~@0`0(Ki;(O$V$(@h*I46v(Yn(3+z&M;Gl`-h-tYmE}JMo`0?X{%O4O&{5yL50p0Yg6#+PLT}>@ZbHBco1cqju|&EK z@}1W4Pt_d}gUdCP+1+XpLK_$wmL$G}1QM48{=4^r{K*Rf&2jSNoO^@&0{I{j7r6|# zXO@RYr+&HkMaUwd-)FBqAJVjPv*)V9e>=^dyR2~QBiC(9>}5YNohRkHA(?|>rw4;h zTS6^D3%=`%{_FOr?T=+&bc{Y?1sYmXyg-*CDs__`3lJoQQ@k zYWp(tBO9JEz*YHvB{nwp9G`#|=N35m`m6WSgInK9oY1YHuJ;c2&%MH4)c#s!QMW$! zZz&&l`N*}pgD;xgJdv2!xwgBbY1al$#*MNTI~+T(15X74mSj8uJ6H8DvK7nBh=_^j zFMp#E?!hRI)MRF6GWHuZ$^$%x_cKLdN5xG*L@~UR4V35*rYr~!4)#QUiivol-HY&$ z+|_;ARf8>#OLUX3pbs+lgqkd4>A>6@w(F{X|2P?)No1a+S5d_l7X~(p)|d1cI`(&v zR+_%U$zu=oKD393p)tW7{+?u=KK_4t#jkrvzb0+C$dIw~!E8Hk-NR3v$|j5-Z^U8? z$dPo|w!F-0$}y~XnS9VNI|8*UlL{>Uxomm6hS@9{{yTKxKJ)5VE-a_NZSf^oWo=!@ zuxa7p$#qtLtx24gWJeqdi&+-ht-+`+#|ys1Z{~W+I-AJI+=Z6{yLAhUv#~TyJ-2zt zkB=vra!jX_;W-`eYJUsEXt+| zYj8;;qf?O&M$cDn)L+QHEPmCN9)&P9={!9ND&oXK!AX9G4ju{Kfu(-o!k!yKH99;P z5!tZ6f6W4{z6UiO?N%7|#>=^L!uozp+o9qRGeQ>fIT^fZNL$BZse2@2VE!$7iQ__S zERh0nWW`{Gr~_+thsV7F4?Mlt_54He-=kp#x!|5HW(5Xi(heFw>A37IGi%S%IY6q2 zO)YqL_wrwrlM2^8vlw&o)qcn3LC;tAi#CX^Y5bRSFVVEo9nl-gk$rgvAJ)YJ2(oawwu_Nij%#pq_XW7xdrV?27T zLWx02AnbTV_@o9u{3mhLtGYRB9~Mov{Lk&(>EL`bL(OJ}hGjs&fhMXIy+n^fim&sT zlI!WZANxBvj78dsH$Bz_Zm z^40a6oi*s0i)&GPuOt~5{Hk(}cT=Xeule!JrRtTq^@#s7!uZ?;9eXX$7~SB*?bqw? zo~WCgy8B01sdjkjlQAE>{|xT-?Dg2K#jzXyuT{Bk?u-b>{(q-1TdWKB&rI<9rfVEh zb6-qYOA zV|Udxa7J9LV!>a%<9-2&!x4|6&pO8WKR?>gh3^a6dY+-H#DE{1YwX@8>vg$A(J1Q( zyD$Fqi72di@Zdo(#tygVtGuwN>IiQvvr$Y>X|H;qg?rHV*=TL*JIX2cn_k+aqKk2R zWi#U+eIB-&(6v7J?C{~6zjmyaeYnYWwQT_3XWb~dJwM^9t|fvtK(8tBp=R07YZ?^+ zbjT>?{at=J#^2Gc2nbdeMzf-UAd_Eudal75_x4Q{?*S9>fh>~UutZyCEj1Xrmok<}s9AMPKG^zYcN>Wk~ z*)^c}GgTZb;YcTvQytt98 z)(qIC;_Br^zddzV?SZ{}BN7tkUh6gyw3sr$;azVwTo$qb?`-)Xoc;NDMW4~1yqDh_ztnp8Diqxh*8AYR_DovPuiYQJJ?Y!UguWMB)S)Bp zAI%Qfwclvk0-I5ubGkezx9hgZ&F^FVe^v_*dG%`rZ6XqdmhvA?!$;hApOxkx(%A5M zu1QJ1Z;V=s0<1^Ro|r~ixT(y3k_aY5saldX_jwF-OII*CVUTg~pmTHuqDpBb6~YCP zkPAkQ8;0er-TcV&_C^Ck!&(QwZjl8jH^lxjvF4smUJQNHG37pZ&ffq`*WkT%j{f|>Va&_b*M zrj-%07Y2Jq_+EcFu)=77R5zQcwc4DV2YT~ z5;6qqL)U{YOK@LEX_G(Y;~Gifmey@lC6L47&ZCbK-O|jN zCgmQ#7>445-o*7O;<3`xUbFWdZ69ye)UCDvOiu`XVXl*iXpSomF^wvCk5x`06O%S- zi_K~aH&@Xm3Vzz`*G=%ARrIDD#6#8N!0{c3_{g8`+Q0f}F6JRcZUeYrvMNz*Bj~z~ zv}DI>y*^Es*EB`iS*z4s58rYBYVa$yII9~J*ZjS8+`w@2CC1Z zyC?ha-SCe*E%?rE6jpD!=l~d9Z**)#@2MYZyeoJ$tZA(I+Sxu; zQiM)V#wdh?IZ1!Xz7&G2*yc0m%-$^3e~g;H)z`a%fFWn?3dSk6X3=)njN1a^DZp!L zHsMa7D}Czt@wv&03pNjq7j(k2lRPEV%qY&;Hm-1(73 z0byw__O^)+gHU2|WljL4UMJPcnUR;GzA8>Pu-mfAt>0$am~EFYk46FqeG?)kX~`iv z=W8=)s_47{A-VE+_ar&<&@r&2wgjin|Dm5vzL8_1$FTNcwje1 zbR7N1Z5elf;I!mHbE{eNcD#%zC(IT{bQ}^Z7RI47XOXl|yF1~VL;ugzqE4RZ>p9rbH>e5?Kgjd6z}6+e>)=BEZ2bnL;=xr>-aUP(#x zwPG@jKu34|;PGRz>ww02H)AnxrZzU&E9>vFZT+u_AR)XHrBspms1cj@tG10;WW1%X z5Z@qeN0*@P--{swRC9yvTe@pvoiD_!6>HE>*YOzrtE9==#GL@a|H>)`q_%;qg^l}l z115uqX^j83aDG*omtR~}ZDnmOjCmP~uJL}ypHCY2EG>3?{;5_%{MfVHwYK&=%olKu26cb4L>_W>nDgA)HP| z5UlI@;asibw18fQ{T0sT>79R)%6YvecR~PbEQ(3`{p>$&?OJ{3d)nVRC_BNb zZ=UP+rqLb;27TY2_F#FOpPuEp5cPyozwX;LMtc}}e9Y@(=arFQGx50Hv&%mYzUsB< zvibXYS%0s5vFk_U*ZPvHKlV3f8~eW~Y1#O4<%9`GN?fk`cWr5D5!;w4gbmI-6@@9i zVmgW5pwM&Cq8t(%_==j>ffE-w#Iek)0)e7|)g3*$`-Tl0ZWR@&eT%oBJ9iR?h;3_f z$h5J1nf+1aV^o!N`%XP&Y)aqNynQR+Em{yY;}2=pv-fAl|3mw)#}Lj@TQ3a!>1Q83 zS@njwI5e99gy>tfn;7bc0zrMxP4}L;oH@I-SVC|F07qEUD(OC z9Wk9SE{0^K#iaVPDyY2~NYo1n8GW5A z99`Cr(FPX|MNB02obl9lLWrJQ+qjBBDkj@xV5fYj+|Ho zgmi9hbPFY%4{yU}@$+^ie%2c`d#qW#I;Z+;`^zm;ZER3J$|WZ!gS&O6M?jC7vL;b~ zmeu9ZK`G{4^sRUL;G4=cIM?`ubK1kwCB`%Nj}%r2852CA|$#xhL&{M)Pd*@4mIstm}3vc{H^&_IRynUTt+!uls=b4pqEzUaGs_dUIxkpYbm3mDK>w1H9lSn0udQlqd^&UP+{gaEw)PW~PQt}~k*B8{ zc(d3&NfDl7swhlbxBwoI5Aalve|9^(|B zfz=~Z<4T?~!3X!ii6jyrHb>F}6ukQ*rZ6$=Uq1V7G4GeuGP?!yOnWHELo9p@eh zeRA09Sddg-ufYsw22<3Pc~yt?ar%&2BgAx6bx*dk9pskRoA1^Vw^=D zR{|l;IC!0X(k!Ok{^fd`HX6pxby_ZGP3B3dtPXkl*UmrfLwdcGk|62`LU3y7;&Qz# zGy3SctgJ#F*!JfGH;(JoLs5^!ndR97}&eX;9wsB%*9v59O1k zPB$Z_D=-VHXMC&8ZefMVV8tL{tSSa1Z0F1oLycspy5~W=-86RZ+n0a)wt`~5E2H`v zqy3B^2@OBlbhV!}$X7)r#wKP>_5!Mt$ZrP?i!`z?U9wqQG0WlKrfW4IOo9{Zn*x=l z911I8?C1!B4Po{4=VzS>&y_3hhj{ArH#cwxMWT{;d9gI1tRyH|BQ%%O0Y((fo#{=; zF;ed+W>Wz&j+{BOu=db4xG#=jhXZpr16m=lSB4*^LY?+5?0)PPZJlOkwH?LJ6e4uK zw$x3i8^>)yuqkTT8Jxg4aQ(kUg?@Wpfr`%;ID!a(|dqkx}hS>?dk&G==o=&@F ziR$}Lmd7{+2CF4Sb=yG7ERkw+%FjG3w^0AECP*(%k+6IWjbMARVg$kCqSe254fPg# zi^Z}_lTn|KX7Q{?IJiW5@a4@HW2hMs^Q{zUd(TquMLt~>b96?<$ z|IL^A3~zu{%XAOKyhe)pS<9E5xzqE6`fTvJ8rmj`F&k6^!AHQYj=&ny1Vp4LD0EgP}@K-*A7!oV9- zle2p`DTxayjR5%iO~-6-)SS}Nb2t4WkUHGJR;`lFt?xFJm?{QZy13QWEXh3E7Vpt+ zqby5Uva_>MeBPk_V1QQ9oVM{ZWdfG0r&f>tNzIP&PYB)+EM87uRXsUwU24bPMz%j&THG)M z%=Ej>M+(4Y$iZ#C9eG%+Xh41%j$RzwPTRk3`IA3c+A1v8FuzmBpk$)I|EP24&*zem zKJ}F_opkEiutQCn<47>7TzwiJjQ+auWl5@qoM^~Bo#fF#2JL93;&!>bsjbZ?CGf9e zorCh&^}Wkvch0g|`StacUILV*tyKsVHL$p0z35fGxiHdh$5@EX$uS1JK+$r61$cch^#ii-S=N2U^ZT*0TJt^Q$tWZ#7 z(U1izgpj(0gdQeN;t%G5P$qER`a=~gA0vQ;qCjw?7I(;8nqW2dP)H|reW4MjXVO|y zq!HR~-`$%$N8LZJ3n;0r21^`?^BvDv1_Ea);*P)f%$zYJ6w*Y*EE@W_n+|j4^jVuf ztH9`a?Ur)}d9{gIFGl-*=#%g&mv}}(*TJ-q$!qC+Q#y(tA@4KD%~hQ@P>(@5X$Q}Z+9imU~;2#{JWGhjjFm$+lYHR4F1?!YndKPaW88? z19<=O^!t&$(T6KM>lxN7tkIP{HI^uq3 zv0}wQjDk8~u59C7%4kvq%@xZY(w;S<9v133UNwYNLtd(?thB8iwjodIxPJH5%nChV z4k9Jq>eO_+#VHMF=%Yz-?nsm#-z#Fnk21KPNRr5oKAZ`jHL1DFKW`fw&6gXgPxYx- z=#bKP)&vJXzu^!zF(}I`p(Fzbk3#Am#^eP2#i`$WQ%7nR<=o2{fg~eYAd42Y4;zW2+IZudS26zRI+3xWAPAg$8y`- z)nDt81iAAa-OuE=?x!OLN(^_tdaPn!Vqvu|lWTO?VpWdtIsjRCop$|?n%CrECMGKM zMo%~;phJGgYd>?2;fapL@Ys4ohIGbiQt#?K)+d6eh2a@B(XF0=%x=quCaYkMfCe&`UlcCB zixw|-2jh4LEp(<3d8#Y81@jM`myPP6q9P=(*lGWWTw{uF(k!BoU^@8>`FVL#(A$}hZa&=Ylf6I; zAy931xuDg)sBYwU=F+J6C-BxXqhGz^HNfMT=hoqiWILH3y>NNBPXEnQZ8xZ!PRZ&& zM*W@5`-PqK7G7wI9O^}|%jF=b_UNHFe4lY$)uZI2W%CPCJ$-z9cJ9vUp=+yB5asNrX=R}+PB8@{1!{qhTe=vmkG*N{!%A0Q1*u}p3VPCE8G3~}B`1BnmN3>k5Z+)J9 ze_BF?Ui$3BiNga*oI-{B6ZHISVfOwrEh6T&&1*a%J68eQ2Ntl zjL?M-lXW~jaAZ+&u_!IL0P?ab+D7mEaN7yNt^F{Wie20jxfUddcJW_^rtLQC#gftE zeU%A)bU%e&Bo}f_6zsNg=`S0qe^d9GdHNsAa=p0I2Z*Xlze* zu6a(%&@fwl%%R{BF5{|dYJpU~8-IPuY6coPz1As3`A|tANyY~!aOz)0e5jHen>>%` zjhweOI>mV8JZce;Gh9jXIMP0lXUJ+5zYc0 zrbjQ1^?5rfZeqZWGTR+DMPD%-jgVL9ab zl_;5yOuC&0mSFy;S(=_T@UGz@IUC{%AYfM*w$!!HQFU`c>`wj=4LF@}HMJ&@%0%?F zCw)^D^DBwldB9sj`mwR?_m8NCC2_?yV()F>y+KE1ryOq0pNX1WcxU6G#DPn9Fv47~ z8;#X^G?kp)NIq_Wn+6Us9Rr2Byq$y#B%BZ_#l*rWpy3YpsE2p$tEie$I3V^-jPa+2 zeo+FkNfl!`0O_e&QQehN2HbVRL*Yx{i+j-b`2S60vF!bFCKBASqjEQ%8N1lHr~?+( zIpD2Jm9mc?KMt2Pkz#=ENO)w6i}~{9HJbwkd`#FMcj`0CU%hKVg`Pguq_ivGyLQ0k zAomx=ZeU`f{qf41HLG(MpRcN|wXaLn%QpowETD$hF)@k3>_XGy=Ju2|s)9Nu1O`Gu zc+lgiJyuOnw+`%Wdu@0VH&dJkK+*7CNyaCty>L`NJ9HhDboEvq6`uataP@zv$Z`c4FKX$f+(cB;;D`_65 zk76WU5Gz1!o@2YDpvzTVTkW-d>xqzSAgzzHmmS(xKR83a?Y8|d@PtC3Lhu22>3L?GvV!r{ ziK&f`3KDY%!9CH$H#9Ufe>k0HO1RJp@+dH)oD)N?PymMyAC^djiKd0UFe%~Ci7wjb z@=r3QM1o)jSFG_qmoL5kv8}K=_tB#ZrK2h@;g}LgDGuz~{?)I;_wC)A8vOR3m7yBh zHcZ)4s{_}~sHM4i{M4x(!Af^E*?ySru|Jb3MiZeY<4Uql_{y{LL5k8MaBtY~*emPY zQ0W>D11|Bwum%yEqIvQm=MGbf0*w}+HxZ>0&z~AFqGT%*v6%KSYPBr+`xpjD1&TpM zAdpmX$a30#bXJjfw0WJ};a{m^2*+ZQu2?$Dy&b$K^A6dHq%9V^!IJUX={Id#u=m8#q&*|T zdM*>30vf>XIFt5KL&AK8$1Bx?hj77QBOQAfAV+1{ZGmHaPk}_wnw9d;n^^_F&i(U` zkiNUVI10st&R-VgCZWm6XX@XS?al8`9=b8GXZ!e)!?fuZi~>=HC-`MWMiy4jb*k1k z8VQ)=@a|Hn3230g3P<~8n^W{3B#Du8X}Lf*4FPk&_0wE-zB2=`NSk;W!UQ{ZShlrA zDqY*Q_>9~?s%_((Wkm!}H7C6e674>o0iE{-dzX~vTDBN3*PiXH6>iaTeL&EoTh6S_ zK$#$z)XvnM)^~XWy7O42JIM-Bf!HJ~*4j}tq7>*#nr3`Tj0Rk5`}6n4#=9c|Jzj1$ z%1a3!G19kYxU5&*>-RgY?zEM(*FQGS@?AnB3epi!V`3dFdJ{Kp8V;JVf9=PrL8KF^ zMK@2+xn5JwC0|pFK9sg9)!S#0hAcreu-;+T>M3*QX4-8#h%7bt(+5U|g9_X&P<@bW zgSl9cK6;tM;|Zie`}g<2PikSU2X{$SE_~&rvhov~jPh=WkFdIJkaJRP;IjdS<0qU^ zdRzD7=!@saZi{v#6O=Kaz}*ex@0_+x(9(B~#q|G>&?z?S%`r0uu3+Oxzi$^gau&aB zX9a%Ygt{$TwxI6JgS|}lcEeyo1m%KpQ>IfOrgO1x6&HKZpIEW*0-p@gyuwkqLNQw{ zdDdJ1Th|q1N+ca6`L#iAw*w05b9d~N&X-t4hBTbEP2JsO3$hfbt&0Zlu<5 zuSI=wKiWHjxsg9)1G_sC8;}9ilC5Qk^IP2Qewi zfTHG3A-`1xaRY7Gw~LwGmObHfuF}JWdv#JANur@ z#$8Y~U@?_89lBjUdnLJX!=1vl`RCVMGiBZJh9pM|i*^JWVN;vyf9?Orb?Fr*kO52I z?!L6~U9$cIVW7nKf+ZHwjV1}EYYH>S-6pe*kY&7 zj>Q?F>$1V#pS}N4NKq!k=pkZL5`(x%fk9j*TkJi*i|?PirR~=%r>S3Pe1d4*loB{* zgyDQ3%%x)rX#&Kk9CN2>_o^4L%^Gw0;Cn~QvbaA_K0S-6)9ClzEIMOK)z^g15URPr zY^Ptu&bG6YVx$1(R8(E`E8Rv_J7nC<82D-(y%T+F| zEpT85BXz{CGUua_0;~V>wta=;;Wh~7%0!pVDGyhP^oD=}L+SheTAI31E)Tu^r-f@k z69!WGRzn|KR@7t;73>+Y>5h}EoLuBEZ(yHot*sm5K8)1T)C|b4(!tXQVNJrphxhMq z#nS@)HY?_5@o?n6s0P_!TW}_`bKspr2;N#Tlv_O*Adu zzC}xx!xhb0d|oUg5KkZTj>0gMf*|hTL1m^vMMQL$n`XX9#oE=i_dg+K!xGbEJl6b)Ez&0 zQjjK$Whglpr(L|LA^cMYzEaLVqr7vLv(Dr(Mv@u+3$9GvUPz(ImV#|m^z7r6Jbn5U zrXrMH%%Qj)AhXQnRPMJVKJgvu15-%-;JiFbQ3cYHwwJK@QHvZLD$-QEs&Vz!Wo!fWetLP;Ae0%#{X zCNakR?n#EAe{yS9$L-rECQv|pJRm5sY;$6co2pI{UL(}S&SdQ^-=kcL5e}}24dKkPFom4(!V%V z%XX=#o;9-9?|J8JZ`TjHuy9c8uBgd;V`7F_SD3q-5;cf}C`QVuEoeK%MymE%rwdZt zo~ohM5Kf5>=NCs=rI~MN=p)Jx96f*b)X<%-c-MA^ddilzKg~bu(pE9@f`7=uvV1Q) zAdfK7SEG30)1RL2?YJ+Z@<+=w=xRe6b2nF4+nQZR^{aeoxoEV`%*lU4L=arRa9Zv? zdHYsI@@|cO{mXBKwAaSfThuqp4UdUALVgt6sIOcHPVHFKAZYpjfcMvaf1l5SLhGuc zyY{S$M`xg0>P=?@^gg54M1@X)BC-{jD&lCtu=Ksj3%jRfWMpO*P;eVGZKc1PY-JUG zKXcd7h95t|xERd;wv#jyIlqGY353-D0F5KP!RfKrhk8fv;wd4NUj#xBRFClUw^1oL zd8Ke|+mzTvi6b;*&5I`K7!GSk*C&LWQJ3o?5kN3E2W*m8RCFqL^u3`nCeBxKxJnst z15Pg3?@ggRp>_)2rJ$-O2#uq}Qx9g4fZex5J`2`43l~|5Y81Ay%g-yxqi>uR?hD9% zs_+SwvAy=v7k35XdRXN!QH8)<-G7=3+d#!YZnFLOr9U*&_U$*2kBKG^cE^oI*Ii~X z;4j6FkmdaSPHK$R-L#As?!Iqo9Ci;)Hw@erC6RzR=lpk79uZ-aS;#Hu2GdU$*yYl- z^L@`}W`^K$e#ShBs*tveQG}%##tRful=vdA4*+ZmGK3^6>Vy*3YY5HP`*~>>&+lSD zoton&C{6@-GY3$Ir$SnC<+np{=H`<}N+(Ghd3L=p*KYi)d&^CQW?=1KGJwOV6pt{4 z;JbMxZscNN87s^K$hTsEUM=$hkc1Y-129Bke5#TjhQr@;~sxoYUXdQy#Fy zaS($-Xpb*GOIu0(1nt#USq$Zo*|_a;=Ptc_y>aP_#IvJklm~uoP75Aah*pLI6$Bs;LH@hRCpzE= zluxE$Myx$sVn@X!nc;vXI@_fSKd(k{iudB|ig}hx>G4!0w48KdXETt&uzbgW=-Zvj zwd=1QzI!qW7v^*3I3;~My$aJovp0@L^-G(-M9^xazo{I#u;a&7dxzZ%ojhq$6&V3} zWe$$YgWy%-R(jRe){1gS0F7w0Vo7X}kfa4}p2}b4XM6tn^{Ooo8UhQ^gcVbUC`#XZ z(dXmEZ(WQ`U6(q{9$-=^6;l%aZS&TKOFPkWtVhlW&p7*2SP~WF$kC%cD6E=^xAWiF z#r&68qU@4pe*!Fg6stp*#<}#j{17PBSGTP*-6G`zu@p?#Yb~X}u%kxWXB z%@Rxnfz3g*2^jE*C$qQXaE}mWhJbyTkf%c6&`#!Y8iWxc0~4}*pdg-CSM|{}BiDa_ z@4mUErkilGc$UGVDku`6RKnE=wqIFd^~)i6XQ!31JLYbk*>}N(+4HuBI(5HO{v|}a z=jm5}^^OP*ZqKJ3k50mHUaIOS>3!6hsO@>96E}zLzH3dljI&t=WyMmLd{afRVnOLZ zBMq;7C+~HM!`ZMWBJhdO`eeCze`Xw*RG^GEv;Wl@T(B8P+`xB4nNW4+o6nEOQ!@M} z6=!VyJWV~c*8B#OMT2}l%&{0-OfG85_j|>mqP3PL9x|IjS6=h2e#81kxJn>TY3xm3doK5*bs66i5= zOVwe$HYb1gWe-TMAnCX<9soR1mz>6vbkxVk;gQ-INk3ZiV8uCWG z+9*vB5Tsr6#uZ1nNAhet;(M~2NkH_P(ep-OdgIE6|7I5IhG(KI>eqwR+wQ0S4q0gF z1dXBueOCosCveF{WB1EaQX%(HRaMp5S(i1}ZtIwiY9+S+%s%^T%PMGDqOB#uFSgf* zvn@k@(?VKR*h3a^oRM|$FffKFhT-c&xhzAiMx{I+rI{qhJwr4wOd01ujp2`wOU>gs z+I3J@b#+9)n)H6^KgWdS=fYf^URX32$J)&KeZH^;+5JSL>R zvwlBTZ>p=vR_e1bGGB7v*1Px5I!#%@1<;h?;Gqm#bHr^h2?8s)i)?x#u(+|8wom>d z8H#ysv{*Grq!T-ODSP^_cb+gon)$nb!}^)|VKfYu$S*MOonxO$GeQ3TWe%9{2e5JX%+w+6nW8ZA)uio)umfsGmrXER0 zkET=W<3`jG#XzT@n`W?y3jNb4zmM{QPye}R#3UhC@bwMBVU>Q)(D$b`r~wZ-0m#!% z%DRUj+dxo(q7rHeTN&KV_Oh}?AD0}6eJhfmp7^Ga#N9V$oj2NVzC{}VxtT}9bChz@ z1eH~FlTJAJ>eu|Q8Zh~*FK_sSO+NHf&Ztw7gCRlFMHqr!Xz9v;5hF-+VzagoId>gf z`*ppz`_OodPZ`SGyQ#0EBZ2hOz)$X9Mj4(!aoxHf2A5wb==zEn(dlVL1w=p>R6mK( z6-tLn)Rlgy|D2tj z^^J`16`LOEJySluWFAxOns6+^bi0Bo%Uwf66yJh`Vaj?^&FFLfd~x(%T`3k%kICXP zfk=!`UmUNhr%7N4Pllag>|H3Po<7U_=?4Ww58^>OKd0S6q65%G&1SH#EK4%Z5-4`{wg)OM&Lw1h6Ok=0LHjTBxni#TUB+uH8!;; z(gTJ_$S;=13uBOJa2n}EHKVr2z76Bv`NG3VKfmPL5m-Tj9jnNM?bF@!7){LdZXXSKfvJXXa$5Ufmz99pCgq z?|IpG4ME5?{@5tc#OVgdpG`)7Z)fFA|XtwCm#hj|(Dj*u>`X4N;u0qfxC}uhsC$CL9o$jJj@?m-g zLwa{~>yo0;9b10>%wv)3;`3K%kFXD}^ck5jyz?FcKfR7+`5iUOJ`*?tg9Kj#Ah&FI z)?FsEB{+O;{PAKPDRYjPAs}l7F>!`IefE1ZU{5&qN}BWOmmJo4?!t|m+-4Ux) zJXN7VR;s%-kVAyk0mq$*E5i`EP&XeMeJ-6quJfyGcgIW7CNNCeLpWam5TJ{)b#Mr$ zQE+3)r0L+nBnZo(s4zDTF|Q06cA`?W;BZ+7NG(m_i}e*cb%yR9K0FjWT1ydw08I0mOKCg1@I!q6LAL+ zRT3j3O{?!lsBGZD0ckIU&u{OmKOf%{lkz^n@h}A8!BnH|v}3}!)W!b#zHcE#!Rm%R z%X>5|8y&TfYa{KoPZ`q8z&>8o7HAFFaWnl=x!>%04|@FuRDqAov3J=Nf`hLsUf2vu zhCEuL$hh`4I4z-$QOw5&z6WUb6#DRE{yiIVqfH_EXnIF^3r$Ca?#i9EexXh^d6&O?V( z7`vfkpn%jy(WyG-2ZIu@RO}8`Lg^eBSaEC>HbGl?Scok3#U|HX$<4y=`?zz}>r0r4 zBdifD^p-y@auk`uZ>#i{f^H^6TzEWYJJO^8u2*c6?b0TqGw6tr#g|P;>58C;9&{D^ zj2T+f60*F?Y>t5#v=Q?w85se4_tw9BacmVxb%0>qX6%a(pWnA)jum?M}be(g{rIW z$fI}2K_(%jRyT28kWy_;Ed?5k$U&-m_wEqM3qzCoyhi2({c)4(a}dUhEE{U~pThj~ zmEkmY=+&!kHY!#f*r73gcD7``dbD(5K|89xv~v#+soGs9Wa~`=xFEhxf_6g*zi4ca zBT#0-I~zq8Pvm3&#c4)qpbMk;5Jc!x<#;Q^y^1tkLS?qK zoiqTtJX#9y33%xCA=mQm6_+giQghEepwQG*^QmUtmcfUgT3c#q$k|NX7=;(PlQ)FWlU-teyy z_R<__s-p|3Vb)qtVzjsPHb_!*eSCFk;FTU7cgp%rx__=ylj&f~aMS5Y*A#T8Z>M4( zzVf9am)KEdl1}g5(kMlu`b}dJTANNyAVlbj26>kmnJS7+5;>Gs#3BOMQPZbV;wgQn zGA1LhkEFg?@$A^CQ=S#-4T#yUYS;6_gvnN8TZB}F#(n_;BFxQVn|$b2WO(WvRfG!* zb>3t$f{<%N>T!R?V<(0|Fql`WdHW{(sj3^R-Q4{z1xY~ z{ow&hNeFLQ1Ux+VlNMJqXe%94xYMhDuTVEZ_X^!HtB+-%^d;l(SGSPWI7$Y9k@_uHNaKk7}bPU3aPW;C{DwWnjrjGH%ZNtEe+yYhejgI`Tb9)QVCy1B1=M#2FQB>6ZcH+ASF~%x{2js2Z)VJt0QMCjxV-~bMU}&$& zVcLk_?r2pQ&kOrtt5#b7Zr2E1rN0ohT=Z`;z%RS*YF#mMa6rsNf0fk~Cz#c$Fd-gA zxyfj+JabTdk04;|X=N*RoG5uyk>>N;G1Q^3p+)gYb@wS(=UO^-*n6bUv48~90f{t780^k^|GVjFzvS9UO6%SjMP8`K>NbL$W zT7eE5%;rU9T{k?q4msBMk<$&f&$N;jS$;bzD+~HtXsOtr+4g6gLO?;LUX57~sRmde zx)IE}<#AFT4?80eJ$T*}=g8O&Dm%{QC``}GT=L%a$d$j$Vg{Hf-8kI(D&FFQYfSkK z{prJ=D({L_k09_2&Z}*t0c2ps87|vmX>AnhSKtFWe8bE&Z)<9DDUrsvOg=;bCMIGK z>C=PTT~^i|X8nH#f(6k3!E1?=-<85cjwjDw~_D#*tay2oUarke#19ZVT}!@R9Eh}Utao|kOR>J{l@@LFkyc^94Q@sUKhcR(wfwO@AT z*sxUDC#n`<72oG3vWW+f@WKsQa3p+)30L~^!S43BOE{2cM?=8f#U3H~Gg`F|hITI* z5}dW)LqqX%PT|`SkJHP|x^?X;LnX*igy8waD{x*WTbUpUpciCyMnysOFKt7@- z`%3n`bz9e9XV`_9Nu>~~!K!xBU=Bm|PU^iJe`UtYwiubpMK`*8DTaxcRuEr0?v09! zokIKoN10L$W&S`3gDtFbT zT@HmScApKIwRfqVb|>*|hlmev2~`wm>sayWOGItYlimSiqZjw*;0+z4o^QJ2b32{j zM?3!~cHn$r|No91l-}vXYwZ!AvUBYB4Eg@OU+VNdEjeU!@voDq;@j;`dlfmnlCKhH z#`}q{G*OR3E&fNaRWM;w{47qMtHKXd^*a5pU*e;Se+!>Tk^Jw!Z9^#f?+d8$ZsM0M m`-l+r|6b_-@*2Hqlcdl3aLPi;VYGz*tS8Nwc-GQ2@c#oKu6E%7 literal 0 HcmV?d00001 diff --git a/_images/7b5ab8c778114aa5f3811e14abc6a3432a0a14b7f0dd44b84e807b42a82bb443.png b/_images/7b5ab8c778114aa5f3811e14abc6a3432a0a14b7f0dd44b84e807b42a82bb443.png new file mode 100644 index 0000000000000000000000000000000000000000..ba8b050f30c3e192a18aab1ce3fe78699a6b0738 GIT binary patch literal 27297 zcmdqJ^;cHg7dMKDk|HgoAl)GyDj*%A(jhI~T_O_FCDNfH27-w2&>)SJgoKo|NO!}X z>wNFH_lNgCcpc-6Glt-P_Fj9gIX|_Y7wW2V_&C>au&}W3735_!u&~Z1Vqu-xymS%% zCUYQ48vZBZDy!}Kz`?@R!`RszOU2mL(bmD$*2?6%yScNAm4iJ$moOI($Mq+!u8uCE z+}w8m-!E`EI9qbxDk}K|7rE>xuj7J+MQDuvJM&&D&k766nm|G3&O^`i{2 z^}*eAO8x;#i%7djPFA1NSjOjMI=b&2*>Ci6+60r0nOn^lsM|j*RoAI_$rx-qj8Si` z=}hLuE6&(#U^Qw_p<6KnDH=R$( zXk=_LKhg0Vcl;Qtm1o=*^6kUVkfXqTyQPOR=kfXkR4UW15XIqL{&3m1Y*xBveD{{s ziU5}K$$|NAV__bZ1o19$*N^=#YHl6IbMqLvW7z4>qIa+tS;9QP=ezAV6+i8mwnF8f z(cpL`PUu-rl-z?nPa0e?5~6ZZ^it^7mIECqYrKUoUbMFtS2mog3pA#v>f55xO|r7O z6G~4%h+eTtaaQzEsQDJ~MPrpO1y<5%@(gtcz7!bc9V2(l(&&r7ui z_v6xHE4E&G861SWX&36inwS?$E(#wgnIR3AdecL7FCjVU?@OM`lvJKm52m~vrhN=Q zFw;9TpsKNT7MNsFBIIl`uc*=;w5v!7cr0ld-{o0S5Y}3P9&N~MWz~fjuOW4c$#?ru zYoMQuXrCB8O4^abTZ z^yO)&it*`j@99d01m0;o%g9M5Cxc45@uGrdeCuMD%>qR(d~U#Ff2EcyL}%dU;%tpm zne;IB=8a)Q{U0AiynoN4YA1eSApP3&K1YpOGe4W~h_IsS@IP9AFk0i<*vG2B-->B^Dc|gv{IQoW^^Nru|!tpq=QGL@3#xPjEr+! zS($Ln;ffd;mwxM1Q-p%Ne7155-#44V=u*3p-ZCfCjhVJ{W*xfj+CKw><_W!bpSlR$ zq*cCodURB^KbI!H_a|sztd)WO8G6PR0&3w{5#0UFZmDVK^7nceF1wM^T=?(dC(Y&5 zKzpAK_X_{PU!N>BMDdv$-h}Xk>H`SqZ@EqHJ!EfaU8c#K&Qr6 zq#*>~bhnCZ`=(iwDxE0S^QHa@$6t6geKsi2_nFkd^)eff7!fq~dHfhSM< z7Pfw9b73MpgsR)OB>J5G)cFyQ)Y62U>l0YG{~5b`Y@M25`X9DunLd|AS9+UGVRdtk zbm-sSTwI2Gk=efc8;1MTGB#z5TDelezUkGf_>xWM zcSA@5m8Vx{dwP}U)zHbkkxo(7h8OLw_bVP--Me*7wlgeMNZ_8eHCqC++8jK{bta~e zObMTjAMAzduVpTC`;pPdkH8j^FG$MF?D}0|!!JE^a(vkKikt4U9_AgqSMjyFb0nO) z0zN*@dBszIaV(ZInv(kT%oGk zhPX;@!ieZ-i><#sk#tg-v9VV|@Tu;tj#pnMASkW8MYQe&FMaBja-Z4Z&T@*}q3w7T zWnP~`-#ZoltWXZEg7h)FgSQNF(QD0A4m@uE9-=2fZ!|$oQsMSfE-m7?PY>Wl*2bl# z{`m2d9Tqr_L5}6&`zyO+9&}KV)8js?xsH?d?wAzQqm#qcs)K)@Ix;2F!b#aT;F4>9 z-^9!vr05gvvqRHp>*>mrXy2U(=tjj?<;gqWoyE+?#p(9nP1 z94b^M>e?*|5$Bum`?UowByq~{B=OTn>n(J?hszia?JrLsebStSZER5KZV{GmSY1&c zePJM9r{RlngLa8EDL$2;S^xX{0(QUqS4w3Xu~Dz>cBve*{r!z~^GO!`t2k!0%#Ke4 zBj2o~&CK48+0Eg+v-;|~paDzRoW!a3WUS&AEX`Zk8}1k;dO@h@wy5~-?{P+dW(32= z2p3qdTsd!yx&0#biW~F!(4pTZ8XCQ%S~QuWZsGK@;XmK0Q2j2oQ~IR&*)=~ZO1W<) z&7o#;_LY$ZydLqRwT7zoW~x#D!{z@j4qduUMRoa^5mSBi@E^qs(*dEzY4&BV23ZSd zEotA6UtU?lZz^7`ng9Fu3EIB(!MHjVuB^~4MxEO^QztIDks-IH>n6|d8aWv5iswOc;Q#>N=s8p`U-c8Z{ooa zKrhqqExKx{a!_!$SFL?z%w#lIz`h-{!g3c&xL}%~UHyV*`DYnGU&)neT zTn_(4Ku9O4{QcR5^3|HdCnKetXvbt`B(N`yRld?P@_PxbM&pA98%-?{E*&DdA43?O;lfirLg6aF= z(I+yrBit4Te)n+4O9STEd&4bS_nlN{^w;rj?-*12sUxp#w;gmE*m}};ZhtlV_3;rN zm0;v8n}MG&t?xx$lYMh9YRO(n#y%bu46h1>!8HwH4yt+@ZLF3rrb6FDSxvJ3c;VTBs- z0mYo&RA_b=;kNMb@a!L+Zc&Gv!z{ehl;ON5cum3Vd#mj~fq6wmMS6=xlh;X-R>zMe z{GYe}MpxH#cIM0S-M9=dVP>@41vYx9aYM)g6C)8F)ZDPizk(0GU-r-8HPrbfP|2o; zB*5LTP8>_B(5Gql=d8Mv>!*u*#lMk@ah_?7t3C3aX(j4P7m*IGzj$~^`mH9%UoS`A z3$4^D^p{8~p=iv6Kh>*t+0&C_N^wt~oSYm~-=}YGvnCyOcb)Rsw+qKuQ&3QZd=KrE z+G{GQS!NoX}N@NRGXW9}F08^7XPWhP&NdoU*55E)fBS;auw3bw(D%F!tl(;?84Z>y3C? z(^u&cX>fbix@Vr{@uZt+n?L?dud}vTSiAA>Q{hIZ(1asQ%+0wphu$1%>{Xi5EMHnx z`%v7x@5|5r+*QwKdoJ^jLo@CaNUze{^4=$s7?E|>b;H7C9_oHh%~z-2PGVY0;u8`? z+?R%KHB9xqkt=tcJeAhDeH#nzLCfG-&DJ6ykBPEd7R#Yuw#-)t?QUJYCOLmxK~MX; z%!z@!_J~jE6<4lmhA3KY7_An|6Q;d7LxQ-1DuF|OTBpf>)ZZWQ^e>-jV)N;*lvf4# zlceqBdg1h_r=C&k@i0UC$aW9!#lQ&-n5(!v*EVS6L8l!fo*hOnqoPuVK3g?U-P2{ZlTr8-;H5pB~Rm z_@=oE^BcO11pS=zW65TSy6FLxdrrN* zy?j!V0VhWRhodHDW;eYy=SuR8^cv{`6*#Z64iu{|INq&s{JS1x-x5dt9Y8ruYy`@S zOtI~Lf189i@)kPbp#S}PtK>1tXuGQYGx*HsNuP!?OE)FyIOyLDMRy=xyhJ&Wq3to& z&|dt*HKmaw{Ki3AB;~!lKCl0+!;>fP9XMnyF+=CpbkZW{YrkGy!)GR8xu|wRUeD%P zD@BA`K4x#xo!R-Ru;vHAOD{lAUdP*mAGC|6UeYBy;xJ*JZMKMeZkj)xd>WnAuuSMZ z3abw&H|a@jw%^>Za7`ZNpwu(B79Qjf-oJmJgxgSjoD8sZcvqqGqpcUc z8d8XEf0DYm8x>d;%<1r;kB?t|2o^9{RzH<&3LN1S&gcojubk>*2(n$`n*qzhO z=IA=sktP%a0F=-1&uuO)f11}G zKJz-J$~-E2@5tZgdFEuwcU^hxac(N>ZqQxM&km2(S=4SQwXDe%DjTTU+M2H%J91GU zP^#Jn@z>tbzC(-1^5961^M8!d_{Kp4$=@%9(L|=wK{Q9=E_5kKQ0&snK zYAq}p1mTH6x~E?%If?X0*dB(Vp?%|4m#OVO;dt$%AJ4ambBv`j!mpPQN#12g&s|=F(8+Aq@4cV|HGgtD)&W9C=eI=!0Gv@=e00TK#5Zvq%2LbqS95mAQ{~gqO}`#u8>L<^WXx=KC?fcg{dSZnwV0pJZbS1 z4=L%6kJ!TjP|*M8CGBj@*Ina38M6y_+%DdK^LIi&gGmc?C7@EhU(J<1KI~y)ieo=N z*K$}{c`ANS(q=JY?-C8w%_L_Ef_s9rm+OF1cWdDH*_jCA9sF97!?2B24QEd16PSH#s`;<=*$%E}*;GSH z_w9=mTB`9>6e)qlj_StVnu~2y(Gis6UcwI5+hh{~StUAMqkn(qNTYI}&kCRol|Jp4 zJ$db@!=iDfYD>P$D4Fa1dm)#2F^YG;UU5a}H-V6qFIpOIWEx=Zv1AWQ6)#U%EBT$5 zYith*3soE9@h`htEY-PIjzK|$L{SNS1u_P^(0tSK&*4SnJvyVO)KhDdmkR2#W!TLp|M*!rz~-ldv({zBwHub@fWN+|xqF8#e-5 zTjdY778;UyO_%KD8a)`ZLY;11XQg%Y!R(mwPnKd=={;zav!YRUj$B)FwCGH20#XlD z=K0w2-nVYa!${x>y%-0hNN73p4OHb8bRbDRf@$uRi`;4*AVKW@| zxb3acyh?SEq&#?Rev{v} z`J$wrU*u1EfPzCxgk+ z%dIUNi}k)?N-54Gb$(_Nz+fVmLF$JGdA*<03W8sbswj=ezY)n$wdhC=v`PiMcHz|` zQ1L z`|Zhh_QI-qBzC|8FWWPZ`0dZWl97|^D>RaV0&9Cj>or3J8sFwzC))CQ3zUlMQ~>*Y zR?0&s0!}kPUb_G7$^A;bA7t;WG>R=$6kl<52Am!mRgMs~xxw`V`xeX=dUM?|^d?lD z>fsY*TjJ)ry4RrZH7)OKR98t_H-(cf4HX5!WFCRHSpfTs+5c!=&cwuI3GP!6?o&%K ziK7i*J{lDcwa2An%VrVK$}~!>AHgRWd$7}&_ev8=oUeoTVduh3zXSccw(sL3_7DP^ zAMM<=9shoPf=!@txVt((;!v9#aC$-!V(cMCU#{WlDa@(+?Wes%+pjIW+`ZhbE!R{b zhpz8I*u$lERK~_9UVj~H{g0Dx*^tRaQ{QkHuR?WiqmsfGOe^8-2q;J~@u!_g{Na-j zjUx@fg8Y_UH(6O<*pF50&u%6H4*;Pyc)Z$&T{(OxUpkcF{Q2{1z`lmzwQ`cMG&#uL zyT@nuTL57rpVewh4>3a_uMIPe2M@deI>3v%ImoVG#`9UXr1vXkMi&-iaHVop5;1u6 zaDeGxN7(fC_3cApdo2~Ue5+!bVi0xv*9bbTu=mz`*kWd47Zlfh9BTHNJjT74VdN??Ck4vT^Tm8p2MnX&NsD$oo6lqWqs>3-Q1BSCDpPT zX5asw2w=U|IL^(fc2U>AbuWmS_dv~oH+56b3bt!7XyB5kM=nUI9x8%LYhj=gvN!8Y zy_K3lvVJE+)XfBhUutpBpV0ijzC4>dbB$1P@A^4xf|(|ABQyA!J0`&#bm2Gp<<8&i zMh4*5X4HTvNRL-}rSMxuqvv7g^inE_Pfb;X-+KYNAM~l`AtArVdR0XHkAy)Up3U$W zhiMcR^KYn#0h@sOF_bS!ZDOB*y?kgAxqW zmu`us8UAXH3-tmcHqI89Ub!m#MT)2!8(eAnO^oE%$_%QcUHp;!P2vRnfc$A!T{x*%-AF5Y$x06NTET+#l=2dDs!qChC_DYess zmhuS7Z$=lyrBSy*gLDZW;0L8wu3k0qP#QE#WqS1SVGayU7;@dPmuEyl-@Xl3M*238 z(@OYgZB=Mj$hxk!3fnT_aK3jg{(MLmX1Jw>pY#w@6qR zwb+en#6eZISQ#x>P8aT3aW7Z^A?8oC*h;oS0uwA4z0h?Qmav`W5q_T?+bsWLwkb~N zH;WP*tqkIaOT~B;JWrtk43BjgK|2asAU7$gNyT0@W#?x6;D_?Gyj~ zS@Mrsh4y-Mz!nnOwW0?;>+wSa7&*8Sm#?IzmM8P#s`z&QgR0}55$HTRU!+6>Pl_=` zi+lT2{!wR=>oR7;*H+%#VllXxWq!O5_%BXMK~eEFRM^|MZ@*aeG2xJ~JXWGBw&5k zZ%3yz23oGSp#A9kpbpui+X+l6EQVEO1R~vcxZb_pT#Dp;TRv*Wt7PGv7MnOXRi2_J zuj1j8cL%9I&iEN(9&-zMS??SsYK{&T3x`E_;8ua_(SsluP#VonKR)j&>NOK5m&|WT zV2?Syh!e0eFjbu{nYHAUT-7)$IP7t7c3Nv`SM|ROZU`Yg=0VQg3!?5ztx)2{<{ii? z0OqoJwAnrF_&4i)nAG3?55z4obe4dRVA~85WyE%DZHHC^LE#Nl(>(beoankrwnKDa z&$uB3c(5g1#6{Tk@0HV|c`3LaGF!k5=mkh&OQ|N4KlsI18WBJ9RqDq(A#aj?sVchg z1}r+Y{~J*V)R+;quRV5ej-l&@QJErWmzry8Q05p2JGQ6TQfW|M zmD3Rn2^)F?@($vzU@}0%(wBBljerfr@yX$=SWH&&?ADb}pni^K$4H$dL*s{!l-JOR zA6%>)vu}=~YJr(7^YCHf;9^8rHH=_6XrU!b%MCknMqg~*H{v5caH*y%mAYS{f+85r zKHA@e;Yq!-I?)Z%@9Ope;0p<8a;9}p&lnbR((mx&1x3?{ZNSPWWUgdU@jF*+wpk7H zsooWgO2`10+5RrbtY{9V2v}W(g5R)ShS~BIoW=XK{(gl6z*u@f>_lV_Zup4@yEAE* zZABYPWpkS<>`9>yKD#TfE2Alf)!yqMjQZrlFcd>p8e6J|{jwB7p2aV#@X?T#nYO5tk-BtdI{c z2!Pl+h##@3sn#B18_f4*H{zsX`g(a4LoO1>3;pcnT>?Qq{=x-ZGBdbWq+bV~!}fm2 zE-IS3(3iIf?}mutZ-9}R%#0$;(CzGVK6?i`*QFue-T*zTVO57$ zBQr(bCtl&9pipDOBFg5eX8i4WgAMbvY_28coq}RT#Eifo>3mG?+qXRaN1mvX;^u}dkM}T)E;s`IP^**p;8Za zSG)Vvq&ia@$QSrcBL-X2e-%sOvpx5!F5m_eYW*2(MGYt#Wbb5NI}&9eUpDTWEEcA@ zSYVT%ab6e?RQ@|Jc#r0@2!EED^w_TG$}Bys_ICTI`S}OXzGZtxEd>>oS-_q%V;&Rc z^IaJz9{{Lwvy~x6f1Uc!g&(sv)|FtWbK*|%bH9tPs;B1Te3LJXxv*D9hi_uMmOrUH z9|)jm;IZF}h`rP7rXTZ*vyNt2XuXtx@b~$T?YveECM_Y)ww#X2_ZS>#b4%xmH>ac0)YXhU5 z%CTA`-28E5VED-r>(tgC_nh9N4P6zYbrqx{6xN=I_Vn~Xrl4-c-B}zn(g`k)7kIn- zu$nAd1=Qy*;{ExMm$|WbI+6UG#KJ+me%^+V*yYBBR!_2%UQ?xoQ>E10yPF$k4PV7| znd5)@dWj!JIun4|OPC&}_IkLIU0%V%r=+0a>FG%^?@J}J4Qm6Ubxv$T+P44zJJLlG zTId3Rk~-%nCXxUb{0{5b0$}umRw1o)2p$9r2!u1n4XoWORS234&F0r#j)+|11YV_O zV=K7>DP$DZ{axK%%X)b-P%(XS62Z5bLMM*z9R@)&euPzKxp;C>^}7Tlv?U_@8su^ zBP2Cr{?CR^IX{Jko&JNFhgvlF*Oz0_f`wPr!*U@YT0G zR_9>iaQybZnfZLiwf$e-f2hn<$B$?oALbtmAYX8^>sB;<$3ZE-3pfSMY#0b;t+6+# zMVy}l)6n=3pDBh(IGZa^wk%E?(@-z;{R}}+MoX8D(9^KJ=U{=l3>tVW*st0+R*s>R z4H)X`u!~FW$9}*HcYu9H0hTai*4!~HFmud?SM#{FEAr!41c!YTl^)ZV-+>;d4J^~L zJF}#cG%GGKu@Mk{J@gjUO7~^BDw3H1HzD{&b8*!arp{Lu)?dLRQxbOM8v02C?^ z6;d(Zsie*QGhapg8X)i$Qqm?phicS*hcFIwMt<9*_}2u!R7#XXg~f4%bEK1p1}lxj zO7I!)bAIBcugQg}jp8%O$rP1(ZGzzETXbGSYz+x9U|cr<=|dV85+F(09)78mEx!W; zQ0L+2hw^ismoyzyn0_e+YikHM;qQ&h`}xK7fPy_nlwak&UTK)yxv(%ba4NE)>inyh{MM&rB~SKD z?W?ynk-YHi*)tUI*oVQs0Q2Sh_wVp}bO6l7%Mt}YvvShoO(#pInc?BHxb3$6T7Csl z3(W%kHqcR)?3+HRW=VE}h;jGfLlTgt-T?Eq9r_Xo3;<;hs0o_l(p3Y3=xP7@Yw75d zarjiK{2hOvKe!kk=HT-;C)81x+IRbxmOEyO)MsZY2VOj~q!4Z>FsO9?Q+KB3XhZ4W zz-Jo|pD9^bB-$sQO2T#@U)3!%l{n-zWE&3GfBSU*hs`b7o0cpZZ!ZCDLsQ!w6K@Xd z?mVkV>$`S`O{<{ewQK|`KFA}OgWQqGsW-4f)`ZeXwBBzF9^Ku%Fcn4YPknL5Nz}8@ zRE1j8uz`VI@)NvC2z8`Rx5SK${ZLU*Q?uMz8t(t36$2V<8uW$rVaqJ1wLfSPf)^ZimfiLMDothbI;+@!w-V zAl)ke7;XtgD8zS$Oo2*&^;|aro9hn7e(VzBWU_4+L#%Xte}&3(t&e;-PkXI05qCwL zLg?^m`9gC>VjZ)Ajf>Hk;(!1Py~sV-C}BX#L27izIIA$LrvI5ZJrN>iR-J*iiar4E znm`z+6OhFiy3L$jr%Lels7VRc5$)%oAgoON20P*v1b^gzftYEi)6CS zl}Nt=T0lT2Y3sorP~@>9wAgGF0FqcAVl?x-YlMl)ag4sd%fD0E6eTW!IB zi}X`USFc`$VCx^F(*tto!$p-e03`M|X8!{cI$xh7A$NCGErwR&(&e5Dc)<6kNI{_G z$OSbpu;;(`0euA3~>0ZleOjgiyc$#;#GvkcPhqH#O}S4B6K~kajS|gX7u3F z=k`*j)`flhfAH7{t4JPiJpf;IVYHkdVF@7kw1Z@)5YC(m1pHn6q=z1|N3xJj8vF;z zsk9bapGejR@76%Q_4-^8wpX(^<2n9&kL>h#y7teU1EyOP58J*^B}Y7%!h2qwmSy*L z()e>|3NLrZePV`-EgxjxKI6T+(urbipev?qtI0T%qDG306!3@>hj#%zUr zLr^C^JXDao{9@+fqFRAv>yI1hY7#Lct`lpEczDXnsW0uD-`{(~5}Q}&W@MVm1gW@5 z1p1&*P%8nI`e(I|2M!s>-?qFP<*}$cq89_xzzHx0zsHKcQc^CrVU;|PN0izFHLGv3 zj^2MIk3ov}aTC_)JF0|yKO1)n0((whc5vQv9%p_Etw&G+ya5Cipi{knkVgO|I++tn zOMksC)snC2bb(qiE)BFJ7{WI}OTJ9Zq`ebq3ZNVu05X);g!WNlh6nSvw)x~o-OF>1kMx3$h76N~on@sWlcp-s z=u5C|MtLwJD!>wj0mF*9FJ-Ie+#MEl2N3k@lU5$k9S*}Pik8lCQZ9N)*3OJ(376Fy zTq0eIB`O$&gK*b_vEdjfsyL|t|H7CX&M#`%UyNphCjAvUjU?EHr ztwY|+a&d^>B;%2smd;hCGkBqQUSKQ!tW8B*9RPC)uSSJ8y~NC)G8_Z2AXz*iGZo3PSy#LF$BP2*?u0!pu#l= zq7euqK?fKbiw-lpPb){Ow3wEBUMvXi5`AQW)zBAX(5hm&YxbT&h^=yDKLY6v;1AIT z965nvj^g-V|0LC8;7-jeSm-pydwFGUgJAN}|6qZ+Ihv*&=<5gl@~>md`j2w%1|v}) z(%Z8j$CrTY*!Jw>Ispry+8X9Y%N{-rqMtW_uF%Sh*BMbLP0qpn}5fRhH-IDD@LcJ*B z3R*u(wEbsr$jR8>9h-7{!A21rxVzdXsFHB(vda&KKyU9iUb+0)!wF8=uRV}MLfSL3 zPHl(3x?^0VsR^)AzzPzDNFDt9L?3ViN=>yVqa%5Px5; zu3%z%lNxQ(QzeVc8pv(*)CL6nNMvn*JZBs9iE5$bOYnMcH}|STveT(tALhvAhP9K8 zgkLMQr~Zg=Lzr=>)GiGvsBY=PPS23k`Q*=a-L%iFB>I;^C-*Vt=Yj|@uGu;d`LRAe z`qT^sF${(NJQ9vcLU`N2u zW~XVP?Bu=-hy|uojW2xHzGF8wHlpzG##971%KeRQ%`+lXA=N4s?DJHkfa90&^!Ljg zjVtvw!rKy<``*YA&UK_TfI$J$68%{OgkgrdY|JRYew72GqVT{|r9v!&+dbg>TbhKj zSobs71fzqVb-h-?PAOa;L$qdR#f;u5dcI6sVTV*1vYWwRNQ3_C3_0zMUM23Hw+ac= z`+G4%z+Ie6)~8$gptX{58!E%x0=vfsQj0|`w5EVbkax^y{sX*Y`GQ&JatfFvh1EOP zN^Ax#V8%k=e!ZelNmb2aVKSFP;#*>drTf)a)UWm}2^#JM$Kv#}X-0&yNzS}%Xz%Om zOM&5R+8k*N-Cp3y&!?{pyvS^=4gGWjllf8MBYU;cqSbwOK-!kPo?q(bK?wdnb~zb~AnK0`vlr5wxO z+CF9hc?pyS1&yWHd)xZs!w>aJ+|@F`!hAQb>8|6$r?Thf<@G_H6L#`YjbG)2y`fH} zJ0}b-V`x=J;5dWw8mDjG97%~_85pt2px^bqzt2#qS7G%@s}Q;*FWPaiNIafvk6|yW z{wL+A_(slsVbt=T&+vc?odY;oJ`tku6hd5lFeC3pQzJJVy4_8!u$Y*6koB{ndxBY( zgw8s&@?8E2A8~Rxarza6x0Q-TuFQZFFNBld-+u%D08=Tkej_y}QQs0+X#ZzDq%QJV zbWl`|6s5P%0!<;K7Iu6JmwND4o~Tmq>bf3;w_igNI$g{o8c@XA-ZYSrc&%dyp(7-W z3{G*cji2D-AT<2qDkFr7Z2`ZPLwpklQnD8wgHLz5R!X<}4%xfcpAl?->f@e*-j%1GnV!;3fzo%-tHt zfIb*lsngVTjk;yM&qm zYF_t2XFwonfD&gyu42KppL9#uVB1InW3`0ti`;V4o6O8$3Mxv}zL<*q=!(X+4(ccO2**wP4v~REv5FiCGuL6cY$oc3+ z{%0AddO~7%4O&4G=s=DjMpTX@ zaP*>_0{kt zl6{*4=*0ZcBLNU8+1hd-3jwV6j+ZT!vu2Pl@PG#X9h=S!_AJtJp&$H)@DH*gVb4-a z`KKdB>BZFci_5U8_34>&Xs*H5umt%3JT!D1yrN6Xg7Oa zP{!yWU98b1W98$tiKfHn&$?!^=1wr2} zDL1A!9`7COZiMP8d0_La+mfCr04fx<8RE@4Mq9(p)Rzn{N&@%LDg zezSmz|H-~31a*+i%nI@{;%%_!`t6J);k@BdGi={(ICQcH{nct9KLs8^o}AkdoxnjM zh3&;bViFQF4<-5}MCAMqwrFAtWd)eOu|?JY(x7Ph6GN6hzv*%`y1`t z`yhor87!bdgB)Z{)NLTsFfwLX@D7qeI`a>@i<#XC^N7`^ohw`ElC$)1Clnv%uuwOj z){-kKDZK$-8jvW2!N@oRJ&`5#ccNAb*y9v*G?b?++=pBvS~w8m%%S!X6JJScJckmG zkWF|Dtp+ra9w5{qc$9a`ooAQqIR_!`ljY1cON~p&VbJ`%*8HlarwoVTgIcTk%}TeO2X>lskfttpz8g9L*%sCC;Zz8VG)2xGHM(=i&+5y)T3j3fQkC=CzoOT?4xjYWxz|oUm zA4!o9@;`|yF3kj{8nfCvV4}z=fZ3uB=Y1+i;%#G-lA6)%faD^gt8g^U1frLt9us~# zVg%ORm@iwikyjQjVeQ_E=Bn7T3~s-(80R>0j@FM>mn&C||K4 zczlIck5Vvj(u7ca4GZSA8E{r1|0MGbk>o>?j+L{PgqBC+CG|720q#3IzWe8Ww_Wc= z>4V~ELiK7y_SI_T7pPROzF8-Ub3v!y4hXju`#0};I4eLp&11}s9EN}`s7Bz+L;q`? zK#>oiQw+eXk<$)G2ml(TrMzncqCz3zEr4by42u*?or~DmM#r)*oYscVUD>2E+xAJE zd>%HEGlGdNlpl}^q(*m;*6k6{Rlr|ab(QG`gF1npL}cSPnZo`AyuiS~j?`Nb5S#?H z!Uk4hFcFSm)&-ukf|mp%&>T7wPQuxz#uRX*FA>ENpy_}U(*XQZ2|P|O05ZZ5$$!Z$ zuNG*vEPTP5c@8h$1qMI(fTkS7XjgRcs$W#`mV zr@$9ib!Cl1+0di{P6=vnN6(k|CPQkQjJQ-k#Kr97zcpEGw>buCPS;BF3{;*REVGfK_ODlz<@;j2vSRNkk~U^84fg- zt!b%ipUA?)-ZDG~2PiNFG3X!@AT*Ee^0cxU;r3>VF;4-zA2x#+4CBq4>Yp?@K`=+r zKp;-tFX>`^2~_PvU0V2QRSDU!h#p;EBKuh+J!KAne+tAe6G+O41BQZ`H21r^;f21O zzCJa8oV@xj53dbmu@CJ}uL`P!@Yh1+obj665md)8ClSvp8A$mSNp7}#S_QFHv2_dOMdn0-JaL7h5HQfH5cKhpFz6~g=|cGrd8(Y!n_u6#qI;2TeA0@BVqwE%nmZIdcfB+mezA40_PfH#6_*XNv+;x)jqE#i4sI$4+^o)$bpa7r~ z#z|ZTz)JP7-Wyhns=0bTGddSA>-pPBDXGTbUBtUMA)$mgAqPW9RELF!SLDQ~0SyEw zrga|HMi?+R=nV`YWbN(k)%Jr+RRK2&=dXOu{T<*w2{4TkO5qwhq7WSO**-?c%+xEUR%{c3g@zOmst zoQ4N>2K)#e04xVZ6mkdWu_kEul8irvdQ}si3v#|OTgEU&P&inludaRtSjy{%A2fuv z)45dV~-Bch_9@O;3Z4QC03tK5>ytm>Oj%{o|gZ*UU% zA78XSZb&_t+Jy5}dxNznO+ee9{LDTBhu^313wgpkRZ>FCY;S%0C!%=nhrpNjrPZ!q z%FT439Z3N}nd6uN#R6IyA)H-!2NUC)^{;Sfaz?lM-vT~DJf$9m4)+w&sh zpBEXnxHavyVZbg97Ix#sf_x9+7cxh|^iqbpd(!*14c|`nvhzjWkLxTI+zTruCs3{- zj8x76<%iXpeO%B4!Oy!wMC2q*x9VIj44&;o*VE?4Mg(l3+J#-_@D>)dxQxW83E&G0 z3a$w*l7@fp4O>wSHKqDYeW$8%Sx|(+CvHNO(eVZ&O`fqjy+HEE+`B9!)SeGYz}|yd zy0thM1JE42fom&Oo2n6_U;2bjd?pb(67NxcDdA*vqB!Vx~fUi#B&+DWPpXiCnUtjp0@aDOm~U{F7c=3#fX~ zjm@h5gLG)tV6ICnt%!Dm+028Ac; zEDu&Q6w9wjxR_sX*%sD5sqpB^th$JqH0x%NdXTTp8&1MHRXs1`0)m2%^k`@ktt zXrJ*PXQM;C=3ETboj`(+i2$*TRgR!(Hix@NGe=o5IK~U=$rM;tU*G%0aa2&GIla*` zNuST@g>!>Ee-CkIidUW!SF)*=e;u9924n4s4&gg1 zK9^PH@rf--uD;+!rqlHScEgyssCydX0ZtL3B!bG%Rzn`o2G-6$P`=xI6N^&m1az)k z?IIJDGX{y=V10UH0v8we!QQvlXLc=K>x(pR%R6fE;|HBB%juPuG}7w#`MY+M6cmi% zJa!d$iRg<<&^#8ZDpI*Qk};0|U^OW5d48y3!{s}{*@q@!Wu2AB`xF;`=%eFFDQBFa znKrhx5MR5d2z-Z68YR+-s|y+CW7fKwJ+!@S8AFU8r!vhwIvd&NIK^imGZT@m79}aJ zziv#!Zc-xsX_9|2^R+>kot_YcF9hwq8LroG&w0SX%dVyAxe0ZuEB@@_g2eR> zMX$xOUf)i^MKMsQYx9s+Al;L$q8}jJWAQW}yq@l*kK#^~=W%zqA1iHaS4!!@w{Wl@x zY!PM&TO`{1g87tbPOiVVRhf9HDW$IAKWCEuI=@3hmwkI76wc@9fyR#)3zL~qLL$R? z_J_G7_ArFfsGT+;&jPK`F@@_{`knK_z6@J)iVs$T-%wQrBsMdiYGci=?pU|MJflKkVK6FJiHYINL(NM3A#nav=k0gK z6hfque&)CSSl{!*gu++;gbvovFb1jy-QvE*{QB`158Q~M8?$HA$6q?RaolURNHcll zvTbLClPJ;;{6Po4Bm`-Aa7G7&MC=Bh_gaO9b9_5+fgL@n73`e2g{e#3PRj-`+WOZO8hRb`dDt~9CG)gBVACz8_-8dZJC$z_; zAw7x96gpdKfB!=`QIt_0IR@Wl5l*r`!Em_|n|cf@L2t6el9fi4WrU)l3*+YAtJv1o z2Den`K7SY$(hUPUreR(yEr!=~#XZLQC?o9Iog=>dV8NajdpY`~EW4Sa-HE@jQ);)* zf8Y{Qm1|Zt!KAFO4D;}HY2!Llh^tqhA6sRUi|WlO-S&YmSL!fdf{sq~zpUjGAeyj3 zpE2Vfxx3=4H6sH_2Pec`3_^%E$U-bN@5&Dlw(K&45vAofuxUNH3F{i*<)^JZ9o^glZ(QSilYWsC`OJjhPKjTcnrPqUHEs&*_~|L3 z8X7oa*ZbL6$FK}@b$>(qwBvz>##K<3y7ZgJ%lW5UqXC?lcij~PV+0JYb|0d0roQL7 z+zk~mUkw{3pZ}>}o1w3jO6z2UdxEoF6Y6`B5fO*&ixDKO8?XM9^92x3jSWan3+K3S zu6)w02iNrG;l5wCxXX>;f`kC$)wbsxoV_A=VQld+5axWq)?ZmktkP#TSYVLSK7`;R zI7JY8wvfd30vfOW?R~*j5<1h=FJ5dMv=ru{h$B){r&X%;y3r)b6?AOE$4Nf$8p>oQc2L=~?@9f({MkZ^Mgxc6y78teW4fJd;-7m4 zvj{hA?k9%JWbMR%i0Bpwv$S*(_m4K*hVdcriuUB3SXEhC=9b?t5laFC#*y}fA%Kn*0U5&y|s~F4v2QE$*4U_j`h97gorFXwn|nMsz&0Vilq+n$DC7sEmn^_WyeKv$LfEUyRwF7=Sma3T z)vH?|df@19M%)aPn!;I~vh32b#|hgC@?hdONNpb3elbhYTd0HF#bsjks*jk^=GJgH zsX+ch7p%nytBt}u(4Xxf2Qxj={*Ie`F(T6CjI!V8D;|bszO4Gm`i0hs@Wl6i+(yrQ zM1=xCTGJi{a1L_Wp@*4HiNe?^Lwm zkevA{)BU<=V@;@BmciW``QH|~wR=RXs&`L5`q>qJ+ZXdtN3!4l^5HDo9hsbhde|?r z4~%3hvmHnao1rcFr(La`XY*PcF@K4fN;CB*%Oo=LqOI1GRCOPA@h>De|&ZWh= zUK%sz&%UMYuTqax)-^Y_tm|`a>JDX4;4d*@ZyLhe8RJ)Ej7FI~e`^?|i=|ytC#B+on9-6d+)A&yJ>jNTTvyiE z?wNpc(f%%%2fsgM-?;enICCP#RU;ycLHz5fIvcoKs{NIMj1CAIRvF%4TY9!hoj&H9 zQS6+5f_+hlsLI2=6OiY7t978%FJNn;@K# z8%Ky*8D;m~KjGd>SY9<5Bb#6BX9YfxL+CFCa@(0Liu|WZqG}z+Lb9TQ$H#FNy_{30 zA+I7NBm@8vT!^F@L$h8~w&D*_)fS@;C(qKy)In=K?7SNThhlvH4ceDJ%CW zp@xD4NPG(vO3L0P`Wv9%q%*)Q$BSpHji&>YWta$$w0{V7W6)LgLAQm$ErgRY39I^m zY(jt|`vMpoaJ==To&k!C^?eZ!EENz}B*Fm|6~1;^#fx)!z$xXTwF{nDXZ#}Mo$9}z zwk50r=W1Q;FcB()oeHHD33*!w?rWQ}(-F^fy-plEcBnx<*EhX59Rly`wI1=|%tn$j z8=s&J5DD72KUZx$)Mqy9&!^?G-$~A*S_tbTyxa9!+nQ^Wykq8U)5w!1ez;&VRfp6(odGl(8P~a`-kHX#gWi5O~*(BdBfATdR7|8URJnq{`O* ztvnYmZ&dAoQN}N%?z&!3YV81cb}_IQ025s5Pa|}S-kK+@YL%9)cRpFd=XX}r%+0!hClASuM3&r}=nsXrBN;)Ld*8)?#%pRxea2W)Fmqb26a zX-=8}bc&=|!(p&oXr5yK_ZjH<+JBxOzbSj|?H`jCLd0qf_&^&!K9%uHuq$EjMgzcy zR|TB$e|`EhAjubCVLoy4r0}6b??5XBVXoG#YV|@w+vU_~@PCy(8@&oZnvE(SzuXq; znpC_#B4~yGTNQoCrbAc zkwaxg^}zF;lar7~@WA!KPI2hN0-+0`Q0RMEp{9HoJ|~3 zu}~%_b)ViR>|t9pFD?%Za{Mr&{o>1-W%XaK{!~soX5R47`vhHy$DWHNtMlqM9*QrI z{-8LvHqDq8i3vbnd%fXh6KNuqhvp(L-3dF$a*N>3J}7zr=a)L)Z%4C@#vlLb zMf@%+QJV!mdfmO5kZe#awp&NXU`E3Q0TXEYtW)GKR~@glc1IKsMzmZ7>JA)`8uU2o zQ~sC@OW|IwJqBx5fcN8T-B-9jUe z`TNg^4mkfV?$-UBQi+F?#FXIYi+7x6Mb7=FegzVdt%E)UE^%`E=amqp>cS=B%)eh= z&>lKbY)f4xA|mBK6^<~{XlqwM_4rjsy{}spSnYQji}P!`$AHG$(a?l6W@RzLvpuCd z{k$dy#V)jAn?_hoY#8u$njOc*g@hD)3YQEvE19wl)Ng$RIqfX-g7c$tJ$b6sdw{Za z{(XH`IA{Orh{LuKG5oE@eMnuHSL@uDA3DNGFtM>Wj&PT!-WtnG$(HSLf3qrk_o_Zi zBVdt1*$To~#sGdg7y|lMaIE6PNK^&X&fS?TD_e5Hq^W|^Ed(n*u5{{!T1%Aidi2ij z8_{fWamdBl?*}tX5hzk}Q?>Wn<$YZIP1!t*!rs1j1?=2Q0FD6`h%idIA*gC#(Y4n1 zfE|`kK#i@*1tbCo1`tJrkDiz@xt`#XSSGc@MrQ#f|S7!hgg78O>OfMVs z1=)$^mT#l!p`axe=9GSmLQHYDwwgJ>f)S^4U)|xIG`@-b<#}$+U|kh}<~`2>wiuwM zpsV;vRJG`NQw!tnacNhhV=+Lp`1K&pEjd*+bXDqEO6a{QV5OH2`oex^W@TErG6pi3 z3mr1yYrWGR`zBL|p9fKn1jK5)U#dGdi>D#@NoFdm<3S;c+~=AK=kJHU&vY8G@0AMX zfKxW$BnLgh$6(@nm9B*{1HNP-xz*cxi3&1r3Tbc7FY>7r$T;s$tNa=>UjJ!ykIRmk z?$`SZZSQ|P3j`NrT1uynXq@)`Co>aS#qD;UmQz>6gP+7_Z_Vw?gSan{XMPvUqycw% zzX$|iVjCD1CC{HL)hR*F(?JlAWfb9+&K%i7>DYzsLkqg~ z%u;dX^kSE$bxJm?CwK6Cu!FmV>04!nXYp>y5OTNnzy2H8y=G;SDk>`;{!g`GNIftT z(hKVKByKj8y3|GPqKj4%$2~GiaGKSsI|d8-;E@v#B?Xp!_)Fu`8%83eB>onB^m1r+ zML7)OQjXtGSDOBefhfq}5r%EMO1{540iLb=C7-qoj&MSV<6@rxTf$!kwN0uA*1|9Q zGScD?hOo+(O`I|2UAwcw0+X(#?PPW>T`@DIIA5dqnp1hNjX?sLTmwB#d65?~J_dx9 zoA*}NB3q#I#~x|#w_5!Qp(}RoI|bgoviiK2K9Ob~j!`#Hkuz>@lsWtjAaau@m$Px zYoUu&f6*;0>#@gbA}MpeheLG7{k_C|2qdE5vXyCH`ipd#*R6!!TL0~rw8yVxBUS6d zBv@<+-#b6y6IX+htr}Vjh87felG~X)6-0S>PsTPHolO!uIn%wDY1_}=4!$cLT|?&r zME`-v!^!JECQVh1auqwn6@!BCwg5;o8ylb#(khtCBh(i zmQ?8QLAsF#Ul9DsTdkbrC^OHZ7nMI(^TrX<0*JC=vGf^k<2jI3 z+?0M<9agDCPyt^?P8}0n+5z9fVIyxk5Yf`C$Nbk9#T?Ywp!%OZ->NdY!oy`wjftRk9R4ib8H_1a5Qsvt(kaPfWNBr)DcC=Kl8l7l-Do3*7eGs2w{H`Pb-^ zo&JZWr{ZNF^^hRp_o)-aP|$e+OBDmH>ds+;vDL#ZTeq-t@?EoYR5^zhSb)jY0Ph$f zTFzVXU449|kPa2yQq)#M4o+5wN-9>kcC_0hEE@0Z74w6Zt;a7SM=9 zIAx$_$j}6kwDIC-<-#QfK?whl{w=_@0;Qisz=PLd zo{$LcAVvToG#T&Flh6rR7RUqP@r7CdzU-_FRfT_T>SMT&S z2ZGjc4j~2Tpf=m5Kur*97V>`pWA|pm7&i*mj2;ed; z06HY0a0qZYHlbNj&;zKLXt!jVxQ!`Zm<63T@WC}Qttz!Ja1g|jCRV%`PTr{YgY1l~ z+*N=Pyrbxy1NCgwrx|7;2E@jRK(Yi%WM=pqE#eNeZjf4$vB2W?>+)8Ao*{Fx{XXD# zcZnI}GmV9}qLUG6fpx>Qi4qQgr$fCcPwTHi6G-wtFv{En@VX&Ty+9B+Dm`t4r|$&R zCenb0qy;zuG~pRG+;&9y;HCBcv2)0@z_i&g?Ft*My@sU#_6C>4 z4q#AdW_`>+gLBF)oRJNooAaznX<|(q&v-rQXF?@9A=o@HhC!1IN90&<*Qlogw}R&$ zB%}nmCe#;ZK+%VHXiy+o0}xUfShdgs^LV|nNq_;k2cj@JC+}*UIg^T-m5!RF6ZiAm zv(`Z(bsg;u?@OS~UEu~ay!%3yB>;Ji6BTVl?Fyx}OYtR?r|3Je3o^Tfr5spl3~df+ z!%E5qC=NTY%(^Vt725Sk9k(MNg(tfvtlRPtK zjPa>LBJ{^9*dz{Ym)}6FX}U z&(fom{bX7^hx7wvqvZ^nn6C5=`c)UOJ-u*k{%q8+F>Qld4q4p7X8?Jxry(j|#-%o1 zLF1vP#8O%@_r`eM=FX1t-EkfT8AUY3LL9DQa>3a%*V3%dvudE@LkCwA18p}bPU}qc z3c2qT69YMomi0^Zf<<$Z?(Mg|Dj-5}mo|0e%wEiX znzppGS@#D>9tVR`o~ID`=#BD{eP^|Z=oKI!!6ei6SNgm#e8fm%tfpL)G&R*Ul+_wB&i%5Ho&eSE}^lM?ZKRzC@ z@-z$m@sXp+iB{Wr4spzU`AARlwauV?f65=!C3PeLe}%&-*792+vB+n?COtI*L|msH zjXkHmuLMtIstt?GRf`x6+bTcCZ2&@;FC^YC-ojbac05IGTWJ+JmhV9V((co7Kh`4N zHc$4CXB+LQiNa_RMQUa9D_V7758TusS3Q{2-}y48wu$1qu$ZmNQp#Xa#(2Bi*&`iC zrL8%`=X3q4=gd8Qj;3}okBjkC{$L8ry1l1R^7N%G&2r5IIW8;(f<0L5+JK*CmzH$T zjyr;>^nU)r>w^&X7j4>F^#ApxLCA#v2QN%o+dBV`X0=%+rW;-tMR!8W0RKe8_R9YN DY^}yV literal 0 HcmV?d00001 diff --git a/_images/8b81c2a184c076c22ffa803d1d8ea294a5a37b812824dd1cffab7845b1aed61c.png b/_images/8b81c2a184c076c22ffa803d1d8ea294a5a37b812824dd1cffab7845b1aed61c.png deleted file mode 100644 index ba9e82e1b750e631ac4c2d36158ccb169dc9399c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 26399 zcmdpehdb8q8}>uWDk~Hb9(!hG@4d2;tc;9g6UoXhTV|A%5kgjpvbRV^LS&bjT~Wq+ z-F<)W`$xQv<9GayZyuj<-`9Oz=XIXv^+f7wtDYgECBk4ZXVle{^f4IRWDEvphu{?a zOV;ODMfg8)Ph}&|tFCsQ-c}yAm@8JEZceVAPPcC|-nI3(bKBKLh);}|)fFetfAmjMg_bjlyGUk6=`KL`IR& zZT@>|=Wm-%;}u7xb#ZZT|Ecop7Jo*bF8aGP`R?@G$yyW-;fTUUpr0tU0#6JUegs{3 zl9k{m{~Waj`tKoPVpekaSq=|RL?7I3RZvI2_qBS)f_~pnp-Tb3PB1s(h=gCOUHbp= z&pQ;BF&e`Q4$pdq<(-Q|3Q|m##n2+CbgdEDy40K!?eAn}n-iGZ$j1t?iXLZ=OPI7a zB%bB^#1%{%+uPhZrQec|KHn)%rmSZmq2%7(J2pp671JYx-!k?1Ry1%Fkk=eM4kNRT!DY7x!7WPvYTJxL3444RCB5p19H&gs!X7 zw?J&W8?Gw$YK4d~s{9&THaVUg-lj^qNzq7t>B2tRxR^}!jqS#B=`o5WFXcW_m1*G~ z2b!AU#ktf!Sc;Bk`Jf8du_4l`(fw|7dvozg#5ta1o+r!~UNQ+?{ylOD?X@5?n<6h7i6bknq)U;jM;TQdu>t(^nk%S>O!+v#{1J$CG$R%R*n?&Q0cC`_2` z62rH@6pN|5dL1X_;J(bLz0^B~9=)?0{&2TL)#Imngv5-9=pq@s_BWwAh2r6r%{}wC zrK4(B`czzMR6aYR-_Q^zaVOtaA0Kd7kTnt7#~IZ_(TBrk#IfVy*>NY+%(>F+A-rw( zK)Ts8gW~X;b^Vprs^qk^QC;y2ZS4#q=$^a!)EfAYo`jZMW}I2xp|BNR>y=mQ@js1m z^Y93H{P-N#^_QnFT`I>7yjE&N{`vFg?FUTo3i^+Fs5H1Q5Q{yoQr1vNbsDXxeAE8J zPt^VIFXzd|fD40zgZqJpM}IeJ{eJUpZ*OBTA&fcx``h~`ccu%5zka0;(Uq!xf$s0Y zU#CEbxp-NV@v;C(uJ)hX8uF|;{%6kBzJ1#|GD3C#{{3U0Si_Qz!@s|YDL+iSah?D3 zb5+c3217wXv2Ee#==gUs{lohd?mUlg?(|5ZH^aRt-1x6ecsoqd_HYR%@g!p^?(~bd zPpc<+rt0hB^cSoRSZi31yIfuMlxXkjIxe)4`TO_p@8jRe7d16C4PF>5%L+aHcr-OW zZk!r}UhCMVDtvqE&=YP?DG}-F=S{mBUv({++hKfsy!Osw|D9W+d3kvWSw~HZUp13C zwkF5XOSBCSpG{3ojcOph$`XZLm+5c+`S5mk_h7REZ%$0onfhMIww5m}*B`?x;_%PH zx>-HknA?46nizY%sf_)JzrnStt$em9>_yr82e2$lOZM&U?Q(^FzS@Nv1tEoni^QVD zb#-;_)w)bKq5?v)71w8GQXY19?{Dnq;|4jblPuBbk~4h1M5=m$+6RK1m+c0JvR?ZZ zZ$bn?)UaRai=%>pU&9i*#W8PezJ2?~BqH*wZdC-mNOE%Wv5Bf`*EtvJ7Y4-?PEJmg z{_GECkCJ%&U(XAM*IPu z>>d0KIWo-F<%{{u1VJ3QGG*`cj7L{gZm<#0_aw3Jf7_m}e(JqG*&|Ct*sK|^z;*R` zOwZ$jhR1XKE?u?@4qlgd6E6+rM_ot_m?OO<*>6Zep0Fjfudv_OwnTaG`iM)PqKdI7 z?6J#dA43*;v$8FfY?I9aYt=W!0}ihvqNDw0*X;cL{f``-ot(1Xx$KOWlaP=QHJ&{@ zq@|56zia+^brv*tE}o?ng| zy;3yf#$WVr-oA#DvXUBR;_RVQn5?X#(nY#pSu`t(CF_IDnqnvV}SL2 zDSm?Us6>w#cjdZgOL_LmCkJby ztj01jIgumkSe$4%yJP3*@bCUd#W$~BDRo3qS=^KS+R>q0`8y#s^Py;f^J3nJ-OUTTOedoQ=xXF?K>eZ`*(YJ5kHo8?mDlB9#EnRpQ zAhp_jxs)g>^_3QGP>Mi9A{nUGD-60_0>>rp}w?6!tZS>L>wGa@7XLbX7@ zrLAo~y!t7tW-8CN-Lq0NUfRCBow_dEWldI0-o!}rz~={kEL4!%dnrZbSJ)9{w$qOmTbeca) zPTm7myzg^$-XnA2cl(>OZ3m;N7b;Gtx?HUKZag(i>N?8Fy?Pna=R!07>7;S}l9A2L z&7g-5@l9UYZ)FE&B_sq(dapA|NYLhKVp7vV9AaB6mP!`bY4xHwPN5Y*5hUEk2K z1zAw>(Y}+GJlUf{zt}D@l)1^MHF6ayDwE&nt|*b$2wH>!THph;5U$(yRqykbGI?#_ zPrCK5@7Pzp{yl+$x&eWgw3#K-&OA9g=>|S2DXGCrGnxj!-<^;)+<$zz>^4mY*OhR2 z&%_lba#_>*%BHh%ry-%-S0X;KJHM&5v!o((av1SWp0wKe{$XI*lf$@*<;i8o2X-Hx zJoDN4US!cE!^6vK+oPbQWI!n;5>Z5^q^DHE5XZ#EdDi0qzq-Oy+Oz0-WAjEqK>-sB z3rmybgRn40Ny!U$@7^UKAdrKr4%YkJ!NbFAo|-a$U;sHVybT^(ttl(Iqn7?LEB#eg zjBTc~yQh|>k!ijERc#j+zSh>(ZDKn&H~z$=q-TaDvx|$5E%=|pQzf!$YCK7bh*+`( zC`F`Bsl01;=M>YR`hdo6I~`8*rBK|#B9F+?Ba=++hmNB!sW{RE1OzZa@IuraX%H}T z*7T7PY9g?rKX;ACU|jt=UK;}bf=}I9eB`CQierD5Mbo?x4#in z_DOiH$Q8_GNnx>xr-)ex9p92?KXBnzc$8RXQS78INGi#8S9zkwxiaAI-LY}?W4a9} zr1J|sNl?}%>+THL3%j|y%MU-lvO{badg_d&vor7h&&Y^wDZqtP@=p3}Du*8Ai|cGn zpGS+Y;qn;ZvejQb8}P)S)gtgPoK*IJ%xm>?$5ex#UT*v9^q>3m>FMcWe!rZKoVSMy zb(p24=|x0D>^~Lh9cgc~U3t>n)1&^G2Y`wMtWlI&;n~XNz8gF;6yd7N;<_ba=lYFa zoWzmPYrg=|u>JS7-r$eGcU2#=q@#cRn8n6Zsv+Z8++<8-;MW|(&Xjk z@9i#;8*ovrd@g$mdm-u?CusYg(v%OX0SZvxA$zaARTJE!h80uO>6MqW@&U)aOfqjZNz!96Ji=LVx& zppkOmF%Ds4P-c>HApq?JF>Att$7Kl{$5*<jiHV(uCkN>6=IwonKXiF@m6(`VhC4W-o32uqg62_syV5Jy>5HS~ z7F}7=egiMAaThQjs%mHuX=h5LSO}u!$jG1*laRpj^YaJh>CAV=S~)tFc$xtYI0f%} zij9}|Os0gFg03!Ejq}8VIC@Dg`sISE>T37($-09OpX~+p{QUgpp&^Phw8Gt&(ylxe zNeLK+GtL+d$Hy<2ryw6}LXR8CYg&W;(0;m68dl0~NU~^Wdz*}!Iu%|s zG<0ik%erX90d`Lombu#QgYH|;+vu;;rJ=cE_Sl?}_um~(<+m5n2}@%E+T4BIMrP{ej*{_Gs^fxw*N9 zs=k@NKE=P#;QyE@`LMoTN=#BRPd$lkf0h4&h!X+e&415KiJsYOv7i2x<0#4P+qcnK z@(&0|iL=p#MRJ2TfY4a^#F<}M*!JZM?U@TAeGnQ?gaw`!oB+%V{i5JaLPElOi<#bT ztDkw-Cf<;KcyjrwL}JU3y>PAnzQ>VDHl%BSnu=t2dw>3XKi7v6wOO5qMi(nqkPG%% zh41oZDtgJg?eOj>A=Uq$^3zZiB+BK$a&f(oYl(@9!o}S4@qyepQgU51DpsaA(zurD z7XhL7)dV+DDsf|40y4`*r<1?mYja#3r@3~Z(efqkmLEmJD_Bx3xx05oe0P_ErTuFc{ULkTfMq4=cR@tj0NM6Csyk8_5XVHcMVtfQVlp78y-Li5Qu2QKe^cf)zI zVf%atMh>HNqh*wU3ny1Q?2AG;ZLsaY(%1JD-m@n9|59v1BqYtfgPo6+b{}XD_U7Zy zUv@}_`mC2^AA#gcI6iDdIAD9!gF}md?|{w(-L^?z5X;7gM{>ksILh z@LaPWZ;*H)%4bbkU9My^hTbEBBPvbI9c%Y7E0*vqn`LJV%_SaU+RRhWNEOMm&c~I+ zm(S^aXO1A#YkiLAP&cAL|3-p<=Ntj|>uUl{#BC`_NufK79~WJB#eKF}vZQ=)0q*bp z{kwRs@A;Ldtsg#I`OH%{PP=B|OXIGmgOQf$SZ!DiW@ET!Tg(!gP%_9QwnEO=`JC}! z>MTqCH#tfiQGD)CoEtH3sWJwud~c7LY>DwJ0*hc1a{pjUHRhr;?FoF6_A1+6qKvk* ztfz4wMn$Ym7erX>SQS`{FqpT;*;5pZa;!x;RIlBtJQNmJG6%cfk!p-3>n=2$7lhLS zM;Xp0RJFgqH%?$2Mqg$&kyJx{-`w3zUVCd&M&ftQTxs$H`=hzDlgB@z2$qbLkAow2 zA0?(dyevOBMoAHx-)B~I4c9X_?f8}%CI?XalG2!I$za(t_EWDn6>hU%P`)#K72=Q0 z0dnQibd#)v=Tgvzr=o40ou>-twdYr7%D2S+y5A4>r+S_9prJsT4PU#{G-WDL{I&a8 zWpeM0sSlSPx3sj>-u*#~X>M!FYgWnr^4d|cK%Z(^;@0o4Doc$M`YK)c%&RSVY=QQS zwg&;yIM#Q~6g*V;Jj0z>9a1o+nwOt@@2Yh9eiQF~$qz^IY>oGZx#y2BRKdZ)OHzeG zsmeT|8oE?(wPcv(f(Xd7KmEa*r;Y2)9?8G%2jvaGP`U;G$81?rNU;>G8acOzpYNX> zo}OkfG%Pnae{}B>eN(>}cTeAfPzYvB-1u47Cydef`F=ZQ!GK(jn_Gh%2YZWW2yo5+ zetaEN$Sostdo6OA9-za`Vgn*bEs?}TL<;fy(lbLX%86UPpI0KwX#-e$jJ|U)GoN5$ zV%onDpq(uf+t;Tx_T@{i`+VpANg;lIvbeao+IZDCi*i2ZanFW1#hJnKsCJb0khF}GXRwbaO^ zG$e5DZplNEpYJs#*r-V0O$d93Y@W?;&~Ne2&pJ+jzfX>XOIJo$`Ma%QvWWSF9wj*q zjj?4Oq)KlLhM{Kdp{RpD)^T=Kpg_Q^cdS=Lh8$z_-C@9P%DuhN?ws$3g%Sb`T`8}d zjh1He-367*xz2E1B{rwg4>#^TI+CjrB*b8q@)rxN728ksbmkwELqx@uWBSIWXxaFjLyG^cjp9$Z6dMKTkvDg% zZy)wZR>hQ2DLaXu4PBEeX&TQ_?btahfmu_I%cJ^7gA;d(Mf=G3gvp z-Mzhv+S=N|O&)jd9Pjvr2V6=2^t>V@)G7Tk?U`R2;t?GaI<0^bsHv%akGVR|f4tAT zBA{twgq_oO7v;QKvo&0GnV>N}Le%kH@7*(hE}^LQV%>@=oi90g8GBLnywWpD<*hna zt?X^K4#y}BGCU(w)8oZ*nP4v~TXu_QctKKE_$bbveKu(S=<(z0`4-=D^@}Mlz4ow} zpwrm-=Eu3;b=WOmM&Y)9pNQC2z#1x$-e}UxHie2HmE^?>_1d3iZ%!(=zwO{MpYga8 zeSh^vfxh&cdg;Ht@87>@KECVj?(@x&NT|Qp+}g@&Ycf{UkJ?;m?KMllk*go4ylzWV z7Yc!~CS~`_=4@SE%e}?@MjUx~Viv6{JXuvI zqqS0hj4|TiK0o9q|EijyIP&7!V38iPu+tbB00f1@KR*G&{aq2jV`@?x8%z7HZK_B4 zYg_t`Z2A;Zx(V+Wm@Lb?Bl*wdIPs6F11@D>HaTeT^w^S&1c$QO^U7paq?@8 zaAvt>b#`_Z5(f(lp5y1zVC}-tvNGO-g9D;I8($xvElba{TcyILrly(_E`3u3lVSna zYfPuOa5%nkINSMNM&Wg>w=C6Zl|8snC}+xLsw!6JxIn*TX5uYw|9S)Oa&CpAhTd#Aey)-^2{G{Er@S3iLZ`GgshFi|HbZ61#0hBN~$-P(AynD;u}(C{!50j>k| zT{DJ0U*CGMHoew(uzJ|h5)q-9u&XZqu~yP#{!^HU?j0uE%A0Vmtlqh-w=P^wVr96_ zTEw5fPImf*q}q1n@;88mq0rRlT`f5x*xb`Cuf)UAH7y$0(v+>eem9Y0Hv0B!6D1WD z0DA)ix@PtF$bEc#DuBmv9mw>^FK?rn5MXh%LUO#ZHC!zF)G^n&QxaxFfI;r7L>#witQXI7x3 z+K?7v{j^+>Qn`MeP%nh2qNcjtuWbbw`vco;We*PzH)ua_h0;gMWdn484BPzu`;x98 zw_$1b6suUbXF`a|c~V0( zf{M=SH6%zr2{fY@`IXwSNn)-8$gn?K*20oai0%8bwUQ=u`#F{(aQ2~@)E5(=>WJMF zer0iM4ndv8v%{aZdf3`Vt-4a+a0GF@IXke`Tkb#d@&B*2X4BHU8q* z8&`%@z8g^=WseVJ%LkX05P+Qx?85#s5ezDPQyqS6q4<1Q<}mGg@ks;Mg*XXbZVm}< zW6G_qt&>FG$E$B8B=7DP%fr)fRa_kY_>q)^Btu&ClpkM*Rr_aR%PS;{!U@$UPf3qBsU%jYL*Ld&^t2Fb|HE`9F>=T#&j*IiItD$kK z|G%nf#{&CyHiT{Fd(u-fMmhhEjG&-GAv0V0_cu-EZ=W9yIE`gyCa0jly>zJ`ubWd! zif*IvFQ2Cb{jZJb__toGT=YFNw}olVpowhO`u?r=@v{*JD`)3e=n<&WdP<=cJ{rQ& z|NLQ3I0haAYTz@9&G%oYLogB8M~^)jvPY{sL=}ChbaZ{0AZG|A7526@n*Oc$_J`U` z=Pe1Qf{Z8YA}@eZp)|We?CrwT zkcB$D8*e@3zr9bXbe)zlDB7Gp(N*k*nzgOD4hV4QhVd|B;^K#kWWTn*^*(KX&Jb(( z(2;bA?7r+t(X&I3G7CcsOoDC^O710lKhQaOYs{GDb0-yi=5Us@V)he#Sceo2#;7Q) zQ1(|87Eiw0!qvF#D-N(boky(GGn*}k5iv1gPoF-$IUWhbK&i59q{_XUVlP>5DC!$h zC`Gu{+*SENae4N~_t+<_4o8bmR{>L#pFdAvVPQch;TiFUoVCXHr-T2|{^GsWvNsjZ z6C%J`z&bCmu(QuY20p1_XJ$r+$pL2PBoU&YbaRymfhI9mFcA@X*lu~X`-W71cQ{6_ zjC%VV2hffZY}u-<)7W;=s_oZE>B(@F+R)y}K)jX!aZ>S-aU?FOv=_SRJ62Y6ciF7 zr=~uoso5q;)Jq3ITrVNu_gC+|?@wJTe0J=1mj)G=#Z))}fzwNP${87*7jd16ftHq& zKGK{K5IQguoNgt+G~!BRlGN1HZ0_uE^CuY>Xi$v@@^=r~Z!Q11Bj&}eSKf90#Wmc? z%+g9nwX3y~<7($B(#&ezaDZ)Uh5{vUcg?6^K8+Q2flE-2a; z1}>Ae!NB-21CQnRYfT=Swv;%fa!%+(tgNg~+6jVs^I!3XkRhULHLr0pR)=IieXUg5 z=YqaJ`}Gn$i1^O_mMbya;$u)c+Fx8NaRbKrp06(#eb*YidV)EC-mPB~uJc0$ngoP| z@~<66;MSBOAt3{xI41Mmpv5Plll%5wO7Wus3me-Ukfm_vvlJ8<3>B9Fhg-=c^j`h_ z{mO5(moiyAZ`?Q8IMH(a!HASV=gJl3GLzQ>6;_ICQw^reVs;Nfd*4mX$cTaHlFJ)p zWMK*G@~&@9@}Z}!0QRPdIMc$av z$Z2bn@L4pPSxSF@?KsL9giBmcEI zL_~cmzKYMR5`!WOPL&9pDmDF&F5&?@A4K8ePlnu2wo51GHwS?l2y>>ijQsY$Y$s*|Sd+uURNAAvm{1nZ4 zX6V!Ard;=z8y|Xlp)iN1PK5C9x#N_a(Sr0 z9tdoZ2f~1k1O|6Z`f2R$_O^nW8UX;qXYh379bOiC>}`Mg=5{+TxXvW$$h3@AS|ipI zj;9nH&&2S80@fPW={VGR2K@cCzqpw$p+_kYc;t_W&wCpUzugwP$&aG~^cj*rs-$D?X!NR0@X(o&uR<{pi_LCd|( zSp=;RUFY^F0+f19L2a}UuzX~{h<|#FQd zgLGp9tiE35(pV)kGzSj>c3DIBr_q(r2M27R*4BR$(JlHHu(Nj z0NBY7fs|iRpzhHy_kCd@>?AR@cWAD7nhupPDvXd2+I{2UlKq#qtcnJ0btqQ^p z2Z#}^ZikGg;c!utN%Z}F8)|GCv3Z+JsxZq|0YFbn!{$eZ={{#ZI-g&K3gX}8cv7pwM zB@GpW4TP8o$~&{ICxt=rKp_AP`|Sat03hI(2A-YZyYV&*X&2UAaT==F_m30PAKw0p ztq@w1`GlLp+wOfACy1c=SM#vvVEMo4h;5nIFN+&C!skhOH&|L*GxuE1 zzY9V7>h|!d)z4*$(~TgISnopC?`Djly-XBM&D#pwKiC-HS1^ykKs^fseJoEoni{1F zGcz+d!8V%;3JRNTq_UQyFK=+%cq`nvH%EN>qSX19FOR>j<-Gz?Z*Jh3;y-LX(K{MH z)C;FLK_2WJs6@tHl#ZI2vHVnKdcBednA^+S?wIx_|GZfm7Hx zCbaPV`^}l=;IUeF=0;TOGQ<*AOCom37#QNg0D)?V8i1KME?@ZpvndDK9~9d5rdoAB zVuFGr^5ly0g9wPz)9*oHL5Zxku8xU=1Aax)areiCCR307p7@3%GrFNvztW)z~1vNj4 zG))4h0Ch9eu!J{tRYg@5iCiE&2_F4fy_BksjT9FXn}IVeXJ9~C<1`);7KZoAd4d}F z7R0{_)5c=!J~>=Yy<`ywqAibEt!~2U=RxTC78^Z4!zV3u|H(yDmU0fi`+X0bQqLxZh(i(OI z6$TB^m7QqxuU^%ww!0z>suO61Ts5mth~O9r+5?PkLx1Bq%ICQ>fRoEH=cXj}IkP@i z=uHv^L(PTr0o;(jh>-_}U z5jYy|pr5Wu?23wfC3By%yZMaaQlTMXg)U**ruLOxl2W`BjUbi07I3+sA`YQR4qG9* zROm~V{xmf8|QYn*f)bEg>L|zMC1pCn*;HiQ$no5a1{r#Pt zu@?kfr=;NGC!h*-)w<6Qz|kMSPf-8AlnsZj@5yD&RL3;zk(##Bsf|B*PBy}8q%Ey) zyKN~jajG&3Gqpd(d?fII8nH=d5p)AX#NJxpH%(Uya3Cs1qJq&!W52`&B}P<@4E}y zE?8?%koEi0h44|wG+t$kDiZ{p+K_4<tgp0#28$32{ItNhl)5`gxSC| z;>m~8lNZAMgb?qHAr1`!F9A+MfCqmBB!FkNoBlYZX5;7QiOW9B^5T#e#6zgNuU zJ?sDnN({?dfjn^En3ArCvVC6Eg%04h@q+1RAhw`eJ_Y)2$h8tf9E|?iYPaLgvr=!L zMzIs74=gNOS`|ESq>)Vi<*Bq!%Q`dT!28WqhzOW1n@64!nJ=8UYM9y?OgFxYRfz=oJY06NSdk?^_kmNXQBhJ z6L6o?&}!|jj1a>qZUuZY3y=toPc9Hpd&`B{kJ8ikP3C_dVyQxVQ8BV}~lM6Z(a)6-7d8YVq?sJ*x z$HOO|+IiNVTzJs;YO+u^m^zpPw>UmKE-3+fn4bP13~hWOf!wd8=`q&Gz9{hVQeQHU zNlQB)!ytRH>F5vli|gemodAO`eC#DrMuLAmj9F5se4sk<5_TnMmtB0%@yE5KBb-!p zC4E9a?w%|p>KsW<9(^4gaA0vLKK0<=Lwrjlsi^inWR@Y)ETGW+*mkXEE3*3@s4kxClQg&b zGg`hE{LL{me(#aF79*u(;m^`LrUB9tHZo{ZUSBban>7Ra#N?SeD0tt3k6s1B2TzxoJDG zG8D#)9o9E1j7XokZHqp)No&9r9Gfi?5?f$WensL+NoxBOnKM?-Ow;S`SV8j|5<@nx z%(-?zD=JLQy=MYr9D-F+G%#|{ZgDGTQil|E1vIHtq-=4ZNe9058eP+F$pHIR zdqPQesBzd11Gm?0sll<8`Kke*cHDZ71EK?8Y0AqT@jNdppgm(&8eC++#do@8woeDHkiK zy$Mc;W-gZsy%SSYQ$_j(L?m=#Ii5CHK{s;w-|kL#@}1_JcIrs$S5gw4{R_~7_e=mX zL@5ct`ZIt}8eL4-6RD5$I^Mdsz#M^wOifu5)t`O`+>|f7E@ai{FTisE_M5Pj6e^JY zIVZ02M|2CDNzg{mSh#A)xJ(?q)@#tC>FK(R_xyT7WWVI?XWHJ;D`CPBj5Dhuj>BOSX12+=4PLtmPDC<JZFY zubj_BlxlN+Pt|Hop1ly@kX&?2xR^2j~}rJkTNM&IR2h8+_=faMAX08ZLm3el z_W&rvA@_)G0<)(3^g#8srp7kqRO&cNMX9$X?P=LxmM}7UF{9sku|S$$ujYkN=?|^H zzkcnY{Tr`?CJ-3kDDdLUOt>~(LvIlb4hSo-KY;;z-XndH|M2M_FwpBiQ#gsTDfF4j z3JM|UhRxtPM<9J^q~u)h0x`OvF|F) z2kR07Q26e~RGB9oR*(@IB`BlHQ0yyRzDg9#pBL^&k6&F?)e1z**58e$d8irxF6ps0 zCV=rZ&E;tSkr=v(U|vMIFqTV+C2IeRmPH42it+WBB!%e;-WI z2nWs`^$y^K(?{zY1PBkIqx1Zhm|hzu6ntQ=k3x)=zP>&<^iHKj$-16RukMIGH{W}y zsU2o5^!~Z?&P(0DNkNW7hKB=WGID%v!ml~#A4X8Zcmh~uVt-EuX4_UhLaVn+3Pg7^ zuo;LOHZnHmL?3fopA<*BJYuR~XQ2I~{O_|uc74qNh$@kYkVlrF0ODpS$S(6`Z>IDm zq6SgN{O2L?Z8_iZ?S1T}5#&em|^ z6xg{AC!niPw*?=A-8HC%S6&iFoi}i&Okh0)2P7uj$aJZuv zWi2f$6L9__yf#)DI&B}JWdOPmT&sCpT^jBE5*64_fyB}SoOh8`!6pQ_t#B|A&I3#W zF&zjCJp_;kxuLZ7Wr&{zbc6hg0IA5H4n*ff7zGU9AZ zHNZ~o{=422dcx(6NKzklBfeB~er6shWwkhjRG{B2#6cmRALmX-A+ zoWJW5Q9U!fuGn0x@Ad*=eSQ5vnW-pZr_u8(IDCD38Be}>Fi#a;QxLtTff8`4Y5Z2W z$Yoqq!~p@M$E2jJjF`6n1+G2{++BVke}EIR-d^ZIuc=`4?k+D-Ed#|@+2J*juN5l| zuC$wQpirj|PLCYOU%rIUy#qr(54`p)O%(+K-B@W*c<=f7wZV)Az&-=?2F*}2kyyeA zS|5D;I*?xwJJ`f#@J$aCXr4O&F$MBY3S{#oal~80*_nm@15&3rR4OG3h$vL8fhq^B z?4&#yP(Vt@AoZO9zlY^uuJU<7n+U{bj=~zMgCL1&H8|?Vs&B=kYg&LklmH=rB)@U6 zMWVo?aG0p!otv8jCxb17G^`AH)|5QzZ4es?+=DT2g#Uf=iTE8h;F{mNnkb!OfeZ?w zaC;EW2}mJTXpvbep~laEHiGD;*w`ya8;(1k-Ti$hl$zgv#!da4(Za$-f@U({G(k-} z^U^hy5Nc;a`~T{1oot`-80_9-A*N*@aeJ%g`$emXunpl`ohR zmB1ED1Cc0Vr;FqD()kCX zzM~MUf^G2LXZ(~tYiQKF%knuHHzTA{ASPU{tM7~+*^_)E=4*T~(o zwjfK$)tqNXSbwZ6eH))mP@hJe)<1AbLL@sf7zD$XSwfvi2|3+o8k~N8N8RVnaHnw8 zWPFc!QxE40CbNKnXI?`IJFl;_Vwj-OV?E4-3A~FMl=7xaTn$ z4qZcP5MfieW@_vaDo$#oJ*0v*0XDhX>~mWUp5vYDf;M%u^eRUlSh^ z7|2O~GQ<#}iaZp`ro-L)rw4bm`x~!>piW6ht~)mqy-C1xwqs?opsl8GW}(N6^%`Js zfQxgzCi0N=HMMQI<(IVIGqO}6!9lBkT+bFIr?0~I%Pc18p3P1t^e6fFi~2Q>c6Kkz zpR9d5(IX<0@a)h0iXzLc?>&MwjF?rOuL-tJcaS=j|4=_Gj_g}KGcPVUUV84~VB0(e zxyY#n%XFxfXa2MaOZD`n*!tf=T~9v#Zw+nT-g}xRl)>90H*79sck70K4Zw{Jb7aq6 zd>@dN!$|cn*%^(S4~>5+*`>fsjZaWwD_o z*Ht32Z}7QbUsqqbM}DKE2{=Rc-!d~P@fg|T**VnET)3J}ffSwI?=z(8-hQh}ye{oG z+7EtSO-M~;``WCe(yG9_L8_liU}Rc#NMZhQ=2Sk5yALjN=9FPxsmg zpNcpm^a%Vlm%IjcUa#kaIZTCNQZ(QDow0#xX8&e-YaW3+#?tMoTff_cB)oEa#J1}{h z;|m+DJZ9}i>7e^7hWCbEI2bfvhKLOyW_lmWS zOlhQUeIQ3?Ka9@Id2{gk8M3irqEFP}eqUrO0t`BGs0w;L*NaUxM}hzc!uO$)8@?6q>r`jy8D`?N2W`I0cYuN|&|bWI1q zs0*wWy5LQKF+KIPw4yz;x1NN^ScS$bc6UAL#N05T)~J?Hf2gQ14Jb0e%}>jt#LG#t z@JUstK}mpy6X1UWv+5kkJRDb_p9U^3QZG-1Nl57Gvb|C`1r=2|7-VwH8+>bhcGwWV z1b3YWV_A>vK$Eu5tC!G0FeM<+<_M=oPFyH+pX5<3f9MFnL`w}QASBE@dPIiAq3M9%^iIysDRIhp7&Q%zR_HY1 zp+9N+{F(YJn^rRbG2+8p!qTdtF6o_kwp1R31)5(sXx^G%K*?lveX*E$Bhy4(FQR4>8cl0x7!V&nRN37Q7ExsI0T+gfmey&YGs8KrKF`rF(9lq2PIt5A zfALpZSiCF!`H7bQ{lO+4_(|G*f2X6vja&kT)0q>mwr(3^pp8^n8EB z>*V@_%Qp?QYor@P`)3UVN7422tf5LZ9Qd*TWPh;hOACJWO87Lr1SQ129CRq?$`J_M zCVzyP0tkkFS^XlQMv%IBi~B!vr&ryl}6Az&S`$~D1 zUArB28cB|jZPb^ISeW%FEAK37gQhSutRt%|Cx=1y3ux2Y+S(MC@7c^CgtAmuT3X8Q zwPKJVe&-a76e2qs@E8e?9~XKGCyt?kR+U)VXRwVhdDIT%IC8M&!aqTnG9x>H(xq>p z?!oV^4)(TCV+T7%cJbm%PoBhP*rtK!S1usI5q|c78*$&;w1TlKZu;1m({Mn@8xn!f zLkkAsvH*$F7m-7~_-f(5+0VR$1n^)$=ju3+ zg9A3=_)6=po6riu1T&&8lH-)aJz=VE_s7J!#>U3lds|p&C?Yf;^8xQpB9)x+-#5OL zcYtgI_mczr4>(9?Ha6mca&fO23hLhFhn^@MzCGn^wCEaFq-@w$@f$Br}4-`OiinEGY0VUa-}bl`RmH zZfL%+px_x8S&%v)ZdzOcE}#Pt%Qv^TTS1%@fJzIUs`XrZBu^3xG3sCwSU?XJ@Y%NM z14j`wTJ4Z=k-k}Aot^^1OsVM`5&+kVpn0D;RX0Uf7-t#^i&+K8KVlo+JYv6f|o3kPm9zW^ut@ z^`N}*4-qn>*x2L`RcgW47l_^4WIQ-L1a;dRu^dR11%C;ujs^1xGzfrUd&Z$Ng}Gah z#Z_+J#3G*!6kYckeFb)%EG20Ek(U6C3PSIOh(G`Va8m4$upVJEoUeWsnd(7q=maDK z%_K2!2a3x^DnFo_A>D8gMx^qeKSwSIG50w(u6V5YCNh-l&AnFTcXK=!yF<4So_70Ss^eXK?m(oD*7>0~`(3>La4G=|g zob4tO^q3SM<>*bQ!^|Qg)Nncg zZAFgv8-D-(eXcP3z5@8Lwtl>s&V|HW3wkapd8z7x_t4_ygQ{;b3yZuoTF!s~A2<|d zpaInA;u3+}0bo}FJf4V|K;yJa{J8MH*O|0lr8j>r%; zX;aQ9?638&(GbUZFlW8FwbcU7j!LVxQ-EKMm+vW+|NE|{(<+FO0s;U@f^d{k>2QaG zUSO@h4ty%w9+|zF6JWZSg)BDK;3o=vU7n|KF81H;L+7B7g4{3*7*YY&7QQ2-0(A7W z){8^L=lEs-KgolT`Ur+a!4WdQG?)kZL|20Lzb}I7W_%3>7#P-pf5$&XdNBs-F960(QDKAhCi`8ax!{rc1B zr#+(XJ3UuyzT37c*albqvela?6Pa}S%F^=(Y>S9li9UDfL1^d+;qLcAI4-~Z=%2*$>=-q$-@#mgklUh^ximV2^$~SA-~@ z^eh=aL;u1vC_1*+@fLEg03blRJd8e|I)#u^Mn;CY9}m|0-&bp?umc;0{`K?A8_`H< zg;iDvC!)&w`=vWyP3v@4#DyNw9O_T|Fsp(`P@!*XJUv*w|Pe9qa?I;2J#s{>pVxtM$4%%;tOS zzSNn?3zqV$C&8hAe_eJICRf1VC;(rIfY=q+>Bc>v)}uYSv%1sVuadxqmBE+>K70Yd z9;8O($3}zMwSmVn7|V_Vsy&%qKYL~8g!e2MGqu_v8T`MDtn3BN8_~HDudUHAaS z6afOj1%hGtu|g}+7_qVB>0!VMT7$o+yRWZ(COou~^e+p|b>1SqCeMIUAICEWAw;NK z1D@Lb*P1aZokF+zm4MA*siRInV@dEuI|<;Lem4JLE_YhF$ay3vjD2U9XZUR3(I$Hw zop=ajAS4a+U|dAVJj+r2Cpf}r;r;e!`c@~kuChT^W+;MQ`&XtGx4l&N2IJ4d^NDEC#c;>dhd3XG6Wxk{; zPRAzZ-=DBV@sB7X)-45(x1qzh)UWGib9&i zZrCN~y4O0t-}!L9obSg+Ki>7e?{h!*bKlo>-Pa1O%%v$1mc4=L<0ElvL~>A`ax7Lu z){A1D+FMezLAU9J5}1T9_Q3ENk(k}AeK+OW@es4Fzn@q9aVN^A&sg%_*vA@4+;n(c zT->P@5eBejiUOuO50)(;P;NcFv6s^I>kMm#y|`BUHUk+u7rWHp&Tkj)xfZ=?efpH6 z%jV{3)Z575h9_cTVm2fFJ}UQ>V9>Obyumhk3~a zpM=J5@J`nHef#Fm^)Zfgw>R0_=qM`3;UWO~R+N0{JN+_2=fj>`ILHVdJ@{-6uZ1K6 z>;?oA6j58~8No2a3FqF8y*nfo4J1*`q;9koWHqIP7024*GIox%Xb%j3QZY5vyx~~n zaY5(D(}~gSo(LoeF~)(>hS}>Yx5}Y&QQtS0?ZnSx4LW%1ICAQt3B}aNF|_&Kke(8V z3G6*yJJ#;LStP?O{O7XOZf9)(1A=H^c}iDlSeQOd9lZVRJm(m7lUy}9Kn@@d36HU|wZ+k^Om7}ne^XeM zF?|DiSWr>q-Qf)-E65E!4SvO72rmPyFf9nxg*NFLM@Y#()?s1^S=otX^-Sn5`6_$j zRq`!o0@hcMq+P02o}MmCg)FLebDY(0dP-7W)W_z7QYx*iTxXQMhzKFrEcBruL30A$ zf@enPW?s)8$jBDCm5YGz<6wS*bOz|D<}F^_S+pZ)wgqIs_JZ%eGC4Tk?2fNL>}b}?_;fgrFA)qD#RNLK=Nm*Tp>l;f`J3U2Hbo$ z%sBcgjdaTYDvX7$^Vo5-5af|LAAr$>TY$856x}NrLKghdiA8np><7wQ_ zxF#`V@i^cFYfdc|!hDe_Sm3_*?~`$WqMuTfhr++DU@mZ#STOQ0P*&8VdIX#5{FX{x zpE^KEXbVeyTBI>@q=*0~mkXK+fD%(vxnp4b!}DKICN$wu9B?~`JUK;*JO$svSL}HU zrk_tK&+U#cEp@zAnYhAc|I*r4i~rowLG?|ALm4g$Xe<{+ASF?B;i9n7=`9X=-__M+ z4@eEEOG%$W1FEFxSwCv)<96ywL3Ow~3y|F2hy872P~=DOHc z2y24fG?^Hep+X5z0clckvJemZS8>UyGe*0q*J^^W;o}{{=V0)QNOZ=s=E$1k+PC92 zZCBCt_}ezhKxO z&GRX+W;j`>;Rg?HwTA*lnp{0o9=L|6{}>HA{I0@#cyf=q{`q9I@Kf)NO|n8*TbcUepvhX4_F%&=SufEyCmgT_580r zt~*?5bqG@o=z7ptPA|n^>s_@p>z91qIDVS#@oISW70K{+ZHgW{S5L=18?75+VoRpJ zBa(6>sSWySg%%-YBiEM`oaMlp_*}owIMI&h^KRfUll|uEsA-%k6HBh#mytG<3ztt;DRM>DjZn=z|*3xBUu0>3{yVE3MqO=9r5rd--bB@4Jh> z>IZZ(oc>%x*oTy?YymP$3k9*<5j$7owvJ`11NRg7PXHx4K`ZMQvQ-rF+YcB}Eq=m@UNs!}KX>ZT!g78-_-E-zQ=XUZ4xYA;vcfc3`a=T{zurez((F zPVL2w*83V4L_-4s&HN15G7!XMq}+1Bt(B#6TIS=MsYtu7Om|L^@vQrUf82&OvXfj*S9tzj zZPRe~X$hy>@EqCLW zw8}7Z%j(_|1M-fMNlpa3QGa^Jf8wwNDi}B_E-uD=juu~{ApXiPFl5hUFz3v*nZFm$ zh_VTPZ}-u^W(Vx7YWB#z=)NxOyi3`PV=-R-!>G+zCTOr+R3u$2w(N^{Ws30rYJgl>RL}?ny!ZQU6j7>Rrs$(gx-`! ztKje}%bZv7yK?}LpE?W{gkWe6RB5il47<3=(QTav<>kGuWTmqyUF*4%mzYu{L0ZXusnDCZ_J#Cxed? z!ptx*Gnyy{LZPwlf-D0zmNK!$#rV5iW43#v28n( z+CH7+9xR18NcOkIFBCs_Oj(E-1L`bS=14)J=eWl&@h8-`x18j)!-*8P#Amhb1-54SpUKb^CH5RISU{B`98^%;~B5Eg+*{3 zbd{ldQ%m0u1XnjIzju{Z@w%@&8}z)jp+=@Q9rWxehLa_V_HyrZzDNX`vkYH$j}ATv zhf<(|-&Ok5Zddo~^SR$YsU)r@TFEFbRO6=@EbMC6xi%}8e@k=`x%6k2-Kv`0)XcUD2oyUP#ahUDxWKJ9GzK{*vKQuncQbaawv!KHL9p`nMJ zQ!3k*SufSfIM-JVG#ElTWjVX^}3AGYH;2R?}t4~G-8?(SW?;iW!oK0xbZ zfvO3XtRiS&IKvt~s|3IGBh(A65|K`nK%3^tkVFk++i#%9FtYX%qkr~B(=wU-rT)zc zfI_0uGHDvELYaruvmlZ(HMiX!5E|*wDuY}xF0=+8JRtapV`s9mhyuUlUO5edDfCkc z%lLUL^E~(n=Zh{hbJ~Q*K#6UUNPQ^BuN5>d9py;MAsEao>_5&TnJbH@&>f%;Gt3#V z9Z$sPYbnPj%2JEOZ9f$gBT7UVT1XPL;Yn1f`oNQ@$FnhvFH-5AgccrtiG`{>9w|9N z&B;Ky>fb@U-$$@W3vo3m{?(X_&a1&5PvAs>tOu(Qx>_CoYQhYRAW2}Nsvf!d5?;I> zkuG5AfOnaL@4>8~5V3##$9YsP!Jqx~%7aFbmwjDov0q#8x55O=lH!)c(rIaFT|1kZ zq`X9*NX#I97ULu=%s!x)E9O(=u-lqc>{G-6sDx-CAg`bP$B7ObFJVRH`)|B5|FqQj)~A+Kt8BvD)=W?X>-F!dF=2}ZwH)$$o#FN^N#gcOe0SHu~EadLmqD`aIIobQTm#$O~{^#MX2XiV< zpIH6w&sSa_yf?I4pI^$~^bTiV`2;Q=Nm!y$SS$uP-Sv!`jZzGz>BLpJdqX!{?LBr? zW@+-bdETmh@>x;QZS}m&lM>b2BcvD^j#tC?25h)??eCVRL#tC ziOn;ZY9LaMgt4J*^wTk274@-iBRVaD z+qx$aXT-8J@QilJ-<0{|dAO;|R-LG-=l2gU)|2O#1LLaDlJuWm-F z)YjR&4ze#3?1Diphi5`sm1l13;-qUdSuXxV_`h$ZD?7O}@YRiX+VQ5t@yYNhYvAW} zZgyM#9&x6g0Sb1B^x^@v=b}Y?ycdtxyWFGx;>JLx*6@x939Z^2=3wS`O)u0GeA4Vs z5p6Pgk}0hY=hqc=mq!isr|JowBF4rwY}JI}ius4V?YdJg)Ri4gx)Pl#$kaoHb8c=@ znBTVCsyy3KDl&fe6Z>=K`zEHUM)MDFj;`$$30iCz_v7sD*G-OtBOy<)WxYAf6B3tm#tUk8`5 z&K*jqON-5va;}re`7-e~=S1-U*Dveh*=_4GUQV}Z;By$gc&3opqk7fiC=q$M=e%0V?cb)c^nh diff --git a/_images/a14d32935b261690016cda1f27ca562e1f9f7c0666d018f3afdba61ab61253c3.png b/_images/a14d32935b261690016cda1f27ca562e1f9f7c0666d018f3afdba61ab61253c3.png new file mode 100644 index 0000000000000000000000000000000000000000..f252aca29e3bbeda3583052b847afe69490679cb GIT binary patch literal 159809 zcmeFZ_dA#EA3v_rAPu8Jg|aDIB`ew4qa@1SGb$=YCc|MB&h*NcJcy$Y_#~Y>g%% z*)q3l2fp&CBSaei5pj{d?4sph?sCJ($&5tB$i>mt!Nu0fn90q|$=S-mUXbSu58nwU zOBWYM=d--LcK_cu@HjYG@CxS_KEp2|b5ziECL!5pMEtwusbrQF$rch4MHwk=_oVS2 z*UQ@9JKxPrkx(6H;tJ~NF)lLnny`OyHz=s5t0&D5UrFu?xqT1+=eM=>bEC)Rw7?66 zJrtKK*F6|gyb?q#QpDf$y)vIF?}$~5WI49WkBRtaG=1io=)eE-V_N$rbB^=BuRoO~ zjsEW&{I2}JFJevpZ!gH0&W&^XN&9sI=H{3O*E|L{HWc#nEotc^3#~8CH#UaXnO2s1 z;feXuP^y#rO-r)=+VHNJ{GmAV&6!E@arW}W-g{eV$X`D=z$)KcL0f2Z-@jtx#l&-_ zUDb@|*%Tw^pNXO(!oRVUB=J5tIO96@#z87w|Iz$y0XhXLUGf8IUot~14{=O8i*oJq zo8C#aB?BKNt{6F;V5~NsDxH&(o*kGOK`Fa9#jLckme468wf}DAErohY(*75RitY5e z{S-+`j(9loP378!8=DAbnGn}X_U~GCqKu8F4a#`D*&Bvx-g+yIu*L;XMB~Z~pm zP4R9n3j*m!i5rO6#j#y#>6sb-=P3S(LE-=Z_r{hh#W|Gqrbm$)8v9-QnnTyYPW(*B ze?LR#I=QyF>Y8;&nQcIJ#+ZUZ;O-Oou;Xg>4RZLdO(WwmS$wQ#3Y!YsQdj=q;*@Hr zvcIz4L#nu|;dJy)!;N&RNoS;5(q!q*I5L$u4b>;@-HqEa`tP>X80dp^iY8?|JW^Bt z=si;QXHm55QcG1%kszC#ot`#q%T$q(lWWaVW6aTc@rbPaAa2|_fYX8aNcwLD`OlQC zXgua}E)D8SZxa%(D>szj&NKM^v)qepl1I0IW$t&g#pI6?G52W_8yg$9@h&MB7Z*11 zt+?{uhqS50N}cxIxXGoHr~JTwkH=ZNvjw{k)lyO4@w?lbbKsW0vcFGxX*|VY|7$T^ zwL?xH!x+^XVozFiJlBn!P>QT6wCU_Ba$v+=RkyZA`fcC65qzHwk5q5}zp@gRmzT!^ zD26eJlf2B&H~Nq!TT`q*JQ>MKbNZBAP>5_>ZFrec|7*9)x25VL$-2W?0!y5KYZjO) zmfo0p^lL%FXRY>Q$l;lVg$$d{JR$oZvMXMn^^hl-b^Qbe#HXgUfQB?vvs%s8Ifz zb8+;05%0GGvxfMc#HBx^v>{4``>41lje&uI86T%2m0pp3hVSME$<3Adz_sN$_A{S; z{76!Y<6-?i{3TVI|I{gSta19^tNQZt_pgw%~4QL?AoK^(LDJ`+)ML` z+#W3Z3n!I&>#sTaw%-J>BA;dkKGBJ}^L+|EN-ca6munO7Z!gsMl-&@y{)<%5qDedN zYBWn=xz{3Br$%+rtpXHYU=y$Q)BRIF%avy6KR-O3g*Bx(dN%s$Q;wL`SV0TbkD*5& z8veOC^XmgCDe2Q6{@A!v3eW!)$;{fa^Q9NpKIdF~_GQifM$-HH`59qQzWyV^=4d%G2U2PZhR#Eu1aFR!dJ6+FrmS!Ivie$(>1DJZm64GteZ%wEiU z>QwA8Y5$i#>no&NhOoZN)BVx~!mNu^y=o{AtM;c6_3Hrv0fsdJl(>x(b%hC|{Sy

NYK=MHa` zho^>6j#ht^uph5GIT@o_=$Cs6tNdomI(K_3dPs7HQrxeJiI9+xJ^1~sCr+G@?mk2+ zRr|jcqB(jrBsuvgs)a@EkyzklSWr;)*RL_23x8Nkr@lVZiC!~0ois&v_%JmMP4uvY zSzY8k6tnZjnnx&uc;fI})RQMqq)|`0l|JJ5_D?^5J_@8}pZ)Xo8ATbY$M5XF9>*xp z6Gz+z%1bHYxNM}D`9yai1-%eQ-6{>atY1xXdVFHy>}Xq-(4va8^qp_7EarwkA3kN* z9X&j!rB&|fdg=M)Dr^=J&v}kJJNFIO1X8DEVro@J|JzPa6e4SiuMfO@{W{(DTY(}2 z^}&Pw_wUO`vbqmCdE`{FoI}GBxiP6PT8My`8@p++SB$&LPJA2 zXvqEd9<6W9P+DGDu<s>zk{BhzUIS+j8{dy zukF6acI4^_8rSTKQKHPyNf0o*Tv{y?@OD=@|1A6Gv(u_%_fgVPl%D?+z@VCM z{2@}DO-xMeTiURs_0P8@SH?Ihb+C)aCnoX>3)ii@ZZwz*BnnyiJ$b^sZ3o4>Z{HG9 zrSCf}{Q0V^+le{9$@8zX>xrU^P4!lOBKoz74hrC@#uI_@ZZfN-w}f;^s%KS0yQ~@4Mt(3bFs9vbbjLdAqxwO zoJ+ZQz*_NQ9s(~6DmO;GfsCe(y}3s0+d;JTzZ2heD{hut_`WCfsAw$qLnOCOo@tnf z*WVLPB}sUE&whlV8U7j?l6`TlTw6l^Kub#taUWamZ9Nu|`2-9G_477d`mt}Kk{7MKQJs2UvWe8DduaDhLb^sC_8N}X5cD(E*+ znagpMdn`^KeQ@w( zbyd}tlP6EcH0hQ&nFS^E%t&~z$ozck(bmq0FJsSUwnwzLx0_b^Z5Q*L55NdBcVD&2 z$jFerzxU|nGPjetdPU~_)%SwYB;>;w*8k*@VXjgWkf1UIg(7IzEp#bQKM))5!f!F} zm1qD5V^h=g)|s4O_l>963JI4u^x2~Lty)>CtE(^LDl+w%#p`2FHejkG@SE&7ZU5t4 zcXy(=*WZA|SU)Bf#eXG#(9h40*w77eygDV%_uYz$in>78M@dOJGCG>^%;Dsf*L~yP zUX7mBxp-&Cp5q1;Hyh*m2a32xO)M>IF~_gFxqZa)L@>(>c>NuBnQ-RWRo$ypxXgln zuS`QpSydastc&d?;xwqfj1rsF$kP{@Us%u*|BFK5IwZ8Ifm-spK=L(1>5$W4ZPiH2 z6ZD$=daVsffXDaM)mwM(-u<)Ew;4laX=Q;M!#WFaVU&LP07__P^{pP(sWY5=P=BGK zzQ6On$D!HK+G2$QvpTu#BN-!?at>c~*15QYiJzap>)SVeyYAOQFC6sId!Jp()g0}@ zQfr{1gd}6#<>cf@ckD2>wN08lrEO$y9~u!s`R2`=GiT1Edua;`e&~E1928{STj6cn zQyP;fY}5Kohd0L03$s%q%{H8A7oA*Q_^b70w>RRw{s!rc^a6WmS~uBWS=I|hC^-eu z9e7_FDV$4QRNd4Rijk+Ddj6i!)v@{*?zbLu{Y~`WY&F#1U-hHJSvTK!I~x5aXQ%cjEW@`FXZDqq6^bKg!l_sx6ynvJ?8)FEYA+@#`gQz(D1-*q8qS$w?>=h{*9dhl}=Lo z+u3w#>3m(qbR@4`9CZ(L=rt)XrB zu{92Uei(q(_siUx0!Q3Z8{Ldc=UeY1>kGE3X4k=gz>{wzjqe?9b27uPn9kV=~=Ow2#NJUKNY(j4RhfLXs~zDK=#+#w}6J zur8PkIjKGpQ^Xi*a|r>m)5_M&a9No0!UGw`%~}^lFneBA}$FPdsLq5u?mz@-dihX=$ksV?k*poYGW)4hZT)U0oph zTi@Vd&2<0!lIsH>9WJ(C-B0@Uzt32@yUG+dXkD0ktgX+v<~L1PU|?W>ccIPY%a@-bH!8vTQkyk|3zhd;dK$GBRsKD-7R3 z%ulJ45!WNEi&E7&rf2_F_w*d~_4OT`t=aM?Q{|y{p2)H|{tWJv?Z!ADY}*z7Oy^>Q zd9yNxZRUj-F6E>%{B^&_)ShHzeY&+}o1>dsrtya$-rp@FA+Aej{ zzuVus2>XF@8a zsCrM*XDy!VV$Rc^Pwtq2GP1JA6kBMHe-BS|A-ijnSr$LW9=n1zIdq(~CEb$ANQ zKPTpG#PVEC)Om4Dqts>8B{?O+x-%~XeNWn-q6!0T+qOFfJsA{H>}m{bDv2`s`bW?& z(NB&=pVW)pvTes2W!X-$>P@PAtx%?2*2}biBQEXK%Mfiie2!c7L7*J z{ok6IdsW3gOtH`87Lk|ElxqGZ-cp{`@Zb=y<4S^rfwRK;b@f{GW$u>Ktc$H^i{FQw^*9 z>XR>FJ!=vKE!^jZ_jr1G3R$(@1ue=tYj*U&fe(PrmtR{(oZZK(IPfvV1i%&Zobu42 zPn|CeqA1S!>hGghlb2_&BN572c$~9q-@Z>6OPJ!CfSs<4!wzbx>W=-@+tEkP0}toF zeqGbvF7$bVbj5#ezFz*?kNIP#&h{UA^5fo~r|sz^A3i%hi5dERQ)K^L$$tt^?f&~> zd->OgU1GvI!>t}4YkOCcASkSC!&2JY))uv~zN+=wQUe|Fsa_F}Ktk~Jv?F+h--8Fc zAxzMKxy7E;)67&(kdf*Fd2yc|B*UZCS)ExQ0gth?wr<6ca7ku7a6tClxpQg%?qSD{ z9f~_1OXlqi2@EtsKX;k>nGCd-waUL?B_=NZ4aiVRN@{-mThv+CKk4-GpFY%>rY8S!;7* z4rH0D#t-o;&F+WZfvf%4m>~GA>;^AD)?+}=`9EK|rKab>i<%yZ6D9Yhr6m>UI{x89 z0yv>v@d*kxgxekRrD0%b!p{nt%?olyvQRQGJR0P%)EtvyRs1#l`C;@4-ALR8JNdbR z&N~|+$C;V2Irg1)_?fPnd=@uDEnZ&J)`5x&&2_J}Xx^{A!V>N6rF*(4=N#FqA9Oz* zq?V%oyM@BJK~~CqPM^sY2vk{YaBEi}Ux7A9eiR|It6@aHO5ZubRMM zT7Eyk5-x`_uSFif>*HWP|HBz9XV{@g06ja;{E|H{Eq&eD*#tsRd_scRg}@ZF>g$8{96n_zS{>{5q}QRYy;NZji@VA&%^; zU~!z^^zVPNEuHz|WDfyM$PaM6#QbGbO^P4Sk7O~jvI>lfqQ-9}n>;LNPV`+>*ZYS{ z^qatl&Umi~v0jMo>-F8d_=s7NidjBX+uZ%r$B$0HJWVN*YU=9yGcz+^TefT!6ny1! zsKIArO$4LiBiP{8-x-eo^hiG z5QzG%hqKe~OWt-#EQ%D25^F_|{%-sPN<8B}%>+>OIh;y#lvR<+$jAs=o%8EX;Zvtn z1xQrJJikmowtS;n8Zn$bNxI$=u90``8vUZ`vM|rCP3{_15umLAqHxU2?txOkDe8ZJ zKg(0~L(l z1@Nhb%Wp~&k;cF1L?f?wmZTMEpSW}#D!bV=XeYh-GA_ujpG z-QF9z5cV3-o`S9ahvb&bNzvMmK8*2b^WGT^FyEkz>#`heWcn>R<=v!O&C zrTX*i}jdhzZ3kY zPd7(fb%6l!yZ+HOHZ~>{06hK7^Y_T-r+OKsrQg#ufBo|1U1KAK;46m(fjfSF#g6@3 zp^Gp<#l%+bo0v%M_inQFm>o0%(juBDC{=pt&jp9H>?nTS-=!;+_D6G=*6az1&+iIQ zVBQINYI^z$Z*0G{>a)qQMWsG_retVn=s(ZN#}^LX&0cy{Pw(MmPgxs;svkdo#0%RT z#9l%DsaM?ei0Q`m5d}$1#qNNj*OsLw;xferV`kT-+h=mHAZDx=8Biz4OKB2SSL!-*N241&iD4}$zGPCE81W0Kj)F*JU{xQL~voO zb2HcX6Ffa)t8lHz=V+GLnUio12^9OWN8r1bXW!b+z_B zBYNh{7Yq`i14nc?X!MI6Z==Of$?UzL(gUbgy??*$ z>eZ|Cr|p%a*i^oBcB;*p)Z4;Sarh|~bck0KW{!{RjaHdRmPeAlO%Ryf@pI59we$27 zfUH>_%KEHVdowWZQk*)#sm;S~H<7a+;t5o~VxRT1vJVbsIP_L1vN@1d_o@=IO?m@n z!x^u?&jpx8(N-}Y3Q)L0h0e2siq-Gmk9Oo9CfT`~$W=@Y*M z!mSkEwiMSkE=SeHPHgUeSP8vj;(O5?=+2ebmQoK-+4)$Nt4S>-{P(0N7{uc7shm-k zfH?Qgr}m}zZfKN*OchxN@7rKetp51XAEraP7t7Qtg@Y^DRsM~sYk3Bhst_7RF^~$p zyV2B_=YD4aZ*di_|DDhyFc>;gT_o#n)Ws)gO3cj6g{!%FV1^LhxuLWAJ~Uhe#>7?# z1YrTx=FmtZ9UdOW{aqX4-TS*K*`)cAIH8F^?|!1Lpx?Dd5$0u}J$_H-;L(%a-4~Bt z7~mE(Z#2ZrfL6?3rGa|I;$O!D2@Vb(Y0C-|uu|E-af#@U$3Ev>E%Prc6Yc2esQ)e( z#_$6dnyA1!#LzfIzjXF5(h|E%8$enSe0Vamw!b6DEEqkupS|7 zb7^CJu~%kHY}?kY@N3jdHij25rohH`9OBVuVqv)p8MY05oe(Pezq920!Jm`Fy<#CE zu$8EJn$ImPeE9I;9{48J;loO3saCD&WFV<3&c4u6UTsT_6wi%6jYW z`1j~+SIuhl`=YDYS?_;SAS ziSlmfd&M`V7-C~%txs!}U*ls_rZE>`A*vE$E=1&@iB&$!1#Q?j$93T%I+v?~l|#WB342J5K%(sqk69Kwy}bwC&gko1Dz|c?~KE#rgT={NvJD19$G+DRG;i@65Z( zeEhiI5fP^^#n(;#v}Z>hs~W?H;_4-m&$^~T;NePPSER~saWXzW@TD>B_M1ls6B9Qj z(@M-g(_e_=2`MS@@SB6Y@Ch`NR@_qvb)q^$57GFDn0q*WlNPRWyH8XRiN}VN-jQWF0Z>j_M{1Rcy>G_aCSjxP1y*kIx!albSarEo+UP ztMFV1!X@=X`vJ6_02)Bnw$-i~$5mR}!UHgs4oOuupXQZLFMkEWW&>!Yr{RE63e_$#N zNX*({M`1a`AJ7!J{Q2qKr1@QY_hy=W3MEJ`zP}Y=0OdWluy6D7@&F?Jq4Y-qASa%7 zP=x^|D8>P6OFK4@3)?8?6Jf!x{04%yL63h^Y??dS1v+a5* zWVfDhX>xKBEksM#cR`+AHK}iYw5>5k(qO1FSD)uM_7+i3_)i=5(PnnfgS(O`gs-Nq zh)L+?=5|I@l)ZSp>dsCg1c4bD(;WyCc7CMg`PH&Z83W=V)Gv*;p}(mtTvm*vg}TqX zo1=fz=K9Z4*9UN+L85{oNukp;&D#*$4O#-R-Jl>{%+XFof2Vt+b3;aklvys=5Nelp zwkB(pH?+|omA)zW5A8GDKfm?P33BoSoN_buu6#M&lr92p>C;}Rsi^>Z`>3g@F~(c9 zcM6vuv<$_)^S8kz2|V!q`(Xh5#8Y+`)>jtbRVm&m!`%fR zJ{^i}4UeG_7+`6-De6M0#Ou1D5Uarkhn@98=ORhS3QX_ic&GZa#z!~B?_5ejtz2JQ zx=!pCTgth{{f7@fC@d5vT7;X>8Ek!MQQ?s1{3+-nhkMHu1}QgK{*9Q6(C@mwe`inl zAnr1v9+Oojeg1sBfZ2t_f~x-SBUo~2JVEIo#!P@Jc{Q~#+(Bmcdhk4^G5`^=v8jGA z96sCts#M}Wa~w;Sg*1m`;jpQrBVQcP)nCwaYierLVdsEMXV2Q7k7Pm5796q{0?2;? z|1+5JRQUPMkJa)z;Z}YuYNfZARvRZ$t1hbxa?H-m5W$4@XF6fy8fZTRau~Mjcz30zki>|o#1bzpw5j#zw&4ECG#u&H$-yKBNS64ys2`N2_%-K znrw_=!c{0pc-L+d7a*Ir{9ZT5y_0`}IL z3Ur)ER+_2}p{>6YxsN4E^TrvWl&HK4ZW{8A7Y1P%^?(2Vl`M~L4FlF7vNIV^2dSl;HkE^uoe$9DQ)NPIRwiNmy z4-d}~NuMM8_U-%i>lfkw3R|}m>MUj%JHr-j4nwWoG(Q(xm`45jIIYX58dtJLqklK2 zymFs0UYQ@gbMKyP_lpEFfK0kmwzP)ftAsfs`K#Ps&(z~#yP%VyAKgEfA&@bi#QX`%cro!CpkP_lrmR&E8 z;frL{(m(b6CXTlG&e&%1{h_nWd~}Zb=+V!=K0F9~@W7<{E?K=sd+!JIDMCes!>KvC zgcWmInl>74P6^A;zwSTZ4{MZA0-&X6KD%@hwoz<9YZU1*)`S#tb_56;fc-%ZS?<(@ zF-k@P0mO9A%*-4^L}o(yH^^fIQbMqv&J|jJrTTG*ifZ<|X*F^N4+(;PMBUob@(Uys zs2?8z#4f)w-*fx+ZS<=URI5eT$~lP7FasL_m|^|0L4P2y3g9CfJzWUnXi!klFAO(m zZE-JO@_~cOAh?meWGh|}-JzVx)_6#)>3l-;gHQv=+#uqDNK(L=h_0|PE5L?#0yvG? zWFv+r>YfFJD? zru+Z7tGttlQ^A1wgul|@PaF3~J4olGm6NhW*vT;&tRpGRqFYcWYVEpBWu%`BqI2J#SJ3p+qZA2#yclQMih`KX^okVq630ez|(Hkzr)9gW@rNT0QH?8 zYU7326A6RY`}_OhKqtexqoShnLrfurUN{Yn&}y%o)}Rm7-+9f-qZ77#%O-vgSrm;o zH`WPS0+UMprJ>Zqi@B&HXBZgM-UE4(0c4w(p3PQvwt(_O&Do1UfkK-??^GHZ2EsGOMn(~t<8!Dvjnwno;WfU0 zEOqB8_>KQ!E*fiNqVNOs5`w^i!y+_ziBtOOe(hubs&5c{W@%-m6%dAHs<+gY8?Zvf zb)pmdRRoG57;@7z(vV9LxV~5LfBO~{(H*Ua?zD1YZ~{7B$I}B|MlO%>sdhFMS~Si)Se>bD8C0F4hRt&qjBx;IG>8`h zb~YbV`ms+4$Cu!z%leRQk)`72zo4!)j7J# zy-pJo{ck)jiuJIqj{}G~mt8_U12_e{@5UOz`2Z-_V{OJM_UwTGrn+dE3LMw+M4l*( z8&f}#xWd+Z0{vYG8L+-S!yi38bi&p&P%)#qE|Nq4G26f7eU5f>v%9;SmX3~)_)vJr zJiwCFN>`v9YKD1PKdOH3d=&zTQ1#y$>K8}}A7h$t`BsP6T=mi2Xah<@Eg18&y+*ixq z$D0v>A<~|aEG>mLI$$AlpF;NUu8buDw#ROx1wCEFIJ;$Co~xxYkizZ0zquH?!Fu{QEuJJ;-j*#} z2yGry5e6t9KYuEaJ=P%tA7b`p(fgbw79=+IAc5U*;{-HEAV-M(C+YU>GlO;1;Gpj7 zE5bNA5LHLCmKd&!Y48SQfXGMQ`FQ#!+>bD48QmkoB2;|*;_uiz5nPh$%cG|FFi{WDD>0Y4!5skX|R&T0)5I{R^vLF95k401$e|RVN1&^D*_&~rq7>0hdXA! zW0B7T{bIbgG6jFqK+G4!>Y-`OPN^kCBJNdQX>ZUWo%k*vT_ze7zF(-ooK-2+&vdFQ z;(4JBbHgBKhNKEMyTF~ZB`tyIhk%~JU~fTodmyu5Us!m4euq8;=z9=EBK?P?D58Nd z-DPsLY5=x5XaXO2H4HhS1BYVrM@l`ueR~TA6e3K!czJmd49r$f-3l)?RVI*Xl>S&G zOCSpQl|!#Ya7akh^L08nj`#w~X#i>w_7#btsi_QNsKkEz@ZgY6=n8C#1YFoG7I}8~ zvl4nG=jH-MYlcW|x(ki)P8up9$>gvtZdxPXUS-uYH7c-dEU4N#EAI8=P<=qvLr)6`Up7!*0|NzoC8SHo>x**wk20Y z!fINFyv%9)X5m=C&87W9!crSobKh?IG-GKcQy4VL^@B1#MJ7#mY%H=}QbiL5I6ps$CKn2i zv9Eh(EeN(t1yt)Y^5wS16S-{hZd!N;*z++}nPFjJ0$rW0t!dzE^@d1dq>;(V33f-a zDgjTWcDu5H{Wc;pOeh6JD*y4%Y{1D-;A_W~c`L-Xq=3a`j)#Q@5TzM}h}rYrTfGHl zk5gytyov{F;jq%awp6Ww42`EL}MW~#JgKt6!XUB z=jH~`?TBX!l-*Y1Y{7Nud3@h8*}i=`u|;$(EWC;GZLzw%bwUwlf?FPP8&2o4r2(vi zQ1*e#zz*ey#(~zD`SDf6>#nZLFe6`3oC0wMjJxzR1&R&nlZSs|rvXFX*VmIQ*;d%C`3WOFCQuAw7G3jsN&BT$PFMEim{#vIlWGm5{!!7!)I+*YF?gwq*Py6 z+XrkD*aslaMCCyN%m5gno4uJHmy(j=bUG2s=Hlv#UuX_Bi!SmqvQcndF0s|2qi#u1 z_DA1D_#_oEe8{B|-%6w4J{W;Mqmux<)Wz{KV#0p>`t<-FF*cA4CRG$g0q@n)8lskP zahsjhZ;Q5!4$`s&YVS@~5>PqMDo%0#s=t1qjn$6r+w(EJdGw3XvA5Go+&lv-Z;i7K zy{7;7?>Iv)aXvovL8pe!j7Df;G!WnyLbl;U?Vbn z%{`LkI%Jf;Q@#7nK?}>iTJ}a^aG4Q`PX7za<#D=eS4(}K*~IPj$W&pKe?h^~v9^`xCe)Ch}aO(Hi6LUN89IP_Yp`Q4Y9bSgg7>kmX=1s2d^Q| z^@RH4bBQSpczOkh4udpHW6yvET3`Uyg{E!azMbFeuPy5PUSXlD-?@*UKHc|r&K)%! zk&~J*{PJb1Y|^Zc;#MJ{iiLcAdAA+W^3CbHAo5*!;|te?@Nj{Ckcg58P8|iD$W&F! zLKOLknwpx~%Te&twaN@37!@=pE~|@_>O$E@Y$!+U2B;t|;11@7xq?C7weot12LHMO zU|smBuapN5enh6R*mdk6ntd8}+wq9szTrgme$1+iB9rhu(eJ5vvCh<#^YX1<7R?*i zdtb6D61lGru6|H1U_Wxca`QdG>Wt-TY;5E}(5Zmg5Bi@8KABTB5HerV$cQCUOS7*S zB#`xkc}94cfVdxk%IG9+x@TVHJ#j+0!BNHE0RM@g96$Tlv-FH^0+QL$(D9JA}XwvV#E$33MnTz{kCe63Q4x zFjiSWPwVFpn5l;6iaEixot#GDOD19qa4ZOYzg+J$7p?sJo&}l8(z{~6xGhbkT2D(= z{v~GyOBQw6Lz=E+0Cvu52n zeNtlt7@k1?Xwk4N)Bdgor=&1~>!iUi60&Yr=(!(mgqBx_ST!`m$F5@?;02m2vuj~E zZ8WVDzH@tj%j09Mz8SKu&%O++jAVs}N4DToHIGmRZ*ER?dU*40NGpPjedRRv_FiYn zszoCUd-X~XGKymU3qo8)G0tBwr_o7Ohru3W88*>)3a6vsO&AO@e85&A+*!muPfK^> zsKhVSiGIb+1RzT&MSJLl)J1L++Z2-cOta+XexzZ*za0TTdwQhx^4ICKP?K*cI7#*=avnNkc z(bHp$DjrPSQHw_$6v#ZYnUbL84SlT|*@~}Q>j_?q#7^A~5+ZN$?%gdcu!Y>|sD**O zBCtxZwCp`)!!?MBEKXj9a=f&*EQmqbo~?Bs8eK+q?Q0fAcMp&L;bDL9T}WZ+u+6|$ z2|5O;Kn5NEt7^xRhJwN_9Gn^e$_8p~sqpr)?s%T<6wa$i1sT*B-WblKXjb}o6IoJA zmj&#B@t!h5lz?(cs24=Ags4k^_;*Fwv&6X}a0r>snZJLb;fb6P5y=?cT?+x=8&2#P zRQj+Iaq>Uyfk;HIwJzMvp+_DDJnAvx3-#a89;w=Y+=PYim-rBDL@AuZ6hQE45A>*) zh!Q}%+0;`N2G>ZyMQm3d|xEH!Wk18n8LP^EVsu8DJwx7My$dS08KGfsQi1621P|_MJ^%-%8z2B8PhS3 z#jz9pBKxD5f*Mv_>O66CIK~7ba<{1HG-hi%j*Y;5;+7ZJq6XFiOC$g>%Cmla?zn6a z$8Nvoc>X*1vqk+J;sEu?ca*^Pgf&Hz~+!NW}Hb1TsgC3NqO zTqPmzr|KNU=EdZF>$6U;qN0N1B^OX!RKZ7BWwH3Md>JHtf&ugJP~Q~^I}wB&a5b7k z<9JLhm=9>ivQ^z zs85^`AX4jKh;m2(;9!MZ!2+cgIY6q?SNHUdj@Cibo1UAK*3ybX|1z|* zQ^7&5*00yhMV$tB!7HodIjZ=eudh!=_%xyeu=pTsJtR8Gwk8zCT5EbHBQ7r=p0Isy zg$k5x$Wspfxgi&2DcdDH&qz`ybrdwq@+} z)1&H|6-QF3*;qINj&5!u-(BO~>7z;4gku9_nJ+8%$qo31^4^$x)>C}_4w09CeYGFA zO)F%n9@%DvdO`^62u|+|*#T>SVfvrgh1}Hoa=<K#-qU65TH}&G`Z#AO5gch_YQU^g0ncH zi^F@e*bTmAlzh#4)>`P zRr1_MhWN>wH@HY)E>;pqXl$ZAg!qVY7+rQd$=%D(HLSD$z^{9m%G4$Eo4SkimXFU# zxh0R!bG7Y$7Ievadn|U*6Lk5&f_va2kVA>I5~w7dpr9b}Z1mpPru7{M2mxp2EIJna zB7%rennfz(pj!L2Cvb*=8P%MZA0zHT3^qI|)JiHmTH-L~LmA@LHq^SV04i9%N_Ie|_g^%z=P z*MkIE{V3+g@Ay2ukTW_oHr9X#0$OaAd368+1G4=QXl*U9twWc+`gT& z*B2)YVs4w`+Bwu8zf;qFLJwC9nhr&N@K6r5_ zPTP^ZcWYa^oD$AZ6Bz^?wo(@6^M-PS;b{WI960#^Mk?~j*k?NwBQH;uCVg%`#VqYF zQ}1w6z_gt&x9Y-N%!q}e!G3<6ygYdFN)7HE&xpuw0!RcMJQ-9{A_8owo_F=G1DWW| zlTd`Sz>;6Teoe49LYRW-kg!t5DC%|sn?hCC{XuXrfw3SkklESUAu^!?{2*X!`W?R$ zY>yw(Z=?1aeDsB!S*2QtF@$3TpLR<{NYZ3?;R7HG9Fh{p`SLspCSv12LCVov@bL6R zqCJvA&w?I_b0{G|UwZ-fs}b?WnKKhJvjwF$ylXAM4A3N07PTw6AZLU8K?mXkqKm1# zd-wi*?yT0{w;u1Ie8ha$0i9>dDao#ni+DY|uwaHogW0BDWRHy7XykZY$h-2@>12tk z3m=7r&Pm^?);kqd=(#}gC!dMnZZl@f+~TSFF=b_CLI6WY%S1zz^yZq!QQeV0e~=-alUbCNmA#G_3(vK; z0btgUs?rpr*yu{djw79gE*b^Nl7MclBQDT6i6cIpopB)2T39By;k5vtR7VdRv>^ds zjypf9q@)Bfcni)tndNkzg?IubiHO`-`PkNB>KwrhV$7-|8iO>-UBq#4oQUA@@AINA zA(L!ohMX+7!20fSzzyP{BH{Y0n+Ors8`akzI1{H?VL+5um9{5B{Ov2Es}d3NIFpS1 zsDWdZW)CSBCui~uHec&3EjgqYbOjEWYVa?sDkKn4Oz!y$UWY4%azUZ0I_kQP<$~Wf zzB4ZZ01-PHr@-4vU2V)8<7YafOS+)&qwe8Vp3fM#PeE6WSxFTVy0WzN((e1Ijpg5r zVo$`c*NsKyZPbRh2>Pn6L{C1^H(42&zk+qr$=)dyfu`FCAnh4ZQEr2M37irU zInd9DxucZ_3jlLSg)e4uY6?=5tE($D3&cTf4i$rVoCu9x5JO5-1+6$BQ7mElVNt7i zcz9cP;*TeCnd|z;D2W~yGyT2D!@+7{;=48dPeZ4$qtdF}&t!@|)zrMiNBo`aQNo=P z8Pq)+yU%XQXlQ5vAtV75J#$$De&{N`&Wwzbic2pHI1uKY7`KLNF*8YCH+ZT%>t26} zn;)Gm+--Es2)&UCHY_&%^3u!`CrMiznMSlXWBJ6lUkXM>g~;t7 zAsa1K4WLM4+z&imn@YWe3OfbwF3Se|-RNisEXy}yOS-JR;>xPTPPTQlLO&X0pA>Wag(Ub7%sbKSCBU70= z8=aOVm5$DhI;0)eT&o>=KiYgTH09^7)pYl0*rJjUEEdHU@x-84`+GSOa`=pXtPP>; z!YyPe`}%Xr8k-kWIULqPw#yn2=~J9r2OL&*ECZy4Uv2?{M=G95m?GOo~+Cj6~KG1qDHB%iberZovs4;FMFY)lH4%rO{Q4VH{Ir zMcOf%?mM_kHk%}C(R=kPNQpQ?DIq*OLYct}T|j~B=2;@Z!66w_A`t=a$T8;=e1@c? zB=^k?aoor;pg_XbCZ4Lfxj(Q!Xou?D!SI=kJC7v13B3u|hG4ejw`6;qLm|=#cr>4* z7d&PVmbwjz0@pw!Oi+E5*hA;!_g#T3;O_@-^`B2JlM2VLMRrNgQJBRxU_0tBP2 zztz^>PE%3sdv7Z%ZJ|{Z<-P&mM550T{xx-OZi4Zp3Vbw*VMDeh?3)sF_o=!Jp9Q_KFHBAohjRK zhz0*QbZrp%RHU7>qf&_8Kt?vx{C@G?k6;1ty{MI5q_Q_+vK}5+$%Wo;(1b{`=uZt-cokMfk-$WXY+r#`%nPrrH29s zz3wZgr4`}lr|iy~TL$1|IVg3t8)UIi8z3WUV>Lz)IY(Z-ww>~TE8$s#MP}=d@gl@e zG=5|$NQ->&9vpxz&If_KH?B6lvG^Vk)&6YD6$uNEziY4LhX$g$kFg7jx{Wj8pblNB zIC8P<7(L#W``??R5p)(KxpV*C@vbIk@x)ljUj=7!G<>s5pioAW6k6)R>~_bVNuk7 z>mGq8U}9|@l#yZPmmY!nGBeu7j`zAG4clbOqm@Bv@5e$S+H)Uzkt3vZBIgF#+w^A?q3luxmhZ!LbPAEBO9Z%=>6B+oSfkMO%q6^CsWK-3r-)LDFZz`=^ zIDPVD!HrSnpDb^79%voz)X_P3mtwxJY8xRqpU_B4%?;__SM`4G#x={0BL8PN^*Ih` zTH&pgGOKz4(6!iQlsFkgyxRs*UZP1su$NxweR|~Hix<538!N6O-r)K}f4zF09UT?a z&vVEzY!gtoxJAWug(3IaHm;GLveTC?UBVf?ERXI}B52)sGX>5upmk&bf#Ku0Kkyy| zbT$SwB$FEg0K%wJ61wtdbTpyw_f*l(RSBj&d-e<=69FqC7(F*1&{?K!v3F+{C^vDG z01Sp7@5{k!86G|kLvE4q(Q%*=)-M+k;hT&&4}}@&eCh+uv2~_|myevzERv1rcf{I* zr4rQbwM}Ozb_QW40CC3U*<{J0Lm|w;4zC>k$TU0zB7ln&D}pYy4fQ2vF5I6d&Pq7d z$TZ(=$~epJ)rj30BemMxop+Hf%E-p10l1&wm9QAHRTnI1?wywcA_hdR+t`h?DUKbX zju88b*$fE{h1$+9eAd6ctwA#@b=7O{)-@|)LJ4C@2vX*ER4+0TsYD6i4J6k+EIXdl zA+1cLFmo4_2oWC(ctXE892q+Spduo-j080TNG|@{c}EMuc3H+0G6w-_VXcT(*+K4x zB*{vqx#`DYW_E*SEd*pg|UM-ZgiJ zW4S?ZF1V>=IebGyLRin9r3d*#G%k7*2QQSY6oVu%DMmW=ghMAr3ey69AzgP00u|72>%dDe#QDHCFNx5x zF_-(SCxR{ri0`@Qi>x`3^B_)`IIiLZ68><-?_FQ(s#36{##BjLv{h@Ft;5H!v{|h) z;JWN*&tA#cSCNkJ>fBW2rY54~G0os9L}ChW2HTHAzX)+#VI!2*E5iQD$NZIPAZx9M z_m8V+Lj#YgKL-r}mIv|P8l-v%_o0RV=g*%fF25w+SjDm17%iDjT)dp6Gx6ipiRd3q zYLIE6?137>={720&Q#o?2P1Ar!p}K}D#d+)|p2VU>sBlp=D2qWgsNY$tRJaD)&q zM$q7y*+ovSX}`F%-ny5XI!Z>$7$94-@oX4QXCY%xG-M(bj`JRgzw4wWEWUDGVo{R5 zgIDF%MoO&)Z1N&U1j!Hgh`0P?&?{F%hihtTs=w9R*cgnjLUKmN%*cO%6OanJ%n^_i zyq5!qnpki~1d|GW$YPt^$)iV(#3QPh*aT(7HtmWl@3pr~SSB(*Ma9SfAIgvu=l#>! zGgjYU;;9?GbY;Ob4DSM9E%7bNA>P^n{))4Qc0o^UaG()$(Gi(t*qnqJ1G!r*KPix_ zz@j-+hvUTA0aZg83i9o=W}naZ{1UOc+)BD9Bs!%Q;s)M6w~K9`dfS(2E_X{5SJtl8{j~k^21Ymprj#0K)tq`ocugn z6z7X=z1P|#cLd@rpyJ{x&a;a7ZX}`I{p#<(jm|@4ZtLqW=x!4}E|!!fdLxyQLACS` zpQW|&m*?5L*aV6EgybU@MFd-T>tr_->ykxJ!_6VHf1oz4kn=OG6t77jgaH5wyy8L7 zd&LEBI#h-HoB(nLBGWW&^U-U%ZwujH)haBEnv&r41;nc!`cB~xf!T4w+XCtuhIIf2 z8uiA_PK45N>vk(%p69oB_*eNK`F8Uz#!UA7mcfY$6$lz_H*?*Ar!gCy$GiBuiyTt= zBw%zwM?V9Ehkz1+v@t8qYwg+cowna+^f7JN!~4i0w_$?Yfr@lblTL4>WEsQy*uhMT z&*y1J*i<6}nm;lKm>&* zkIkGN5%!7j8Ei@v{cuYihHKdS#snk58`9LT@+w6haV z1lbI{0-c}~*iURc{JXk1^XARgxYd;0bt|JPPm7+mdU8y4@;=_5cgw=$x>TbBcUo_@~KFXPo39NzEm&;%(P zh1BbJ?{<0l^jMNPcI3qs-*v&cQ9`sv_xhg-&(o#$iz8j<$gyL06DV9yuU>KG^QUHu zQun`m>F3v?i^0#zyCXbXBz&{}1MMo5x$E4K)nnpt)Z7ITtv{a;Ja6hDnN~VZY?bsWU3{vwH&G@Zizc59w2%H;`hYz zg@0|rv_*nVIhhPJ$y}1ChkUx;aUbb+Z2y;!^D0WFBQTHd=-5Ji(2sM2hFuwUGWuf5 zv>Q#pw2tQ275tB1-#;j=ad~p&hM;ZRyigH?;diC%;A}z)Ov4~S{k+aJzXT+>|2OO> z|#iy}4kccsCF%9omYgY`^RuKRPf3ZR_Sn{Kc-JV0 zTl9fXk#{pA54t<4X5g2iw0oT2eD@ESTFZYhu7f-{k$ZJzc|`yarwdTF$%Vs5Dw=j( zbp7GP(y7J=6E`)t7^&B&a_tO6eFlGfIl*pY{emtqEZ5eWelm_ppWLC>x^(H1j6P}8 zyr$gzSz@TEp|cPHrTXx-L!`jy-I0mHEro;SZ%xDs*V5NPqV``=60F0 zvbBZd4NJ4Q=;$c{`ZKF{InVUr-V4W2eCFy2k)(~Z(2aH^8Vpb@s0ANmcoZ% zUD|W~ygj{wdnz?gQNK^A%W(_qo;N62e8mMw$0!VCutR`ZTdv_N<8^R%7Z+@n`6T-M&Ly0lcu>`$w2KQfg~JmVhRJJ9q% zenOuw4;o!HaKD-4rTgC{Rcg_~yD({V@(lAt?bHKfs3ZmGgo637)O9YQhfzpXvJbWb zxFd*%isQmUW2OLju4jm0kTii#vKwNl1MmRjL-@Xkmp7okrHtw9S8VTL* z+xl6ig}ds0{;gA^#Aim;fgn5q{;jAT;A>4+JTe~ z8b|E-Y5U0urZI(u zArDfn=7eO<|!!|PoEBY>SHG?G--qjrlPQ%?qJUI^F1?*-_Ri8HKO-mSO)z)jWsa$ zb)F!?$jz0MyW&-ljhYo!_a?_Rz3v%aD~vq1W=KmUD8P^IN~hpB(eC2S=kPgf#PIVI zXTKVGE%3+%<&aIyzc~8X-JPSjVHU?8VA~SsNvKwzy?_2iwKL=1!Q≺zs}ka|0&3 z@WXr;IVC{)1^o|&grQoz&y1Lx^|9!ot8M`Z1p!RKx(kPdCLZ?gCU0^@^*0SN`}>a{ z#bXPmQHz=%{1GqS*y zGtk)MI@OxIhvUxs$0xf%LV#y{LtIr_h+sJGJ4_dq3Rz`)^tF#; zsMYDLpg=YP?9j1~qGS^{By=*MavMpA5XG5`8~ao49h-2@F7;MEnnT*~gu!9Qf*}-| z{|(TKcR+;HO$R`WGEz#!bI-XR9chbhzIZX@!5Z>9SDfjwt{8 zh~M2kuoZU$&W#w$BHGniF}b$ccJyp878HoneSDHTm#(fX2{OLyflD1tkvK+pO+-?a ztGzYe?jw?c_`M}@v9V^9&cegKyrk31ciyyVW(csDRoAAxoB`PYD(8xz8FIX$s!AJt zO7uqRfsc|#Yh}((jAx<+QusR`DbhIEy-ho{-5Q@)7d_%Dfe$Nvr?BlEWaAL!(8neO$VXl+(lmx`TLGfOSh z>=)XuYrbi0mmQ8eor*i&JPn?V$yV^yt5+*i0g^@T37hf_AQ_6SnWAE>lz5?OoP^WN zdYF7(9@&-0OaJNzyUozt7O+MXP2NaWY@4i*oXPzZc_B8$k*XaD@W=$a01?Gd46$s% z*eg54qm%x<`j+;r9W9kTbCUhMlr4z1OTWIlb8(^V{9nru*Fx9f2Xgt@vC zG?3F%#9B^wdRl#*J>4N~tf&&8t7DHJcck4FQOUDsgCDHS06i0u31H|cLvz$4$eE2F zoTGF+b?%%u^Srh*+N4pykegT{(Hkty&q`cF#PCJ(+2xijeTA6$Q>N1!^DZt z7dtiPmwUn!!qG)OP4P?ZY-o72c~8}d2uf*@#aM1U_x8+w|Js511qJqQN?8zu*lAk+ zH^wCrg3@;i9FhI>bFfLO?b}-edx>~3t|SEhMeLplxD-ayDQjSG`(zf?PuqFJ=;Gyd zTP`;9zF$35y=ZCSgMvb>d*6q2KCs9n{d>o>*`sNq!fQKin4c~VM$4<-w-Jq*Lal)8HK9@#}X+6$MkDT6HDyWy3R4L&*0-EoU zP6OpH|F!!~jTZ*xtzFnnQJi{MtNW*M)JKgPmF89d`s`jr z@$f6TFPD2vnv_E$Pn#xV#q?)Vetw#+K6tSnzNkbW{n;vY)lCo=bIlULh1`x$=%2Hc zcx=ZYu3NA1G8HT)v1iXZEH09HPi{GB93gWB;!mpjOuj*Q^VL9*B3Xf?^v3eQ_C#OD zJ9s5UO!P{0pEJjZteA-e3eZ`#$L>WFE-0Q(iTF4o(Jt(M+Q8@uk#>+^b~39r;hX_9 zp2MOB17|-nl5anCQWX5MNIjNSZeYr(abul9d#nFOe5bM@0|{&z6mSy}#F2B8kqjeX zS&v5+js6XgUwSjKoVGk!1LR4x%VS}Mo@-)rjF;lk7|2K=sTd5{oYNq!dP=&Dmxp%0 zpSNF!-qISDxz=vMl$=jG<*p}M_1t>4r0)11aho9(Xn**M2!)qEIylD-7#84l5&t0x zl_D!5$ELjW?OUnKQvK_Paod^KK``ga>pry9`2yA!3^}5kSQ=1X^HudDb;%8Yh-`qL z#CaB`OefF*);_;u{P#F!YTvA#_1X$-VUbr8|MQl9cn-ytG&2YiXFOTbPvi}-i_(Ph z3dL1aJ_bJz2Y@D&ory&IoG)W4d0Y6WG+aGV<_hYyqocXt1sq+k4LQ~4-CF4WBc%bQ zs&I2;e?t2L9uBv7ga~4b($f6mg`DQkr?Sn0)=||lopG{AA}LDhV7h(anM_8w9skxK z73qK(3l`v@gZ8|CVD&N*eo;Wy#erN|b7FF``_XnpyAk>WbzaKK16=^ZA#H<2Rd+ zI{$5_$%#pkl%o0gW{52wxQUGGhiU6y7(gmC;N3g@w7)@q$mTT!Of?=ja1RN0+Vtt+ z@0YtD-v19Hk&)@sY9kgwiK!erd0^l|O7Z(}U~wNX z^fyr-`&pgul)QSaJV`#Iy!?l0&m%|bhF8F^6oY_KYySUJ6IEBlkN{&PdHsC46@bWa z2r~(g25Be6KnPp~_J_n4Mu)@9g&Ci&P{|>jG3+UX0D7%-R$6ej#3WfjO|U;Uv?!4& zy$Kh-bEA(aZ8X;i$ceVu2I;OqSB68HOqXstkMoBcBCXxU?N(8iaJ=4MIPh=9uU})o z{Fyyt#x3r`gNF|@8OXr!T<=UO={=ZxMVAL6unDs$!{_5JE!IaLC37R#y<>BJ$@1~S z#f#CPXlIriA>b8^3$mu5sss5km)FT?QFnAKF=QLtNBcYRxCLBA6@#gV$hC?qH#4jP z4l)wy0z92_@{UQhZ*h;FK@z%tq0Mo^$6JVE9u~8F791R^#OX6;Sn;I7juq6@x2DG}=?`Wu9=S4HMvXJ`P3M_(_ zP_`X#wp3cTj%nT!5vBzn5l$pXY4&07-0^B0^8~WFZIe|;Rw6gW38k2qP319t-n>y1 zcM)d3)OM7Eo+ zI4^CQlaL$?V2SxJ%Q3V##)-`JQT#UT)M;Pyo_nIhgv-UuF50grOF1&Sz2?EvRt|K1 z)qy725}G^mPx~I3xOfVHJg#Bc%<%u`C<{F;t3aq5WgZG7`%|yBWDoQ*p)~ZdCr>&7 z(7nfsj0ci|hdHR-Xr7dUmcC5Sl#+;>s~c-)uI))1OD~jk)*|Te;T|{_WaZ^;r6ZLg zG3uwVm*Ic;yIlHUn%%bqRZbN9KWOBQa>^^e*8KVN_Vw!#L>SJCO^Df_LqvM+M%181 zx|GT?+JZ84G;%{>ZHPLqFLS?9u^gLxRXEyBt-9Tf=-2IHZEmX-9k-75_07(n8K2kY z{Kg{|P>AUG{9E8EP+C)(=ruCM_J z7JPr|)azVm6y4{ax!ye@s1xd9ah)k$B<^w8F^YQ}_&UK9_2tL5A3LvQa318`84WDJ zN*`7?q4Wrv{MZL0cA*lb)uM`I+!KUeMQ4G|h0GG}>Ud;w!C$9?<%pJvAJ>m4<7NGr zzD=SUWdX=3{tE3;hFHS!;Ph#R+ap6GsUsvnq zgw;EAP-~z4sC$gParNgG>c)Y5LhXqW6S^=;El?T9C}H^vnx#F&SzTRS^;etE3SK5K zGx-wgTw`}0p}~vkDeRi!=lTb`x{k)N~LpvWo?Zd8PF1bCtH9wxi-{&3(f;!yD6QeO>s>DiEdnUtdtO#Ein(cH2_sE0VMl5(D=`46Y&&nztDtQ>LX?eStFd`yER>tZhl_q4ZoA?(s? ziYrDY*_2|zMd~wPfYZ;sTfZ2}lKn1CTXycwaig#u=9u})UAiOQs1=b%AWsoU44bL{ zdHglVS}Bu@^@gurb$tHw^V@+pvyQZH9r8$Im4kMX<;(JUC>O*;}ja*u%~QFyK+p!LL$k zt9MRrSA*TNd^fxVV0P!Al-{JS_xg#=yd=w{rVlw>e!ZFU35JdQSoj5kQo)AXbpKhx`_N#50y* z9DY;$+$H{?`#PGF%O-G;XuLG?8YaFd3km{ONp+lKvROs2?d zrcZJ^HjY2&LMd~D0Ku4sH=VETj&)C;Ju{|@(VqPcaz=LZi5VM;Zu<2gm2uE{{|Ftr z(LO@gWQyY}-*(;Y@*CRzlTvRrTu0H%xGH5;0!@dL%;l!{Vo>cP-dHp>q z=CJ*0%^)3sI0QM6-a6A!Dc=xN2^1DgX|u6H8^9d3mY6(x?d~u0uw+H7>0UTYxu>6a z#b4HTr5#5DD|#+J&5PB*1t4=di>Xe!JE&A_b3C%SNKg@q(E zGqu^k`~D&URLsp?x~MHoE4^{Y;$%?s?IRN_dTy#Y7}!v~qZdZphDQxbvJdY>wLz{D=&RRD8u~K~is+3zFKgyt zW(2Q*QA%PY0P+XTCdQBswA3=p z9AH#d?O)+~moS2A(PL1)x@wP^AD;c~eCf|7gL55Yk|Q_%IvG9vd8&SwqwlPzSZ_s$ zJk`_F91z}R&0Vt16Lvb#e0bv6fhM8-I(l?xY#Cs%vtXMBE`A^4H#U|?nYg0UO$ZMP zFsZEt3LpIYd9M*D<3&Ix){{>a2H@5NI;>7z0{Gp7cXZbGp%O;=CMS=&>a_)<(o;>9 zwL+iVeE;8^nj#bNCX;%wx1le?tdg)x{(_2V0es@XBqSYAOLgcq-Z~3!!ltgUCe46< zzmuvM7p|#ON02{-sG_uyI){G+9~$v`;ip$uJ58GOQsL0AqVWIoe&uxt@~ZGvqg;*1 zN|&?(bcdQihtDeL4w0rWVkx)0VlMm0YOsda5@y2#~|#ai!q*nNE0t4(xfO_wQsAm(JxRx zq19W{tRlbq_}zAELVVVZY3F#mr+uHmFJ5N}A zt}b4@cuL@s**SoJ)y#m$g<4YhuuUugB{;=kJOw+;4P<$Re9N2>C$=QigoH&Thb;*HM(;vFzL14lEJGnywvxzC^VZpP z={6X!_z7Pu-BGH>L(cyGbcM7!oCuCeftUeju?>G&iL9>YV&{G9Ui`>~asq z#tLyw#22q_kW!ZOS;A#Dz;soK|F!GmQV06Z1#z2j;{zWwwE^84;U~&hM;+mY)8vre*{@uoXkv2ZW37;VRI!rMxGP~ z#cD_AAnFJd*Gy*(x${@Hu#x{=%D)cLflFlL=&+}uPk0eH=KfJIos&6#Rmaw?N1*ak zM7#(yjR*i{lnKSK+{akpW8S!)Ib6NR9}|BpsT6})EKM0<6GjR7sQ$2MbRY~Y0<9c= z@v;no9DPwVHPDgBq5cA8G717#WbCC-vr03jHr3K)$G7KV$$?_0Mn7G9^}Z9U{``bK zMUpw19#f_osQU_*uwh$_ziBGX5m@nI3-Cme(wAmQhSY-_`@hXg8i-f%Du;1X+YV?M z&pOAD5w2Rw_j)V1B<9u^)dIB0ZWKZ`<-Mdn64D#&?Z=JlaP8VP-^Ss%)`CGwtRXir zkG}Zxvq;X-|E4rC;2uIK&1AxotCPazE3Gk(GD?s54ml&M3&>^WQ>JuVvt|v3#BMFk z@klh|zKlOVN1f5T7>WrdOjRI2A~)Eg`vLuwNCRywD(=~{k9w36l80O)6H(k5 zm`%DvEElIY@jN2hxnJsaow)TR#amfM+Nk%~;P-&~542FcP6O6FBF`K(dhxZaEDQEQ z=qX^-!&H!p#(ToC5XmK^%BKaK6U#7Szi#T>DV$xZLr++1=x-D#vZIKYDHR!YtoFE* ztKQ$&5IT;A5pLAINm032?0^!}CfhDE<)^{?B#ygqo)IMCSeNRbt0!Y(24jFtu{{z* z3M3tor>KmZNPt2>h0SQ&CzyS3&W49)m$aZ z6|c-yUQ%~yV$0q+nVk;HDG~UZ=RxV*H+{Nn*#WgHBO$vTaSI|r6d;3byWs>ChxGMC z9AppzEx}xin27L({h$VPqgZ(Gpq(i|IHM;$oMyu}(2TmR`~q;B1Bg5eeIJ#nj7#V@ zY4ok<#i1B^fvhKTCgq?4(aHWGe2Zi_md`cn$1}c&cwKnl_(~%01I(b1<2roT?o{9+ z@BxW2W~LQ+oe+&CyDa=mKtSc1MPm_pfw>9k>p*LmBsolONgn3Um5|U%FBZn!u}s-w z0lSron{X)tT#>nm({=yZRzz`krStP&Tui5jme%;&T&rRLGECH3gK~f_@gy=q(n$Vq zKYiNYy}=mk+TU3SSK>b^-zS!bY6nRjo%07VkRUM(4vCfk(-0VLmX^#27}4|EoX5c4 zVwOzkL9?nkX=fQ9Ud;1k$_)S+fG+=vYAB;jseT*5a!2Eu3O`$e0+Z;ONH~S>R$*eD z)As;#N;LlJ*B)2^SjzqaE+N@;#OD$H0dWLTpbu>RAvUC=)aos8At5OeL++ftIw@Qx z>8P9%{T{ucXb=>FTKwVkmk?pxRT3f(JDfLs3U@{JevCpY&St8FTw6uT0n)^v%$|Cs zevK#UzUXdXG$!HSaLw56E?-se{2m*}8`Qs+ibv*dAnb)SbAo*`#tdvB2@KB)hGv3^ z@~FbWJ7XZbaYvJ(au60-sf8U+7{_1Xp7@2KClil7AEj#lD!K^_7=(f*vrWaKh`APx z2MghgC?>`FNZv92N+B`qN1-=qDKq6z)II=bDfjGaU*&P{Wi~cvTT!=0xnSeuG+;KX zxal(13Sfa=z$|#@4{inW(ndXc9JX9@nP#z7*CE|eLGB;8Fo65Z=%01ul26wij5m2aajU~tmXQJ6pM-BxRv__MhQoPMu1DPT z2_e?#@&SmXRrIg_J7AKQ3Rm1=NsB#S_f0()VB0{wW66CZQBr-Ys&a_9PG~<;dw=Ua zJ2qh@5?`;dmYLSa5BC+Gg%t`@=|W|E$8{-#fin18LR9q~x{FdV1?4!O*`5~a37S&+ zIF}O-B9OE4%Z2IX-FsOd^fp%K4pCE%NS%oX(Munof`GRWs&_C%lBdM2w@*1vG|)B( zn@@K~R};1~7HLCC-tL{;ln2O?wReVUE3R6#3Qa)B`@I}Ba9tvR1EBBwC#SX8PawP9 z5Yk{Vz1z~>p?GT&J3%`G-LP^ogFYA>lcMf5Kq$i#lz>_2NFLsPwH)a^GI;}k(8QKR zGO%#LeNW?*=Utyxw8$e&8(Q%m1(g6kU^op#3*GiJ?7I`*k`+Q!2M zbkU^1HxQ%(e&zFnU9A%KJI_5hsK+I1&s@?1pV^cQ4}d=mq5pM zgIwGR2RQCUD7I%9^))>Ugfw*4rpU-hyB~UQk=x&AIz!yQZf_d(>usoZ=|R|=nPo)f z+@8(J6Qi)fc2nvlk__}roIz>($V&3hI-1O4!?Y?$0R@e2X2wI33=%)@sg{384{R zqH6x8mwH%te0lZPTK_9uTXnsBcmKgfcgudP$olv&Ze;9Z9WAX!aFkR%;tg0{4kkV2 zQ~Z4#^NC{3&TpZPPT**aJmJ~_b0CGXXvnSZ%Zz2q;QwBRvbH(B9cXTEGV9^&&)Cw) zWGN2~d38qyL;0y{$+O27ejV2VGx3X9fAP9ASRnx{8W9m8!8JKTRi-4tTm)n1X&Rm1 z(MMlD2ogd$a57Lncp1&qw)5xz#m8AhUVsh-1RL_x&z-H$9Xn=(25mdHhbA~-$1~Aw zmX(d|6<60PZol)cx5IY~dAgN)YuC80r86xIB2!2qF3S|~$~nWFqb#lB^GiP|y%m|a z;Zvc}=xctz$(}v!_qHOf*O~3VbglRkyQXwn{E|f<9_4M7wi}3RB2(l?tAXwzMS1tQ5qYsi%SV)0rzfq7-uaRC#O;uI3nC$1KU1Qjc zSXIpR7h{0^`#V!BWe}y3To1Pdap*n9aur7(WA<PbFI8Rp z3tLx;7O|r*8l0S*jP3;ou8^;n@hX~EboY4pUp8Gcl*i;(M+=J^o|%!BlX~6M z6a%R{^V9y`dY!(Zbnvo*f&%n^jQhqb;X`96x?M0-Fv5yp~;uY@u%s+Tv)|<&RD}Bd|V2 z*RI|lr`oOCJ-(~N0wHnHIO_PCRDAn(9U8Nw#ESx{agT)gWJuW{MA0UukOa8!(9m@B zC1S%5%u=(q6XIRm?99kXjTdc9>$D>3Amw$W!Ho(;mBnx0Ha_~uulBE=(~8|33DT}H zAYOfksK6I@ZIj(5)CLs2rjn&YP~)Sn-$wWq2M6?G*&I?NZq@p|hI2;E-QCZPGggdo ziCt_N)5pf^sl$Gg(85Bu!oos%S>T~o?(UHY(gd$V;u>h9t+GqMnP%t~dPU&UvD4Nq z_VX(SRG0BTWK)`lc0tSC;7UX}{Iqy%Jap&*ikoI%`l3da8BJWf=%I2b1nsXJ=Xi=W zCn~dretw$$`l(W%@*m7+dcz+3y?j=rWnf^?ElNRy z5EZOKQ!R#!1Y7d;HBeVq7t{&YGuhqt<^|mgx-GqmzmMsK_-6LUbA0E`+re-t+Ll;B z^^u#>@@Yoe)qFgehKTGCSrK1?quIAkP4WL5$;Xl%G`xq4$T^rPrUqQkh2mtSQ;guV ze~Tq)C}XLFB+c+=yAAtSw_}S)JhdcUUoreP6*G-^B01iF-@d23EK0;K90?}7Pu=Wz zU0+{+_@qrqokt!TVm^LHy&egHlq8{|tu9NqOCAQrg-z;#Lk|tr=?b-e3tQgJJ>LyW-E+G?dIqs}*ix z6iw^jT_q^D?OYpM+c(6Y)wR`aI6h|2`!Os4z&v%{yt|YWwzjtE1hbnY_JGAG=V3| z_KkJmzRUtCwcSavF4Qz)5pgL4NhHejEKFAL8~Sd*oF^j))vdQ?iXA!q?nxhw{{177 zP`73xJ1Qz_gq4b_>QmU{^#?A38@^!40|>I(ig_a2LPR9pBWyu#e_z`K7by%V>PU-1 zp-I*R4vf^-e9u5J*%WT%=KcGp#_1>oS!OU9DFPje?3o-7^Y~E)k>ckfVysc4T2g72 zvIMk#V*aZYlr#*D3m^vHj0LqkU&4&y=wfsS!YqN^lg6-VW6#BQv{r1kfkW(z8c-~F ziDJo6uc3jr0LW+(0IFpDWg@4}V)_y1NaD3V0?HZ~w6#;p;oW z(z3T+Gqto63V~vGE5CwKf<=?vfu%ug{=UMv{Lqi;&knn&m81!Gc%LtH=rx)gT zIzCLr!x{ya41SYz>QBXhNz&`l|Id}+tPbC@w*K!jIL*L!-LsDuMA#+BMl2m29S(-Az?>ZR zphJEb;>qqlG`3;}550YZHmY@yC8scj>2kJ{mE;G|yC)KfL512HmbGO82k%5-UuuT- z5xaa1qe#0bT5boA&UL~*qBqg`B7?0SP?+j%q^?*gc|i7-Ly-Uv|{;{wy5 z{{wo)B`5owzPFga%0#4U+}RbQZ_?DLvbB=712A8Iq1}*S!w$m6R8*C_rlh2Zs#Iof z2%!lp(}dxq4#^pR@Y$0m&~g)|-eK~~fZKBG`SX1MGu!}Dz&6WOg$$`^RY%CVmnS9BFg!h<(dP>A5wT=~_ z$&pTzKU#-Uzms>8nVsPB)ttXdF@+V1otL@uj_3`3QlvBkBBsIeiwX>_?*(8hrtEZa z_vntrxXkl(2cnC-zpyYB`mBvge>lg+| z4(36LhK(SqOPU1y$qw>iT`>5e8o*B;HZ|iI5etf&%~vtEd&x*!(UM-;&G7jJlqlrV}ga3A82DE&=S4X|(k! z^R-M(JHhFKU6^y?a&F(Y)K-ZFfZdX^`|QLT(!qYh4OepatQzhWhH0^%Gp zWo=F4WVc)by6i!s3TgMM2L!VeA9Rxf>!u}~*6q<_Ge=mkC~%lPbR?}39;ao|2ul|Z zl(uW@7J3UD1OK}Ia^Dd*`c>(q9sZq>7y{H(qy;#<8y_Be zaO6R|&~a|d9TS?}^lX#n_$T>y&Y5A~MLmxYU(^ z)<|UlkVxMrQ4Bh`XPc;S8*So~^0@=VWOIwrU1fxgsUkdd`croh0d~KY` z?8F1oY9)jT|EzLF!eeeSo!SD76xhN=^Iuo4?}=F}k2?!w_#4f5e!dENK1xFt^whrj z+zMm>l!&Hb2VjG9qv(SNC;KW>>2}D~iYTqN4h;{#K|F_TsV`5ynBSc={C|9mHAT5P z1~a+2x%eP4$slK@L!YS)7^dhI`ekBQp#uPkc#GD_J9-Qo))mH|b7u?Di6I1I%cppY z9A`^r?d;B71tH)Z+B!PQP~P#`zrs}FEZ6;MuRW-8=M~HSw)a8@pZzp>r&46(#vjPp zcQP3`?D+^-OMYa{&cbW$yi#RbF+-E1-P{EJ38=cm>_DCCmt?AZXqp>DdGG~gN(5Oh z$umHHVC&>m1~DzO$nPgVE-WlTy(j%Vsu}YO2X^hc#VAdwQQHjx0Z&k2QA}jrzu%gd z1Pmb-6yQ8FagYc&=JM+M88T$-roO%VuLN#b-kBb23Y__; z>ew*Iak6%FY=M5qvqxv;c1C(SROxSQ7^TsmwTu|IQHu#Jn0 z?WMKb&+a~G6BgE5-!OLE)h6znnkRbpH8!Vw;zG3s1|rzk{CGTN>$N>PBdF&^pg@X4 zU%ZoPQpNBSezpDdddTrQ%}meApP%$+z5iQ)8%#0bK~GOlM)+bIedEz_wBCOG>I8}> zv}n}%=mQ6~pFZ7}*xjpYBbjn6O$S7SwvkcuP@6#BZA?XCY-~EO5f)$&&{eO3zI-QV zyrCtibIk(Zt-F18&Y0e3yni}q-3<0La2wIAFvbK_x5CAPr zd&6+-R#Lzsto>vxh_akiafnuqNH^K_0T+awvC$qcCzD$m=d+N^+Rjc%(!sS>EnB_= zIv%pNRaa0a92cs#Gq>_;p7W_r~!a`S-A*+5ir&OhLBO>dKo?yZl zE-iIze0*S3)cDxYDsWO%u3D`N$Vjx|6_u6d6yWgY_|)$_e}3uuKS*eb5nBQjI^*SF zwXK60xo2(1)Wr)Hyr%mFyuIx3aXt?LLNnr0j-G~w*{nKD37Yt6eUwQy1OPk{^Hcda zna1s~C z*UA|{VHcSN*9?81X1?P~eUJaz_vtdw!5f`@79CZj|FJSnxFJ&#DJ`EqhoKzcufePz~P?cy>Q-hIr8N4`#3b=8w&f&v{ z#b#Ry)vNOXsHkCPp#%naI79foK72c=k!&ZDg35Nzhu z@xlB8?{n^W@nQo=4!T9aKym22-ZCBcbHa~oCg}d_7i(ZtT|SYX6R8FmY-~f*2B1uL zk|@i5=RV&Bg@jrnkDeVrj*hyzx((l~r1qnznhu21_}~VZS{hAie!LMjx*3!b^NBL; ziLqu`DgTW$kSyrKXuB#CMA8rx7pF<#<>loSlbmeJ1}+ffHOZyh0pLUgf(U?KbR)O8 zfQ;JBxB4=L8U%|BJ~Z|XYPXrokxxD|-*?h(1K}M|LsSnSAG8_yR5@ZSNgW{N0}+o8 zCYB`fwB0s_*d>TP1EE3bXR-LQ`4aM zZ;k36n;!Qp8&$|W$VN|JD@q)ImH+wGQ=*rAh_v4d!-3*jI(mP*sxzH+EC$6IWepdU zlGiSir$Ng3{6qEmuUh;6Hqk#Z&&JiILF=(cEECqQNgn2-a%5!uWu)H%8tLe4Brz2n zvThaIshUzvyajo;{pevd7023!_6Vs3FOdQ2g9p3vSX4E4X8JrXm7Qi75}b1Q?L%pp zNVhMRp7J0m>}V6aukIb5gUoLIiyAS+Md^Yw)=oJ%CsdN+4v;Sym)o0o=1PEhpMd3Dy*2TJ5$QjkntP=(h= zd?|vM6xpDQtE=GQ?4QM4kYu%!IdUR??X-#c^Fu>IuG5Q1XM;9M*1psK9xc>nLnv+| z=dsE4pn!JQbX`ARqOOby4PU!D`H^8WN*WNPY4~=No_JVhnxQhvE{m-o_Tg&~o3&(y zX)k5beX!GpAMG1~2rMiP^f=@+V}>s3wG!lGa@_!)M&nQ_f_D-O^11jmrMU`D2Lp_H zlohqfDUOL*=X-RF$>4>Z7b@;c!0m|hLf0WnNmRDx__qR;7mXLB?;a@XqIV^(JNyp` zgVxRL;Jpf{A^Wqd_wH^#<oYerd3z!h0?b!$! z2b3LI2Uf{fJu|P3AGy%Mu07 ztIC1-U10`uDb{l>XTh3cN&A*lB;Pe8BxH5+uj=aMDDyUN-@g6Zc*+GNU%6wCR`-l| z(Fgbk**im58N0sZ>pHO?$I=ng;^FnRXYT9nywYskv^HNUQbc(O)SrF(c07rdE8x6k z!dm={d7H)vj65&L5@E#C%{Zz##1I2&89ZEo2~v&omyQ^4sA1to3vmnfVI-y&)Jxvf zcGQY=a6j9wYH{sAAr6T$(<8~2MGdGNRc;o;bSP}rWJD}|=L%43zaIxE6MHWn@s}Ep zvaUOym9Zfj(;8Rb(K;%MG-l|6TZ2eI2!Pnrm$5e1Gkp|+zH0L?_YM?vvXl-U(Hydd znnSh+d%pCLM@SeKNjW19GTFz8iVRNL%z_{gLm7RxDEkIJCR3x(Od=HLAg15Fy8}5c z#!>8qQYA0YGc<~Fu;NXDvB{`Le7tt|3pKhYd!3~*CxnP)MF75Z4nA>;RB%iaoE$xY@YGrno4i33Gq;WNTA!Q)vK?( z_!$`yVKZu!EVaagmU4d&it|=&Y&@T|Di5~kvs_dNz*AYCJIhYsZRP83k*iP zPL9~U12h1ob?8aum(27c1un%vKusm=1rTdlFtrJ+io(m#H;nU{_En8X}7ghN;-O^z~kzm;;$y2!|{{iAc!p| z3|pj@6UE+~qHA4v+Qev&Sy6Vj;>1L5*hrFx)WH-ymPgHhNWIQy)6>`2h_qWVbVRp= zZwqogLJd?#XXOTea6KGRvs~kX?I#*p&{1VAtwWj*dtV#dCd5YD+%_aNwZ?yY?5%p8 zh>xVz`I+DV<^0W{?0BOdo4;jlT@>V{|89_GU1>zh8q+}=nlAeB&QVGn&<^b@Bb3Yq zQiciS)*;N(49{_Pbv;DBNlH!@H}-BvE>jKMta+YbusfxQ|QmQUtu@d~GH&7?TBDy3Fs&zmmxwv{_Z3 zpYH}c&5i5;fE;0S=mgEVfWS;7sQHZE9Tt`WU?j>P;bveR>6pZHN5;*l$EBO0+S{#q z;-1#h6<)@D`x5Bdv(C-|1dPx%gDUPAi?PUqs)+V!6W05$3MnhsN719!smr|^z0+y~ znBJ%5m_d=Au|`iNh*?BgYfP2f1upxhXJ5LE3}e2^J9x3{>FNJyX=!yIU;tq2f;!op z-@xU!J^f2q^&Jv%2ycKw>LO+_#iYF{w4(PPJ2>xQfS`Q&zV z%y#bi8PtU|SYp4#6RNSkvfJIwtpih?toYI}HI++Gn`}XGmR4J-j0-}}vReM45Dm4I zO9}b+Ti7bSdGTkFNA-gBg`eC~znT=9>?!n9NgMFzK-I}|_~Z@v1B-|;wTR!mP-X#N zUd|Fwn{C+$;@@5$l?1&z{KUr1aqG`6kBq(H(Nd;ZJqD zDfbTkoo4;1x4=$)YTjQ2jx8v z*}wlbqDnL{dTsjJUs|<$!I`+vAA@f!>C$Dwoqwm|q2|}`{@Jr8XtkHa3{b!|Trmf| z1YPm%vWkh1ZtednYZgR-K~cQbgYU9T8X#PSROXwKoqK71vRm+xBL*}X+-Da1S}_(a!=JbpNgv5n z?R^@lh{#A=2M5WyVy?t+0t$|MWNw9~>Xd#UqO;iFhUlH@wuO$Jp?EZL0GToMkXZlT z52{4iJs!O=s_N9iXV9-0Bcvh5TY>3__jFWL`ulfNVC-Rsw{zt9aaAF{W86uA^+W?AAmHMwahleIx|>;9?Z;i@ z(i}Yba~2s2mCRl!5>e`D?i{Nb+RQu;HI~t%8!xl64qGNq%if;tGkbQ~)&{Z|jnG?x z2&rAN@&pXxv2ZeYQXo!g9Q@X;Td$*p<96cge)ak#;P|6{%$x|I%X9CgBvhDPmb73JNd(H?AVzUc%N8q!WGz6 zzM9V}3>JR@YPv7y<=vm7Rh2qD^Uf|=k!{>B)HY$uTF)cn9UZp=v?;ZiOtMZO`7+9u zkbUbYS&>o2d!QRDAVx(v>a@OIA;KET#0Bwm%h)hM1*Jl>_s>2b{`9A6#F`09%gv=~ zee|eT!B+7PrAhyIxNylxc32>T=RS^k{fqC5);#5A=(Qoob3T2V1BfX@A9BZW=%gS` z%%0xMpz=5M0h%J^ZS$Dv>TGYH*U;NW@*FP$GgbHX{a1lIy`kjW*2Q!eNmgxOv(2{- zSA25q9OUy)_28|+zVXmIFA)z=_9T!e{({%wQ0^C;B zg?;^Nr&tRX=Oj{Do)zvZ7jO2i!A!Q=#OuA&)3ir-Iwh@kZ92A{%qLI=_4Ur(`LMP` zQUNdi-zlFXDbMfU4?!9gF>vKMHUM*I%E85`BVWUmFvZJ0iHe4u7FKo-wSn&QiTx2t zfec`#-R%vHB&p%FzyI0+2ZjtZHGKLKb!P+KDp-p(RqkoFqip5GCS?qD92KR*m)g8e`nCXTqn z@1I;9(0_1?x7BC5YpNIrE@^vHv&n@cd1vQsFMlzv3!cd|5xKOQN;>t%Q4Y>+s(=45 z1hUD19OZYOTKU75#7&j)nl@QmR~P0s%{3VbrR)ap_fDkrVX#p4sc4pZQ_l+5 zz#)>fh=NdDhnOU>ada%Tc+s@owVo4iwpPz}@jkmUKX~PmI>(r_9xICKl9Q5T0XMQS z5sP!85_BKapU4~yfJ*7*rVTwjLTi)GhT8<%Et-4w#N@xHKS#8N17OI^q4ixBYFz35 zY;tR6#ZKcVhZrg0=e*uoY5z&Q3Qlt}IIH$A*0BX9b0hvM%YHm_dRjmC??3l1_9adm zemlvR$xKY?XKXAtoyoxArF(cL6g9W4bEQjwT#PdDaS1vvgwc>8L!_0$(WqT^56J+ZArxg?t8`u24Csn5{!E1-c|h;B7l-;%)R; z5MqemH4F{6k`9Q8Vxhw8Pdaj>7*7=(c5R%Tdi3mhJo_zrLh)$<4OHpY&1vPz!Nj_e zwo`)E+5O`kJnG%Fu|<>K_b)W8s1$Di#Dh9xO!b;^v~{(#HqhVme=WdB#KRQ4dXAc* zbAR2$s*VvwF<(ABOscPVo7-AveOlUZ`juP66q;_SL}4V}Bea$e9^1=&#rSwC-Q9<; z=dBajPjoOri6Ogkb5}EwL}IkJg;XOG)iauRvii9#Wl3}Yo#9tkjUI2m6?wI+H6`hD zt}~`E+z{sf(5IbAcaYg2PM^%`r+@hRJPi+}2%qk+(CY#7v|GLB`<(m1M|<4fKoFt7 zOdw9+_qCV090;`;np2_6>Bsc^NMm2a!OCISC%-o)X^EW6uSFY_ayOnmyJU0q7G))m zKm_IuNTB*A#e2h|ZY;li_{yI!2aO>qBWhob+R)|gbB($kZo^hoDj+uop@Q~~p=}eW zfI3HLZ$6iejg4@FGQvQK(7yUIzD3>W@Tt=#lq?jzBp4WRaNUdSlhD+t_)2T?6~(ka_q9+BH~XyF*C?A;Of<(B4y+y&*8LA znTwHM;?#l;@UUdwoV#~*_4F7MZo!uKDN`5!82%4@4jvRwF?Lo7iq9^b_i74_uhbg| z;y6Dlwkrr(24jxx>3yk3yRAI59y&UW5zWJHA&Q6C|A+fxso4fKt1!T4T`epc5zE2Y zQOyWm%e^UX|2nIrM|e(~_WS*MDc;oVd*H+3;_U1B<%?J?*>U8^Oyfb{=^+>mxz2M+ zntXLIZiJdF9239zG!^s z%5j~QC8x~UKV^lmYez2{_%FY9Zz3gr>D57frVgrLQ@wN|jn?LMm=N?&`U{*go zM(BjY8aula;!ip!9|S_CRTV83kkqzL16rcA@^aB%zvfS97qyY&!{-@yKWyhs39D_O z+XSGMeS`|5XVUsGJSQYM+)6xrLroJ+Y7@{AiO2uvp9R0Eq!Zs*V`s?P`muO){yXQ% zIw~tWJ3A@y=|jb_&GX)8_;p@h6!+~kxUh6%zpF1s zea06YR?LY^y>Z?zm@DvOCooPCodDf1mm4!~%4>Laj%t=jKh>gSH5cl51Q}NMKjj@g z=jQA@^~v6T)!t(^y1aPk*~ZOz%=N^h21?1NrNrb(f>&PzmO~8Z1=82N%if8aj7cDC zmIR9b3Vp0p9`t^ZM-}&(E)({ugnoit>xq*hC5!!PkC09}MvCS3G$1gEFz`qngRcxg zR4Ez=I?0WROANXFU;FW<5W~wdQW_*LhIWQWq+CGBMQdL3tBmMu1nFRU}mipl>k@b~D^{)l?Vwrv9`OsHdI z`3ry)G#WTy&}*gwAQ3ZQEYVunuwyh#MC=ZNiN` zFZ_(t+8DXee&AMbBMYgB-)rK+m(urK%q9|!NYzKmk0Hbt`10Sx%VuvJ#SoTA%A zR_u!SC;IZTvdK%9;EODdQan*r&Dj9!7&N ztjmg=we~j3zgH3ZT$0-e>BFYi4g(neQb-!Nv-+ESsF~_be8xGw+e^MEg8pV=$b_%6M14keiqk9I{FW>Z5fbJGK`G4frTqObwk8 zdP?CQ!jP6{m$~!G-nUEh`^UNU*7y0Rl$N}jQbNvAXwt-Z-iv|g%K(^E>C90fh)FI1 zjdtG5$!RBOVknc#-P2(r-?GR=7G_mfED|Bt8l0Oz`I|Nl!|g@%N7A%wK2k`<9r$f}e`d+TZ_rIa$tmb6on zHcbsm6x!NT!)Vh^h5zHc?(gq^AIE)szjw>$^M1d^c|O-UJ_Y?1Ct>l284J)kiA39b z+_fEJLN-osU;6q{{#19j9%m}P{#PtudEu#kP5Q3awd;bnCHlBJMEy?j<41NPR7t}V zb9L9j_FMg*I*&39o=p_gGrnl#-@i|n>UcO`M{9JZW9xR0J6pT2e^!1o9|Ay>gKYM0 zf!UCZqW6L1fSKB~wc`ljk`a+!6zPMvN5X8~$+W=C^nORfo~Tr?7R zF3Rt?b~CX)17$7<7qx4Y(L(O!VhlFRYMcqe%nP|GjM%WXLyB@P+jX%CC8 z#z4=u|NJuL%`MswXxhKONaK*)_d=nF7a@6Hm%6Ew0RKQi%G1rp$!Ze^%bVM)!3V`I z!P=znR;n9VRX^0s46_$~&S3j`kFJ|4oxXL?Ie))&MRH0?5iMrM{hW3su9J`S{j1d} zVd%b{-hEQ*yW@XQvfGFLUB=JRirMq;k-Uh0h>|?U`p7BP3lO)Y2p}qr-L$EY+soC% zL;upv7`4@p?A2RE9ZuJXvNBF{E6thq>0$KgHLW)82%|M*nqUFOtFfu&@W+B8&^ywM zgX=r(I{BL&i?qDt;=V?Usy;X@H)+3g&ae8l?i02kq55ek&Ce&wDi zUGc|xiRm&1Mvyrjp4jHI7rpME+^D|@_Z-qH9@@4LPFr2fcL5MQAy$OhLgyY5L+r2JQT9to-_CE-4j!(on7PEvp>28Y5Nj)LFu@F zrJFO}Bs^`$5A}#rtZ|feOQZ|Gwv(Kur{|AmV^9DjbqM!9~V zdZG*xY%;=UgN1YE>#*5C#*PL5419ik`RI2ue+*45C_cCKOV(YZs`cxea^)cY#n-uw ziU!27GbRnAyFazUxc#L?W!O#ej*z+{R^ZpP4aauxu37r7-%GpbotqOHMMh?qx#?N! zCZ%d8?Am`|_3y+C_l~_g+-@;aqd1iM@eT)ga7seFB#~0}@7ljV62y@ZuZ!j9RaLil zH*_wKY>;VxZO5g$J+|NTwwlJ-Ol-;_01m;WTvjlezE zvW1C70SFvDVr?Y+n*yFieR211kjb?DI<>VwOH&w#^4e)*ZJQKDwTKa^>f_HWv|F>D zjb*J|3ORsnAknem)PTR^4p+i-(9GY4k$GsNY_BU;*vSEndsmW##^lX|$V^YEXokJA|#lb?EWtxhm!4?4poR$@aX6)=q zMl%exqQ15~RW)KO4-eehhTov>Brsuw2xKQyV1{_-8Q$z#M}Z&*B=w$Vo6P8l2&1?? zw@x8k$R|IYhLk4Vz`OP1Hcxte`ZUO8w^Lc8z&mNR?UQ`24F#ZpV^EpgnKwNZZ!C5h zk`d|@PE1lAyo0VTJ~1($x=?x$)>O}4{)gPp4#;fuJxDL1&-k;Z(FO-Ks`V;nhhd4S zol1Da??kOm%05__QVk+Jh$$L_!U~xYN}TT_y;G? zb=EF}1n-xgj4}KC4u(~xzGg=}1wF6%c&c=ohl09ZoV{#yK|c6`{E-AmNmw?qL~%SD z*bY>x>{r>Rl|zH{izAO8cy{8U9K;&UjW_U=97d8Yy;}{3rM43Bl`iu*yeQQ z*fZr{N2!j)3X?S6p*WYp@HM-FTlpf125j1RWDQ}nvndH*c5YeFQ$?Qp!-v1pmn;m4 z{&Ow7y~V~XPxWpu2i({&WB>$m-9RLo)MxK^?9(Y+qS)|8E z)LY7lPkk&_l)X{v_$~v@RwcVcvU)oe&_I32h^0QO4 zXBZchdhw$t@!!BWA(o`1XKj{Ntbh6ISKs$@>jv#QxKn%b+)@>2f&KQmgXu%iF9i0fLULx1BPSw$Ny{`M6$<*m6*BJWli8@X>D zkoHMs=8T?4wXgrtj9;VJKx4mWn*X{V)9m%gv^;u1V@(#IAv$Gs`dpy(aOV3UFhjiR zx-UWzSnLJ;{pqu3Mau*AI6Af6o;>OSB`mwv)awlS*l;ukrKUvYf~_F)RzpLLCR6fN z#B?)u>}ECB_fJmsgs}xOOM0ySg|fi5Q!c%%$ZI(pxp(8Cn2>&6@3UjB)in3B0N2r> zPI+I_qST^n5bTRlNQU+(JaYyMW6Lco`zN3MPM-9SQ;!dN9N72mQh@r-8A_8ymmCpM zG)i-0|ut1HR-dD7&1C^8^x4- zT^Z6ulxXCJy+e_BaDDgX45tGq;4EUYa68)W0G4Fn15Wgm?*rbyy|u5=_IKOU1`lYd zD{7&qUOH#S^`nm_YfT9Y5+Iy-K3TiW7WLC#k;_=kwUCiabY1M{W)f$A6f~$;F9h%H zLE0iQd6Di@=rx2xV;sF%=#e8wTw;DvG;8e-dIF+!a&Bo|=dOv!4b%3|?5VP&l|}2Z z$HuuChHL!V`l}|r!_APs#mbXSBZXN(?yCrlK*i2_wx;8z79Gw!0YO;(@)Y@2-%oj; zinw=o-`!(&IX4f8lvW2^)c5?v`7mP!`lAa=| zP?UJ$ip4%T&e&*|87!^i;a#aL&OLkfG;!9EL`vMwp{9t< zlFdf*f-`cTjm>LrDG5$3t%T65psHcmQ!Mwo>TP3CO;e+|&S+W7d80H18;aG(yJ_s# z?l#HX#meMW%nj#~l!ied`6c0YXpucFoakn!A z4@G$A$HX~gDC!2j|2L-NkRQjIJ4*^N6A2_d!8<64djp1YDw3o15fRFqj#E&C*S=-;*|U8YOu1;F!I7=syLYD3m6~Ip zk6lhJJ6P5^aHvA8uDq?4k|eNF~(sh*o7I!VrgE z8-bZ;jUk)dx!j={X=PW$V7p`A#hU5$?uPtE_^?RJRIT;K?!UaMOHn$qpD&7MLYsEL-5{`&s zL|j1lCk*=;Z%RrkU~G?!6r%i-IYbn^6_4wch8nnZiS1C{0f;E)ct)GvZhH(3j8d2S zYQ}VEA<#4GtTjuAV?OMBCI@Cp)J8PY;_!w`p{Q>Jpv}Gi`D#zwsJRFB?-vAs+tr?g z7i7beG6S3q5^7)PRF|e6{Bz^lH9bNGz>9e%K{UKM_m=N!ZsFdl+i)k_g4`p`YjTy! z`zMyiO6HG@G`oDc4?jqpGjQaR2F9`@>`G$qAt3=L%R_$8Tjk?+QcT0oTpX~qtObe$ zG!*R#pH+3{%=ZfI7obwi#&|_T1<<&K6~kiKqToA4q;q^wrT8lRXJ2to2zJ12vgZ4< zr%$W#iLuz|o6yWe&B~9cx!my$hke;!$D7BXtYk_Tz>7porSzT3VCw$Jt&}?5bw`0^-JbPn3W6H>k-HTQHTh4y(Rd9NY zaR_0a_^bsb)Zc&m#L=TKz$cux3}}X@TPM;DdQE4u=;%5d3}@qkA`_uw|HrD8ckPRr zDJQ#VS-n4_Ij#NT9bB9;##n3xOm9QmFr2jkBw3$$cLAjsFoV(jOP>Evf(d)HzJqCe z%PzwcgS1b9Jv!cR(( zQo_+s7P}4pH)?x6+t>S5-Pew5I=%lP%_FJ4wL>23DM5H{YJrEG2UAuPqry?rTzUjLaPZ(yT z714X<+{+*C+g{yNdqnivjc~rREhM{X^XAQ13|aw|Q%%WTz-21WhqaGJjzaRnjT?ur z8Ex9JL8@-pJ}$hFcZ--DDS#I3Bi{bZ!hX}49z_j(ks=RMMK9t_{0!=m_mI4ya@Pil zfj^2&rbRbIXSwQ@^y~93A;A!-Dh+PZ2(OQVje%c9*nq%j3UdvDfbPt7Hazk^TT zk5;?e&9EMQhi+f$MW9`yL?1$P*c&oE>uY~s9(OgVnVq;hHOFa5|{ zOP4HpLE;d_P%lQ$z!}1oJHCtyOYK42bRg|l$pGg<7>&?$eH8EJH^=`gK$a z%l=#K3RBg<+8A)V9cna|9X91ss1`H<@(NDu<1~# zsWTKnd^P65gE(_&iBv3dpAO!RyQffd2D6rud7jEWZ`5lE=*q^)4J)HW_S|>AZ|~kl zCr!KZudr(+ZV+o02cC3sHIeyW3xlk!6*$P!u|FtG2e)Q?9K*t!NoJks8lEYUHzSOo z99AOCI2SZJ`rov@dy7YONZYfAND{ycWsU&!G&p18f?aQe=FEA1&gfy&=1i?+8zmZ! z-H56i@0W6#R^<69U6P6-H@F*z+p<|-t+{yQc*(UR8OdFh?;tK^MQ*Gb3}6|@tCw;R ztJ5@^j<`RBH1Nier(9x{gsp9fzZ1aCQIZTw_C&n6#^k1sa;PJ7EZ3byv%9`c|F!$O zc&TmN<(_)RHM2>+Zp)$7T`vA?Dckh<^9ix5MTAJ3n`esT69LtH2{=UxPGvqhaxBFG z#)Ux)o=$P})>BvJs=0*qgD$TGC7=3{_k=(hU2*Ek$F& zmR`8($0!pvh7krFAd=XaJ+d-y9t#R-6cDWv zA=09U2e2MZb<5mYn|JFM@UF>n9gbOn$N#c@(&ep~PinA(bZa_{?u zb)Yk1{pN9FW!t#5sk7fN)K@$;6Zhorb~*_~5}rU=K@}w9(qL0X*2le3aJVxe)I3w+ zJmjC}{UYAZL;*+V8f~Nd5}H_Y-GDKvG=_1zNTfTTvXWOR`EKCf60pj8UAtj}b4Jl0 zT4(rke{ce&{Tkv+#$+WF=-A`atY|qXP{4Guu)re;;}ep9r$A7t+jtAy6i_{D*oAC) z+eMqVY}s-Q0LyLL7TQM|nn0ts(8Rkgjnz{Z{SueB4Q-z&cKP6C;1%dqg=yZEs6W?j zYu6&rc$3vspuCf=g9o=GMjPeCnm)#-)COLwN=befoKui#b>)qB`lOTx^}bf7yZ+WI zlK3dP5!#|#^!t*Vg@~H;06p||`~%c)Zqxqlax-f-uU0>B!mm-%7}RK#z-ve?ym(j(AQ_HtK1-HY$i+Zj;%bhkFSvh2nMRGHsPmmtR&0M9PHWy2 z(C)*Qb#sk$Fir}joZ+Z0;*t{yHKs%$Mm*pt{W6xgenwsmFf^P~IwCy$1tv=ozmmJU2O@0M?GGtbAkTg;HJ zx)V~qRegAOwqM4L^`ACGEMMLtrt)SRqGV`bWsC)@mJTPkN#JNOLlz?0GLfu2bGObd zTVCWsl&~)Zh-r~y=OAcjY15)qy7}&?LUa&@HVAf-O`Tq->`e#2G-r$DS-*)+xUqex zBSZ*^p2JMEzVh{ST8(y_o`Uz7Wg{I07Z%J*TwNPIR)DKq<06$YxTGqH7nEH{oy1&) zqRQ#Br%x|J+~_cCfQ;+pFcTjEOsTvs&C5AnwSXg1<6ej@;57nWt$eyT z++HsgtyJKeOzMsB0)O!FCQKB?1w&oyHpe7g| zPgis4j!#RnSMScTbNu&wPC;n2>ZW_|s#<-lpKHw~v1kr|OT#gor$_FJWSvQd0N24C z>NkS&Eo1T+&KJX4+Oy4(40h(fC)j%W|ztF|R#Ock>W-VHD?b2mf zxSq_$41a~{MLbF;PMlDi4eb`dJa!T#F#sLtGcX8DqWVhb5J`*qci}e)UBj%VQK#;4>^tugr8t3s9mX1pBTG)O7a?X?8`6o8Q zjKk?^y@_`7BsQbTfG{e|?swxVo{V@BqfLed|MTVh_fcRZfDjkhM*Mg~9T7{;D28MTyLVr$p)Qe}H_U%D{PdHhBJvq0+ZFDKHs5;y7qB&nqc{kpg z+GH}f3%f#cC#)ToA%-m&P&Q(++W_&|v!9=9 z3$7(s1eZsdPXa#88OU_BH#21LW}C+%&uj1Xc)g$CO%nYNku> z3d?Pz9IWqq2S~3>6&;vO3cnd`7ngs8Nja|us z#OW`CFu~AeCNR-n5NX|MPs_QNBqkDAzwqA9lueru(`?|9=cH|A&J?Dp$U=Zr4i%oM zD6#3jJUAFX$2_e(|IF>}9%*G`BI|*rC@8DnaAhnCQFh76$wugsI2YdR$ zY>r6Dozf}hm$N zRHpasclxI-cO18TMVCZYn9x@IEn=8%a#uK{HH}YBYacK;yxU8!>gXTCt@Ns@w*9O+ z{QXRy(Tfe9^*@{Z`&WH3{A7I#@FJA&?@sMrJKit5%4=HSmRubpuUS+la0nPHF);ZAd;O z{f^D=PZt33RncW6XWgFk^u84T{zpbrT2R3v$KSw_#7#Grd2|;Uy-_ydIT{gLG&^i* zlpOm1`ZFddh3YkntV{|ndcde#6J6ZkJyZ#x2FNHk4?%azoepNQ`hWVY%-{#zd-Q1D zxN&0|PKj{Id@!H|cNFC_651OS(xNmK${B5scLo1j25YLdycyMDAa^LniUqhk32J+D z|4@76C)O#e@RSo)!r`b1(F}^Nw|Guav-VtY1o&&TzusfS-9U7Nv`9|T=ju%OL0Jgv zVA`?SxBfBL&(C$InU`N7ny5#QU@$&myD)j!IkLc?WWuY|II`C$E&?-V|3|pH3HAhU zi55!cj8j(2j3$xq*nh8RB|0m9y7F^xkk608VdUh$`(>~3L0j!~e z#xJ4(;LQgLJ2MtLH@X%gQx`>?T*%#e{P^)UTy2n~fz5gbbu3|-2=xy}q0{jhWhdt& z6kNjDD_>*17U%G?c&du8+GuJ0Q?~asgsT|tS@GP~Rq09%``~=xF6Y;YZCj7bS?E%R zgZl(HoE;?TbTqhP=V@RbTzes{MRF78=I|n6#>F1fd`|S9bo|P#eGa>K1oo((Y1n!| zedl#F540*GNaG-ruAUQ5hz%;8$;F9A76EPFym}RS`0%HC#S}%{Qo85^EVjAO{%i+z zY3*pp+O!7{mB0gOh6o#nwdPz9QXc-X(9VEK3dA=ht7VKkzqCJ;^K1SbPBC@NP+*^L znKOZ|6IEC*uw?(`*61%5b9q-F3Ay08qNZCWB|&s`ht7ixOR?_Jrjk(|ivP7z3O^1yb%t-i8E)8o3`y(XsCklt;FdN=A+v2RjFNf*p^7JET3<`rtab(XYYMNjU9+JrIgap4 zvuzxwOfg_(PvY1*KJ!5|9p*7O&fv11+mY$P9A8H@SrR^l@`>Fl@qa*Z|#Q zNH|Js8oY6x65-U05?IOcMlWHVGK^~tvZV_!gIJhD3ts(v(0#xF&%-bEX>>{ET*W|M zRv&`KR)u0tC4Sr-rw7mJ$gK~Fd-ob}y6)v~%cIEe4S)`Si3-Mvteac+?v>-ODfIHK zT`W^9BpDw9A3YYvke4)`7RO7?{#-ROs(LQb3NbC}XZUrqa1_k=J&iLMW-{k<@yT~C$O5R1z7U(|a_edUkT zmttLn;~YF9uM$hX%bZEjW}-T2w3uvgQt;4;%Mv7iqKNN22y_QjEsYlkkisH-uY2bf zy|GLl=i3Sfgs-od96gl|=ZO6nr>(r&Cw)BxruDO)G^k^kG71r(V087sz#$9YC3dhv z!7P)w;8V2TT#N5&u(j)eX4$u&2$ly>0aC~IY8_z7p?B;4eXYT!^?$$K^mpuwJV;{b z=?$kefTloL{<7h+>ra6r>Qg14TZ9X{2)8eY$#!`o9Tu z_B=>%mkm$Pcg9f2(csDu3SN-X?=!>ZxKmW##;MkV=|4O|B%%tSmw@1__KkwWinGrL zi1236BN8d2qazpc0;&J)_bomISIH;CXQ%wdjE<$|xo!U$cO~3as(r40>Y2#(dAPD@ z3OZ4)8l(ph^0AISIF|%ciCd)Z7qpJnEjC_v?)T&eI?wPiNGcQdU>DM*bhlC>7XJ*! zettF15Uv7x2EV3s_*7zkQ>RLT>~v)A+zhZTn_)~<7Ot;%ubnu-VThSo2W}S*k)NZl z^#B4Cs1pOd#Y@Bbxx3BEYb_Lk5OMhM{q{oEzzM6+I;}Eu-a6=Wx|!vFUJBt@?r(md z+YHc$b(=J%)81Z*doDBoI+P|`!Bw{lb*_&5h)+_x#g%)EqHFAHXM}d|3sV{ zz7=uE{7+9!kzragiR(%moC|(W{ zOH@gJGLWPtKB17QoQA5EvFYub%;Rw77}RUMEr-LCdIhb({|%GKiT+4wO|rBzuMRku zQ^oSv4NOQJO~+6p5@xy*@d(f?b(_qCB~dqpA45;j-Su_HvH=aadDfFLNI4`i?Ekr1 zKiGz7P&r>BxnAxtHVa3)G}I`Qj?a1&51?CipwUQzI#7wTKr;a`f`5+dBv=|1xI73B zeJKE0=U^X#R`PdBft;|q@{4vo&H!g|H z6quDP0KAk<=>LP?W6_c#azD!!HXX!GEp9#05e))Y}S>M^E)2_drEoqhTQC_6h!^|V2jW|NDqL`9; zhBmJD?VoSNxH>z342gD95QQ@6sal5)e@FXHp$=liX*|V|=9z1pAWEfkSAv+OQd8WW zHF@gP1)O3cfZ(kVpP0O*W)2Zbr0_5?Bp;c~BTBIxuraGuTqAc#+Xh_b)l34X4*vTq zjuqGk#fwb#f@s7LtEKW>ReV1FnWycQlQ_4Ld*PR`!0%;U-6SFd947is&%1=GuZ%$(SfK z{}{!jF@@Qq)scT4deRD66`NRQ0b^+lN9c@XJZ$d-tW?sDuo^|LCsPEdLkrW6>8nTh ztQ89yx}ouNh6EW^(Z6WT(8=~MP{HsQgARF%C&D|o%!&=XV1UQ%YIK|vSlm;zK-r3 z2D?&|DTdxh(Zg&20>AAX9iu=U%|q(eGggISO-8R!6oN&J5L_NshFVMX;VeMSHjkJ( zqYe0vOtJMiul59MvK~0_E?>Gdtce4~!p{Bsi(w#dmy{U0FE~l9K*`?U*K;2x0>1c{ z^j5{ZWP--J7n%biFiFwSr}5&&KmDJrb5Oyc$NKdcY2Xb0q^bzxDgk@?fYJoP8 z+K7N&v0 z05(>y-cYra@~>a%yD=r1)idsEinjX1WdNjmGvQ_;SP* zN(w1l8UWm17j8R~olPMgb>P5E^ZqO6zN8WczTl|n)~jUeVrTHM#F+d)H8nCE3Ln3a zHHbrmsQLYUCP!Y_lznos_pmHoe18H8Oj>R-3=Qv&-8lT#1cRi{&udl95AVufo2IQE zWr@V9QCyn5^~{jWxEj?Nj#k+6RipOdWo|T0H*`Jn(2{` zC=!EKS^Y;#dyvU+6fXkt;N4lQ?OBbs%jHFPQO#Z2h(BXo5(11+Bo{CPzExIWwPMPFh zP|OmHxMbHX#M*U#zmAea5p>_>^)JYvm#6sEbe25?q7Z5veNwP-mrlh1sQ;x5#Z~}q zly#A6+5KUJYo|Tz@g@EhH4yTaILs};LOr{h)zzAkFkOH2y&I)ILE53ehnq&)1+Dp# z+Z2dc)*i*A%GmKD)ugElwW}`OK%0x;^oxa~fzBzHp==Fm6!o-Tj-lMZ94r^DmCNb8 z6cxZ!r^~5N?X0?fp75<8B3r}3i$6K>e1Ln%7gYi7#|&=|_rj@R-0KW+O`Cfz^;84GkPu(iZJ_IC&J_rA znS#!(+%wjRA!VwKDk!HNw}#es0@IV$4=Cj*MGudZK@T@86L4$^a7`s9=6!j|J!Zt& zMI#x$!2Wu4E~qb%1xk{a@3*{v@(0!$LcxK}$`lP_`m@($qkuPfg)iw&*bWPQ(WWCL{USqLV4A5Mo&#UgTzHw~kZS4^jtF z3J1Z_c`>rQTEbgV9`TMK1RA(NTaP_82RLyyZQf)A6(UTaz5>qbC}V|YeKYDhE^oY@ zg?Z4G*h({_KbKpMn3t6hxld|$X8c|d7fo1R-%@dFLRN>>dTvIR2S73;z=w-!81OouwTR=26ZqMr4oWODi z@ZJL0c*-xsmP~b=wikC9&l^xcq43bU8wVEl=mwA{j23~;Hr!E^o0^V$0FGBY4DJHk z$YN=2db^w53PJzXsXLg{V^5hN@(CiSxG2b8+JHRW!t>!@h(RuH#7$Q%vT}1Vf2dH}x5T8GAr3v8dT2`;y}Xv3 zEO`+U=8lTdI>U;ZMlr9lyj(wd#iE4^ySvy7L7BoJ75`@r(EJpu6Y+<#GFtx{=fUhv zR+QBu2Wq8XhmnhZz(Pm+b8JQJQi-@*?9AyZo?X<+92!0hTCjP+BB9LbMM51?u$A0= z2neaH1Qo(yqjH=OrO8h-LmaE0_;|I7ED9^y)5pee-lQWfy0kuSH|%V?SjP{bbg&%F zWHy})_?#M zsMxAlR-_6qmOb>ktW0ll?bmh_xX)ye{MVKzp&E(I(KhRHXz}OBRSg<8XfVRY3Q>_i z&{D3$PBw+8uxX}?lI%3@U-N21Lc^o;%T7(S z+VUW6yxZHOKqJ;Or#nUp+J*SK&!5Nj^&$uAyat0AeVp*}$fBszXocxuiK=|O!?UrQ z8(IBS&A&!JHLhzfsy!k#MX``jw|8Z1lei|~o?0`auT zC}?U2;1n7kA*g9BHnJpQH*Wmr0%!=tofbbDfJ{d{LS_9w+lDSXc_F$Y^cExVu;YXx zNCC++p4S#UiO2chQMP`4Vyh&aFieg50+j`l%bMtZOZE3S#8|h{-1!9t!6)F{k@!(s zPU{C}00TfP)3{Kf?KmBG_;~Hi4OL#+$}9D2tLRp)hg;V+>^wH+P~pqn>m(tHdF>q; zafI%z6_FlvhmKry$Q&nezYE@5IN~<9Df0jLiCuqp-vyW=8cibj!YDE4!#-d1?AL;Y zB5E+XMz{_crZ#4VCOAwp-hY{SRAgix{U;4N*@5M?!mIy`K^Jc^wJ4jIkOUwW!wZQ*urQkBKg z&)7hpSf&nh#AYOujSTK9xgI(qPl8v>Q)n+-ll=@jGxoX|RQ&SRSSxQ& zPwy(wE&U1mwUvg34c_hlnN~#^O_l|^?Ch=UzWv;|GU!a2Me3fou4xJBNssBkL?2CM&BCFJCf=ti4V|N8f1CxE(7QonVh!uiFQPJqC#%Nmil@`W=v;;zOeo{k0cGrWuesIP&S~-+G}%Sm#rUk7m*nwZ|pt3M`n&eGgzOWY3i_! z=F}pb5_ukL4%pJw#RU^&68AJS+3PQDj7aPr0f(3EGKkbsU?#y#JeQe%r& z{8HV$h?}*aEPp^}oL-o}SBP1b%_p)Bs!)+pF$I~*hjAO(FU%9sNw8EI!akXHT=+;C z7NcSq5_FB+reHE*)f3oHLl0<)WraQB-^gyCle47 zmYF#}qVY{Gj4UKPm}tuGOX?f7h`@qm=%glk9=jHxZmAc#sM+t9hIImXAQ>>~n%^S( z`!2boXc#pPYN5(jZq|&CtOV{%QBNZ%qX7Zgnix$-2QB&xD6T;WZZfNw%sq~ZFC@}r z-1ZCSnZxLx>3!7K-P5xo*>{CV*GQ`sN4N+a5tTA5(LEz#ydT+MBwerKj1hGjy=2*n ztB8#lK8-}0(~o+C1pPIsZ8Xx}&I{~!ZF%(1_ov8Ax`njl;K74yLPOxYS?UC!w*rTi5d1=2 zk=#Qe^kQ}ix4K+lI3=aY3D_`de$V@yRpP{dSxR;j#Sh9U`P;xxuQ=EwBv)KRWF-n% zxQmhDqy@u71~#)%(izoe2(m7FFRgWE%BfY2H<3X?)Ydv~T{w=ouRTi7F78RKN;>E6 z{Kv~m0pGVu_d99QC14iV`Yk>kAMyH?n>N+hp1=#3$nU@-$z2bWhKtOm+Uh1KtZ|ac zr(vXwNwv@Up&V!nA|wf*ED#}5S=_LW3K{qB-nAj$gu)G2!yaIG3E_i;Ef{TlDhb%s z)iV4L)V2ImZvaZpcJ4z-iJi(3sI>P_t{s0zGF4C?U>=NR+#a7-kUf65vL$U|(DSKjXy`q(t&r$3 zj+pnCayEu9=^53ONxV)7yp*NQroeL;sKvPM|Kif+H^=3Zd?$Y?C{?AZElg$vY;_qQ3} zJbu=aO}P=NHnA0!KH5K2?cxvjkL3!NVI63f5MJsK;6MgA^;;g@V_V$(am+Y@wO!w) zcPM!(5@m>_g>)_}d^eLOy;kt0)eE_i99^pw6c^9A%v@2vsV}_2x?AT5!)j=sGI|Aq z1`g2}e4n}nHGxy+kBy|9*o_}Axh%&(RD!oX4CDE$h@`K-9~1~XE0$ZCTM2HxW`;Vs zfD$x_v;>Z&^_bRU+dvh_SPy2jqdL!C^}MvySKFX;82=`3fmM6@S&{3N^8xwJ$%+1n4)D%ojo@QZ4z%7*-#Uin`%PAE-DPvzSi#>KRGdz z**wiyu$S)NAKznDS8ZEdN#VHbB&uhhq!KNcNjTvb}P%)Vi7OGU+&?jJtg7(agI!ts+9 zUe|1-W-}|(#mPy-HviM%dnfJ>clB~@*eLd&hH34mRG5WSZ#foyJoBgd&yU}iZfM>& zy)yrMZT>>JTm%xtC=7TumAi{Ve?FJ_Z6l+eJzF4*VU6g%J7aC$`w8n8h!DihL!(_! zhf~K7lAqKX#5eEuZ4lG;lt4+T5%SO|iO~}z8ol#ktgZBS5cLw0%%3%0nEa#C`nI#L z7HhV#7-~+;{F!v}T}Y$)1^p9CeA-@&c^$N(OXT8~O8U)=+t0kSXW7Dc$9voC_IcF9 z8@ClzxR}Z@z{(-Z=3nvm^A$JSDRr$RkBReB$<4cdwiFovj~-bqyQ%lQaWOMgDb`fj3*KN2c#1V$uP<`A^u=Z6QtI2qc+UvsMTVPb zL)lD9Ctv?84e1K+PVu5>^@185iEFq}v?z#szB&QcDwvzZrlBr!c(e*$m(*32H~X~0 z;BA1quYnZFgd5l(E}gOKpN7mfeCO^M#m|CXtR3+^wRGqDdL!!;wQV;{Po)R!Ez>P} zaKC#KW$l%FPqwQ~A5gGwO3_kJuHhw1mdv9c2BZW|?}GZIW>4yikaqmTlS}rD@Xc3x zUD}j{b#+OifTeY1EdVJkbd%B8P$5L`BiEuL31&(^Dgd2Aad8%>}}cs$Rwj!gk95Lk7`lvjimF18R_wF9X{HgVL<@7(Mzmf1B+?)~qEiaMZ_Y%FaMH zf>p>K$;gPfzXL8y^VxWzqhMX9dCl+lxLsPS+8)iH**(~8WjFcbcNZ{-*)9MmyhF#11uOY%3q>Uc*>r$HZQ_i&8`|#)VYpT3q!dQ zz@ax19QDRS^mVkgEf4PUJuxH6?cGn5T0+p_54Nt48h1wF+>nDfK^7V5!?MB63aVk6ZlQ zPE9-%uiYf|k}XOKAv3@P_*gadTU?{*CMYetEx7%?{>Ve_6x0DG#~Y1PJ}|>_(U+-5 zMzzV>QZy&oJJUbR?feJMsfS2PmVL>FByohUaSx^j(K%D3#U>}OL!qs1b&X(bz%%GtI8FyZPEXFV7a2YPOHKUR<09YCtE+%7Es}+;q8xva+~)c%nveJ7Ro06HMlHgzB@)fb*LD zeL+Ofu?mvP@G2(j-Vi#Q!9-H~(qj83pM2%)p@GLap-TJ5 zisYcVt5|S z00MC7OI)s!6G?AaL2?Uo$dFw2f<>UG(^NVj;e7ZE1Vmy>`Tx#YwqgD>hi;!2Uwxde zWBsvt_PZh(5sw2-7|67Cc@$B68L=?Z_+LV+h4hdlR7ozTgcH*oinrUeJYct=4SPYQ z{YR|QeI*Xh83q;Q<>FMre97*aT&#-)Kc3|lb)|Y30M_R>x4Q^L&l$vXFqxP!rj16k zd1(K8?95!kp-7?W$PEA_oY!^gB_5=FIe|R7eC#~@!N-pup{>`tX-W12X|myYujQ}0 z%*_US-)0Hqn3CC#Tm|}*th-u1^;%^W6@8fN$?%69`|daDTgdDQ zdQl-Rxf>8Dkr`)Fos<4^p8KzJZ}wjLv9Ctlgjy>n_g!7R$x;hN2LY^ZTN^gR+)YLA}nL(3H#OEPk9yjDI zQWdxw9Z;~*jmZ75!#(~bS)-s-aapb*wclHdl7L@#SQrEVrwwPr6il}V!AJ+^b8`zD zhq(*CP0QpOj$?kX14Ragq)7m3cZo2kQWAmSyIQc0a(XEV%wEa=orGF;N^TiTofbfn zhY;P!WexfZ5C&#%3)@9E0+i#-!V^$W09&*Z01BeAp)r-Xa&(>?i6WuS?4a|;wS(89 ze-fu}F(0nfsQd8lv)5rc=9q-dhc4hPY~8laHm0V9P}w}~Ute!pOh?KE z9?j{G=bp)NGCM-VwA2MsYH-o5ii|Aonr>MNfCM8b(_0ZPF4$E$Q)XCCxvq=6o%aId zrK)+pXHyO-?nowuj+xf)3%4lK>=S5%7z#@oOqHM*_(pqYb*0$AO-CukCBcXk5d{-D zNN;xx{#PnQ1gi*iWZaCcxm{VHDYf(~gb(%ME=#5>m-EC-8AA(9Rr~JAx7^TrWrNRu zhijOo1WoRt-dZuXq9|x-e}zMjjShNeh7z0y5GC-JqsN81xdogXGVb0hc7&B$;q~j? zEkCGqSr&Hw=GCjM=01=79A~5Jy7Y+Xfx)b)x_76gg|T!=rg5k$-~Vo3p?QppgWk@m z(?SzYw4xDv^~0R7ej;CGl(uYzq9P-A13NWEMJw%|Jx3j%_h;E7kt<)NMqv=+Zc-Q! z%Y?hRQz8%Jg>y`cEg1z`J~y4~=+T$%+-Zf?4>^GEwDTJkXeb4Nr&U`^SuWuXX;t+7 z&U8r)pSfrI$UI8h&(r8g0I+3`OG^aS&wADjU|i0Ldy9u@HnkcH^-At2S0g+w#%S0oRWbH78I;Y*KWdZ z%4=fe8i24EssFP=K9O+UXh-yr?y>}zeNJ=GXtL3^a zjUygv{utw`r>xR-8O*D#x*4K=4uQzOIVQGmWsT7l6~s6UyY^!F#Ej%I8h5{6N6y$M zcJ8_JfT z3#d=wa>gZfBcda!M+hRa$2N103WANS4aHb0e^rc_oDOWyuIk==I^no@p>q9`+e|kp z>39FM=wvds@H%laG_)eSYhm%%McXzV78p$;KU{_m?dW)~jcK5s2r6;gpzqZomJ*#i z8aHHMT7&)p-XBJgdFK_sb~(ix5oLrZKsd6rz?GmA(oudM_~7nc85S=Hk%W2zKt-;& zp-J(I*>tP>LDs*YzxEJ)$ae^`h0^xI_7A(Cju3Y>cl5K`&)H(OSjn&6= z(grUoR*T(d^=y&S%*UdYKQi1 zbIAAtQT~cc50U_XnE$#QXc;6n1!(z>_vwc*7G~go>7T9AzLo=8K%1(;qsLWit%c~? zx^?R>f>nVM|C9|EWp@egQDH;hs(yt%H68$e*W8hrzka7Ao{BokH=E-p4ZjA5E$9^E!KP_Nc zV9>5+9@qg3%L9=?<&U*4oO@LChRCu(2W7|-_`)n=df0@?l+1b( zu@q%s{#O%-3`w6NlK=nGlLUe)C{XI$xiiO;sFgV0nRbxL5N+48XP9mmELgyEXVsz!U> z-R%btkZ!N#A7wUzBZwQ84X?nvBvASx(vrKxqVCsf#2RINOfMTBx*gYE$7pi*G@JPP zQQM2!7r*@`$`C&Ni>j)dY>9}Nm~^!FzkdC?#Z^GA2OjZOHvZyj<@UtrA&F7w@!%to zVz#D*7dVU)8H;oj#V3HiKh(Ok*Id0+ZuzjbiK&M&Gi%0IU_;a$Jb3Kip=3OWjR;qM z!Ctm>&Na%p{5hXFp*Ftr)(DeHTFXoHLI=#U(M>2Hvb14vqDS1G^gDg}wn|O?O!C%& z`I8_MRNf@lvC$CDyO~uY|CqmE!E1a%^!ZYclMPo0YIiS1x_w8NlTm3rHHF0j~o}H=2Rz3cFb90SQ^e@$Gt)19;?+nNG z*?+3f>w1iH+w9rU!{eU+?j^v^SPu8ys)8h=ljpME1{4w!Ke9AL6^{c)*SKBQpO^^u zAxFKyNpIf>^CTCCTWxcl)6QnxfG?L+VCd2#j!HKWvO^= zBqUAYyEW{E_=%aD>^!U3^#u|&8C^h8L2_yoh7h(1CCje#^eZrp62HJEQ>yS_^y~QX zGakP0BmeJEhyYbpcDnFrjzz3eYM0iqZb zEs3c|I@?Vm4=0>B>~Cjj1p_*pP2&Yh-keykZr^r&yVTLii9`l3jU5k4N_6Qt&_glm z#!Yt>ZL|zBr;3l8h$KhCjI@6LVI~<#XD-ZDL{2RWmTM3>>w0j|rAwFkKlb2E;6CHx zkV!uf_^wMgaoVz2I)RSo-;^67YqBcE5@neDDXt&>qIAJ>H_=D+m~bu}n-T$L|21Y0 zkM6o~Vff3#@h{T(-QC@>mS6l(G-Ju4)7MI@0vqbR+ibr#S8-eJXlvRUX11Sj zzdkNhyBb)TrVgE0S6yA}_3cQ^iE4RWlv-RU|1|Gl&q)i{D41qXhUUrQZ*?Q8CW)A&^qq$co;PQ*bYpVC30k*f( ztnv8F8SwKdX&?NDNTq$_&ki7aL*mw1-=Yg>> zp_D0rWvH@tQI+_Yk>4$O1@w$9;DWn6chtDi6=+m+gLwRC!U`6bF290VRa8kdV-l20 z*8sCb&{-M?41h{wJ_~+bxoD}kcZ!j`(^b6iVvc|wPAqPzXf=_V4w=XB5rM;FRTa(G zmp}R*{IN8+Xh6eNe@ohFMyT`&>U2|g?y42KNgKYjPv#7vQ>di%rA^V8d9E7SyAB7XjbU7%LN5-$;nq}r(`lIX&^jV5h1#E_&Y2+H8D{`o-cbKabtTe zt;;-1iCv*su*J6vJi%m{o&KY%ImiYL8A5;14mQAg&YT_+5{og0Gt<~~MdCkn=1$wq z+G24Oal66Dt%dYjznIlP^nDsDPTG>mKStyCxq>Kz^>Z5!m$q+C0V8|aT3wQ_k{UM! z9cb8u_R@l~JX!Ire~nxvKqjg7JYule z_cktS_mEla%E&09sS`DjWaac}*S=%N4V)O$bTTa2Nn$jh%$E*>L^$=J9U3cOSa?w$L!tz;jDIb?MwSyc*vpDU61{W>x#Xr|XMvrMlB5h~NX47ViR$!&&YOH>u5g=O_R zUAx+uobx?7Ys|$$zwF3fKRSGU8E!~(^C*O`*F=n zJr%+P-##hV)iFFzq>A1@ja(v2?xyANJ)VyLE0vVOX5p^T^$#narny7=yw%wa;og z#l4e(*z<*UqRirEmH{M^Yk{$h({i17pm|lqnibJcsV+2*yISsF=3zBu*|#?r*>2+g z5HT0^JBNfq+#}9m$%m&g!4qzP5`}-3+egxVFgRoGjiE9Kk9*NHNTFxK+|;-XD`B)o zIKTW|;GKG`5fZG4fGlDwqJ5$tC+RuOej0+>AO;N6hJfI%X3L2z4M-#R?-!}LbRTu= zo`OVApGXmKo6j;+4;s-4y9*^CVs@EIIZpQjLyK*K`YxFyoj(@K1Og?82Ts zbXrgszO9k*KfHBpI)nIASGiMdb7vMDr?E@rARZ5*qYr8!`1p zuMe-39{=5u{DTKI=J>RhfY(-PiV)(F8Pki-D`2|eIFyM6BCkJnYH`HPjr90D8*8W! z5fHN(re=Kf7KC}d_1VYxeZw;{-VW?jll0lQ^RD35DVHTem|f0`ySVQUDpje%#mB4eR12LMIt3Zl|tqJC;Q>#3_Zh~N_^WL;9-Gt zRPch(XCJIg@W1u^?(Ajf+xmNa9oDw<`h>#9%?_%Ca@>cl>wg4$4NRO<*<>HYDD`~*ej~%$A zJ>Bk=<6y}-5g8bD)qYOCQs_lK&_EahyiTq5?K4^0p5fpREr0-Y(yLRs^0E~x#Q2#e z81CtL!@iTX8e5B@7FqE#tUZ~VGgV#-Sad5uxuiTrck>o+1r<^e&{}uztRZw9&Q*gV zo34Vy6RIPiRCMXRba&hLkC!Z1Fom&+coN`FEIEfBWB7Zw`ab1kfdaDda@b>_{z{>% z@eV*fupf{^E&_)`8Y5m8icnSfWy!Qd#5qBNWSzh{74}djFp%W z(}LE=n&@v@g1N~RcYK1+LP@3tQ?rM<%&nTs*rgp5E1m|^1%4uz z!tiAO{>a9N^vM8eQgpIdlH0|*=n`L)`;F6;l9m>}XHO@ZK`*0$p|v63@w+ti&N}bW zw?AMWWJQsbh@()@N2Km_YJ|2l3QM{B=+cFFNu}FPYyf{%CqrMg@4qK-=Gn89%UQoa z4wjm4Pb0ztyweT*+K5aWE_9Nuhnj}#t{xK({(d#Bcl4A2EBpU?l_y9Y=4QFSy)mlb z9uTO*>9e+te^kw>l_*G{J$Jv=Uzn``SFp}cYfJETA<37PJh-L99F)Ulbmt2^T9HjC z{N?xTbNLrx%B*4#RI<4@UeLgi|blD6z~T%qgW-py-WL!K>kT-p3qhnoklUC?UQ&1Uhq<5SHk zPp;xUPZ$9Iv=?$LJ~F(<`jp?VIQ5j3?Z7~&jha@a{)KHp<-KE_l@xB68DuQGTN+q3 z;i#IE*Tuyj2I1dhO@xxR=gAZ49f5Bu*&2$Wt?D~7h%X0XKT<69Aa?=H`xxmhQGW-+g?H5mP^|G;tC8Dc zAJ6UncE`bMi+0!!?D_AS5h@9p9^TqNGGjAZ7t!6NJa!>$OQBEil5^{phu#k)sL9P9C)V6F+ABOXr9B}b;^0z`rE zi!v!CDp~|7hvngQU$~pRdgbcXb)5Gp^XG5IG)=Y!+`5%{b43>Y ztqcL_MSgxf_bE2(1a`70f|%;)C@E0SivI#HhLB+}$eI_@j9ddz+ZLS8PH`i(-KNf# zn{<>=sK7QhPm^(Rk%6NjX_3K?=7KD?R@Q#L(i(`y$w?vAEq#vl zSMRUhou8LpOGs~bFbM<*Gs1<77mI$IhHf1$CNE#V{+|228we_OGA0nrg4|Z9$m)ol z5w9wzVZAzJ+{71(bL%HGm@w&-sppOsVb|<*b$w(Kis-u$IQ>f&F=DeIPV{XU9|I&T z`}%t0{fgUVl9Rn*&O=vb~U4oT-detc(kqueSs<5UTB~odkeq59zj1l zy6jV$mdgK_vf?#H65t{a8#U@wgJdtqaZGbgSe4duCYV!4<#{kg0e+If3E*$s-Lq4# zG=V0t5^!z+#zBtz;P8oc*RxeWI?|`)zRktPXdCkx4`wM83Rh*9X42~cLx)Z}d8TEH z7Ip?(-QkJQbxHQ-jmpwC5ue4x$c`T7R?I^ou#9AY#O(s33W`{t^rGTwu&=4_fmzst zw3;;OiOq1)2ZNAnUMOZmIffBOwCsDffZQU~CJ^FjGiKxgGAPHYzCmac9o?l)&J6i= z!15~Jj3>YS=*Rx?@Cw3TO16_}C)9?2wp2}4FH?vg@<(aa_pG@a7aF-;&s1ylen;}b z?>|~v!o6W8BvzhKacFQ3>G8S7M&255bqL@bR?_UN`%b9DGO)DmAH z2Rdx(;Dlr;YJ*jwuPMyU%Ydkb=Q|M%#cI*tKXaySC5n1NX*1wvln+EH2>+3bQ@ghm z*d8V$)C&XBpV5FzC-yoPkFXuJP0>+#=FGyd!1*hzQwkGe*OhiS6)~?_c@l(?z_dCvBC@3|2MgvH_PHYo*UcTRR&B4kas9ejay=)# zL9b)kI9mn!ioX}>Bo~)0MuZ^*KQvO;Abq5>-!t8IIRkUC7H1PB6goeUA12}mS$nGu zvp3tE(rJw9LVie({>}_XR=OMQKhvZIE}r}bIe%z!0I)Mq5!(#@LqL~$k9)|13{R)F z3q*7VisUrim?{N+&vEdL4I7jr_nbR-4)gwawRdHrPQcVkt2>5|(`ajf$~O`~o-_W2 zE)PG+*Uzs@oHMK!8Z|A*Frr$7%^-TNgZ-OB5mPzKz)yga#xF2Kdg*-Qtm` zOI84C0Dc#lqxe^W%hbO5rcK=QLns;6W=p+|XnkM25MvqiKNAkj`^wxAvlIJ<5xZZC zJ_Etb=jv(^zmZm&ppInjBGrbyeHaZsd||N{psW6~?-_KXXx^mo9@u&}@ywDZ7kVzp zJ>XLG$LxaU?uj3hYuwk`s5E8)`z7$@3{1v3EMa#$7nb{z3G7kQvk`{bRuhn2iFb6z zb}g^BE}v#`mC1+fp}u7cyC$4_B*qxbbd{PnZ)0DhXsuGdR{a=9Dr)UA(y&sfTl)N^ z5G{DC%q8L}w!sD_Rjx7V+O-krG&HiVcbzMIod%vRiC?NZD^+`obK}A{2hDs(8ymG( z@9l~M-bJdrf%r5b-RC&5b%Mccm)^bqRV5=&RdByek?%8WR`)$8BC9_}cO6Dt(_>mj zkEKR)1ZbS|OwgOez|N>@A<0JrSz!D8+b8V;L;`WLgeWhrJ35~L)GD}D6z?1O@7(iz zetAfs#|kQY8o>c8stv*KljCe_TxZD;U(PUp2qjI^`7Pl=lD9CRbH_hs zSVNJshSmymp0JpK`Q7eNj?tehQg4HtM=|td%AJa(w3Lc`3bE1xXU``Dj4jI;-9k^j z?h}K`a#}q`>0P--ckha6GVB|N4r_CcO>n(@bW-Be*hWbQomsOsPEB+C+mJ*BatNGe z=@C(_#Z?d0kg+Kf0-0TLYdyF{bc2SSWD*O%AuZNnjA5g|X7loC{i9L`%kU0LLcQmu z*!sS8GnDjKPc*1_@hN#ob|?GEn|gRpJAM2@e16HHBbWR9{ww`p{K&xmREA`+s9s7? z+RDhdw#X3028aa8*B2%@SX}Byn_4e8hYNv{GRMX!=8oA)9K^E)n!WtJ_FA{Rvv&(2v`}&n7&uVmkj!FDP$d%peE!i=>F5t?;(TS@#sQzc$8Nt^W;(+>;9H?d zz~niFZ`6luqUGs;tr@cj6HL4)I#_oj9&~~Ae}3Q-Su{n~-Fh@V;9t)-po5@F5oDhPSx9Z&i& z6orJ)7yLx2$C#9NQBsgg@axwtn5H`3*P*CKQ4i3L^d9sJT8fR+=C4=kA#%wL5LRe< z(KxMyofeQSmn;E;H~}Gm0a(tpj_bd&q{ zM_ei@I&^KXwzZ1Di7+KPT%H{-^bDI&DbJ4^WiEa(V&52kW`FDd_JEpv>g>Xx{ z@iDulvWY)X9%FWkLpg#F(<$up>YjvS7*v7Y|HR;%e4J{T&+mk$0~Ut*&?_3Dk7)wf z>WQ^oty0xxUEwK|5dDi={999DW=AtH{1t%ZU>PVEE2UllzbgB4b}$?&26Y%#8#0S zO4Z5Bz56GHa4RDX?Y?3JUltHq)fyY3)OS5;D+n(1FsnmC8iMH9Fg-yKn+f;x;hlFQ zhVD*@pU^?i=;r&uW`kPXh<_(^5o$qbdQrb=@+VOWf;}X96pm48%=j64s~C{;$6Mi) zGjRiI6Js*5{-nNz8W^RwSU5*i!alnXybSuju>JQ}#X5cz;V`V`x^@ekK&&2rnVZ;&MR~g|+1~LlY8Fum6&F0?k1K)Dr zKKoxL>ctxX>4;tN+{UP_TRjUt_NhyIp7S&FLuJz~%@^3;-SkhJA@rw)-vWvAY$@HqgM%dO zjG&)fwHFYV$S1zT3_Ix6LC$T}H=1LM104dA9F0H-gCxBBQpS8`oKb-MN~N)|T&b#* zKMWW{tI~#f62)RvoH4jRF67;a;%BABC$f_q8HdVD=?aS9X`wcqk z{BB#>!hwO!yG)%A*;W*r%#{!svuXPZ>4hm<%$6-y`2Io`(YUx-C;U2$<*}TD@-0 zEUI&sST-OYvMXsDmtCk^@)}s}f*gGx&^G1-gyKdFgnRc_&q5y|Zc5M+;oLf1@DH2$ zdsgDfjt$Cpy*^>t_oUmS2d?(8Q!oa*O7X|Dx|K0)7?_us-;RB|W#`T!gkWNSO>G?3 z-x!J;7HD-I2L`Jv@}_)E$Aw%fFt0WH>0lTYg6N71TRZoWIn-icAtA3)$)srK^vJs4L?@1XDd{T2{3Fc?*{<5i1eVWKMI;HjDg*aUQff4 zp8`{hE+_K+iry_iw(@S@-bzs$=luSh9(8mkHqwEsR>|H%+Q8cHkLJ51TI?1`khe@) z7YvE6QMiq~El?1JV!N7f9}D7~VWQb!b4LtCQ0Uf*;?q(ai&%-SGaJq#NR~>vznWP2MtdIq>v1=DgR3)i<_?jQqoxS&B_y`TS z@{H0O0Oz%%9~JqZ zacfSn>%!!pV>6$7*hPqcAI&@91lLMxVJ>_-G=UW6YViwcoEV7;89~S;)Rqi-WWLWX zdO=DeHyE)&D4c-P_DqF-w{9nJeiK3^dYuFB9Q{laDg(^OQoWy+LLa{l1!3Uws(s6{ z`SR9meFL5^ffA59=LJoU&&KHx#xfsI9MtrDQc%E2n=wg_hFPxjN_KtiH+#Xy%ZgM! z*31d%QCb4F*1RwMk>_SN1^{OS^C7ALul82G7<=*9#Omg`xx1kyGr(=j&p~#wCN#rh zdDebmoh|Wi_(kEH3|$eB{I_4CtT62yTziQx0ck|!aw1U1!7R08B@Aog_rKtDOnRS5 z1@M_YSs(uL-N!o1kcquy5ua>TB5a!icm&&71yKtKg-B~?IHfsXP`9fM?GH-@q(@3E zW;Kfg_KR%{49#!AR~7$^7A;#sZF9tUt`N6q1i4<&3eeJDlwr*A<8Hr3 zG=EgQxqegNmb~9q<6dlB>9=~}hsYLt#+`Y2u|lPgT1VVbJ>re=q$uGSK<+gR`i?}2 ze7z12Kz7FE?%x(=iysiI9v@JBJ`%1I!a=AkJ+Spw0Mnszrr)U9_XtD!TEZH}b3&Tn zQ}f7Jj@?AG{p_7W(p3H7Q9L}Jw&~~A)cyuB-W#+2oQ{(4jtRiGskLB$UlXKw%G1j# z_+0XX8C4mr+W))_zRK4CDv{!JrHbZw#~)betkU=?%Dk61CZ%Vs3~%vsi%l~lBgZoT z#*G?vO4!lo_02BqACuNwo;;yb6pR$9;1h;pj_yhiaE}?YToONK4{7%=JweG2+D{T_+Ku~?+@mw--ZU&ZfDFZj_4J^pT7@mJSpT_z30r5qb*KlubCYjf0hL<>i?~& zvZz_{Yh7`kxy?8Qk%XGf7@6^HU}6-IJ;Qo&r^3vUsgVpO!8p>@H@0aUBI*K^HVQFz z%J)K!o!wpE*rLM|*&@oYP-8;kx6~IE6?sfg*u1N5xwXJouu3kLP1k{u4!dZjAX|Cp z{OZRRj$ONV=T_3f?lM$_)Y_FS?PV37VYe^q`uzMFg#k$>J0|Yc6cIZIP+#r9Y8@q+ zB+4M4X!d0#XfwwO_Th6ve9Dv`;coX8f+lY6!GXr7f^|JfkT78GPwLQ@5`3zkU+T$@ zasU`p{%`pX{~XQ|o@*Wm1@)UH6S_n)!jx}4W`L9>91@-E2RZQTB)-j_JzmG?@Yop- zjXP%g^tJwZKKzjTk;vL1?~2+K0uM$k*^Xz!cf_0{C!{9T&fycC02d z3d@5M66yYA-_k`eoIpO;)A;kWMH`1rsw{Vb6~DehdS=FFV#6z58?xg-%hCJ%GWY6! zO=Zgm6Iij2;c2iiVVg(iXTS{$v2bCm`=ub~9}yZXWR+8=A?*Ofw4%9)keJ=h3!igh`n2uw;aQtnsrBrc`K@}H=ehoy{TH1HdeuZKpyJ}zuvWyr zhBh!Z=oLihJt#$qSm-wzRVm(h^q) zc|c;p?iL3$7iy+-USroUyQpQ=lkCRrw9Lc)_EajFRq*;qC&FEF>Gi;8pBI0&d=dL~ zU^*tae215`$+wgBF0RoWT&Kww3~*4lQ~Ore$z7E z4RgX=S_Ar!sMh9+h%1UYM>0I*3QF}4nGcRNC*fyB^c6r^f8k z`3_TjvJ4V!zS}jV2B6tM$|no4=_Ihq>0Q?!$r8Ml)MYtMbAq(j+$|WKU-(0XO#LlB;zU5D%xVo}M zfW0q3Hb4_1SfIm#n<0Mi2dmb3Y0mE2z5ju+3VKPS>WcQOYosHu0blLeFWC!O;oZBM zz>nm-2O#T`~W%WK8lT{NKxzOlK!CKM$f8x7p!aM7x&_y-+yA9AM5WuQ~AUUx@j-chvf&|+uZOlrufmXQEInJtU( z6}oT~V9emOZo{+4@mfBsXpx8xIce>%`X=2W2@_-NiM?jfiHQ~p?6{=h6c!#**Zr{Hp;;62OWvtx>ej&vLf|L;;-iUlqq-L zQ?DmGIMCSZhvJJV%2}%3bf+=IQHN1;?aE^tcv*DoHlbj{jYh$H7pb~G|IciD z+^N|bLRh|i+q1em8ywhZ-k9lxi;GJi+J5ji>;;5b1rjdQyLLbF8sr&P_mVA$Eq2{+1JmQR+dEf)vKXHx3%Z;8tX0nUxiw#MYo zm6Sj@K4mx{5idplE?lK@x>K3ob(mX>)h>xUeys6tc3uGj=K_SLd)F7mZn3IMnl3mt zqiP5Pk$F|NhNcZ6hrm*6NV`YZ=0fGe7~Q51Lm$G~m*kFZ+St+uaSwrULn&{-r|fvc!s2A0B6A5WosikBkBaKr zrHi$C#$W%DlB9R1JnaL2o+@2vsu&j3p4)R!OLpxoc|Vr)l|#G6>_9X7Hu_fnKKnEo zpG8DRyGPuUz2@gCo~-Mz(KYKYy@M+I7su^7?*e^pIK=3EDaH+B3_HZ+M}$l-BU zaOMyrE+TYF*?sDTW#`VeHYnKa79AVC&Cx4){+>TA~!$VKrAVF zR@fFSkM>}_5vH$UlnAaPsls5`6M9kV|7^VfB;>7Vzo zul~IVI9rUgy`I1R1I2@eT1Yo^JF>unai*A*aI&ynWT4Ep9v&q|_1zaQ*KXgQuP%0C zvM>TAmN-5DuK={mYGi_t&p!6ys#&XG4JL9^3P6;Rq1cB&F8jUj*9800TH2b*W~YuD z-mBYs>#3T?%=-mvk9K{>J1yd%$U=L1!jy8~g(-Jat*3@QPnBiPI20S7ngD2gQfu7l z6DQh~Co+f}JNL>ri!>>WWXqD^V|=i&&V?}votI_SfYj-KM z8J${x?eVE|7IW&eUflk&(QR8pZ(D~-PrN|Hul+1L_+TH&k}+-)s89|FSCmH2(T-|Q zF05?3nr=ScIi_+E*#AYWjt+RF7Pf8EwSI?8nkjhNrtY*@m!euRZSzaW0(?t*Hf(Yh zsA9USE~WlwXTvpW9w!$UhHzo94@$s@K7IU7k=v;ZVE$-y*-!h3NYsAgqR zf^C%4Y#1*)P7oJjI+doMW>of~idH<}E7z`VfF>7zKcW*FW5OQG z#V|q{E*hcxZpN%v6*{JFVv_Pww^fYB|AQrKrnGR zP-KQ;27yZn0thCV4XLU20z->&~Gi+Xx9R7bXdP`SrVrg$)_Uh%Wf?8#K0;*UxhWdCD# z^}Y@x&srD^9hl~|&m%?Gdc>r#wgcm}hAvd14%ee_0=)R25VT)Ejr`MJyh^ja;WGti z^OVcIe33YKXV-OWW}S_7J11q^ARmqYRtrg!$z7pm6@@c}f%4*@UnOYF zi<-1YM+uFbbF7{zWLIfp;eK5+_l8J71|yaKev25jy|VUc=y&p3X#tuCL?Xi2L+&k6 zZCd3SiXp-!Jh;h|610Hn)1k(SkQSuurEMwxJ@mK#EdA8$MrUp9B3>T$=`Hy{yOpijOZr-;Abu{h;OkTt-7XlYC&6-x=(xpojQjx9t$pD9W z^5I#Bal?VCEKv)0ssEV~y3K8TjW-I)!z0IDGs(kMZ4ej7`VB!;bGh zyb*i_dtfR1X4mrix}l=|z!!|hT;H;)bp~TB%rqhY<=~{ht!MoMd$FKmg3D(pK~Biw>oRgFhzm?p<#`HFT73UopkROAdz)scj);f} zwUDxFSwzbBei5}L1I4s}Npu@hdPv86yOy$#uBrrxmtphv!At)Nne{ѻu#79>k z7FqVXva^N8(vOcXVS|c+Mb}`fn%YilY+kQQ2zxZN;h*u|)5kq?GYEWF)vIe=vv$cb z0!tG{x6xI~GThW8U8H1H2s7KHyZ$ z2tY)5K%|lS>pDk8LsR%*>5*15P_j0<9My;z!Z4L^%H#`y*YgM{QudPEBB%y9ADm&5 zxGRTHoS9&W$v_k5BK3b-fl$#8Sdjr`n=n|Fd?<-QT!n>$kbh)c9jTfO)Yyhh?wY?nlfI|~^bHv6`)eI!Z?UqYnE;Yw zODcc`&T9Io%LOPG1P+TzcBpE(pF*+=E-Nne@kOYzbqx*I6D=ce4B)rz<8(nvXOEK; zO%@{yLyy^IXi$;y1Hx*`=z!)0!a;7`XgsPUu|V29fkgof*v+R-^%I!|L@;Ny37y3Z zl$}TM@EuKja+GMDrT%58o0FH<6lgp3SrUH)Htlok!P-HSt}lC+X#4rqvNBUYk8yjG zEt-7u`ZD0mChI{vWrGL7w+9QVsG%}y%4`L(MPdF?a+6pr z;{eHq`vX=}f=3b4FB_^Bp88ApD|t_zT)6lhXe|;p)p4?~>76VD6ik2`a!17(h2dAK z{}`j@OsrT-fZZzYkfUGMP$Z2c3Y)OI2nwuFj6n7b-z+1tY2H--081F;U@D?gZ~OTt z`c^(ZYbGuM@Ehb-_C2(}nZEImxKQDz?{Ex+JVwRb*2pOqxw@3-wAI0O8)}DJzqp%x zeA1fQCL1YD8K;U*Iklw~%qy1)*cFV7he_wLoT`G+yJ6-yriyJjXKLhZcD2&Kj)|^_ z#u=1vDz6{Rydl1)f$iUg22o$>Oejux$`}{FdiypK*owO_ zDrT5bE1K4diy@7ugeT8^JOEY-HSd^6-&O1BB9M1PGOYaBVB@AuSFc=I1IZ7^ExlF> z>c0b_^`T-K$#vJlX^Tt<7`PUcrtN{6ctD#a$BidbgD814ds~^Lo4zKp!%*8vF4s4b zRP1q`UAlBB-oiQSRIyISZ`s3EGxl-$?wFX%!n?uEhUZhkneH}pXh#r!w$0nk|0aH8 zdOMVd7u|YE(Ft~tvbyzesuf{B;(#^lz&FFK03H7cVz$>7%80BMBzbN_VAIsE7Kpjm%MTN`?5DRcL4cLzf*%|_s7`ljZn8&7k zP23IWc2(`(TBSDScH4vRPOegFQs3#$mU{ibuCa;h>ti?EWR@(h z5T~}Al(l&-jz@IGQ1}bcf=KB?@xPxs0T=6&rC~KlcPM;5^AKr8aI0y-;7s&vbRKnc zd?N~#!=lzBYJ_g}n_n=+;eo`*Y`3CRZG}Tx<@L3FKXz zy(yP+L>>u;U6L2)Vg@4`zmXxDO>or(V^w!pmSCj{X4ZtT<4nA3_@b`xkL#4hP0 zz3z=bQ6TnD{9L9cLPTZ6EMJ@JsrJr{MO6*#E_f)G^f;>e7itIqI&HpzhldAxdlQPl z>0q{r0VBfKuIX&-mdO)cu&yls{GzMlt$=2MTEi~h zzPEkHcK4CPHuiAR)&Ab=<=g9)XBNNHlraO369<9u6OS?(XYj~eA#Ua@BP9j7`!oey z5Fyi)9=L6}r1S3%Hg7(BkcH5q7a@8G(}dcX#{$(;_6&3K_U2!D%ebPFU`#FgN9~-) zbVMhzI~0Pw_UPW>qo(T=|32(j7@cI=t;I>BRnhZmG1k#eu5D3!+th~p2@}Gw=I%BP zjv2bJaC$8h5GM#G197_t>F;8@?k4Dw+Wh^UBcp%3xh;OavJC^KRo&hgyF_I;v}{>& z)T6aVVXv`jKl?3^`|02+%K$1G{h5#;eJ(8JOS&=xf`0gl>v+w zZbFVSFfd@VnN&KWQZh9)+LBq!$O`tKbMzSd86QCAt-Ke=*n>G->29ZJ` z3JS6=Wg0WgpXeaO$w104BD`+GU3wAwmm0@5?+n27o$M`3KWWni^JLf*;;$Z7d^U6@ z48vCWuBVI!-2k<4MzvwC1a2&pGM9Ea$~kCL0&&poy!h~8BgiyCuh-{`+xrc(S^JMO>ok+1K#Ep)YsLBAr%a&0HP zr9%th88EGol~kgl%71uUe2c8d}(KFQ8)pp~I||Md`!`IxTlH zFDGFZM>ON3gS~7mNcmV6UJ(dD0i%nm)P(6whOaK{U0$e6nMZcE%-ibuX_@wp4Uzkn zg?5cz?PZ{!ao$pM#J4xkvMm{*R-`2c8F>_&Fm4B$TEM?yy7}({C*RFk2Gq`i({mtt znkAn+eLC;@^&@TzSHhu{Qi<3nV-iYH@eCzf8|~HxB4Q`O(foIx=Ul;Nh~ml&&(qhN z>RP>eHf+`1s$SZUZm+Bg9)0&yaJ%~Ywb6B9Zk01wq8z-qT{6-BCY4KX8-p&-USram zOlpq>OU=OAj>j)BDv6CMN3Ct!VY~=@ks87h(T|KC!#p39&4i&I6(~G4)oewj zn{!W3LmWIymKz`qgD@t%NOaeDEVjL{zj@R_<^wGgq7{7{=@Znr-*`43AW2u#Siw z5jdVfDP@Lx0A?fv>F0T!gL{~S9_5w-J11bb4;&^7^%RwW_J(l7Db*qpJL2n4k)^T2 z6pKwH?$Pn_X{E_MwiYb#_fMfH4~v?z zJ`((#r^oRrN3QegCHm5kB#|ts-6w7cFnZqy;X`bXpMV~0b~|EN_UYZb zA_^ZwmQAXT&9U!$;>@P6jK-_r9&;Nf>by+dyH`3n7PR@$AMk>2K?R2?5(>a$Hsjjs z<3&RQ?i`GDH0WYE`@q4Jb=K28zn?v~ke1-?(MgBO%C=hWzQ_+`S=j)t3S9)Aba#W% zw5Q#lVH5NQgKO2)d<#36k8nqPau&NI3KgDEp^4ErpG0}zG;nk)vy4niQVaD8xn zV+`2Q31d7OmKfaW+PW2QOK)#Y89#dPxCo^z5MbVn>oqOm&0T1;6ZbIZe|D9 zyT<4lH8V|csa6cCGF@vps_V@X+hYe+H4Pm4_P;&DYU}Kov&x2PF}#eRLkA*`Oq0hX)l%hZ^&F5B4% z+iT&YfS$pvX-1jG@d7u7t=E`BfmuP$%)Q)q5w?O*35{QX@R<#|H>0A#eOueoGFw6Q zJe4jRo^sROYgE?~{QNoDKK)wYode-9`u-Lflk;pu%uW+%ykr7r1T)X*?N6V9$3Sj_ zNb4}`A0)MW3u60JM6)k1ek9$M(X$D=>E@tou)IZdP10r+!DzJ&_3fz){h-UZ>>3cw z_h?Y#tPEvWM0B}o`TwFwR7fFg==%A9&&Q}&np4hoJJ4d{%9f&f&5bx!cQrJ0JUI%n zh5<{qcMV;+jocG)8!E3v;s2DzDUPQYhB@}t$X>i~Nw_lIuy$pB^cm9K)$ zA~P*EHf~%Ny5UvvnB$*r{$=t~3po_vp;F71|2nbJxcjLss89R+{(%|CTo??*z8;Ic z?n7MzOyRm-1vHACeGqkoIMyf+O=CcC|MdLMK!rJ|N_qHg$fh(jhsMMo9{xM^3mpvt z2p`F`lI3}&%YNU&AZ02PV^oNn=mN|rooECvCEJF7#3E69*sMqPK$M zeLz1V@^bifGv)bsfM0LsZuTn3H>go$Wa!%ARz_`Z-gPUFzdL>V^a~-?OBFkX5|;q( zm{(n48Y>G;sk$q`uw^_>wcs>FlRvItwP1IzpjVU*V88qF2VJJPkof|wvee9sUO|Oe z2qt_%+*4K#b%Z7;?J=q@8Nd!*({NHjOk1LGrB zbZH4ir z=0uhYft*jH@#_MdH|ahwR+V`mIvD0SVuHoQTpaRTj%7ouk!~CX6y9L?JYUK;%w9Pu zdb;_4gmSc4l;5)8NDOkckIPJQX5Lx&o@~4ob#-y#=Bz9Wlzs0XoZ9?2t)E+TpwDF& z1@~Lsa*Di#)C7qF4e9H9-oZTsl77y&fx^Y4SzrYE`uO`f`^6(g1Pu(aAlt7WloqPf z$FERb*rM-i`N97alErrSlvBx|QN8KldUdgaL2^T3#@Fr)fb@@fpPZK;1B_g_O8#ZE@Qg}-L9_9&bpRi&nFcAZa#$}4nZJ9x`Ku6x^Pnv3H-WKPzJq* zQy@29YDUHuViXL`THJ6c@WmEd07uGYF~QB3^F7H2qwIUXya=Fokor{fcQ&5O(KWVc8L|} z7VkE*c_DyaWJ4-J##wKD3iQg%w?i8LLi;c1JngLWyrpS3lLMjCvmJ8^N6RY6x0F3K zM1LMdjzba^6a^=;p{d0D)RBHWckIXvtnp91@%fgWo24QoM}bU031i~o?17lY?t!Z@ zgV;_*_;PEfb^H~dhv)kU>5nji_K@q)gmOcdwiP5g%HOB6E@N>}Eq1@JC~4(sJpi*% z2d2XuASuHjJOB(^^Wp3>52U1sunbL!X7M-VYnLxymYR^ntKqjE+TRbD-$Sy&2Rj>|bP)T3YbLTOT~dtR8tOVW$a#>E8X411bB!aYWWou=x*n&1cZL z0rbp1bLI?(Pk@lfE4rPMU6Q?`dkfr*2sLLs>883pU$@Ig)3O0reh|vycu${rGxl z@rd9a4i-F1-8s!V!xPy6v4uoztlyL+) zU}Gufwu9NVw0!!9@_Td7s!n|S%_+b4$7e&cS{`vZDUB?T9Jd`+s^FmdKT9b~VIqj) zM5Nv{sCK$9Xa_vTgBxnnfJ&r8Ln7q?;b%EL7;{&xcI`?qz~)GanV0h8lYXY{WSGPK z)5X`JY142I`@_V5O&mWkWx)YSx>XS7Ay0VhU;l~ZoBK?C3gPm9WJFnYOHX}Z^pW;- zIjIDyRD+37rMnFp)ZW##*fhcr4nzjKwgCaYeExhfFE5;?QPhG+cI~2Pp$(w-SjLDR zsPpIh^fs8cWLaNp#+o9!@YS@-U)aCAZFxfH@tT@p z^m9;k^2K$R9SawwCx(|mT`$t}?*6ru?kb%-d;6Y{eRqNta4C2i(Ob5-B_$ZL!iV{8 zCyPKwN-<$ah3d%iX*SF-^O2}IzUq@oX5`2GUOjb7KbjWj?vc)BT3#zr&L8%=m95BE zPJ_Hm<50pYS4(T#xFNI)Dr8yThSYWUvP}5P@?exsCE6&`E%U?{5)g(x5uU12@7~9J-kIsE zHRG=D1-j8QFvvvIDUcP>N(xZJgWB!d$^U6LV8N7x`Ln4zx*8cp5`&pN*d3d}sz2~e zAT`(M7`yn|XWJrNECn*Dvow~5=$}XvPc=#_se1T=0&wdl6tdQf{Y2zfqN^=o z0$^Hd6mp^%Hi3Cl9?Sq&1fGf%7e1`Lg`cT$wj+C1_-E)M3&=0 zFJ_lt=j?yvaxJ*wI}W$yidD%)uCA{2FaL6Q=GLECfwv0p#Ft~}ZRa3wgJizy%Z_bS zi`2FW-VOe|I~KO2dRt?3>FVaro0hMhlmNvJ~QtMAAYCvrQ-Qw|FJwEly z{R=D20XG;vrrex1S{^>BRURX8~Uj)qnbxKzqVJKd=O?G!DWp;h$Zvv_##j0~^J+w+)9iT9{F zEN^~M^GSQSJ~Y3Ls(SW$^5lsaDl$m-DTvW`{^xYJk-MIgU&YKgKQ{eD2$%Dc z^)QQ408$j24DaMQUw3PvP$Fb^3zds3qEu`j{U5_T41y879-6?w^&y~F!` zAgMK<*Y^?2v!QSOKKwxz^-;be#cmDQjL8WV{m;Yu`$7H1`iLmyv*P!aMQMy=gy=!h zCB|9eEr<_yEwQ>(HUQ`2`}%=F}o6-EVmOFv1NM9?8~lZgh|6#-q~R ztYZiMa*Hv9|99cx_0Lhg9}ha#S7pob4+kyBG+I)UbW~qcQxj_^VDFAhn5hJtR6X$# zbc@h0Ob@=Uey?)_5}z`Z!WKn1xUzGdl7XxxmZCJ@g{3u*n7v~qF@hRC!NWp^YB;f` zEUgL0>MNIR<4hI=R3?f!e{+M$VM$FzliY+*1wnzsX!kOnww@!1*0nkBK^AQ@&RG8} zEiLT?RUHp|Y*t{6lebPPxIEWc8 z0A=szI$r8R+vH%xDU~x6&1EQovu;qtCKF{i3!QOyfnE)-+volSgWd`&H4#xn<9O?pqh4<7G=`CTp0Wzz<2=U{1YfK*dpZlZ};cEZfOjo7-L#@+qH|h$?`u zau89GwdkFOLposaV2*fI!8`V-@c=##>hMpUe5;EtL*ClfDuy!3fRLZ_kbkJ=>+v0bFiFxUJNRUKeBR{Nl$G} zMWX(VACy$w^a;MhsyT3MEt1}x{qgI~zg^aeFOtzWnWl%%R!pyYN52nT&!|(ZZ+UiB zlrIuILDSV2ml1q9Vju+#X{YH$>NTzT(7(&>15n43<@*H> z1k)6{<*e!fSV~e34_NvAaAn#MQ3kc{#Au=gEm=3_0z7*Y=3ENy<7fa}TsBl%{$UP4 zj#yo57|FCH;q2n)X3bLBY&tkKU%1)w{qLGDLG>A%Ntq(I9>Tt0T_6h<_E9PV%`UCTe!TPu?%w};op5olWGZA_SVKJbwmUQR1sY)0Gc)SFOw{P>Z_ zUO^5{Q1p8T$Q1vr?P&*D=*y53r%nMqOAAM7)q`OKa5#Hn_m*}q2ip^Ti-gELVc?EI z-wFzT+O?k1a7Xpe34f)L2Ox@fSM8PGIh`N9iIK641$OP;U2oF-#>*+wr+;_)ww3v! zL}`Z5$hopB``tosCN6O{HleqsoaX7sQVBX#(N2*gSPkMZVZu(L2uAB08F%rMr!zgs zb-3%D6T>H8v=fb+`El;H;*2U9yRB0tccJ_3oIMDoGphZ9rDJ~uw56iifqtN&KYpPKMouQ0cR7lVf9gg7I%%d$KeCb$D`T%`o z@7`${yWhY`+{^ddHDtLO>46Ht&c7NtB}{e(!?JQ!UIrX3Ob;v%1(YR%D!ift6DwnR ziS&-KKet%29~Q8}Ij0`_>MnSQJkrQUw?M6EdybYhJ8A{Pi1tmOH=6F?=-0Azm7)m1 z;KEOpM67Qi7F7V#NlDLhFCj?qoB`&A`bB5*Keb+SyJ0-uv$VV9S!9h2Ql(nWX~^(-k~ zNjL9vJB4fqT6>X^8*psgfa5)lakCenYLPJd?*NNB!6=x?l$gSRHj5$M;CEsMG-SD{ zIQB7*6f^)^-jaxS)1>l-%qq)|8Q3ac_cAOC&w61g6T4$;VW!i_l-T&KRX)^^;`ufI zR)0{3!1KH4zL{H@h_sgYV&P=^(w3oq#0@hb!(qD7u?Lp#KQnLRf4jAjI9B24L5n^T zFoI?}nU5;75wI$5d;KLyQ?jysk6 z+t$%*rrVYEt2&pqQ4YmaVcnT0SOP$O2YPbF2mwTww?rG=qtg#=dUsXV+~43>!pWtq zr~%HxV6}JjT(4u3J90)v-bu?5wW}AQm-y7E=2izpQnY{+N5ZIKAnL5}2J#$u^a<)z zoA`K&nnCSW1@5`AqhE92y!yPS6T8Yxj?$m%3ZdWjp=%A3q*Fb*YJqESS`2 z)ZA{vsdJAOZ|pa^S?)+Hy~e47r@#Kuv~|TR$Gsm<6n`pu_s{tyusmPyGBc|rbCt8PfnE7rhz=xDml%3rd4vP((S5riW4OIX~`L_sqfCI)nkQ zkf#J&;TB+mW_;4D_K}ibFT^(1s93QC$HKz^^a`d_E`%TqVYyU|e}oIgfxO6f2iw>utW>tqYof1VvTBC;wl-VOKH8~$s(Ak0^PmlY%8Wj| z)8Ew1Pu{oBE8XPJ>A+_N^hQ77|GKu_+JF~ChbDW4IJ!GNnF4Ca&J`&uaEP@DHz~tD zSRNicEgx=)=dzQ6IwnYQE)b#Sy)c*a+)4(vei;VXf{&fGke?jes zg}oY2(&^Q;RfJdQx|k;0nrz#UZWgM!uBTM0;+8i$fMo+L5t+rT#f}_YKC)IHWu>Z` zT8!C`K{~5p%7eIzZjJu4=fYu$Ea5gVaBy^GxBbYYH>8K89B9NOh3L$nts87v(uovH zgr{NRUUX|;#DcV6R1koCmF(8yX%{cG3?COYKwHcG<)3=Z=pH*aE-Kr*m_3<&ynD^8 zy2ix+>Nf;kp2YZiB2Y4%uvO$}*A-cnarXM|m3u5b{#JV*Z4P^v=3 zZLSoxN{;>6pMKr1~F46?f{}tcOG~>pe8I9+S^&0Z!0E zd=0qWwr}~>hY!bV87F8L$ckjJa85)bls|mPBY^Sw54IGsyPsO>8sae^M(y02(iZ)E+MTO_7s;#^Z{fHf2~TI!6l9(Mg|GBkTgSCbUf$Te$Og$@&}} zxpwsnkBl1NcfuIOf?qAXg8={=(lo;i#H?S`EzLJpsII1SqolV zc0IKF+Ga4bJ~&@eihSMG`>1#J4PGST5E-lyffkBg2{IEthR}zyDzqqL_zvWMmA6Mw zw>p94pLl<|8j%;XKt|suY~~*?`uWLS&Ss%T?AiIt63x_B^u6v zk|z@=h~I#3L=r#Jg@5u>0??Ux^@j_ z*wzbzv>UQp^Ccr2SuqLlH{q|}>KYnMK&H^eB6D>|ibY#HdWtRdAhxz1zUVdJB6pY3 z5v19&314@tTm=08Xh`(^iNBNn6Q7~JxB~P-&rxyU^sjo`oG#{SntTXoc?@eXc~zP< z2S3eZgP$vf=}e8q7M>k_K8$E`7Fohw?F=o_m3yA7=-9Z{J-v zR5x0wY15|SgGgs5^+M+KnlaJZM|v4963bQW`WBFCi_KmiZ_+!#f1Yx|xB`D0Q*YnZO4BD?o9=PNY5AVI zryI_bXmZtJc=r<68EVGF#;(oGG=+r8_FGfeuh)JcG02a&I?>%Q&e`3~&C1iWjiRC= zTwKiAH16taMj>EN5!KE1?QUT9)_pYF{^ye=tG|Uz({b?V^kPglUqhaOS}nDw2~2AO z_rT9ThG`})pZxyEmSEfN<#kUt{aO2B2u@tmr(?7mc%j|bSG1MbpJ4}O{9_r94rt)y zoO_$tyCFFSKzF$B_&r73V?jlfm6iQfZ{mEo01huge37&8v}}g%!I@lVNKu?|9%ogS zz0x2TogP;KOoWqYB2TRRLHxuzRANF(2Y9Oa{Gt&$x2Y7x#B7;mkeyjPc)HJ@@(J`k zEb;12Lxxk9EFHt|#QXWezY$<&?tdS=ky|C)ARJJ5w_Ty_Gt?s(k9j`FBB+*L*o-hb z4UL1WKHx0FTqT0R3~7|F8n9{8rm(x`%ZK5V2|IyBB$LxuMQz@k2iqDLq08mnMSMCy zhOJv31|mM;jTyiZ0r$K`dQdQ9*xrJInvE|`u)#=XX`DjC?%fx{spKyiEGsj}-Tx{p zXXjrXSLzmQ^M7Ba+GOJ!r*o6Ht9zUK+k*o#vPjuT1sY8N%r2QR49=OMMfo?C=MBQq|!1F0m~o6G=rw4suhKpN>5Ku)|XHgWN_?!RhJ1a#Y2|~57mV4+$+~uzYToO2Hu6_ z6Vvcd4QGxeSB{@LwH>TlJhWtEr}S3HzmTO}zF9YP;6Qnivc-_M^dNcjM$Mja8zEis zWYcL{Dot{%14Pe*= zt$u&o+D5{pLwy2T)Ustu*~#7TY~5LU6Gp;J>}{f=YAcF^R#jFp?n6{O_oUy=$Xoxj zI8=c&AU56PIQ5Zs`s(Y zBEMs9<6D~TO%`Dt6*YcJAKpE}ty6825Rvx>SQ_^erd?kbIjjBb%3!@6i-=JOE~2OyC>&^N z7a@VH{_80t6n6j?vAPHiRgN_D>UY*4aRhPp0jfs4aPO0lmf-LrvNsMPyG5<_f`r}8 z%rTYyHeA)PUz=G|ngi#AOm7iVio8pF2yekc0vx}|uIgthUYa{&1MkLp z19Sz%#AqQIuZ?@DvpY*9#30ZU?CmvdY#wdOxS%FxY6qC@w`kj06Co}vidMtTlB9eC zR8_wk;gInMmz*Ae-lr8IoS0u1s&vvNEco2iw>?$DJ7jOoY!T;q!&cv=EGusPv-K_0 zs<_K2ALK44l^h@-vU_+ds$JgMTYlRiRQj+K#iA6Hn#m}`EQ%}(PArsE9D2v>oL_sn zhjM^0;Rq)^VPH^wqpY6H-JvgO$EH?C65w^Oh6tCGdG97&HOOlHqCsg#!?8Z?O|)VM zX{=bbr|0vpL-zDG$2ey!ostucr10xydf@7s3zt@?ML-;!s<&ljS+J}4lWQXsZ1@$Z zbCrdf$C5kBZS}EZZ;Uy=wyLU%GHO{utCxjibR};^5Yv(e}YZDH(J~nMc-RK$FS_@nY zO0~z{3HZcnNQaSnfAb+liXTrnXHEIbyiR#~d~noT^9Q7;R8BQ%O}-cIOg) z#{s7>gjINyXa4@ob-*_$SFB%8Lp*`PT~KIl2wVBQSLIkwpWgRu#E5+kM!l2+>>#F7 zPcd`Ym)YcE@Vp83ZHlL+zkYhS$(gpQbB5cu+@QbV?Kf7>>OBiXX06`eVFXH7f0AIzT zE1~N1)S!~=b2$7K_K$dF;Q~ml(Hud_klbOV!%PS!$8CTAgRlYcQ^)S3NaIC7{_b{* zn3x#!jjNN7J^^e^MRx8#LswgS02^oMLHr^jx{{g~Qlq$qBmkla=bDBVnXn5@zkiw& z6~|uozyt8G{uGV1Y)j|QF~yn!dyOyM6Z{sEu%O^LI2cjq`r2+{eiHGS8Y-3M4lrJ! z(%1cykyn1lPX%|lPUSy;$|x<>8Ps2hZ!$mt-kNYvgid@gwW*zqs#5;xKCp4%r~>~x zQS(&N4=wzewM_W!|4qiZS|Cml4##0y?1jDX?R(k3+uP~pDqb}ek9l@Fj<*z=6rz&S zm-F>@XUURKtWh%Hs}qUK5uCa+GEh!oSBdlgsE_AOob*u5!UT9o@HPJA;1vd8W-t5A zIm8uJ{oVk7i%Y}GAIu9 zSvPdtBK3{(YB`p@N4jx9QsyM#N+|G>AAK#^If^C%jQQrlMVP--Fy9tN4c zE=FCrbg2Zb8XN!QR&iv$g-=z1yd$utW0YHi0M$0Tk&nvb+cEL>7RIPH0&-T7~!{(TjhV&4>R`6aW&lb!_#JPaRMHa@x zapLC8+HxWvGu0O_!kP5o2ffq!a|8F2#E~oBfIDq6QZ=f#Ju16*4SxRssXA$hh7_Kk zI-P{{>zuRp%QlY28jaM=CGLMPqOyO~WUG1;_-W-D<%TYE?vEPg9Gfb1O!Ej+tdZ$V$)ehEoPcH2USg?1Hj|bQk_(#&Z5eQhR}!brnUYRVU*8%u zp=~#Vd&uK+xR;`ZCYZ~1IZm{A(8+O>C9TXxY0mrQw;1ppH2b&Uo%jR=StOne zqm+fM#t!boG}6(O;k4D19(SFu&a-_nnW~E-7-KK-mkjxOI6Pec>EGW;U_4?eE|RzF zGj^@+m{&SXv(9GI%ZcuFHEVa^0}~V!w95>p9DUV5@{>x}t~rp>&z`$rQuV#5t?K!p zp1KWNC+Zpj0K54 zz&pd^$hznphzR=pa8RB^hES9%|L*N(zXqI4y&2|Lx&ER@AzJTSTogm{XL`!&GFdK! zRYc(DM$G8}`t{hIho4_A3jcL1Huh~%(H-hys-lChp51e;Hb}V2TN3vwa!+8=WtUog z8mOrzekX0WkEnidY4hyx{KXYEPpTS}&CSh)4@mMWhjY#)n8=`)#)QeNA7GIfp)gt= z$&wHfO$L$;B9;|KXtJG%++3`+M=Qi1sPF+K7yjUCiiiAsRl<*KX{3TD=?g8G$A--F zQsZNJjl=>(c#Z{0Pt%N0@)8+N&%M#Q$mC+hVD)W>-f!l;C$)u{mkRFTt5C?>W0zKU zY0IgG=_Ln~=cy0vPkwj9{*>N_1@(tv#>=vEfnhm#q@_jV54V>rgY%7yjC`9gQ;}jY z_UKWy(p^!fPZQTCCEf{OsL`v}q?L^y;%w^ETsy(Ges~|{07{bkDs>DRv~ZI!RPAML zYpdP2ujPmMoHG`4fq*{zS-?cw>z~ywj=nwP!sqrkGaouhF=%;n_Yav$+``FJ#|MTk zn-S1LV_Z(63~~gO;^U-wviGSoogZdn*D_r|GJRW(ODYJU9UesgE*f@_J-JoHT0#Hw zR#pOmzAG%WSzL5cQ))B%BuZ^rX_lW-;B94PmHAYBOn*}5DvaCz>M;OOjh zN45obTOuj|qA8&UVvwjA#jh220Eth;zijBW6=MgM4jWdR*=z~%MG_66oJ**9j zX$}HV?6c^!VqNkdj1Xtawr|SxqE98?`Z7Nd4pLbw!`R$3|6Z@}pD@vV|9s`f@OE!z zMHMWbMD^c~YXxSlHhOvzk{o%3CoAo#nqW}hVY&?Ffp=NcWikZ5W!in6!8!=p;@AfE z;IY!5G$*sG%EO~HRlFt$H(`!P7YM7n%&7dC#ooNvxcb*FbAnM zR~zHM{@eJqVNN0Y9~?HT%x-AUbPS+$FguLt;Cy$C1{ea>*nZ%E2Gk7wPpf)2W%OjW zv#TW?aXbnW-k1*hcoa5HD^^$%d_+};AQ4%}ZW=q;JVH^f5R;)t zBY9!IHHWFkx+()a=J(_QZgiBrW0(S(Hk};@k1q``9L8l_o6}38k`cUOR}Su*4BLj>*;Nz!t|Y zbBZ?B>KoZx-*Fm9fdI)TYx9m~Y?HBsMy2=%lDZO-i5#)e(8fjn`P^*mI>d;OI0;&8 z)vs~*@7eo$jQykh?qDnPfvuu6Lm!xbZZbqK;#cpsWL9TPT8zgobQH1~N+;EgCJQ)F zC_$sief&BSz_m?1oWXghCfPQA#iLSJX0eRq2{Dh@U(?+jN8};&D*akM2-Q*xVyQ+E zm7sW2a6!WsU!7qjQW#ll;ZaLVA)=0PQ*0tIYd@qieu;SGQNl*ULjX)`vS?AMR*x+O zF@Ta_1meCxic#(?S zyJhQ#pry+1_f0fj(@`t2<@4eFy1jEPT<BAtXU^J74h1Q&A(wMDNH>M zCxxjP+Q5S_E;NUy%$pQ!J9SP2O{oTD9i>Gxw}b)Li?brg5}b z)Ff^OTVMx^iK_rM+`w;Wxi~&(Q8cmZkU1*!^j z5u~_P7RXj2+W4-W_L#pPp|-f#GHCDqleQDL|M5B7Fu9-God(f5Tw8a>A*1Fe9GO*6 zU6re6dTwlDo#MGUVvL7Y%agUFF?nR7lfnK`%GLj^rq&Y21}KzteJsHHHomHiqBahO zp^&jiR}bjftFcc8TV)dpu))Q~1I7%@%AXv~~f7 z^{1&tS!uc6A8KbzE~!0SS@3P$YM&bcN2>B>4f$wSSw}#2B zUqc->*j$qbQ8_8YeZs9S2Aetn8;Q9A+!?Y$5vCUm9{f0sgm`|8 zBBeFwx{wP&y;ZO%zn)8!v?DzJJwQW@QbABe6al5_*ZAfIFnx<~f#j9VU$Nr840YoL z3WQ0eb`=qW3QsedY633nK*!Xkf=e-WlWkhGUCK{>^8{g&i-g#Bu?x^8w12=4Liz5m zMLK`ec)>bohVvy#M1ljgmT}G*GW&0sPy^hGGO==^o*;;dRL;8F5ib>RQt(h&;C9PT zAG`-z`Z-X;_os?>_y6Z(t<9y3@q_#pJkBPbQex=W{{HbbHNs~4bW^6&UpfzRPXCh( zH6tqbBiV%UTZ~(AXshS1!b_-y5I^1~SXo?8ku;80NqRH7$=!_J$Oh)uBfe&3X5M`M zT!YQL*4KtNlDkdMOv61gX~hqe^c-rYD{tSwPnCt8LqorFwWMc-eXxpLa!b2mf`4G3 zI4fMac1_AxK8qRm7gd8p!qd;J?62LYELj zU{7_XJNM4KcjLrUI%deTl;Sc01Tp=E-HA^r0#6}v_(+A&;N@~lz+>>Ht^-?D9C_=O zF$T`c0V0M_qr4#$WxyK|GgGP;-JwIL$3M(*opo?NRwC$=o<{866EGxurGV{Pu5PVHy@YPIr zx7Z|6)b#7A+r6i;FlL4O3zqf_!3q}%hVJFOfnm&d7D0}3OZK6y5evX?SMJr#9g34E z5P_P$-sAjy+M7O)6RR(?r*S*;V$i3MWu1S$85Td$)^qNXyH8{P%zvEbb}@qTi?S8! z(!{A#3G((|zP|EG^786rv?t4Lc@C6;@M8-0y1S)mqR;1PjMv@G#wM%fN(XW51q1Xs zc!@EGLT*BQylU^%8O&Iqnf!fd;YFT9>-&E({^(t0BC0WB{%t^BDS*)e=uK~$h|wrQ zv#gPtuUH;W#)TWWlgR`jL1%|9>@f*yP}W3qA>WvTWSDmUCc_WN0s~Qz(;Njbu;C## zbdP?4kd`UC_1j8vD0;BggTLTNw9B(sMrrIrm%%H$d5$mcIO;>EJ$ts->A84UsOO#7 z&_6Xa^;yk=Wr_28s0Ae0pVsa4!u3~lydx12M}TXuf*+A~#4eAymJpkF6>fY&Wd)WF zFF>1OkSPq9oCuwLY>(LWIm!p~el}#_!0HJrrh7K02JJON`~Ay-JO5MlfCuo$$Q>qUwAvKtEBqf>`XPHN zWa5Bof-<9TIgT9}JE3aJzeDfU%g(d&s5OK$Geu=(Z+6Z?f2W=u7r!VwCubq86`YK- zSb z2?#5ZLj;11pa2OI5osh9S6E!w?0UJfu7Gh8(Wxghuk$R+rBxCY4y1u`mX@bXrp@L+ zvVdw5g`w~eFl0+}>-ny_DdF18Na%5(B|WwWe;Y|LKch^q0cuDdKVGt<8uI2QfR{ppXPP93F)ry`*X`g z?f1_=uX?ew&-GrXgJXKBgr&4RXf|x|iN%FKGTTIr8{NHGNMq##J`4ARCnnxD8xrQ} zxj;;Jp-G$OEXA2>2URi9)?^qWyDG!e`k%%P;LW$5 zuu@7`-0wke*d;Omwhy#Qn)W|=+(wg8v5W62SRVf-d!{C-@hnnpkn-nfN0FW!;ea=5 zopRyA5c29)Y#_HxivaszGTMRe#pnBJG%p-)jQ>i1hc`U#nC-x0x4X1lgCh{8VqH+N z!e4UV|?J)7eN{x%+6H@ihpkuU%K_wQGfe^6#Wdbn0CWk1mZg zo@#Ecg?|80J@uHWo!$O#FSi}?pLhBh>?0ZIgiQ2-sD%nGmO@RhcW=BQ?5?iq#iQOg zx;fYxS5p1N%NMK!fb}V6E3~U1l)XdtEie**nO=Mvt4RoTa*~M?tVQ06ZKM^bENu__ z%M~YARjS+sD5p83!-R(CG`rAQ*ls2@Y8l$OGZXD&tB>h`eA||+?upaQ>yP}t?N0mrbchI z#%j0R08^){wx3h|ul6__zqov!x-+XMU}bfn=Wx6#F1D=uyoGx)2_S0)3;y&O(iak2 zC`ioqkMF%ZE8Z?KMw1hA(q2DkM>n0ZV-M4hw?9#NL9@Q*Q-9RBvTG1PQ$((e9ogwX zdl#az0Psv^_sCTp7cNYfj zwdqkV%W7s1n0g&79bq14EqZMvaBug_>_9Vw$aO0vcx83vB9z@=@D>$whCwSPt_<4v z;~%Z3zg-Kd5M`MPBmt&{m180iJ@c=>RaV|cXhWu?^fPB-#^Os+0D0_K3(-M-^gr+H z)jHKyJ9ip!J90#`%~0uO5oy3RKZ+mP0A8$uQjTk>RYrQcGRc;cE2>K}DvXkS8{9#P zfMN|0FNkPGJUx!xds1d0|B&@ZJM}w{7b3s zS8ZVayKhp+llS?#C1y$}t`TM)0brNeHC1uF)e*;jZ{EBSl3~H(kIZ{e@F|<`KV37X z^l-r|wzGK_%!E!Z&qCGGd0 zh}6P|ERoG1w6a3hiHnnFZT|pAaocqy)j$jp(l0~ZyF6EfVkZV9;qbbZK9ZOKvwTGN zZGL_dk;z}6Sxb}G1|?-Yqp74%VpYZ*zdtonMRZKNG0DP0P+HV*WQ$+l%Tz$NoWOG7 zT(rK_d6&D<==I+;;XK@a^TuFjHzxv%>;%LphVCkdE*JMKyMC%uq41EZjNi>U(=n<-yL zJJ1V)9Q<*U_zZqn!qiJNrLcrm?VbB62kalZOpS-(43NwM-1g7nwbg=}g&eh?63Opw zzumG`+g6U4xJVmBj*Fou8(~$n?j+|iUD7AcRnnV6;Y7fub|Osoa{a}#54TctGy28+ zUWc_I|5>FGt`Y#_b#--RL`5r7Y`^Zyz+SCse;u9j7*GivrK?dVblc1K@p~RbzW217 z9N6AOJFTco*(|dxy&$W-)0_x%0-iEK=ND`4&JwOPE3UbG+}P=FyLjL$)6LMch_@z7 z?O^3l$w9FvQ`s=^h@N}?Y=F9{5=#qcaF}!Sef)_akwZv&fIFN_)*yq@5^|NB6{LZc zp4(8hRJ3b!OVpsbgA0byi6c)X@cRDGd{KP%`1%!WqbXF3X%D?h&g>PMKfTWE_oFnWB7i`DzK zvR&4+H1$1B&Gcrr(Ji>y;G#%feTyZYY+4Wi3Z;|?2NQlaY*bcJ5i3QqewNMX@csMs zVjq#ATefSb-qiWDUEQ$5r{VOYCL{eItmwwTh#%1K=#o2*=70imdBt3Qaf8NL2N0oE z#)<@W%&Uv%3d(+L9N?p}^#MxMOQT6`%?qar5X2Z46 z(Zi&Q@Ga?MpdSdepZC>AoGjQcOuj{1)gzbE$<&>g{6 zk^f;|!JL)X=>IJt9r<4SMpQj0R0!}}+Jy;>ROnH~Up@8TgU|7Grk|0mI}Bc+&8f@i z6~7LuP~R8n$QKGhNyt}H9YXGxCAPr4vRs+MO}w25Q+JRbk%R}}2rC3UPPR1sWX*9* za}#U>d5l!ZGHW6aI4)Z@`=1xb0hkp#beM>0AC*VHwWCIj9oq%MK4DqBzzEX0=O=S9 znNPDl>$L6H@)J0)(bb52ifKBLLdd_e27@C=*Ah7WWBHAV9F;|62jB(h?Xy>D_cI8) zv*K`Gc8zzu)tRsc6F>c-e^2Xa)VpWh0gwsM7_?b~|0mBqK-I4>!^SY1mXjp}2dtXR za)`BF60v3j@&T$y+2DYIrO<#Vns_{r!cOIPd65L(5J6-p&AOyY3)>uC=6eJo!bFFY zPg!a^U$q~j35c7H^XLD~J44ctV4GfISn$r{QFJ@CwvIkvgrws?*MQ+n-;0 zVgE%=q8QavmdUCRCSIOP0v=FPAcb}zzRH}IdKFTjLeY>}mRMxcuGFu(QNkdGASGK& z#p8=*MBsWNAAxqJZthl-e=uOnjEmhi^iT9|dAIB1#VmxBM=cM=9wY zb-*{MS|Bso+1ad@YJ}s92>AOvTFXi)R^Vw4DY&t5!iEh~HW(umM5t-B9H7IOB40&a zedh7-QzQ*{RCLUOLwnv(7^!}ZclEBQNISUWCTzy(VVtR+sEcIMC+pk!e;Qbvk%UBP z0uJts%`T>fNJgpi9s)si#Xk+0lPyt8w`BAfIZ`9?{=rt)*R-1B(mr_diSm+9Gq2}H z2!lhoPrz$rwh`_nf6@X7!xZ`n?WjA}cP7E~h?%?|>*F?MVl3`&dT3fETxpa(PspVroAD_2q zHEFI{_Ko~4%hIq{8=z-$D~K7h(>7pCzq_lf&dh3wz->Nz{0M-wGxCN}t|vWgNghvH zb2U2JF=Y68KA9krWo7p7Kf}T)W>k+kWm8@e-M#%=)hKy0FeYZ4c5^BBU3W+!SntV3 zJ%7`9{eUGQ?{@BdsfF^9^ApE@81@w@0PS&@XCBX-KWRM%KaAO2NJ%ovC)UV9_9Pd8 z<4nQ5l(*H==ZmQa9}7l!4g~~vTen}oDSAy>w`-Si=T1{TD#IPwG6g0o<9jJlx+V|* zky2Fry5*giZWbHY9enk7_}=zGbI%4h{x>on;ha=3-+;)BVEkfU)=Xk9AYnYUZ@`!3 z)ad*cwT@ePF0w|5YrvXW3&n7%kDTGBYWh-Jm+%;PSz`aLs<)SJc)!8stEVrWOZ&u9Z78ce_dP1QVBnn@Z)Zvj zXb2&T87DHusD9^n;MLV}US18G`qwn{HPWCPfyjy>r1#?)|FgtR&(3a*hcjH4Y!GoQ zKz$Ya_G&}ui=n~o(5Vy6bZ?W5t$Pq_zcMNbpJdtABL!?j82pG&6}h-EQIQ zTNlQvzMHfEcb$y+AQCBW8f@Wyo4N@4s3TA?0yoy~d2^P&g*P%xPeXHli^BqtD494hWU?_S*1l?7Eqyf9bG#j7z{RvxpEX=^r*v+~L?@iE_U z+g@vkMag5m=3#fN)rLQ>Gk<>Qk69g|P(fi>j_RFxe4i`4pJ6 zH}@`oIjM=bxa{?{;Z$OR(XNfoNGo3R{O*E5?8fNx)YlV|m`H@kr_Hv0OO>?)e03rI zrkaX%j&$MF{dXVlVta=>QW8jU9av{gblW?+`r4H%|1D0jV*v^GUbc(uKRe*XubOE? zM|D(H9T$3e#uQ!U?x9(kRx?U~Ebjf@+@EJ7;4c~CEE~gw1}4_1)K4fS`#9LSJ=#3( zgYwVs-w{k6mXpo7|JvtkC>AAu!$jwkRvY|0(aZ&1l#HaRt6ObfL@98aW5z1pF(Ih{ ziZFX1-LFk}beqPG`|Qr!mxWABge=02uAu>?F9w&GynZ=LBIqM(w>?bZ*9-dts0+@7 z5UR>QJfV-19dt=s1Ug{tVOM^IwQHx^f;)!*Kf;z?h-7gmvB~?{z3qWn3kH#Ur~<`w z55@ao&@DDXTQBgi6wwpYl{=hpgr~xz1_EqGM-btwlecJDuZ+s<*!+i?3!aWxMinO5 z9HYa&udkZRSBCa4t5cz_B?5tpe+g#;h{W3tVG=AxA*1n6_)2k*{MeHrf_4_B1g^N( zm2gj}m+|Z_m0%fY$eid=z5EzlP4W z&3)U@K=Tfhw9`J$3k!AcSM~5o%-WL~(^*upx6bBZ6|LDBx=gmT9=a!a~ z=;FdvSh#hfcId%+_@K9Mi@N|pM?@@cxpm8p4upgl0hJM{=$_Q5_Wb;sqvHd8lvlRc z_6zx=v%#kQR{NaXeL{$B&*E3UUmnPi>sG)bvgAK1ayoil2HGaVpIP&w)mmHGrz$ zVGWLNMaRs6Weu0?GxPG!PTUekkf*DWzKFj}rhiI3ocE{p!-sP>xU8{Ex%s%=)>U*eV!7G9G>2nFJ!Y9|Sy?F$Uh3gKWUYl~ zp_ShlmrF)2wY?cH2*Bc2))sCY&jo*(QW6?PuBLK8{G4mUc-)}!MdiEi?tFD&CU>~{ zS9uR6Vcxe^6VRBX$Y7Jt%vNRHHPNL<^V}bO;8quMi+Ns_{>q>a%1BI+B31gElVdo0 zt5>a}dOtu@cpmWk#ibQ81A*bC2{IRq5%a;}#x?Iv6H5*Jvy{SYY^+DRR}VUT{kk;0 zqP0bOLIZ{zV}|~~UXb1gFKP?vJ+pB8Naj>@pgC08=AQ>I#-@rVCObgrn@+3znDAvC z3Ecx9dsN44Q3?gkWPl*Eio>JUrapOc>Dhx&zyimvNtZ9L3&u`t_4cPZ$-A(`Mt0MK?OcH)xn=E^ByJqSx`?l?R+A>lDwD#p zvg+}>ZQ)HpG!=6n;6e3k0Y|S$yUxE?|1hT$<^-{iVCqdYG4XL2^%`YXzr%BZro;B^ zp%j$WgWbPZ&K$M8rqiTex>t*|8ZZ6XVP5S1d)P`18f2{)#Ceio1dW7|UdfIP`FVMY z^~k6qxFlQ`Zz_wkDU9$1;)fx7z444R0dthPiEe7)TSt$^acvwgI@wW5gtVnpZ3uh0+N{A7`t0RG9v*{{R!Puh*S`Qe2p{qjr4v;e*^6AHQSXeby#V(BIQK znd;6!XYgQAP_t=Dn9Ed_z1J@IhfBJC{ra=;4K{r~+`0#H1TsN6b);Ev2P2656)pFK znmBgp+?i-IBcgmG1Uj8DV``7BUF>z24ptl=nVHx}4{rmgD!pEw>OZ*np(N9rzDC_G z-3~8qCWZ#AdafA1u&kLN+@KGP67(K?Vl<4?l<}ys$i+})yz^kZ_E0~+@YU09Kf9i` zp5kjcXAQe`)bBWfpZ}YICWEN}bfWU~2b}3GRBdh{+p)#uAl2tct@M3-HQ`Oexq6F4 zg(Des<1qJxaq-N4LA$$QlOYNktRAAMT^J9GbsCMfxTtz~UPJvXUVMP7;Cr|DuLYI- zW2Rxn&jXq!PDqKA!Y~l>G-$0LsoWGzR2CT1(~os9^c;f}`qsUBGUx)Q zH{~^mhr9^M06O8E2$+Sp!_?b0$KpFi{{5kaXZX<54rWQShEkJuphKh)$33Rcyl&T1 zg|$zgR{f%8)6~;#rcLU9rx7xr<#Fuy-BxC$5a;Qg?*R zp`2@)+m2w$trPH<@vlzDDxS+W2E*J?Sx8~^=-d0i5|Sg^9QU5_$2I71o_|$uXauo< zD@gOI07FGvM-sON9hnag<85n~VY}z`R*t&}3beldhg6 zdAe2Ru~`epbP*?fUB$M zuH4+#{B7C&0dIa!U@E5=)Zp3>r>v2^G%(-QdE(Z;%ocxY*#FuV`cmBWyT2kA5fQj@ zt$I%38*oX*&{Q!I5QeD8<_uZ2CjMRI9+^^g=x;x3whHWZfz42-@(XtdO=SGDo5~Y2 z!aK5d64o0d_F|qoEtGlL{YIysj2g^X1l-td;lcb_9Qq}D`Qh7wi^NhDhw&8 z=hIBp@R+H{DH0wd1W_hgQ$SY#RmwFf#RBWYg-8byh#2SqjP)sB*E9;08Fn#CpytC0 zofbZ)mvYF&JFtxeutTL;z2p;AR@0d?+bPYncr;pzu|;zXxT;+WH!!3E|3Z5a4SAY@ z0^~K5gzGvq(d>!rC6rgjxP(l1Y~)3|&C&)bw^!ZZ$Vxr$J?N>=T#6RGQ~m(~A){N^ z9zQ)k?&GKnU9E%GB~Q~%i`#v;m#L}cA7jT`F152AH?8dH}04t*Bj2D}v* z>MWb;nKAsSVThNrgx%%0Au@ll{F;L65~Y+V&NF#K`I#Nt+fM+*LR>I3N-ew$US>5w~~hd9f;`7~Kw)nl)ExP|SRf?x4J4 z#N|8ktq!aNLYX%r7_PZTNsXrkNVc@CH8sjyP?3`V^%u9%zy`ZQ&nJb`o}naPefLKNQK z8xo&(XY_@ngBiRd$4lo;b1F~xHa^yS=NX-Lzr{~3TArAEvC9VbZqR)67&FEpe)heb z95V=VFkkRaNnkSxLw$AYJaaSv$)AbKI`D8z`I~*$o|Ooev}_zXjbnB z?nAtXGg$zg_Yp#X;8MJ4!DW;`@ElSXXF+=1G^a6`omWzeMH*>GPWqh-Zm^eSk2s?x zKD35e_Li3nzMo{f?gcdo)YC#-*=QTN)D#*{j*eU6;^M4qfF2>kLYvf}l){yy&-DVJ zv=NA8`N}+gA(-9ztA$&?85?V=j=5OnwNnuGa>80<7{i98wz^Jv_3G+cvAxXh`x_zH zd5R;Z^%`*bWUB%h!EjCJUMSoIXQ6eSbFq+_2a8rHVL*re7-_Q*8VZ(_>3AMsM}wAC zv!^EiT@bIGm)O7RlIk{)Y&V8&!mK)GFd${K=tKqHLC7R&`)2x?_f~doib>o!mG$a4oV3u{o%6)tU50S^B8)7bv9M}Gl_|pjCZJOq6zf)yS2ZYzPQ4`uzpjQ zx+a&5Ry{u5cj2Bub)|l-z^xX7PqRLU62k~J(0WuiiOB_IKY7Q%IKpD!=q$lBU9(YL zU0o6g9Za&mKYj?^^3?3%msY;kUu5`w#fmC|huEExPIX>BALKde-`ZXv5m|)#&zm{x zZ$wYly$yB=Lc-F=Io}+LwBm&vy7A}UWp8DpxTa%csOE5!Moe^pl<;W=rVyr-qKG>t3*h} zrFBP$t8kG?gw$+OjR2{%-*2Yh79}aWa)X7j#J~u<3(;>7M~_m08~3dL36v>~>d*Zc zrcr98J$rWLPU?{njH1q?h+z%^&OS3*$sV5=#vvoted&x|)De{2aLk!212|I8Y4y4W zMSX3BZ3&Z-l;xvaYeCoNn+fQ^@JPnmj7gvy#oNVc@r2ulmzis|rf!}Lk^v&X?wq7d zr9A~q^;)tk4&OA|3{kJc#MbsV&7AarKjZ|XhKEfsxI6W*N#*RIr4C*i(~rZ)oj+~* z&wc*f%|4yGbn$%{$bSVwciK2@0f>S;C=MZT(*yiM875ZrJp#~EghDCp^v|(;9a*Fa zR8?(OPXVA665q$Tx_^w!XAH9_oj`#4+cu(im7(UDGyNIx{hsPNON>>)shRN$ngi^7 zfH4M0qF68skrE136mHr)Qz|z4tL7YOmRTbDcR}Ui9fhNZ_LGyoMb!$Pu?rlUFR-&$ zR#g0(nsk88WxyqID+1gV^(c>m!TV5hlL;%PxtGGlB)sw1#nTjl({#m%>h2*E#Y=>% zEiaocp7hCz%kBigMQ|#~#LTC^Ic?vV|Ky2o_wGiEcQL0IejzQ&*qsSAJ1ZoFfTE)s zxBg(TkT#!z5@*O1Zj{C6?)KJVinDvSO-Rhp!GkN0t+}|*2lgpCi$x%{zDf5PKWegR z21O!e$W5vzg}Tic28yF5lr9@B=UU2RQGU{I@GXkfO#$UKsG>-y4P!_OtI;iO2 z!3!iTj4|4XV?AXcYo7Hkba$n=bUV{9ZPw%bV_WT;txT!2j>*5=QZdM6#E(7))=poI zE;&6Xr!C?o=zqps`HJl$Fv%9TM2^6=t5-KfYgKF%*3^P=t+goTxH>}AB7^xDH7$6O zb%Gs{SXy9OFbCop-UX^_vbALiM+^4NX;^W2W+|J=a(NGsJ}MW z`ef9&P>Z~$2$w1s4k8yD-#sC{)6g-An#9~h z>LU6jX4qX(YS2L%Z`g2kfYzfIFT!D3mG<_ORjLqbDICl~rlm7Ztz<1vOQp-Nyz7C@ zW!?3@eNWqMSM%w-&dR^mbr~BUD35}?OO%H{XMFV5w zKd4W&&0gStM{C&5#olpQxn~}YC51EGkL5T?sRa2w^S(I=xrj&jD#fcCreG-Y=PXyM z?#nL&7jdJ)+jQ^;t`N5f$Y`%r$IRov<}y|&-usB_gII0t+A2H_QvCm|-8-8O6*w6> zcou(dB%tsX%OP>ypJvw5c8C+umoIbQHoL)LgH#eo*lRgsY|&HRE@DxHdV7uoZQ1oJJ! zHUyMgg(1SmEuv8Z%0^nRdkA>ILj?O2G3bE#;}U(v?}rw4p{x?8wT1A|c;5;F40z!# zl`wi-TXH?AMf~Yy*VMh_)f;Ku z;WWSze$kU=O>zE?kX<)tf{uewzn4%+R+pzQDZcHD9Sqpo^J8vI743C(TPk!&au1QpEtjUZSdtZ%m zYvuwIjD5uQagkpCP4*4h>Y%=a_pqgx{{ILW!g%5>8LoKp_2=OIL9-2q)6p>FleUA> zQsz~lHjs{`;$$Ya0EQe?X0c|Wwpt%?`2Oy|_DfW|%o+4svsp9M3m3~gziIyd=O3QV z0vZV#zU_c`vKxRS(Yz=&0-OS#KLuGD>6A<*19VU#SfW^=sKN!3UYfyzxQmEa0=R+f zeoRZg0*hEMX#PF%ez)S#`>si()@TEB=30=THA_rluD5WnOEm*$% z9t{9s-+W3oalGX{675VF81Fl?KWtX?{F&yy*!~-ys8{OBEXy#e@QbZ12_Q)tsLF)!|r^ zBNOk2=9&)~kRNSY{pa!CI=%O9qKX&watfLr2Wrp+;@PFZqJJB)NIn%cKq zF({3DW-~$!Cj`I)Av1|T?dI)hNl-mkr)Dos z**pOU#k7q*nl-x<9&Y=(c>Iu&OJex6Zs^L{9&wL&FN`OlAW?!)a~*&5J zyxTlJ+Pm}A8#JQQcZxF{Pnb*yHP4;QO*w21=nrV#YwwjA)2FvLDaO5tRyJ#065X~~ znsI>9SMEN)4J(H(z-T(*UAnSh6$KDb#v)d`ctkW{Oo^}q0a@*uc3GkC(ch9!gSt$| zeeGAqrQyue0od^&sftk$A%uc<)c)QF~i)EH>>_&M7HFW`lH z)~@RO$|r5}`BpWd#>TVM^aGvrmnK+GpVtM7&m3=)FsTgU~6SEth2B+RHxx4&dMjGJ`^(y8J>t4WchkthfpW1PE3cS zA@tPO=X}{@rFd;)yK}Gl<$rZZj@43fIuN{g#fliS9pm(sSKoOlbOo%;1iq5_GffND z00QPiei1=}g+&nLPfYyxp1E}a{#D-duCM`UA^jnNF=CLlY%~gDVgM}!Yv?1~3^=Q; zEiCRfp85?+&i~ttQ4?%Rvm$fJXVlbl?-7<%l(Q!pXCbjW`F>tjamm=3;h4v$ozM#b ze4<&A0Y{-e|DpfGZ_vD14p-6sMs<1bE(IV>0l~qlK28jcu^PISm$!==iD@4#6;g-R z2ow;KiN)af@lBWjh$A4!PEdK8{d8tOiFWrOaoK^xQ{~7g!|m%5VgqG_^T^qU&#M9%XeD;&3xt^tNmzTD!Zfr`S-FjPUzkH;Y~f)5)s}6V`25ZQ$#y3 zP1%&fZ-9C$Q$iSsW5^}lmW;TYoox&>Cc5FL^Ss(uMkL}uLAI7WV#EKabEpqQ4Y3w8nBqxag8P2N=+>ryg-7PXJ zL3MSYv64ckLwJJq#PnK)wOj%Rhhvub{oH~g60=Vcz1WPw~6<{)m-`Lf*1!Xi|K;k0L2&9OH&Nkj^3!M%6n5)K{+jj36`Vn#i zTNEfNfjsQ}TmJs_>swKl3T@VUa2fPt##$jVHDxIhKP--#G_^E_-)LfqVbkuOgYbAU z=DUqc_EvTqWz8Fz!jY`BjLgW$U=@o@4=aLu*Fygs0VkZ|A?^PC&-12v?ZFd?+RQiK zc{L5A{@FEA1JGb#?561Ro*x3W>)xZRlQA(&K^hZ+sg&iEkfvdg8oQgW3`@jG%foXW zLpB^1RE92X)EBO8aqb5+6?9Nm|W~`ah{?Wr-dYc)wNDAaBHr zQLHTIPCUMW`Hh%E5e*a)Zb=3Og zyxIduEn6~j1EdonBZLn)?X7fr`i305wdGL!XC}w6NNU=3i5%qF&&B&(u-917dm;Ky ztu!JJ^3;yeZ@Z~1GB<{HL2?!YJ$$b?qY85jaA$_{g1uoA+|0yN6+}a4!&jI%Qp$sf z7IpQ4Kmd#qjhc)JSu>y_QXYp!MpXlxbMDyrl+<#+EoV%6Ua+?f1&)BQ5U%`|y1LmJiPodyML4sC>=UaMI~QY9(y}GfR(??YZnoVxD{mLP za{3LNN8q~2i-UC}bR1qB(1}p~0Q_Vj1+C!k2{8k7L}DR%j})zb)qx2gP>;72Jt-Pk zUANyyVq<+mLX_BF1I{E?B9y7v?$D68yxR*SFt$E*Pu>6W&)u?ul_GL%LD-7bG>RPv zB?3}u*%Ou_hyzP-tfd8iD6J0!ATkAQc_npMO?zvJ?|X$PJKBEO z2+5NgFNz47>P(nIG~h<1LR2O_M3K0_J1MxkP`WIBb~buI=`}sbZ(gV{ErGE_xAEv`*vHf2XF?a-t z>6w4i0QYY`-vfMUyj*7W(be^%qOZg|AK_hbM+XpKC?TomWS%g2F@t$2&C&fykxRi( zS#BTSOEoBssm;i#g%*=`3V;M6ypSP^;q^1(xX5vUgfeWWuN47GB=P!tWHlAmro5fr zL%M7NAcQ4MRqRNyZ+Lxk8Y-VXxKV=+^%|oFMT<}kJK*{Nr4s|B?H=iVbk~>u{xD=g zf-K|fX5pW4OW-k6_Y@rHxRoeG|j+!Lq7*ePVq$qcI^pEDv8YCnMh94}= z^w<&+3qV2ZulmvcDr@-UX`}F_e8Ni>0`@Fjy#~{N$qtW2>q1YTWh&AQWbdOX6kK3X z=*%jhc&jF@i6V!X(Qkmhcp+k)D9)``GiJ#ANvJFNy{f))oE^D33@2s%Ft8l|KpKXV zCuQyPa}@5%0on!rg&aq*Bz@(xk4m=vv-#(}8a$~hH4HsBCBFoGv;Z}f<(iPnG_kN| z%pnJX_y<>i0@gGrlo*=$`W=Y*QBK<;q99ry7Pr&z_m?$%Y~>7jd92-(pv)0#kN+Ar z$!VZ}S_k^-oNMa<$fJmmlOx7xfbB*%{}K6P@x7h2)ZLHo|J{FPpL(!kBCo_bT6ZQ> zwh7kFz{)t|zhIbgIw&d>!RljAyWiDt>z_(HKuWL8|FDdRWOHG?E&P-&J}ZV850t2W6@2^+y=9-_Uj*sN}A{|7UnF4X6Xy({O999NmHJhIR}`*(qnz0DMjhFOsJD~7yBf+<}* z4xG6`ZT5;nPu@RnipTT1-{7W2{xz_U0W?Ld$ov3}kon0l z2@Q|La^EAFRCly*C!P3{k7&uOxH8M=hs(BsrTzK%b3 zEQ7CYhYtcHBN6i*e!?h_7eu_E36%vP1d@=5h_>UH^DQRV8!aR0Fr7 zmUxhfy#%%OLnca0yi6WeS1#CVGP&`@I2x8Wb;EXKpI?-?@P0=~XA%#gB!4!XVY5%1 z7+=Y-mCIkWm#$hxD+rMH2!Tz?Z~`|w=ww|Y71w*xg_u20GvnKK@3Mj+BeTa<)9Tq^ zC^Se|Qome&!=+9qgnNFx?uNod22LPS>=<{B(6~=OBnB7K1~B0`$S=t<%}Z-u`q5`+Ub7ZGq_|BIRMZ)#cZ{Mp;faXEjxB?kL~el!232gr zXj}+;9F#`llg&n$l*yCnG0wpZl!365>2fw(On?k4>duI(3~V#o7IkTEm7cOy zVAd2h#1To?evvr@&!p`aXVs81Y)aru`GItamoGhVAZO(|0 zg^L#5o%3NGo=#uK6v=2F0vdfz;Hwgca`Cc5Lf=&76Rsm-fd!pjXcPg{^ek>O-;4?_wSdn5Q?7# z2Nt0Pmb&qZj+>A)Vs@Zx=9&yml}$^;$jNYU7^}`rOj*ZL7QF|xpF-cm-#LDKX>_5b zg#~?)5ap@X05r_Mq_=c?Sj7-pri=_b&aHZ9EN^j4WE}mLRnOm3nd6OsZNuCDvzx*7 zakmb3<8Q(2+S{KvY(a%dDJ{Aq1XIrQ=iiiba`9r{AL~XVv4P#Du(AbNr-*pPV#2e} zUd~aL-D12;OcCZpbn;8>AZy^kWocci-+b%ct5@-8n;VlI>No0%vadI1DD;)dA&N?9 z9l4AQgRWo8y?0NHo8%@^{Fjz>*kc|?+cQpa90-~VhWEL79%kil0yQ$!fM^G8}avaU`I1U2Y@W@x-&R<0fiTn z=k~v2m*MTsHRI%|)Kq zHA}rab?zKYHiK}XJ94B3ZVzMz>Tdxe34P_|g%kRnai36EzT0WV?BvV^-)*d&-h7_z zud0gvY!N^zV_XG;wS=T0D_*EV!n(C=5LTT1n$?v(>Pcf*JmVBvj@T%f#S+sVU`W0r zj-{cnDHMY##D#yYWCry@xYqRTU>FNnGY`XV7b%b8_ZJan+RT|4;9z93w;QAva2JZ7^ z<0sZQRxwqo+o1oE_DNbppFtH2xICQzK3D3K>V8sF(g9J7xfoZ>n<(JyJcM?mX!zB2 z-vdrRBEn%PgcRO*%NYwxOBaHqBz;2tz?H8?yc>C7vTp2B7X6A74kZ9us1qhH_b#i) z;q5LB4b&$t=_8iI%W+9aSQ0RG4S$T}-W={05Dw_EDCX#oMc2S}O6QzH`|D$Wt|=7B zq@WK3k`5zQMZFpY8gGw7D>D_Ha~Tx;GNzEnC)?8aEC?*_fn))Z-MMvZ3&|Kejs1;( z+Gs0F=M9M|2ixMm4;40WXlMoSI90zhw;-xr<{c-Kf+3M%O_en3YW9R(TlZl3(;XBD z@2DauOoc`Y;7Tjk9GIU6sT*4c3O!L8b=U?R#_yk=wxc~w+8mm-fY&bt6V)TvP#L9_ z(vBN|Fa&!tC}_tNde*@2sy>IV&IenK6$0n#Uy-h8q_u9)1Q4xA#<;l#TnAZe;uqd-o0oWDqN<8OCn-e)G|z z%46GO?-$cUBN1$cy{jy9N8yWo*P+tp8c|e;avo6CG#dHa?n(2CuhG&A?bO;c$)iK{ zu0q$HmHobS>1E$5zITFij7w_Ni>-^7y_&I7YYJ3km=vrKNE+8E1o02pBQ47ORG(JH zuOk4}z(fQ&A=J-@p~dqL-25&pC#QsX&OEpRY?Q*4V{nTP1Skh6^xGy}6ZB5x+TlYj z&Q?mGBxsA;SeCFdwQ+3wleB@%KjvEvcm6B`|D?~CFqcnDi?eH7x=~6m-uVZ1?GQ5< zILhWvumc}3KrU-xu3^IhZm?<1$`Yoo!XyDBP`Pu4k864POQv}*UH6d28N-$rm6bgj zx1($|aF!TOihl=FD*T_PC^{y+|AC1VA7dLqoJP;zNW1tbYohuGtw*uCdR>(C3I2^WllXCz#X9>6m0ojZ2qv?`N zv-R9TNR45gwB+2PW|ZxwWG%UE!~!^;=5$sxlr=gpe^E7x_6oThSoWTcr@b2LC!_J@ zo2x!Qds#5Di+dSC$ol}Zna@;?tcCfo+P6ZL`J(XW;rPa%h9AIy8i`a~{-;{0Ug@Vq zEtxaNFq>XkW=^k0_EjhIBdRiCO5e2I<4DJvx#_w8J2c1wM^t@LHOSr6(xUBnqu9Sq zenf8AKjc@~_khvw*5yrq5*O;EQ!;%2R6sr{PN+LE;~Abiiazpr^5)TiZA`~ot3T&M zuA=KjKO|cj05jbh_Ysbz)U9A9wDf|MBXptjVk0+ejh;omIP`5SF%|G#GP*3irUV+g zG+!2^Ol)}cH%6poY!i~w12zQ%Z+Hb-PoE#?w1?^b(k7Ou0%pABAWD)CA-dU-Uk>iB%rXgX^|z?0vE2vJpzixxbw9g4=`13nC6YR6pZ(v5{1Smag&_h7fNiwxc>l#r z%A|s4gur+BZqc+DJ`CLFOe z2zA7T;$;foIqBAx#@>gPSP_DZx89||$Bp#KRLiw^;NVDQ0=Nrgm_2p&8IWGyskqE~ zq`N=CWritGORs(R%j?%oTiD4qz5fKQJ#TCB_Bgxl>~8E6Y@F;iXk632`WN0lIW&8D z!MQm(%aq*46mS@K@ZMBT#anhWh4^0U~RFVbGM+yjq^8a@hS!w?S9HZT*8@c(r%7FU)RE_?pD7! z2@~(!4j(%5O#C=o+pur-K=b@j+6JNf!2m}9)~fIeNIT0TLVh>A@}h`@HeSxO0iC#P zyW90>JN3LN-@LMY2VZe^q{Y#k{54Bff~)~2$z1K31QF^iO--cd*7Nv@F;@*baNzmW zIj)mfL$q^#Le=K#TVj%X-Q)aQZLzL{rNEQQXIMeZuf6b@TqC|7a%VPt|6uH@>vmX! zM?QDH$!h*FHLmc7&=ZhY^eaZN4f(IF8{~Xn}_whw(I{D5~UK7P-IG?gp?tQ zA{mk-8B&ocLs^DMN|Q<@%1ok=u@EveN=P!KLYmAKr9`FS`?}Y9j$OUnZ^( zT+c?9?NL0>F`VCSw9=aLlu6+d9&OjH-MedsMbF+$*7rMVH+y(7SM+&){(>xTla!VeqT4$|37c75GG~sI zd26N4qjNj1-`=xAZ_Uj$f$zK|F@PA8+hG+gFQu#4ci$C^iS z8)jjkjQx=2IO+Q0H` zQE5CU@cxFYLFQg?tU|B|AcjyNa$^xLK6E21iLqc-5{4;dMb%$`g&S#aPlo<{xsi>g z*sZ65RMfWIOQyvV4y~Y~!^bAq{5OoUn=mYRTrqrSeF2xIcP3{}Hqx1k?E(~s%ArdL z$O}=~%<1Y0eFPMyO6h?uS7Y|s+3eQ<(qp&APPMzEc!t8gs9{dG;#)Q=Ry1$@SC?kh z+WBuVyMQ7ZHftp8$r>7FNcQlz@8Xw~$@GzsJJB{dA+8V$E0)~7S#yU;I2s&bjEGpz z3k(E{#>igJ%#O+4n{of) z#eEVOgofU~f4|6$cT1^eEc3awfUEvvLzgZg6T%OZo|RNoY*(#ZLz^jH3nc<)SPU|7 z9D`qvxjJ!`;^QPIWs5*ti{SjlX0xv*|L7{~GHFN7^AQLgvgp_LEyzz(c_GNo{e>yP$?GAl}pK-y$KY${nxG#6_mjKRaj zape$Z9v##=oG$32SiM0}C=6N%vbZd$j9#TEU}TCKZP)i}kp%>r3aFN;kuczKp)~N;vPei^Q)dl1Q0rMs1e@f(h+V)nW#DEGY07w zVxu*A=e@-OvDJTzQZ`kZ%Q}^%`vIFK<<)Ob2?7r*|M4S~?JxaKzk2oR2+~5%fYO8C zWG}%OQ1R2}6DHJY+(4aO6G|%4@UR0x9V>K`thP_nEG-p<2`-gTUY<1|j<3@ZDhdh> zggzr)jPq8S<3;tYfY;&f>*)jmVYrM^{BK!k3qYQr!jfu_?%GX)LXw(6r1P!*$zu~* zDx8}!w3DDmLGM~0wr*ap4!G`TH>~iO(LD9)tNTH-H}y2W_}pgix5G~JK%%msE@%?P zeDmtnLr2eVmKzqiVcu!Kz%(AngsUyT&;8oD{r0Ig&+3Vqk<$&Y{~Q_RqqHybeB(m@ znFCieocNIXO{%yslb|gHc%vSd!7_Q6rttjxcALr`cIciNbUrxGuxjVw z8+pgWclpImr8R(%O=CR@7qiEBzrRevh!{*Q7{_=mNf%%(f(>_23|fV?qB*8A>$%qM z>7R(HmWUFCaaeSperSw9VnOhZs2^30#6OX_mH3-Coq;xDm*$3v-J@a;!o#Pqfx?Ib zG>56tXqtXj_x?z^wr<6vc?WApd^qGfvf*@*-=)!emTT;Oy&IqDK0;ZK+>VN2RM<9T zZ|NOw>h^~?K3sjnZ?W5}jFR9<{EDQMItzt1x!or{2G#B~8M<_+iSOZ^l~oQ_xw9DrpPz`h;WKy!G*^#jGXU1ORW z4|x35k9cnKXw`RBHk9O|L=-x`=p1V(jb)5p3QSxTTC6}2mT6EWX=&DDq%7tjw|Ff^0hq#;Zw0}iuJ%5MZ{khff zSB2uI&j+1;eQLWn_R`#|(kC{LAGPlHXfruAW4f!lOMgM`@bv$Huh9bid5Tyvi{T3% zj}`C+q4VI7qetH93QU;*h?FtsRpQbfm;Tc6$K*e>6Bl`W0UM$s|zWKxXHTr#I=FHMdw-2LrcSMQ{G z_HNTOO`d62PfYfJ*h^_Z)8Xx8(_4Riku%i4GD?g=*T zX|ZI|5sLx$&8jNyRH|FdYrVB6WM)}SZNQ`(^5HT!);f2MsNIL15&aVW#%NI=$HoHs zwNE=w4%jR6^u(7F_ESOtYN_~^ukTtP)Zr(doaj10@`yrXbNv<$j#Rp{X-IhS_!s8p zkGqDpb=A8m0NbfG`#azGWmd{bM1g!{-RO;u!2 zA*LdH;%OV8l+wDOfA|xXYY&3^4VqW}YEWC!l7^HI7y2pl|J8kNm3DSXmxs45*ytbq znUb0^)_UHJNvbj1e<%s7bF-)C#f4O)$8@ZcX{cb7h%9Z zFNwQJUB%jhvtT%}M^E8w_854basJ^iI_MulHCD$ydN&Gv8va?xnF_D12v(Hr8ko6F zy5p$IX2XBd(^1MDta>!P{LE?d1=bI4%$xS4ORwElk|(ZWP$jkrQak7}VM=w5QO4Zl z?Aa_J6NNUaj|P|4UEkktwY4tDm#*3Bd_Jgy;z)hn!XA=6MyvV^K6>nds*_G&xR%w_ z2cdhq%$+-VpW2vw+k~wlC-%rp@7mR|qvW>}L%;m>2@4$1Zf0~v)B7R0n^rtCydKc> z%xK5e`3uC(&Bdd%0*^kCW;+hjUt>02bD!gH-I@lnDje()kqp4}+`~v6XHr3~ps|zc z+xLWO+hGX6az+wZ6?*Vn{p&H{8&tm2Zv>9e9juuAA~{j*Pr{_umUdc6TAImA<@_Du z8OQ_!?7X22dnmE!5ox$jXsA5iW`VrO(=hd#Iy%#wozFg~G-o6CZXggxRPuTOu!aL2 zR$i(Q3CiBHF;;h`o}3S_!I6GP&+joXYd>x6nYTyXi_`p6>#)n9b6CTYN!xseHo1S2 z)k+Ti)?tP1R(;8l8{87sU6AZ^a?;g7>cdUJsEPvi` z=RCYGPu0BWLL&VAJtuBaM~9>@f22j`PM?7?zmz6-K3;6 z5PTLv?W??59Z-DF-3K&v8M#9#3Lh&khF9#u7!A&VFqI}jleB}X97kwrnJ}Cqc61Tn zb~~u>Y}0XRgAC9Z|L%QJ5mn3ED(8*GhwcUJ+Pk-8tK6xYNgbwEhe+RwkR@k-{QUVe zyb+U-LTtog_vb%BPxqaTjSYNy(DU||+g6`adY~h;Sc_?t7_?y@`kar-$uX7Y(DP8; zbH9I}e%gk4H9egaiFNA#K0=rm3;~14llYnb&)Z-)}2)(I;YcWD-P- zr7&&;+((T+Ez&6wyVcf~9dTE#BC`@^9MEyPqef-WBfVgOMYxkeA9?r!vC^4#{z*&A zAVnEK9#yU0-}46pWZA8MQLKu(08PM?u_$vohY3Tc^G;KiAGbM|BSckue$q zi0cP}#iy2*|MdNP z2!>JS_m7`)o8~dgZPTV$`Fpg2848n{`xTWPkBsbq!GkcW5JslhT=G(h&|PTXu_I0~ zcS%(Y&?)_3S>9hJ=3?xiAj!~yebbf(-%sCNMyLa$laZD65!3h~V)ZL$-5W}+KiVu? zw{v&g7L`XFJg6~tY)?>FCOvrX{}y|h!5-)NVH-OU|pso#%#u{7t$ zsNPuzLeE4j=qx#~%_+61tu3b@D$Mg}%d+LmebduTn(GVfNlAW?ub`3j<~ep1UvIUO zAM$vt#bc>E3VCMGUB369?rQorF1a>0kTtI_FeoK#4j}QaU(ruRFLx0PaJ2~3R#>NZcp*w%d(up{V`u)b&wYwx@^I0 zPumA~uSu6tlsU^^BDX|G;&LwC|$IpuR*Ba=rD zkk!W{pxT(Un9Lx%$UJD+i`OcxIe&W|8FZv}iEoFPp)tlwDpQ_6D%*%Nkcr?Bp$=2Y zK_i((K4M>oYO@RNkb_|?2QTQK-*F*e*F*w}@X#b~c-Ro6e}XOwXvdBD|Xr|a0~giq>+_1D*;r0Y{B22YZY zLcrPeO4)@G9yZUm*|ZKB;bFAnw;VtMGDk0_fhkx!LjN%R?L@ZNeDmEukhmy#(m{cu zF_(qRaOhtNc_3`dG2FkHkP~A-g0HEq-S2)N`1EPV%cCL?p8|9o_|`PpbhQSwyVjUt zhJEDu3jv-jt$z)N4IeIq!{{sbfRRb`816|@uzR~ZW3F>WaPf8}Dhwr}7-o?qO9l<#+zYim|f$Lsj z+PjcRXS;zj@30K2pFubOaZk&Ukb>K3);hA92S8rO%V(q9{eW`CGbK&fD+bBq?2-r#;*==$$Wk7nudj^D0J|GJ6SJ(9 zpB~I4uOy)CCa+{SpB+ZvVOk5sq&=$GjuMEJ&&12@Sh4bOlhP5jK=+JAJ-&v*Wteu<@BKqt?SnNbPsVQ3R+e>Lmuzy>WJjJ= zRORZ1_uadndzB6(ezgA5pbXvHeN@9fK9Y-Dzw>&b*9;5OnM)k@+Nh2>BxeYhMsgHB z!iLjig|!ophVDK5TQk4|OsrB$%kN{;YnpZcy<#v-Q+QLlEEH$K-NNPf&%viLF&dlv z{p6uT9np@FM%2-^-QDP)$ua>Zw=z(*uDSmZq))7uVo*2xSCe;8h)_pexH))WRBiw; zJ*@olJFSqn_@QXb)!DLIfMC39W=y*0kNJ+i3hY;RS*q8#;q{UGkL@-;H<*{H@nxz> z;Jm-z-x51H0~r|U+Rg-o1CP59MS;Lzfp|@ZzMDjVmWF&|O$AzwG4h zZYae5utf!S(W3CiH^2|CH6$L|`coJ5j96i4lb>bO`sZ8Gvuy+RZE*9-k@C!Ilk&VS z{bX}rjb7xSw4WV3ie}vp?&+>$`Dpl5i_C*xWAZzlJuxf#QCwknScyGE+;T2wL{n4F z&iwtkJxcGjIo+G_=-}6F%DpYE=BEzK@?KT2aMtNfqF|+-7ZdI$qbXYyh4{oR04-PC#V^=sEIJoV5TI&}VycP$wwa|n7<7~evq z{XD^GTEwA4!v7S(!WjQ}WICcK2g}`G86wOe8348Ze))G{p)GUT_GdLd5@h@)_d9<} z>W8|LOnXLd9}?IUyLI!at#zZs<0VKkjcCj<82BS{$)~q_B})3X%2#I>XHRg*bWU)1 znbtn7#KP#+k~c=9$ya>SOTTwC18lPFetlxLQfqVFoPR3v%w2vqh3zcNIOd=tX3Z)2 zH8#)M)lk-P<`KQv{IPoYX=k9j6pm!uqfD>JE*{Yn0PHrPnMrx$wvy9pGj$Al4UJ!T zc-(E-q9GPH{UaX*NDW%OU&SBmmqBzA+6%(pGthv%O>u&n0x}&h_9S0FoY=jl!|kma zy%Kh%TrO-J{`p))rn7ff-RD2@RZEW5PpRDU@_QbeVhm7R58iryCO=;+^YLui9``I5 zCmRw5OT)|U!j`}_VB@g+`0+j{u=`D#qz>04w$WUicn+=K@|=~Q12Io-su&hHc8m2BMu@2?@T4zT zRZ>SqlD?>kvPw~=y;$`Csv}IZVJiy^Zt@NKus{(#hURzspy`Rz-G6wcuZ&PI+Z^dR zYdsVwdoBfQCah$hd;mhO`St74mRqB_dYI%)J+aA1E`nL1ukUVMo&NVB96tUUb(Enl zi3NnI-NC`KK%aY1wp;I5>{RBKL{933s!i-xhuoH_p3V*dWoUF?$F{bzr)y1hnpY{z7%ye`B-lbRyuT(eXrvRg-X%IrIGq!SJmY=@PnU497ie2Tn}A|c^c3v~Aj1kgf2l3%&N zKbPa}$Y~Q+SHjB+F@Y0+gGR|NN)C=c3wbBvRzK*tBpdf4R!d*GdCeGNp5Ev{#ZkG8 zRFn?T-fQ#5TJqnApV}9HOjd#&TBRI$16Bsmx3)V~UbzSR2%|*bL*ks9mkzV53tDCh>@vSQ`BD-R+o|_B8kpfR%JHG+_(uwb|<{ zS1eyH9x;+;Z$!L+lHN3@GU{QZH#&upOtxyR#hGaH1=J|955HuUjT$hZ9TefT#8H{o zTpkHSI?`?p=Vp3iMQ`TjrA4IWp^8QYC60=bhXFp_VMRrY>73I*<2y$6@%`IwYuwdb zDcSKU?>oI3an>zt453W)Ob}EKD^_&C_wDxGy9IY#d>mBR*U;a<;P%`4WcVRr;w+5O z_@}|z=eVvyPeUG_dS~FyZ7q~)8Vuh6h^={k^mJs}$o~B$X*;IRx~!>&j%Ek(buweM z!W9-W83oiH!q5!sy3LPYtUA7TM&#;qV*_&1i=xNbj*qtg-toXVWAFW=-C?0Oy1DI7 z@-f|Pw0P~CKF-4{UjYM&@l`Z;*&ZPR3Buih`N6f9v+PJL@7^scKbax2IgJa~zf#!5;lsONOtSw%i<1*9b0$};YmXj&kW)$?Zhw{cD-deEC7e zx|>-@C?-5{&2Ust!FIE=tSsh+(hTZ_k2!`g&IA^kU8Yu_?(N+xCw?G_VBe|}XD{7e zJc1j5+d&xQH_qq-h~P{zrJteAG`MN)t3E4-SH2|#VAUa;WD?8ahlQ|p z$_f`9GnFjlo|63^%wAe`;3_jz?m?*w+zLWc<3S~4!FcikQ87*_w!UCxM5N=BxDp_J?l{K*DjYq;- ztvA~G?e|JlXjRybb?IxirPo58tC{!!ArIZnH{%c5tj+4>?||>FBonI%qxLW>B7Pez z{PVkib|rRW;zORNRFu5)?h`{%IrFjcqPaWyy|%%?;Pc0iUb$anx7HnsjEn~Kw8TJ? zB9V6>1C<(gcdB{$8k2F_eUxo`PZvC zO81WpD~l}6do{1{?>3#{h?K7GmyVf?ZNAVpZ1C?W8PhE-MNK;y14Th3i+Kma@nz(m z!=qNtzC6kol)`lJ;^T#5t!eltG8|$0WaA2F=kkkJlTC2^d9<#c3hvUPTk@a_518Uy zzP(+u!^WA@r%&Fp#dJj{qbLO~Gx-A$$HdgM17A?wK)EhmkSCOk8!kKl*fH}X@x?s@ z_0&=x>hE>2$-MLUdCA_9zp~FZ`d7>|BNX*UyeHOBSofav@n_OAJ2jAL3Ps^qxO`j* zM^y|{v7;$6O9XOYGVAfLY)^=uOp_e4bUe#7;T+z5J!B(+*r<#GEJ7I~iFFagQ z;wu)N^mBrku`3ui;|aoLFsyFRI(Kd_#o=Hzxja8w!|(AV#>D+DpM2-~#oZ|Vbg{;m ztL>8-O{ec_=~Fi(^npvazW=-q<7>#k{jz5n;7#5=Wy|9cDeDgH>?^S-zxEp`ZuP$23!F1ChqCwFZQ({98c4g!$DD$M;SRevz9No za7imT4jtx_j~}S7fx?vTe}1B8CZxTUH_zOzX{6oz`0?YO2s_6F+w?Be)ctdT{7&&( zgn~mjOEc~6h-wyKM#+5?OuMkgWR|7Rrq55qzx_3~lFKON%>q0~q7W5;Uc9X~lH=Y$ z`DE2YO*=HkjOl@muH(u`Owq-qL;+CBo4#B-_(nu_z&rb`U6m1Xm`S=QPj!B8(5AlM z?ANM}59}vjyf#yK$=YX=UWJtcs`L3tnM-^188$Y{T6!9Itw-ahL#tk2=)o-zd9-`a zp6w*iOtr`LLWl!^X03LrskRH#N&UXE`lr@i6~7e|&JP`SYSG<;D#iEv8dS|`>$2Hk}yZG{@Rd}ylq-i*kb}=+G6giHQB~7B%m21bVt@71lg*Fzg>yk^+n!Ado6m%lZ90-TfjW|K zzM^v^$A~>4CIh4^5_2$0H2B8!88f6Z zbcOREpo1JJyu8V7%|4aLeJpL{F4J}tu;kg zMhxua;{=@|_LyRP))~rp8&sREwz9z1u3l9@v>s^jOHo4yxZ({JfbQ6_0c;sKuxiNf zxLms@s#>VK1UEuvhLDiv9O(UNmj0*^F*);T9<6UzH8pwkhg<+mY!dOI5${uiXn7?KL>6%3LY@Ra-4y|GLGJuXAvXi+ChxLSe{AqROUd5&@X5+ zTvf1q{-I!eJ6fkk@&zmcBzKu`Om9teW-5cB0F8($WNtS$#uC1+= zkN_x7SDKi(SxqCx2v{x0>XW*bdpolw7mg=3Lt9gEG{6<8;r9S~>4SXQ`U@P2EDdai zcp$81EGTciBNGvcl0Yn75t}C5-Q8ieCc;)v&5r@MkVl*v5FS1^v4BxSL!1(&h#bO( zj#ggWki50E4?4^+*Z;^Q@hM8e%~l$5`m{@82Ry99ND#KY>XVY+E_}m;FGtsyjEtzK z-X{ILo=4E4y2i37edXXm_r8y~lD9vmzc$BAfc`uMj#Yo{Gq2cbKs3Z%eR9>8nA^t# zj4Q96_RT)@-A_+$d!1Fyl%CRz3)S144p4NrNYmhgxfYWgw)x~mLuC+g{?*c;LNc^;rSVsc_;rS2r=Z~`gt&hQJ} zmV9v{Y9SI~G%$-Ej)}VtP|D@h)=D|&KNHJ|*`RN`na6>*6~_lwC*$#B^V9Wf)jK{B z7X#BT+TE@@?oICJm6T)%U{rBQ?pZ(qqojjz>cSMymvJ>H$lDLcP6bJ4Ewb_K+47vd zihCF5PwCdvh>@^B^dL@1?b1t!{)<0%9&sp`6e`nR3and-Q6SnbMb8QMUdw!Rdpp^s z$Cja0t?yONY#-BdqVQwgREoK^xVDHu3blBwS+4Y)-hU^;**QHe&G@tvD$0YXJhRkS|G7)q3rA#GD>Q0t^(le zG&;036WTs3DrSJ`AsO)El1=o1!H}oo`zxg+zip;q`1fMGd?{SO#2L*GF@vxv#8Z#q z8bNCQ;($DR_$s1i+XRpUC0b~uo2u=#Dhx=wJJTk*tOg@G|$pXckmyhLPiD1Q(r$it*0cPE8&W|4`-S}TWhhmU=_^ojhu zu{2c@ZBA-&aq`;_+a{_NXR$aIHwCL{sDTVX`?JTK1|1^9#UMRibAJClV+7Dty`7};v- z83WNme4WC)gUI4+>H$=Z%deyJ^EJJ<&cy{s37tQ-N2S!lhG=IUfHVJ7UDEFS?cPd# z`-V`2MPmn|F%XB-qLWen@N!q2sI?1VRt$!vRIjO_l z135X66uM%aQPJ1T4?i(!3Sbu6fhM#NBO{t^-CeECs#D4sci4CAm@M>Nco=!DH)W13 z8ck7ce7dKwQZs4s2olZUn{t*b{MymxAE}g~5~r!`4GSg67h>)1{!{#?|Js@L;b#r; zT)4u*g#lWJua*nBe5Vwm^b|W+k)%XZzoxGrOX3k(9={%dK0lttJ>Zf`zH%oSSY7)!)`;OUxYgL*vh8nK*^+nvaJ>^FA0eKN^!~3lcW-cp@b4&PEtSaW zlTKoVz(v9cLIS%|+7xx?+>=W_Tv>xe1%HJyZbZ+uLQIOW}#dz7o%t`UOmn&S+^4 ziPkf)*%BHz+`z_BMOv&JAaSZ;bwX_Vz;<6hq{(!JEWj9ObvhvT%YZ?HIxu>Uah)kq zNMbVKi=Unu`1JRlXQfiwjrw`V?F{-zFM0c9a~G2e*$y*mAG6XlOMv@eun*OO79V|g zDfYIdFz4c(%PZj5BZbyFF6!L*^D=N3XjpuToLUR%!bNiAoKCI!00@*poDiZE zP#j@23;Kc8;?_tf`W6NSFI~QzsXQnJ)Pq#fo|d`nbEHDMSgr;K&quu5Q0q$DUjAutwE~zS=9UMjd#>7F5=_H`L-p18O?zX~x}M)w zC$1OA2EY|}Ejf5R{(ZqW69dJ@VsWYDGWucMqteHoa3uj9OiuGjPBwypQb37ZR?p{j zAHQJgg}}Dr{q2K0{Cc_GPgZ`w(T`uE6uqPdH9o+;UyYz}@m5IhE^&rAcEZOb{rxlQ zHCXB?mX`YpofcfS^W!~d-!G@!*qGVrLZqxJzTcaopWOmi ztX3xQeSxBcKCiI#5mk)v9s-K|$pLc$yGk!uv0;M(U~+hAD!F|9dU@74+O6!t*CiIY z;(EE!pigscwoXIE#j7#$8sd!rchIcwBzrhzk z?9!3bDtL#DzwdEg#~g?JS}5nK#>SGcLa;xHm6b%@ zQnbylo;BZ*kD$Qj;dNV|9R7erByuquY2?5tU`VD4?8(V#fYtM6PDgsd!uP{lN$~yI zEr^NzmMVAszU+?SG_8 zSN8cdH+x7-27~wsU@TN9%tRc#V>?lTNu*v76Jj=3zPV26;_Qd!JG;mq>o9!GipBPh zLCQ07HW(^2dQj~}9Vb>UBf26LpXa0y`wWp{r@KE#XR4KB(IMOhTmhz3!^UH+0(h>A zA936johxVdPGGi3xV$loXuk6YXU!ECBvhv=>}FLe11&=%|IqMZ-3nx~T{KdA&A|BoIH$VAmx?22$Me zuP2I%e;OUP->r-MYFPASvfb-{xTj$Ahwx zYYr*d`(!v9n}&zz9xMAA{rg$F9ATRnUH%-ZvvrUAhpWX}sS`7&C54x|r)C5cj$ zCL&DIUthfcjDH}!Dp*sL!QV@1u9fv_YYOZrE!}y1`;l@!9I|p)G0>~S%wN-ej;JfZ zQm!iy>{ra5_<0p8oKpzv>qEl_8A$brs)jO~I&InqkOx{JdRWDSUva;gvUI5$eXytq zs5ZQ_K1d4CW8l3d?+JdYlU7pHQyiE@=FHzuM)Zd)7s{dJlnzqTYKN4%ZmYB3Sg2jo z;dNW%iUbMHUDc@GyO;LWoVovO7%^;Mr}k1H*kauOK(+fK!?nHWEx~pL?mX9dICeP+ zE^qVzW*n#$`1@BzS`QvHsEl_{P&&|HSfOP}2`mj_a>eztr78kzXuwov#KJIqN~4-Y zxIt8V*wfy_8z>2QDJWt>d8ci+8$S}`j=YKE#?M-+R%T{LE<>ZneLR{X&m zliON%$f=H&0jg9geo3k`@N8{ddBmclWRFp+L{~~AqAPv$W6Q#yjUM4+Ld$oHo;&l( zuoheFscQ~y{`C3K6Qzkf8+@;Na@I(dI70@Ll*+1>)4&VAVnJ>|u3IheJm1_Ry2$!J z(>|Tm-mzmx!l2UNh?w>S5- z+KlfX;?1L6ejkAZvnliQ&+L4nx+&j{cp&VGIW!$5L_syf!UDIn-D`63bLmS-q_Jh} z4Fgt|c%$}QT-l_R-E$qQ_-2>5=*syBF+Y?qOx;i+r6e(%AT1KC($=k6C-xb_cblXaGz-lA%jj-J2uxcs4nc)zPXnEdM72;S@#%uYEy5I zS5stNw!E?%Fl+icn1MNO!7bAq6Ikc|>!I2VpEX|>X5YIvftge5PSxBVGr$N@E1XUe1AB&RaE66Wpz0r{cLFFY2si%OoVyOAo{8dQX;64)&wf=)7S8GeZUMdJlqd zA>%O|8MpPOD3^iiueiFm>mQ{h65`6WYlHD#ot|g)V_u%(^@D<5MM#_Z+wID5Yp_pc z622hdFXwiHY331GOgPh+KqVvekT`tkozMw^3&P&dQS`f5wVTWiShg~Mwyw7HK8{!3B(2+y(C+&3xp==zDLrX5HD2w_I2V)bJe-t+XroCryRrFamU=0m)wOF%e{U19P|~dF zI|q3T!)L4sv0A)XyQ=t=;`qbfL2s@gK`VQEV(qr3`gz@JIcYd|8hLt5ygSy6eunoJlDg(%L}%JaG+Vd z(M9OEwjU=l_|VB0F3f9EZqn?&H0-`auOa^9FK&K##C)YiW26iwG~G$q+*0lV)bqUrn2D^?0QN<}%RlL40WsDHgc zxG0Nl3;0qM-E;58K$Rfv;S-k2he`#~?umGuoum7vVx5k<-6tAJv z=w`&fMHWWU_^#@Qj9|ZkkF8EnpQ*{IO*ouBu(9fe+@MAmDuC3tZ|@jyaMvGl?WrAa zSd|jovEbAEAp-|awGF79!YSaq!X>XtG!|~1966z#X=nr*EUT#KObsr5_0>WZ4ie042D>PM$7cc+rZM+7+f{ z>!|w#vk$ULx_w9<5Usa_P$^-gB+JrV=$5;0XHU*~48Y6Wi~Xm+*9IeUd;r{)KoPjT zPp|$t?da$hGJxFmS=6L3WOQSHTOPfnaQCO^UHR?GcSrESV&Q0F@mb|_*K$g;cHJY? zhw>QKw4Il2FNH_}8hhU9FAgfw%+8W^HpDNwOi2uCfXBOJSe8%ItqOyan-+h5^LWPP z4wn;_uDt)~vkKk6fM6h@>9G@~ogog`S@GYSS`7-19|C0T9s-ciM5pe$EI;h-Bf?5{ zz3Ndt;wNCftn8zL!AK*xB%+7P+dQIEV|Os&sJ`^s!b}MoL|i)^@Ospy9mBH3`o@uL z3vgH^fL#JzO=eH~NB?{$1QX`aHwJqY@r?+cucari4mws1ax6Fk*pB6@XGXJRONhB4 zJ(zrN&kZ%EI_Rp@TdG9UzNT05;(`SWY_cx*x|OOchq1NrKXGDNo`}2*U(8*)G?bez zyJPmIq{ZMhLPAbZA)d685Jn%sI-*q|IK>CgWUAP=vJV48FTXB1q>6c7m{`Y-#>M=f z2|Q6mazw(9S`Ma<&iNMGgy*t{q8oz;a0WUH&V}c);7T}(`CdQBS$aqm1LN%sF?J+l zpykN%qF3jdB7NyJDH&^Dm$x_K-agm-wxg7i2l3|3hwCTSY5{C=P{d9?zMT_A@BBMw z&TE~YG2!#k^P1;Nk*{G0qJU43A5X7r_Hvq27NN>vAUzo_h%t%rJW^iR6pDEl{Y5H@ zj2`$MTMlnCRPI#Nb;3d5%KP3yyPFZUbsyZRQ6k53f36jm8^|(&he4*l4xT3H2T|UE ziF7-X7-701@Swt!PkcJ0Za+G{OHY0R8;m)qDW$dhB+rF^yV7H)dWNo$FMvnkf+{Th zmVs`+zVi28YsI)e>kS_LiIJK-bV?_i3Y!Kpj1ZDQ{9~5VDJzdHaEQ#xfYfO;1Xo7P z7=CZbaEmV4xyBwI6R_Iz0z;erkB~*O3EP*Mjn~zwGOL|QWw|y?LQ!@5MtL^HB?P>@ z^e_6!rZ}1etrvC{=Iy1Wak@8F(Q==l#tWm8v|6$A=)ha|mMmVZi!Gu;R?xOne4z0U5R+}$SbdbeX;xcjJXg4Lj4mK#ZYciJ`-2o@WrcIxUwG3o-tgQQ-Z0rP@~YuC^u z3LWpuc6ZJu9^BtqMut%>B__NTB-jCC#9v;uBYzKl#ng#)pE;WAX+t2 zra;t)BzQ#IeQ!k3W{i~(n+2Av*!ktlGv;FmCW)S5z?`6b8Lwa0Utd=?#+_GI9Qn03#@=LEzRl7kds9grd1^y=0+?UJi#V5 zR--B8>mJXNe|8_eqlX(b({VvSWz$>Ul4@K5xpCVOOEeGbuRFSU-7is%@Pk1hqY+n+ z#1}umvRCTl@*^|!gG0Q(chp!lQ?a|@{I%!c=+m>ZI^tiKPJ4H;rCAw)4J#-x7V=I^ z+$s!wx~{bbfmt?0O~Fmm zNsA%@95n>s&%D0LE9l50hLcDbWk^AAj8f*-M#si>pdCSq5sf2RY5nK2f4;4bx4mSS zEt8PC+qI+9wy;|NqxtQ$m*58Exh7unnjo`#t<;UAgzFH#a|*=Yfd`VX2U5tS>UaJ=3my(Oa;rZOsiMg;D}~ z6iu8E8gdr5wY5%Uu-K1+vCH7WgTK<5M!tJ7x7Xal`c*yCOZ*mil=>XXb#P5x*|4hQ z^hD=BM?#WzelZCjzHq@1C?j6>1oztZbdGVqbI3nxLR3yO+uZuMI_i^E7*-UbVF#HU zqjrdb9zzh)>aK%PLrh{2C+=(8N=rBaI*14>66p|97D}uvE`R06?TI;dwT)88-}mwv z8~A3Q^AOqKF6Xzd3ba2czk7es*B>=cpUxCf4B<26$pbR)+V9Q#DY%HVj9ql(L{LzR zVKVvwF{2^Q<*v3?py*6~X9Bi*Vr*&0eJVzxrpC~ro#y47)0m;?cl(d)qhZ-TLAyIA zuWIb@ureg8CNv|>A^T?F;2}dgLKRVsOJP!UVR%paSwm*g(}d_Hq~gmmc4vUmTucaE zLsr84$_uy=O6|1dv}w}?Z?;c?_wUF!J>}pA&h1dKO)Yunj{D6HA%THufTNZiNbEC~ zJ=)iQ`n@*!f;JD0SM|2qsoNHhRSEkp%~OZF`@rC(P)5QvJvjKHD@uHGb7RP!D^yNA zzyW+s?zZ5ZML~Ksxv4Y$!(Ke)jmn4+-U-V_QFn_l^g1*!`;#LXm3-!l4Hd!x%~xv= zn2{*4Y>-DGfG3fCm7EJ}d=dKme7(T_^=;|8d93pY1PpMbIC`y?p)1Egrg)^n5+uP95Z?a^Ji zN9nmJPoV(ut=DFAiz1v9g91VoY|Pjl>@Hi3e8|uloG;t%_wH1SVO~c*Soo`u^e%q? z^z=)e*mT%TbQ7aQ$%tFuEZx_qwe{}?%m8|lLLQ3slWLnt28*%TMv0nkR2HQL2|(Er zO$vCe_5o}H6>90Ow!il6Lig_b93nNSzj`3YM`Q#FTq=kI%T})zIHtaB>g-+NVNS=? zpX@wwb>+9y7Hv0$A%G~;=#jfCEAP%IJ4G8HJc^S4{us|;e7(K$t`*0G#~jKT1TKhq zTL(Nu)OKaE>nZ+s)Me}Q-b`Yw6g0RDGGpUE|A<9(7yBU3mgLLg6e*0^*Za=RPr)gL z?I+O>(;Gx%|1`g3rTM)dX@yZgDuwnj+>LJxt&nm>15HaAq!5m_ZqP?Z)959 z^dCQk)`QtovEI;=ZhlSJT|%`OBk}n2ek*dr?FX(X*EH3y74iyFj890&tjK3N0u0=| zITHe)`SFdxIYe6~8CaB>X@pj@GxZ8K+;!Jmj|`b=GwaV-wf-S{a-5wYZIyaVY_)#R zDs&$2hUdDSB-}nfYP*tgsM-97N9gs7KMskJjJ_fv<8r79ry0)$0|09+{{03}fG4-|SFyaz;^n)h2v#{BSF zVZC_qUKEH#Pxk&J2*yKF5}VbXIGQ%umJ`g%t(~5(z|~2 zOsIB!R-I5(F!IEkZY{IMTX;;!&=nh~n3I$N>7*x|T;&>>d4+Q&#SRLjGgdzm^gEzC z!!FHq%^EEsy?n!_T_DBZu}8infRUCk4NNfDfnyqUztvm{dr0m|?O; z6gQN6QWV8enI=1d#J~!ux&rTJ$wwCMnDYba7urz4T6hVG+Pi$92xd~H0y5w-rzGA=oiv7a4~#91D?2sl zWL={N$yP|r(9>ObX?HEI6DNwsjYUgZwXTq8{14!r&71GDWx|}F!L^}M9p0?4`u^KFK_XVU^Wo$t?JtkEzA*6$vz3klL%-kJm!&}%?%ILI@ju1Z1l*U5~1vx zCbMSJ$xP|)-3I(XS`1lld21DGa>$Vk0jvYI$xgQX; zjJ+Jbg8O3JjIy$W1Zt806J@za)=mjoN6YjT2UbkRO^rM$fC0#veH#7pkxb(+xU;F9 z(Yh#zEThfTI?wP6{1HGgGhJ_&=Lab-KU99)UhZ14vUjF);EBu26C}+fZoITiEA(r3 z>W%rVszi_`0g01foJex>mpXBEQ9uc02$nNJ-y2(!vL8QA!?yuwRDxk(hrkmcvOwMK zz?uBLy^RNiU6W#Xi%gE5V5*TCvw6g-jQ8*Fhntx_Iu}R|vw9ov(2ig^E#dm2oHyiU zR*b#**wk~BoX^-fn-u^4>3wgHdsx^mr_B|yp^|6DO=0%hW%lcLzmQJD1OsAad`CblEImhw&iCWTysy_A{$q=z1-nv~ zCA4zrzF@G%ZreHE#AtJO%}(J;hq4ja81nOvHv6|X|G8}flO_6bZ_HhTYM<;ov~YK= zl3Ikdf#oYp}#JvR&Zv|6d6pY5k9K zZC#ykvgp0;;DUaNf|6rxqQxR8#RIlH3WYS^P)O>P+-D-5fbhJ{dA&X&|GhQd8^UcKnN82%hB}OJupI;|FUcJ{ z{z~gSX8pIc{;?2n1erw6*r8%*+tv8`PkFc2!unT|;m^-#} zeMK5uw{A&w)L%}o217Qq>+K{2c%`eW2>rR?WwxQr>K`Ir22kt)B6K3ogiP#yggJzC zNF$dM$)6bv5q3L5AaHHDd8E=LOhzXIlVC{Zk5ELv$t*lq%->^1@Abb*MU-Ytr%6yj zef|11FME?s@?%*!x%L4WqzUhM`PiTt^_$H*^{*9i=Qt&f)PK$%yy}?G$j<=4N54tW z8zc7Bb0EayogX&}<6b95ji=b#tMgbL$CvJFqF@pnHuP;8ITatCL1I`3c)|grvCT$K z+de$(BJ@N|UkyWsfS6va5CeV4|5m4Ha)C~FdS4of4BEsCRRh;QVYp6Ql!S?)$F4z% zI8pQpH9ipjBmXdl1}Iy)AumBrWE`nv9OEh;6HN5~xKGMSv?|iL0V6>lY_P<-Af8s+#Kyqi(TKR#a58&MIzR2j~ts(}@(q6bAc$ z%o+*-Uf6llfmP0ch@E8DA2>Vc|KJNec7q`wK8Ty~t;dLqV#*211LOMJcsh%i_w}po zv;jkW^ZdDHn?FKSf>V24zPt|ofepAKqF6)9BGnz5iHsc!!4uH4Fseb=H?N^k6i$3N zvJv4mj)FJD0L3ia0|>AH<}9tO(vcAeYaP0u1v})UbW-cS{+WI+%76DItD4&$nzt;c z?s%X7wQbh4OU0#fC|X#ABPL3yJ7Q-U_>RU?#5XS*%X6{fXjbyNC>rvIVd`Owrg0|L z{KNi2$Oi`sTaCVR7)mL{YlRCazK*@ePtyUR`yVkcgjK1exPlQw=WV3I|6lR0Y#7Su z_lr-5wt0N$GD9|LSwg>;!{e?E8gj;NZ}k@y2cJKk*}rx1$?RPw(_8*M5n2pP65x@i zN5{nE6=rlD#(WurCM5sWRngX!JZllBfkHcx&K-{3LluInod#Go#I1l#ioBJQT$2{_ zor!gl)cKReC~#4ca2I4!^I2nNzu|)v&VSeGaZw}Yx8D4$!$;cnUS8$9uZ=7h6Uvh= zLsALtz~}8rr0!vfeP2PV@bN?!IkaVBGyzfgHrcyK89>bhkwWtaZ+q2DZD`zDrVNCf z0u%x-alh5`&Yr1?(=Tp0*3qor`^1?m>rL7=jC-9sxl@0~xpVbRDqxekif#&^eQeUR zKCl*a_iNl7_B*HuD;Gf%3DGZCOY;2J@^08YA-T_hNqOVaPvhmh1q-r(aRjT#a6nO) z9YLW%PnH=sZQeIlVWR1|lk1|3qgPDa8=dx=% zHTEp<36Mq^MfXE?lL?i{ho7SEF2e7WOV2vcRZa>AM)xyX;I-^rN}A50?;gs>I<$nJ z&~>!SeXB6oH!tw>+!Eh?&i)x?%OKVeFRZPKmSK=p_^LeieaxViSRabO$ON{HGp4}o z4XrXG|Hjj%b)=~5K6uiUp)Y#r(M~LDFL$zNR=Zn!?YH`9_~z|d@7~R7PBK-bn1m7I zV@SSx?=Ya7ddSq9>JAmy03R&Yf$u~=abrV?8VQ3pX~5vFXXB@y)K->{59JmfxVw7( zmQ5DHiymgxWgYptx+waGw3$qtGF4*53lfY2HVS~}0AXX^8o=YHeW~l6ctC-2{y*=p zc8eA*qQ#Z;iqEPOA^~ifoad>W%!}f_C8ZCPh%cP%uw~(Uxjl+j!iB7@QqJ+L!uaJMBfHDA+2`8fe<`qmZ zFq<;EW|Ht)x1H(cb(y+yr>`bIy#L|xvV?_Wu3lU&d0|bE%7zUxmq)-dtzJdyTs=@U zq@-n*&782`K}UlW>3p40xftOfj;rilD`+CNsxdQFRCO zm#`!a$x>N$6!pLOIIo}(BW@0Qu>i_xyizKv+-2g-7mn;XbnX$&C&SxaT`ciQx$~+5 z(=JQ4ul342YjeVP^k5R+=+i=kO(jR0dExq6yG4r%7M_^qJ=qKWwxD0B+04-Sil{6o zhNaFno%;KZo?{)bf1g<%Dm{2@6@u{91C=eP20=Wp9?*6F@~rRw5H`V#F#cwS`KLeWKXzxH zUKH%BXfkzf-x(&Vy@E4^n^OXdXvuJo`xLS;r5$Vhh<@4scmlZzh^oBYac}Rj@`&<$ z7`I?=7R1r=JA?cC?#pd=IeK7BpjgMrFiR&c-jQd(R{@xdcJC4U?$eY1P%tr^hvYYv z(qDID>0|+uR;=x6BGWkG#qbR#NB6X~RPO?pP2<9_Xv6F%k`ZOsApf=Y%7Ii3t$Q}m*2MIjXPBS(;iJD+H|vIj2LhZK@;_gEvF4uBo2|g5KcJ>1aApixf+hhccz`2j z-pqTroH!KcgJwod951dfHdOy%*LA8gA?v2~@x;v+yj&T7KjUw#d;UMlA}u8)0eDLx zFx(s0tK70GL2Dps%Syh!-A5$ z#Vo*v-yHjTIpE0;z@>t2z}2^}$}fPzH5(MJPQbFT{C57M)G)&zla`(Q543v0(lhMO zyV$KVvXg;5GvL^6fNk#-0bml~2U#_t`s8~b0p)F(U#p!xgpH~@`eJtPkz|`;x+Gh+uLI;LS&*Xy?w08qhW+P0 zVdM!6*U3Fr3pZDF?~<1QX6ztlP~;g#FXwZ(-?#SQM5T~Tkp~*ij|og|jSY-#bt^k750@A$%V*zd2JA+0D1HJCEqfS$(Ampi zKG|qu^chx$Ex8LjChonpxVn0)o17%jfliH+Kq^~KbY2S(0x<-30)q}H&Y@Ve5IEro zQt||@2s9i3lA8$Ju>e-ABo6c+NU@6^Fs*>(I%0s~JZccJVf06SnN^W?s?n!R1|aZs L^>bP0l+XkKhiRR; literal 0 HcmV?d00001 diff --git a/_images/d122e190c38f57c64f87900ee69e5f9ddc764fe94eb3cfc6f5154678d1b51bfa.png b/_images/d122e190c38f57c64f87900ee69e5f9ddc764fe94eb3cfc6f5154678d1b51bfa.png deleted file mode 100644 index b0502d3eea6c7fd3ece13e823f293e264bf02045..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 149756 zcmeFZ_g~NZA3vNeWQ3?tG-xQ5N<+g)?{-SsLwnPZHnKvcElGRtrJ*5dFKuaw(jFR0 z^SZyB&-J~of8hG<`rOXvoWsd`Jjdg4Uyqlkg4{KVT{OGM$jB&2l2@*ik!=njBil5$ zb31) zyKO7T$!Yn2et^T;#+Z{gGdCG8LVjCP&6bR8pC0l5O$nm$revGQ$VgYjmG8ZsSaVQT zHh(j-=I-Fj^Zfo%MVX`Lbg2&8HVWLjaMZoHa3$p3)bQwqHJMWLg?X9M*50`{3{g>4 z?9UGz*mm%!A{W`_hxh$#6Oz_eJkng*St53wJ3if{ZhSoPn{y|}^Q6K*uKk_%q%8Kj zoe$}Wzbzy-!F9d4=C*V@AthzZHK)Dqay|`R@nLKi_#~+rQs^BynI< z?7tUy_~p#0h(p8=itnenx;5Z`FB|>r{`G%x6$kB#}|G`tPpUC%v37%(ye$|G%SBcIB$CX`HJ^t%A+zgO(x7(P94d zE^_}nF$WW}>k=fZcWkL+9`93(8`SQoy1*p9H1WR!$9zV<+I*>`iMAx2-lgXM{>?8z zreaLI7X2+r%p$bnOWe-{|D8DnA3r}z%7X_zR z$p(jpd|$m1v$5g6abuam^X}cd_Z%I$?oOy`UlG3Kq(8PO|;>#kPUEQ)B-w zL;qH_Ajg$IXUWOQi`>>|QdLCHSahUNYin!Yb8@<6YMR)it*m_I%9X9#wrxvLX5GH` z=zTRwW-7zi!cwE_oF%IH-}q|g4m{%Y{I?*F=qOTEq}A1FJUu-P3=G=x`+IxC;>&?R5C&am0s;b(E&HM$u?9ZxNY!XfR64Ex-XhUKM=MAD zEEgA-u>1NklAlRu+VRUz_f~xRv{@~v;P${~Q&ZEI$Azfm<>hzH?vh-ZKGTzYEV9H} z@o+*)!=3K0J8X|McWNx%q5OC8XDV3O*nYMr-(+NDRM6B+aR@Ic5P0|Q9oDnC$k8_1 zqjFzhK)~&Vu^Y3qv#%IE*Vk5BbIorKxuvSq{hb@Gsjk*tUHYA4*-e#jqFC7Z4}0P-_LX4$E;<-ZaVepOHJBo>a5iAhmgd+&WlQgznL z++1E_FB}~QzJLE>;1d!QRJkzTshHgU_1m`})6+gLUcBhzqw#u@k#VlC*tzPn=Rwo< zq(GbgV&}zszkh7oO~sxdax+!N(PeK1f1iS{YJ|hFY$KJg`^>$<(uG)QeYdc!=Kovb zf!*|VHXhf$l_+Pi`-g@m8_1cTr?Jx!@MF}oww8~V3mf?oxrL99&X`p-$Z)FnLse_M z{3es$LS8pFHzyLmAU*?+apSAd(7G6sze!hCY~R`uPVFmxjFn!rH}(6AiiD>g^^5u6 zEHl|qOqgKLFfo1F_R%Tu;Y{vQ`9@CPc%%tAtMbLMq-?K%IcgggXnwqN-|pQnpHrLm`d~ey^l6;f1r>CdnS)wB@{nE_IJ9qAg*((Uy{*p;aNg3LLen3!gpRSGr<+PR$|yuv$k% zbHMEPGN~tf3LZ+eFOB|aX}KQjs!Jky_PGWH1=)>!d2sUblQtS%SF53+p(_#+vwtQv z$d>0vm4=nyN3O|-30}pA#@kob)FgIT+K2Se@>_lGDVj>JO-W(z>FwRL-<14Qp45L! zASqFKr)})i7^h}JbY#&Fis>xQpHqA_2^VMQ=1?OCadnlIl}CDw&CQc@_T}Vl2&$7| zpM$EaC2Q;IGPAO74OaU~%^0O*WpT^B6ZVvd)~kF;yMKr^;IPBzr2 zZGJjfBFONBs9U|qj(udeZEf|x<(R5!XoR|?pq}H6$v@VI@MLBum+l>ml@2CT%`x$9 z_EAz%d6JrH5`V^}`(Im_Ay-y5P*4eKxqmTt@W|)e-^KP9`dIMu^A{Br0Y8Zqw`S^i zJb%86I9*0Y%w!jx|C~2vUAcVq>eaWxj+8t+JVp&~43#rZ*Kt4Hdpt@b&nnl*X7@vd z59u5JlKZy~uqj+@@4Y?uOSZfv%kf}X!*Fm|SOZoNHL$#;#c!beDQ(KM$@7N~H=~q4 zj*VrS`_;hXq^y*xl5IOI$1ML&)0jE$Bnu0R(~1i@x%9&sfq(F5;NUqPbIk!Op6qmI zsT)CtKYso!a9-pf@$jgClEjk{!KT%OplG4&!KH@4fNe7)* zORatT_SmJ%moxM7jDP>A*#4ovts+2X>Ki&p$ZGz>8GS|q{5_Hvi_Q96u75HyQOK9^ zr*xg9-=n-miJo2~8?3}B28K;0=!4}?_ig+bWBB#!7v+Hi;-;o7R8&+;fB$lswIwjS zzI2%GyYs7_`t94ds#yjk55bw9QulD)cX#5e?}IHn+=3XxP&sc8Hy$@oi^EdL zyuHwz@X|~PmF>=-3AH!;){R+)bu_D*oLYsbh|GpIw6i}db{F2AOj=Db7h>7je~LsE ztcsdS*D%?gM_hDVKvi{h?)r4UM~~e3oi^TG+}PoeSF>Oh91!q1OvphYxgE{j#npAR zCARJw`Rz6{-sa}!n7FvjUt*HEkGkJXi%x-yN|s=SYne$6bL&Xb59K+8FH z;Wk+Uhlz;G(u|X{MkkY~X!x^dJD5@-%bI5Z;+>w;1=3$he9 znd@^Gm`698%uA47JbzyD=Hc&$U)uiNtS^sRT3ZFspL+}Kqb%hN_mi0!_o_!*<3mJT3!8^^jf^TkKG;Hi z;WoX(MH{Nahp*nf%cs!0=!DO-5Y$f8qd$|~Cg*8zP>u@SwJ6pyYP&&0IaR{6rgq}6 zp&5Hh{cX!(vAmNfRJ*D3I=Gma9s?7hAJD3#s<)3Qc6|DD>CaSe-Sfk2Z!8)TBS$B3 z?jia=T3h-qt|I4$?~BhVJ0i0xqY0hBFCH0?cB?(-vx6B837-*PWzIy9ZT zTYt{``0nyL^R1?)YV0~Cnq7G14+e&YT#hztO8u49)z$QZf^TMLZOEMFN5rT5ihT`3 zLiw#{$J*J*hc5r{7)YWwD;(%_v`_t6av)BOhtf~W# z(jOm<1m7}wgu;wI_#`m!uyioTP)n>d(bXwv`Pu}pCO4a$;oyi%NqI@~XTCGuvE>av z-IG*H?$J?eUqfoOpuqdJot?o#4pX;(|F~M|L)SlI`)6iGcdDmA%${o|B7*+Cb-yNfp?J^#T%Ad&)QTLKE7G1XFZ*>Q2vQh$0 zx3s&}H=G%$m}HM`y4q1|5Pvv(d}Hn1)aC9Brvq6M>w$pF#_4Xc>H)6Ex6ZVe#A z=aHH=CHWB;J2Nx$B`v=gfzwO|eS|H{>?kt)fV+1dJS z35w^9N8NA z=HCG|^L_KC7F=btIeG_PU{g}v=CBKQ9-^p)3h(+e(#(J(e$~ZAxUa8Itl^I<&RUV{ z3f0YXOxDX_*n_wosiVjJcfSu9UoJ()Gdta ztok`Xa+>b3`qx|@*at3C_Y|>X$VAC!8;mVYb zWLW?ewcoC9cg?+1qX&kS!sUHyv_f-o&KI-a6W^ai9M?zILF{#Jg&e%=>t&1@-zFY8 z6B`#tNkdbcqLyvao^&Jn#Oc$gpQ0u)kSKu<0NThBPUN;3J`D~GJU~rNGBab{cS1Pg zn$HP~uNe<;|Ioui)jddI0=B}0t$0Q`20iq1K za3@Mz`ZA7?)BG6~6&0@&fo()Xe{qC!dlFByeXQXveSH8~1`&}H=H})S-p6Xdkp=F} zM6|GdYijbrrR~&UKdxK$aN9BAd;4u|ZHp&!)z5-F3A?SnMp2J&T8jeYMSs%&RUfjj zJtg;!U1sF;*SkHX0qPr-_Zh{<_@ApjDj(8Qa7Rx>uaH-HR)_D-vlSRV{d=MduVjjv$S;M8cSlU-m~NTrjJB6 z+!d3MNMh2u=J&BU`k;TupG((6s1nAx3p&$vHpsKTF0|iVQQBW(NZgTu&{uEY)>phZ zGTNRTe0{Uzwd8giKn4p-OSMurSAV13bfRv@uhi22hGkO9Nnidb}G$Re2vCo!4CPEtN;d6v6>y&y)G8{}(=&Wx?z}_TRUI(UiEnAR zdeG{OV(9gyp#MH=EQlUafjllB<}q@L_A_`c{Z8My^DxQpi&^e50h_HmcI@D@`1&QG z%Fi(5wEVl<8|$uQnp#>Rg7&PS0fQUs{TmQ@c0&iSPh0Uf3;`PkQh4U&#l*?!Lo_#& zFZ2LrBi(tN0M@)tsnLuim&INOi~f=@+%mS-e%aWVm`AA9vF?9CGEu&Cd-5}Z_br41 z&bd6eQzQOlgu4I@`(?Uy>w6Q6XZywPcZG(1oWyqKR$CQCtWD|a9UCI-qWZ1 z-1GY@<1Tin_~+YJy%n$x;=AxADJ5lad0{*zJ|3mvqSL%CdUx%aK=!)9U%yxvPL-FJ zQv=#4g!TMh`mJx(SCkk`Jux-q?c=i#-6IxN7bncnps}^pAC+^QX@C1QKSnf%u0ngZ z-A6du>TX%T1i`&K`K_YRe*7Fi|7r9Ax3%Tp%M0d)Z$5C9e3qF)J&<^LRB?RmRJq1d z$A62z4RrySy~U}p=HaC1>xrs)R>w8oTj*gOyc)gJl9Fz9zqj1FeLEyo5~@F-?8zOEl}HF_0`T$PzrJE%*9LC{A*2G>T3) zw|!N~t540EJ?=1l)Fd{{a+-ka_`!n*4{lLDT?C%3#^SQRe%HFM=p+Y+H(DoI zns#yRYcBnfo&uir_4VqkdPrV@t^h%!Jq6iiRk=AiF-b{MA#XapmZ{AuO!jCg6gbWq zsider@bK^;t&D@mKuf9wvp4RvVz|1=G6@^PVw+~)ADOyM|FpUj2^EKj7M}n$OI54 zb{o=NyLJuTuLjN9Op9{~*Fz;uGja88aPUq2wI3_n8qHfjI9Nl@2)y4?St$|1XT5Xx z?%hlYn%PEP+_kE7YC&C@`a7V=w9+1@*u7gHZ5ljTjPtb=iNs|(`7`)k&GF;M8z9P# z^+>!_*wrscps<0Xbrnv zpE@T(_nz4;mHbSaGa^4~mxi>hQ;yB&3T^fzsz;oJR0>_7ysIlDknJYTu`V_ax9tgJ zsidkPMrz~XQ_Bm-Uu0+7MmO=YvPxOoadUHLHBNm0mSfT72a%Iz{D7=!g(@uye#y#| z5Dv16^>7HpIc}Rl$>PnUX1Q;$F_~uVtYC{u(T#?Vj*i9A;X1dN9rO2n{VHGvC8UV>=vs`w~{Qc(U zQ>XlOtNs0cc%0Xe~=?8gX@LaWy&oJ-i->4Xi)gV`R%StX1BSKeExeKL%J31CV)R=s8_rPshl^}%yQS;K$X18y zf@_!M^kZXVGu=1b&;VyDcKDM)IXC(eA--UBQ&CaRuGvw1iEBA-bL}gk#MSk-g9c*J zysH(_AJ$4aN_5Q){K_n0^W8gj>eSa_XZ|hQ_ar!MO-@RBj!tJ|Ya7BhdGn}$ujR8B zb=BM7P43&Zdp88Z&QR}C`|+SMnW>xU+U-JyskEM`yh0#p%^%VsjN)b%H4pD;CrN;R z8KPvH1DQ^oHRfCWyuot*ymERYqw*p- zouHkGmn9sufHZ*xXo?A3P6;21v$C>C5*2U5!qhT!H+AP(#{(N&fHGa`zCqJn@%i)j z@$nZ@v8R}sC9G3TTtAhUH=CSi*DlI$9$ra&rp79Mu8*JR(qGpJ^BiWk3kk}UJFMef zVt6RGZu*X$1GG4<76k1?wpb|v+;yV&LohU|Aa=D&CMIWg>^-K7qq>KBb%%^}t*=S1 z6Zx-SUK%SZii!`|>zt@t?YA*t-xrK1I*lQUpmG){R^1CnA;;JLg>JO{+6`VB3W7;M zSA;4t$~0P(9usqAx?q&M0Bq1}Z&c|aPVJ%ut|88y5B2&X3e@3@Gb+`wJEWdh4|ye& zo~Rre#LK$#(i%4p4^bZpXXf0wFW;YieLB@&+Js6?E#h(k1`yVl_#y}P?-zSPb@mL~ z+$o{%e8vN6+l4-q*v&3?R*D=(?OoXAe0gD~S-6NRjlHJUC2y$ zs?n#aXjuPt1gmt#cXPbauy8HzUf>&TeLGnBtuSWxQ&L`1RXvJYX9U|NcRSPc3ooys zeeO$J4j(>DD2BLgP(Kb8b1uULg5g(<{tut^y=Bl({s}5A!3`>nZtn!;4oSalG+q}c zzoqF`f4?o^^UbH&mFMnMkEeR?OvEfWK`zyAD+@mfzyL=yuIraZF8{3Z8HU*9<@9oC z=^h+);OrzD4czqKi;Kn^>uY4kMBM;tf05mW)?REW8W0*P4c))2tV~B1Y#tgCW7p1y z+K;s1F+@nbx`@%lh=>E zeDOlbDHEz?t+h*BYOLK?G{9EO zdjG(|x##RmfSYJ*KlQ+;ys6NgXEtqq;$*|aQWfKB!05&oyH8Cmz2MHz?O=tl5&QrQ#w?AktkSkV zTVUbfVCLcRZ);NqCV=2(To-iKv?HbKrfV*zi^i>6xANULM53?xK&0i8nDqDeFGu5t zA*hGtUtR7jO|#cPECA-*QGTmq_~;Vh!Nf(Q6YXGAF1G06Ce-NCQc0AoqeO{4v8 z7pkbv(j2#Q!^?X}lz@#>7(K<7zJ*>9dPub;k)>QsBN!+?ZGo8kaI|7 zsK?I|s;|V3MV-RRyQe50SvT+>RPbK7Ti#j`)ahuLOU3IRzAGd9RY>25!*^9Cp=APc z9E6606@!cd0<;|lqkm(0U*9_-zyaM$Ft63*e3A1ap$=gsF2i2Drt0>TF5A{7boUzGcb z9LvGT37*ybz`(+S9mN)%cMH-m*na}R*oGq~0i}g}&z=;XkrXeErDX+Jw)bWS$)~2K z2-*Pt)TS|e8gGIU*`B`!(#^Z;t$TIAA{ygy==zB5*!--d@Oa#UKCH^1z!#H|@e1W6 zORxNiQ_}#*Q7t8zT2N+gZY+>4AwfCL8blb$TX{*$MeqDP)mN-B-5*82bGansK4nDl zi{tTpd-Z$QKL|T2JqwX)+0EX-_@(;$=&ibr*b=+D4jE|_a z^*Fh(TAU;-+u+wseHbd8f?@Cc{H~7+N^131$F&sL8dFkIjv!r-ntce0HquP()CzD# ziS`QcsW3f$h>ng(xdaSHYOn#y-NXqmCsZ+@L*izFxz!RZIugrH;S#6g{piuw=w*je zdCj-G`wOjEBet4!_XP2X{{E?LCQ`=lU*P-tGU+i5xXZFLUwP_x>W%k$S+fJWrlvIx z{jODycONke==g$NFhm0+J9OyK?e$eh2v!hm1%6g~B`?01Rf4UF0(u;pmQ$wy@1S62FkhMM0l)beA*jh*jsa$|Y$URT&lq8tScCZZ7<^Md#1BZm&{ zr=fYyUI)>S0$&ko2>HH!#(!srB)nWe&|wSp8-$b>9uU2JcH!9Zo@P-S)1gXWMfBHJ9C=YCQ2yKh`H%cVi^ z4UUG}A#*Q403=b$8yXrC6q}$X!U6{YNz+~{+Slpy-lX{wQLcuEkroN&(E0(31Nu&J zUyL8D0$l4y9v)kuHk8-aKL7FK7J64BtZxeMDQZe8swdIW49HiRJ~UQL1xp3Ce&2DT z0fmkJ!iCpXy@mM3)hHGVab19&bx~Je?3vO)7a4wh9ouylA9Wd7tM{I zBIrPUC9cU1p@`>T|KaAhB=E+AJD>~6SqE@|y-;6;nS2f}A{AN>39qg5jJ7+SXetCFGl@e z9SiNlTi=@>Ie>etj~Jl66)k|ajLaV7Ax_fMi#hJof{g>+8Je12+nEsdx?_TN&rsTs z&q`-@JR#W8(UHqB@I|fY9v3L7AxaP7V87^7Nfm)Km^xY+NWesfSWICEW(Ij=E6F*@IF^t#8x49**< zDBzyVllt}MoI6GDo{BiH3m~IeVDlKZeMeyf{7O$BAN1=n_S;Ik0vtxZh$m7Xp`&X; zp6Zoh2>uQmW=?i%uzhp;cRO3#jw#BVz{v z%W|xG)u*E-W{2wP-|)VGt)1=i*9Jt{d;;eBg~o7Ec?*jaQqyo19H#2;(-Qkjn6M@h zxUgvbogc#T^7xU=BVJP`g!?g$bLgrnS_-f%LmfAPy8BC9VUGZT68`mNxsA|UIA`~0?C-jIQ@Udt4?YfI6{ErZvx+@)j0-fstp&7vl43kuyqg{2 zO|IQX@4FYjwGuZXGb#%*ULT}oAXl|C0mv7p#u+#iAU_hE)y?7R|62Gu8 z%eMD0HV|TqZTK0$qIBW*cOr~Kf7fttD5!W}ko?nWc9Z;%Y zT2?1ZvhE?sy$VfG86Gacmwh||;B!T5d*}Z8WrxMXvGf78B0hD2>88w`k@%M$f?+9%W6&RI{ z<}G)-$@#atKZw;HmVPBmd&gIq(kDHZ=T_vM=z>jC85 zeIVLp7}imN_uRDJEOuGo!Ug0)EFzX!h0dQ3z`;j80Fq%2iOK6x`qSLp+~(+a=y2bc ze*Z)Zq=DgT)stW5Mav&x$;!r7;4pmxv8@9o2gUW5=fhG0Nlr6qefO^i8SXtHED7Ng z#PMm3PpdMaF`Ye|>M+@jY;53l$!z1MU-)nJq5S)BT~Vcp9wsg>z96DaXct?kzF1Rt z;Rpa_2BwVd^M6E!6i6cIH?PnNP7{&AnxD6eJ)H;UkA0DSFX!BqWe5$ZYLGFqDH2&5 z-5saI_rGMIa&6Ox8>(@vqvFu41_&jTcBq0kA9{^|>u zC^bt)Yj_Qdg5V90&0uvCjm&01lowS#be#na@TnIBZ{?b`?*dB)YvrGI;F_(jzs{Gs$=E z{0R9A!0F+`hdA?be7vOZgKclZTC*J=0R8h^=}2T6|1Pvo9sU>beFhe?CLoq{zfKw=AGWiFl=tu zp(*^>QC0O6@bfvZm?$L_9|*U{V3v6dB}2rh!|5DFnhwPE{8AzR+_~ZmTVCpvItn?4 z;laV%Ai+TXD~jX1Z+@)Rn_jjPe-hc>3~6EK-o2IIzP&+qcvJfVe^a=qwVjZP5-);) z=(_;AaFfp^{cK!GJ!)@Pv37)AH6m|n7KN71vQ72>9a&K3{#AMi87bIlqqgBs=v~@B z?~FYFmM#ab;(x3T3xhB#p)uo@ycv8QH-;=U&eUmodNTOCsHN8w6!t^p4zH-T8a!t0}wm-0VIur_4@@mvzOw{+a~(@_Z%_?asKCZU_7E&my#Yb6he5sBSjdh7}rWp{V(@$^5jVf8s|su zhy>wvB-(vbrtOg}dvG-JydTgrLQR%_w~BF!(W(v}K3oxb`KfA#ZkaLl$pA)Abi`)N zsTim+2xhU42(oZMj|f3O`Jq8TI2aU&R%Ah zYk$7U-D}Q3(w)@xY|7X>&o#F>0;4S`+H;URKrAjH*N9(jL`jtQ%iB5XKrsZjvsW>O z=?(E{+`flez=jbmKkc_#WV;!yR{S|M2*RP~StpO4=IMnC`mMv5JFggVp zJ;St>8Lq(}HJ&|8BqDmc=h%h)7^A~I!`&_K={e@^zQHMSc}~M_ZP}iXz+mRjOHE^q zAzJKGJ~Ch>DQ}T#dGb8x{hs9w<{@{gM2+M`7^kIlWXMHxazzS7^s!Wr30*_p|EdbQ??8fcy~1g(RET*t`mf zAr`b!!$9M1e(uq?wkUtGXL%*G0}>Ukv~?PZ;T5f4ADc8 zBL2cQip1NbbK#eg_}y0vh6W80Q);2K=kcpZHqPA8Jts|d_7v1F0$Rv~2?i2`F(&pT zgmH*0TN30r3Sl~-7hel91poiNu&`#}>X)mYI?JyWjFkIW?u&W&lIX#9V{IfyI@l1| z$jB3x5gf*vrbxt~VJ45s#ydMY-kItVV2V&qRL)InT3uh6#_S9OuKTc$`zk|8NeS>9h4(7Amt^&UM`lOVI`Io%Sq_(f`VB#LsB>hm@9(A z;EQoGguQ6m9j^{U9eDKQ2{At*81H!ejmFO}Ma%0#O>GJFOvE(7_3M;cg?2<_^Ee#W z)nWJb(*(ys9Bm$n8lkM(}wM>6}b$tEUc zc^>rIHwcmVzJ9&bB|0Ax)GTtXXE6Wd+@aOdO2C0e^bux}Kk(cN&*8 zGB7x5A!~wE1NICmp`W%yadI*nBrZUZD~{o9SK+21%mAoAUVLuu_wNBrgVj!tti9`j z=!nc10F5d*0KyecsYemyKuwkPGwuDVD2T%Y%`)Mx87K}y9|@0 zhF+sjacLpAk-So@92^|risaw>eJiZj5_u{@y2aS6L~#e?EkuGgwTBGCU?OtL*yi$EIJ>tjPkLrN2z_(0Q&;0>)o)G!IepSt!8rkCO z>kH9ow~meu@h4PNs6bZ`0(yc4BJe)*Ze})I5TtHVFDRzEC%%6d!}J02)I;g+Yi!6t zRY6w(IGr1;IY^8cpu>AUdq&U7nnY?`aYbFhu%a*VVg@yoaI=Up4%}lfoG6vfUZqu6 z=zUNO=2rjO7AOAv))xGk%ee6v=3oI;&zg=5-&&$GeTAzKB>*;Cty48> zunnBKLL~Dbf4y0qW@BI=hAt2hOp@4^P?%!TJ7R>(n#GR0+=PRI!$M2MC83aN=HK2# zWcI`FDJdo@&rkR3jIJUo`3YLQk3@7?bF;5vw8X&3i0UvGG7FY%^Db6aR>iTe0eKM} zfQp%cRV?-sN2mM+)DHVs(|Yn9dmUl6p*VGR2Ysoic>G^Zb(6BseoP*>t42G{k2KTd zGTCRdVZ587DGm7v@4SjD|RvF^p@vNuED|GV_?gYp!BpWi@LV=G>{n zMxwfWm0}h3i@7cKR#8W^t7eG%)NP zAL~({=g$e`2v-FoCvl5zD0Q5mOUe>|z=x0W7`@bf;%W(c3I&G(Z2ZRNVSMfJZP$qL zEKbgSqN1Y3uF}%dL|Pn>Aw@kmsjrH=63c_i@8oa%ycAvrcsUXmYl;tR(N(hzYWyVV zR&Z8Pg7d|Bb;X~Da$d9oqgkk-D`g@1JxWjK1jjRmF@PZt z0>G}XtvF)ghDC~fPO-7Q0B-ifGzM-JNluPXg61c?gW)*4=IGAChY1J>$be|D-Tgsr zRz14%2+kU&FFw`R@9~n@GEz#1**!$E7%``CAEdlB`r1Bx%PN4&(80e)>+q}%Ap9%{ z!_bVbq1EDQ614$v2OFE1mj}wSJ>*?uvy(qnZpUj(1R1Og@SYifX zV-nl^6|~4t2?&J172(2Q1@U?=E=4w_>~$DTYv0KnDHy#Bb|fm6X6@=kO+N+Xca6Ksc3(>qzvEXZsw8*7Vr?u+YGD-Q{D7}T5S@DRK)=~xGa zOf~XoU_9hDsyz zL&$wy_`!n*I1bcd_x;|zlY^Xry2-2RQkKqV*Q5jZ%sz0rR`@DT4!tIUZ*(5CNvCgjR2cD7hm^*pNv zEM*NK6tWukF-nkuq#B}bo>H;I^G7H|^5Sm8LBrS{pzt;#4^iXC1pZ7+D1o8*GJ0;> zvi%DZCxAX=G?Ah2a3(Lqy& z2<~Ab_yK&T)@fFai>FrNA^`tp!+`WyHWEQF0OM$L$Bxq{Pe#@(JGh@My)3@;^@>=R zB;Yf;GdG@R&~z6owwD;(gBa@n`t{d@TP-@=5Y%F?5&{V^QID~%YTB5Nu?4YDK^W6h~+v5B47a-;`8S#IC)5ac?mW> zfm#hwL^C9`HN)Xie{j{_%aD*;D*~3++>W=#W=mm^*d34-$@*6J# zNP!2qfzu#_*5Z~0OexV7+6?VNenpBokCEhbBuhj@gt$Lg_|7*e!59WcqJcGV7w{4^ z#bkp@{>u2;@d=b&qzoGS{aLQipV=uZjk52Dx5X1MFzbStDomyCfcv-zGD+o&yf$`r z2FU3nzH;u~j4s+{1!^||6reNQN&f7PuyJqDXU%3k^ zPS>5sH#@8Geg+dr?Ck6qzuyn7FN)AA9FruFpCRBJCujQh+>0*#XnJ_sLu5_t3xr58 z$*bL~8Q zBFA$WcV23xWC)NY9^n9i%q8dZE+uGCJ0PeNH4Hts^i9R07vyU^-$<2AIhf`z=q}tS zIJ!UJ{LcSywlqCFeYZ05Y--ZpQ{##@JX?59vt_9V;^z;--T)zakj$nvFhb1D#A&7dP*;W!MDE{libcsH?JRTT= zcwbdjyyCFsE>IFj$AUgTPi!wJpCq8Uxy6Rt?PwD!W+FBBlaC5HEShEixM#yeAWkJohfNfX}I2!eld9#WnavVlVFk= z(rhS!&*inWmZS|vf9t_moPTgSa-L9GEjAaLmT*4K&gMaQdJs-BJX-gu*1s`Gx5U~F zn<9{oK0$PT)Xz>K-kW%&nx$f_Vp)vb)ZZ%)?@mO5YOc-(ml{9<3m1M(WRqHK(lg5j zacMFzL@|C<>xkCOl8C5iDNRTN_TW3TBd5GBkYj)gM0TX{m@c4CFF^;Tqq`(9-efv+ z>^zNEnSBB%A`!d5#&SW)hSwe$z(}BNJaj5J_!@+Mz}ExF*$p7CEPzuU8xisGyQ3G* z@Zg}q35-Sn-r->``-*k+qM&lYIx-APItdjR$t~IG_c&>^#}4pbRXW1U9|W|8P?3V) zM;TwlsO&tMVI#qcXU3pr93z7Zi(RiEq%0_#X&J+&2WF6!ta$kOjc2}>@ots{iA0+fM`1<0K>2x(I|zzDMjOCB`z8zbs?t68 z_D;)7euGsivw5?{pIevKo<;B|;wD#U;q_AgZA-o{7nVdiV8VcW&qp>i+lp zbe_ztE%x)cue;#cAIQ0-Wu{6*LoCXX$csQZLE7TR@LZDo<%5B5K7k?LxqX{nSa>yC zxCFsZw1q1rIf_zY=u3p+$Y=R&Ud_zNjRjm6HWNJ}Oe|lDu|Bb)PKGw(3nMX}jEqv# zuFHZUh$mchPP!&xPkxR9&Q=9*;lBZGAu;_nszYz)A*Q_W5tJYC`lpH)vaq$W|vct1`rMiL6pQ$R1Qo&?frXvCTn z=1XniaUbW!a=6gD3GWwx&BTswo(RTSbbSJh549^!jgF2kdlY!}1r>G5>5-wKtI%TL zvJ3z~@k(3_B|=|&HH`c&zN7-j84;Pb<}h~{{Hf`a#GD;vT!{pO#7nW{b{cm2jY!mS=5f6= zhQcGeiAOQ;MWV~OAE54kf|r7U{#+vZB*IiK{})T=9nW?9w(<7V(xjmhrJan@&{RYu z$w-Q%$VfC4DlL_k77~(`q(O?%5FyDfLM06S^Vu=s6% z=kDD!h)0x&g|Et)&hgK|t}?kq>RPrd%^okaE3f_2(UEJS79W#M^r7F{;{AOQLMK6{ zA}aj6kkWh**jJ$U?!SBje}Gyec#qj)3v(9D>FZ>-#77mkZk)ej|F2X}rIix5y1Ddj zTwI~4-;X$HyfQ!oh=x%wzDZ1S!FXXaZASOTrY7K=!W`r~(#&YNQ5#Vwn41;*p3Jyn z{KUp6^Vx^UsHSN$94sQSdu;u+ckkX&x%?>GQ6Xj4^_B{9qqpQ8%A??1yGqVa#P#bl zwMy?;>w4Obrq0)bH1_D%aw?DcsAHJ8h)Dxye5i}Pj4MQs0IN&l)Qg#UAY--E=o})SE%d{XlGLI-WX_^(x zmJ-O2^Yx)v-sCvSD%vpWfuYWdd_@o>Fzn(|-={_bz7+z7@Cu+4#vQ%MaZEgSbgq9YIpTi)5tmt0T1@Cdx0<9~F-rG!7d zBj#3oyn9~4dF#fvH4_tJT|P0;qznlu-!@{JMJJM>R<5%p0ZaMc`MR#BOnWnr+6JgpUZATWha>R=;zco)eIsptsp{#f)QabC3q5z7 z9k_bEedOcNxH)qU#fMofNtam_-d$5}y?X4x&erC>v4JL`Pp>3S*P9bCi^3~u;un4c zk=?jnQ8G);ob7ZJ(qm!Mtcl~tTkt@H(*`r6{L5$Cb3Bnm(*Txzw)`TZA_NR+iE+3; zJ)>qbmo?hz?40`KNk~yY_-SEVKffF$z!a_tvrU&S)@dT{MOv;96HtgMu1)-4X2{tP ziojQ7VRjU`9v1l*P*-bN7NcXL{<*#3g84H1C0rpYleFl>K8^X=lI8CXY*^={5FdNy zn3ZJl-KS2D-==;qLn2eBjDj^J_u`wQ)8@Da>>Yb#}^I zw$pur&&Ltlj~l=9Hr<_G(x>&@t)VZ^oGF!x*p}seW3iN9|LkLJZfB{+hiuuk+16GV zqWtb~jAI105p-dZuu%eIVF(uYEA%oVGtoH3+nf39**qK(7;ivXGcl>b*wl38iuF4; z6zAnhdTUtTtY~3^KydCUrkqBf5aJvZL_RuZCkFBcXRp9a;d9C+IM3FNM(Ey2~!PRTVmErb1zs!3UE;-)*eM zp=m5}_c55f;EdoUx#UC|%2%Soer~_x}29?;&|$ zim%ba#(vHS0Ykc>y&=$n^8-JdI-FbOU!))A~bxKp~D<~Abm#3 z*xz~msvt)QuQQ-O6zF>^TK~i|lsrtlP*uBl*2)n%}U$$-xwl0 zp)@dQFpIMpNDm+k691$4XgW|r=i8bYU1+e~B;9}SwL%+ef30=v)+NO)l^s2rBCz44 z9nNb&A~SaVy85W)PleXIwKkVm6wg$YtXd_#+-k`8XO>ItYRqcR`1&?3cJ3OLO$7Hs z=ceW9CIQM9w|y=Jvv;>~>iZcaqnhz1LC7PaU5AK1)ojm_k~?o)d+y0n+@x&s!rpb! z3j1ue1Ljd$6DGZzoO4qquSdrFK!-llyH8S#xYn`VvGd!N%=3Ejq^LitR;Tj$MTMM6)eF_7wcQ^}yWD?-~Fe zw{jvw)E+XG5eH3pHpIn6Z!0BatwVHZyAD33DHxYcr+FsP&o6)8psnzHr0mu#@Oy=+E~5@SM_=|8|0$rX-H0=4LZboY~)_ zhmYLxXiwQJrl5Uy6guAgp-gRL@$*`!l7DXZlNG(My#D&)RiDj^!ht9T6FpZHxd%bS~d;Y$-0zHPvtL)Fq=XwbUU@-3w47UEj5Aj=k1H31<3 z$Osj3QMs-<<_ifo#OCcwryc%O`hDg!OPB%R@R`Q$}{t;9oh zHLg>Y+_p4FwdKwtxkoa8%*4c(x~*{c*8Bm{LsAxDWwoAk0zvd{#>q(<<2t|VYSF7| zi6Q_R#eDJAj6O1@`4Ot}@gvU0{rK>2XqV+Rd+#rPV%p}`om?rU?*2g0F7mcwy8Swr z`JWFwHkBAwtLb4k3u@k`siyb%NwM&v;4Dmo!Hz8V9%Me!g1oHkLWLH^br1JShi-y? zHiM2UDL;&ato(0F3PL_!XHrn!SQEQ|6ji(_Ab0Xf zRE+w>Mno*#e2~$yy^rgIDex*tEuiVW9v-_sdQ5j8jd8)Qb3%(UJgu@03BZ@Z9R4`M zfQ=bR;gA*eKYsijo#>`~aK2|3%9>uoh7I#mI!&~D^?7t7P8{@gCsQ*rzC_t>KJVBN zonda$?wl2;=y|x=jtl=(TNiNqByb2e$;zZ}pO~d}bA_n})yyO&!Lmw91K>^YX|j<# zkOo&4Wh0UAJ79ol@G*&^+dFmo^dn{{wq|$6X5IdE4;gT61&={gA@^ITcNpX4<1Ga2 zeB%uhYk@uAymJTt-n7=HCxH_tOhCvgis!iRb#EVaT-J1W1&#*AmVqWUQs@=%AXDhqKw4%kfsLU z)6cK(j3oecIVoJSf$Av;)=}b69hHAhKU{t6fO_-0K8O_h`&e~1>3K>!P;Y$9wY52= zFx~;(JItd}1MLTwTu-4*BtN%Y4LA^Hg!HhjEqU#UtoFfa2op#XnEjQF{Vl znQ^Xxp<$6}ns_qU>`dSD*OB?&5pVBMT7b-w+35eM)UdR{0ps1bZ)Ua)L(Qg!HnkmY zD{5)xlyKIW6XYi%?}BQ>*kvZws@A-a-D{8>nw+$Ip0aBEe^~`QJY6MKoyPSY*u+@*$&4}iqrb@lWg(K`m{m$rivNPx1%i175B-nO7J@m z@lTv*L0OlT1uyP!ZHeDXef^874r|Mxe*hGvg3fEt4%eN+WQAUk#Cq1M2i5=PGbd(> z(F=f=`ZYKMcD{IEM_ZH4WyeOCD$~2pP zr0P6Cx_0z?)&&=M=#h$@lR00g+=Q|R03FHT@syTt4uZiBk_Bs)67UfcFYZGgD4Wma zbcR_!e*Rof_|>qRlBEb~`XdZZ*P5ZToIlT_qp8+WY&_-ZxiBC?K8(h}~2yrCD9J_jO0F%h}hK9G26(!l2q2sE%;P+z}T1 zs=Ec=(iQO8nAU48Tei9M?j+u$s*%;mS+hz%q~zpO5q{yC_WwI7!t%Nq_(9@407xTO~nGB4MxoYKes8=kFTA z9||+a>rG8nQ#>*Vmgg#c(G1(lW@Tj|`-5)X6)c@nZ?!|q0~*jgruOikt-r3s>Wat` zej$5emLfTd8@o2f`2;STa9C6}Pr5RS|NjxhHg0>f7%tOlL^jM3IstwoF?hwjaXon) zxY;!3ZxdbDMLh8|Kdsi&+Y5S4+!KUa*Y;M3p*VtCW(yad7&dbO(=6}mO$ON1h@SMi zz2+Im9XrzTBldMFlKXUAdB>;By7*18X(=QfajPDmNSFUE7jiq=;+Jj`bDowZGhRvM|V7!u%zxdsiA}JOVuFefT~VZ z7^1YG4!Ry6y>1~45(e`-aZ0YLD$J6m6DQP$!4=V(>i#~pJ1LHsq!W-{id#W|oebf; zdygKYF|#e-cI^1^R5B>)otsP<31mx{b;Bg?tMSs?U0sp@Z0K4ckw@;C*B`RA?ZXpv6!;m;~FG9jd-^TmLwqjDb1OnGo> z{qLujJN=CtXKhf|K>+vABt=b=WL|!WD3Zfavxs^Uq<+(k+$AE*yRJ(2Dc_W{v<+nh&&xe;_nPxDDEvhFHY%L z45gq)DP_3cECI6u#J^fRaB)=OuU}QmFwu`be#Ht?3fMRwUj&$1PutF&Ls7mJUeL}I zx+~`FmAs$0yORq<^-Z=DxCW{7HZM+$Ynfo5k+VaJaYkBm5HJ7fix)SF*4<`S3ZdhR zl@kjQsD5=UEUw%RfSk%DR#Dq2_?=KF1u;)dnP(Vpn^_TuAJU123u7KVn|$N=-JKb~ zLZg_UY^1$Gx1p=B#Q|k-F?52Pr=X--NjEdA7mVh{-Oi4V>u4wExr}P?Xlw9TU2V7> zlVaj*oiMr^-|}SZQSit2fQZzw$8U5k8Gzry+M1_$nn?-TD5FE6oKM@GGsOJgr%NOE zXpt!T3;O_^0VJfAK8qW+c21`JmMq!I%&wa23fE-c`L%4ujFLK!)||F?92b<@18E<^ zw0(a)U0(0-`u0I#G%%|$8Ut-1IRcr~v!CVkp<q$Q{vwgAIRRBM_^WS3k2s_w1bo z`?NNtZ3Mb?=@89Bth4x;uHM=YN&#l3&nPX_HFpIioV{@24(b(-uFk4e^^3i3)SFT0 zpR1cNWy&YWF7-F&m&Mr*rf{BSx{IsnnHfaJLTKY#tQ(R>wlh1^`@ec*cW{uNi$F0N6Gn3ED%6j0mepkU)vwerh4QNe&onmhE&f|)|5fzvYY zyp`IH@7fgk=ZdESqwZ=EP8iJSZ%-8ZD0G{Vs#?+hTDscWW9G~;iy09%G3!-nX(g|c zV^K4_Or?+zkA7-?zNalH-`I6ukA6SU zb=AqV443P#Z3;7dRovg6dLsi&BsiN)eT;8ebOsD%>b%0p2w#* zJL!YL>E1&{TE`4fBf5!yxfNxaFrQQHplDa3B#7p;K7d>g8Q21iFcW?Tmg75h{eo!Y z4+0~CZ6(H!47DgkXQ0EzK8--82uhlh_b9cbM4Dl1Qq^$&nt>mE{5N{XhrV_<$_!RQfdmRBv-mVc&S z|07+!P5)Av-A}2)L*Lz_r%qoDLvj&aCUPFE=SQSFcXdukOwS&YwZMLWo14 zQ)bP=ug04S zZr#5osJb~Gto=-IX0vO&?{_dgS{QSAMJD90L)51&4*G%`9uL}p&N>h^0| zuS~KbIH=GZBgA~XZe5gNlnB&RjzaJ$7ybEbMM@ymeo?o7q&$z-y1;YF`MeX+&uLE0 zhbTQ(QBi;Mz-nyL1XS;F5_A~p9adDEZVojtTlt0d;Z)z26(tGe#oI7GP*|9MI^*5o z)lcjH-z1AMo>M<3`*nVE9$BVfZwcva8e36WQN9kO{;F zLK@MKrG25ZyNHK9*PIz6^zT$YG>fqM+hhGCv>59<0&m(n~s(IoGYbcSVB8%sV6sU+^uHVgvetyN_&5SjYeg zAobCsebhPQJ%-xEnMgI3p_yS&Of`N=oY^VnH@>Qa9z#NVLAOAosY>$h(ou`RgOXPF zf5fz_1QUixi)-EHFk;~1+D;r!FCRjL&$Kp1^+^{mhT-#E%>M~;+;!vWR^}Xhuo9Ru zU9UBrZ)$8TZ1OWPGAb}ii3%ZBYiZ@#PKq2Vy9=*O6tpzQQp)G-0Fs46IRG%8z<<9k zTiWTJt!(+Uz$5ksm9|S?I+Z%%S_|~G_);u#ral=y2aLXD?TU&}@ zuNB>U0|yJuE2CZP>lTZwb+uo_+Wf!xzBAbP`$g9yli3p#*kA^!B-WyxGF2Zx=JCw< zylGr3Sm<*g?Fla|VaxKl^?wY)HyC1oDhV46j0#x^ z{~bzBKRImXV`NOo?S!=srsZ3k{@A%Ul~#;TzohCgLQvX$*?|NT+Eq3IpoM}R(Kaxn zmZ7^H#jO#^jZRijVM$cuz4S(m7_sKT&Rc17p_{wbusaUO70c*!~kJw zsioIA(|VjXKPYKpc&E7MBm zmK9v_@#!xJt264028bybrCo?tO@T^4BJ*?(`f`d@ZfqCN!Iodb9`e(pI=KliFJddg zE5h8f=Egej%V(NS8Aer++m)?=M+f7RT@d&e@HjS!C|u{i56; z&r>zxvccpk1ZthuO+ykZU#`G8>QlipYN*E@gVg8!xZO$-s}Snz}&NvFM$N(oA|KfiHZVnxdd2z{Ri9{Th1 z=Og-AXp1Z#(&E0-#Dv0<(fKpGx+cHOi0B}E^T~&|K_@ljQXi;y26Ng5-wN_ES;bj+ zSqjA-qGVC$`dtiTASW?Yj7mL7N^U1FN@DO2BbvNSs5`q^XKwmRv9 z;k~H6I*9&^HzzVx?ft<62a1bB*%P9@vZSp@oUCg`!Rt%oqODcdV4ZoOBXVIXZ?K$1-M}0EK4_3(*CUM72 zqHkBQMqGspNe2-f; zl%|@Gjkx>^0IW&0yqcOHs7z48UNqJxe8q$K#b^q&jO7AJE#byQdw#FQ9cL`BrwzgEX1u!sU zO-Gt^N)*q)3H6QVq^?7+Ajv_D#>GWbuguKI*0F=HLWl}JPek_VP(6CHTDPdd+&M;2-kR8=ETHZmd~z2$cbVguHPA{hgQ_AbIY3?LrrXpU25iqp}n! z?TG4wBYK~O-?!O7DiVO<9fG9K$DVQAoq$K^H$rBcn;9ldmdee^=@a4p&1K~mpeEOq zU-ti))K~Uw;4A8}nec7`yat-@r&OMX_l3s)W_>(&ntV|!(V>7aj-tsIFXFh2dUD!0 zf2~k`MZ^A*lA<|)-;dFXQp68O%VM1(Tu5)?-UbS!1v=pqeKI>I$C`1juw3kNZB`aH zuy^4kiQVB)4z>{!gZOG%oYZZ-5Ol5<7LW8tL;XFdpWi>6w{5Xq*L% zORBMXupIeQ+;a2$2IAl<`_Zf6kVpR}t^9;f>D5Aj!| z5Uj-i30;pMZc<9~f!MQUtK+Vvt-a-pq8*nPqMSE)#w}!osBICU%ys+swz86KaR?Y!9ELOrNfuYQ&wqcbRkCA{oV?K^q+`xMK7ul zv{>^nY^P!uP$g>pXKy!MwAa!qP8RqH_14e;y}VPdK4~b$EvYw9)=E(4Lw*-Jb1sQp z!B)uQn95mkr!oh>Xfl4A5Y*?IXDz6e@YG~3^;<1iNhEfC(>p*X#2PF#ur2K=K8~|` zZ66oFKeAAP^l#v27Rf{v%x$KienN0Z#i2&+E6i9bTE6dyTVA~5OWr|DHzMJ1FGuC59CZFhpjQZA_Gkc8Hg18{Issov>Akrlb3 z=WjkF>7iYr*BZegI&XDjZ4&2N<;)oIszV2bEnnF=2|bqubu?3nFL4q8ZP8m#+demN zg-8m_zaS*{b6MN8o)3CH4j)N*;t3sk*(!;z5OR?5PM)DJdn2AAGbSEtkAu*;W zr7`QfsI*x>z`VoliK1NM`-z{#SU#>xm3O47@z64Z?+ix8{tuuo*AR(>50?(Pf+`6I z&N%xjXh-+)V?EQkHJIX0z$_rnn;GGH=7gwV?89)3*~xrrMJZ*QvyToOmDHs=$ zI0m~|LaFh6r%?SxO$>as;)ipZINCv-v?)nMVZqWY!VtKN%C&3@&KTE*i#JYouLu+M z)oW~&q@fz5E{g$e~vDS|0-0UNiu zSk8-jJj%R9tF|E?AwF$fOhZFNQ<8~^iQn0amP@I`p>cuHx7MVz_C%q`ROWZlLXRF) zp8~ZcS+o<%U38Fq{LI+<{1kG5x5*95rR)~sC9Ix1c)Fq@%kO;G9@=fmcpiT6Gl&pp zzwRk3zH?D)aB`Q?LCxA+bW4M-r*htb7&8@9*)=l|miwRD3SF@;X5dcj0Eo9~3}v|G zL(jcq6|4r`KcWz^<-y^=9fe|@2{P-J0~L=Qn;xN%E`Tu$3!#XH zxFe!4DI}Kwqt<^NV_LC+3)?e;%#4*tuT9G zjx|o!3OoVk!M{J>qAs+z+j3|Jcn+@>ScUQte`-t>yJI-Tov`h-)C0&*sI8qb?HL86iXBTP>?fN^Wp&dyVAP>#dXw||g;P3k zG7s}yF9ieuQz(9UA2yd79S4M)h}g-?nh-mEp7$t7*E9UrG(R*kaTW#rRf=ni@n(Ow z5DIzB8J`Fy2z2mO)QZX`gQ^wxu&*LW`w7M1bRq}8XZK#clwA!p zFLbu!$mU5KGgRfl3ho0_nst0N(UQ8w8E1iR_|Ep*S;ixxx2Wm-15PrN6fz(^xy-0b*+;P80({GH&cuPJw!mkX?Ro9UXYv z-*k16YC|qq3ii1ut?OfpZQ|hEA0iG>EtUqkywCxV6+>b{zlQw>S2mckPk7icVq(xN zHFwX>5cO@MH$a<8oq;IZ{mH(q^2)YK znYJJjCU31{Va|P$AMMIeW{Z@J_;AZ1VG(g1)LsCX6v-%zNKD19&1itpYoxX{s<(xs zX@K=d%~{`}g!gMUNg@3M(YM>IM~{3 zu(E1jxcCjzb&mA2+uDfTg}bij@WVm%2t(l#&da9rf1i+SFL zCdS6Ng&Ey*3|_Iih`G0{oLpyfb8`$EQB4bzi`Xs39^ru{4|e_(CFU)Qr#zdnx?;c#gRxG~;yR5T8!r8=-tQ=lHSdAZP`5af zY?v9J#gbB>cuV^D%$&GgjlbmJKWj;y|0l3-*tA@g)wRzqqRags3os8<2m2Z9T35SN63Imrr;&bZMLz)FpqmP^*;Ri!=s&=yFn0fPl z^XB)1U0Ua?HZ;7Ae|3^&5-W^_a$W1a?m{u^qDFxUYF4>G5Af(Pzyb>pjYHfk!}VC& zPI3?<_O0f)Ad-f{BO(0~8O&+qa)7iikl$#VW zKp<7y0*}52SJGp4TlmmAD>XcbDAl)hTYQpI(8+_7}z6T0 ztvApTl#AZ_UPCO*S54>~>r&-HS;L6!Wz=G}Ly$Q?5@zw`q%*eZwUpQrbwShAA7L4m z3Q};w3FY-C^o7$QP-#;AeSxQOc>Z(tfe4c+oe8pCeDB$G`5Q zFc@8a>@CTUVTVv-kl%GfWQvW1+`hQDIAU!zvkp;f&^khR1fhe+jx7sl zVrR&Z7{kjm7N1?ea$}eJJw7J8Rnx7!8mxy$D=h}BW{JDCb;GLVp;@;NeZ3TQHS}Bf z%^&?t>@Z;5e(&CKRv}u=Q2Tr2bV(OUE6=&I3@)tHek{v9^?io-G&pLadJsa3kz06t zLI=SxR_IH`G)U}BQ}dw7jXM3|xBK3K*l1HS(c0GE^`UL$sOJ${lj={24U#yYz4#=M zSBN_{N$ON$Z{NO^_R{oL2HvGayHVV;d7*Gu1>q46wCI;GhU$=X`FR{w0Sux3g9nH2 ziKNCrulCSnSv^V}eRvL_Y81+d>(Id*XIU^E8E=80CZ>V)8gH<|V~6SW9R`g6z=*qh zXr2+RCjP;ZR)2$q+bq^-oqQ-kQd;X{7?g@RvoP1Ai#`TYChWDSUb}c^{u7G_(*7-B zdpxv8rVj#Kk4QdZlH{r^=!sBtF!ISo7XTemsAxs+c-~5Qas2rc#?XWE!3)Gv+GPZ> z{UZ@Vta{wXM5YV~XanC+eolBFJZ%_duC1-rSgrPn7$J7KQ3fk-K9*Agopk6x?FIEs z^BYvDi$U?<(O%Iz{E%t;DZ>vJ@C~;KoB3_tEy^~%>|~5r7#kWpOzo~WB5+xGMkl|V z=-pRamm#h}Sa`iYDZ*dNBV~2MiwkP!*6RJ(doR6Bef)UEcGH9Y)oDjf8atsz$=7$R zqx08=F>C#A-nIGryy!ntz(znHs;rM8ah;Vw;5yTKZTaOiG);_~`E{a{r9Sht={Z;; zzmJDV@wxJD&tAPkc?ud<|Ik=t8LdHCKx?HO=I=5m=o67Nr1v`DHPOb|F0@_>X9Ykq zYTCcQ48SQ+gvsLElHaGNt$eHJ_D<}SWPo&b!7nxTG>PPk8A4D(xo~vBDrj}Ux3A?5 z2uMKTs<-qprbGlR#1 zTB!X1Hg6qbJKMVT>*xP(7l)pW2P>9tfj@|bVRi*GxIAKvn&-KfFZIN*_xh@HR>og! zV@$0F4Y-ZE(&|AIHucLbQY7LD z# zxrad!hG{Q9pB}Lg*A;%CN8|DNn_%9 zUSjpKT;fb@J$U2&nJ$9f{5}&7b3}mm1R`{oV=TVx&m>V%P*hL+)7DyX2XPChvXV~a!~Fg&7qQB%WBq%~I3MOY&9;w7249v|fI@1Kvk9r^BB!>o*)oKFN( z+=|vHbV~tj>=N@@=S0@W=JLc%S`)7ocgR$1t}C#b6#J#g*1aS2}s|@a*!#{R5L1qwL%pmJBMIUp!j~qmRD0-!TmTtgSpjGs`i&|&kmyC zVey*u;9+DVL6GJ(h+M?<;)pQ$(Voi+FXjbzP#EELVl&a-ar^d-fSH+310c?Eal~{B zE<=0rA@f9U*U1cl#a6Q~SFUcO0c9KxL@{d4oU({x$EZw@sI#SNrXh8Hz2s{uZ&rg( z6ZZQicJ&t+ONr7P8!s=E#Q5OOg9N)AUmMTrin%AWWfebkPKc2(ZptbClXPK5%i0+ms3o^>CJE#RIZ6Du4h<)gZbnwh;<}9skC!a@+jeJ1 z`PLOxpISX~B$B!r&FegHe(DV)y?GN~4ea@+yvFaV&h7h&UsP2aE^N5t|K@}J_DK;( zx*0CIHDR>=qR=Cq_2zY6acb>hwW{XUw=cY8?dFxaH2m6?w8v^Xyh^yMGjket%?%9+ zY92Y&wrCDYQ}|2SQnbr10pZz$u(8yM2D& zdq7V-J>eBYsMTMw;t>=(KZ9*GuI+0W2ZJ#|3S{^ZUb|>#A#`a_MnP7_97Xt5Knsyt zy}DRqzbC+v9=ZxFD;ymicRHwUG(!Y*gttw{Ahx73XIo)vdJJTrz9##`5#`fIiA#?O zBENek!GmD=%=;m8Mvv|Q0-zDYi=IU=6PCIH&xAwH>5+9B@3K$BF^*F;spc}9nV4JB zZ(>atWH8=zpj*4q@qdBkvgf8he7KhnqVg*cG<+021tp6UlnC&|r`yPN3&L|c{`k7~ zUE3g^k$1=V?+xm5F6iUq8(k+hRt-^W*krQH0j4%14`HM&h73=ih8nlpni6DRhvn3( z+G; zOi1L4gpmohm0?#^X6uh~&6R6Ud5GN8=_;=qSBNlM*tG*(2KQIJFL{%F1FP0#${u z)}i$(9w(D9X{Y}S9}pApjTy6M9qasoGXj#lc=TxmM^otgUq-Ba9j+@wL|SxX9kvGG zSdxjkFMlMdjy>Y!=orL84m$bDZ{IM0l*2N11N~+6pb66XtqjUlBo{MZ(l<2~Zddm) zL|fi^2lG;(dm9@Yzk%w?U1eouks&>SNQKj+0wz*;$*iOJjB&4@aJm$s|6{rig!2x+ znj|~zdv$7TLdvan<3r~?emXJC!A8yB%o7Y=&_^+u5Cdu|rTzz(sXL3g%R#Mu`jG?L zHYa4sj8|GPO{e{vHz~!(Hkh@2G10DJp560B*dN{LTCB%9v2(W7?G6dfZiRnxj#752bj^Uz&A;GpIyLCXywQ%wU0pe}{Stc+DaeJ#4-2Kz);B;&u7$P?x)PvF% z{Q00sbQr@@v9E?=ggo4@)4ui{yEtNg%IG%MelB(=WEADi-|Ex^A5%xiJK~oxVMRJD zC%{7g-w%YbqmS;~^%QpACssj^0Oqo!u@FcTVBVM5d4j%#5=NwJ{0kqf>Y;-_F8R{GL@U@4=^WYwFPJSUVme4okv>^8OdAOO3nr{VR0GpS#&QWyBEw8Vwmf zCt(D)L+_I(b^X7^(&RwZ*uUp>z@i`YGZ5SBrWG`X{&5{U9TTiXtMZ6P1}GT zi|=^YehFLr)Yljreu5n=PzE!&zfaw9r8<6j2wZ%rztB7^bRitc@G&XZ9@7PkUe2P zOASmrCvKK^S|)TZfm)9Z{Yh8N7Y$tUNwny|OwDjl^3*=UVX)}>qkj1~rHPZ>5da*W zT{z7$?em5}*=`+#6oMg9t@iyrl)cPnjA_0Iu{tMOf`dOVr`qMGX@TJ%1rB}WmU5v(WB-hjpjLM=?luGLP>9addk4J|;8AN<>Gowj+)cRT;9 zS`VM+_s)9VrmA);fd_A6YkNAY>RFW&x&3L|`K+qZC;!%evVECXU;6T8U)V_6+D9Xz zn{;M1EI(BIA-2zr++V?0EI+jDn>YIOItz;ht5y}pUp{QAr}y&X>5_Oa&YjqWEOr(% z4)DvizYOCAs;YQsbbI~!_xD^h8rnfuuSNSucH_ar-zmLTpX2|sxHuh|J++`juU=yG z$k-R`=$L8}6D^?q)YAZ=a+JdM+vZ2=jT5|f*3Au?a+zvYY@{(6ee%!4SFbM8^8D90 zC@Pw)+GmQ7DvO?hL(@6&%rkNu*9et1w5cr($x&`Nu!$k)OBj5MJT$35!UJ6!krn#?Oq}q`F`Q()2Eo{LB2z9;GozY>bRT4 zkg4r>e1N+ye=LrBdp~{hWMTNH>K?$Y3>Not;WsU<7{Gsi+IQc!wg*eLyKDMaEE|7r zm4gXRS5toNJ+c2+$H!!LQiLRrs@1SUmF2@vH(cn` z9u(Dz2=uJ#*PvCe$ZQ*V4ur5^y>UN&{}xvQiWN&kvI$SIdHN-uv>=L%%fXOwC((#B z5bm_3!B_XUg}+KVvvkbTQ2hcMmt$tBlou5II6JhHw!cPRw8Xun);l8RSigTYu)#X< zSHis+;)eiMuX$VwJK`_}Fyd5JRk!^QDRKQ{4`n`oJ_f=k@!bdSIsT4GecyIMb@R76 zD(2?x+ZG%dp_b3?v7Hw}`!U(Xm&Y>=%;t0*0KZ&G-z0?%EC!{(y)3wt>^T>l`hW`6 zIdg{h>C*=n@bd9~bvmR)=$jPZ6QKX}ON`NhKHCzLX&59oZTYsH{zHYS7C4%~GI7`= z%)A{mN2fxWA+d1aCHM>(I&`{K=2?xh?*kgAAFrwYVq4JPt9SVQb{Fs0&x^^5?>`JG z&Cr1!F+1AMYFSmf6$Cd~GtC^d8&eFiU1(ybilR}Kc4Q<$ejGIldq%lKBWO9jmYfVc zbz$)Sk+Go>13p_dtY7|Zu7N0f`f}*F^A-P^iV6$kO!W2?i_K2Z(gby9SAYwZq33D5hNJ^b4YmW=BS!d^1qb=hG^k87B z%e3*{aC#t$l^@Xx2FkP|VH9P!(A6k)C^nMdN^M1=AtZq;Zz`{u%T{rr_*9;$LYE{5 zjf9QADz`B%`cYBQ zppG3oLUa~>BnbQX-luSRgKAf_%}P<~bHlvR=SIe^m~zFi`$glVq?WU2Eg`iFtO}DO zl&@Dc0^V{Gcj!B>HZX7mC;s3xGb{|^uVUzHuXz+{gD0D9i1X;%xk+Z-3hM(`#X}}kzp>n*KpIDPC&*MPC-#|d9n8SgYd=ouBp|Y}4fC4NeB~vY#IMvL|tTb*)jJ3f+&yokXZ|gtTaR>au z*W%*Ei((lEd4g-yI=bWv)whr>uo7nOIRCz8-Y?CUFuVd3vStf>b`J;VY5N^|ksniY za&&8MQT+3N!iSYZ%9<4A*LKV3eQ}5c8^*%=AyhFz%Vr)rL|PhWg#!8L$npatyAgi6 zy3KK$ef>~y+sz&!YI6#@wN)>Woo_MjiSw2n%`0E5t1URS^$oSK7_rxVs;{f-zj=7= zeszUz9e~i7KAiIN(*n?EdO1W&Di^#+cuG1sJ!bcOl##;3i61N+JN;_1)Ac-Et@-N5 zg`Y!wlS{8uF~FD&82u~OiaV9obJrRzC3o?ET!WqZMaL( z4hd)7Cp%*Frd=%=lrC-i+d$tS;^}++qX$gfb?eHncV zaXq4O9th|5=vq&^gCn~w9V00gg^~E4THH=fX4RzR@A`V;gdpHQe);kgSrm7N_qA{C zCCkOSbn5*U7aRs7!bShtvm*k)sJ<-BJNW(qNAHI5&@%!4dAtL99$`E$7?9`|USXfh zP{;mmVhLn50zJ_Gph;RvT5l5))F8xYAcmBemxs|4{km@c=+if?>IS`NE$FlDj+)Yi z&Oe5%NVcl#@3harmaCHTiWflaeAq;Q z*-?4snVPm9*P^2C@2U%XH77ncHkAQi_8O=8eZkhW)WcstTs%h7czUISl%&^z`5jZf zlCt-m=v~$I2>2watiZvl)4v-7uGaQs*lYy}ROh3!?OC`OC)3$`uxCxM9y`U-!MmlC zzH|HFf@7H60Yei_z~+(xr8|Ktg`*eZV4&O}Sb{W&LBUNkEK<91>r)?V_3Z@mv=r-M z#BCOs9mp71|I%R@=37+ud|zk%eYV2w2rKJja7bVQ^^?hgNy~`fn~Ih?E~GRURX`0W zyrl21IRSx?T!~^ckjx!#GcCkmeB;+UIe#;B-Se)G3!|llS4Z?>2DXl$=Dlb{MpMYG zoufY+74*3(NTP8-7t@W^=5GHjuOhvp>!1AZ-#-R_1IY@A@w~M{7Z`6m^3T_7VS&Yj zK(o>9-DKw+no_+;KXW);d-%4qwr*~2A@6mcG)CRHVgI|C6HVY1<|fKn-FsgHYr!CFJ>tT})J5gT~7FS(Zvdq*-WYHXQ73cldxy zG93o==uC4kd-osh0oM`|6H^Me(u9*b#e#8^*v9u9hfFaaAwQ*Uv}8ugptXv=-RJC{ z`1FOnvb_B8@y&mNLKZf*x8R!+7c@Q%`|#)eLi1%}Jj}w3En7y)R_Z>B%3Bd>GxcSy zcJU3LTep0(0A&PQhKDHpTA>&UDH<~=|6zx7E>80#x|4rF3%cwd`FX>8v(>AG880Q# zJKiomIAwko_rP>m;<7Q4^h67}<{Sr5^}fE^V$nlsRnFh!^;@34p4f9=%iv#T`vX;*B{+#jrOTp%Dim#jE0{#VuaBlX!7k7&V>q#bqs4~nA9=mOd z05tjgGiJ!#=24+m@ux>FoHzZ-sdgO{eHD^i?H&f#rXM)GEQ|!}jEiMJc#oJ)+LV~+EXSWIiIlFU9jP*?ytkCHvImXD}$a4LrQQJp{ z>MH=}(dBupXU4#w@+Po;fDq~Uv6+Y0IKlAxOD~5|VPoilc4Nrcp%2HMTR1c=d2c5P zS6|DP+#?zu*P^4Vs9Gow7JYS0XKNH5B@nz*CBDbkhq~og#_-wTag34dF7#JJrtTG{ zU+yigLR>Uy(o^6V>WS%m(P>?PMJ?T9?$3_eNvoaTFCA&{E9LjeL;F(7`u1Ft)MSxg zs#TMidvBCrNpUKY3P0`Y4`+Ejdh=%+6xshy(PrJZQ+v2FGtJKre=}YdlRNwu3uTyt>75f=yXZ@&M);2s&E1MF7)esiM0J|59PaZq= z1e}3phS^8%MmKH$$2`u@pzm{Tj9(G=WOcuhF3z17*H@XGl#-Ut1B55y9gd7tAfsGT zbLj!;jS8RO!XJ(@4BWJj zq^6i5zEM?;Z<~IwIsV{@(+yq4!Z;wjio}MJ!$#V00S+Yh4vsJ=d}%SQ`$#>#AsX@a zVLNxXd9yf;G(oSi@XqU0zwefw>1#dpZ*lFuAPu~~JQr=4@>4z8)LX5u#rlyB40cWmt#f_e}9fX1h% z7)Il#9r4dD>gaujXCEXI@7=oz4E0mBA4(Y}$c%9}!tN2ji4cW}gR7I*q0{`nOI}Rr zad};BiH}$Lix0yzQ?2~$JD&|3S}|x!{>M}2&!>Uh-`n=7H?u$bdwp9|>Qem8_i<$= zov^g!4#35u1;L!*f#D;dhWSEB2PG7ZnRn`5sE#isXT%)>nAbyOL<~(G5OIFM$BMy9 zp{bYIljSep(ShZy?WTp*Qw|C&HFxgz0Y0@OhIg*&dYt|t<=le1axj;aqfWF={)w>e z`0+};s0r=Mp4X0%jJP&;iCN1OD5zH`KLv4&{D|xQQsm(iCM;+asC1ejIMNT5o(3A3L7#Y5(&dj;h63I6PG zvd5Z^D8RUp>7ri3D`{re%{dKc0cL=gsV5iXRaJek|lK&W==PF5dOmKhJ7n=)% zcNDM`@zKfgBfD{VY+M%7(BbJi+SS!n$F-^Z{&^G~=z120>i>M(+HrQl-79Ajqc2Y1 zt#YXM`RrD+Q2iCFSBIZ79Wi9ctB7S0J%VFUq*<|vQonAx*p7})b+{|b>X6&s)! zbVD5=x#bnM*z^uL@Uo~Sf2Z%D!GkM5eL4);>CUvUn1y{iF<`=Lu9I{@lR&+|AH)`h zj0QnRdex|`q_hF!wMpBbGE2jFX^^Fid0PNvEwLs*TSo^H!sGJtOqW#w~}!kGMt&`r5RrjDk&X4SM`w|C+=#8znBzr|X9l$b2U#JiNGihaX@dmpk@s9#dT5(4up+ywm)L*kK7) zqDe^Bo9nY8CX_TJrCghsIwEUhn>*WX?X>m53UFf zjE>D3I$%J-c-3M$X;`i+2yWn|i%#eI_dEh~ZYA^Ek=?ei+bZhjiK9oa(9Q|YHRDGv zcm@saP?!FtStI;sZj%Qg--zyt33N=P#cDt7Uy{-vPMtb+UZlZY>9XPxye1FFp>0m?!rQ&INp^Y+AW=o!z#VwAtP@IICADDCAPO_@o-fMRx+VbcB-u>#K zIwIY)vNE%Y&y>O{V+L=kudi40j)%W+pGlRAiwj(xQ(&gb%jyKC%itbuY+np@U|Wlk zV&mV+lZ(r5V7vtA&d5V`s582&kaGrgcLy{x0h;RcVJY&1gWB?z+;9e@7ibWv9fj8- z^S$iLJ_)Tim_I&-jzUYWAU-nDf$6&-AF&e&tKrXIzM#wR9c>5P2$f(Two{Bd2p~iH z_wUabC^k8Sg*23iufJD{U@AVESUH1X(5&rW|1P(bFi&qXBs{Qj^b(&53c;(XU;dd_ zwyH9-d4dcm#dA*cyAVhZ5C5M&x$nY-;#s8|?d-mFT`f}n-A8GMV~YacbQ&XhD&vEo zEF+RUa*`R$ufyui?U9)T96!)`{zycU2;~*|rITC#*`C!39k&5%0QdGv$KN@nC=m9gp(MA z%GjM>YtaTV|G22;G9Ji0=>5 zO@&HD0bIfiAoJ2ydRk*7F+A_2G%f-v`*B)6!gAyC$*1hHJ9OP?^t*55qLMKVx8*)- z*7K)RU;gBywHkn(T6CBuG{Wl{y$^Q5jNm;l8P?iKN?=7+Z^1a;zaTgWU5vMyWtjb( z$fJcir$RM?N|x^X`SQj%11-8R#3fdk3t8y*d8k^kM}QFw1?DXr`;A!YojRP!;zvkY zbXZL1O@>eT$a-BIuE0R#%Z+OBY60hFyqT7odVtO;x)_X+W^1d9OBEV#UYo^+4b*x2 zp2bg|Fv0f1)M_29oiKb>aPk+%2PfTs%eE6DJ+6TO^6$)kz+x?Aeq#Dd zy=pOf72B;$OYK~O-2VQ^Ip15rDcA{C*j)XkrlgS~)1iEgjj}YmC)ML2n?f#Mcs)a|Z|9ES5jxbc( zxxe>N6$w_t8urY@q-D^P_V8#TqoM?7nvv^iN?!qF4_7vEofUMxcx6k_&8pn^P8-f2 zS|l}QdRWv@CK#fMM$LHYIa844;%HC2E7m?p~GUBAXKeAUr#rSOh5yL=wloe!c&`w!J4d$9SQ zebn)rJ|+W(Y*3T}F}CIja-_ICPY??w4?O22^iV7rn?3sydB$t8)$YO{+3yzWS)}wt z{wYoK^)q1y2Q+MXK*`rm-vLi$j(eu{=||n((2k%a3r!SLu;lu?bCpVSRktN%YX?l5 zKJ>_%%ZF}^uk8}?rPx7s&YZ!U=8W&wp>yZXvmp`EtU|uM&o&6s_fz115}7673!M35 z850OH@F~Qy5wV1l0pCN82r#ugGCM*3v~~$YW(F7~B+tD9V>Sbf-*SAnpwoOb#=YT5 zO`l6qPEP(^n!JP}UpFJDN5}5xsr~XlnyE#o!5sTO>F)=5pu7ofJ-W`|3 z@%x*Z#bAo)BIH~7n~ZdIPr}4LyK7rp2iUJJ$f z;l#wmqRxrL2|fy|+D>Yy-he{Ea*{(P(V{Gc1+*2ALx?1&pJVIB+klCE{T4t0B|CJM z9&nZWzI#e-{s1DM&>K=}=Vq>+0!qX%`0%yE2gd&&O=lk0$Q+U=Qv*VV z22!LFN+L>15|W{T5F)gbp-hz`$xNtZN`;VANJSxY%2brz@3PPP$N8Ld_KtqP=eh4S zT-UX(HLl>or$Q_5p+y%X6$Y|22@xIcxinmn-$x=Tp&daRAx6G6v&qW?RlG?o`;ia} zl+3Uw|L;~oK~maJx(mm2mxA31_uiII>>j7%>;5U^?WDnP7Y1fda64jL_bV7~{C`^b zDQtdW7(j45$R6;VPH5W^k)aI}_J_2NbIZov8uksxw$At~JeX}=+6u$~3XMC20opp3 z!DTyZ#z zUs(Qy{XwqFx^KS}YA74(m5=oN2!1G4BGoE;2!IPC?i(#%X8N(aDcJqxWm0nSN9(n? zQjbf^JZMqL2gX^8x4M}&RgrpOiqJcxjGuY&@sN=$@_k>ve^xEf0M99+i$Q#@SMMTw zBcn9m<)18Ds#G-|wR%7asTJV$#hW*IB~^)72M8oZL7;cGB3s>~JD4WN_xvB0w%&p% ztfG3x;X{png}^IzKb&u&OX#9r48fE89dZRWcrMl8$g#$0W;eP)5E zwD>Y(6Kq0RRC&tpXMg9w`$x`Rwfq^}>|x<~{prdMV>PO$XZzE70)OQkTNZ5-kMyV& zqoglzTj8T_?x!L68sID|tHejc{#8m>-Wb*m=igSZ=0p>DO&P?H$-&oPulsV|mzc#_ zpQS656@Hd+uc)A9Vt|La`QRRqwHG;43}pOuMDdqy_>V#)!wnoI>=5`xkoP#QErh~= z*~yoT)*PaHhC(ZtKX(O~j;M!d23cwbs=WE?iBom6v3DFaWC;ELLHM+(wzff(Qq-O0 z`)#Zo90qnv(s9evj=1}01kwh^)aEnAE+aeqP9nmSSIgMulAV)-qelyuVW~vdr{@=1 zMH`iWX#ARWH_$X9Wtvs;EyQncx3GSeW>H0Y4Whrqrv>*NYZDH*aI!0LH zzaDdgz!g1iIP~#LySnMO%hoAX+V8a0R)lA8{L>l?L3RgdnJ_`eYmdwW3315m5s8etYIEZ~v$VubW!$z{U>(p;MJXGwe8)6JJ7VuwF7&~Xt5j7kPMqmd0wE^L|H8Qn^%iL@X6`!}cdT9Gmuf&TiAtCBM#eA<%v$8QRFdiM2@ z>gsjLD_8CP^{c^{AVXE7*4Assn0s}9URW1;|3K&8k(ZN_O7SYkQ-K(P%3|WHJP|*z z^-%Uck>EvEP726u6rl&*XhxR2P>1j9nxrnYN6ZAz;?B&S;LbU-1|^w#n)VIa@~AD(;58`TiMoNC%^|FAPt%QO)( z@U*txF7ybBLn_rrt9Z|5_Cp33WLtz&7CxG;zY}^E#VQL7ZciMfv0PXNMOZfwmU841~e0laW1+4fFk# zy2SI{_A#S=tv>Mf5vyQMj+%p;dcyWR?LWa(P-rD&*;~T>Kvb-a8^0_mi3&aN;6vdS zz2d&w+Sc2ALnriR+SBOc3!?t4{!V?75%MSo(OJPj|4LY)tljl8_=t>Z96h=qq9`>s z*0|jw$}XVf$glxl)!;=R$RZ_uZ!JLN=-KuUJm&e`jX5!CLWr)$fIb0@#;U$h^}3#N z`#`hOzMI+qlttW!WRovf@zIp(*O-`FQ@~}Zr#I7jhK0fPycQo`JaWA ztWMNkQYNDS2mx7LcKH1HT~wgrbBor9P`~i;b-%9sB6#mH{ky8`>M9G$wCV&Oi8N6` zjdZoDq`Am5`GRZuSve zhtQeBRBBaKm2~4Yqj-lk;@dtxJ4=oYwjcBuip?+Ntb-uHGx~ORc16nG&XZy+vs+cb z0m@Q&8WSm3KF&DJlR|uBWp5u0=1Sp}x9}DUI>=3!laR15Bi^*Jv9ZtKisn~Fei~PJ zZN&Xiqf8QxUvK!px_FmoZ0X*DHCnTKC0D(P@DS+?WC~%^VViwT&DRIAzK$bc+ie|> z-Zt%3VUjoI0C{n5W%HE)%pCE0Se^`adDsI|n=R;S2DR^|$le;pv*{Y@Z!S-;P=~n{ z^#Q&a!WIF?1XA#Wn1IxUf)RB8^Q9^CFvk)SoR}7!5BIZrAXL!~~bCBNG2dq&z<;KG8R#=(7DdD~`d+^5Roz zlTI8zu8Q5!OxKYA8C??t#pL4IGus1J5w*{1bAZ~o*-w%+d*53?g{4zd()Gi`~?5yj@`K7PCe!TN!)kaCqPU(^V< zL2%c{p0DYeRj~_6-pSm-3l$jwl-~@nDPDWH%Td&>#uE;Vj}?PydJ{^*gVZQaz@HY;OWSKuW``Wv%!9>4>4;FtNw* zE@Rx2>;BY=-vrs2uOniOk*k(Q{A)>RDvzCWFkUUx6HPH_l~H{&F25*4S~qI2y@_1n zZQoT!EMd4>%3stxz}SpzszHd7bhaF?VSHe8^{ckf>={&iIJuPYuu5iBk|pr8y*TmS zZaAxPk#iX4kdBM7t(WEHL^t1C_h%RzH=%P9$tP`nC507jRtRZ$@1V#wnnv>+z6*PZ zf*raK6>}O5+>voK)inJN4*mJo7hyZJoHHUrp#ymTC=CJ`;1YW#fD@kh08{~qU-oJpCDL^NW6T6^YwMn{if9b0X<9T{)^KUSq(SNE+ zl}l^GZ_bq3B`%hpC)XLO_T=ZlD<@dbJ_Uv%&mXRiQ8kqDQD3iP9w=-YXbgVyvJj0O zE|Zx8$D;QdE7bV~iSL%_Y-C;nCC4%PZ-`feKNUM12Zu#OOrjg5zBqFDa6Mc#x^xvQ z@t%GAnjBTn`5BDRqarb!<+Pl6TFyRLCPTOYM(z|&gj>nz)P zojP}pwv6NJxt*^?lh?X^`cyqh#ex;Crr1hujB1gbXy40*-XC+=jL0maM#qXy-i5+FBI<2wwR|HTUpm z2eTc7V-kT%C1rAg4a5u1cO&Z2dcSJrU)7L6N6jSl2J9UlBI?cso&89K+qMmL?$CxF z9Nu^-6|!cpDa@pZqY`W&}K(i*MRg9V3t)mArK z0m5VSXVxUC-(fxI*_-j2_@qG0jK5%DCZlozJ?Ly+8E>3u)woLv3#B+uSUj5$2vA1NfqWe{Y#8n(4+q%4^b)iJ;Eaw5 zdJ$U!-KTxGdYEE_5(Se--f1Mwk3;SI=`!IASn2EbycirS;puy*98R3>bPp1UjLC9^0>NrhBMZQm&wG{W-?!HLT2=l$C$YR$TIc&LYEL#817 zjg!CGN0lo0w;};;$BF)al|>tge1TT zjEHduDZ|>@l?PKpUPl&0BPMf?z;Meg;aAwz)oo2j>WE*zRwI8g zL`A@ZcR3sSPu-A?2idK<^?ezx9KeN~yPJq4v0%bZXrpBuVaDoXEWTb7%$A9!g(47J zg$T-+!FY5Gp0}FR*IP}Euqt3FacMsP;8V~grb}Z_ocM?LO5#NZx_}Cb`f$RlQVw?r ziBi5f#HO9*tcXd*40_T5$?^au0B8&AtK8p*Yaq}dBpBmrI8XfE!w&?Q$EW&nqr#R~%=C?qb#Od-T5)542l9%c@KyL4@^ys~*Yw za%$DcAH&f(;ghh)Q$Ha=3#&`4#9MFOgz+wOZxJS42sW4tkl=-M0c4N`senT`TWYQ- zd-f>Orz;xaxx`vZ*f|KLxy>`^~g(B^&Y3aNN=mbqe~^1;{xQSeh(#1dq;spte9s;eoJY6y^n zRgmLn&px<2Yo``rit6Ars%ehMz!iQV#c3fIk;7c^YF>|ngBr`Oa54QuboLt*Z?a~F zc~X!-nq>h>XPkFwBc0NS5h_+zR{R|g@O6)9H%El&NEgJ@mf~XX5T~F^E7xFG!4$3< zD$`M;MzPN1M6Oq0pb-OP%{aE^%E`nd8Ttq8Gx<dZLjY#w^R+htg>_VZ`rZ9|7Rx~^tfLK!(w zb{8JlxIH`o?P3Vgaf{<aNrb0!wV-kI2?l7dx=~NCau$`)!Oo@ zsk&Kso09YMm#!F4(v^nS`~$s|&fK2SRUa#v+anYCOiy~UPWfTaJJkoN1jH%s-H|~x zCm(r&{vjpn9RAUVbRm)t5~JPgvUlTti46%AI&YOeeN%k=2fI)D+RJ~47@O4tFqDAm zo5_8fM|+#kZ2B&U%QJQ4qXav>mJszsDW2VlPqs^cR=3$8hmoxBgmj$Wd zE_^F?>8ctUrr!>*H~IyX^9Z{$5b|QvLbx{qRfIT#$~<2cLG#gT$PgtU0-Jer3*>E~ zqBlI_gpg6hO0Q%5U08b&4fr#0N)CX_QZnX>RcpHqUuxK{@roC$cV^G0rThvrHnmwDjnT4 zz?W9s}hOP;1_UeTKk)bI@X)1 z;m?qR$F5px2W$_4&iOo!D0G7rf8eRbD`ItsGJXjZH$pscQLwVUDU(rk;+*mBT|d9u zd5Wf}>~t4DNA25;vlI&&Y^zrTjCzLrK6OGEPKWZs#gEC+!{Y(P#7_AC)vLus9EFaW zzwgP6V0M=yDOr#)%5;>VB07wh?UHIF+Ac_n3iZtk=r6I_B^#5#3E4` zpH*JfRa7X{4~|RC8SYO=z?M1YX&E08pg7s2wZ~yZCm2@$ra@9xmnc4t~ zMDf~*_(Fq=-vPiEL&?I%bFq%Z#8gzIch`GX^kL&uW(jx^)I^=fwl-`YnePei4g$^& zRu}b3*>B8X~CN%R1x48y(%Z%ym^xnWO1(5&+%i}8};OqyCN`-ED_1R z9NAoZw`F;Mm2(ZBNflM*k}ye{Lk?-tQ-upUqQh&~uD8ngRGb+UfHJ+hO+193gglI- zx}}%9$PI-QWzwGB+hyvDuUf4;b;@K}w;qEh_t^RI%qwzDTMGCc27mSv2QY{J=WyiO zQJ|%0v=?eOv5d0@c>XsmY$GKf^{`C4+ePcREd7^$DnZB6_s7RhRGWMdHdq@0fQvyi z+ZX`wf<-Ssv#HABCn(0F{pJOQz-96u$~5HN71J0;Qj^b*r+*D~!KonM zNHq&rOzo-A03`;k%NNLHD*B$b!$lem22+`B(p@IxH9waVX~i!Ju65Dl5VJ{>2yJfr z^4y9(95txzM~HYa@L^-f%u0Od4-LBX$P>j}B87Is7 z?sGv%nhU@AQFRJW09?X+qwuTL8`N#}9s*u88haQziBX-ipd$Yh(oD8DZvnAAiC@#% zTvGt-H9rRMRo|fYqRM?ilM)s-E!ym({)3?5ONNHJ#Z@0GzGSz0gqKsaiGx}zm*EK? z%tcf3{&7FfIThWizEKBwBaj$9R~(^Lg;R;-a8I8Rz!68~K8zULb9n z;nkR1uy$oL%^6LIZF8AwC+-P;1^_}Xl;zu;np>sIiM6O=XL9M{w{C&c`){gNDQ%7l z-w`=ke4j4AWW531GS;E(3_S2m5GdN#uyNC-cv)r9Nj$-2Jw7d@hXR#n(2BVpYM(>} zgXs*_0!8{jq*YkZ$}#MPskvmPI?=YZVt}YdZ=$cgRsMsc ziln?&zm3zyKms=kksRky+VD1gj(;uKdie0+#ET2xul@YiVwL}c!T2XoVi(Upv0qKK zyx<10Xzys>)uCxDBh|$a*ZoabUGJV^38<@kvCS#td8V~jo122)QDF`D|1%PGg}59^ zCiU@owyXEo5kwKldPlrh#7hVBG^nUmY@a{|&TweSt5>(kT&ZmXRv{H5-V)H~F^9+R zCHBa6JDSYHnITN8%|#Xm;~XMd9BN_OwS9mdkn`LT0l@H97&C2J*h)VREFA(0St-V^ zT_c!VQnZ<RoQNWYV2&bXT+en z0qPsFYiv+_g|{n*%KE~BpD?s&uA{UN?~!))lw0rWoB+6mMo=l;u&mW`~YfSrra>xo|H?k2awBsu4ZvMDh!<(oSW9V3BMeOtr*=+z$MUeH zD1S&XW;_srfU1Fks02p;{y3CMn8{CRG}uGne0c{&NW1p!2ZJspm@RUdv6=GX!c-HM zdshRaKtVj91)5+p#y32 zC}){e==S!7uUeHAn58ew^f-$tI?>=PE@HawR?9;D+7d|-@JG!o9@eyJ(}SaZpGCDQ zNm>gsjlQ)E&4Qze2*+qDjMI08>5DX?3j=(bw_6A z%tw>~#Sqcur46K1S(ypEm@L0zmV;jK*v#X%Dc2?60!0zYg}^{C#9YE(GN^17jN-?_ zq&+ligIO{l7T3U>9rafXKs_ozD7l+nInmhpp~nq0;^=WfVy;sk4q{+XGg3Q)`2n^P zQdlpHOJyjMcFNXfHYbMDAhX*v%+#Z9`Fp=}atU*lIfwqVb9wPti>4ek(wQ&Q;&Wed z{J`V=ew;hBCGaKkG)8S&a#cV{|EhLxZbPeV_VZ7uQ@gA4h_|oJ738Nv`+lRCRwV;0`2Q)54+~D@ptj$G$BjRKGc|Yt*6;)uFoT?qq0=fSj7}a22Wvfm!iG zBh!iTMLDfPw~ga^8mo%mDvmHbbVm0?SQk7Z49GPqG17Q5zNq~GEi)bJeoa54?@vPF zFUsER5Kl)<_sUs`8kG$z4AT8?$IK^Pv|aO=br+SCK)xbm@#~IagA8_7X4H?ir9P0Z zTe1v6vOVS&q(^XlR3kc3`zh^Ocj(YJNF7vl92@3b@)7X%q)&NxeDBBa4?rug0oKxg zZJ4otp#7D0ojXU^oSMgx7gH2)Neg>>b6y)wH7U#_9$j?|Kyf9F6Lzfmj%O-&xV`gf ze=vLV(5FiCEt~bXU-Q+WdC}s?z6t@y9yzeXV6v`*M+uYy_uM6>OePd)*-|^4va=Tf zKPNPN|FMOjbL%NA?iZcOdWm8fx^rgo`Qx0$NUsZ4Qs#RMWqf3*C6XPjUPGwJ+(Yg_% zhpRZE4|l$2v6m_5iBiekdPdCAqiwr&yDx*m>%T)F%OE<{XM}c)UuT)%1d);%cg%5U z%G|sYWwSWbVhI6N<^?gdeX_(Az{mf?W3F& z-k*d$HO^YlSjYx`AK9{ue`dVSfC@%a_;b+=Q2Wn4GoqcFukD&75Zu z+A}*ZEw+@{!-fecgY{B$%hgQx3K2mI5KWqpt!VfgB`93W14w?F=+T{jD2q@*1nQH1 z6N(MZ&07FhjcB%Fwh0O#kUmrzGLlclZn(HCVrA`W(U8-kRn@{&%XOUQGf9>v;%_L7 z1a)KuUqZldyt;fs>p#Li{!-X~FwXQ3bm7WH?Vq`Okj{(j5zEtq_0)rb%>7q;2)Ovuii zYvbbHt(l@Qj0OYWk%ed7I_lh%!7746ZZNAJgHy;=OeTrsQK!Zqk% z{wfRN7&O0Xm?>;rbEYH4G%RMb{JLPRl`M`jckb^tayUoz4n2Qbx=v}1Y=GH+p|BlF zDTqmAnDge$8N=rT-g$UA=W!QpjhcLevWWC@8Z`{Y#6=0c0n2FSKRi4ZC<@K07zv7X zM?jA+zl-Y*irm%GavV_^0aS-~ja424fuBYs5@-Uv`Ef3-hc0s25As3IcQ?c(C@ zB!h%DSJ41Mwn+OUiY<0?LzaLU_eM`mF&(6rju8a*hoUC}iy+Ew>^5q3k3DxOxdbeg zq4sjJYl-*cqRt16-A5sOMZSNRPtVBpf?h9;>>BAmyyiepdXqO=_v=)h*b^g`Kb-mb z#Run4iW>tEjBI}M?BUMvZ(s_}xk=%*{WUe6pvov=;FGy7k8RCRHFiV^0enO8VY}}M zUm|a5NAW2mj|VIFLbgJ4B>P{m$0v{Crx+a)%mid78AGTDHS_aIthKMp@IPdDNb6JS zRK1Oi*-3wa5KK6=oNC~t8>s&-yfxs(k;%vQFRt+|<%|M&9yLm}F@KUqL@J)x=E+Ng z>QB+@=X_~+9g>9+EamBy6uf@rg_*loh60_=W5D{8mRjVxb2bhRI~dxC4_L2<*Qm6C zIEf#4^6PC7o$gX#zK~Q~;wl4-0X^UiMBU8HpG=%)DJtSim2vm3oAzP`pdC#!=;>x$ zT(r++*$~V~MavH+13s5s9dN>01L&iNo?ZtC4^aUSr{!CVlDO#CjoH@Ly^a5*Y}d;_ zLpFd?X4<*$YR}jsM`X%Hx-Y+9Ifsmn4~RwbnnWj^ywsb{GV-) z0`|DlNH?XmDMdXboF&Y3#sfUGugjbl)s)QJjEj8uD~Zus5~caleLxw!Tk60jde}^A_txTB!JR{ORPO6V zY06!-2;HrYU1=ki`T5z(E-QCJhnPp`F05|#J_w~4ctr7CPnj?iY_T$mX_9TI@M&~P z)PH=xKbPA<@J~aBi#SK;S>U+H7btW!PrlKyVWwHvHm*PFImRRoa+UQ8*1^nym;bwe z|2EVN&@pVG3JUobq-WKFzzjJa^!LGv>jeEqi#64&YxnLuU=VGZ{sJkXKzxYU1~%_q z{;BSO9XBa)X~0T|aPVAG&emn&n|pEP15nO zEuYv^0z+wATg&d>=3%C}13s1VXLMdIQ>d`o-11nvCrB zqs{qqr?>q6-tI(JaraZzFm$T^rS%9ym_-t zSe;C-gRIX|PYgu2!G5knt+`fBpY6cIwdn>*qsq$HlYo>nGcsJJeX7=dg8KtEd(rZ? zq7K13G+T9jVpDPK;)MA8sV?(~d905j57yiL;tZF8(&ccS(%LKps{jl|BoCc>j~_5OaPSbLSBo9<*Ai^YiPC{f*LDro+kX(vm zTeI=`$nIKmC#OCF49`xkI#4)=SIh(V_;+Y~ycbBsGsd8=6dxX@>LvnULS@BrI)Hi; z9S5Ie;D|>ywYp>Y0vAAjeqm)hBG|{xPbHleEc5w6&4(jB^vYLKQ)(Ej->Apr75<0 zoP1e+aON)l2NK<{t*tN9q)79#pZs?BC?~SN+A4jVAGW|#wYE{Z z)efsE4ZST?CwzHdns%pt|4uo+|A_2MO--gmWs#55@}e${4Xw7hsSbF(bU2s&Fwqxe ztS#apS_rl}DJN}Ed3&SblqplnI5y%fgD{D%mEKYzU@iI@GB(}<9Y83UCdUHz2KWuH zi7iT-s1b+*kiiXF_}t^FeJP8GITCi)B5~|%&9G~&?V8{J^R}>ZUj&xTGT#D|N8fMj zCApx>XrCEde}Q3RYyo=1%8i)Zt z@A`?hh7vyrSHXw;e4h~hv{=!BNm6i6H} zSR2`o2RU(*=XZYPf`>geGd$;nOt}2pevxWOM13@RqShW72CZkgsQi2GxyuovR&Q-( zm80CDk4!DZpStRZNeG|9L_6$MT-=9yiIa)zPY6 zp&1sbq!v%%u2Yz6bI_CRN%!jDqaQ%_z0;dED3yp;%wrozsjl23=&J@B$B<781 zszmGY^E`J1|D)iOL-Q?{KJ^(kF>!sJ%Abq#hix@ZsT+K@39k!rlW+uV`rNv`6}g!` z60TnVHXbWlP0APR1Y>>9{Jcx}OGe@MV1WrzIlV-sc~9-BOMlnPOO z?ra&_p=y%Su72T@hppGJtgUVI#L@1J|O8Xci8rn=*l=4hzH4?@y$mUcjR(wL;v zPymPhZ(kN~64O4tlE>p3dWlpzsyqf28mQ{u9Rauuor6OqNp+t20dSFWXaZm{EiVxa z*ENdg#o0q9v~EPdvT|SO-N@;>$;T|-J&xHmvCs1I`G!?}+ZJ!Rk(BVzLJLOsFS|aB zdZrsq8zy1)K4w;r6K1Deu~#Ffq5&FDV)1(tWBCO z7p}YEc=mb8>|Qn2;YHOKBTCI(cU|DC`N!Y;LgW$wI9V{__52Gm$zH-MjCvBSDQ!Lt zGFDfhO{n4ojwT`_koVHvp1*l3MsLsFuk2@FaEPO^6JsK%q&TadCrDz!!F`Zw@yUm{ zKhxGc_ntxz7LQ)Wmm*3DL5I}8C@4}oI9#Eer>X0sSYMms4d5Q(_ylw&!mLZb$|!c) z?b}V_tdHjmro$SBT8xSIa9RyK;{>zj7x96=t{wexi%;yi9fup8el-0{)}qeOpFd~X zLRC$z$pzbB1V7Y#ugRUZrp_&ZR-PigeAv2k)z8$rl(gcp98Mxymht_CpbkcNV~7a} zsrw=#L}A7hq)lIK>H~Dj3_9NBK#GUcxyh|eLbq2QZR+pp*?smVYgMPo#lvedzdD>^ z!eEL)tt>_*=9r;S2KE9Mt>CI+vLVtam|Uz1xlU3tOz;4pjG~&LsIYK2<(>nOf0t}6 zR1hMC{GhKsLmf|(8(6oMy?nOT9^j2z=va;~%m0bYL{wTlWggq+JJ+@uJU%*Cwc)&W%*++_o9#POQd@x7cU#zK21?$i3KYrNXW^qQHelvs4bg=8hC=jJt@a zi*}bid%JB6Qg1i?VPA1UM_h<#tjfbWKU)`zapIqA;wFN{>=UpZ{T*d)L3(j7Uy7b8 z;iHo@ek|`n^R(#En$Pa=zw2z$2dbcfT?%`~bjq#4B@sa%#JNM7d>ChR40)*_^S8|jT=9nHbZdo#olJ~CyBo4 z_wRF_rN$L!0E4(-)D2|RLC}GkMTGUbI z%V^i%3hvRqjen>qN=gOtPb+@NowI&2HF!__ z-;ei~h1#~ZDpdH0fhs(~HyJwQWz#7vLk}RN(%SmLz3T5d;BdRNB>h;neb|8Uw-@X_ z)YG~d;~oF>lQIL?# zrZGy?1vEhgZySsTt$?r~rFE1YL%+u;=LHSqtVUw(v9$c=nP3kQcOm_>6= zarrt2MV+uX1esQx^-}Hwm)lEA4MiP>L~V!c`v*B4n!fY*@0z?myP|!lWwTu~TE6hU z+j&7hHi0bccNRd#3?2!3dmN+v3`c{8Rn?aJKQLex7W*2Jhf`MtCtFde7p=aP&ukOi zS+Cd}7vNKB_~FDX*qXL%bGTalrZc+wPJ`yu1IdLA44r*&va6?SMDcXZV_VdN<^;TK z1Os}FUQVoJN_QCCW?2d0{OYgw{W zv!>1U-)-6*B0qg9! zSG|qi@$Bcz5nry0Qn3Em&`paLEHIfdh9v0m%V zO-)yqDSiibY}2Vz+%${P6hoAith2zy*cq#{5%JfHV-@U>^AbgSjU1VrrZCavQU)^) z=NKsylmv?XEnos~^nqPW2V%wWiRLc)s40zdcT{=Y-Dqss)z{{G$W zmC5iCBPwNL3(8)%eHpLXQR6P(RhC`lRaF^H)Uj;l9+b5{ux!B|?Ue4QAoiK5DH{W< zDi2LX7JmY(9?Dt+E7{wKBOtW%H+DG54uoAd^eFM~al ziL;llsh_fNlC@5~1`VozRU=A+B9&b#T$CFWMwsl#se0i5XBkBy=!9euq-l1qZr#UJ z8#(bD50Bzk9tjlBDDof=0zp7f2FG%~C}|D=FNx==2rvs%`Gqu0cB2k~U}ciC3^y+4 z@KIR`B}pML)xzSi)1A*xvbNRjE%0f1F(Se)`a^T=Bj1w$?8O&ASJ&nry_JOxzxvJr zG?$@AP#e*mpm5;C2pNY6S5|C;lBSi|-SjF%T_V`?yVdXxcVK=XE|MnS2$$KfnSm*j zTnuM*trAPko?(33jx=W*(Gxy~cPjju`OzH5aMcs^=&mV4X_Ts}x zBBU*2E;F8=nt3h|^tzH|3!U(!L3lvPCh`nN$AC?n((U3G(qZrm=`J|R*oJcx3*VcF;us)vAGuy^xq*KR-h{lPd1|Jh;G#1@ro-KqT7zWKhrUf+ z=x$uDr!5vjMW+w$0XXLIcZz9x<0)mN>jZ2vL<1JpAHvVZ|>(;Fgr)_K~i+I5gT`snEZ2^`B z!grQ3UM*pH(Q5@8Oqv)RMUmE0dwC!KpGn0jp+8p^xCLHA@%$>qdkAGJ-W2 z-&9)63yXFT`04Eax)}kiVXV1>jH!FsfS)VlsY;DxtQIPx;i6_>pfoLN5ivhX$(LD_ z;M>Qt#ztBhawK)y~W@jz1ETbuo2ksv2EyOG0m=Hj(g(t-hH;Ng3POi&*2m=lklfQ>eOX^JbIWnan|04K#~5lWHc9z$(<>reRNT@mf7_3MEUEy zpK5p=4^d;->>2QQ+;1iO<3aIKl|1}nCy*dWo4Bv!PIuUnIS%kMl1`Dy8-@S&H1HCb z?yV1brD4vgvDMWi_6v zgPw$F{=6__^1^=g>es6`(QvGFp*-}5a}L+?wY+speC@IwHusuAhmu3sNJE6bamF4)t-@aG?U z;nS9{@q)8iGQlnT$ z;n+fh?l!9)qNw9uI#u!7rEb4$yM+*km{hNu^XSM#TRlIQ87ClZ61ML`_`qBu(+jLY z%CL(+b?PV+f3zN0Q<^Y4FMW#kdxm1u^YV6M#UFVTEw8?n8WwtC8fmWMKfUiLTCspxyi z=LT^|#%mcVG7u9)q+syM>xtM?wV`(=1Mvt(i13ZuSIK3icmx)u;cY^ti{Pq{qBs8t z<;8?}T^BwR#hPxEtPF!~MKbL~+9;{OYWy{?Pd4Q8mWU4+7Wwoq7|LP~%C+z=z8@5Y zM%P*d2o510)!-_UU%=MNgd5$o{~RLOBD)jNc9FX~GdC1OZdy+jx3J0qihGhMWz2(vcTvzVxSd;h7)Gw@#G;JDVT3 z@FHthv@C3<&&Tq23Yya~V%uUOEaGd~5nNoUb^O0>5wf)%juJ@yxK< z-_2|&6W0xE+2|7PeFnd>caYy6UkN#YOV{-2(>XL^B(h^faBRkjfyZ^VUz&Y?Sz5Ge zLZkM$@U(9}e4klf?^KanZtFO>0q^5X{0tkL+i2NQjtNt3cHr60Ytg4pP2nW)=t@Ny zhbbeL>m)k1=037?O>M?Yg>}8GIfeka6jB+LLbZf z_lMt2Yumx-b3zXVlFZWTN+;fkVMq}y5|yB9rL7>aObbzr{aw<@?ctEao2LcLE^S5& zV92~N9w0Ipjr9@&T}|g(%>%A+X*+vXX}8%Z{yTYjHa;~}Q;1*BQt|dy+TybB9MFMs z@O3XE)ENRndwwhIhUO9+1lcjP1U4Z&51}1AoD@$EKCVZR$~ahv#;l=vdCOIG3g5gL zvBz9UoJ&bbZoaL`Rbc4Q5M8|6?PNo;D?FnDs-&mtEpAh=m@Qq{JiNqQ)_s%PC}5v? zRa{}Fn&6-C>?3@^^s;}x;B?7o4uAk<9@_bBHqD*_*>Mk$#D32k?euBp)?Aivh;tDe zN=~0<>AT&4)-?UdL2hCXC}(1kNP%dix7OWu>`xwt&Ly91EVpmN2I!$ zojrBrXUTNbP@oik-=e#}eD!JrfCxsft}DL%;Bp!lM(P>-6t+CoFC{M+3jPpLp8tQF z{BYhl8F48>(9QNEgWq{uy(1>ID3LX)m?Jo$?O*gI{C1wz0|1W^dnOqi8os$jw`GL- zSF*etVF{Z}4k940cczzOi(+5eCoTxKwT)>?uw{er=|fXb{Ur)|v^Ts8BidJ_uS_!G z8l+9U5xy7;2bot54Yi7IkdQc*w=W&xy?fih(JJx>*4^nozAj_h$@j@E_8A7ohxLyf z8!7&RfVi?glO=F(i@}+E!2AkbjW5Se(j{z(-GgjQVJ9ij4frS&>2)Ml)flX#X`RCJ z7NZ^dA9N1HGj^8#Z}BZRwyBEp9Li<3h*+BiT55!myI97CH&B}n0RcTu6Iz(F{W>{l zqD%2xyAHJOlm!D1)`7h+?6JMuC}xWIBgjiO@{J;{oB#%q^_XPs%EZ*#U=(iow)rgx zAyeC5UGd2lW7vnRGw)Rt zTcg$rKUta9=%YRisFGph{2`CrTY?;E{+bdS69alfxK!PABB7Tr0zjk-dFq!&xoD+U znY-+Iz#ykAq@&$)b|2qpEasAH(X20=8823M%wAq_(Tl3M|9DA9HtGO^w*=R43+u3o ztR!PbXi4ecA>5+aCr!o9wKk5i#Ip2;bBDH?)jqBx=1~*JQmIgKSlHSsYH#k%BnoQ; zY9OoJJ$;l>l`+b9ez6%6!{=9hBOu|vGPO)c)@iiQFcc`NLsE8XZc?&1o|~X?)%}iD zCyUT=1|}x5#um5?&^HDWZ{xV@TtxngHl=ls9z7CIK&rnIT?B?`U3;Pc0e6wJN9v{U z#f2mQbbSaBTCMpW)EF?GMMtt87W81yfDi2G;*!CGM)hgPx1mv%i#TR#z3KyB?LJwW zHfr{-X|sb*51M`7tD$xug|a6J#W^e7i0lS*0reu#kCuLnerk4f+i(vB}4J zT&cv&AxHbcKOv2K{yE!w4a+Mo;~hjA9dq->67swI(w9QA5=hv?6$X{!=DP_Cg)-a| z`}F8B=0lOim*jwtyBuBP!`{A|^v=;O@aE>l8Q+cwT#A6fcx27bbuH^MSz$rktM_W@ zs&mK3K#@Y`cxkCel$amH^onZ#;^n>8e&Lf9Q|Ao%B)6LDXZmC#PSVarDTHH8ZU&oB`2f%=!!sh9~&kc$JyW zoH^3esgLEpHnD0A6Q55 z#vMCaQ4Wjp81P?5Wy``#0jK=E5k@iBDeC*h&o5!h-T~R$b+o`tbqpSRl&L{(DVx3v zG&=Ox)0_UW1fFIqp_Mfy1GYcaIkT58{|!wI0P5MNV@=;q>b2DM+fD`7MiXzYimvt; zI;#G_2wUS8=db7g{Ac(;hoAx^`whTYd$G$-P8f^5=(%N3?ZJanPb21|!(<*&1|3Oc zo)DO#C}!Q%Ir~AVXS1CrSoOHzJ^wgc_ZZD5Yk~^P0L?{Ts2eS+N z@Fanbj{2oPeE2?|>BSLO+BI4SQ$l`dDYK+DHoNmY*{#`})+CaDjykb2ORw0aeGoOB zPfbNSvA7;)1`#riRL@ibk_y&vpXQ)N8ZTLqu$ zBWa#7P3Twv4Y$(~KY6M2xWQ{9oyXJqXAj-^C~oWEUxC5R*YU9gPCVmi6k+X6L={5> z8Z?Gbv1y6A7jF7%WoH?r;?5-6X6xogLgV&kU>lLMn#cJ)ue!Hsvu<2uYj@-A-D>wo z-c(dqzqGc8%d*e+%YSlI8NF78_DX>G@E*Fb7;^aT$SU;~fnJI;I{iE?E%3y}-tJa}Nb+JPt##&~R?vugjDa<+IWKIg<*H(_eu8*na$hxfC^Yu%W6D zvxvG}y);-|it|Y`@M|D-JlA{w`c(gw^`zl@EVqqaU}vq=Ph(ZH_4hthJxJK9p0Os4 zQgJ4BYEa|cm(3Rqz=$CA#grUKX&huoneG8 zKdJusDCVxWqg9g@%@1&IgSzd-cPXn#PY_9NB2>hGgt^(D;=14dxL6R;n`>3~J)Ci7 zjOw~K{T0?t&I=sy=W+Xa=YE(}zHbmb=97Kks^y12!MOX^b6Na6VJylDq}`g&E^CM7 z_>x%ptM{=H@WM33ZpEw9)^FZptz75!{p5lkPHXL21)80X+3McV{|vng1s7c3iF0cY z19Y-hMc6p@;zZ9l{c|0cjuD&Zi$Cv*J$wQuF|>!cMdhH97tq&c-bT4^q~gJ9lpH9Fbuo zsFao(>;SEnfb)`;Q)>%Svzcb9_)gdr<2Yam<>spJH58kaSnW3s`f{rCQbIk-Mv_%S z5OnOeHm9Vd zR_JR%2`*a4aXt{40&F9@v5Qwb~Wt@1<@D2N|QGMsaz8j6~Y5dV@iNtAqEi!i9Yww>_=L33p-6qSML9@@y&sVRnFt5_ZwKQt+b_E z!=^P8KO}Q{Q1tXCd#c=J4i}{;C>50c*7z*MHX|<>$WPsRk?G3@E*4F`(ar9r<3bO>dlswI6=y_w(1a z&U`}3y@r~a;vFFCOYodl!Yq-(L9RE=%4H9dg*z@J?*38a+K%peaOlyVMa46$k<~)1)Q~+<8|L283@{OE6 zu&_sIP|M{O|4yYj+U4J`|-|3FySV4O;zou{RSol3yRrRH($aQ9XUMLKq z^sJqR7=Ai~5=AVHJxvp_k)f{;o+Rk(@!`LX{!zRf75wP7|KKIZ9X|{_|9kubEP^OG zQKu2wsLiK+bX%1$qgF|;+uJP2SSz%FiM5 z(gx}~@BK1jd5c#*dT$jmd^kV-vkiJAWSOqM=BIv`YrM9%?K1XAm+IVxuKiW?+nH(1 z{BbVi+uM0sev6^d>4b?KBy)~@^6i6HJbE3La&^cM%d}6grcu)(8pR+X-enNlgnGD( ztmtr0uczM6j{P3^k1t!)$m>{q=P^!c8kqJ6aelaRL@*zpkpN{SLtFgw&yr=!M8hjC zm1uYe=h*PCkvNeCB++d^L5v5I6F%+PGpOU+5XVrIr*4}$+TBV|Uq(h3ih@~K z5pU8Flzj6;Bd|8yYESfzn{5z6t+rWldWFy!bb=I7+Pb zm)eLOEh8vzV8UCC7%_rkgvpmouE4YgT73Xf_?--PON58g<9Ol3Hk0uKStdiGI$)`0 zapmZkNw+_fJY+pLx-3K0vCIwQas-+XwRCnryD3z#N6-4(iqwXXvV|?A-l@O43em&o zm-Z0*0I8J4&7^4dyhuQ-hy!7;3B%(MundoeoE|1q|4#^%Qhg8V$qXc zU&t5+l5J;-Y}ir(=>ZEe9z0k;$Sv6^PS3>9`RLYM(;eKV?@4@jD|hPE;JETUqTrT) zC&8Ig`niRTvQlq{T=q0b6Fl7d;NTW?d!l&Gn3tB}=JoD;vyrEN=|#VDuKO{dPnbA3 z_@1}-Nm?G3T<0I~-(psv&od@(rlm}bQ7hnkV-eT0*VPT-mACKvZnqvc%SBi1WEdSv z1DAa(Q9S!5b*S_xEsBL$;pq2N2)OeDUQL{1U=%>HtwSHK-5vWQFRGwC;CXWNsS1tZ zw{Q1*oU5y(tc*dpW2Z^28-WiVJ8`0&Z%X;|%MH(W=|%Mou>1&De%gARsx9`-cXx5= z!OSjTIJ|J$oU!lrN5{ucVqS~6n-5F!5+PpD#ZqWZi@h6$&NQx2J9GXJA=2=fcpT7& zmV|h`^zy9dfmCM8y}YLFw?GU*Z~pLEOG(NEQxN+%619MLe7;<73X~%~I)=H&)Jl&G z$d;L*v^lFOJYHtR-7{M~h+F_4s z*x5Pn&5^G{_Q3p_W)|h;DZ}C;O25U$d52r%%HU_HKdL&@5dO~^QE_7f@Kzno*<+GD zSGMi2U+;gS{N!a$&D;S6OWAU9Qu&DGtJ=N>)y-tc8zl-HhO8SGv5;|u`wOptiEH1V z4fIyBz_%rN_bQVP9*0h@tz2V91Nfx$aT}2?@}Ud|zMTGBtzm-(Gp;O;>$pU1!)w)$ zi{Gv^y#zn6_>*t%^=uV{5>2Y?-ukFDjtwja}WJuhhGIDa7l$o26p+My%(hy*L+8*= z8*TV6uC-6~>pcWQq$5Vx7dtuF(tpuO&ZkCl>=D&0=Gzot2h8yoEgSbW_tQvX4wF1n zKZIEiq4NMMx{kzv`8oj@Rn|E9`uKc7BAlE&E5WNLT95&D{uOB*n5qsC-+F3KS*!~? zG~=qzW#i!qz$!y%RjAOb#Knw~Tr{pXZZrVjfPp`m7fV1VPN)_-Ym2V|5>zV2R{n6ggf*Quvj&$na~l%HR?%u z`G%~@ZMRH|5{OUsB~rJ@pm;^K6y;D?D*anQ0?Ft-q1wvAqDPZ3f;{3gI2GA`{lv2`D@#AmWwT&q+$&zH2PTCmrPfPs(WI*coYK|AZ;>RH_cbUc> zRzG*#>iUt*J+9vvlT}=YYyiNgXUuKV<$T4-p}VM!)Z1kx zFSdMbV(_b8=ZNi1zb61k%8DvrkhUr+8qX9)=(nLmKfYjnvYI1^Pf3hqE zfEVW8E8mSa)lY%UK?Qe{pamf3BA_lxk zZdEcJZ_v%Ar<&|1Njjdc!iHaDVQBl&{OCh!IKkeKjyADo%(ZLAQj{yukjScod5_G_ zvIMC<(KCks5IR^SJ%z50U{4g=SX}q#XV?3VtJbX9I%GWD4=RP1@7~2tb2ZsQQ}X?k zzYH)tmLLBYu2;6xFpC8Q+~H_x!if_g+wJ?$u^&I~Lg@(Co0YW- z!e?lS$dD;{=ICH1@{Pnq@xy36BKO<$wn|_4(ZMb+dF6sGrCTmH&8{B0HZ}d>hG#%L z<)V&Z-ItM`=+aW-bT33d-mPitab(es>8=6oau#B9xjMTt)tWU=UAA|{%jo^{W={;% z`rW4)n)#GmZr|YYnOgu?d_HBAk)~^@`^*kMKFFH3sNko=u!P*X(~52p6@2l4X8*-% zBM;}?<%Pqfy5wC!EUfQv@<{ND5W!&o?cF1tBin$L#UTv0z)69V)iBW6G1Q;9lSiiy z)G#y$y`KXE%o+2_I-@42@ZculgJJDhZqC9EUdDitF>&-97D$2$Z(~%#ABS809K^%F z_y(e7qCD?-R$sZz%=Glqnn;^@kGaHDV>dT9$d23C<}t5Hbp9-0Fpza>M04la;w_;L&E_Ak6A^?ho-j{y$5N1ixKu zD53d(&8L(Xg$eB(UZYP}o;`cUB#?y+17jtr)df55BSJ-t*U9Wn?yx1B$#_A)YdOq= zC;1Kilbui8D?WW-V4!r&vG1#8VXw9IZD1ENi(cLQV?te)Wgq<;DGO=}cNm5*rt!WT zI_3~l2)Wh+$4AG-`GNed7`ynXt)bQJj@vDVqzsMlOh}pVXXt?gc}pJtHK=6Vg5O^M z2&A`od~m7=-?kw58O<1w8==eEZnfm_QwruB739I`}3gd0H*}jk*TLd4# z)ii4~7EjLptO=PhYt{{bPe&&w5gd|O5!+>aJZc66 z9~%6iw_?$&Z6mI<)an>KE%b8d{{6p=+{T?_IQRJZG5nOl^+&!^3bGVnOA6$E_e0t|wNIDU~|9bksdndr> zq$9m#9|5zM+)-I?v?c>z08xv63{%-jB6I?1TMNOx=33T2|8z&xLpvuMU$N$P+}CzR zY8Lu&XV!E-a zA@Wi-u#vH5g0={v7U#}K+rbX##Jcg5*NB#Z% zMXJx+Ol(O~kbn1vTlMDFXU9f=-`wwU4kHWzYF%Mzir?dxX=`?_&vT?B(T{SB=?h0n z4oqsFeRz;M?f>(CCt6*F6N^iLMuMZRW(V zm7`UZCK`M2M|0P{6Ce2^G7@+b3_}MLbL**5PDyl6B zWJY8&oN38Dsr4ca;(ob4os61Bb;t+Wr-4|4JW5)0vSYfdsfkJvDQVe8Y)VFq1%PDD z@$k&5ZNphFfs{D5`0h;Ze?nCV)RL&6Ile*WW z0Vndy(A8|C%sbuHBbZ`{cb$hc-6$e&jdz`HS7$0H7s@f1PJ22`ju;v8s13KSRTLY~ ztMPv3?6I7=5H5`sSX1onb9|zhwTN^A*;x%Q{4cM-01cXYooShED-N^>s?BSs4`}o8 za8bY|+tF@I^(OajKD)nBiz|KFW^-FM=roj=lvf;VTXX!g{$*R!D^r;Th+N@$^$HoL z+T5|zv0sLs+A}&R$142L-aBo6_-HL&q&~fR8FZY#GdL^(Ul5wiq|pl4cHwNhG|RKG$VSbyPCM zVwLm0BG;d2bcOgKUAG{67q6wPb}g-YGs?v~0TGO3k2T8YkOvp>n$G6BU&$Kh4TE*H~83Ft&`l=N~;|NaCpDnN(yGi}$F z1aHLMDM#|!D;PwbN$^KE1%ZxO^#wG1Cs*+j(fmg-p3-4J^9jqwUX5Hm?Y0BUSJ87L zG4ZN($0mCI;zh~GltvMK#BiRmpdRU{vL#jrc=c!AKJQG~cg;v6+hpN-C6Pi{I&?2d z*CxhVq*Al_K^Oo=QS@Af`#==+!9)jk7B}uY7I#rFgPyQoAVsS_T7s5PQF%B=Rf8PT z^ueEXNm@evlC6QLwC9X=RqfX87YoR@lJZX414p$llW9uGtxgKRO_;FdZvXk(n@f^M zo;B9F{`a(fw|cg{ec^U-^%AS&%@))Il&VQ**Nd6^{gQWDazFa@o9y;eG@NtW707b1 z`q6vx(~H_I({4`geJf}0;nB0Z?B}f)rP|b~yY)sW42+6nOnJzd({5QOI8+ZZ%L#** zJfQdQ2k2Yim_#2j&B$nb)?=M6V%`!V4$-y%d1XU(k1UxqF}98A!qBzeyy~3d4&UB2 z&+K=mv2?dlA=EplsO+Y>&93gJ*mRrv{-Z}B$$MdXz^`@;!YcNCPN8aC&&?ly zlmC+ms#;Va0CJXf<+hx;)8NNIe_Vcat&wrz+>&OpSQA;IbYTe@4XWTB=*Di9r(U}B zoY3V#xf1Tjk;PM;5q|#s0sf2_7KyBz4q8ljk&E{Sh98vf?LF&xjYZSV1|W|7*)D0Y zMz@Bo_8gZ1C?;b*l+hX#Re4|NUn3>U6n+VSEt3aY;&${VmNUustr|6AL?*tx%5P$UN508(n95gS zUwiK5!Md2upK>pdz1=wLt2T7hgF_7+IU# zyJy8M8otMD)#uYEQq-p$n9}j^;Wp}{H}*E`yycYD4~wa@X9s8T3+TCc4F_afp z94QvwpF0HA*Mc7syOAAcuwAnENJbIvi9Sgx{;**ZdJ2IOH#!qB5GCnv*T#>w^Bpel z*EwmI|4c#6ZHVj0+hcQ%Sq-1F+psXc-<>a?KNAmi#?;eCld~v`Ie~%h$dl?=f3Vq? z@EVXTm#`D#5Tlw>#veQE?qsvA6xY2hK)iZ&ybQEVFpLI`x~+1(rvXtx?S&0n98tHI z_JXCq+bGQP=F5nAc7Z+Ms7py3oqfHQ70zI_wiY5b0X7*$ArSul`)^Vw(V>{b4n2C` zdXb#4cq;oKGIe~-83hqs=lff;7N?s3pq9U)<04e-B^hG3du|ypK6+pdwpkNy1Xv}) z{V8oWv#L%KhW3n5f_fbaH|%Py6RQi$C4x21py9MP?J_>NNCD?;D$Gw&SER)ff(lu` z$G{8twm8~cdejoHz$m|a(>34|u?m3z2!Rvt_4iQ$bTBR;p*GNHHt>-4u0I|;e{s+F zSockl&SBe=wrg+CD$e*4`vGDfg>XaYTmPzvICe};MMD!ZZ-+J63%gE@+DI2p0HG1j z3K*5^sIUXu!5Hx4MP$L{v`;}_CnY)GF`xhbjhsS$e_IOX*xEIFZQ*miSu*8%!)K>Gd z_5EJ0*{@$*tQlHg*@b1^Kt3 ztu^CLpB5a2*3YR^H?;-Y$7k2r6<)m6-sMAtiJEumsMqT)%`bbTxGiH#j9c`U&qP|G z&-T0G1S22u=QG-UVAj8~-c(w*@7VO|gX}4nLe0KE9Clt|mE-bh8F__E=VYE=`)wGe zaXEsJ7D~u7ibVI}JNcdVxFKA|<7#TJsw&Asz#mY2MjB>$1qHGX9uKLL(L@?c&=@zp zbx)r>nF8nKJ7D0L*`GTrY~=|PC>^&i^*h2AkyS6GN5Hn6LYXc}D7sOq-}Sj#w0*;m z4+~ghcZ1ODDuo8z|t-84w?*=;P+fJ+F-IoU)WA&G%Jv9nO>6SlV+<@}HO zqah)ZPzsMI_#jUHArPH}++@4J zAY8h9ISMK552Fl}IBA}9!wH+85@?7N*KP)`RMfkNOx0^xBl0_q1qc~>t3sXR;{>w9 zF99#gikprmf3#{PQOb2>=wo!1aZnPI!lxFXMPgt*6YSMNVJnCa>rp0SG-B)m#Ib(4 zQHl=2TmS|CqPDU?LUi456yWmIZwYCJrIIL*4{o(P2^%3FrZp6)nx41eurd6u$xEm3=N9<9piv@rn+t5uj+Rq*mvxn0bURz@4PyisDd`O*3E> zS3a$t#EuWt)tKBSMOObRK8b>gqyxS;b2EW?5;=`fcLy7be4A-dt@-0T-{iB14@XSm z=V!?vhi>VKcH9#@qt@<|=Cd

V+o@3X5j&c|HlOWCW#v3R}$QM1RrE=Iw{vL>%iD$u~I58Guf3he!o$=gJc)9 zT*zzpOtQ_n|M9f(K4oq_udXR&I`d0heEtS!I$_qRL`Fxq;4lCUVKQ|2@>8E5&EeR| zHB;Y^-iPNJlp^ZpsF$*TkqT3$RGikEP~GSLE!w1c)VjU)%UDh)_Vr23|luo<2y=;3YAlXlwp8gaqE~#y7N4M%S@RvWie32`{I;+M65Y??7G*_ zZ}z%x^ieq#l#-_=1b@jJXV2NfXKv0P%20d;(1tjS>|L9AH3;-bXhX zkXQxA*}mCK)KGj%<4+$Mjn;6e%C-`9MGEZ@$NZD#W(m-iB$R&+eqWuc-UCUiX*@{-w-M#ZNpC&LenY$~k7o7+Sx<#MJ`qSRp+JexM zDbgyj&YfWg+Fh0{ySH3Iw>X)^A_SX6Vg3fiK&N_*UZi;bVGcWJ!&f|voGLqkFhr0@ zziXulr@UUMoNek#2oJGQNL&S^>h7Y^(cR}G%{-)c<=Lig5N3=X_ISoNf4!87eZO2AYk1t3uqb4IHWZwlf2i{$Hq59NdA zp7TM!^AR7<>-ZJ{O@wfwz`+{((tS&;axXvI>B{4B^Dj%lqptIV!o)#d8AX@j)i{Az zM2IQ}t|+s(IPKYZM-2u$P9?~=r8wllctdBU`vjNDGFE5j$_+YNC-(3EIHy4OvPYT} z?B#BW|6IY)CjAZacKYVWo0dpA&cK0H@s|qHi~4k7vnr8^oa>SW#|E1uZ|!CKt(Zj+ zORQMA@+2=Vm-$7v$9|sc6)R{XXqtOqjcgi#l<6{A|$%;R}1#9R{bib_V_ zV#MA)onQK((sQqwKZcx5_^3+DEY3AwU>WBTX%&j}%z{v`Wi)+w-wxqjrti4&%p)I+ELn10_EK=* zqPeu27X#=Zt2OBp?a5N(U0hgcSa()SM+dd{HYR!Ho;?$0T>uRi0*<2ZU+iLd}&B36EX_tZrU8gnfm?1vmCf|lhmWkVlxlVSMkxw zsmAdj7B{5KaQgt~Gjp~bJ#u7s{Rwy_@WBfW?>3eBy&R)9qv?QvLH2jfX)stN{qhRj zYm{K>{Oi9Aq4?jwQ1D4N8pBOw07xA3EWYkc;gw@dqClH|Ps^a}h9QmM@iL=_n(*`b zABn5d)D+`wJ3(k&Zt`;LCkbeg6mNGS>?6Z-u_{<@q!&!1tEpgQ@$8T|5Q%plgc6c zZ2R>2Rpq+H48(v&^CVgeSId0wLmc~DKRUbZM>Q4!syylcuDrb8pj@Pt9v&WxdGPp> zc=Y$0cBtdTI(7D}cV!owSW8K@PF?eI=bj-+d-t}Z4G`y^O~2rtILYznk%iM67uMK? zG&%BVYNu%^w*t0@+Xl{Dw5InZ5DQr<&mKxd@fF$V6rhCdT5veUaE=A!9s6W+z3)Vm z*?(5_|EDu2zv{9iO^f5S+8ZpJZl+rW6QShe*EmN6K2N$;QLmzi_0HSSC4dmhCOHbn z?i0UQgVc(`Pn5$iFyxcHXGgZV0W(FB?3mOYSabD;4c4{kviS~dlH8)WVBMa2tJN`g zf``gBP0{w;={50Q$t=wP@*N>T33Xc`jHcN) ze{Lm42efNXwzGC(g{)R&6JxjEcl0-@#M@%^bu|awecZ9eZ5Kstf>*5S);xgC)aZcr z(WoO62TT9A!opRtQE^nwcu~KDm@|;lzU^a=vTdvT{(t?2T1gumqbhf`{qkM@{#F6% zm1SuL);m9Y8aszCpPpD4GM2Lmtnpp0+F1?>&{@|gH%o}YDN}YGEzUxsu>n8txJ_Tf zs2l&^&I;_GwCS^V7wM^(Uu|->pk_ch?Wb{z$p)8s7KG(t!YCQK09?2?EVV!}siL!e zl&c@2b?zsFY2ME#6e8_Z4KFu_P0#NqXSPrEv}Nz~WlgfUX!jsRNn)bZf1 zt1KKS`_NiE0L=jIQ&-$p7+cJ%D00m;`N_~uNDX@Zr+cAau$@t{04d9q&k<9QcgcrhtgtM<<>DLAFD+42~u}mwqLz{M@41r z;ZC`_pval`tb|etFKkX)-O|I{88~rqHetV znFKRxGw)>Cy+_3|S4e24?FRjKhM{NMy#Aq(I=|$@v(*e1^tFj&>F zbv;wL%+YZw);C^Fu*o%CMJg@@qHnKWTiJB_;`wtSP=CF@_~7c7Wqzy&pv^q}Z4G=o z%Q|lP3?uM{FbAA$x60|i*UG61HHwiho0vVry; zIvBaTC-3?CfG_gMrbl4!>d=9yqmiayJyW6PWO}e!5!M zyp&sUHN>VNS2c=E+&6OEECZ!eRBU!KUc-|?!PtGfj_KlU$(1oE9SvdR$L<}|e=^Wj zq%xC@Vm>oB*Odw&V7N(6ZJxn$y)FYLQaAR?LjV&<0BGKfugO{ zz59Ug`weqaJ=tNDcYj7|TX0Me6$dw+jD{S{q3D2fyV;GbNd9v3s(M9oamcychKELmfU&E8)JTc{VJ?@-Bc z+0y8plx>PbLqegoItbdulaLBOImv2!q4K!+43t#e=)OGTosWZhLmrYRCuvc=4@{Yx z?s48G$9&zo;rOYPCKQu;2|4c=XyjDy#YptgW??BKpVIcSyj!RX!b*#SC+ArMyMgYBF51p6KQ{mFD1WT60G_G?ufk2SfyV%}jCv1TC zZUJOqnLg(%YM51(M3v%{liafW4KS}3=Mxf#Bk>ppV~K(E?8wlC*484uKsqlT-6beQ z_*HUC{r$eu{U$jLaaUjfh7!inyQ3mIazOLJZVRRu8yJ_D{L!j#Q(@nQW_=GB)Bn$7 zD>@LoaH6!{$xkoL1T5pJI&f#{-4hc|&{6MxYO`YAT#VMV`W^N?1`=5dp}&Vr zr;M6M2|qzZ=~hOu^tiPM%UM_+JgJ)%-8r&+IU$g@@Zc*9~B5cV2_6A;9$pz%Vj4+$U%qVOR@oi-ItphnK+0y9s zNf(LElE#K+^8-@zP8Cn{JR9FS?EJj@lS-%D@E#UKO78{FAFGHj*$wZ=6g{6jKpN&1 zUi%ov*&Qd%1if$=lC#azwDX3uwj-s-E=-8$Df_Gj)5GroQX%6g7z99@fV}wHoJ>1Z zi7zUCc4?6qZGgo(uHRW~q#1CYdCkA+PuBpV8kNWZ0o*IqTj8>5)d%I_jqM(O%h_zf zwEyQE>kvvN-cjNyG=?2{pY%bYs;VlLUCGWaA;ZQTJaJ+l3yVP)jFl9SWmG^$73*8#1zO=QAB z08thJjKtdtEwc-P-s#>dNpqvxpPnK+pk(X zX3o~f!C%ilyR`GbV&f|(ug{Im79SxN5F|b6TDWwnDBh3|&U2P1M zNQ-|C3neSHOxpEh!x0$X%qBI=WlX4BIhg!Tq>%3K{mE~Un@-qW3iOHvgxOly+xOuX z2r*nPOKHh{7|66b`}aBYjV~kZjLmlb1ROsG)IT_*Zq}K#TCRWHU9eNR!>oT^ z)N6JLi#U7a`QiD=<`p-2;6(;Ne_2i)a{3+w_(HAqD^?u%_z>lXFHlz&+G2`R@t{M{ z1PY0X>2;jMc926*&(Y5omL|`=vT41qSt?&0pSqDX56Zp)2@V} z=2g7cAzA|6e(H>=Nb1q#lTS&8n4+TMwUUw^yyIlyVSBQ}M4@9)!Qms2ox~*RdKUsV z67{|*X5LF@mB&9{edwpQ>Fi!(-|?Nj^hTC<&D!*?ow~FgI9=G5g6m+-nl;y%i|=-J zJUES6Mx@qdpJ1CjZ1OMi*OyxNK!?34G?N< z^YinY^r$%_on-z0m#xjrHX~4FmieB>Awz=A)@;<$*BNQ*H^9-Nf1eMVhp`aL5Sykv z5A<{=2}Ak%)otkFM|pX2JTs=ou4LVn?)B@}T}_fA1~S@5%viW7NJT9gLvV)T(Cx4Z<$BRwspT}vD0N|9L= zz4P9Ad>JW`l?43VQxWP71rLv;Smt?zBh1U#%oIOzJ}njMr5>Wz5RuN4b+i%}&3{+j z5IoPzVdm4hcTV(3+BMfXq$ap`RLIG0wb9iNyP`Ti;Y|MYuDyFF4LT$aA;fd!>h3KZ zb_vfB*APUN_E(~qXl9+_d*fIG{7Ag{+cJCm$Sjjh+yRE+W&`}a-wOcy`ua3^75I4F*BjGM>YB*5b*9iS zOpd#e`=57ublSZc&E;@PGBS*-g?sK-sw+0-h2Sl2GH{+SP0ng1ptnnS`spdz8|VvI zz$dSCQ!iNfwwBv~JJVh7@ZARwWF%KR*xs|a;@!Io3^BByJEOi*pyn>ER0W7<@37x2OEYPNMzE!(OZ^A|XqYbRCL1Tk64a(hW-rt~v!g)=lpd=-w5 z$%70Fc{tIH651iFRG?))dGY$4ii`7%x$GUkd%&(&0S`~iaG0}Gp_Q`1HXk4L_CtbI zFBZAz)@Rq`pmYtY5*zg?iSYY%fgJu^Dv1#pf@LY78n*3Ul z>{kD0u8fZ;rY8K233<508m8E)vg`X^;W^z2zwTHZ9_N{S)b1L^b0f$++$7lMOLm%4 z&a66{LvN7t$CoOnM_*Z#7(2V&&;$o}^86tn>}gP#vp%sx88zumDvGw2)^lzV*hJiv zcG@hM9ts+zn$)@x3eIko>QyYiu12hI4Wu~ z9?`1(9S@8oYz>=XWJE+$+B`|?8@BXs=jJ0gP36g=sJs6?GDWv2`l=CE9Eky8#N3YX_zGvhV(1wTXmiNWI`E!ClQ_;n#h2j1M+G2-H89mS*h-w_L+^e7R zn1mdhF$n7$wsA1)4GH_2PpRHqKJSY4Ow&d-kqvPw(3-h?)>~8l|Go|(f*;^aqe;O{ zF>8Pt9St7xd+cANpb&uZxm$gYh3*S4XlpZn+tedH$|qTL*C^*M z*KtRIM|_cuvZO+%Kh&^f!PMvDG{d5G1tc6cd^ipqJ?8xuHfNeb{fJl%{erPh&;@cq zxQKV|-X+G{s4`+a8;6chuxM`J^SF)8tmB%)?&X-R49C+3JQs>~02ZQaykTWLcvM?@ z_Nu_Z{pyMUS04#sS1`Cn^cN7(hE00r9q?8x!SRG3d>z(1P*(k8R+i>oDTTeTSB<2{ zQfsGqf*p=dPN$#PeRU~&|9%>$kgr>i?H9=BnYGD&)tVRtHXH*8O}aaUk|&9#0HX|A z>*qF$A4mEX!8bImvT+RBot&?Ykv~>eeR`()`i3hMIj`d$Ghgy3(L#&D1UXZqs73{f2(0ICPKNki|Y- zmnL>P2Ap?Ft(;FPCoB_@B=`AOA3!~hr=Byh59lxjLd=ogF`ON2=M%_*P{#L``w3}E z2-e-VckdfsCw3(ZYK$y4^84k&gGLlfNh+nC8Q<{JKB(Mk&Kw*s9iSRyI>AGKSbuQT zB)e(8ZHpVbsI|H@`p1m41A$ZeB7~CcAuJ*>YbvI^_HuKZdug>8%3WrcCo?w-nKAw& ziVmC5gpwBgXT;4yj*pL@KRf+Mn`riS3>xi!9*feZaD}Jr@uP96wsdes{ysm=eR`Zn zh9>QF#>MR+3lfE)zn$t;n{4B#t*$N!TLcwM!wXmPb2tDn{tcFG?BI6Lm3M~r{GN5a zZ(?YaWqyoB&zTRVAJO=Y!1nP>$s)OhesqnW241uSBZkB--M;P1i@A9D@_zayjLT)+ zp0I~sW}Zh;>6TcUwLgScX{2pxcx<8Ig4v8J?P1)7hAg5(|Jpp}uC z8#Nqm1J-%Sh!Nt;L0cr&C^1h$@mgIirZ^B##(MMgduyZS53+t5OkX6*1K*zByDW90 zczhwGPJh+%-Ld18UcWzg?o?J&yGNrgvIHn4ykX3v3P`pVnSIqKnBeYGZoM+XR)mjI zrF??_ygblvDyc;x)3RRVrIFo|^l? z*PH1c7P*7=C9@Yx7Goo7PkVYA5CW&$N%sJ#Sq2M*wW-~WjEq3V>-^3CY(|7%AhVXT zipm`(HsK*^8xzd z4#<;>xJl~im< z%Nl5feAh9>cm+iOj0B3V^S<9$m9Qqyc{-^udI~2wf@RSceWw1S&Rh!gto~Wm59t*s zgP?Gt8i??F0OX6}-=5eK;No?N20K|Fx88oa5S-0d#Juc_B%(%!S1wXC${A#eVt)rX zK{sU-K0~%iNodd6vxCr6BcOC{tJSIXpQcKTrdC5Ao<*V?$}pM78v>x3nY@=LbN2(p z7+KV3zz9fp#n!FM#1N;qKb%g^+-}2&{(=}&DkTvTtW%BvK)FwATq53ZG;v0uzPg5F z{VfX)$z>)uKLn@+EL7yalnP4F#}~dmg{+WJx7npzE2b`R{9rsyTisyP%ikV7dRYAa z55|u{!c6SknOr$~9G+fTMt~?sYtX6#L*G4&`2+0Wr+J0SUi3G}pxcvB$Ri`4T-eZc zJ;!Y-(0=_Vk0saROn#sG1@;K$-j`en;Ydx{ScPMy$}PvLOX=9s29-yD&RII_h^gx< zntaIMj{W?`m;npXwZ@!2-I{X->rM1fXRQNMcnu4l%>J&Qel%(`=<_7M1enUTq(LR! z%76Ow2)jIZPL8{}&Fx1_3OiwDHmm+mP4R``^K}%Yc0s30c7SI}ekQsKZrg{|L*i#> zu~1f2LUi8iD|F%P$jJ`@l1duApD>2VtEJ&LK`;JIetmJlfhQJNtIz=-sp{wz34Oq<3HVRO{oJ#{Ne)GW-ehoc%&9?iL z6;2y!ZIqsjIQz%h^?gReW=l8)ua1q`gOZXG^fnTb#W#%m?!j*XGV73nSahq!__v3r zJxaO$U&u^)SFH!&u^NBx+qFw@Uq<5O{vKz~Oe5*UD`r!!E*{D!$u8YM3Cp+tF+R7( zGovcDeo#r<1+z;^dzG!#ff0+oa8<=r4GZ&v$_jJ;riMp!f*ed0$Ps#sbQ zvY2mS{X`e(Hf3%ybSt3D1+rL2{W9$xKkllXnDT zM;V4cXZj<@&xc1pR*#fRBO`=<3^j$Q(bL2;ZXi#4@3$; z@tu5lPE+O`ry5J(n7H7nd_yP$@gp~fhF`vX6p)1G5kt&?Wn)HCk_SREu+$)2C_HC}N4fT3$^#kC=NQdb7&Cs{As^%3GcPVw*dI1= zV)o@c^SV_pl#Yg|3TMhymbq920~^1b={|Dag{7_NP1r%Dw&Hw~&>>5<{Vbla@$(L8 zaHdUgw^iJx-r@&CV?V-7F*oI{2#Zf{38YAO#6>Xo?N^rZyZF#p9ur>^&ROv2^zqzV z8+;+6Hu#u*`t|;5=>3P=blgrVpF9}cYw8ih=X2NUS7wcfoRYrteE1SybDb!MqZc-M z(#EOAm=)h(*9X_)alNTi;{934R>2A=mRq0&xyj_Mk;57m?DIE-hMwnrPR*eD_YreB}nwc?%gqH6{}owV^~S4fTxnr=ITG{yT%rQr<9j z7g|N0TEAT4v;eequB^gigHfFYUUDO@Gy4wJ)s=&fM}_oeHHl4Tehe9xPA2~gHuLDr zPXABDWl$H2D^-sRO{o-QnJ1rjk+qfRpY71-&^=4aP#dp35s;#?nR8V=tyG zb8a1A1tNVun_`5Xl&S#|E7or0{lkKRXu^E99%I>*gFU-$}hWV8JN8l(1IyK2=O-f{?3 zilWjDmHUK-Pk*pG^Cv`P=55{SUPd{;GX5Wu92zj+8I_nbg1rQ*ZYh4%Ey4O++hc#O z+tk|gM*e|1SEblit(pcO)IZy>a*%s)k=cCCYe-21hM5g1qg0N;z?<|wke-x(c9_}I zf`XHIX+N#VM-c(|q;MpPQ#e^l-<>mOW@c2CEP6GyP z4tFXz)$aEd8L}-)s2RStoyv&e!vmPU&;jGP!Z^mdU(zzB2Hh5MDOxE;ELSfjQ@}h( zRJ!pTjyV`7$*zWNr3cl_uH^LxdnK8;Ey{5rL0=NisQlQS8!k35n*Ff&l8ngF!gO zfrAGPd6BqMy=X$&b3Byy>_6>Nd$qNJ3N2ckZXU=RBS07|VUvMX!&nv97lA)A8WAAj zkP$amhAX2lVhj$m3w(Nn?I(MWwp>`88GCNU>31P2W6$->>s9`1Mfs$rO`D!W6HosK zVaHfy$YtONXx7kwUl4;Pq7hI7#I*ll@BuOyq;3G?8cT?;%A^rf*@*fE|>olz}dRsJFGgrR4PpKYPZWCH#A&)JhNxs@-hc^%F5Ec*c!%faF7A z8aH5ti$q#b^8G?XLyPRWOi**LIVH3o$or>%RhKX$R%YzzIwM^h1?oTP z8#};cs4L2nmlRQnNTLka6Bcuio`U6!8BG$Gx&|6e1c7@4HO!4Ed;L19 zvzDVF>sS~kyJJZs5>+rUU^Eal-~-fMEQpth2}5+)g$LQH**{<0>3Ohk-(H9Q&O7if zY=8fWOK0eh)CVL+@v9u^qSsVSb{wboFZhTOa9T+!7Me# zD^Hx~`1-H2|BEsh4<>^KL4v^8aY1z!%Q=-Pf{T%C!IEa$50@5@c|pP~Lw4@!T@JQ` zDu99>8y9C!LDsoHhAScxHK=W@k^@?NH@y=M!XP(<*REx|?h}<1kaq8(pQ9~+ag|-H z0vQ8{pj%y8l70jfh-L|~q2a%~4UIY4*#<#vRg9HkVs^k2ju2wK<@vTbnhc5E=ps9-?tNL z1&w0@vqCpGGdk+*S#y_upGm`ILBQIOk< zWSP+u-_#ne2YV63dngTnfY8i&$fY4vB;J1Ynl-%=H1`dBoHAqLZ`)43?lC`lf9&4_ zqJv{TA1hCv@ZM`=+b5Y=o?44~|i{iX?9(?o0fnnzEe<@G5G2%lwe8T!K zGc?#5gW#N2iM->Klig3eb8CizU`X&AjUECD8dPK+W@vXaFTAJo&wO7bIub@*umDua z!@xt4Kt<#y*nruB_KWrRb~H~dA8I)VvMe~U&)LZpr++|9;n=-R-5~bYOs3Jaao)jt zSb)L^bhu2QVT7V^k0m_$CvLBjBkpfT-NONgVs^hr0E@v&$gZ@I(@tZX{aVN14Rd1J zHh6y;I$e7`h-7-Fw%OmMEv9|&a5n14VN0N7QmoliRZ0^;#IKslgr}F+$JsnT<5u|T z$B*T#o>dJsO_ZC9@b5|b#^IbkBt9IY@VRGeOF$hD1U{pu4io30;-;vH;z0Dot;ZKf zO1yIM!{o!_UjhQ4UoB{wZLM*1p@`CTN(Td_ zg5(7j7JraS^sOEzdRM*GVLxr@+K);AFb*K52wFq1oF;Va}nO~_wn^_Hy zlelN<{Ids>{C4e9%E>Y%u-DT2OJM@9-ez)F2sqhuaIye&ES_VoxqxFb>C9qgaFC;_ z@9vdwV&bY`K@pka^?7i-AVyJutDyAVdHw+{?}Ft^pbS#fIcYCIu$Lf>RjuvM7nj5- z{);^{oT}>%a?8ZC&a~oca;xlL>#7(@?cRgPiu;Ufj-=0r$Bp^CH0|o0WVzj>=dO?W zIw$St_qXy;nHxK7sL^dYBRA~!DaS8wm(;os+gXKO^j}DBP%kyHTmfL6u9%hV3q4VN zUcH)twco`_>fR|sn8Z=i&%sTZ&cd>;}*<9_Pw0GJv1@Yb#7(Ar3b zZc?Avb&`qIQpU~0ou`=Fna5096!BN&{)+k^%|T6-CRDm^sqF@!AOcA#)|67va)=JZ zW6z<|pt%!tjX>kgX?vhU#e>CMf|pk|M)UDHo_LH2JUEJ7QP#iI=q7o1U!l;()fqx* zpoag6#8iHZWJ_{VsPNV=LC{{J06wbBVkNILraI$!#b%lmc;@JWX-!$tjcXVNN{$aYW}AxKjSb zH7*~&zMV~9GRAGeW{5z3j+o=o)Q+#I=tGO0h2X8xVyRBlEN#&-;j{(>)RP zo4v9wOgT`wA|!oJiyAMZ-!u}JzQB!o(ysZB%anIeA)e-{)xpXW;beF!E+R#W4@i_j z7RMY^fMb$MK+eAk0+3vh!LRukJ^Xk^!Z4IfVBD5V7x2*}3II9NQd(2jZ@o`Y0BD1r zTwd?&oBWi}63%$pOK+Z4N*JQi?9agZLaIK$_M89BHlnafbN6QeMRJ!L9Wc$@{J!mh zKKXL!B8qdGXH5qNcMUZMj`%sPmD4#(c_{45O~FWMH?=Lw>*cI|~HDaelfnPC~0dkq}uk8f2jc#zHx zmR-22cf#dzHw7xNaF-4BwMhT`fG4quN!Aq`zATIefn zBGL>gKPNEPSt9PaE69s9IUTuytZ+2{bg7isB;W!O*3kBF6LR=hPxv2Ugq&(84mtz? zbIYIy<$>X@0vr2(suLa?{=f_DvxOB;B96UUn6hd?ns*tmv~Xo0w~%9kQIJ=r)bj_n zHsB7Vkg{@2{tXK7dw58M_Traw&djv3GNI{_wX^@1{lm_5YB>~gh8;(CM|3DB= zwYl%O7zi#zQTja;gYBpK2mV_u-mWTYXnMxqXi?*KaEN_~p7vAAQZ88)amQHo_TIk) z7Sk&IRR4>Cl*7q2(<#KQr&!6w&5@g{KCxA3T1Y7JscrfBSvY!qD{E#Xx zHU@a3x{ApY%Fyj-bD%q*8_>DFHGdh_z7WEb*_d^Y{EthkUu^r??e}dH*RAXH?c3l_ z-=3Lap2m&DAvpv!hpg8ltdG8q1CXc{Nmv@uB7kWOx=*4Y{jV=Y!z^Yf4jDY*3FTH3a;UULBNaL)yS4V!J!> zHc5N9iO-S0km@DeJI_)XgpRA{#f+J}61k5aX=rM`DJ}^dR1|JDvck4(QLos#%EEQ} z0V@NW+%L@fr)GsRuZpyYAVUxq^hvzLqA|n5TT>Wwm17HS@P~8%?9;?6bY#Mot6hBv zaa#><{&?+60kt`s^0odxW9+!y8f^jA6fVlPqc87;gatNe4;&Z;8MJQQm&eL|s}+eP zIhmMf8F_F1Wbr=n58=%W+RtL&J7S^YJ|e}zbkG$6h6L3Vlp}gL2(%IRZOK)gd69LE z$s;rty#`mMH8pRuma+LMX`4O0f5Ks(WcdOE_L+rOYzF$R0{|vMZl80{b*p1FCq^XHEkxVw+%LcF~AVEoM+H@1NxopXAmAPz zB&~W3#tRDpEs8TJg?F>5U9-nFiaa`glyY{t*1pLGN@4*7pX;FEi_b;2l_vz7F#dI1 zwi5+nL5Z!B0>x5Xur#-Q1`L>H61H$EQv@k*o8nektG(cXMXVY2Y^x?e3vCbFk#)|6 zt8)I6JD{_yj@FOS;p5k@b>_93G9(KEs?4rh9Lumo1E~0=pM%$j`=34dBPH|Q%qu@1 z$M4N)VUW}D?dccp6%`fF-@J*=zsTVz=3wr2Z}P?HBlwJrv(j#|YRCQWwKKah7f?K} zk}L)bwv%Dx**5+!MH?3UDIq!jM&v1l!fU1y%&rGrH%a$54Bl!KoGJiS`D2Cf+ zUpup@+8tY;pZw9PB&&XBeuKo1dw1uv(%PWS(Z95h0;A?vQL^A7Z&Ej50Io1*^A!b#ndRaT_n`| z_KDAiix{CsPw zlgp^(@%>UewQi2gg2uwHLj{fQ>?6VV@7_JhDj}{=vdT2WoNJ-{Y&aZ=oT6Lfzpw-a zJI*0W%P^D{TssjP^BT49)KZuNGK-LBI?xG0SuWD3C@5GoZ|2PKH$#A^1or^1a?v-v zGX4J%B8+=0zidP@&2_wp)+wn?f@WY;b>YHN`b-Bg6lZ3x27shV`f{bK8>>5i|K_!C(|2{Bb{U0Z>e*enzWvyQG!4|9?(%RO< zWkC-GgKc~Fwkp5hu8f5}eskuX;y2naSz>^AnSVg#C++Qihx(Yfa0`<+nN_4grM?{>YC4OB)ed(YYI z9fMj+rcdUaCfBH@c6lM9-Q#kIJV&j9Os`QLh?G2enqln zNZD{PeeV{?%>9rO-fmgPF*l%_WU-h;jofh`Iby_W5;%~Rk`=Y<=%_?Z!Z=bleRJ~N zxw1&#A+dQNeIlHuquUfG|7n_i^z`OBr+((n4Q1wF$HHeuO;L{A<_y)+(o$-s@;dPo z?I1!4(Wn!5yw>y0=k@O&YgKrh2<@@yAKP_*bQpK<`W@awV8Iwr{4IzNghKmIgMu`- zLraIi>qvMdUX#HgF7yNtCt}h3{0~D(Z%%N~Nb04iy!67VyT?9Fd0menkoHd2*vKi@ zuKV9eQ}mB@s$p>`+W*xt!`?B+qhderrlzcH2!L$jb%#R2QRuLsR}5w%GH`ZjbY` z3oL6^`Kv2(?|k8rA?H3#GG9>LdOD-D-e`I-ub93kF0TkD$u4-NmcsXEUe~v#4c3Zt zHk_LYA5ckiwrqGNTy1TC3q(#K0hp@%={It^V)OMJecqKk{o1uAoQe`$!VwCnC4MB#+-^3+dW{R^o$wDRb3GcRAXqRwJ9(m8nP-qe z$_dN=ptH>V^`D#QTB^)r$)5Ux;EXN}#B5TCN}pvD=g}KcsY@^QtVDB5h)B9_&-G2% z)Pl|$RU}Ckbhd_QyC4MUeA6BdY|q>fe)6Po<&F5wd-Ly@bSP??jl@8~V8$Io$KKc; z89(yAojh~qFT{(CmSA=eL0#BUXj+yyzB9)Fk5eZ4Sa3St+Jf{K_4W0ix|iR%-*SxO z{*mfkUa1w0y7-sFP#gWD09j6Lx&z3IIG7#~>(PQ`iqS|p5Lm1wiv$upGXn{kICWs+ za59bYfRD9xh#dB|Jnf(n-I45X5RAk%ID{$5q;mjzURCp&vn zzYe#!b@Mr?7NjPifnf{Qqv$`EPL>=X;1t&{>2tmxVWHP>_Mf`0FS?=&qJX2#v1TQElBs2h)%`n!$+lj*5?D`&g<5?o;yXf5RDlp zN(3X*e|r$8k_Q!^-{tFNmM;@g0833S5YRat$#`xXDaE_TS&E5*`dPjD=?iW&x6-!q z+4m3!Z8q-RVNF;z6`u%q*L5E!jaD2&(Vn^TvTl6T7JdEr_%>RlSsNtWik-wd<1Vqb1HIZ<}vbS{KU3l^W$C|*H?%Sf(GysaJ(TMJ<+I^ z+|_XXy>?--&we=i8};FW8N400p7ATib73IM0MRu#1Lo6GI~-IFA_tDzjuMIq-NF_Aw2t*^U+ED9VTo zt9zEOo8)noi^rBingfBnJ(so8Hqn~%1!y^bXqN$VKgOqta5yPWy?v)nCTt@0ef{9F z#}9#J*b^*4qzIRGZzzQ$eMu>l<|)!XCxjI!#xTR!<^W_t@zD1x(!<(KHJ?1$7p?P9 z)}Q!q4NM+CN&{E}vZgZWgC4mEB<;3fPJ2Z(uIy}>>AQ3de4PayyjbD4sjsMd@J=zl zSvD4VhK1XZ9QxmSkf%f54J?cPfUeJGHemmJcMD2h(BKZ&#E=#+9{`BDW&n%xBH4A671*+OCA1fsVj^)hQTHZHE`)tPJ z%yP!u*@V4t1V1wMHnpfkSR|TKi1>~3Y7h22-q7p8#=Sm13awfj<5l(1%AC0=KC@udXhA({|5= z2lKe6g|dh35z?Q|O7;qDqyUweo><7gL&h>QPw9~{mUSBC zgrw5MJd8S4%)X3o5|w7+*ZE4GdU;4#{6Fdw22&2>o=7#>JiJdn|T9zOj<)scEG{FR4Y;jWbo~7+`K6P^;u+%%E{%?v#sacUQwC1d2FM7o3;hE7QC(Z zC^y2m$oWC$rDe?bsrbDRy%Icfs`+em?R-f*R@SYbHF?KW$(7n1cfD`j zhIeUDyhhu{F=$9!8$%>#1gw7_9{-Ky+fC!&PTT9uq)+Y>fqFm8QD7>oF)7S4*7N`$-ebU=?)BhhW zie&9vQj%Bv1J~(LPO{gWwO?2`;FzII_v%@qe%gf}P<(6!Usu?Q{g?~;=`fyOQR~@w zPDRnMn~4{^rR;qF15=35E|1(dp7lB>pAE3)E#rHrHqW6$(RJEZL-q*}6>kQNk<+Zv z{K9Cu77erDUBCIv+Ma|5me*bqR=9?|x|GfTM|c@*-kfezy?|N^uVBxtEuoxDsj|U> zNkKyN7_}cg$+5Mz?pM^loystUSWD9-OTvr%eGJ2Ca622_oFBbuvg0#rm%M+@m|4Ek z=e?wj;G1p}q6L2wawu$IGi+aRI7zSz=MKzT+%vuORXde!PX8;vrtKPN_LPuh0Db+s z5->wJEk4Ayl$252VNHGgqZkb@LSP0Rzm8Vpdv&QS9>7+uPJlmS$(3XW7pwt@OrHz8 zcd=1_#0cEjCE54RXzI_d@eblIp}6vcfk5<=@GP!W1$2@8gSY2~hmg%Dkw4Eae@kj{ z__Bv5Wva2IjJ|9>sM_`wGZDQWA-+#-A5Uu2s+BlfUH059BvzmPj7I@^c^mTD;iK?r zOy0CfAIOC6N?lRdJKU1sYj_7;Lgr;twlM3#7TEG|kuhaLFT?@C#MO=6Bj^SIMRb%k$Vib@ zReu_OniEn4dMkUC!Oq1bgyx+uAQ6B(&}3}wdZ0Ue_)R4C^sW9zqZ1lZG@*qvPfiUe zxL^fxg_6U0{(jz`R8miclnf6y=(tJNGe8qC1v(e>uKS!bSneeaVGM{3L()aeEr0p@ zbIwfE42Yd;$FV6&dUh#VZVtjVOYZ@qOJ~bQ0BaRhSlfO?57HUz{G;a}hlPQSi3@X? z3v&30LMjykou*d)Y25o^Lo>&T;Xdzl`qg~>br6P%bU9GlSIpdH|L(qGx?&j${WAK2 zW~eFF{Jj)VvFt|xJ~TZ&*;jscLE6H&KhAM3fmIhKEc)XbI12KbAy+niYijcEnWe)u7O5H{t2>oPYRkP*~==Zn<|UXg@J+PtJaD z>{1=f(z8ZI1f?B2cRn2yN(D#A6|v}3@#pncS{=FSCykE!(Ydj!uq8Psf}`)*qa6Q< z$%ZpFnv;l?PNHh(K5*Q36v5v-TMGGg*&?Cp`W#p?^Uw$^NTKR%)-`uEUJ9U+aQ;+ zL7@&b_O_srO7QXtx{>wx5hU{liwsVg)IDi?S>{8NNcDX2;lq7eLJ9lgPOI)4j*{?y zES+~;&;R%MLvI1$sS^TZMwaG&&FQ#?iE2nZed;uwPpw_5k^ zJycjeT<*iGgx@oFnqT*Oeh_9TDMbd?x~0Q>2miNnJ(?6_ZEY>i1W8gHb7-4%{i@(T zNh~uV`m0aabn(S6i+#^8Ub*7+bG{F+6!ard40XnyzCLyko?Nu-;2i5dZ64?`cM9zm<4Lbw=g>Z#M8N0RfFRgxOLa&wT9y3zDbE?zFHxGI(YH4d- z3~DDn0CO~#{)_|gt@-w?b$diKlOqZI{2R7&j$FTffLns4K?$j%GD3Cfl;-}9DZrS- z%Dm}f+ zh#(5zfgxR{t-OOz-COU>XD7uB7S9FkY%L|(kr}HY=_aY~ZJhKR%T+Fp@FCmm_B^2H*5`e5yP}O=aV_3@92&+q)UPJ#O6d$Q=>(xqMZheICV;&Ab}~w zrJ}5jW=gcKPp%$DaRU+du9+)E$Jb9;{3dS(mH5~U8SC=mq0RWB_V6M7 zr+1Z<>s2u?xQ|)iD>q+kQhuFfRhXL!<^-x8d3P>7gz8y6-Z4f2tG~S(D^_#San9a> zwnxn06QP-2KjFI+y(-;5=3V9kcTt(8dmCR?97SitiTuf8$E@zLXJg8(RMFA(I%AN4eDpzh;8_ z)z^BrpFk?bK;tMbcd5X@91dkeenPn?j}ZN5^01>DKxe^c;Kk=9x}Kbu5(MKi zcEdNZY@x%8yE8|P9*v)a!^rpSL^0XbBb@lc=d{o9pFkZ0f`Uu_ShjK@9Ton{M`N;J zKkQd!L#<#Lj=WR^ypf9v_)5g)lL%&O}izc`qqNM@qf0@(u~8D}JNu)&MF8##=W8SD!?GIzj5nM4wZplk{5xNh+a zg<8eSYbOK;5RF*712lMC?qH7G>Fx5w3xbkTNSFj!}n!SIJ^ z*EVa_wfQDKd9(O`enDi|*3$~HbZiMY1+Mq~lr<^n>#3U>(r!-cHmHA!u*6Q@>7^P z16HQd$-FxAdS4viB-*_^=Esc;PYJ5P)iq_l=~zb6d5zlb6X4|!FvY)8YkrU5KEfKC zg7X~99EifbzB!^_EFWkjHY+R6&@&OEoWKZ-Di!ARKm>y*Y3?ce2gzS;rcHxG5DSHB z>gvvFS+@*4yKI2#aEI`mMDO`oIF+NH;(P&k^&c{1`kmeusH2&#Mw`X6(58XnRiTcy z0*q%+K;_rBi(`8%%J$pGMi$DJFxVN&O=r{R^LM;+Gig@mUb1rgFh^y3fxIZQxE^33 zV$B&NriDumv#oF#%2%OrMF1&eDygYkMVm>{DE6+3#Z3=7s?1kik7ne+rj7l~N`F2w zkx=$6d_BdZD3SS4p2eAf`D5I*Wu*d8+92VmLgGMp6Xxxr zv@2OkzrZ`_^&`uZIo5E3Lqto=Sq4sS23`;{Vm3ix0Vu*{bo5fdHZJZGB;t&6Aa+wq zd+>75(d9xdL{A>o@)-0Lxu|e=Jr+A+?9a)DvT>sZdxKWb9pzl4wEt7r51wih=P9uFcQtaUfPDZerb0hwIq&cy`l&m;q-S~rv?5U6&@b`By9GO zJ;E{wCC+21tfC^V`kymq&GtF`X}{Jrhp|pe#`c^NK1WT%Xj}7#pZ83Pi~jSfUcTrV z6dA=6&s!KwP}9BiiFA+RM?+t!@@Oo%zy#467ph>mzG?&x1a=D6gXK|=wx+6XP_rKMi74}l&!0aB89ZTq-SL`F1Z*3HZ(5v96j)4UTkB|(=I8ew?Fb|4 zqHDp5*O}^93=J?lJ%0T7n;!M^Y&XSj_Vr~Qm6+Z^?8P#xNahzv^7j=j13Y@n^jx)y zNyf7pgiZ2vdYW zElBlY7>J1UeS8wd8i{nd3OJD{#SxTX&RDf#SGN3mBS_n7=89 z@lxo=E?Y{m$TmC_KXk;vF)dH`Dte_UPmu04D!^EBLdfnO;b`K;m>TF?Wr@=5&)+Xw zRh|_Cvm6apDQL`5F-#smrE<4w8go4DK2_Gv-qgJ<1qSgyD>6>U^3esLX_I+t4Ca=* zn>|(KGrN_<>1fnlf4TP7#$EI#tMS>@Fh6+q?D&Iw{~o^q zhOiUL3$|7Kx6e>=$e=;O9*fClDTc7N7rzDC5)>j94OEU|EN=Gf1hrGF&Jwf2G$DMR z`5mqccU;lg8@ekADaHI3VY|Py&7?~IH*f?UDoUgHxqIE+K&0Aqy%PxA4W zF;PN8BDUx%Rzb0n;~%XLFXv88wX$+S2gr9YJXEOHN{|&h0jiZbaU-ay1R}uG_yLG8 z>{;mUxa*W!-~wv9$HsSA6p{4di?W`9|1SB0)CP|$X)Q0`uC(5AWeVzcT0P;X3h007 z&nrr4@Wjd!pD}dk!~nL(Jp1hb$sF3G4F@Z~5Q_-$We4f>v0n;mEJlumDc7Z9qY*Kp zC?~gmL{&=iqeO++82V|}J3K3Zw@0M}yf9DSzL7?b<0rr@x+cL&<*~3&jBEGkF{reM zq(GIZh8HdBvc7T3@sqcYt&C9Zb!^u1X;zonk7zM$ZK^h`3Iwqjio-hViGKY_YUM7P znlpe&n?}QJXY^#T!u>O?DRGRM62c3EA_3KhO+~amNByRUkQ6Ykpg)?0e``6)+edds zF8p|&W4dccSjaoXrb4GaTwqk)wjEF4F~?K6WL!yCD}LCQNa7bt+-1O6p7}MXb!cER z)_7L5UmJ5Wh;ZH`zp~|3>}UaCX$$l$(P_W?;eO(o>iayqtYE zo||s0gYvI_0ZqZ4f!-{~f1|6XA$3Cn#@D<$3v8J8^l5j6_R_*nX46H9 zDsYtVKYj!;nU8=^cUS8^1u`V?OBaxsN#slZZBkmAP;FvG@-5yQIHW3+ENXNU#Gzn=d<;2K7A zd_UTj#^~_6els+-b=TgZc~!D?WP=#s1ZOc_u%HLU0j>v_q6$-8XFRbIVg>$0dj&^MsJY>jL zvd^vzmkfK~pRkcpQEMoOvK7uU*vqAsjD8&md@EKnh2j6wvsW)d_?`YW#>0mP17`ZH zUoXUvq#)_=0OSFkcZ!8%2$Rz9blHX6Au} zM98b-ez%ejZ{JRO{*~7RZSz>SZ;!4fwI+?Z3VQtNcuVfu^F$lUOZP9AKTLV zY`k$U+duN$r8(yQLEq)(E>V){9ujgk_ONDftN$qf-&vK_c$8wfw@RWs9<0b_Jw1sXte_i1bK&?0=5-xdFO?|3f>v?Hx*KODunzp>OhY$2{ zt-NmY-@i(#s_ijDqO1LW`sI@+x-lDPSX;|%wZf15u$C$ zkZBD?^BCXneQ3RNmtAnXl;cDDFm>9riDqU&_f<9YMuZq9{fiY!BSAP>>)IV}t?=cG zR|EZG>XpwzA80tG=O-_s*OU1ZF0p98``ND@mM4TX-kocIW`Tral>D_*P8J;2{%njA zZ1cJ`+Lp?wKCnM3WX=ZEE$G{~Rfw)lSJ+Io6b_I)lw>w9d3->clFN?V8GEyGax{6$ zYQ0-cZVkF`s#N3XdUat^wy|1cqa^pnjH(%fvg3zrob=Zkv87}0{{2TdW!AbX6syF3 zc&PU;4{`JP=%D;NIql{&y)1Y*c~YL+s=TNF=oQZb(QlAHXS{f?9Zmjaa>KQ}mO;2} z=l?Ff*tB7nF9%tk&)j&JsxzxBw+D}%P7Xu?@b{5K)tj5g6R!;;(1?q zNw7r7B$cZXHJyTn?SqP6BSk!vs!T=%#~fq9{rgI6?wD<{TiX(Y^P_xf5JSJbE6nE+ z`ucYo5R~z|0@EVY=dAImjbB?cHrqP&_&J`p@sh?3+!ygX;q+wquK+Y`q_X_ddzzDe z5;*_9)#{74Mi(PHQ|i)1GEO@=B_#|iMN`0M!p;=nMKGivY*_DgIG}YbMC%M!y|h6- zLpomAwdwe+Rf&Fi8~VzAF}fD?_aVszvRy1Y7ZR5=h3~@*RD$2fF+R^UjJ#ra2xXDa zh7B$t_VJ5%rrrkkS5jA(Bg+PTIi9f3Ok-xNEagQmg8JA)hm4cg_1#H0b%I=j-wFnw z7-?JP;+d{ z%H(>v0njnG5K>XG7*Rxs#$4LWG?{DQ1CcaJZz$S@ChLTzT=Z)h12qMnWxv6LJ8^yq z*u`Rsog28*(~h-R69I6=2vWm3fS~$aw+i!KywCs&V{+|#2S(!xDk}r>TQB|)dmE2U z*S@#@{_W3>HLpNP*@3F#xPIesVCKn}^R@-MO_YefF@t{8Y52YvmYPwIEpc)R^veFz z9<5Fg^9DMz?%mENao*c@e{APBwMH{%?UBCV2Rqt_DU% zk(2|Z#A-ML&B8~&oAtNs6opA%o+NS11dK=Qb_H^9D;;&QW;J#xVlV&@N_FfVJ=afD zrAsyS@WvFISj7lkkXidBBEj+siLF;L9s?thBbh36+M(5$IKJWXFv)K@Uv3qtHE#|r zvAA0>|KgK|g2rbH|J|$ekD>w)>(dLre>Xs3GT@`8t>kNnGNfeb5!UYUSy;j_47IU# zoPx7~T1(J6+vMCd}Jh0o`% zx|+&|4@3BcVqi=JO^ibR9MbI7YqFQu(CoI>%|x%s?jQZGab9M{e-DRgZ6I}g6gjPBu+`T<$X zua-d>mfwWC!Btc|?uHtiAXHTQ!x_h+w z+B0!C%T2DA*DQ6IHY#yD{=*k9Up~S-94O|8x;p%MH5~(QiL}li$a@XsPvV2@Abh&O zh50#5jC)(<@pszlF>$;4O9tLf={NYX@E!Dms0Nsf`m9%=Z8&{9ucQ) zYiAb%{zopi-3iVs93KN|9VpRsp2Yd>fm2kH>D##eT2>ZGZOD4{hDG3Y0lB%kfy!M2 zm{#R&7k9r8#^}rhlc;hjJWQkpZVBj+_xR?DV`Ld!mT+1Lf7ackh5|KRemT z7TCTI>xMaWiQnI?(i+xajA6f`^i`1rKyG4t(V+-n#zNy7NcK7uZ zCqQu_Aj`=yfm_zy1Au2bFG69)tj+ZT67uAXETEF zOm7{E;LzQ=Wq0lflLlU4VA--a6zGp^WcS<-18tza)%_~J0B;g7(bALn%3@|QB3b_F3Ns}c zVS58?&N!(CC-)}TA{o(QWy`k>3El-fC1Gbko7>RXI1yn0Sbs`r!(`F>CMWkbwj3H| zvvt7nfR5uX3_d>ii-lu^;yuE$v-U~CgFy=Seg^F zY(UCPf?!|vlj%npSX9aew|)MT(AaO#jN;53FUk0lNkkfo-4K*xd|kwstRoLUvfeYC z82-1p83mK#gb6nsK3};W?u2Rj!1_8GpBICYg3v-RxfqtV~VluzwL_0g`-JAd2o0}4l;pW%-P2ORqw2* z$PlS4AjhHEx?2mKt9iQk;$FP@KDfhKZH;c-!l*5oARe8dHp((i?08(he2`d-#jun( zos2!YdwCU;({7gf>eH)tfOs-V#>Q*d6-umUHJN0-A}-A{MULi zXL5M9^3b(vy?ZM%MnTw-?KHl>%hIJX)LY#@=8s&UKCSn7D+~Gy#JhaNt;$9wR90d_ zXa4+-PS#PRT~$7wyN8D)eLd_-Q})j5znu_%N~si6J&OX1Dvr>y4f-+v<;%^bc{bEo zOhro4rIDa_)Mb)P#Iz4uAFaY~Zt=hMd=L?#i{B1(yyrR(ol3{5e> zIfiAH181H;b>gr5r%zi7Uv-o;53#d9|26;{s;xX4XJ$499l)&OEJ^o}NMu z3tB^r%3!jYL8>YM5D5tm9IF^|$($dwTcO^aR;^N`q+@a70pl&3ETs1H*!aNUsdGYl|}Q!JRWY~xE| z@&SsY!h=#%4Wj?7mp}POMPllmeQVXCx(Bqw_Z(RcnCwjDk(^7I_KWueXHgm~e{!n& z;c{|9F(KhTRRfum)F<8*LftCwOb!g=;O1los@}r`no#DYduy60@$VDLbUOpI(0Kqd zanNENJP+;s?GtR7J>u7l2Q7zN8`4-=Yc_Z8lf65%_iPP{9p#gAd`jy&?pkKn~H=!H7e>XNxAE13N#Nuc*V?}7Dgh$&hy_H^G zQx+|H9V$Jh#x(7rP}ifl6WhuC)N`J*9jq$_O4aHy;xWTQRDJt4WcCNY>+Q5c@=W1v z(TMO}V%|j@AMWc^OUodpFsO0v{r=;%Vnyig-KwZx(_Wt(-y3O%z)_DKlL0vO3(}d9 zGn|kIM90Y7hs~eQvQa}1&C1BnDRuN!$pzC?hEZ5RHHp&NQ!~b=M;#*19jG_ycdSlb z9-x;WORA9#D|8mPZ!e9CqkHvHDxwE+CEeVn$yLn)bw< zcOt!DbssHV2a3d2nn;wYOMuEmadCNtI%LzdgP-xg5dGx-AiLVvaUa|cZ`mqZ)t|M8 z4fZ})cz1GCjDD-rjTx>oYu67Adh%)GM6XHc2iYSNGBmqM3ZNvx|1Dhnny)WLio65V z_AGO4e?hf%>!vd|@P0+b4ww#eJ^&-Mes`zk+AlK!_o~u;PpTsom|>}MtgMaGx0MA4 zj_34C5L#Xm8wjMpC1$;Q`cVxJJ&dyRWeuR*~+qKTr>0n2w$U5@>8m2svu;h!2 zXg=Bv->rEhr+!O9cH!U+GbYg82&Y+ znG_P8ga{=)->I>%n)|O!IbMV{qrh+zmjI^65QsBvUL_D|BRFm4!nPJ zXm@S*K1o+6cAr0`dq|9W)^qXhNImU4bXe2y!Il@!o9xU574Zs?SF9fn{Ra!ocz?2- z&Pg?e_H2Pj?-OTnwC~ul>Kq)u>C+^zwb(|`>3IEV&E+msgu!LY>?GCi#lOUs-zm}V zhSCLleP$&(GCrOMNiJ665O*RE$nHr%mnWKSmXKelFfZxH!-tFu;wJA(q5ei(R26zH z0sNNsM2G>87ZVpSIh0cjmxdJ;y}KCBMUW;Unea!ho2-;Y!Xu{IXZwu>bV)C++z{Xj ziVQcBu_f#6mNzv9Dv~-oso!zl7gP~r@WI3PUB zf^`2z@aGBm7isnY?|rn2dHMNL@Wvs$R{Qv9ngn|BZk|h;hO8LXgIO0|Wry&BJU9>x z3X+c=6;p@z-3=MlQe#)Ds1&F}L;!(ixxS@&x5oFrmT~99s6;07<|>tTL6=b}7G_t` z`P6_5vQ>l9H29>Ms)28?&CKUj{(0+;tddC9|N9?yRE3bh=}1Q{ zv4|~O*3ZaD1Fj-TH?z3IxHnzW0_qo0n&55PnIe|Tl2NbmNq)s{=eN8?HN;b(7kj^1 zZoockT_%F6K7ER$a}nm*qW{{L^0reYT(%3{o7R<=gibO1PwOSdoIwU@<=V9mk%T?N z5`JZo)Ee9GQdUrb*>!)Lznmqy3Oh2l>kShO3S3wy5xPGL?qYvhw)1y3~B!;bFhF6mr5;jH@5~jt#<^}~q)I(7NwXN88C1lg)3)~_i6E=@IzKzHhdNVro&s;w=U34v#5ipoB;D#x{r1lCF8Vo5G z0y+F?6fVC82gDq?$F_RI(UVyQDoNq#8MiBxg-f4qF@ zQa8bXhy@?~O4B1>ZG@M)*pMOa^N2H=1EK){1wOzZ2M(u8dkbJEoDj2(9{~NAE}LWj zIIIKxm7JW2S#$)Vkb)z_fmJcrK42YOCjg4x=ltgl;Y0NG#m^Tll$_5Ye^+z!f>Vw2 z?#}%<4$C>w$i>}!zLZQ1G>%$F8B9Fx>bxe79MKQ`dFwR)J_`4yS z!VtSU(Zx!c37r?hs+-x(wGo~EW(D|48;8P@ zFgr{A7jB=&2kOpKpro5VVRuYSAd&`I>+zMu$=sU{D>xTol4@wcA1mW4NgGfbD59_G zW1D5hABzQxxS|@{i{>d~$sWR%*1gucAk(8d9-~0*F%Ohp5WJbBGphI2(vs2 zA=XA)yXw7s`BE4t@_$V~uA7&*(1hv|yjE*fI=Eo=7UXc$qhK;`^wY~LTR0p}$ncA~2b#uC~)>!|FS`FR3=;n2Yq(xo*HWvEV zTVU3V;0&zl**3DTZ16yrmt5W2Ml5$Dh%K>ah7b^#_35VOJV0MxjFVKp`-NXtO?n?TKzB5$T_{GRcFeedAq@Vg!mG+a-LgGn%uS5gw!5jMP>I$&{NC=)$ z$gF!+hEi;gr7&PXaSizdugkR-sh2KXxIm#2$$4a2Zf%j&99xuAd9((?1QoP&_1^{$ zzOsW@%?7eU;fqn%sOrpGkL6SqqLU^gq5UWcZLV!;KTJ*G{zo4y!H;mRCD;@gB;H%o zhD&@MgkFujzFSs~cdAuoUB9HagiRD;J88(}26e8hdH+5fUDAyW0Y5bdikEzIsjF*p zR@Q=~;?RQXBdJL$U)QxbZC~9dt&enpj)uYTr&4CkPdj^pHc>aG>O@XBl)h9iO&T%h#-#RcKfyO?sR!p0UW># zyzoK=z|*kCytEkk>eRSUi0o-rRu5jjlxLIAC#maB zdBJio<#pensU)Zz+4P+8VWD8m{+$6CPbY=gBk9Wo|2RaSQ*!;i$7@^8stXxIBn>Wf zwpAR@=%g5Ts9atfaqH)hZ=6XBf&gHJ@#z&$IkLG<1_H}{g|jY~|L~kSTYv11Molhu zSyHQiXOp)oUsi-vtpCCQCnpIKS3>j7tMN5&)Jgh41u1_J-pT03%TeR6SfK!GqF&ag zUg|c%Wv0sA3y&Sg#xJgX{rWZ3+NQcKkrYZ|KOpfP(7yk!ikeH8G54>&F(C5aeE|}s zPC^L-DL6@Sq_qWSi_s)@bMEt~ym8NB_pF}8W#n_gbiv<0uB#vJO_*ddyqIT9P)sZ< zLadcR4I^}0q-J22J7`k7jO}9qEU@m#^qiaagY0rys$)WAtGSKYG) zhtv#zpdQXl7L<(uXbF$F)tNC44W?3ERb|kxyD#_=_6z1>WT80o-1*;G@vorgC=t5F z=+p=bQ9)6$A8tPy8S>z|K8+dZAiXafq@=8@9$Z8k`^hNzP^_gty*H@CPbtj) zTn0)TQ5Mob)G%j&>eU=dm!su&T0MZrA}o{WkHk8T;eosM>i5RU(J?aX4ycG<|>h&APEsg-2F&L#9V%yP7=->YY}=Kq8sl ziSE(N$|`E$#vN0LI7g2j<%S3IPDYkYFpjaCGlv!^=~fHEm8jaoiya+zlJA35JKFw{ zrnoZB*aRHO*_Wh463e9k?sQsL;p}nr%9ZXCNl12C%~Qpg5r=2rFx!6{94>iwLxB0; zhTN2tYQc|!*vIbOJ79Q^xl}4h#;cfOnC;L??K5$6e;ssg)2{YZlRx+H;lp9@x@b>< zdS+frC4n4%RJTQozg)yPx+y_L7Zoj=`!8=}@Ov)I#08^orkp)n7t$_1cW;+GK)dw0 z{V+iJ@L|Bkp$`19APQ;o1CMR9*q@v*d~oXLT9f zpSE+Bnpi1}D?h*BN7?AgJEgPr3{-F4@cR>2p0_l^-f!Y43As)o;UPNhs^eWAkdw3-0 zc0mPmD+H(t z41=lGfKO+`CTKs3?k7>ZZf$=BUBKp8(0xJ0Adx(D$w^u5f_RYT5GAO&Lr@iD2QodR z&Yhb&eR|PZ*73;o&kW0}UafoMBb>oRwxtNxCi$?r?O_{wqu716G<$@W-Wd88is3JY z5cGb>|2U=L#ZobT6FYDA#VWnAojp60yzYdwPt@eF%ft^MLICMDE(}F2y?n4tare!A{aXRzGx>eK!_{5s%8hD zn2!&lS770%_GbS+Z?bc&>#%X`7PYe9xqe44m|V-9C2nTF?;0;q%%v-z)`l+B($`mD zE5%-K(`VE^^h^FR`Z@-U<{OdBSf=?%_UYfhgG6Y@_?(SD#d0sdeW64O7x)jA-B+kb z*0i;5xpQz_cS_eOYZ3WcXN%OYq7pB6#erlZm`b$RU9xUICMb{y4LAqEoN;@?H$AMV+-VDNGFVzVcmzQSQZ?shN*%G2>ig%7F^V?3P$Hw$G2^m=Ii+N) zaJhH()(pPxH(0khx%|QNpxWJ)K^BP%+r6!9M{ny|1i}`Ce*~*J(jIA!ARp3(O`GaF zka5m}$B%z;yEl^Y`%Rdz=#=*k&L`GFgBxm0D(1!(RQEA7oc-m{89tLBJ(vf1cR{1) zJuobkAvmQ+A@Gy<*Rqa!nCxwV5s2&40e2;Yi6xb)o>>D32UDnG;f$X{1e01~%|)Ga z*KX@o633|qy}o|s%1%)$*Sajp6+Hob-O zv!i?}^}rr+4Yx116tYcX3~I0bJ@xn9@rPON!a006upmx50*aKL`M}UyRO^K(d&Q(C znh9AZV*}xufzg2r%wNBX?muBdFH+J7twci=5Ma^5Q;$%2inXa=VK8AkMlOFcwdX=8 z(Ifb*(<>B__3*%v9y>NuuTz@MrG}P_U0MB)P;~H5!h=a`er)tvpJH}==qU-AcX!w1 zpLY$|S9|oIuRyStbsd%1iP3-B`4!V#J00p>NiUxINTn(HLPG8{?NuHgACIkHFS6CQ zS6%Mw%M_irWmJJF0}CADh>p_a%7~pvh@`P7h_iPj<%pJ)KOR~~kk>R5=}C6Bwy^`# zmwS4${OVOsfTp;g79PA+1`5Ea2CmM4;x9sN*AyJfbk4JvE6ui44N_BBE+Nw-ZKWYG z#Pn%Ghb?sr-(E@RivSMrPOM)P>^t2qUFDKL^|i1Z373x^KlN&b;7dRR1rH1MK|z=t zoL4gG?qo}8n@1+<%F4l{*nB{yx5IWNB)|}K^o`kBS?BvFsRW)4Z}gjy-3CpXesIR4 z&ZV5O$MUnsYt9XH)YLk`0cGDM^ zb`FDZW==ddCdQ!JTU@1)BPa6$a@WE?3cs|Jjd~siCF2yK00f;u*;Ll!$3b^~){n-o z3-E)<$*T)!+YE#5g3<<2;#REMFkKcS2STPp91(ei!VD;!YIeurmM?AsbKnJr?w$$W z-0u8+D%`1erxxx%tLSuh=v?Vh8XxldxR;(!T7JtsZ=t+V@7;TUMvc6GVR$|Vx;5xtyI_5ux9%3s1X4IpmQ)kbH)8xJ#S~bD!=!0{x$_I?M zXb5&3+<-usl!=Mp1&qY!JOeRUe-AV(jq#H3H^b*2(sOY zR2=_TG3RrWvXYVn6@_H@QE)>Cy3a)f=UM z3ZzBov_xfu9MA64?{0e#EF=C3ELkdyQImSV_s(Qh_ExlLQ;UypxDX5SDOB0A8W^S~ z!?9lM{(Dhq#Qq$y(~z-I?Ny!8Oo;V_7?c&cl?|M}HLjRiLVWCurMHkzK`!Z^Zx`4B zg*ub5)LpzlQ~;d^F8DJ9<0tB&#C1~+KTl%70g@WbXe^NIMy(s+speqB}Z*mn(=UDpT+5kni@8e3$Anx>ErKvc#vi6^o>^gy8X{R z{eRB2+G|SY5C|C<7Op5jTe`M0QfcexFpO{A{O!x%f_s)I1v~BvuU^BNZw8&Mk`82o zJRlUkW1qPmO_i`2#CbuC;`KE4vp?3m3N`r~i>kB6;I3f!BY68!g zfY$NrDkj_fKn@D|#BgJ0qI?k11Bg$c^TB=k0F%Ok^c=HVLff*wT_;Klp;SjuQQCie zOG*F3B=oLm7eqo}ARX+zsr^v+B(hZ?Ofxo$Jt%6#J(8L?V#EcHsP1dW^pt7eUZ4n~ zQON#RZ^gT}ov<0j4CVRJqes?_<{ zmKiPcB&)FUVT({+hkLWWJ62SV#hJ3dt6&BkAMkKJi+rZl_pJCqcu zY2raGBGjMKZJgs`=FHR2doWvpFb z=;_G3-@iN`A>p!0muOCrwUyUR6)A{gQaOhMNE{y~QJz80@Lkrswa{c}?w&5n)hAHmd!8k~Q9R7xL2MtmBgTyCm&=!oDUEkpj* zmkdolk}lQFp_@Ub_3EoV?|Zm(Zv_86nvt=l$fPn}?&ORj=8rPiK0_#)?s3jlw3P_b zK;yIw4or#DuIyB>l(t7uD3yLcJAqS*#rD*%ODLbECcdvTANXNQU;IIA5=SjT-69dl zvjC^8@nZEB{Uki#Iqr`jl$;hVcG`FFU?)ID5f4(lv!}Vt7Yr-E4hDm@mgpJl$M+F%P%315$3qAmf*F#za31vd1S5M<_yD1@kF{Knumf) zaBC$^P4DWUBjkQCtRY@Lno0x4MCoj~nWjs<_8TDoFhi3MIj@+YQcx7|mM3wVVY(@XNeT58NZ`zv zwx6>N z>7V~jG@et;DZ$xv9eC{!H%+`lGa@VQ2n>aYIVUV57isNFLk}TtK3;bHD&M@3KGe|Q z!;uvPC!vP3)3v#%iWtwRtB`h)qQzX=K#8|4uO58#AvNM*D#L?4ID2@Qwk7gKt-gIF zDXC_c_*CbI5fyW*s``*6CpR{1-?5`c{2I)im{S-h;Zjk7dJ}(Pvo?2=yAzDV>%V!g zE{U*OF8^G9P4k_Vx5{-?x_2L)glUvyVwtLyoA+=oC>0uHw^qi`MqoX^En5U~PIr?p zv{v39Y5he_LfqJ0cSB4{&_;FX-aVYU%Y|7SrgJ9K45Elm{o>F%EWg&ff7vt4?=WAM zAn^0zw^9ONVs-avV_x$WN^Sz7MA7_FO#E5>(%jiuYMhY~^usy-UqWiDKEDtub?&sy#-icHNYG;isPL#DC?Z&F&9#+rdV>mY@2)pBEQ|&v-rc z&x3O~I{<>$K+kK1cbS9?m&#Ar$kI|o*7p99(J-sND)S?okQTbD&*5c&!wJrSk}O@J z6c4olYu-HY|DP7c=vXDrEp3QQ_ZLkK~93(5-9 zOP$2;B^9~5d**sY2829)eYSrmUCE^RsTu)y|BT39_&ep<`^m}#S7sWA^^;5i!^3hT z5LO$YuZE^wD){RWlqn&wf!TlF_4xNYpzVr%-clX};*hXqJ+7>Lxs^%>S&$2-P_$yC zogX}Ghg}_=GwfB`ufLuX_UqAf9hWIeGEfa*fHK3^6R!LMG{<_&P(z@oXPYE_@2y+6 zM9{zNRVk3K@2+n|il^a%^koLMW5YbU@`fCf+X&p`@&gzc*?) zp$-9yymj|(5%Q-2g+Yw5MSLyIuU<`R4+i;Ws%4hWwI7F{(%@rW*^{d68N0gzGiH4i zlb`HAB|nh-Y23t;Q~Z|boWY#ERSvC3fR34MEEr^<* zKSwd$BZ3eWiWnRQ&INvKlA2J_Ji&jFskeuY)2XyIM`r2Qd4Y3ybPg@+3VKOen~Y{k zXPyr|IiFWjZQRr6&!5w`6jQ*Rdwg1@_^A!?+ zroUhLO{8)$kQi}!kb-Jdm{(4VDlhI)<#=DSAS9#QTv5UEA&&Ap7`GNs0GzD2d^p2M zRUfT(KQc1NJaTQUM#%L0)z=<%GjaU6He)w=7@l+6GlycFt(>T!oZVC=lYrW*Miq{p z^b^idn0XL`xKdqjJ>y_jqvAwUB&-*@-4TruDTjUTL8eu67A{mUI=F-LXyZGc8jIOQ z@j&pvkar@r~HY^#w4=r3S-FcJLCx-m^ zQvP-=suW|yZOu7t=G+^xFuk;V)%l-_ z(SHWf_TUr|Ubkkk>2n4iaI_L)<;#~<(G^dG%x|r0Ywau|g|<;E8hmF0J|Yd3j|1(P zo}#Vt_}Hmq;#>djoFvZ8qbE;};2Wi{8uh7Q_N-ah@pS-|OEQ|$ZRBRpRG*%n-k!ex zpEB)l8>8Y8ducyu-W7;I20%MYE=4VOyqGpkyZ0ecG;tjdcNpo#2F!&>7hHJVv-=QW zA-{yylQ9GIyg_wa#13%I?jQZh;0E%%$&A`~B2&iZ->ZaL2vJqj>pK6@t|p%~dq7g~ z!k|LwTg0d-GW-1+J(61jYvYVIW4=Z}IY<&hLPBmGTBqnH z`}lENcUs-4@Xg5g#nmRuzDbfrQ&kCteiP59XpD1PoQMz z9;QMvdTh>A&w|najkmU1&XFLzCo>@|wB_ubuDRE9=mmcgoSauMNesn7KZ96&SAs)A ze*8S#)|01pyvG^yPHvu(u9R43{w@wv=qqh>aQd&iKU!;BOjve&=ML)U4!=g%*#~CC zeaT9(r`9Foi3#6Ls|M;gAjV-lB{{?w3r|rQz;6gflx7C2KH;dV^8Cer?`?CV0?AS+ zFp!zR&yMg|<~<%|tr@){M@sB5)fzJ7+l>WlTW4at2mkoU$pIHA9*yE@|8@svXY5(w zqHQq$W#_p)q|g72+tS%BPR!8*@}ksP?d`q)(U-vK^KKrQ?3nwgA?-d%)tbO;Wp$(Y@QN7!j0rXSMYXEgS>|gZM7dt4X7Eqr>gC-)*g$t<)&< zjvMYA!1HNp@2gvX<6W}c@wh4#}{ zU5QHvi)OymT|D%=bvYN0pUMHKAynI)h_kGI|7Pmbsef!SO9)3$Pz~ch#;@tzOvj1{ zF@wSJ7Vd7wFR%RYi*}eMkuYUFy$5GhSmI8&!q_o7oun&Q_Iz@EdC^0K`lD%@{|Gbq zIa;+0ru@*kjzr?cL1NMIT_)$o^yICWhnZAFc7+FV4wdUtL8=Mo|^Ao!`Sx?zjvh?n)q*Cfp zkxXe6%{!^@h98lCB+D23AEw%f}t zK>yyHKlf2i+baFj54Mh)7wkQ{vxel5_zB}W=m^&gfuN8BX~-LPwsk-)M+4)d9XdTWH-%M^qk!!iXz01zsjT|P=}XfD6o#$0x4 z01ErIV;V<#Do&}XC?eO?x7!31~(n5Gw0J4VZ{hKEVzl(9>dcdMd z1j0OuT=_Yn`=S2hr}(=WYiFuHlr!pi=jPM32dDM*LJ8tp!+ggF5;OoRn=*3bv8q9y#~gbXm=z>r zqE3T2K$sJR7oiw02873YqF_sA)}%abgLenk`jxCHnHv|gZ{Y2Y^2<=g3)LFus(#B8 zkY>OVF&#(&DLR0Ah`Q`X&%3_jBGtZ_BZNPk{$acEAs}b!;3XgeqJ@Bnq58&zeL~s1 zzi%d6%=4%Z3(f1>_vnbib%pF=Q((plg;W^oG-jLob<%Z{`{=N%{=pg$PCSU;a2=J; zW+9qKWh0LF#KZ4h^-Oe`JKeBhG(DLj7;kn}7quSRY!XP-mzZ~Yei)6c&E_1siG&d| zpzat04I)HE)ZXex_rdY+2lH1M&^7@kYCF2n8tN%Aiiu7xgj@#;XlZC5(Y`fuy zlkQCQK9(WLlyUjkoQUrP}Ts?V`kggF^pB2@TA*hB<~y>q1=fz zpG|2cN(hj?FhOIC8YSigfcTZwp5cHKjPE!5%x~8B4FH;Pt*-Y2xWRFl4FaAYL9@j!dtvgIv#9P<@m7IC+16B51!ATl zmM+z-W42b7Mvm>Dvg3abTc#Hu7dIgJJrWUtF9M|b-4kQ zbLZdpF}HGJ@NC5TScZU$2;F*ZANc{Yx1`o&E=0~K3}-vCjATRx3ZARiuH`e=Pazz9 z>C&%be^2n0HvxqDn#boo?lmvj>OL&$h2Bpg90hg*s~pet37V^!wP!B!5Aj`!SjGFiX`j+e~7qfORu zK6K!-pR5Nb$9^K-*O7wyDsJ>}D;@b>aD{3_hRQF$q@<;p^VPJ^-$_epst#xTv>p7>~g(Oob=sC}a#NNn>&s)G<& zjamJ`Kt8Am+HswVr_3H7cd{`zlQtRsZ|rWx!C?wxRlodSd;k5%~WMr1W9A`_b@e^;*Nd|KK@ltVO2BI*!A#9TugNU5FY zpEabh%sHWk>HTx^-}odHxm?6D1UMMHy2RXF-p``xUUKuksnA(q8zPhlaOC;?td6dq zT}`jlX*wUAsq?Dt zz-^Jm3F+|!g?JG%MnyDOdjc*=#GCQf-ll&Q7|!`lpoPqA$ic)B-5B&5<&C7l0FJEK z5wP9@=p@DJQ(H1qD9;}2vIw3eI`wYh#^~+ZemD0Y9eRG<(v`EPT|OdFb+E(Z`dOVa zYD<^3hNKl%a_0&a6E$2A{UtBs_I&R1Bymq|XgT~ZVERVHcXzs8hOMVmpmz>d91>`l zv4<;%)=jM`5E~+vkMZ)}L%S&mh7l}PlCuj@&0R3`a}etgi%LtSg+&y^1}0h`kq+@L zx#lzCx?STwWJDuRNQyQKZt5N1)ixL8RVw06W7nNf9b`U;qe#OMcr3F>8*6MI^RuA= ztN4}dRYJ;zjOfmVx^E;5(3jKW>CevM5#A;cFQcgZo)$rqYaG-QcXQV$)7|3Ikm!~! zzn2q=1AqZ~bAiUN5hFfO7ClE>AZr)M=+s`;$WSGYOzPU-$pZOrJGS)Q8BrG4cZ&K5 zghZ$~w7c}+t|}s13b-yRa30e+9h&tKkzEgMm-wPl5DYY(;QxFd7K;<>fP2Niz!FaZ zc%HHPly&@uNp1SF=?8~2CdpJN2QTUD=GLj;t75{1{{}7WFf}U{&{!;4VJ1qWV}i$; z=s(-pr_-V>&IL+R2qk$9X-j)^`>42S?jJZ?ma}A@MrNfiioc-8hV$+1?V}vw?B^R4Ft=i z0X$`0UwAS#)dS#8e6pb0-SO>vX1X#Wim*gl0Yp_kc|&LNgh|SoCd(%C6zXv(ai$=Z z!mmI|9uJbi2Z7pv-zI}e~S!5 zIzo{*6Qespdfy5^zdKCgBHTsvwpco~mnDeAh!`DMG_3A6LEBs1JknoaA+Q9L0gX6M zluOzvnQE(#g}h2Dvcum(|=G!H%0 zYa=9SCn!v*7uBGztD*Wxpl05l4sOd9E{wRr{p31x=J-rfrGa^MM{0H=ABZ#!{ogB? zE~0*pRKl3oG%v|tnYt&f`-Yx~ z-^LpSViWoWu+3;(Uwxrl?*T}yMAR~C&GO|tTZn0!v}Wzv$r_TZSJ}B@?=dXYISKihFc5Ep}RMj_&OJgMz z=lj)Pzkan34i5ez)m2T+B&FOh17I%(-;8=d6EkP+t7TcbRB5{yoqJ3f{nvHik@F0j z_7Q!c^Y2^Dao>qczCzGTpSb&*TGeIv6zJdYiU3BDY;G+(m>8~#;J?p;Bmd6oWfA1K zhQ$wNPhY*7Fw4bdCtR}*B;BW?`%1~{ z*N#DLe;Z1h)b_&(vtuDv?dC(6jz>?3_8T4SS|8B=N~0RcnPHrS|Xd3NOi6j{`@NUqxVn2sHvr zzOjPEdj0x;oFr5qrK`?<0XK&S`Q@rVmeID*fbqrN7PR9MdD+mqG5+|Z(l z5IV*o`)_3dP#xe&0C^4<-+E*CjgL9aV#9%G$|R#Fx^n*Jj{Vt7f__efigI5$Uj4qd z@WZs{s0NZ%=F$VO90Veu@@wc5XuW02&fTrI9Y21B7>g`|G&$^3N121@A4b1UiD<8= zD1#{_&MW-|`2H=RWBTba@0!4k1RqI&Zr0w%{v2MC?L@daa%j^2Gyut`_HsYu3(hY7 z?U=wuWntKlin_mN!cXV7eR~g&+p9hQ3vgB~p5wlFHg)G-!D=BQ?(V%?{x)FW1+a87 zyngI?`u)cbJ7D+<8D?Hmu^*WB*BJ zR7Sw7^LvGiwDeBA9O_G4J#-%zn*WLBbxUj|bLwBAI(Gc{ZXTH4GUNoD^EjN?qExhIZaJj-9h`k-iT z1Bq+|$>`0u@nV0V<&;MN!PrJdxh4BP5k9t1HCSZ4)sdVhB`J>~g>VF0qOS zB1i9cZS|xt4Gj&XLiXfW5@TvG|VLu`g0`)z~Yzbc@PbkbMs|!GV1=qQTneAK|%+3HvU?0NU>RB1~VURiCzM$n+pWrUQyTtIZ;m>e^o#0eKRkzNzu*MPldIYtO@S&;A z`$~#-@2&L^6k*U~S}^QL+l!U=NK-0>E)-`YI*!1>KSpw<5yTyM>fHoUFEZJL1(JD= zY%QTZ{GV1=0&RuB1l`Tzp4D8pD20s>LI@F*NOSoCVX?}Dp^K1EBUn~kXN|v*VL+K~ zk`oTe*OAdlq`b^`ZG5pHUW9$yQnJu|I=Q+U6s?e)+E5XvKzAkdw44Xq>C>NJ1`ciu z5+^g;C9;X$JFqaGv;{u6l;sg5`p{`$o`&ZievUYp6~!wYV&=iEDfA_5+1&NL-7TpC zF%iKipg>PoHx;gZY80Esd&W;sf>X6gI+RK>Eq!zz%1}8i5AVr@NBtE0kk=)t%Uq!~&&p zutH_Vw~QA^=+sukbwHzqDvE%aefr}DC;-9mszDx#SO)lzJ=c|u*7W`7O?z>dfG9!E zW-KaaSBa^YWF@lm#>{zyT}XuHWV6Uh?}jAr(7U?lY%Ceaae`kurn^8#U}uf2t7Up8 zPsMJ22r725nL%WbP_L!Fvg=uhvsrJb(y%CNu&BW3&JY}ki;c(uk$I}Ts;wK|1siOf zs0QFp#CGKg8!opgir2Z-SIF%+4&3ktMeBLd8h@2cCNO!xlr0mTxh%vjdE$g=-&X;D zeh-BI5Gr4uyjXOAS7Bjw?=ADz4-5K}pw_k_OKqm}DW_+-0zCq*Muj8p1H^cq)D!{# z!nYZWk4pu=8mnjwT~C<>ikotKD0Vv}zQQ`bcO&wxT)LU_aE-fSPg0Zx(;#h`{q}7y zh7sW#Wh&&8N<`1Ufxo=zDPA+n<;%}IP5u#^S5(xQ?*)1$_URe~DPuPT?KgDY1QwC` z>C=PQc7#BZ5+UtWmRixHix*~csd z>h###29ahA+(8Iyg85O-h5-KPc=}zuxPeMX+3s*@*~uUoGn125TcKG?a`ip zbX9t^U=zrv(0ouImiILtfJwrqP)}%9X z%@=M9Ap){kVgEH9J$mw=@f&#m1%(R(sQ`*0zL^IP6d)9otCmDZM3k@6z82VIEadsx z=!Gce?`E@du`AK}C+?07>qKgs-4uIk%W1=)?fIsVs7QmIe0y`fEABFhJiTijJ9KzE zq1-r5fHX{{d~H()Rm#f9yaULkP~H(4+5J13#lgofeSY3j>(7C`du8~I3i3_ao&Y>} zuy{rLzWkr`CISc`b&!YNUN|dqJq2(*bj=u50h(jtm*4ZAX>|&4Cg17Fb4J?QQhbtZ zI-tgVe$5?|l!x#1eFi3N1$sY^;K`;G(zR19;+q;Y>1h!l;aZa|2 zpbpR$iqSOk=}^`^h&(vDK#jqx05$=>CXPM;QxwL4AmDRk$_Ob$Qzf&lU1NR^n~F=T zvUMc~$)6vo^Za$1yNX2Z!Pu*_65IQJ{k{%zogwg;+VWjGk@$`{0)24MF;IwPcc7)P z$rgXr$j#sYyIfy$=5e3cwGH`*nk!ezNEyZGh((>nLpINpGUwzXD^u>>TM0$T#fuE! zCXV-xt;!IIEzrT3i^!AT>~v?ZXU9<$%`rI#OPKBBw$fRafdlY2j}W|D`MWpCKME8jTTMP+5I zRBUWm`T9fZ>C+3h^C@#2g%X?9{2MycNanwPhkjrLrtW@LJEG zcOzsXX5r1-;YwckNJ)Op+tW_ULq|`qgLj!u3aA2hygR_uMQ`3H^1MNi-udRUuUo3` z(m{3+of7Pn%a_~F>2P0W=8}yrl_ZEM4H-C4QQSZsJC4J<34&8zUM@jOmVlxu79x29 zAJ`NZ7yaK$-gmKcG2EA(;OyYA)y35Zgbo>;2hT~A#9btqOX$e-%8C<+EQCV6L6{uA=exiCvJCv2^(qy1jYJ5=`q_<-BT?Vj(GiS_F ze}8slquy@$(3u<`A*81H=bjPEF1Ugo^E|13i$^k`u))geM5n5yA{+okwkYtRc>n$P z9|it4YKOA>tqX*+5V480tgH}x@^mdCGA9|7jQ>(Ou(C`&?%8Vk4}P(}GcG$ID4=zN zhO?!VBAU~i*1<*vWE0c5-L+mTfMv)R&4n4_HorT+zRc6Y6 zH1%0Tq0EyTTkof?Y-`;Bq$k#Wm3rOU{)t>EYd$bL>bO(Y?KgXZe>>wVF)OxR!G?w-)?|L1=`8-8+Y)5Yzp;Z#KG5!4pf z)Vqoblf;%M`5pLlcu{EcxU_y~?D`Z_d)w+I8i%qt!49wcDM86nJ+)`4G^RwGO{X0ZM^K8Yu4`FT3rM*^b zpxaDhnQ{kZ5tWVnu=e|S6=VWpaKvmgr>gG5pXS!DS*;z#vLEpt0qHtC?T6wRRfnhI z9tO8^CfEU)t<6g^-yK5RsMD{X7mTh8=Woy4`;I>$p2Z*HX?n_C;RO^p83Vw-?J@+2 zxnu@jdpuwGalpMqq*gv{8TAQ-Vo1t|kIPMAjzm&@8nxt04VNAY*eMBRKi{l|HG+$e zK$-Yx-QZ8wtok^5?%d?}4L8_|1I8c(JHjA}Ljy21L}%nx|F6bsYH{NxZj%p@-ITCV zXQYJPiPRU_>oVCwf2VLOQ=r)Ug1TGSCOOJX!n!Xy{LR2NeKB3weve0{pt)ck%V zmdXTkpNb654vs4i9Xv<~?xFrmV9)GYJ$)nyDG(|3tUr=6+mQrho_w(fMCq`^?;;XW z6#U0YylpykqmXR#0H!*gOg* zd>f_%%=#jCjuGD!Lz0s50nPtetwbspV%uyK>fIe%?}~_(AT^<{C-Q`?6+|;1_VbU+ zAMtOy1HlF=0P(tSmysz1>)xkkJ!fC696@r7V9I9HSCe{U%dxdl!|auv;+IHqJ<~=9 z+upw=ZOM+E*-3T7GQ*9@jssVS_3IheuK{$YpI?32g$oeyBVZ_2{B2&%3mdUv&QKA) z!w6B1&J?vt+EZ6>WDdu9sx*4;N!?D1iH*xPFr||INuaaP8Y(?Owg)l|tf0M4-1umn zM#9?9BzmJ3LH2#zEM#~W3^C|^hF2D*GoQj23_-C(+3z;t!O)_jSgDY(s)^f=)HQFB zD190<_~+7qfYIoP5bbVaxHvg@<#4|#Wuoeen+U}fV^8}LBd#db&YjTIxbruoPm##x zplIF#cqr~|Id@;oLmx2<2>m!Vb>e}ToA10`K+T2u(jE2ae+wBjXcYK*taPK-sj>pu zO{;yEvBe6?_7n)oUAtngb&QNcuoi^gP>>I8uirec=`3ye+0eL~0`!x}smAaY1`bCf zBw9q!Z|t-)DuRK+q-pSYZ$Jzt$|S4GsEC|=p8PIcY84gUnpC!%qatY^%NbdPED|E1 zpP@!OFO77-1`$=n^*WBNe0LA2QqSqn#Ow6%pOA!^iULsjE};>z}7tZ4cqhOZodcT>1*6=A6jYpR~`=u%E#pQPat6) zj84=_;S8{7tF!3$S{yMveL}8+Ci@-fl@cMSYCg~;sGbc#Im;pSDADUvGOHTv%r>|u zr%h(j*#8N0@#ss4+Wz}CFl~%43%mnta`zX#XsU?68S~yM;oLIS=cjKz zr)SHu`FIwN5x9yzJDYbUrPnKGYi)r}6W^Pz6!c? zC##6rhXC@99p70lA>N6D3cfn_Xi>Jeu?OL@7XlyR{{_aKdVJE9%3GWQuvA`Jr}rOL ztyqzRIR#>k@fLlcNnh8lF**RWn`Lj`$mbH=%EAd@j^*sS`@b#20X1(!eHYrHh{ncs zVtGz+f+30{kP;+!1U;(ryC}ZfpVg9*UEaw^J%TRV13U_z32TFz%a%#Ur&8NKF&&A5OjV4qt=aLgn0|k17Ie8c9|@akF=8`<~msGVtxqRuu#c9+x%_shwq;-8udF zSmlr=&FLz4XTNn*Zz$_u(fyKky9zfo;o{CqW7V^EKX|*Q$L%XHtxgt{U3|2jXM^r{M^!AR3LC zd{d5ld&Oh-NhD=vAQanTRgBLTVsZOl9#hiTVCUjEyytwg;NQQl1FkD5mwBtb!pB%%&*2UzucMNche1;%kXnAF{}dnA_gIYnv|FIDLh z;oTNqcy1$N97H2X&vcd8kuXUUOJyNI;R>85JCoaqzHj&M*|l?zZ`yS0wEP@8r&|yr z;J|82{As*BWMgxdw$mwD_Q~tCW9#h>`V-(c@L-}Y;Olm1XK$d=_ekx&+M}SvFw}0C z0lGGi89bqB5G6xoZVmIkMT4jWXREp|f}WnS60S{frPT60&61eKg`k{8mWn_b{5v)J zIq~tKk_Ch$d}g&PE}Kltzf>}y&$xbL50!Tx>uxx@so(L+=NaBB?c-vFl)CWq=6l{& zNLLus0&{F&sGa(Cd8^X^b8pjW*n^7AlTq&X>eY+1Jgc!|v%^-J4c*M0DYAf2UL{<; z>Qe3xBF6=hg9a1u)zkhbISC?~HX<@IvDeX}h2%{2?qwbr!MuT5<{j_W)PlUXWCakX zp%UOm{cw<7G+cm^;0kx<#@QYf;}w9MP*8B4QDKDHh9_s}YPfEdLF?r%V~@8jmz}}> z-_Dr&k+n0v2)$HyM~7Gy5o@R>f#?%ovDLt*Y<0k8Fs}aSwgu3=z|kK&+Lo;z$S^%G zHj{JxSUTF#)R`}3TqCV-^~EFUabq(R_zVICLJtlasz%zb(fWzQHD zXP>G2y6ac`p?5d$smYyDJYQBI@!!{p%d0Q+Y`q=W{*;26u4&(r@uZYv`{*!+98KgxUg(Ez|U9p)x;AE_eDsWJu8@Xdxyk?p-d1vDn+-O z^Ri&?fL-zN|3s55n%ft6drR{~MOz{Sawtj|KS>D5!He?nVNA#OOjg2S_~_C0?iYzm zlnTu`;O91M*d^DF`n}Bq^_`Ee9@XvPs_^6udvxyQj2ZV#!(v}70mDp^0-*$H0l7Oo zL+OH=!G~S+x4VqD10NAhD9@0H#5J+kGZx^{nwcWvaQ;mny6gW;u$>o;JiseRd867o zZP?Fg5|9}oNBox?DO+QBheQPT_1@py9{ieC(=^vI_?>RJ(g()B<*PSjb-f{w+MGA* zTn;`@%1G+y=Q^t5UYg+&EcE1CL~#Josygp}O)|luX^q#CldY>tYnO_MF*M8_kflyL zgb=*w^tbz*Wg$yu3M{Xzw5cDs7^oRRBqEsI>lYzZn>w&FAYJ3vd2JoI!v%x`#4cni zj*ijKT^&H>M9pQ24jgBOMg^XxIXUy8-zc|*TY@wADnX{?=f@x08u!+`^r@T7Zr6@A zQWLsgymV#kL|@PPa3x7vFs4jwk5CbpH4bgruRVWEu|kTPLA8+D15csRi60y_bjm&z z36aqQW`f`4ry18F47X6+3-S^fm>>udAy1)Mq`Uh^ztAcGYC;G|u3D87vOEJ-l2fQ! zb=0Fg$p^>J*tjKWssu(&*)=MnHvg|n*qf_=k87Ij?UemETbXtU&4v)4i5`1jl->OK zDc0I`Lq(SLyUI#Y8R_~WzOV0Vz?{DseH9WrVyiop&$~Sms_*^R30-WF(ROh{)h!fz zl=o@2td+mU5U+fHSj0W=Tlx8NR3E9Q>u&g@->p4A!>*l!fpZv}0yfcby=MTP=CgT! zisttoR>8B{WoQ=^X*h5FF?(6|x+h!0uC5ELz1I)DLN-^jWVBm!Finj+9_wI^H?rNW z6dBqt4{j$KX@LMRhnGclJqykc6)@t|pYj^L>s_V<-?hoTzvgk+oSmT-DL*O)*^})!~?it{?hLIY}`lq>b`6Rr)@JF5hKw) zB(|*6goE8H_J*JLeAPjS!g=BZQEtYJ!#2)n;eGk_OY8>PlS=^Sp8&jh~TH5cUg$>-+lAzP2Tv~)HNDUFBzvz|)^%u`SraWu7w6;n~! zK1xfvtGpf6HEDou50CEoKgh;1i$AgnXuos%8Arq(B^8SG{>>HI}CtliO5 zmYt#}y_}SC-dgqCuO2JRvXw;g0<4AD@Bxr1yzq?SR>KCDbww^r6Y=hA=Ogyd4Lh*| zYozUg_p|#*WoJg+Ps^TlLt!8$OKj<3vR1vfA`D0JDv*Ab0v%kjU>7eGp@^Zk-_c4c z6L(rV_W3%%1mR5)%L=V#%aQ&mIP(4<8tM84f5}CXxDOEj4xm?)pP>!No`~6Aym+44 znEMZ7#ilDziP)O4m*@p{^fGI++_smq+f}>KY0uvL zKBr}lFS9=Vwk2`In}qql%AaMm4#P?$fE&>dgH@5V(wLB=lO3OOSn=)0)pnYWQaW3m zd*sdqa(I@m7h^V^PL$MM4a#00Q`2tz#RrR=&y#J8F(DMu4ci!nG*0Ti_{w?fT(W|0 z-Zd{3%j8W>4~)9ZBhnr=Y;UbqAtWL`$LBe$o>N^??xR;I6Pm+L!QyDS!2hjoYs`_} z&0!G&c+NQP34vZLGQzgjhiS_$R@%oy&a~&a1j`#86(pr5-1A?zvR^OOvWZYi35mK- zSr&iu@1dLddAia%-NN7R)LrhOLtv7^2hVc@ZO{o_(;SR#?8X{gm5X$jetMuH@cYVO| zSjFIlTOVwhMm(3?{LrQ}Iicukub?1=O^jtLS{iFy_dkx&o^MQg4ez8_2Q$RWzJrR+ zm}kAhQA45%Igfyy5*~Q|-R8AZrfHTOJ-kgT;rQOj)XWE&Yigue{%Dpu^LKb2Oammi z;MnNjn8X)&Und7a2!^ndi4~|4UfNFpUf>$kPnDXBu=|4topVGiAYVS?OeFZfeW2r* zri2Db`xxw@PE%s9Nge>O7Pt>TyZ34%bco>uj*G6D(VN7J!~3dls2L26M2@dLU+Vdh zaqh#0YF)PfZP90}`_+Wq&94}@&}tIDRUJ0KG>YwGu!P38)M7M0#R zfEf9v`pxk3N#r*k6FBgFTf+iXxVyH;V}^_`U9OAEJTXrQN{Hsc1?|$ zmd?q6jt_n=y8?hZ>BuM<97l`WzaRG=lideb2liHL9s7CT>h4O(+&ncTH-3;1`k{z`y%G%z2WbMcXm2y;7g`3+dLeH{Z+dERbI&?6mFyFSa)Tcn!tIM^ z8L}3*nsAd_Ylj@Ne{(C9^b1MG&Xea>X8gKntXxy}LglQD=fhT+^JWXT0?E^hIjM&- z?}(J6)TkiBx`8pa@gC8!J6Y;lDwC(3mzO7etej$>iuwn7yjlW{VT$Gh+_|94X}klf zAb&4+8{Nn1N~=+(vaNN^3J+t4+9mC-}_AVkT=sa@tFHKBNLOKOq z$OJ6%uNkpWd&peQWfe4;*DwbKDm%MA9?-wPCol^hyLZttg(aIuta!*3OFkBzfXGMl z-nkpNf>VlXOj6{XCbiMNefWxlW}oz)2W}1hgx>e=^KON<$;Ypr?(3APl;y92klg`HbE0GtbEY9ygtO+nMuLu$ z?BGSLfoJbFe&l(SXNmDgc_%s05ek0bHyov?!kU+#G-muH+#akvd3NW_m(<@X2D zeCOcFNFHxPO^3bJvfouZ&I)nZE@OF}aO?47)2v+`o_w!M%$$0o;~kC(NR?RXS8$Wv z4G9?;-KleXBu0W$k!6M?ERDBWV{b!oE_l?iS~B*28mjjGnQYp9OBz|D!@n;NtG^OrATqwACXBhAml zQkk>FOu^Upd&ATGr=W7EL|IR%Cd9wMCO8-ex(~bC)1&Y0!IFzFg`ADf%Zf`-b&oCR zv*4=K_`#z>ZI32qX7<9iPSEDT#}{fS6jxE-aD8IC6V~f*wpi`$Rjq(!HOBG;04smnqfTmHaXfH)6lg`kWb&{BUcI2UK8 z%-p(#9orp|%q{P9AzRn}@!Jh$i=?x4rzF0Xy=0cR?(auM&ZpkrK;XA`?{0?+Q3Ul- zlzU8?X*))ut|7usYDZnOjc%8Taw4y=f7F;RbitT2K|Wt-JUO=~jQf=6&K=#8il07h z)ynT`L{`D)QpkPxZEok=G^{sGu(F*ee{%Lm%X_xV94vc=-_C&z z5nXiT;NkeE!DUzs-Yz7#Ua`A|h6t?%#XIcRgD1eZa$t4vHwMX#If^UViG8Lb17vq* zFOu0PYm2|E1FRKwBRV5eggio*U#qAJ;fL|S(eqq0MrI+ofJ$-Gq9#Fnua^kzu zmXkL-Z@GVc$jdS9SMKR}P^xEblu4fv^H$H&okAGQ{}|1#Ft@uFt^+)okPsWMW6$*` zl&t(Vr62eV%vwWOT3GOG{4pHIx#Ja`n%Ak~4te+ys!-NFg9zt9478S)Y?>{S-_Z&10M z>WtpMe+`t&IXDK>_YeQ2l@F)HO^cXue})K^EnY4D7$|BIg@wO@VYus`*YNiOLD9Z> zM>pl#HUEP79>j_ee*|8|+S?1v#{@kJ88f=;7R&qJoRe=Ti5Mwob7Q&)`j$?bjcwoG zxK7)%AY<^)wwcq_w6y9@M}!n~o0b%!`d@grDc0M@Y0h2|vGD2Kn}uIi4f_4#((h}g zpXSt0Jom)cXo^ag@DoEeop3LW=qxQ4VLU2fq4mzhZqkW))pH(C3qKap|75q)wqupu$(w^ zLWik~Grmex-qyRL_b9t$OIHyng1^JWeJ8S}HTXl?BWx9RT$Ttc{&%&>EOpxAv`J15 zDJsUXOPz8maQ%hS&ne9|YNFcVGs(%#m7&D??C@Obw0f_GxD8yrZs@&4mp?|7oWG%j3@$>BG z-&t*ctMQ@F&Z>@Q6)6FH+lBRye3@}%x*+cb*d1 zKcGPNt<4<+4j*N+H_~H)r_!xAe^_}ORy*LF6$> zxNWrO`Vt$i*m8$PPwZJzpBFWA%9M??C}Q>P2HC#oWg@n3XK$~`+`sXGRnxv$noT%f z`lb2`es}b^qP6@Rnk}te4T|^P_eYL;JM;dt0xfzCxbz@L=Y-)YQ*io_At)SZ}B(BsZWV0$a6IHrmka zhcxg&7dw8%1Za6)9ou<*({@=t8-6v!*|V;2M_{bu7P^QJFn@$Pe7_PRdD z=+AaO)@XN#7t?^>hTQP9h2bs!nDm`er!^ayL7rJx*RiMY2}@=J65)5CEHFS{gs>U?IZv`2EX}^9#k5nC3xCNvgO_l>Z&eZs#su zEKRoh2qP^PpD;s(dyj#%5q8({y*DJ6ZJ2D`b|)mJs%IK0n!*^xtJpiZrDmtax$F6B z=easeH61m|lb+##S-^0lze0VB(_4_Fz+YGW>yBkAU7Xhc$(1858$yO3Jf_AM3hxby zBO@X5Az>6T#7L%2+sZ1Ixo*B0sZSOoN>HZd4PAU?LGQ1jzh@8A>(uT1-@A&=0k`if zBLmrtP+pT@W)|@oT}@05kk1nZlM*B1`#7!N>o&xiuF#G%-|(_;l<&6ym)WyL82Hgg zG9hRmJeq%fRv$3EbfVfnC;;Vk*qVym@SZ~3uNOS9>U#G@K$X-M!)Pj7s5#=2jQ?L7Mcq(|XxH!>KxU!() z>{;|r-_rArP3xb#$6)GuX%U7jY61c-`mlCqW}K>)t$6=_6Ac?4uI*b5k2&hy28TBS z%#z6FmK2k@&>%8o2}%9ZHGeGj7amXeu`J8#)k%~7C;S}RhXl4{|GmnPo(5DO_~-i- zQq+e&&oHJC^Ivg@MQi}>Dj%aB19snAe^E{*|=SSm+17w_a(2CQ!A zzj2rgmnXsIEO1XgLeQmt6K>>m8@%)*82dvaxo1ZV+D8a}DWG@Y%om7kb(Qc9CLp*+qB=+lgp(=BN66*)Itz ziMznlbFXRv*APz&;fXZuWAg{&SOp4~rJdc~^L|F1Z93D2KyWAItUkxdczR{Q#q{*s zKzHxnzxOQuyLa;J$3drLdsc1>x%~CRoG(ii|G4yyj;swUeYE)T2XN$kUV!?NrmW-q zx(H6hx&ms^u;=YEu|6@0irYWr?6!e$S%1&2Zu$LcncVB>-Pj#q57VEitX;E4+sv#d zc004JMNj5n#t$$SMK1k{BMYSvR$^4O5 z)%*4GSJI4Af&mfb$|1!$_$=KLmUi-@+|zEA_TSq9Fw~lHGJeDDeiIKS$Itk0$r7>i zNUej6gcgPgaK*oqK6GT&-PnH5rAJw+*+eYvDV-|4snmFC8@^#QPF5_{7O}tsP6f*z zhnNr@8sS4y$XUSNz}K(l*K@bS37%{%#H-Ic{khH`eN?-r-ESgS1$KJaK~L=KWF+Go zA$KJ-w<7YciGqIQ+Z9wq(bqExusCOHAAbS5lhKq$h;^T9fT#VZ?--k>$zO|l^6T`% zIywN6^Z>f>>-s~RDPg>)h%KQqJ&KzjfGr<3T_MHgcb;t)U%Ceb1aP%EwteFp-QcPX zkk2hr-=mS$ewP2eEWI{_O8`ZkUSR!`nT%blb{NL-^SFc)o-Br*sFxh!$Uu=u*IW3k zx-6?~*_vALU^vz9>4i;WSs~5ilcd7Y$=!bXbd6I(pQN{RHaF!c`&zs2iTSeE)O-6t zM=2|vqUIY+1S1<&A@fE=k*KPcczwD-DZRWqYjE*EvC~lsq{+u98+`6ILk1Ni({jOR z8Oy3Eh3UYdsB6UraE6;`jiE;5%zL~Fs~`}FUPPsALqkulizj_mH86RK(l6rFkyJyx zz5ei$cSR%*f$)K$e@l~o*Ff6+AGg{5xU}q2oFBxQy{f3;mK6GTF7L*cy29|kYY$Y7 z%jP~b>r842zZ0EHLDKaL*Uz}5Nx?SDJ}ZeW*fX|@v0L5$SSm)Ut3YjaPS6yQR_P(6e2PA|MhddJ&Hykke zh_3zb`umvgqBB-bwXRleEwlO6OCB$xqux+|)uGh_5gDalCdO}I9= z&OYymOo|{}D*NeE?m`tJA4;-5R#YS}8@(tpI*H4@phKVTf9QUHnitiIHrS!XVn1uQn{9+9+g`63cGCEsRl zSW=vq{v)J}S%Z*+E6+1rw7D;FYYYq+Z zl0`^de`s~Z%8^Kp&b#MGK{<<5EVBz22}_u_zTk1S7s5W;>5{qmB!NbuT?{>^;Y>U^ z&6W^$^2v@S4KgSS-$V--ppUhULn_j3(C*~6dVGK6eDcZSC^>^I3opH#a>VT<4G@e|R?5K6vZ2owUL&^b@MJkl5=pP+h1NeDn$CBW|1kM2} zM%N_lb!f5l%AP6Hwk~~>(M3=6Nl{4sIeg(PbkMM~ z^Me0&!MKQnp((`6pnrcWl%sqxA_S$bZKbuhvFsk}>QwY@eTjqS4-W&v^G!>*5HN85 zynzjdpZWjDUcVGA`{w#Bx%4JmW$EZ1BhJpWoqCi!7{dKnH8_5JcNl}5-)V!TL z`@#PprD<1nvMmUfz-Ef3(OqPcL;8;!_WJDHn;rH#%m;qvwPc>U`DNtgD_4#Z8qHk% zBdu2vdP1-m7zd4?3l=R|aw>k5x=m-{!eXp}A;V1-!Vy(Ed1|M%b`FD`u&2U9c@nfw z3PH!#=4V;jAb%hzKN^~OBE2l~N&CSSc%pEyVUoUx?PIp4)$`D@H*q*WwNsJY*hD8` zJRzxcht2S-`f43oC`6%;oN@3AMI}W&RDUZ~Ejee>$Z=`c?rMS=@aqTw3(RW#dQ&!> zu%>zladN_22O~xBMA6e4Wc139jo#(-)o|k6p^A8_YQKt-u=hUHh!o=2JQSW%wL8ym*Oe z>%OKLY>lw()y^SF2|rawacUV1qfQ66{J35X$Z^c_%~uHA19Vz>J9;Zote7r}+>3q{ zsX6uE>mWt}Xf8or+9@5MOcZR{nhVzlY}0Db4Z#=m_wtd_&wfJJfLTmJg7#Ikk{M$I z$S_3y6wZ|>BEN%2`fC(w9zU94BQI}V^|(v2!{)P-cExpi+E_ThPy4l1))XDI9nU`m ziC%Kh9O2prNO`^BSs(50uH4DyTD&dD7nCV&UTX#~*=)6u(Oc={&h>~Sr}gi0Y|;@H zd36G_`25vy4M&(t@O8R=fQ~Q~u3&CMR3G{|st>wavW_m_EsKxX zqCS-0Q7gq+EL#*M({}Rw?#09lfcEZA-@~JsS9pP|oiX(0VnrWsZ+D;y`u1-L`3uhS zG9YR1<|bFOq0d(B|K(XFm38Ul=bJ4Lr%%10L!W}K2i)k(pEHF=M$gRBbbmP0Uq7%& z`pB-fTkR!YpT5-CkTB!)oY?2f%2sN3-*6yNr&+>v_G~ZuZ~}h8C7ms!^GT16a5Zj6QbUZZN*E-KAhKGUHkUA5f`E2neAz%_& zl*kDG)(r8=(?SAB#G24;FCMLP_0Q{j$qTkheA(+9_9$wB5e=^ASo>ca3GsP;eeGb> zh5ru5v z!nJD}Dv{EazQdKZtV~vBTtDQftyO2Kn51{rW#w~g69www24puHpR5vrOAfjS6b!_Nmk6V^!gUq zU{Ph=d7JOa#BSQ171N4dl|)Bu+05uDGR|)+StMM(Oan+SFH&6PR-Z{!nD6FxBzKl{ z_pg{E1hE6ro$p@kXdEdW`XWoGy_9$H+O;24i^8KNbvs*X?-J!&*pji;E~>5npZ<1} z?a?7kv&Lx@aASD5U2iOzY$2kKS?=k7eC^5|7a6TF*(bHSYM9JA@_B@^P2;s2hvvsd znEM^B)zg-6dy$A$s~p?j0gK?wOu36`g#QW^8MxCyza#vLB**Uf785jrmwt~-9pU-HUc@i}wSJc0J=y>z9-zYAxMBIO) z+-CkRLcYL2HKMUq*ScBjL+gNr+Z6hzYznz*@T1$O2MW4H*CTjL^%q#>c6f}x3J4lD zd)s->j-+73GimP5GfI5Bb1Ho!cd0uQXkV2FnH?!tKWJXK(X5oEnVC>Gz;Ql0F<7C^ ztHygyuuJ&UPKp=X-H2C_Jilwg&-j|0ecjDFD-NX-@P7O$K6rcYphn5=+m6j#yEpT| z!4x%{v}fH5AOrfGvG4~9gM1O8DRTxlji!8vfC2{dkh2$@@jSA%pl4~}q8sJ_^L}};g0%nnR-K~jTaT=aI57|DX*Y|YF~=sy|5w@s`Ha!} zX^3k9bQKee*iu8BPjjaM;J9KNEV8W!z5ZksJbJW6t9@g|?#YHh)oUkWVyhqHiA3--R6seVPfa98%E*n3)Wvx}W)=x18jj7*;EuJ;1&(@Ie&|&J~ z{+_2FRv9dwY#o}fpxara67E_gsR;+!m@A;$?Dm4Ov5EgAZW59`1dhh^Q~tjANzY1@ zPl%Xz=jOd31Dh0Z41I2#@=hk&>Fp)sO0FU2o%9o8ynh7sGumN2%IN<_<)c;(`UA zI``7(Jf*96uP-n`35AtNF3t?}kN=cQmL(sV(p6Qbxy|;dl72j2BiORi`Z+XMNQQWN z2W_NEcDXN>T%ny*6v9bVEZ}PpVJ*mf>tFm=gq9!cGMb;Ab~+p0o(gbSpHSCaa+ya8|?FcjD|mJUC3Y@be?*-}~=<8~$8z zB%x5Zc38AVz{%yje7WAKq1&JhU6gl3M*3GjU9VCU9?EYMt4pItA1mBOOatq0{y^G8 zzo&FyL(AXND+U0|nB~kDk0|TbU#pj@YTcyyQz9c|Z}D^=sB3B}fQ>Ws2{z*9+#N&{ z5-5wx`hs~i2YF+;d&&Bd3!rFVnIQK~{2z=}w{*wRd8xfY0EuvwQ1PAs7638fdE-w=9YL*v#Qx(u|1`r^!73{?xh5TU>X)DwheKg$}R}lad5G z+#@&^>^PSkQ7TqoBF|)hN$pPG%pudp1|m*36pu)Pm(N58Zcl7%5%4t(+0J|3?9qI( zz+iPoC)1I`pjy=`D`O9s7M&^#5P9OmhYy!syGv=`q~qgYbg*(J4Ax@Z#X3P)ASO@` z=+wC=e5|tE?8a>ociU5g8-dw`&IeHD_~g2u$+bOPT;FV*^eoY0vU0`G-*dOE_;5Kp zCv(Y_D}-x43H?BZ|v4V)U({ny=@3*&2 zaf(`>_BSooOIvoBQtDBh+_ve|{ZWE1g2;!q7}^wzs3C`GeZ878Ub9hvI=1s~I%p@Y z)!_T=u3k9rF!7LW^M5s+Thf(xJ*&s1x*ih3hkTmJ=HD+m zo21&L&&>F@6^0sER((k3PGp3w(jov-3H|ys^-Hwsemky*ute25%TSuRe02-J(lJ`mQ(Y z+*#2~Jf>uCP4n7HY6!D{_2HrCea zuq+W)TvpUr;ULMc+Ui9K+y?yJ^p!P$}&7+2R=}A<5 zdG%)Mvv}X7H)>Xt8btT(G2}sC9qptXPmfjF-Df1}C#4!F4W8G_X6h=*i!ZP2v|CzU z@oPw4(|=n|eI3&-N3V0|Z9YsyB+%S76b%*sqyx48fB*ac;&W&T{`Tj}H1nZX0wnmy N-e!{ZSu6KV{|~Mu9Ebn_ diff --git a/_images/eea2e649c26e8415e05af2dc7aea168b29d2ba3be8955fc81e9bd4beba2661f2.png b/_images/eea2e649c26e8415e05af2dc7aea168b29d2ba3be8955fc81e9bd4beba2661f2.png deleted file mode 100644 index 2a715a41d64f5c86a61537844c773bd64ff64b58..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 148060 zcmeGE_g~L_A3qMi8(OqODh&-SX%E_4Nka?KE)5!r_S7VWN`t0S3PmW9cG^-1(NZae zl!l`3{pC16pYQFu{(|d=>$n}~&2ff$y`SUpxUa`6!Q_x0Jsk%fiA175ps#I4B9W(( zNMs8%RQO8Hnp(0c11IYS~b+7tgHD^a`UMj|7T4rptb2V9^1 z7-((&HEr+T?{^)j$V`QHyKFV*GBMXC+v=0Ebt{vJX`k)sE8qO~E&KUi8T$Mwc;Ah% zeY-;~uJ52+6fTLNA>Y*@aCMhxR73BuqW0{Z z!)=SNp>L0}8THH3MDY^;I-Iv24<)12V8Xx6*ODkx|NGDL2Kwp;h_6vBp0@@z<{zE|5y=2~2y8phh1Eq9FHZyw`HAlVo_nT~TOg1Ozy@fOc=dbD{ z`Vx<(c>q5-ihuJ2)zy`@Ke7=cFEsspR~>xdT(d!r~+f=O#@Kbt6vd zom}^4jn)@a9%&FKmru{jYpQ-}0B`u?v6YnqT^EYn_$jZvvHO10rD4h|Ch@72x7Q8Ik7P|eC z&I_;85;>`?93vOyoXi;JS#`(_h{|Q-=kK3?|2~U_g~gYzUnxi?Y}lCmqM}Xsaf5?{ zcCT(8C|tUZ=MVV#nU<2A%+Jqn_fjt9&i&1836xixjXC~X&fX|owTBO-()u;?Q`}~ZOxYF} z7wtSeHj9ago%HYsf8-%7D%$wMtPy?nBdU7dcQ0Vj0w*8lPCM)wRZ`1(vS|{Iuw(XL@zEbo_AMO zUSlhErBE;V<*QfZi3Jr-?JR>IK6I`>p`#>kZfh%i@PPH$BhSdnN++Sq#ctYqdQG1` zabMWJH$CXm%1S`>lP9}`_;#E)_E^hUi$2zNaQOq;&jgI`8Tl zamLkrY}BXzE0I3uA*Qv?SG3x4Z=`7$CcZL8&78xfg$4zJMA z&=)UW)VC$`kdZEI+Y@!~-n~Y$)3&xe-#$It%$*!J_u+9!#nb1$X1ZsSl4ts@C`Sy_8M5w%2xSbzzD`Vr6CZ{P2kW=+UDF zxn(E|Sa~wi>`)EslP6Dnd9Gf$LQYZ)_>tGx+ce>uU#PWY#A2)PugqK|%PMA0KYnL@ zTz&jGPpbN#jVG$Mqk`ZmZszd zrMPoEY%&60*^=Y-bafpZc>NkHIX5>tJ}%?_OcZT|nTLlFeS>SCpZ?5Z_NegT_C1?( zd#!#4(vIDV|8G0(?qAyHvcs+LQBrinLe4}!sZ07*L%zz_l zxcYDWsZ*!)jg6_}nj%qhY>pov9UYar-P<=bbn*OoN_KYk`nEP#ZPtJsmEc$fuTR1@ z?R)6mn6;VIb`cG?*;Th+*6i?M`<8opdx}N>tdO=Fo^*3-`1tWgjS*M1|G9G%r1Cp= zMrUW0C3N;pOiaA!?4&U2C+@ub>7f!6orm{{L;L-c3R+4-Z?9MLJvl+aO|nK}7VUeC zP{1ddB`q!H{rjV&dVIy_ z%gg*;`Lpv)ag5dB8>$Bn9vu1pol!nprC=dmtY)e!Gg{Cvy(Hwgj*iaYV=tZsFNU~< zBjj#TD=h!^ZcHX%VUnI(Eo{sF{rhPs$*XH?9hYX`Rs3nY$z{@{pm0k#f_#%&nQBZ{ z7PhbH{dw{NlZMu*}c{Bii@c};A73p z{aRe)m62h^)gVz#p161Pp~2~6H##~DltX{Bp_WilQT_PwBW1s{?#2Hvgi7aX=;7|3 zl9iRXL&k+@`=YK#YM(q|;^0V(h=?%#a7L6RfobPXdLAC0$wxnb`l8v}ProWE{K-W* zFUa@rBnbn#wV_JdySpbA8D1Nk?9Lvn_Tl$Db*hM)$LG(s6N_JX%Z||VJXz_Q6MD~< zKC?Vhd$l(2o?J>MTBG*i!>saNpOi)4zDHdyFBf0@^^1&z?-3WXc{`f?=g*%N;^sjN5*H8E|v$9g4?aU5VQizC% ze3_nZs0&?llIWw0(bU$~#@;r)eY^b{|J^2!4-5h=A0veXDUB|8ul%r2h!EYomvQIL zor4wjO(iG7U0ruKHa40ZJxT{GckY|b?E8lv+H(m6O6NL4BjIJo^?5{L`@C4+8@uuA z$*e;z8`bN7m*$S4AJpTNadUGQKKg#xrag3|KGJm9kYmS=glK9;gOFt052BJ!_uopM zIm6t1En+sG=zL`PCh_~veak}u4_=zpFg9kCIPo;zC|h1Cc!%?WLx*CoUEBWZ)vK4N zl5U6TCC}Vvm=!P1zj>3AQ{Gek^l1q+!*=D?ckgy6DJkh28a6%g|7!kZX=cXV$<{8il_N_*n@(CUT_|+gd^e7yq@QfeGK$wq;$| zm~x8;EE8Sd$EMLQdwQrk^4$a1WCOv+vgDEKGjA_ZrZ&I5_^&wAb+or@95_Jx^y$-) ziHVrlSSmaT)v?E?V~UE3G^bv4bVQYviJ{8Tsi~ZgOe)`!GL>3wb07m;k?7|GE9DMaZu!s;7+2O-v#-mh)(3txa6WnMmhdtoZ9& ze9hCJSlnp8a}hhCxPO26nF->7t|x$-Tsp}% zs$cQWbFka?;-mc{25RY4CjG4%)N#q}Pi}WNh5`Jtu&|hCwcpv2Rot%46}9po8CUIl z^ClL>)A4$9aU?#xwFA(}D0|Joll zLtHd=lmOYo!@2EepM`I5`}p_}T-BwE{axL2+%{`#YZAL^QxWPqgKJ*+cq~09)AsGu zR#sNZfj=ojRCxd(z0aL%!)?iE8+sPJeP(8cMTJ?9)2N?7`343CFZ=o$hI$GI$S#Hq z<>j=#7>-4g=VM7wJ%$6Fds+s-heVXSl^Jlcp}J5`Ahf{;u8d%1q%D-DkG+PeF0?e3 z9=>JX5m9vO7C$d92_Uk|tfs1f)5F69@SGQHlt(SB`RZ%na|)sY3_ude=mQjQAer1{&eR*3T_$} z7$z=S<6K%+cC{pG_y2iBcTj@0%}K)d3ZoJg-twB8vx@IZ-cRzos za$~(Ze?$1ib*3>7U4jPJ8GyqJ@7dGRn#3un%kfG!31vY8rDvl2<{(a~_m`J^B#N}Y zu{YA2HfIu? zslI@wzrWmxx{!o#-%gV#BJ)suCVOsNxUv6S2fcON11L!Ag46WBH)+14GY@+3PZjuR znEFALH>X{tnt9E7W_mjE?zb1$mH{>YRkIL_6HfyohlXrWgXlCgG+34`tgQH@q?m!C zV>2_~l_=Xnw*kT?mZ`N>mnc%Zc9D~Q{Ql*!KFS!La`ZDFgVPc5Z6~uVtM3N@Ijr<< ztQ&(BH4YADC|xTm5*+&YQO(eB=V@25vz(7df(rZ8?)%-pcX*veGvvBc&tkf+P5VwR zE@c;s+1x8{*RJx`xezyHtc;+EXbpA^QJW5K=9PjfK`bUZc0)r$;n6)@oSd5}C@9d7 zc@-44laY~GKk*Y0PSi9vAE?;cG{)<@`g0=S_hPBG6b%?RB!GF8JenBI$t7qGBa74h z`sjy%U#_`gAK$-E#L*fF-$?&tKP znwlL#LPFz9>y%QLiBcP%TSe?3ZlR1zm)%hky(QQ`&>mnZb#ZZV;m_;c-Q5IJ2?`Fr zoSU0G{O8-bgRN&kjp%MTz9~O~QrLnMS?}_IdF$4g+qXq0!+_r)3OIr^zR7IUMh8N=3FV^M*bF=B;NXx~Ru(t6#*lBUUwEUb&1t7U1Q0B8 zwt|-f#2Q8anN)*boqpL9&w^rHdvnN0sJ@l{UoDjbevmf4hX2`nFjIOH_B4L^8n&*>zH)y&P#j(q+sd;6^_OYRbd zAdM!=zxs7xbYZnRbWQ%rZ%U?~qmiAfzgDI;)>3MQA%A4g`Q@LmqEY+)jGv(@K$$y7 zIWX$??;sPl7!-qsw{Ne}W zqZIw>mD$s;DB#(~QeP}OJy}5cOCQP{XFNcSd@i#OGKE3?iYI=zD^5e%OlyP2OUOOAq z>gkyoj-?=~UZ>sh_n80f$e2plI=i#8^Wf7!8POm)CPI!*={p(B8~tKpGsNk*GO`}; ztERk~{j#XEDY?0fc6lSt3zOXk#}^vf@JYx71qIO_DM-pei!{Ja(Kl}FL=6FgS^D;| zQ&|Y0=Iq(CX1P{)s1ViMBU#&B|J+P+Fh8$Yq8z*=PEJlP>Gn#XhssJ-?>xLxr6QV)Rg1j^;K^_KT48-fPmfH`-d!TZ(qM|-#O~) z>PleNV$)Tk-ShCM6&&Qv?skz*(@W;Ic#^xzs9!PsuX0F8NJc~zFl20OEOEq86*3%; z9X(3);G&+5_0={@WaL3kyCuxvjW`sVB+U4x3X; z7?=E@QO}~PR_43w{46H$E$8CWk|q>tD1%WKE^Njg{g~|LOucqZCb{qJ+qU)9g-YKE z1ECk|1Asit?CdYrYo9#}eet)YfxgH2NVPZL*!Xy6gxRrU*+=AgXd(Ctl_-a;D_(U@ zjVpGuc^beB=y~oN^Ae?kC(-VhBED)vy}?$f6> z4kFpTQ^^6VmQVG3Bq0go(~HO|>Ag`hzOERFH5h45V5NKZsG>sB^WA-&f(Q|uEeQ#U zfFC1dK=%Td!hxosa|ka#WxaFd*fxo4`<=3zZat~3wczeMz+`*>o@(CB=}606&y>mh zj_TfGGyxGq`nGc)CRm{34DDZ9O-wE8}(0gTv zLDD9E8i&RC0OjV^R!sqx(fUXVh|pI8Jzc$W4SHMNn1$+|!IkRj>Jm^*111@ZP=D+1;_~ymndF#P%neZUd_0LR&)7XaYvODX;h3|LZm|G&^T!xz9@~!ArbY z$h&v%8mKL6z3jl-w@nQVWFTWK%L#f?w+*m1fCn_Rw3pe3X-ELu88WU6I4Jx+ z!B8CtpX21octBq1wf$Rxe&Rgd-X)+St7-;i#4Y1o2LK7*Q6#KF1>FH|U2|74TLJH9>Qwz-7w#7brB)`6Eg&j>< z{oVDQF_CGsT037`3V=i9fo)ZCvH4`oWQ+_}bc9TI{h80joa+!KQZqx_`#JcBqBnr~gbq3wIGsrsgSAYwLJOS-Y(>1^q z2$eI=iLvGJLcmkg_QV|=9E~47aBi2di9qq*vSmw!-}EcKwuz~!ruKGP^!U})RhD3# zi35g)(I&#p*jn?tPnDX*!%XML>TYil>^IYHc+NbQzN=ElKX(_>(bC|`#@+z$pZuCX+2VdAX1W{zx{@uhugYaS_rcdnz;3SCt83K zfkZ#5uXA&00jI_cPHSmt#YBHeD0uobJW=%Z@kt$;rN5X+2^RFPL5VsX3>Gb&ve~`7^JyG$H)&RCsHe zm{sh0cP&(ONa&mF^1NAF@TU`G8*`U4KN7FYTlaSC*i+zt_y1?BX{qiLq3$=yziQc}%`NKGM1jB!H`Xim4-7aImLiBMG z3G^D)RmMJlQNYT4+<}EP%fpAGp)ZD+rVZVP!&cKhMH|KbSeL){Qlj$ z{HIT^yYVfS0z;1A;)tr~xw(nJ?9Q}fA-VKir#*M>93%vK5)&uq1yn~838!GU&+IMe zLG`2FOw7#lE#|(4{45Fjm+3WxN6XqxW^NC%d_E9F=c}V!x?E{3o{^DJ-_^Bca&l5q zR#qT9o@R`vc~8W?{rf9}mrut8|N6DGG?wjE7YTN-{^yT95dN=fn7ChNW*Cn6%D=SK z8xa+wthO$QZqj2kj`+M%t2pyGbM?>l{pTd$pg<*5EZFf%)~GN)-~NSlo$;-SEkaB* zY&}6nfQ+d2U6i@TZXO8@P)S_e$mh5L#t^(&vz0>zmVHV#j;Cg zIM*g}G8j-VApnDrRy}^)shkbt8VxC9<8qyIv+-8w8$i0?6LIjc8gO~@+u)R~zYYJh z{Zn1&h2g(Tk1HxGF9*&dFMu^jhIZVc99tlK@XhObr{nYoGjDEUh-+Gmu&MDCynEtV zhtv4_`g&?m(vc%atRK3+PWiC#^QV)g4C5z9MGl~id2AD3ciTiDU;z5{==bk?7XYX^ zVUiMf4_7PYiIrbPRh6vY*|Yx+#;d&k(V~40Bq@H@~)-7tlH9{0SapF@-(vm~;gB%wZ7uYO6xBqd=U3miB zI1Z7*y7ufIxFNS*Iv$0Mgu}GH9>S&QO&ShaNa}J#azMhiZVOCo>!U|SLylj%bO~*t zNW0J-LL^ZgnmZ`>#Nj^qG4v zS42*@n*zIckALYaY~tR&eS2J99xuFhJ|Q70E(Sf9*j0!eh%M}tuim&)vM(W?w@%*H zNS&4xoZeM$%ackkD`z#*B(RC&J%{_s>rZl$FD>KLdDV4wsh~g;CCvZpn}+6Q?NX1I z{r%B*?(Bh65T|lTn5_UL2&)0?tp%m6%eWq`vdgy?q(=KIOBA~yxCP)j{bLAUD90d%mxt-D_KS zzOqtET3UK!a#Cp72BafHE&OlFhd7T?3K9?}e)p$L6H3%Y&>_ZYkJ4G;R`ha0EZcqP zI{VTJt{R|nd@`Cl+LExKvt8%FDY%8DIG&pxcSUO!#nv@7{@U>2G6W8)><) zT~a|I&P4cpZS8(Q68Tw2f}1llN5TuSk3Mvyx#8`t^78T@Gq1&<*8pp5>CIKU_TlGl zH8mc+OI$mA*C6i2$|`Q8N`1XapSRJ)s3oYEL#qDPyGw)VO5N=U7SfOl=eT>s zgQ4_Y?`J&EuPEBb6p=MHHC4L57ELH1K~k7Z7L9AtFfgEl;7J(dINErKq&_i@7eSD+ z=xg6@VSf?ysH#fxNH6v#vn}yK&e+D~^4)w!(1}hD*U>vVI>sC&0ZHC0E-nCVI&|nz z#pB0q5IIJsrW9t&Putn`+B!JwI+UyW=SWogonw#3AlyI+)`X0?g`VD7;?~=Nffqy6 zBHuWbj?T``5@{Np3)|Xlitv5(tgQzt$OQ3>Cr=6=y0K4idCeSV4{VP~|M=y^o=h3) zz`#I)PCyQYgd2yJFZGY(BILq3Dt1E=i43-^VHNgO??WMTbx*J;{bmA>N*MCry=M6% zLjO8uh3CZPiZ(Z@#fMaX^||+--2%v~b<`t%`pXwP5PMPtn5KZBU_LA#9CVzS)HPit zO9-$Bjf`N$iJr?njAj7moiHKM0T-8-4OK1`2&0ZQ;pn2uNJ>lZ3b%evjsyh3Te7k^ z(5EM;OdyBGCnxIx6DX^w5PJf7vZ1~GK>mCvE>AOV7jgg6!t1QX)4L94p*ip3=VxYO zioowUK;p@ecJ4?S=T;4Qv3QcJyr@WLX8ty+vj)J;(8X!*LiRNXCh+F}6HJ;m-raKJ z0E@f)LYDE9*v#zg#g{Kl2nk?gEquc(;k(|cQ*$NTxRQ1|hxNca)!b8o^uuh~7GbjK zJvxiB11YON$kIPdOE=uifXjt-Wny6=4-XH|>^uegpv%|F&~P(6)o9!?BKy+R*e)QqZAP^=y;tfT@7!eJEAlcVanbx~h562&QVOa-zg8j8W(Ty@x=AQS|8H~Z$Pg@0Pc zrcELP7P~}54iwy*1pgLXN-QoaYQRRmdGiJli^}G(en?zJGQq4yV27{7q!Bc5d?KpD z#M)=YX_82PT7;a$sSq^!``1^q4{?L<-#fHk+yN(ru=+l4dvox{zO?D@OQTKH>pz+p z;ku)aoi8iQE<Oar!35RMRpu=eYH zPd(pBL)^8)p5Zz+;%^9~zxxjKOgNySp0>8b6+EeEgHrx81I)IySFf@rCMJ#`{P0;7 z>64K471J?!*r6#YOb~!XtEN($M)PWFj_m5p$j$9_y6iPnO@>zP;$R#U^hEosK)#8v z0>!?*iOETW8_ufNfjeT>%2=9>Utjx^y|IG`1H%6lU^#HS5u~{>fps_GQ$nxFWR+Hx z1M6H_Ss{@KWP)l4SlV@C|Ms4q9$TIIo5(4_GO<2(j4}ASzJSA0(6(*c3LZX8E4ABs zeV(%3Nu_0j|447&HAFkmZR-2`S)oL-FAZL~!a~SJ*q)U&_|I`@JK-0jT4nR)QkGR0oxGS7cR9hE*lBLBQmq%fOawAQVM7~ z;qoVrV9Pge-RgWgjQk={9*!~P|751n(5(z-!&XMA6NIM55`P(s)wC!pE2mt!B3;1i zSpfVVU0YjgmTdYt*qBMpUm!2l0YW4J&cLenE@YsN7F1QS;q#n-{`|QaeaD^h@{AlG zaB><(Mrxye>!$%yTswC@PaN@89OJ$YG01oAmyaTsti1dfLL3O~Io!|5rOJh*){!d0 z60Fjmb8GY&q)qrM)^#DP6=@$3h~(#|0R6PCu#425IDP*@0Us>7c1BqO2yL5xM7 z&}V3Ayz-qVq5Q$uYd~rTxgHlt=rWHDucoI9J)Uxb+LbPTM7qGk?B*UwE8C%9ReBAp z+C1^2#aXndUeiVpwAeUTVm@CS;u)gbjR0dlxa#a291MZi!Q-!7xng2sk~i>mRb(1U z#P5fE@%LzHg^P&zB+9~PZdbt3BM)2%{y@a%KtNK%BoIV{&>vmw#HxGbo0Ee(7R|fIj!Nd}t1F9^bz(!%XQwn&itKvr=d;)2a{ihWBu6=^*7Tr0q3r~sWX?ffD^wFbP&CAgKc0w_} zeEBjB0|WQc6NS@5@yH#STUm*%hp?JLdXdpN@UE>pLuy>chFK#-Nnc&03FZsB(eCBs z^QgX2(a}E3-;N`{E3CZr^Ihq;&oE`q28~dpZ4Gjsn4_PQ} z-)SF#7_JWNkbFmHr@ezi6wD-|tW2uDfr8Z7+37JjIg@LE>;(Kf!PEO8NV{}pM55Y@ zRJjAPZc`3fVFK1HtTVDNheCYdMu>p%xpNBdv<`&)63*Jfn`Qv{0e_cnZ$DW*3IZXJ zhlg*Ne#nquqa#8NNbwSRU_6aQ$vdU_RbU(RseH69oRY2+y~cgA^f)9gH6OdWJT;wF zYHTD3vj>11E}?-_0m3H}%bu_Q7dYV@A8m>w@)ZnRig^Ry)o~TBT)pap=!+C>M|O7h z{OmiKnqbYy$k~2yss@Kjf;JD;o?}E2V@c~pCZG)`dSaUxqE$&HM~_2S1T8>RkQem` zH-guHV+q9oG%y0-gG)8UI{(b_uU~xo_8lz@hoG_MYK z|8b%hI~npwK_pT=0$yN5=Y#{17kANiO;zBRlx39NvqL{I;r~QjPK>)y1}HJM`?Vtv zyBVI#(NWs{g$;v)>{xobon;_&k?Qpq1BY>@H{T#*%HmcQbYn8=|#>N+z} zdh*n%oxTU5Y`gU4&_nk_xffGToJS8Fd>*d0@EsvfBJ{K}=M`QyAopfqpuVw@9P3i; zGfstLP?vRTe^d8qI4_7U#f>71g3nrXG#&YC!XB)KCJPW)iKMP+EjK+qeL!F!89R*$ zk^l%jPyrZt4pu~p*BrDXlF(IEsY-!52e1DE8q!8e9^03p)E(jUz!^B)rRI2M`EDb^ zGSv+YRXO`@NaUB+f!)`V$43L1`Vg_#>Db3Zda3_Kvg!GecOriD4ghi*=gvLWcAnS1 ziKB@{g{Td5u{DliC(+9Zn;uUPqw42dGt~PiHTU}Ui_rb0bUZuL_h^NMsb0TvBQDei z<~^K!IF*~x$_=kc*#G(c3m@;jou=_&SmhwwVXzcCnfBgEj^HxbYuw{A_HKWZk( zrl9y$Dd2!b7BWcaM$!$tuXUycmIvIMf}}@aXha4Kj!SQ)i@{>FetdQ4$NAqW+c7MW z_usHYT)l-Qor(}29~t0y7fpY{?TQK}Jb4R@6Q8BoBiB_!IoNbYk@rwMGr0xkec8)8 zc*+CxHod&`Y1>?d`2@ZJjX`@$>JWHAUDb__{ax*~;1)|Ni~it0T8Be)@DG z;f)fOQ!^kyanN&VdnL89jLhMJ1GUn1OFdkaWGNA55&$0XJd(a7*|lF0thj%_5u$Ph zT3gK~62BY)$v!>ftgpW{yRs7CU1I|l=m1B`;GyiUIxZXlI#-nk4;~OY1A=BqKa<|Q zd-tNJ$K}%Kd;t1U6sYB`DXP>T#iS9jP$N(l8t+Q3CHiy(*LD7t@eBp8oL9Y4M^T^} zM!jRje}&(!uFi0ase)()vbY&m5Jh&kF1*G|JZhI)dU$WD(#cD1Tg3rls?4#C|Ld0S9`--Z8v^fS@&edF&+;o zT@#Aaq9}12&x_{Y&xDgw?LA74PTVR7Ljlpl5yBhiUVx&VkYEiW7!9lF#PcwEJG&2& zaNMBbh%c|Qxrxbgq4VILlh{`(g8uyWM`1L$kwvlPq64mVS`ZH=NszEz2~mZJ0h#}m z=%58kB1|V@n4-0{)pY+}Oo1@c3Qr)SgnYm6ZjTrH+n`SpWgHSuymo=*7x0kVAeWM!+Y)o6FXy=O;G*Ge;_Cc47 z(PTYGmF&RAs<6Dgw3I%04)#)KZ@L^pcvxY$R1J|7)ESAZ3A^B-!T93%-ih2CN4tq= zJ-!WaTA{B5R1GLDbRgL%m48dFA3pNHwYL?W91|t(+K#xt_1Ut zzt7V){eQxE*Yg-nzQ3!v8#{1`Q)z_Acp)``#`5&}W6Rq=mUZJ~{``CZ=p2(UXS914 zYEYJHg5Bb@-YcBV9JJBy!l(_ z-x}EVnp$zruIZ(ngJW>lrX~v05)Km`X+&r%I=bn6M=Ya+-;Q!LCx~NBXI&B71cOS= zs2-o3jK$a%U$~g|uFD;vbYEv?2oHVz=e6gQB3yz`;SMlxL;}j%f3=Y7VKg&ZU z3!*J1`jl>xoeK$3#%{~ZI_6^10M+m$ri2feF`Nx~A}uTq2-_QX zG@%&rVEh5=H-dDKCM2s&HrEbXQUDEu+Izv?4E$N#uHjXk@Yurz(X4Ji?+ zV(kYH^bY&`|JvU7CZ1Pl-~G>bcoPfqFr~o|$G>4G2$5$T302(a78vPzzlQh)b9lae z|DKE!Fb*tBh#vT5YmS6wi0a-GPwRn7h=>N|rcF|tByfqUgMNtuD-ld^<@fJP!Wk%( z%^$2Y*+_x3I&`Fy^}Sa*yB059xDbsb-UFwDrfl2bX+dsZSzT?wc-7<69}yX+ z#GO$&ZI}lwl+$eb|?Fq@6Pf2so)iks&^$e_$Sp0ILuo=7RrE5NNHyrO?1 z5xv>s_sd8hf$xBD?2=;EE60cY{rk75vx!>RIt|p0m}F!_+laM6DBphV)}2t-Nr1R^Ip6Zm>yfQg+w9+EjBElXh_NL|u%PRLt!(M3sZfvq4bwe;z7bDBkyY$7-b#-{Efs2Xk4lkoe`huoy&T<2 z?Q+P?^BX&9X=gAO5O?)zf5p3XKwzS4lBm+J_4oG^-YvWkI14q;z8Sdax%D|eiixbz25rj3(FxGA8H$`y;uP;1VD-h-Y`KpB*qZx)qPCQo|Q+-CC@5`v&Fc3 z_bsXHtKuvP8M)J=L|pCS1&rynVWsRnJUZ98;U|p3xFL`SRP3}cdPI~_H&{BSF&InC z$grB+w-(P_lL?2$18vF?2WMrRXM+acn6C|joYbAZ*69B?h$8b$vhCGLw*HhTM5n2< zOgeCwdVg~%b0^pNO|$$V+SqU9!lGx-Zu}jMuPa(7}T@ zmAEc-O#Lx;auQe=23NiH_3PIORUu{NkQb-0vVQvdFH%0>4(U@vSM@i-mlok6DwIAq zjJ~I!rj{$QXHQzSEicnc#Qgj$EZ{%NLa5MI3;mtSuz545?_Hj-mB?=p)@I({Oh`;L zo1VuRT3j9uH(po`NxP@B19_eNg@px+eZ=%LXvkb&4R6#+)a5NjSGGym#3K`6@TW@c zDAE%?i(gC$HiB_Il*VY^;8Ko{+bo?k9JgftXqF=+QRhWqq%SizGG@7ATz1klIMP@vUN(Bj3X} z_QNSa4Y&97yhymGE8l9rgISNFXN-9i3e#aYrUiqDWLuovSy@=D&D(cPpU4dDG{VVCkn?!MD=4T_Q1A(icxh<~MNViTSegqo5a)(pSXlp? zbVXqyKeXMZkR+r>kB}aZA>=E8YeCE^pe$!?UgU@LP zCnF9Mk1&V^YIS~PG@@T!-2KMyK71HQj#KOQ6Ra#T>W;|smi-@f1z7k51SnBL=tA$w z$;#GGG0I*+K$Dn6^qCnD5juGh{X#Y6F7UIPo7=&9@R==p_wKFf)4QF zjz~^s#3z#i3B!~dA^X7@aT@O14YENnQAH&s46`v2$01}@8WZcIQ&ZFcVWyjf;Oj8M zdqE{(?md+QYJh;e*Z zG(-zsSs@0Q06DbKLh)mHne=%!gp=Uff}5IHTDCg?+BfSm?V|?WUgH50-g&s zKD*U6MKiNp=K5 z^d2E0X|?fgL-(R3??LHQN~s7ZVLf%59R~f28Rm{2Zf>K94H5z?n)P<2U0toMv2NKv z;i3X|Q;@I`Y~O5`4=(}?v9Yn)LA}Hnpw^*74A6)rgO@xZ!#WLw*P$2TXhrkuT`FPA zODwzJ@~#_{{-rEE^aKLbKjxOl3fC%WU6^Ctg97Enr5bQp>~Rt84I8u5W>uTf=1LhE7uD z)mW(BTenJ$f3>l(!7SVU9xFL{_!5^fgNR|xdgR0o95`^&)3Z5otC;S?z`u4le+VKH z{M91pY8^JbtGk2!bl3Gc%&Ux;G#Uph-pzEx^CnOeovJ?7dxG=PzAiKmn;Z^+7&i_$@jajD*YW zvmk}`_;V~+3hgdo)>GhQ%Dj z7-5N3VmLC+m|ubu_{Ei0^xpAWDn!`QdP9MS%dIONv{h^|opBxst(O=q!#S6i=tbYU zfYddi1|mOPm;k7+q%`_tw28Rlj*k2gEeJ*rnL6z0-tP|x!4nxNVuAwCSO`XqsbIo$ zxx}UP^IcRs5K95B7Q`ctc}`&r<1jL|q0Co?tokD6MH55uM}!(cPEBwsc?z+>VM5m9O48zRRny^KQ&)Xhiy z{+2(;^%8=TW^Yk^@9Q=n%>MlN`BM`Xd`a#x&#LsN?c5l_AuBRyHZ*o5{D1Vlfcdda za35ROSJjY8+JwrBelU*YD^3#3dv@H7%urj~``D-Rv9Y^$@1`cE5Q!)SF^-0pQIL_5 zAw;nu-rETScC>L5;o_b?eVSi28Ce$8R^Y(Q&{$xqlJat=OH!!)bygtlngHq#7<)Q9 zHzON@hluG?IiH(Nw4aY3Gu>1G@1biq=l)&Xjajd}iVE++Hi!YD&y4EdzO|a+HuD)r zM_HdjB1IMB*IQK~LK5?GkW=iPoj2j`3sq1@AUu;`dOa7Xn(LuTa_)z&Oc^xpo{O_w zdqPyh2SnSct$JAhO)ZKNlej29t#hmAW(Ud6oH+w;E1`68T?Dm~uzqnVlX12R0qvoZ z5{2dEr%$S%uH9n8s}H_>IZ0&I;Y^_`LK%{W0w!57w%Hl-3qP6^I+nScm<9j{0h)1^ z6YAfhlEc9Fd8_vvX3yvYQf zmdLMp@Hb*a5yORPK|9CWky1liOWn_JvE;@B2(l2FIUg?IwHb-N=7j4Xsm^=Gti_sG zZz39qjV9ddNzV3b29TE9A9*Ws5#a2>1J(S#+AKRFL;DGGEEy^X)_Q6J$v114y~1%ky)#1{WQUMT|K z94CPqNXU2h7kx)W%Mp2i5I~p*_3EA6GBPsa#~y6~0wRPyb@lp+sX$y4;^`1ip{KnI zP)De9*bV8mqeTadj9Q>9ArtmcN=%fC9`YA*0d&hhQ*RX%I1Egl3m37~idq@cS1;X# z)?a*Z#jDA~rx*ROwPPndyXsdU|m?`Y`T57!?ExfVWG$&IZzkZhr7z#VyNcF`BwktJC6q-tp}5~K#NXim5JSz@;zUXwSm=d$ zYnem&%swQy;cO_*zCEx*fJq>}PbdAUg_E0G0_2hTx-EEASi$v}L&PIl+-4lUrVogV zz8m@cxte9UbtLLIfy^+`ViLHjhPOnCJvVI1WjRs!$mqTa@$v{Y!KbYq-(RJeeiHYw z#b<(@8He0}7LE>BR~tqNDu{&fT|HBvZOB`(5cysiKFAftM81zt<*Pdv&}92wzN}v- z-ctng1zD!Z=2Or<)gj5EL;k?TN!nfin^X#asKU0qqH_EToU%M;624a*Q< zM&K&3>l6oJpdt80w|O&!0m}dRW*E%uI+NIqx`0Q3*+(h)LxuBht_RMOaN?E0N4#^v zx5}~1E<3`@#cisYF!X+U{<1haxZ|g~MB>#tSiz6VEPra_`i&Mz6QT4- zS&jg~;b$XQ!2^s$Lr<@R`!z5kU0lLolVfsPQbd=6DT2OjP6IC}8Lk#D6x_YL5P3yH zLwcxz*C0T=fhiaPKdvzut3o6g1x|yZg9>5Ruj>>>sDK??Qq=KYBjTk&>d3<&6Wu9W zvvD0$jtIYDepB%DcH{cruwv4ON~IzB5qaYNEBdGg2yhTD<|3L65eVu0N+^<;%?i9r z2nA|?$JHv}*=6deM?dBxqG5zVjhBER4=3~48t*}4h?8+Tnv$8h1C=W_^!U$<<4dRn@Q;jx91Z#51`p{=C}_Jp)-(0!rhBI`W@0(8yq`9|&E)dEly(i{W!hjE|XE zS?THO#%i`LFD_ymmSt?WYJ}X-S64CsxDhhFD0!Jc)|f2PH8XpaVJw`8Y3Oh5iz9>S9cUXJbosD zzHrxHbajF3$7-LQLob8DN=zN0XF=yfkgUjl^DMF}`5uNmg{xDKrNy*8)46Ju?a7?*DG+p zo2X2%{Vc~=>&)?T7F;|S7CV;|-Hz=m2k`&b2!2{6N+2!cyCemnNFkes`Zdk)sLA+Vxcd_TYBIaO^wPRM{5XTxM%E)_Csw3A{NNOY za~^Et-tm(7GaTs&m^(jxzebjXP=LbP_?7pDmWN56@0^>v>ECHM!t7xIg%9sB;ZAX}{4RstT&kSeLd1*qgX-?!p5r24 z%hPn9jnU8X zWz#_=IbDrMzi?M+qd_?Ybr>}~SfKQuYt$-QwTc6~Rc+9?(5BELdFZ`s?@f_2`k-0l zJQNy7nxR6WEIsa{akyc>jjVrsWu2YhtdXiqWc2p?RQN}k)PF!sYc{gB=YSp z97(-0#AL?86;YlkCr{3Pdv+xxGd?WUhU>C^bIg}d^;^4*wpjD|cC;DTw0d!04A~Y0 zYA8CUCu`N`R6dn!W|Q=2@wcDTAeic#e1BI>f67gN_94x{YM_gUU~X- z*PQYCqbZH1Y;q)4iYv>!E?Kn) zPe))_1YCuXI+xhf2w)S>Zo-!8Mnn*TfH~ED0+0kvramc|m~wn({^q?tc>46H{0mG7 zeZis3J1Hl9%+)(5A)&fuk6vN_dF@x{7dU44I-C6*?PUGluLy-5LJAj=Q5$~1z~4c& zdzE3|=5sd&_{XaXu}9d~DaWp!)m@r6ZO)|h7frenBo+5qtEX}mIakZXCW&qC8NDht z?aUuLyjc0h9N(bDV@yJuXFXqC`bDWcgv`mHm(`7>+7+{vWkhW*?h1%*ZuJqFmVG%{ zco2yCy+AW>QrL*$Aqk`rNi#*qZ@tV+#k|y%IlRIg zgn^@mu?K|Rli-lSzqW@Nzy8P zWwVSgI6mxaiHJgL;|pPZTGz4LiZus`W8AT&>CjdA{rb(nXWIk>ag%)5pg!n(6G!iV zNax2 z4FNVSb|z|DMM5I+qEn_#GrnH&@4t$4DCT4C!5FePxv3^NytyQZ86I$?o4?q~+!Zzb z4@zBn-ba`I_wDnWb{CXo{d`(QeCz*M1@mSva+fs|WX`R~j(-xkn}UlXqY_eD!gE)z zb|u%yqhk&vbhy;;^2L?ggGzrrJro@5V>H5>I~}KikAnpPC8OS5I`{BAs5JR=qLWBi zX7uFoKT(W^yW@ z*XJAcozP;q^P16!!`6M$aJ8fN6y_bV%>jmxN5gqWxo!WSV2C!H05_d|O`am#ZOT@= z7sjp)Km6wm^J{3s^qnX^uh6|rHCWVbx&Hlyl$&FQ*U>5Dc6fPFExSkb9!NDwu`ye;NP^5w$IT~Te>ZL% zi$IHH16!cv?SF%&M9Q|eC%3D&?dEB-!Ubcqb^2U0fkInb%R@~>dK$FkKn-h@rQh+$ zSUOgu?V+jB2tjeBXJF7}SKXV^6_0H>1KGj(5JJAKSCLV3%n$0?Yj8d|;03qlT`3*B z`E*WFlzzT5E0RU{ACRe|WK}YcUSywcTzIc8uYCxg#IIoaEHqHe<_Op%T7zI*=cq-?U>Xi5kDjwQhWyc&gk<)L#M z&O#%JHeak8Edllg-Yty9K{S|@rGQptQ<(%m2h~}_M~xcA9r7!nyQ-_@V5JY2cTRU) zFeG=v>S5D3_BhBjznK4^K3NTmOMa(>1SZOUdo{61l*l&mtBGPf2xl!UFcT+EY~nul z;aJsEmJtbdtWZy!z9J2QEDyC`(U}U6OI}??o*`6wVVeO;u(8W78EpzH zPF69Ep7iD7KTxqe6NmoWkjJ757_P4F{G##=IJ1ya1_bD%mPKph3H{yc<*2`8Z2Ot{ z_*XT!2h@!AwXZXN<3`H%?7RpfNR-|z-N`M-J-uO zd?uqCF6*5%T7XnS@`Gm@T$2?RX@ASQT4XIyF(Y>2@GWGGCGL{v7B>6)etXWlni`Rm zA>lsudyoIBEG>rEsOgN-l^JoeCRs#wqL;Tx`ctiL|9#i|@@+o`Oqf#}sbnt~ub$WOIQ z^VwI&ttg-{ieWNIdR(}0q2!7`PQ4q%V$rwo@GZ~ua39vRV_TF@HaOid;8AlH-A1vmix&0qQ!|mH&eOcip|GyS6RxCXsJpAza zH<`ZDy%tK$_20f!?xaD79PNdnB`JmEL7jJLuyY)|nzNNS&IYIsiB2zTD5Hgix4ojh zv0YmJ)(b8HaL>1t*(`b77ur_mRt1SLYyF5vql}*|cosa4?Ayvp+t`_|{UJ7O3cI>{ zM}DC8jUvX&yWp+r%x4>C1ny{2?%d;B?Ibv5WEvfI?{4hgz6?HFDBI`^#_Y&J9sr;g z-~K z5seIXUb0nyh1Yha-@GxOdkEzV)Q}J6(T$H5>u-#CIXiSxNnJ$KKl+-kTh&x$C@iyF z8iwH-ygBI#2Js^U^+;A)`#A5775X3|#lFEqPX}-^b-s2>})- z7l-QFV~=J@zk`*qMfAg|t@^t6j!8$39xWamSL~Rv6&1AT`heLLzh6r}=nTEyc@SOp!-2R(G1d^lsF4ufnb1l-zFo37LtBcqmdJQLOieoj}ejJwY6F*U%h-pHW6K}m|;=*qwC+p{)QD(r%ajfoWFc2N$&l- zf3NVZG&QMSDsd-)jT@vJ$6nL#^34~B%?3Ojy|Wd2D#A|_U1K^%Xg6`>T;A~9*sbLM zn0VkxfIVI$=wTsc%$C1DojB(LRX>Q-L6$mLo3c!|`o_F=MY;i(XD@uW*=Kr4DTZ#W z8`(DASz3#*$$Fjk4#Gvy+_Ps-k$QwE{f^@5C_G|V(~t|JaV9-MR-DRFT1eq(=yI}5rj{qc7FHPO@EMq`GJ zUSeEC01UrK+6E=n$dIhoedrdx|H8{JLxWDyyhCw%D^A~aXWt4!tc1KD{g$89A(!qg zIE?^Rg`TaKl8z9ga&YB?(>nJ1!}AQqX~pW-$LS|T&REI7$9bVR{8P6^*~T-ngG<8i zt0F2nFhm1dam|Bsp$M?rLi`qVxxuLmf_q8N@)Z@0K6R7$j*yn@eh~jLubcZw;IL8c zGv!KV=KfoD6QibHpqxVNBd%s7L}+Go`E+R7Q)y`dEGwRRkjwqarjOaiH+W&bJ8!FTobto*Ah57y@VwYMZ{tj z!@a?e#g69N`MF)QOC6VZFFIK#l5%+g(Q)F-0Rb7eu4LSgA=H?G$eMutPJB~Yw3u)( z;sI~G?LOP<@QcNNoKzfqmT8M@0FWGEb({`%+xE+*{piP0O+P;_=C<=G&JC(L{5+W{ z1^dbWO$?YU@$n^8L^ovQ^JeDaUBk+u(RioBVav*@nW2=Bp!{f~4rFF#&hhyN`~Y#3 zzN2n{rIpn%irY!1A^{B;$o}fs0i=o|k&;z^S7Ww2wJzSD7a>4eHlOXLO}&8h5Vv_2$VWPz zL-5J_#R{$Ay0R zU2=EByO?-IEu|O|ZYZ-;{|)+B^67n8+4}^FZ?>{|vaWRIk#YY?vR4mFR3r-M2DpL@ z;j>?k1>G?6IjrnHN8^aS1Dza67-7wh)6KF-r*&Zz!~Y)$ zb8MP~J#AbynBjj=b)HG(lDxnD#FP?fBs(-SuyUQjp862u$GjKB@)I{tkN=W8Z!Uzz zJm*ugq=L)~S1ESW?7PHk)QAxiEGy;a-at4cN@zM_gd}K&!~>y7kLoaX!UU~FgCm(Z z&;x`XlMBBS)k^NC@h*%{SSPZ^x%^k>>Og04G>U-ZNR#vYr_>tID3L;s9n*67EJ4@=zx+og(630%5c#>DUfDmX28-BuQMZw9 z#>Wp6C`*3+>uu<|vMYoaWN7p5TZQvKa#YDCjJ!4VFe!L9>3lYwij0K!LH*_}_%iVR z>fD0|lyfJ&({>Czl%Zgww>5ZRUS{9rYd^njciv%0Y&h-mUWN4~g^@SldHqR-*SNRc zqq)4IzO}JpIF0?R=9gs?5Xa&*7lbn&cp+DGb{31@Jbjaei2g&{8Q9eD=9%AbEu%)e`mxAv-`F|3wn!L2x!eh_Gr?FL18S- z-d1xc!oCK39zv^gdYyZrBr@bw#$Db4xM=Lkt4BsFbm;PXQm#uwN1$HeBY0a?)sfP4 z?5doB$ByYIYjF0iM&VljEn;FRzW|Vkl5*Z!#2> zI(@pV{7TApCTnz)^d5Tj(<8BNC_n)P3fO=`*_9-7mr@oX%fRmg@$X#NycAq1zR?L8 zpD+so%g2&**qPPN5Ri@&9>lhZlf0Xxa2`JUXJy*Y9Yg%%eO4OhQI*m4_*}~G*rnro zE_&f@KxS0(m3|Thxvlrzh83n_Op*2XA^KIOAFH&__}C0=Rm&z#n2^tBCyu)w^N(ol_o*p#~@u|C9soiOZ1kKWKIgZy$I{2u4RJ=I*XP^ zAfk{yW~){Ov#)C}a88Q(DRg84n*m>#ZC94m&J` zb6wtTSfY_SJCMllYyO(~;MudHyq0@;Qh$yMLX|wN^XzUIG_{;}J*8T7D4{_f#7`Bj zD^QM+?kC`LF=QpwcfEnIM*uIFEI77Ub+?EkjI>Rsf8!^7`1Y+!OzDtEO50B(rc!zM zcin_N^FOjTgo4xkM@)rO^EHEGIbhG+wmx{&>p2F-tDL0qUVQaaSgB(*n(RaV%eB?ku5NvI`_uu6rVF!X0LuY5($>$<)G-K&F#>ENrOVGxndB9Ri39<9XfaDJ zR>y5wqIcwt`ITgiajNEXF4?YGa}Zs!kN`qQ3n@lGK)|E-YcDLtN6^nIeOYHTJAr{x zGst%kBn_SPp~hCfmoHvavbuV7J_5$av8S)FaDFwiNUl*qadT_Qp1Y0`maRkf+mH;C z6l_N1M~P6R4bRSs)al$mwS!t7&uZ<>3}mSwT9Ag~A53}B z^+cG%D5q#qv(bod1?#TeA2p>(;jCy$cGnfrp%0bm=CdMPWL(6=bdcH?)Xyn@yh@wf zKB8N=IM36v0)x+YC<3`Sy38^X|EWk_&bbdW?YN;6@^jwWc|bE%oBUvskHNTTaBTCK zWR{qhRHZI;@y>E%2IhIwoZ(jcU^ zep*xS`iF%00{)6eDIp3$unxRTJyA8Je6?k>;KdVN4P}4+)2Eh+>K$nyF$WAf>K1rgaaop8lxjl%%8iitPuGD3dyG@fmx>-bg1nS?1WH6~!9L-C^E3&O<9rY`7jWg;o!W$D~4 zr-=k=_F~`vWxa7vjijy=x1T7^M3T|rHHZRBT54zy2y_tv{!F-&H>+N4*=X9!P*rXi z;i&8b$`<*{tryS|2sOHP#lB7wsHBcA?bx-8!N75t`2_7dTR9)yjm4|FL}(5KI^fWmUkl!g{gESL;k-suWF)}`eY5_nNW|qsX`gva4+lHhkl~+#~)$&)_k?;wD=e%ba1+AZl1C~E&rCT(gc}(7)b|#?I3o%SU5t?k{)2f z^~p?`5*;ZBqYy<=C@tA@qA{7cJP}J6r3;kW8_`ST8{hWdo7;WZ6SmYA;&l<5;@)_z zqIktW7>>2Xa0T`rOG4oCSg{1TDimTObBRS;(m)^r7w~PmEirczjQyZZfJ?{2@rAd{ zJz788bdVs_ZqCk~mrE?A(7Z!(y&aI()Y;SP<$D3RxVg24IuGLx6@BAhkKiXTU=R8E z2p_80(gF$nxUT@I&5%buf6~IT$0a8$x^tPUh-iOM95D)$Y$M*d$#|0s4}0uQHjU|m zVT&y>R9V?G`*^`ysXw7iE4azMyDvL-%)Wzi}SQ2!{JO=4z6@nP4orFb3B&s9c)!4ty@~`RLVXN-C zwf>#VhloVeur)FR-UmM6wF)h7l-n5eJ@sH^Nj+K?3*z_p7kO@gp2LSH^s(^;oKZ*4 z#~8y|AXgBxLoeG79XGBQVyGSq=b?y4rbspG5WQ{|Tt?It93KJT#S=Ra(%BE+(Rs}0 zJP-6Fs*@ZiQbt3ra?P#Q@chpi`ga8*wpxh0DG)_|?_pJIc0qk)&r}yKRm^$wPsOL8 zZUH3|k$1#wBDFW9Kx1pI$vpx3MxxSNoAzHeBXix6$?0y{a=x%Eq3LrfU&~^3@FZ?- zVK+nlV$=S2i6G;-N$h6*Tq^S2aA>i2I!NGGB%fcPOp$AFN^GYTO1-qwFq+1kJk|q$ zuDxLEQ2ZKMWTgoc3!SCNMOb`%yt}K){ErOdk~~uVj>EBssf2uQR+VJP?LohG=}?Ia zb{pZs2punmKvW^WV<8ucIM&p9Vgv+(AhCtJk0td8=GJSG>XAEg{%BjJ z!CnSGG`B*G1J`hY6x`Jz)!VWW@(;QwIZkCrpA^nTP@#QS#%8$`Ce2nB6R=P*M?GJO z%Iw)QtAob|1EY&MBwTHFD5OAAy$D~WJ)E?$g9*Q3{aZj5Fc-Yn z2TDADmT%5G7!pzzx^V?JE-TnaGFbTJLGeK6EIyrFWNt2ICsJ)qP&&&BZXj$Lp@6C5 z=M!aqNlt^m+K(!kc!48-w+vs1#2P!|*7{0alyUvBK_pyMQx3V5 z`tycvVoJ(rpstDAYfUa5Sr9l#c2RIRW-&6@dPj|$*oUU|PHbU(D$;AA5kLYfYki4h zUR(y0tvEZ2aB#`}EqDPy1(VO!+iCu>v0nV&N87LVW4==TJ)1UJ)E$TARi8e47Ju=g z`NzOpRFwc-X%@dcP_4h%c;!ic|ADHu+1%nnA;_ew#D5H}L6lKnVuHPiB8y2UV%Uwe zytV2-^==%h8B#<_`3mNR>j6b_kF`e&Egw*48h;JzN3D;kT^MKi7v3T=5}+ijN?86e z>ksu>LS;$N&4`XJw0P*DxC?>oCgzP{pkq^n$DfGRjj=k6bwS$5As&ebg+QtxP6R!m zMSL>@wWc72nF5uk{41AT#>s88PlnRFfLdoa1ypK|qR@RKs*u(EN(?chw(t)Hi@bq# zaX;4e=_ZLOYz`_kQQWZ)ggahfi~rTIGrV*C(e~P0-YdyyM1*<;2j9;MIjWd*WEE1{ zV~_l{>UX@mHQuCm?gg#aQ*Jy&Y9N9Q!Hy?Zmluj08U#HOo;+i{;f;kodiE4ic8I3{ zwSu#jR43C$Fe%Q5t3aH;)U?qh_D5I#&UJ5{hJy6MmbZF|=jOkWoiahjfum(L9MAA? zK`DXkab?E&aWf-Z?d)5y+Mv!%t}}Es&BdbiSH@DeFb%JVN9Z5nmjWylD$X4= zqFD+%a^wJeT%U(X<==$UAs9kwUaQQ_w_C)W$9^uJ347DFTbRJ8`}6ZRfRGi@!oVW# zr@0j10#qB~AR$K*y0Pj8##{jojQ!C9ym+{ zkA)ROI7@IzaZ%9;BaMzq8Q4E$+L8WW)UFGiwt&-C%XKbrrotQ%nZ*u-+0wecu9T{ai@&H-2u z@R~I_;}32XqjH3)<(Prb@^5Yg$>6Y}oDjJzD`ji9Ou-r;K;7*z&@p@-3+MoPU||t7 zzJ7y&aS5DOFP|?ZnVUvIpr9H`k2w&i8CEyy{r>gqEmNd1uE}4nlHW7GGC%+DJ`9sW z_VeY&Vk>~*6FP2pCq3w&`Ftx~JKJ~8cxLl9fLt?&W`DdY`Z@#0*|G`>YG(7s5C}dJ zEfZjuNGi&w-&h{Xz+UTpU~BMGKVcIYeM?T)15EDl>BG^iq}@Ks?!9SNOS;J!^)?=HqX`& zc9^`@uba2cl3cFLs7E%hw)uNVj&cjZ5|5ITF*VQ+NO+hjB0n>kG9{x zcX3NfjW#iV3ar7DdXNG}CR<#nJ>8%8R} z$2CnU=-|Z5xpA5WC}v@ZAuaf~ia6N>RS(fCrVD|A#XdP{egf-*^viaXeQ??|!CmOV zBswX@2M?L)k4~hLOqvOFRPbg3Eu%2O`U@oleod3g zZ^#ose6q5$NB@e}5gjSNE!$?$*3Yq&Ou{|Di+Fq{xakOwVeTng*?~=NGVLZDD|8n^ zZ9#3)#ID^fhC8s2Ihz=l@^9#E8p05qVYOY(>%_&O0!Fffl3}j)JLS@S>$)oTC zT*9?=@h+p?>d)@D;FoixEzvPNPZDVCK1b37GK0&s`Y)0P1mQHfe0&g zh@uDc`qJ82rddfB>*NxPDxB=QzPwnwT*us@`{031m0LKaA<#5~-rb@dLCGSRNQq9Z z;~+!>5T;5^zrX1`Z-knB^^1m3kaO@qP&SbeiHM*#ygsQu(${<&fhW+NrWAG!MSy)1 zklJY1crs76*Osi_yTU&s6x9!qt|!0bzcVcE{A~N5+MURYsOQZHj=;WMUf7OA?8hlt zvdWSHu-U(>+;&-8TQkO1uvx+Y2|{9rZp^%FluWnCnJKhAK%G7r8JYmSU0q$9SLY3w zWUA?3}N_4Pn zq~&NMFyu({p+%g3VyY@jY(?;)n;upJ8G@}Bw%g3VBU0i!e@d^$?aLpw%J>{9NU4vy z`YKdkK5_yZV&$EiaVxa;#4B^r_FX$c&bqewb)j`=!@3R~rN(|9Ibwt|*(#ruqRK7mmA=#@lY zhAgYC>GrImJc& zQ8Ckd3YQFOkGo==2@#spmUyG zsg`DzS2X@sW#Uf^EBZu+xAfvTy2(6eR02KHPpYb6)MYoH^jbYjV$qZQ#*f6)ER-8@ zGFE~?pXZUVm1#VjD<605>heCE5FE_~7wm64v`w7Hyf+AZPVpdw0g(Etu~Wl2_q!mD z5<_j=+nXzT$LN|}nqt4@@@{hRIA?F~J9qYyT0Qn=gf2(qci*wQfVwgSZzFD1kw2F3 zd;6IW&p$1$+W3k^yP8)DRYCwzo+Of5@j#;gS)256)?$vFMuAC<$W?g=cY3zPkYDU<; z;MAXt563M%{N=l{z%Qp_CH^PQo}X?qcue1#?FYf%1k=yKBdS&N#`$|)Tm)1rY_wRX}%A^haovnm)>#AiwoH^%_(6Fyx< zu_#Cc9FufrT#YkEgj!>J0>=_eu|VG&U!~lH^8tw#3zf4@Kx*7D!oZZ0GOt$lg3D<; zb`LKy%Jw^_dL?>K-$bkcqIA1cU0PBi1{aER08I*~oo8H}Qbw|QpDOP(QO-Y`32(^L z7DEm>jvxl!bqSYLjJTh-#jc0AUY!@!zJ>cO_cCW-&ba;FxzxcSIb|fk<;c4 z0wP3du|GQc)qx?mrXNF4dH^)s*g3K2{SQGy(xW=gzi)f-*du%YPx&?TD&DI}n|4}p zLWYrGHaoSft-0)U0~_DPiXwl6Y>?C3+AWX-#58tWnf2&!A6M(EoHc(Fvc<~ww zw2lr5yjLR-J6>4CoXzvLT7IWqwSpDZ5!=;|F+)PrLLZ$dwgr{?L9-{)+T*Kd;HHo z(<&O>%BFG=Y*O+6USH3Y@?hv`F$gHAWo^G6!ma9vu@-jg{L8axNul>@s9PT-81{x| z>fWP=?AqnrDFd}P4d%*8A9t+qQ?QTryI`x`l+z1AJy2BiJvjfk7qHKALzDIX5o;!w zG!2V?e6D?CbT7wg+unWmXkTm@G0Wo20XwyhuV3XQjj(>~QRi)vmtwp`aiOkfUZVWs zS0``fZTR>#Auam#)*Y6rvt$AXPV~lrYc`|aRK%FqIYhRu#E&4xA^X=pHC?Pj8{tn` zJ7w)+(xOCZxMK&C>mXMK#U4Li{@NYL4}T&-u^H9@nJH@7Cr^4(4@#_?Q*<({o0yxx z-QQ@SQnPI;<>^oiHD||BxF~k*>f1m4&?Gajv&wDbxd3EJ9Nkvoj0Kc7a?zTT7ND^wZH6V4to>Y?lAHMt?5?a zLflIXZ|{#(7=+Aq(zGtP=WVgbBPmWU(7b61u24W-noZ6zdUDyPUx9p(p#Pv!qW|eM z=|nR@X@N?!PPn)J9U5lz#&ze~n+Lj!zrik%9Wo?1CT6+s*Gu4QF@7K3j0*hq=G(LE zE#C%@4VybE_xEdmwH{cWYMHIvts^h0V%gE}`jK%PrTN;k3E7~hy!1gkMQHPhUJ6v4 zehfrI{PLV)s1*^p1)!AJaCfmvxJaP{S_RrzoA&3r+ARWCV~X$IW%BDaeWzLJFim%>-Fhk5w(o*y2%VoR?DZ{h^`Kb zG}%WG^5ZZ$W(f0UNuu|c1)eVEjtz>ktaND(vl%EGWopWij+eM zBbkKRcgTj1k1*bG$maMRPL{1+So-&xi|^TQm2qW8umM;6{)vQ|i`xxMcKUUz4{6Q{Yl z&O*z?mYC{slIOq_G_ z(p4{;_KBAY>Yl#*1ghSPLnJ9RRWzm#uDkB$**qHeCpA6YZL`D0D_4%8O-Flu>!35N z)S>pZ5;yiJR=m-={p@y6ogLl0nconk@OH!BbA(dt+q7KEe6x-iV^30JgAK4I3OlCe z$<3U3eSzZmMDt?KjjTpx`3ZIPpDicsxwrmj`@#>?%#~z>I336DVHqgD@h>GVG-+t>S{z`QFIipY1Bx%Xn0xhRs?ZM8H5ZerQa0N66RfI zuegs2Y!7@Y<{O!`C9-~!AT39X*Th&Bf<0ALRiR~&RM?zK|0-hE>YNwl4Oic?PVOsz zycitLk!hX1ZOyf|t!lCr*3>~v%V4|EO<#WTn{sD_j?M|FFEJ%U~{7&oXEJ>z!Iu|MO))=H6LO`*Rk51v_61 zM{9tQ8fU8gyE|ddd!utVaN2GMU1NI4#7UFL#7VTid~Nf}Ua~dH4<0?-c;$#ezm~h* zwd&TyRU9x+*=W!fZPos6+n$W)>&#mT&yy`afph~Zudko&^5?aU(z-H&phG;ZD%WG; zPuu6mel@kVYE4a?d^}YpX3)-*oXK+soNDm|rDU_W7FA?IYOK_2a30Pa8?X$93l)&U zLz}ZZ#!6S*(rHIo6t!R{JoDQ0ZPzOxC_954y+d(|AU$}fzR#BT_Z7u7oK=B5&IJ}0 zM~t)_G~|)@j8IoMeI1N$kG0!UB$uitr8w;fpmg=ek11w7SCB!1MAknbU@Bw+Os+#! zps@LTkW8T-)fZX3ORB|gsJV{QFRo`+E%uvnO5dnOFKDmECjp@>RhzZ@i zZ=nI?a}By5yUrzd@A@Nf7pE+{Qr9{t@X=n?b4LTZRCp^Ns;m3@_1~m!A52lUXmVkT z>6^adOgQH(l7e7MfPEI=R^Z%K(bkUOMbof9Igv)AHMcHve&(L?Pr;WjPe#;V1+`1z zLyY4W$D@_NnY;C_0wxKsjd_Y3{#+QHWna6Y3+TIR<{^)L?vYB8sqXjEmpmLH;hpbs z?WeQZ86Ycu+NR6jlS#t3nCw)uuwTfFOW&XK4jS?*F8BVB>6Mc+15={#%qbjK$HnpQ zmpA91K0G!{GI57Xb4AVi@0niz$lvWP#WSBXE+VgS&}9+nL701DfqLa;S(>Kx{Z1hK zMq>TvLqf=_eoM(i=*z6`$cgr3ms~KKkZcn5D8+5h;_Siw`pvbpJo>?@iKY&_o3QCK z2?400LD;b_%_XLJ4WK(nn8zZmq0tJbwC6&-^T`fRQ!UebY@YUc?n^l(x1W6og<9l# zmV1`wLa48MTv(QR1uQrm_Zgl6*jkY&O~EUOdiofUDd&gLpG>=X=W`j0k6}HGNX|Q% zRc<@O{-SC`dvk4~Mw7eS`;NnXCpix8J#d2O>H;69mOV`G9vZweC*aRKT^SM{Mhzdn z9~KWHg8=CK{CrR72MzZY7dV5DPtzh^m1gjz25IXxxn3Q;rs9Fr8dovrK~RW*hViRg zP(^LszWuYsPBJF~IbQ)v2%TOd0yv|iul#L6K;A}lyK=<6k1sPu!Jo`H_iT99#qk=t zzoy2xzbPtDJJH`{fcY7tYqx2kV~%g&w!IOB!Nka}Z4#|Lc^H@~z(<&RJ;B z>CM7Bk4WF@>2c9yJ$iIlfKW`1qO>f46cs<73C=$izNkv-&K?#f1Ed1*XrwYoK|zcj zK;4mIad*7OpZPFB9|=QYT=L&%L7&U@43}3*aFDI0)MMq^+uG(sio}HZGB=8r?`$8Z z4c(EoNGa*WQon@F27}*DEoIR8(vb49j z9#*Bj-#=%VNE@X&J^Ex@_vfi+Q=DCH#Y8-aeWcJPbHw}Dgvh*~=M$1tuj@N}N0Var z>(cNIZn`qy$M^>JfBCX;a!&=nIeOfC*az1F9zm4)h$aPDz4(xc_C8H3qD%~oj1IZv zV76DYpUI#08vzxo`PUujsi3sit4I28Z5%2q4+A#F(_|&NiQMyhAd4{@OmMUbF zKJ4Gk9~+ARQWXDm=8w=hV&D-`o(gFp)kQ(nt*dgv zdU)saq(vD-Z^s{0w?EY+*N>mh!4XB&rh(d)ex$3F^3=9cvpzXvR#nZzV)FCZ#|9tq zs;ot~9Xr$Y7`N`wqsCLAp+!yn_;EOYJekXd>syoDDwvFVEMzP$yz;H`$@6cigY5 z+b(3?&f9oiGTLfPOwvrnH&eo*R$d5DG~h~?03^8wZ#CVyNBU?<-Td3P-|ruJ1n8A8 zcp<2!#y@Lduyg-l`)0z+|k$I(a~eaikPp%c{x`` zl7O~pJICei{pAmOD})VbNrWI!n3_sUh3e=0hUepg%41m$N^oS)jHa$!wdy{SWWM() z>SlTzQCxgFvaDrN>VoPkQN{;OIhCJfx;C61G8V>R$kQewADEEHl+wZ*KZ6)nr$f zl?T3ex+Qi6b)~CfH}|IcQ)dn|KR6j3v*OyG=^YwvwyLQFe0k)tWVA)b`fq(VPSAW( zLs=^ZwbKCz$MD0g6fp|eBWOAM%E`@Pm=`Nm56pzUb2v0q*~$Pn>Oh@+Q+Uj*>MI3i zTZO>`q5w(6L(LGo6MV%_5*3sRICICU)NcN&6(k z7ji<6Klg0t%ttZ17CPO!y28gig^HwWlt~ffclq(m_5R!}Z476JI5sSpJ?ehaz3FG= zT1yZ2DV55_%rD4xF6_QzUeid5{tS9vlz}T&yk6e?DEDInA&5S{zFlc4P;6nCEuv84 zF%6=5M$$2H-2-JoDMQBXZmytnd&A)Hk*b z=P5ZWEU#=Qi$PXV2g;o~MN9MjxOExPuMY;F3RvWR5;;J^>C^A7FI(f{>bk)sH`i$} z13#Oi?)`c9dieT5a-M%*&wu>8@KjLW6yv5@w-M8GmcmGQM zsfRCGfaHx5&E3C;$6acQ^rNSSL?5_pXTW0~IC4d-59RajJ{rox>Bmu#w!Z z9g@y#j3SO45pm*2j7I_uE4|)mxt0o1XdgHP*Ag6bkAm>xgsdQ3|zbdMmKe7&5>&bnYo7o3z9&CR}h>ze;b zm|xS{q2SS@@9APU)FO0xLdPXHUcQWCuWfH@+4J}J*L$=RS;tou z?kdaDl8Xp>>@rz;TgL#`hw00u7yNen^C|6IB$%FvG;p}Mt75r~B;D$h)S<|0OQI+D zR8&0P|9Y#WE;Md5e`dlWRbk&-BQ1OKhj#Oy`Nu9RR3y;@pF6i?`3(3j?KIi-9kW*~ zU?rjnEW)mLR!?g#JUh5k5}2(R%E2n4IYZX=@PjKrj{_d;o?;Fu1D^12MQ-ylWoh{6}Q zlky(Zwu-D_sBN5lOvb)qWIp|`8$l<25Yw9Ej=~3u@xgCg_r1GTbj{o@ZwzO!rhSoA z7pZ~y0!5)4%Dkx5J}aJ+I-jw`9Z)>Djvtc(XpLLH?S5vn7C&Jq`kLcmKh8KCJ#?`$ zmEh2peC=^CqHbX1mmvpzX9s)=>G6J3fi}ew8E1q)2(b4f{q?L zCT4w#xQ>)EZ5kZvuUCU#Ary0j>YklYSxNf{N+uA`pe0SliL!J@l)1j`hzTCb!7dG+ zvc=OZ!Qk@pxt3vtqjFJWU`$i_FEpS;9x*5Yzat4=6l_G@`a4jTvRF|VStx*A7m=#db_WW z_R$wqgm}y^D+K*Dy~$n4!O^AH;5!%?dDXfZcimYw8Qar)*8QhW^FivcEj#Dm54rbG zo;vk*|Btyd7|9JwxVCMU{q&Y)9lXxz4Y8k9)x8NPEKMOuIP@Ih5p%gX2&ZIt;W0)auDsN~r`% z>E|x*4tK`dmxam27yUFh0gn{tVEM;tp;KURbAwZP}_0 zVvBW{bmjG=p-z;W2;c*>Q#gT$LwjHsvmo5<8e}BJ*U!(-1&6k8!--?5{mJC?r6gV+ z)9$eA&ZK9)wjr1e%9BwD zul(k4Np^yxP_1*=H6_<{wr#OYUkY5&{^Bv^5`b&(q>vu=CMWyy(F^H|RIzf6($*dT z1CNLHVeJJ*pA6;C6Jkr?h7gonBpDZR@iR`=ysy_(q#i_o!_+Wbw}08gB$bc-`t^%n z^mV1~urP8`3LxEI(nlb=Uyak(h;T6 zDih_!JFi+4uiqRGDMO}{TY+m+d)KSoYP$A9%0XJ}n~z$X|GoOuDdA(I7Y=)laQR8= zWX9i{rmxaYF8X$PyL6rHSIHG7Tzd}v;qvQd`u6j&*d(-kT9PMQ{GN7&9X(l~HQZ}J zH@;%_M~-_djrFq~O-Wk3c{HZ~j@BC;W+X1&2WL*|kc+{aN8Z-7JbU)8Nj(SC?mtWE zykEj0;@P5A!|er@s-kiwM&%c3jQ(Tf)HpBu!VNNAMQF+CVrr?VXpnuR#UI3e=J4@5#E)pWAqt&YRaAG0ANEkzZ-E*MFS+ zU`m?^#HF)Ec(5t+I$h#?d z1rm9OkFe}Ku3JZMQ>6zzg@Q&Ax`tC>P?R@G?!OFCRR8S0Ix7;bBH%EC`G5 zkAcNqW_~b5$`3#vJ-^!FyZ2MyF4v!L{3W==$wO5PMx+7mcg__72+(fk(_XJxDzm0^ z4XW$Q=H4vjW(NiS z4x0zvW;p#6i=V1vu8mC`h&U4O`_u;rt~aMS=nV@y&oDSvR@2jS?zaGsUg8SH)hfn` zF$Z~p{mvx(n{c!yaXQyK#hqV6i*}v{mP(rT8Cl-M1>a-Nj=PlHvF>qlZ&541`0{md z&rK_`4}=BJCe<18J8+QpKTkiMg*t37IJ-zyh*E$+DEuQ3Ncg==n<+Kv%$m9_BTtm= z81yxG#Dit~%4fYcJgo50=)Qfh4eUrn>^>u^OYWM`t72`zm0TmPZ z0Hf8_*C0xRtvU!8k?IUV9g2|B%FhTf8%8iB-b!@n)PX5x8yvc6xexo(7$r z%1%_QP~n-VW6vd(e6G69_4DULaXUzM$TgaH+9GMLq4dq>ak?q&-7V-s5@ijC~NE1$%x-C*WYIkd0`M1_} z($Pf;)8-p1w7I>>ajIWwV^c=^P9EqWxMrTC=EfHjxbG37tY)E5EFPv};%{(oJ3>#d zPu zR7~b*M_3-9F9yTH&ScBsI+(y`PBt?Gv*giM1=ivMd2{s|KVvT3EiO_9D@K4ZUs4;q zx39PI7Ft;r>|ByUDJ|367K|r}l9?_9*0D)~If*ma5{^AjC#lzS>~+ZbQFwt{Q6Llm znFMGFfr&!+hi6A#R78Awjl%20^K(ixGMyB5cHq$c^6$0G(&sz>EX=i`%B$-pcoJIm zH+y&Pq;;Up{+Zr;iFWBn_rCouYYf)uop43>RG*Y5hbI~2-fFvf@QJS1dy;*RRi{=F(5GILzV~ff)N_zfZet>!NwH zo~s5xHru+!AjM)E`VC4E0}c{!T04JZE`_jrHKd@&iph;~@81YNbwI%Um=oui-6Hrf zRv=6{cLA)xA@^McuL3uR->Vr6$-!EK{F&;}HiO`6p7(;EIbS%mL~0J#?t>@>UNpNL`yW~HS(HNI->mp<)z#ZHyq zz6Z!qgnvx9@&T!&Ef>YtD_^d4t7)FQBq%1`=vWw z8STQ76=)KaQJ(hEJmqdYKC@-ZjFGYN)T{E^oAaRlMPCa6axCQAt+@Sh$^$M97-p|+d zyspQ(_M(#a*878Q4x(}|S2FYC(%DzcV_rGv|LIO(4Lg5#P2AqhOS!F5#j-6wK6%X_ zM$}akR5$Klw)Yva{@pCP=0feC1$lX*Ntc$Bn-Xa67Ox%0OL!qp=b9fHw39Fp$uXaE z9z1x9j8`O}vbeUaywy(6g!JFufDt2TU&x&g(zG*xZ51S~;6F^5uAWD~ z4sX($$ zdQDuou%vn3*UjrzeKqASezGf03{U<(#HC@wNegih^c>B18e9X@VCJ3X(^A)kQ1$&>pmDEvx*)KD1X@e+;+=+`AiViJ zTdPIG1;-|&Ceq^m{vXjmfEFwDK9_O}PP&_p)4?Mhi!nS>8jP%t|3D_;1*r=lG$H)J z0=o&t7n%<9pDMQuO@dp}Mzufp$2TjSK1rcL%Uj7a?5659r4)C4WCb@c6YD_k)3Ph5 zX<#X-3E*-0r@tQZ_m?mjZY{k`OLRk>1NI7;1A@?@Nkc?sDC!uv+c7ig3wQ=B8P@+w zlJ^{oRHCpNH*PHPLAfa|i_nG}a8ppbXg4J!h+XXxJb}oNu_cicrxON_yPfYDluL}J z@tQVVL;Uc$!2K8X`N^S_Sn9b&kTZZrRI$mu0SK~!JWr#??T&phc@h;^5m z-@m=p>(MOtKYaHRp;l0{P8oGS+oG7mZFP;SVs5(IDE=bup~K7pZc)<5(667QuW>qd zNFv7rvaN?GrFx<2c3-`ucd6d`q|}T_T=7SdO)l_DE?A94cefDv5a4m!4n$je+VoJY#nvVHrvoD#wx zc?0*hOY?Acj#qt39sz#In4EkM^p;SG62}R?0QPXb;#>b8TL#S-$bL zV8KoAak~iS1;0c>vrDXABCNV5_qs>;pf9tu8L2aVA;m zz(r*}<1Ez&!l&^TR%doy#LigL&6|I1?Wb-U_!Jepzz~b-e?O7`$&gu}V4Z>vg8#Iq zyhZNF^J^$*f~Do@UM?)I>{IVC#5sMCtRtrgl`H$|RXInMYkv<}*;bU)pwdfQ7v7t7 zxMD`*yqvvD&J{T&&C}tNAf((LY}+@b3Ewik@w6E;vI+_gL7VJZwT`O>>^J-F$#R7o02GjTPZI(Q>{fK4h#A>glvX1pWx>A zlpY57{dv7?gqtEbT7IqC*6z#8b?xT|T3X8(l<0#R@2MOb zkd3HF7SGU-^#sL7NVFY%1Md-RGpUJLY;)fV9EECd8MRBIdSAV`wjBV}a^)qoS^*+c z7ik{VgGwBdGai1jyrRN)`}XbcW)>1NRTd@S|n?!72NIMa`BE3Y?s`qWDAkG+V~_hGB$Y<45nxFGZi5gZDg zJD)nI`E`LrfD$pS`_C6fDqPkIfm==4iv4J5vme}$`RXb|LoZ(r=FLdN5KG+KuD&f0 zzWTGMfxpzcNDq?*jwRj9nH+wZu}xq4_H8jgb#q5xb*_;izn_hBuRTI*;{B(nkd0G; zOs2z<*IRN*zg3o=fGA0;c1;2#1wn-)&C1L3=XglQ5&RQw8WJEzQ0>|cj1YAlcQ6tm z9{_G1Yro;cXLi2IUqeE#dXtGSF8-YNX862aD2nWNjb7T>0ml%jFv?n5oxmeCF0txQ zGIfQR7w~{BNfU5y;Zo{abbz850gpCmX);U_e5pu%!5e`Ffn5dOxp`+U@+w{eG$VU) zM14V-B!A#k<$Fg*B|e+$eJ36AFMTN@_}j17iogmf*2q?CNaMgvECv_EAsEQLIW<~t zzg9~r^z^!8%R|rWV{5JwkTiPG1@`aK zb=W9}$eUS(cZTJ&awR2FBe<#l*2-qlJ1P|0pYgb3cvc?yv)0 zXw!4#Sqm#uxD2GjrpCtJBioPO{AKa@npXk3<#pCKIOSe`ehz?>Wj_Z68b7}(Huuq}ji0)q=5X@4$Q2`WDL|7%)#jd@I8^<<6=w^e`aBn# z*{38>a^6qu9N2qyA(Y9hS&ZmVrpr^Olo4gTL$(Sz$~%(CD2N;%_}*dn_&L*6RaN`) zjxrZ9^JmIpZGRK0w#dnW7e)Jm0t}9Txj8#0Ctvl>w|``XP;LAhU_1ItzztbM2#7p1 zFj|cs<|g-0{%u~N7J z8*zG};zYLJ3^)Z1;T@iRh<}qVp^uw@ddt@>p+@`+ad+_7BPA-QXOZMsX1duet3tT9 zuNM>~8!nm6H2`cVJuIuGADoVe$Q10CFh9;g&cY~5bq>&=apQVzdwFB`e`FQH+=UB! z!*{dXI|QMSxB8PG5>H2owq7t<&}cR?(`n`J&4oP#s3a#MJU*WF*T<$Fm4F$Px0F^% z)=_@RFOeIWO6>l(`h?FyPr84Xb?#?|isXvQ1qr_kJw5~>jeID74D$xy971yD)8LK) zhj5btkFJXRuxZ1FfgB4^c}cpCjo@Mzg$g4(#JR<+S$$)D#lt{{CW-x=ND(_^#1jP!b5Ji^x=WvsB87inA<^ z{WfSDSCbZ5RZP_;_@hW<;IX849ry$7m5`CJ+@0f!=`B0n8kpW5DJ_?=_T5WB7EPKr zUon=Be*UofdZW~D&S4*0cr=$}xTvV8tQ}vAjygHItU3=v4)c%{G?^^9(C`Od(2WaIX9$yxl8o~FPSUMKOMvGt6D}x+ui>%!dg>OU$mA=dhvM(7i$(y{mK4&S~0GJaGa}a?c4P!UxE3YIlK8v5$Q_$ zc24p$<~7!I8c=#@j=~Y<1J)(Yowm!PN1F#Io=v}33$Tvq7Wg06*u#WH`po>`RR||0 zosK*)dV{gax*+guraP%0B0go2R9==CxF|Sc5CC*=CEJGU;Ip8~i^xSL9`-lkuhg|6; z1siA!V1PVZ52ifc1itkjX;c4Y;0k5B$SmbC9Ddg~R88BrS;h6DaHKEIagJg)Kbf37 zJN#2V&2CEcT(?rk2QKGv9rBA=v6A~{W1-Cgm~M-C^VAOPW_-a0w%evBe}tq}N0D{n#v$HOx<9X-sPuWuNz@8Pjq1^uzm7eE}w0p2*xrAP$ zli7h2iMyV4$6--Xw{G?E*h^1OSsP2IM#mJLCPRj>=CD$~oeaW*zEhyiUAQ1WwM=y) z-xedA9RN=J@x#a|5YHeV;k5^f-V@lIls=P^I|b2^7pfh)f5DmK-IFc3c4_% zepo|~Xq|v#%ec{#%KP8EeR~g?$cimp==Jz|-im?E@8`R`#!M|$TNk2r6~!k|prd6f z#^)faS9)TIE0+Q;BU0DAyniHQ{0&C8oif*TcUHBjj?Gr!IYGeRp71#H<0$tNBunJE zTr)#e7>=NkYr<6DY&Xhy0i4H|WJF@tC33bjgFYSe>%s1s^BX?SmS@L^9YjtOnJLwRq{4E)&F)ITUl&3g)VI{5Hi zT*v)~4vp{bntb-`V%jn05fY)j4MMNpzTE=&hEcU}>;o!WOZaEH8!^f8FYoc$DIrqO z|TQ*uYmyBKeOWtBfua-9i^s z?g4k;f2`1-wboYkUt2f78x?5WNMo$1_9;pAJLq=@g z;m^;%ZJ7!i&fCH6H505*@5b27o0m;jfq?^ihNMXf90B75(d-!zU=flLbK!!vv=IOV zSI(X7WylE4FAICBNr6Nc<@@!azPK$xybHsk-t%-IiWf$Woj^NeXtua($#CI(yTxw4 z@B`u3d&Q!l%1+#?OF;MHlP}wt&rNOuZpz(UlyqxW@ncEq-{6>R*@+=YE@wst?qXX; z^7t)g8=G+A7_{+zF)=UYIup+)P@B=dp3jyW0u!n*=coo6%b8;O8Z$6rvJ}#fZ>T5G$XUp5RwNfl6Prdl9QFz_2U5nlNiAOm_>!HW)X=|_y%1( zhM-LRL2mWL-(i~S=brVWMTC0sDUx)!i)89b>X8mhLPHX^UmXE#eO+n&f4~g9y98;S`rFK?KM%A=8X z#zYYKoH|0OMrCcAbKMdTvvzW5b!t+#D*a($Q{A;12OAjhR2}EjH9or5PC(hW^9qvt8O@#~8Dh z`WYS(k^fk9p*&*VkQo0&>1>&a z-_UkXSQd65JiL7CB7a2tXfFouYmAx)#88HTRy!NvgYfqDCdbO213hx&NFX93Yip$w zZeOP*R_F}0XXKOSj$}As-z{5oZN~20y?fcJRWopR(oEF8o1)*J-zz%3E#-t!;1fE* z#;R6_l z;D79`cBau00v@LnD(*Ve(vJS!gYcv7m^P3d^d*XvQE#QQGwM*3qeOsRo3rSj{Cl6L zBSHWqfdS%@bxd}_2*Xu8WxYE8Ylm?oLPUDNz6HYGvA%a9+>`erecl~2n~|FU;5tn-?eim^6aN)qCW55#z=dvut))~ow(W)*G=jaJtShZLG6`XSD6n-7RH$~ zJ1FYurEDrNaBdIk%&omAE7wIH5O=??%|lRr2RPFB&l!vk^oX+Jkr@Xhtt9g5+XXLp znQQARJseDIa1J62y82CP|Y~ z;^lbj?p+@~gHMU?~K3S z6EL23`k#h&9`SZIb9w+D-5_9%WR1mqGiAQj{5b$&vdjRfjq0#rz?H4Z)6uoqUDBKb zFk-}hM4Edl9^f3NMT$Yq##D~%+DqA@LlY)EG$g0apFhCCs7Ac+zn=hA0V%QMaNlYI+z0X&1EwS(_Gf=+tJTFg{_o(E5h6h zG~BU!C%9Zr8RsdKIwQ&fJb!#21uIK5`3vFfbrN08RXf8q%!tqL&Ama!hmnzyb8rp2 zv_!~{sE0>xX){udiD^;BeO?p{kM?|pvdS1wQ12)JYzp+;#K=11dC&^TKPQlxy>vtu zK-28IcP%=#t3w~U6vgQC^nYw>Qz=L2;$w$~3895#88l5KDisF?aHQ1L6)LWmm=t28 z7h?zQOveQ(TNME*YPncD-8A@KR$y}oOnqoQ0@C4m4nntA3&24TrTNDpjS4FoR*m*)rZE*dmG6mh#8S3{qn zi{PIa_C*FK5<`9>kaZ&Y&?tg(A3a(|tc!H3$RVq0J2d&XtZXTCjW+=qXkt=oG5S;m*f0V7Sw-|eQn^ow} z`0-q@zp&!&!{td%KN1`0$kGp=meGGO)DN*qHW}Kfhf>!t$s3z(hO~4PKZPbllirZm zEDNSLd23d`FZKm)11$aW?{r@Ib8q>pWVK%X@f#l!EiYq)Cl5!{_3JC$TU!e~iGK6_ z1@Gnuq{1SMGO9nS_)U%`Fa8-YYE%#~Wb+yIegVQCRGT73A{| z{ku9nd;QVmT9v`rE-AYte7w)qwbFa9$7g;(aklyH+k+kl#?a+a^Qr|`0jTN8WXI0A z{u^-t^2P((_lk|25Z+X_WaHy28!`tKYzAWe$;;kwSOk;>RxZ7?^nwHoug3hqO=*B? z1biGl{LJ!Sx5zW&+Wi+9EWI>vW;3u2zH_nvGlDt2#poEyYhU)f2+4?WE8NKfmIM4S zX%DcrXse{XNAy~@=nmv{;r~%xb*oPzdEUBRE(#ikz>Z-7J9W*=_8w1Tm!IcHGEfXn zUJchJ9)1D3LERu81A>DKKSXEoq;bsI;i;5Cfvu<%7Is|-iIHP}9C6uQ5eI^6g3UwM zZ0BazpkWs%9_(NwDlk^Vt+a1er@|NUlyqV)LslCup~hMp#7J-_k!i?EXIXgk=++Gd zN&e|nUSgb{4&2f*Ak%NnNScSv-jH5T$kAS> z^Yv{DgAZUzGSfY1Q<{M+CdPX=hv6SpRgLZ*WXTc1zJ9yjFQ>ZK8)-h9(Pw6d z1}#5TPgDNUbyzPak4fb^EBJ&W{J;>wrPz00`}H8>%|w-eO|a^Bv~j0Ld3iN`tutu- z8NHI1e|&>hS>&SLZ8io4c~rl1a`kAxA5R($r`B{om)PRsg6F4Vb)IRv&$NjCdLX3a zsBG|@+<&=+t#XS-Fj<=u5)VT7gndm#7fJT+S+*CJE zgnrv(soGgImB7w#aumCF&!)MXN2MNPwK`=7-=ApzfGP?1-x5{$$<)Dy7ufLQA(R17 zBD?{H)2GLo_Bf5KN%lR#BCOu9p^McEpxG=+2I{c-Nf3*C%?h%%(0M37ehPJo`I+L1 zEwpQfBqrHv26gk2rIzgafW=V;Naps`iL?Ao=UTE$y`MSrrbwPCZXt7z>2ospK`y$B z;%2E5vL8WZ3>%k6b46xYa<}ZKN|sJfAXSA(W;QV5d&qb1BUyYjioj1Ro*xrgBrm&Q zdIFzF^{cF$3FC=AJjZATNRyY3Pbb69+?1fmCKpzW#)c*Czd0ra-_{Xds)4(LuWHbN zY5-F7A_*H4mLay`)!QWvs)fZQbZ)%aZMuz^;7drwa!jDN(R+CM`kG#`eZBcx>%Se2 zUeD-JR57Vht$lWj)-W1SlTI7?S73)zH@wzDR~_rS7PFc zD!l3v>p;Nsxum50cLt&`jx-4h^S3j0$UQjgdd9d0M8_Ilw_30u2iycv&GG^TtXgy? zD4hPyvh-uxCx4SYfK#=W26EBjzJ!YH(zXESHz3Y3-n*f}<{51P^-NK7(<#~$l_uJm zNBN#WmbCnjTU3Q4Pv^Q8s~R>!v@^B#uD7vF&=<*uP+C1U8jpB>i#Eh*Ni@JH_>b`t= zKy{QTZ~AR!X9Bncys_`{4dM5f?@t!t5AMd@u0iYyxo%D!w^a~OxR!l6DEEx{oh{q7 zi{!*PWk}=+(7lerC+(etC4&LB>8`m0V~S*bJiD)#_ic;C{P`y4<_CV&-FYqQ>d97a zHk)g{4wP^N1P`LDl;H?|m-MO~h{`()#0)a$7Ba`MLaJCFKbo(+8}oTmQo*#oA7@J0k(` z5t83ALr(8S#)^<5$Nk=uCx`h`9bcWTIs?Bp5ixd%;%aUoT7itDfjv?~)E&Bx-o>3a z?ixx&9&F@PU2IU8<=rb=HUvks2aFs#J6_Zp1om7BJX~;6;T5DBBW@7kI$3c!1*<+( zwu-Nr6+3n2qfzWsS7)f(!JiL57sUkac=RW%*5<_4#}6N#Bh+RoY78d7T7A|{ad%{Ul`>j4iRKlwi9!l1d8ON zaZiZ1h}Ls*hb97q$b9fv(E<+G5M4gd zjGJ4kwaO1ZM1Id^(#2kIG)v5!3M&D1D!Wioq=7mT)#GG8fG+<&_k~h<_qZOvES%mJ z_c-9L)4p~2rt;Gy)?A}1AcI*7)zNG8BG{Df;8cab{5btUUzT_EJW9cjM^SKBJW8-x6c+-9DoD`pVM46LQLm2TZ|KK@cRQ#sn(Q!@glIUb$IX7;N$ zZiFwmb}dBqM#4Gp(Kapp7_P=heuD#WvnHQrTtM5tEdb;Fd5^iX>9ky|W{GZ(9wQ{l zhOG&i2loq_k1jFqjjiY{^*wsi>ma*1UDb5nu*01?c0?T88!a;P5h8)>eC%J>kQNto z{Xy5I@ijrMWd5z$bLKF2?Eu++mkA<%4^i73#ECU|e(qS)+Jo7m!;n!C+*KqCL=A;? zyo>}#Tukt3atNsiymeKGzIia9XZ#zPoV-h9WWXOAs0TtrX4vbUpq$W{0IH0ksd>SW zg|blA%pgy9{qo}9Za1E+KU6~6u?VJ;9qo&Q$_L|01PFy)qXSE1uOesw zN&+*R+v_KvZR~rg0#yTTZpQ-Z)@tnaajRA^#Wy4OIeS>WX2w#04|* z?vQ|NDZ8wH<)ja2(Fn28H5@O>0aQ`m2e!EW=R4E1of;DKRG@F_Q_gK=?O|=$6ISz9 zzg|u0Md_t=yLq4|&uM~Bu9s?s|BNx}=0N@3mditK#SNX><5lI}S;0X;vR6PXW5~BS zSt}E(A`3)~1YNZYu;<;R%cRuG-%8K`@$IgI{ybH*oY=Zz=Zasyf1f9Oc9Ve$(6&ul z`o@=ap>fnK5f4b9i-Omyw1oRW*nn`$^Auk5mN&@xGpL!?u zzgr<@Fxoo!@N;y|vj=y;QBwc+pW`eW;!L0nyvCQj_h8Qvi?5E+nmnGSf_ZU#h!4bB{Q#FR`}Hm1cw-?alk}rFWvuMpYs? zS!hh5Khd-G1j##d$g6^VQ4=OixRO!IrQW%fVcfDlvOE|?4oxV>i{?F?h(4fN+BH|K zu)IY$dqFBW#}PIU#y?N|y!qaVR+Z-sYE*iU-Q4%S^@{#uX?VpjF5ZLE?f;8V5_3a- zSjIRMQ5@*JGhg*_Ekj25dad2cHnK3{TaGE{ZV0WGlr_H*%-kSK=ModQ#@(B5%5sEE zF7L;ms&Mggt>o{zHfB5hF%45qZS{jO@sBMsPv<{*l47hl+J`rv#d>PVQ`fCs`#<5u zVnk-toW|JM>B(0dnnl6B&jUdahmUZ#6c;X~s&#x>h-!-5kUKkr{XL+3jw0V3&*lxr z5w!StkjHc17y~I`YU-F0g6tH)$g}SVI@Kf}H;{L{97NcCI99wE8w0cBPyJqXlzv?fWXX|qB_V_yMvHIvR1*;l%82^-!U{N4xATi)B zFno-T;D6f@r-_c7-y;a?3HRT^gGVuB%0!EeoI+3F0%J*UPJwRXz4vXXtJ03a`+>!+ zBM0l;z|&0ivJZPK>*?FK_XDr+Y+xRAweG?Y204E|lua50We+SWP94V&1#d zq}Yd03(S0q1BOJHt3l$2CnqbS1_o4=o|0Ae9Ri=Kr^eK}v_ujBVRJxI1(6}gy*acRN0r2d7d3t80~ycC%Jn2`VBeYodY*GFBF|EEu2aY`l=2rl{+ zn?6M&Wd+~Qc(l`F<3?S2+070`A3g2m=stMy{=FAnptbIoD@H5U1<*bMs$Ljb|D+>U zgM-lBl7zY;R`VI;N|znGb|o)2%j?dg#$G&;0lI-q__WG7w=K9hXXa7rPf@J)`QHuW=tQB={Wa0Df+O23hmx2R) z95c>AQnLh9`!S7<34ur6nJf~&2%RRLgCk4bO}V5h0LCKsnt`x3i{ZM$V%!)lIo*=U z%K-7Wx^mFPxeq&CI=S;|M(TpUOoI7c=0gQ6 zZu=^_400$w>`d^#-)xSIY%tUvI-2c$@JE4 z?i_lm_}SAK_oQv2qwyVjRa-hFFrD&nzwu7%%!rJ$tg%lYygp~9`xqHAwdSX72}JXi zqPxSnEieYZRD1dr?hIzT*r2@4Q`S_LjFVY#!-nr;LK=>P4`Yk3>k6&aNV+M(;(Fop zh0WWz^+XEtYTU{Q&GRA)(>uATN0F$TXFRQpolkgz+8)_~h86@Lm33uBp5 zW`2Gb>L2MVC9#!@Ew0V5HCnSfV6kP(sT5#XSw@2xBULNoPpGS4U-mE`f-Tq~sFGfm zuOA#3hg1Xu;WLw=+WYR~0AKJejrMO!e}5=n0=79Y3>CXMqgpF^@yuz5Vo3G6bEnnB z4w84q5+Y~oW-UD@aDMqBzI9)G>sDwN?G~nflRxGj*!J(4jZto@rHZlsts#abR9t=3 zRycV?_B74jelb&v0bWPjnSE2C@4iH<7UI*i3-2&7pbNGBeO!c^>ky@>>~l$t|IT6S zh5X*S3#Q7Q-MIoor&l|t;2|$NF`n@xS@=$i!N{5)_|H2lJtiN6|{8FB}6@51$eTN;84El zclmK$5u7RYdW6$YQh1Oi-kj~q+s%ytRTmQT$f5kp;ng2r8Ef}ztT16p*sCwsKVQ7J zT6yqbA81MtUr~h~8yyI85~CJmHPys~@npb+@{8B&|5nx~*NkCC?muM6>HOQHx*Rl) zaJ*z`ZXWhSkFze&2qJ{X>Y=z0MOTUYOj=b*dEKxDHS-IfM-%6(RurFc-DL5wSi7YW zBQL5GGjsFnw7h^xC#fQ!b-a_ltV%;HU;wtk5(HTXGh#_2?tnjU&V(sVE-lK`Azee`We$L%QEk;ZsMR#T{H@8#DlpZ^_}SERG_s#REZc`uDj>_^=? z@jl7J?XTgDl(wgr+&EfA_xQ`^T%7c5G}ee`Q}cr!G9L4~hpN0V&zZNXD7hlOzbzN1 znAjMSoPJivxh*cuPfcz`0cWTxOS`{oW2l`l-rcFA@FPNbRgOJgi8xuHey3`Cz!b9f z`5Q{^ER<*n@r;pHteEz;M3L{+C8aJ*76>2@L+t16d{eK>6K414sji9hu1~d@^(;+9 zp#%C{1onmsk@X8`sfK?3L+>R^3!pPlzOA`}Y?BK?@6SR~sxE>8a5?+w|GoG~!(TRA zl#ybtyUd30L|!pgEDfgM>k5(#1FTbfkllnUtn)9{NHEVOu*pxQ^jl>|74rF#lHQO#%ynR{t!c4N(wA8VeOr;} zIk@lQ=(rqz(}2}IZGooxBT{O>Ec5ckiwQiX!eYNo+;g_X0^I<5ww^yr;8&*0=$KTN zuPpMY)8R7x^mv1;@!-AY=6&>eLo#|K_S>fP_H$~vpyIPj`vqY~E4$OV&x26na5*{q zrexAh2I+gaYgKt7SVFz@Nju0gDU$uR@dZoWo^*YIN3SEbAJ)&hb}L~)P{U!Np$(ax zC>}+%Ca}7q-FNI`xp6oaL9u8k)kj_jqL!1&xuW7IV919~!DS!?4cBI2(r2J<_Qpy3kcSuO*nM9dQ44t+A*fCQOVUSCS zP(kdegltBJNj?jRvmx%bZGRG?oo6{tRtfc=nm_p9j&TV~?Og`a)h`1NB_X1k6tA;@ z7m|1K_3rTQBNjKH)Zq*>ryD{~j_`(_b@7T7MXRjFA~fPc1D0T2wvYw@L*n)*N*NCL z3p19GS@4;0MlPc(w&u{}SuYupac~H`OL$rqYD5UyPHE$odAu}uQ8#CEmaYGS-<75R z0G#U1{5ZvQZ4<5CLz*l`1Q}+1i3u3$QG$F=R$WGX^zCPV&*ic}z}w4=fLS3Zb99{u z$pp?k0?*)69S)sE4|f|O(Lo-dOrY6U%Cm@gNTWZmn;blR=W}u zI;`kev-3H5hrTLxf7oo4%9hbbdc22p+q`mN(Wl>yeAUL8_6abK05aS2vYF|)5v9!u zs>!CHi=Y`=Q=;XWfDuqpv0m{_kg+&Hxiog(6KTc~o%){Hjlb?Fv2nD`PRgfYgpLN= zJ-xES_-6i2m*&z}@m@61@XUeL1(i?V5Rrg2k#v9ibpe20R85`g)JHPd!I&pMU5GYs z%W%C?wC`&O0$~Q{+JbdG59081?UEJk5k9m3@;HkTW>?3t%8Qd+i+9VGSAnXxi!Idt zfq|JKZU$<7_UzJvwJZ37l(@PLQIay|=v{EW^!W1+8;ywBnN4($ZI5T$ zJ!Tl?p8~Ez&Ps4MIWOcenBe$8>4N$I6~ngzCu_U_OsurDxJ-zSe^yrge+ku4Qg4V> z9`rv!4*s4g%QrOc^!I6yVbqR?&72j7ZR+Z0#wP(1yg^HH@8_l>WtABnKU%Wm5HsOp`BPle_j)#k72zjm>2O3rSDa} zVNPHorL*QvgBicMxM_Y(>}bW@sh&V3IlQ`Jg9&NDo_XChO@50w=*Xd z)^2!NG?8%N-u>9SlG@=iAsNi{8{66yO`7f=0O48A4l{8XpIB=~umsnw&ANeksLSd=na4S{7QTy8aid`4!|++DYUv%vny!Q(&e*GqwX5 ztVZ`B#YgVV=O++Stpz9|_r=!s z@esvf>^jXUafGQ9Ya%VKPjwQbyM!*Gk`{s}S@n|{_IP9M(qZhM2Yc|aIM#=jADLPJ z0z*vzKrYtIe`3$9I^9#Tb7$o6LLCFF+d>aY!cBe6iTWk{hIhd~8;#Cz98=zB&(7l$ zn5CJKrME_x&UPU+mDbc`ACbpm;Rcg~!GFQS7qJk3%3s*?9$d|sIb)Ld!*5!|?FEen zZOR4^FMJ+FF+E3~uc8-Cw{N#5Cyh-|^1bETU^df)JAyeulM-vBUU%p$B7Lz+aFDg# zeebB7>_l%vQ+w0<9~!A6u-jv*@({(@BKDz1tRaRR{E8(V?e5>dpQD&eh$;K-0;Cv$ zhAJjJqGl0eE1;wAZCkoS#6??N)?CaTIU_7MyyCi^pD>2oKV*ePMC|0iY6hKtWEFMj zjS6ueD2_H>>H4!klnwk>;>y>Nn{AHG<(&g+lohFvn>Ym^l$wYV72|sCv82tVij#J= zVT18r{kr!vakL_z&ID0=tk{TNYw68J7SYxra(IC|U|}c6_u32^NbjG;kI1|waU^G# z+!(p;O&cy2g*nxnG7+mV!RQP)>QV;bKoG>DmCNH|H_+%hrYw!e90g+o;Y^i|y0POc zmmJsWi??rg8|0}T0Co}afJ83h3bueSpL1g8tkB$wS!3oj`lfyG%d5ZRsz%ZzRr`6= zZfCZPEB+OV<|oiNU)`M3%8z368WUTGw*_?MOt;eY^5?un1A^irIB7KBD#j6edTxnF zrh8)}$YjsCvt~`;Q89s&v?8m@lAiSF-aQYBkhk~-Ph|4fG?x9r^Kk}i`ampn8)K(1 z*7VV@r>S1w<7TfN)PDyhqB`J2tt|H*fuC6xRb zb>cmiPm50$^_C346eq#0t{>z7#JFFSG;#2dA*aYneKwcXCjcn2I*})qS$opZ+fBOjNOX-1RqDm!T8P8tU8L?x13FB=`N<<`cfvo3OqX zCKmA|);CkuMiqW1()I|8C}e{R65oV^Z0<6N7?4gYyqzDy^sQSr?OD0$<(1vT0)PH& z0)Mi!&9PQIGWoi%bae7ORI9>zfRThl(yP8Z*fQQJ`OHu|>OsOZQ&VTX{+~_pr-_^s z&9VeH93OWj^VvA74W|=#TvX$cT3d!Xc~f3FzTh|!d~@{1=Glhr8Z>OsVA|w~mU!Rx z*-t)$Ff7^*G42hQHT9ut%iu9PB z>wrLLKjm8uF5ZlSzvRuDK$5aXt=)l$%*%OE;JC*jx@MkzB@sX_qvXa7NwK}_QG3f{ zv4ca@#sRHcwOWe)iZ1NGFZ{64cGo4k=`8fC8K)lPXq`zxHS8Z1A75PNCefT?5#)LComB>K>*c|{RxO%tR26&@ z$q@}y*}HeQLvQT9RO+DCrB!jeUISV#Ubf`+mH_Sf3wk)XpaCV8O!SPfqh_b{m_wOl zZBl1T_2C%E$A~)NZp?Gwdm~aX@7sdcEl06NM`KM4j|t0LYpz6%0Sh}cY1eD?NVd8T^7y+X#he)Tfu1zpRq{ zh~ttxn)7fmFUL*g!~0G~TmtqJ5)+zhPSmi44CA-1UOl-WL@=loM;jhTk^naYVF0Qo zBFE1YlDV`Hm0(c%9skdr(TR!>;V=GYb07>Ri=DcYJt-J+WKk74{Q(No<8>=6{z0?I zwq-%qku6|O&Q%HR3BgKxapS>*_Ba} zc9+yXkDYrnQqLL?0i52IAVPFxPD2;U($k|yZ>k@^^X*E+x08${UtpXyIml8{XC6Ae zINqgMlBQwE-+$Gob|BIJrB7Yl<_=wNB)EScjJD{yWK@6s+Ni_eu-sq8T#q(;OD|B> z05OHV_xJyo@)B<3TgD(KJPf!rmkeQ#ufcth;c0@E(DyKLv}07LXmz2a8O2COK$h>) zw|o5gxTxmatG25;Z%W;|Bx-Z^i)$O7U)kix83<)jTD_4~?Xs=iU&pFHqp1F3lHG+7 zQfP|){<0Sk5=w$gWY8kB?xnsz!I? zVTZ+qj!Ki#rO?$Ak{5Xp^5WVV1dE*c9^aBip6jaP0}svtL#Et2o_)F4B=!~ATji|4 ze6~YS)F5lEWP?fdqWbTPoSwAhK$vw&hvpVDMn6pv(1VIqm6UG_4-damrkG(TkrIPO zGE30}ulli>b3|`fG0P`qU`95wsl=t3-ZNUZ5_}V8na?`A7otG`}{t&?|OQcbOjI*`x=?+-cVRG`j1DZ#+bg}%|L zT2@+nWmx2_0l7pLU%E{XPmaV@Y8WDWrtprK7k~&Zp&Ujzi*+;k@)5_oZ!N647ZI8) zAt3}<(AJ(bQ%1?T7dZVN|J&He13VF|F82&I$PnYs~3az9f38}deaRxixx-t%kDwH=} zZdvLNZEHEeAYld<49gB6f5KwrqdUoEJ1a3jl_V(#@JH0h`1rUr^RzVHR$F#DsKB^- z&{M(rVC|9vSMM$N_0j@=5%7td4rFXQx^jw5PS~I#*?$BU!$d|J@gxNM%uyou;YGSo zQ%Dm=PKvmOAS{|RX+pHpRsO7)=;#h_r*RYryK(^MDcgH&a(~&_3)Y~C$MjsIm3DUd z{q7z;^aVEqPLa{YzdyHuVMWR;`3jEnyUhsEjh{5EC+~_ReewD**o{uA96>U{iMme? zh@Et7=C<;jz|O-D%|>Ny89ldldfh@Rt4yZjkertp?bp}LbpIo)VS5r*Y^<8zXR`qG zjBiW3>FWZ3v?O=#hAqbQwY1?xB@j0hj`H1KfaEwv9 zZ3>sf0m{;3)2L)Js&5ZhzW6W^4&B)(s@#2%#c7_`o>g661ex+g!(C9Lpzyw3)F_B}czy5s@G?11E1 z`>HNvP4Ud}HL|{eeL99^uFP&w^}%Ufwf~O)jy^8v0Te0QK2q$T#Pcn!k+IUMv{Hd1 zkN?^*)gESQ9fTn2iH4I8{~PIk(B(Qw-uw|l1+D$?SPeo80dd6tq$aXSa;G5U^ioD0 zpJ!;kn3?wS!KkYb_r$krtUCSjwLx1qCI5C`@XP%_sn1nPjp&pUkBkups%Yh$*xZND zF-?xdqvF)%Ou_7MQ?o^j{IEFiBr5lRxKB>A#-fp$2QY?Gui-+RG~Smx&my#zm!Qx>5^_ee5e55i!e3wZTzB)^k)VG@#Iny*9=pfSj^PdoI-2ewg@1wVNwT^DdnrpDpPcteSn9X9nuu*$vtfgC)uuV-=AP)_ zfPpjlDj$shv-eNJifPHKC&xrQ+Pi+bV{O_;r-rQt=q_2nq?6s?GafznPqo&G zv99MQ^^%>5J zMqsnNZK(sGvQYy~J?*ZWQ}UL?f{eT_j!f7aFKXsHtl;w`|w9NP;D35}0;QihjXHp%B^ReFOi%?9G_hC5;qfrof_=r8a{Q4(slR49jBhy z5jyy`NCD~hR3J9M=a<1ElsSO>8mR|v+;g@VouYsX90)77A-q~#6D*iHHM=|a-rGJb z0>f1AWOj8>i$(}+q9A5+?(aksERXBj<3Bg4W70Q6i7}beYlpp=@#Rg$6H)Vh|9j@l zfT5ubRS>{=xANiN5#6ro7z6}DwkU|2gkP~&1U?8n_4WM6o!s4ZS}PxzVRtoSg?LIK zR5t_#d)yV(#TsPXQsLs=F3iy&*;Nxs5yxzgRd~^RLr!0)|GnBJ?jEiBloY5=k(6kv z76$>opS)&GEJ`l-rkrLpr3|JF?(5i+Hm$Vo^CsGo4rp5V6H09gGnorU_3pWSQTjm7 zz89VaudHaakdYn%uB-|mnnZ#_e*N0a)F~Ty*rU_=#Nhw(lf-4tV8#AJG6EY5&H}s5 z@uYv1MI5pQ>K8uV(*;I%v$J3F6D0XwRzS`FpBcq#S1!^Z z;`B(V5uLkM_&bE`2;mW6G*#+S$4p2cvdGy#%KI7{w+X~LR9|;Xznk7O|1A+a2DW~q zx#f1>yh9{5Ind`x@(VgN#GdWRW9#5m64K?*K1;P8N=m;3v_V4hpULV|HN-Mbg*&vC zo7sUvm1g!og+YTYo^(V6IL}L5yc-F`@v*KCm$xszKfxkDrEd$s3kwKmY87$j^~{?wMG&cHhKWwFmn5gd!*Y;qtmkE6Jky0qP< z(^aoQi=)qVcRrhBqv$8fIDR#`SX5=e^igH=ABE_>bZLZK!xsKeDJ9gh_g>I3JRWRO zD)|t7?TUe6{NCjr>C@s(8Y;aS7B}q0roZcSTb?uHx`M3zH!f~PqSH#W?2M}*Qn5+? z3`76zgeytAGB+M3ZX}BpA^^*|PPW_b=}8>E1F5n?F;r9(FYQvoT14tVHLK#yl|#hQLBHdqm4U#H zJhBdu1gwtQM$3mr9DM`>`;(;u#~~>}9B_nJ&qwbgF0!w2i|UNyH3u=4-Oz(Y5V%Ju zORmO??eT}grMJM#=X-Oxizqd43`%MOqF{-aMT)d{J5aPF@pG1GV!-9t%;?1sw2mXs z{Qa=Zr5^ke07b<#Sk}x+5-nXR`6>pcs}DlPbY0|j4Lq6Zpy;rMznc1EM?6(d3p+*^ zikZ``*n!b2JrE;#v5%YTxk|(JHRBoh&^{orAD@c{-*2UBhy|D9DawnS``OKC;s`-UHCruT)^-buU_3` zOdi!eAoIkTafSga{4eTXbvd+m@s$Ak#BaT1GyRBML)DCO$Asc|NgpPLBCcEND7~2T zo6KHcnf>_A>R)3`*8K_8n;lMtU_ycvX2xKi?89y}MTZaRZ4KrDqt2gy)VeS`Wb^kA zUF3=jofYjmBJ1W&LZ3@Fx*T!w>9k3+X3{L<=Ht3FRs4D8_2D?Bv{Fl}TXfgxY5I?! z&bAK5xDmjW=odl8It_M4uoMaRK+YL?SYw1(s>wKDe7ei zWdO>@yfQgyJoDeI^$|eB%zZ+?BXgnRB2v50yZzXGPHdj6X^!c2A`6pXhM^Tr5FcM_c;2Biqg=`u-eKzf z05i_BGmG23W$V_RvL$PWO``U&jmR1#%83yk!M6mzEZs1ccpi=z;@^;C9;OxxO6(L4 zNB+{aEH%x`&FyPFtV`$4vu4jOh^+`h#DKS$5BOLAN6DCBcWOWV^=O}_Y8Bfwvt6Sw z&jpsB(ta+SqxU*{)%oQirq5QoXWJ*v)P0sT*sy8q*`NCN4QtV2&o4mpk~GKt)JJ9f3o4&I@$8T9U#ywqmTcg9|tp{l*|gF4X3oU z>(hF`b&v6v9{u!KxbXPMDMdRg6&I*i)=%k6;F+doSY)KpQGeHB7xS0d$s}5xTe?YQ z{Nc++^R8s??K@#X_}=07pD)>;`+OB@*KQmXmuiEr3r-V9vl9D0e!+-}I3lcQ0qLPc zuiB+`TgTo`F3T_14FlzL|EW1=8sifik@fh2}7q^#mJhW4JS*g1O?bDVhgkc1>%`Cv0=&J;#i!hDQBtZmBP z6Dvhilwh=-=a6r7Ie#iDYPX5XB$WWKB9>MSKxc69z$`de%4pZ2dlyc@>&y)-y)B*9 zEpV4FfB#g5Lk1JAHkaUSZ{GkWHFj(f#ZX1UbT0Y9$By-)d2ApJ1E5;+JX5n@^T(5K z$4zW@j~t#`%tz_+k_nS^buMw3yvlXqP;=^`sz0Z#{T0x5+{`4kJo(G?B& zy9@LXnL!muJim`WQ+;9Twu`Gbhjc!gk_q)hPN>J*`wGD)Syc>ARrJl%@<^(L&&!S# z?myXJ4Vn83&rJ5y>_=+OpDspEZE)Urg<68MdGpm&Ib31VesAuiO@=dri(Ad>!#S-!Tppcw)<)y-51t0-{7s>y`iHe^ z_3;DG4jGXG>t;y+F zTJ+mzc=}>?!62Y&jACCTJP6GYL|w8T6OXM#czAKBm-nf^O<|Gk0}TI!Gk(Rs5UA0G z9&+l`t6bdBR&ufv7N!Zzd39Su^*<7-=H$FfC>=W7qU3@KYpy1GN-2>)OSbxPG?1&twAO#zOA&cU8b8?Rc^pE81Tm)8XtvI9uuK$v;K(TSj)g<8f0(H}9 zqEy*)%Dh7pT5=A>Tfv?kVhIR%0OFllCm=C@`Y4_a%oB$nLBpwo+7WwxKj-7xWOmuu ztR(QItHVT{6g^2(qG3m$32K%b#UY8(9;PCmD(1+ho$yHUevxD z$GB7WlC3hZr_0Np@1?4}A3JaxiB~1tDAp#oO>BJLAC;UfTagnWFx_$o;I90I{K8>{s zzkZebJ%e-PjTU#8fS@?SojTiohs2*2prSz_l_(D3rum{?05B6!-hoIKj2!=Sb||3N z_=|oh>58`wA3o21D)&9m1-Filb%iRm)dQ^nWa#0MS7Ik12<9tv04f(N1;PwT;wGMe zoYSy@1ymG1O2?E9oHS7#@Sx5kmOkm)P>g)W5ym?{)0!bwIgg-sO+6TE>GFp?HU~; zKGlwfBOz#(UWps%q@?qMD@Vr5EBEf zi7umBlm^K@HHO;M6lbmG`mJ5de_rbC*0B6Z)_1x5p%LHVh~>$|&-N#_nl6{%HEeAZ zB+=4Pp+E?cpY_J@L3Y(yvIHZHuOYK$*{MYRz>%3PTsW*S=>p3OA3t{dHr03EzS*&> z5bp{nED{c4V{mfThmdmQ6sxpXwm^;maklSlURHB zY&ErMxT;U*RnF{Hk~x;lIAZ!S{8KTXn`WchRFh z{oTYTU#l_v!mDv5j~A$cL8b5!9`xpY+^(XRJA%>3ab*RY(#esa>oEQ^t3wm6G&rg= zPltJ=8O|rufC`zPe1<)#4_&^cWYqccLaz9xNL8Gx}h+foh)7n))@p>f#PA2-_T+v10&g%a>b_yE2+ z)yd{9+)Ca={vyS|VA7j(xypZL@P> zLj#QkDMXVbx3;>^4t5KOz&G#6{0>bdgizaYztP7&0IZmH!795z#Yy1j>X+9mQ(wnl z-BkR0c8hP43&xRTg1Qa|P1%BaA@`V)GzKvbTc%+y2hbUGdT_%$uFc=|@7L_s-}LBW z`Z4#MyQ{7& z(s@AjyuWcA*9g~4c19`5CZdp$B%)HGq$?zmu9cOtQc6fNN>Yi2%BsvV8bpW&g$P9n zi4@WQ^|=3g&j0++xtIF=zTeMyp7(lS`~p$HOCqIg9u6@bZJ>xL0pmHR`?+vjk$T*fAVsP1Wk4w4Phqd7PQ1L)I^ju z7ZJ7c?7}Z!4&>~U`7jz$G1kRM+b~A=_P_Jw+~St_?xk509S;N|ZO0{~N9Y>c?#htf zPeI`&C$U5)V9Sy$B{?HUj^tHs1MVUd6`@Wm=`okGe?_d ziV=Yx)75VgK|s9_HR6M(eYfFz^=wa>wyrSUxNPe6m&&y!E>D|mP63Q?Kfc~yaq27W zrAwA%2vrFz_1NIG@qlGkRo(jomvgph&D&}JXf_xs)uNTs4Gv!cj(_@q4OObt{-}bl z7E>DvH@-AVq3a`?NA^;1yfbN;NvD(=bw(rt?m&=_)M%FiFx9$Nd5QCc!Ce6+Z660R z17Tjj-mBNKlP0&K1h8;iP{hNANp|48tLsf;&AJ9Yu%R_-JV6GlAp(QPxQm%d?ta7* z;;1w7c}6|Zy63oiU|}^l0yAk#r>yL)%Tze=W$^t-pY!vcdg*4!s{e$865UPzobR|% z!W1ym!ZcgIJqxY3iV+4p&^z3^DZ|r}8qqAs6rDdYQCj}BW4gNHlEVc)G?M%L{Z-Xn+3ypUH%r{P=Z8u19Y?JJ17yx2Wr2QnTdkxx znD6)agsw!lfZe7IYXHK7mDW_#36Af% z9yo#o6;1h(8$U!_Tf!8mOu+n3eEr#c+m>Dm{63le%J@lWzEac~MnBI*WR(5F^%Rs0{VH)~n5c+wPX!N!t!h=|TGa{}PUx94Ca%Z0 zg#asxTm2w=@Fb*25tp^Z2W4p&Np1+mj6$nc1R$KreIPzn4*BBKwv_eg@ko;0gYz$X z`8tHQPnxb+R-z56#IwdweTSJ_Y4^(MGemYgcjH~@UoUK4HpNBf$c~aKQZw7* zqMzaZY0%X!(n+?Z2mq3!`Q73&HU;eJ>gSf**h|gCvM+08|(Cq3#cn#Pk2j4M)n@s0#gl^txWr)3Qb3kVkA7c67cYz~Y3sX{bvtq&;~)lYKrGP! z%pGoof!aHaCQe7+%*7$Iu@;ep^5$*n@Mo*X_^xs|9b2-v8UbHW->!3$%=ed)y@A_3 zpmIyTbRML4&~WV<^(m@3-0<~`3{QAWxuC&q$Sbyk8jDSw6MCd>r>Ey|$VWorR&){Pr)Xxggb_$Modb zZ=+Xd;yQg+06G^R2u=inU3At&8Y200g>pKwe?;5y91z4gI6T&jQsaIxfGUvp$B3)v z@#WJm`$j^hwmkm|Bs{ABLpKQ_;WwweL$G5df%Y_ZSS%06AqlOo_NbY<(g$}n%E z|9#m2pwlFJ{Op_&D+he(=c#hcRQ;Fp+Q&C;dKtg|ac<3`!PEbKVf+lPz842X{fm3) zE}_#7RBcbC_p**vxw;2T-P_F{q0K)qOp=|8uEwREQTznUn&n?|4DADVooM`*jZ??D z9T!>_&0G7yaMjk!-QvJzNDwe;x6C^;4{iP(wh_lu#+^IOdDLh$s4^YTmqj-hAHcip z?K16!Gj?R@ELJj8!VovD%!^^6s@9r!_9S>dJ10kbhcfv3Y2B=*m4_Uhf0Da|c_j)_=0>bxf%}PTlmm*4O|0!{MHzGk zJni$2x9o?V>3!kq;kz?COdPJbF-SKoBsX=tuIchQ*N$@0AAhQEqwYVHL``@m{j|#` z^A=D-DKs~=$V|blLJ7%g*jhqx``tq_RG4vGjLm(tZk8vf7-TAO>I*Ta(I$v|rwM{Q z^zRE3or`AB@5h97L&lzcY$>pQaS=rHo&Sj#Y{lm&67r?%Auf0BSIom@oEuRAZsg7yEy>xjQRkX>;ETz z2gFsvQgXP*PFjS_sy*&q(hfo&5ha@Q_SgIS_uj=!xp%9Bx^d71?Xk-DcCRVg@bIbaP_+59Wzbel+HO)V9@ZQ&9!~a>7WHj!% z&far3UBwxT3RGeiB>TGR<|=j@$W&q3YV0P|OCWm!3CadEk8oJN9H+2xtio-A2{vu| z>0vee{Jr4QoJno4%!`41Bk<@;17mbiei)s_yOEEhx@*wGAt>^X4JsGuXT z=%S6yrWPMr6dx6}OQeCbX5Hesihu;!T>CWbq>zs1pAQaHzqG?%b$|VDgZ=fcGbfF8 zs*dgEF|Caghqr`5I&82&!$J@W7cM4Tub;-?uI1%|cVJv>A8SItZ|KdUr13FP3A5e& zO^Je`x2|rtX3d)U+Lwa_sSX>~p1ewi%Bls1dG6Rj_uE8L*>D=^W5f_+)uHye#N3mk z6JuV)oEBCykh2*KJiIi7x5cIxFPJjQeJB3hfF?50hi}QF3Z$&W_%4<(4Q#;cQhwTa zW@vL6igy|4SyUlBh<2Eo$Ui}$MsKVrsfc=vTq|Bit5x&)R-0NWSE-KE-envt`}n7! zBji^?<{VWuLpYtOV)z&lJV?NhFTjS^Dkqw4MZH1aB+IAZS=D`g@GmY{D0&9KDxf=+ zTsridU;-C{H151z#h)cMw>j?&&4&z2P6*!5QA^90+In&ttvW*!Q)&7OpQ(F9o{G@; zXcM~l=+aKfdPr9EhT!1!?({kF;i?tG=wetT5qb0~v#!{^obS2qp1HPBT5e=YO3Iwg zMg$0`sWpMlWNo9@2}<|bj9P=uZ59+UK%o&==}QhW&V(TVg$cEHVkZPE7^?W;ly#@9 z9pSwNOl(k~YSPX<&vxJf2mF-)W+U~Ftj_MbE`Nj2g9)nqwwW+qsVW3hBCVcg!b|=r zl^*8Qy`XwNZ>n%ZXpI=rFXG^u#{5OB`YG4h6%azqIT76^J&B|Lf`W+)7pig*9!GqP z*BLWijR-F-HLAaQGZI9VNO+j3@j7NxYGd^O6K6r$G)~yLH1R zKFjQc;GGgRJ7}JUWdOSycuK}v$_gWc9wdOGlr+*UjLnU_`klVKpN7UiK#rONOJp@+ zsp7@!%zHaaBbTAhGAek~rfN~Y{ue*LzW&#D3%9{^Q2@!muQQ}yfU9WmsoPA{UJHTnX`9sG;+qdi}Y3RPzE}o+onE~Z+`}#cA`mr$^R0iYRcGo(zR zP)%G=g;$5_(E^gM2?K-N>J?8IJ+?)x?pDT6?%YYCs0w&pi%TqS)t-Jkrg4aLEPOgp zR{~~4pG(rETcwY!m>5O16Y3b!OTqP9?rgxGp$utHuKO~L0^mMOUG5&C9GP7ImzK{? zQCte41_uV5;9C83iPOivAWvr&{N+wOOyRv#Zi*UVQz(UCqz$g9tjL}Fb$r#kZOmUb zx=>pF@PrhZG!znz(@TL|idS#nMhxxwYb~7>k>HW7{a&*SfIf;0|9ywlmBP6wDzuKn z1M%p$?>8Gox2zX2$=1+o6(4!}XK`In+=xQRp#M>xCxtDb^oaNew4Yf#1-aHHCH&PKTS!wY-y0{^aqJdJCk0sQhJdaoEUZSI6!c23r6Mz!K3p zYZX3qeU-Y5HQ_*Jb12Qs2C@<9M1uD432g~~F*Cc-36<8bA8W~0dWR01+PY7lK3=Qm z0CRIf%Vgb?Gehok0u(t|mW{8O^?TK?eifBxXN_;!qV>}USXAyDQVTFfQJj=coB3te!cjOQQDkTVY| zL$_u0yDuSiZeczqzqjDuoyvhk1>yK@gZHJWocw|u!Pi-84GCvxCs1`(c6v7(uOcPP%|s2_!9jDV8AdIRpeW@aM1W|n z8{afbJDdv~y<2Ebrlaxts*^Hxl!~5D-QQvq^#VwTZ$aMca+-YcAQQN3c_F6x-+y=T zy`$9F+_a%D^W#-j|H9n`Jr0g)8MTd;+2&|HUaXEW+nwzW@9p(ZXy1%=b8Wdqt$&U4 zP7TeEO#ohFa!Gi4w<;RBkv$y*6!CXj7bU6sX8!A6u=R;0Mc=Pv#o2N5;V)pd;g7euij=XRKDq9;EHl9&hj19I5X z=sh6*H-=ZXZ?bLMHfC~I&P`3)iRv9W=z-J)&W+L{(|P^6Hb=QcrD8r+Q|}VGI$O=} zN5jyuneS=E@b-YO{Uw+b$zje_+m<*x&!ivlELF7iJaVK9?i2bvZ;MP0LrF4(^kH7c zAXuG0?D>DGOyq_(Ae^PfGUR8R&^b(>#1^ONlt8}DO3R##j44+qSX)^Ymz8-F@5E0B zf}FBc;WzCfIQrTj9+t$h^O8h4t+vpS!k2hE@-IRR(!PKIK!^>ZB0?(TlR+GeqOY%S z@zE%Kl^fh$T-!3lH_-&=tPG1{_5!fcuBb8FdZBI~XgOYrdPMvq%$m=Qs92WYZ-Pqb zg{eXNGcS+4vvT9c%U0F{DZM0QPX9B-7O&H8nAAK3248wKO20fv4ea}Gsv%Zrzd?i2 zNr3>v+Z9ra#CIs&uS|!a(2ZU+E4HEXO_j38w9MMhL<05joQkn(P1Dfu`xor?PAj~#MI8mg2l<&qEL%(o<|$w*6m^rN5|{57hmu)O<#ZHntv{wk9Nev-Z0~|3s%Y2{94X2cJo9 z)3(fPOiKE0y*Y#>IAqPchpqkY;6;<ac3NE|4>24$WL#gGtL9Tk@ zMr{}xk$qn0!qFg3%pr0{<+qs47vn~nu~a#Lr_#QC*#1PeXWd_y=Ix;?MuQ_RABz~v zc3rzh5B2~4a|NH^%urV-fqToi1iF%TbVP`!&Y*;%|D%V{Xzr}j zk|s+;0lOnNDI+uJt*ScdLW}l|x8iJ|G!X+H*UR#P3sZN!Ifi%?R%LCZQP}4u0Y(wx zuo~DqvtP{O;?f1qp9cn2e*3%Sm&g8C;{wu04>Nw>|KYrdX9U%-Ix)oY!S6$3y+c~* zUVGP84Ar=}>MESwU*8>^^5JuJFwq-#N+#nC?lI;zXIJNOuA{hQ`=AVq`gSZN7h#O*|UDoi2dh&rA$Wc z=jr1!EvVyIcBmjrd;)^4pE=%~JxxT`=q2d@kWcWcOe0#nIQQ+By3EsHUC!S0ap^Xd zABpEnbGeCOl9f8m4&KTge-^>Pr!ns%x#*%zevbzuEST5o=g*(#(If&z-J+{4G;Z8M zdq9-=kG$mhz&Ro~eDcKb{|*t&0Ac^+)Eep3l|xC6SnOhNHWej`IFkL|wWl_Q%&@SD zeGZ`Jl0jg+60ZlOeu;wxD#YZ1`d0gP`))pZ?^I|{P0*W>Y}^sN5p%2eC=1od`=e`R zF$J7ihH70$d^Sa%>-@8vuY90=2-k8PV7`s`k z)(^)c)VxgT0ly%0$7oCm)xVJtRD==1SQM{(W~v(q6{I$i_#R=Rdb-yQ6{Qb#nH_sb z)L?8qAwG_c+nhPrt+HiA&>KLyON@U(X@j^1U)3b~3K5Z$HFC7KN6BjK0RyJ*9&WyT zJCY!9+*9DNR7>7*4dGO%2)v30YHQC9*A9gkfz&Jodt&qMLxRv>xs&(gH`HES=8I4d ziMrv`sf@wywbOP!nD1MBG)F&dEvTL#96X zh+0Re@MWGkUw%$MJOmo}bL%CWZK2lsq*ZKHx$qClcja@6j)Pgb23$$>=Hj{(rQ!(b|KJ049oxC^FJ?SZ1a!fEaX2&Fp$Q*dxmnBb)(=dK8mzYI(rHFB?%bOIh=R3Y zK41Lmrbq0a`;jm>+;&y2u}tI zfOCnyf&!?749gKbF|%&rj@U(5Jg8Ju2MyYT;v{B7p*wT|qWd~{{FC$&v@G0aOe(kB z_<~;tSvrPdRA!qHYkFV1)q<51uI* z*)UuFmZ533;hGGm%V}{Yu--Di&%*Q0e~$|qL&Rx60Ne$9r*~y#W>!`psI#f`JkvK* z-PqD~U80ttM&KIu+1qcx#y^Q3`l(!8kj4}YSzOjbc?(o;C|l8OZ{cR<7*bO7C}=5Z z%%87bi~WS6Hk((Lz2xFREDUUeQ+W+ih7U#NIU`s{c;y#?7eLlYTL&2HWcse zoxSn+vzL$J5jS-fnpVpi#y43LqKP4 z-hoA#Mx4f-)_tKT!Pv4J{D5DV9m_rB6_P+XEy1hnyi5pNiS!+m^Z0Q%)&W>Tw{J1F zqOu0ptot)Gv~9{k+N@$aOjd%4laeksr`n5bF|)Nb_)prxx4xa3Sxf{@UrsS`>+@d& z0|Qg%r0`q)v9_U11a>x$zUte3bbBJ{7z1~kGp&|jzqCP~b_?FTe?RqIuts&C5xxB` zIJHu%%XsXTUpXqw?X8SKVqdi3tdt=gnw0@y4b<`8g$h~uhj{jt<*?tyr-c<#rSLGd1_ZJQGkCv|LZGZdiS#!t+H_)F%Jb z|Ng}_P!?-H3F}*czJs`lm+k!0tdVh*zxSm(R5opul)hQ!N*1-u=Wv{Uw9&R+*ek}v za6`Hj{~g$%aY7H|!`Ze~Kr zS|CAM$fBjW7sKLqWxHRRy50OmbkwCrR_%v8wD>gXh@amL&To?BRY#0af`4boN1CIb z&fNnDClH~i_XrUQE~a2H14UWY$h#MDzwT(sJc0!spEl?%Ehe_@*JvNH$pInqMFp{z z-it)4z~QsZuReeN97(;Jrl!&2yc)`*uyZK`BWI;+mh|PBj$ZSwEpJg`4Cw6{b+Zj4 zpjCboT2cHe;va*xm zDLv@8ph_5CA=8TpVU5l068@=?-1*!tDxqZJVOPt>#=!>g)K|$qy#8?)EEBM@7HVC> z@NEETVJgSY1c0||+%9SSy)VN2cHn`&aIfFY9*cA-`M_)Ix_O#z%ac1Vf3W>@!@j7q zL;rrIdVafq=It@>?f-C0X#uD(3yuL67!t*EMP;Lvcms-T26#JYHTk_nzu?OC$c*#? z!k~gf{R`UV==@0BS{fP(4wjSZMf|Jc_b>Wd8Op-NjEq;zP8jVi=dc z=YA0CK?v!oMn;VSVU*pADaxp1wFcV7AhBBGr)yi|1iFNEJTEKto?ekU)J3_kv zK~u0;HSZ}Sv1G%bTzeDy(ZXiYm!CdyE#9_iKxHn|ay2_`;aU+#81}apOFMb-Vq^L& z)|j4wE1L_ijf4#3FG;YB*zMy(I6ggf_=)?c0vwSv?uHRD+E z)auEzY*P+i{B_~*z$qVlAJU3X9!aT5%EHMF}Kh1cOF8m6<$ySsoyhF4@JH z$Q#n-2xcvbb7T+0vIy>q9M0(Aq!!4Rw(utt=6gs+EmONP5@))PyL!sNra&Bxa^#eh7CPP0^sZjXBOLPVh>DDfg1{gR$4OXpC zDX6f0pm~v~)4O!(H`gSg>Ez$8%f_89Y6{Hd#o)_LwhpaOzF=x!SF_fprut74&ZLW& zwij6!h?zv(&Ye|pA-4oQzZm}L=>c?iK<`k%k~Ew=$~kZT1 z57XDI9IkOI>%_4`ZTvO5jWz6`iJi}j){84d!tNak0q*6HC5cV!TYMLi;_gbh|tMuBm{-$F059Wt!&BneEITv(eG;QarJdot&>cca`k9adRp301{YCckUF#o$I5{D zS35iGX+e7Ta3nl@)%IxGAj1qHSU{!w07kqvevV2W`RIxrlehd1nyt|6%Eeu(S^&f{ zSwpx?!lrx;$_ENf%Uz$}yMJ#SL+A^s8mO??Pk?}BXGYCX=2XkTj$?@TmTHf@#l$Po zktUmyzV>e2vgIwZzMe1o0@{q0%}3RsNDajgR+<%u;#WqI~V}f=`&d*41tbx=%@*rRTj_SQx|`=s)%aqkv=} z2aMo*`gHcT2%_u?6CwU8N`&L#~YG#O>ZIoNxC{E)y91xC0swk2%J^({a0Tc%9 zg$dU9HG|J)z%7BamEij9-uq{<;LJws1zO-sPA6<1v`MhNfc%6D-7jO$;t??JX^%*q z-fuw0A^kQD6sWN;km1;k)lT25qqY~CEVdiOU@bT)9?Z$aM9bKBk!rYVC60>TXIXA( zB0q&|e`qr|0zbR@$LstB+Sg7o5#-6s({oBtQIkOHBECy;GSRpluNf3dBrXY0HS;a1 z4Sc(%fh1`Kevg^7V#UYrmKUFT*h{AUXkMhb)il^9c-hw(y&bl~!QmeO$ga7s`B!~<^%}pslDOQQIk{}{;_Yq5z2v-Q4tKd*8B^jA#{ZRvZ{~E8IN&x zzbHgt9Y{lwtEyR`b588!>3m0FACiCnSe895lG~36MSmhKdMO}&^kZ5a=%DyWIRJJ2 z)|zL2duKRbS7Fqg&I|2NxV1a)TDyuueL6K+P;N9(1b-v!+-?4W5N~m0`cBjwpvpzj zn%&`_TEUq^?IJyDOTFMct8o&JC+WzBGV|1Bb~VPxt>9YwC+B@{0vJ%t+dzUAZqx3R zP0epfqj_LzVG&^-dKGvDp&f*YRXBJZJAbBcqOZ2D4n$ctpHzRnsQR41qka(Aj%#X7w)ShR^jfHbT3v55}K227G}!2Xd1`3)`>xii7+j zdYWT2nQk$5!F0O3vB_<&q6=@28M`#Z{XQHN5S06My}FKw&59BBtrEPyyS=Sv>Tfy~#XrBj%R#>|a}b8NtQ?uF=u5C!7){YueL z1Pfx8kq;{KS4nAD{}`%W<~H(l_~Bf9?E~`SU()LuVEnv& zNjFGXw2>Z{eNzcEELA()!2X;0X=zPtZEY!Mp2n>_#5uCd^fYJ*Du{j+J)4AHr4|GX zq-rxUH{ZeDVcAH_EqU3z+2{-RQ&3N!upu#=J>>!R35nRWYOE@wF{}*Pn`WWhEg3Ruvl?Kg0^7{nMV>5ROnAK9H_NVqIR(^IUkCh z_1vx+9$1nU7@_|~<`TukEF?M0sq3-+I*OP(i(8LtYkuYwB*xpLzPZ9T@rI{+7KW#kPUvqs=0h zh|OEHkh?DgBd$?lba?nAD4Dr)=h_XJ56A#ceuG5_{=)$*eG|J|)2A;7lYAUpkcdE3 z`J7PZVBJ&b{c#M+93!3cZp*8ECmdgE*3VB%JH5?mMiXpRP4eO#xM`~z{VI~pwSo_{FpXQ!cg zkBk3AhMr&6;(=D$=R{K0cxmrHkECUGiPn6G785R$_`#(KE8PdK{9U(!HyN3@zf1S- zI1caVUK-79vziA;vidF*HR-8AG-8rC%+09lYodAD9fjZ*1EqItH?F-579nKLTkc#= zpuYzWjJ5RWD;+;!B%Ql$tb>ie ze*fMqaLFbrY^=!R{|hW;a`ZG1amIQ0TdBYhZy`C5!uHQFq$1lvhd2o#NIW%;ZzQFR z^RYw!l%`V6Ki^+%g zX*Su4&^R8oV7pkSL_>_Lj1^+Hbm>$Vmyv?~k=Q_or40JLLT{iw2ya=}#R~P69h7=2 z^pc3F>iBMHCy?huHqv>qr70zg!H_v=C#Ch21T#1V*@TS8t$Dew96_2H<+$=La%$6z zNxvqKzECd+8z6^9hJj??! zrb0sIBg$O)xM;!E-)OY$+&OZh2A)4gquR4(##ddOj++4o3F1D`k2#=sN2FHU%(QtK zG0Q?TTX~pe-zI1Vp_dRm9A;&2d#tzPOj<{xZ z`91p6MS>3RKXPOj!P}g_5^KWjL{h9!W-kUo?Areamkzf{Wa=n4+t9K zH1N&&JBslW>TMRx#;}XXkDVv44!-YWPUFTsdxp&L9a>dcIbr6^_^cKYjVPz=>CTXp zM~^wk%oT_>oyn(H69qb(zK18ojptkA>QV_^FXQ$8rB2Ik>VVCH)>D29-rTex z%D`THKy}_A<%y5ValCEEHGEEx0(PR^gOK-3-vw z6zYnr2EiAE6ExWIa}TPOD@zx6jGK8P&nUR@CPkaX>F;L7pB&@8YIwuWL+u)K{Gdjx zv_A|23oaD!VJ7=m)HxZqstDl<5VSD|}gjUXr>W7HcGU($>K%aCC} zfKOQ*0;Qp&T|&oQY2azWoN{!DjR z1;yazzZ2?*v>MiYTBrMIXHN-clSYMzyIi8)2o{HmUjE|h5neyQC0bm4b${-CeMlx; zfqt25<2cH|_s^~_o#FfQEWd<`Y)!$+UvZxa{1RD1^jh$Bm<36)CSVgE`CBMBS>%*I z&=XPFQ(t@TfCT{)7yz~h83a96lzAe#Wl`(P`lE|_YnBB*Svw}qcv$oLSgVgZJ*K2K zQ`~he|3k37o!w1N@uH{E7a$B#y{y#;2p=JaSs?$!pS3`_3+S9kWU@-z6dy6?RKlf% zJi>7Ia*gotPa*3J`)tpXcT#_WnogLUgait`5nUHPu?oAEr&lqVvO}&#I(EmY2{&h= z^f#Ei9DGM4t-?8^96EI9yXCFVY%J(B%*N=47D|HHvSqK!%lj8x0HuyrNP#b#0I+m? zZeu2{43~sP^fR==y>)Z~snUcQL6VfNX#p0_#jpgi7X$pnbj!KN-0%UMEHVcK?e|s` z5CSZKG3e)3RGdn4t$nu5;8Nq}2}Ylo@Rzz|w%O2}$M&BJp02O{n2yU{WOGP$KrqJw`|6tlr^6rIo6%ZV&bNN_2fXf-5vhmF}kD+Xn$sBS3~5A2btK~gjT z5DPb7;Mad3` z2GiaAvtq@I=)sGpfgZ7n?`Rjf-U7k1@H($DHzPm)5Or{jv1axT9w?K9Z*oX88vX1!ZzUc9WKT160DLA?I?#$tP8js%X-CBAqiG&v%5IBSMoEcv7}X-w^?BI) zwG`w#ky{b`Xklo$OyZ1y5wPBiA>lx4#cthV7A;g!*p``ys1b$th~yMz=W$$gbT0>8 zs6s%pvq{U2m?*&o4jAs|@}$`Xdv1bGk*-X?J-E$H+5!hh$3LAX!V~I!I%E%UZqV0a zejW0L1==@*oTj{PyTkt6*B_%}YS!8K@6JjdIv{CKNt=|P!G;InLNa*>X`dUUMUrV5 zGs+BrUFR-UG~>v3uWF{}C+)-Y;ZtdqlzOpkKxq@<*l z=&J-IG5bfBbuu&2D_?o`6bE7U7Y&vz&AZGnVtqxKDgE814GCn4S+yh4zKJ*ianruL zZ|%li<~(C}i`(ddUVV2K4$5GWj`Vc>+>lO6vt?^mmpJ=i!nxdM2gYj+9l8L`j>L@& zv`&n)Q9xKO?tT(0bkowphWimW$=PK+Vxcw?ZZ^Kal<0Q(Hdsx6PPlLEDDPf0*E(;K z3Oqjb03+8W;<4uW-4CD3`xqKJo~g^*z20~CZb?`eu6E*@Ja`x{qvQilGI?5Zx&-o| zQ&LiiW<(GM!_-B=)iqV57McDRzCa-N?EY7mwh^%sxF035o%y_Jf>0oeg;3XB^y_g) z4kszLNL`s9lj0K*p$1+|k2P)A7-D5GUKVO~AelHy&K_rmOhhM78}yg3v?+l*BilAb|_44>L0}h|Es@TiB%fduMPp@r0xiM5aM>Zc{ct zX|+=qU+eJ6eR6LFE2lxfJESGQ9A@pdy>*K}qn#?x%g_jt(Oc7GNJ&O11j5N^Tn~)% zoJJpBT(e&2@hmOPgQAC+T4K&7@_ewqC}Pv%Oi3$6o*!fWp5o(xTL!8Tu$fW#-VvE& z{!n5-BC>LkB1xt({f%j1LkWvv`CCpMoUJukiOJ;XkvM7@Boa)!6EA{3jyrLe3km(^ zADI)%#~Vci68)L!mvZwDo(pd6TuFf;ydLHk3Z@KXI{Y7FrQ9rIts<(AGMaX*n6_9* zj!ECHTn7@Bp*;C(E2%O#N=U|ND0US30P)WNZv4_Sjmp7LO$Sy-vasvxOJ4@L{*sU+Ta&{bJ0-2e0EHW6i-s1YHMd63fG+|!L`)E5Un6{_XZ#qd$UYfS=5}axXij z6|aP>`)6@a?^7i(U16~0P+~J{-i7alzDPsK%@5}wyw`Kb=g1LoyKroi-Q0e!yVlRf zp|6zeI|2=|241T^e%bU#Y&#=Dn=rt?2sBBYuDD_B*i&O=fHts=1T`&Od>_3x`RZri z=AJXM#8E)K%nMbr_H=6QT<{l9b=o!EwV&35mWk`G6zTVW_vVeh zz5U7d{Y-nIB#qj(9Jc`nIEWqM3EQKy>C&)ubpl>;4<)%=p^^TfwLkY>GyduP5UI!a zmS^>Q{_O5V&MVVeDPcO}ycXdr#JlFl=3E1G{brVyJJIOT1*DUQ@t^KS`W9-~4tswx z5Hghg15(ODT0*}fk$W;F^5DUf=j1GbW)0hyasPg62uV@?{1KU)VSpTbkhoZL)e|)i zJYx?p8$NRk=Ok4rP5l%Ypp=@l!A$$^)DsC=DfowA&WP{@X8GjyU6*y50da)jK3oc0 zOG^pT5I++Z9YAu4jOaIkF=Bfqt>)hBk5A72g}jO?@|0b_H;j%nGV(S!|HHW@u-#k8 zhl;NKFJm$$H!`emM5F(lS7%6al1wNB^&kpMfSdIk>`0OlPx>XdUzao2eZ2V{DzTuZ zO$W5c8E?P4|59SXpF%U^pBTATM#NcJ{jmJREagG-b3hXK@vW~hLA412{hRsuvtO@< zBbMA;jy=UB@=dS8U@vvb*i)I0%TxTa!qkdRywAIyWMIH6FtBv=-vxn zZLs7Npil+W2}KYJVNY72?$;hvvIxImE%~<`n$Som>EzA z8*wL-4ZZ+Ts)YBv)jr6?GY0BHB_gAhE(H|_eJX<9TPXW6L{6l@A(|*s%^#VOoEx-P z35(A00N`c0nZ;pAw*gK#P)75?O*e!%x1{10 z(LjX`Y|l7ff=mtko7_+)2|jdeGhL< ziElLD&RcWwl*j97W4Qm#%0o_xhT-Y8P1?|jTzW!?k_OOU{lyxCZzcMIy z($e0>7R^@1QT2d@I0xlhw`<8@(1!y9+aoPvL3t*-%vO_T|L~ zQ>oO{t!&@Fdx!JDYIE?!_e}PxmpDN_!(glNmo8t{+;DHjlQRv05or=8a?w%rfaJ<3 zF0>A(2F*JecCz8z@axWQRozzJ>w{u}v+4_r{vTpfSSnf@wUXoBbWE{b&>KRSbC$oE zMPGyouPK6@4huEdUa^&%kgfIP(5zgKie#9eFTAd>xA+`8%f%n#R3;^Jw`m9i&aEtJ9HY@W~&cNYQTb{@u+aiFi^*WOrueJlk>CzFxc) z|9ni`;QRM~9auh?&^GW6$s-owAbu5gH!fufmRh&&yUXN3j@t+(t4s0-Kw4e3A2mrMQ=XX$3uS6SsI&)#)#N(Z(Bp7Y{Ifhz^C zSjhvN0LWNyuejQd;}FX&vg#s7%cMqJ7V}6;MnuNh6VTpY@}7KsjjzO>5J*+EMn~sX z($v&ff6wfn^Y+^V=M7^>R`NC~hikPTI4`}hZKlWSC6DfA9_212 z2zLjAwP;M?hiQ*23|Eju%Z-V7Xg^_RUhY7eV<;D=v~A4CO~v9vZY0HZIwE^EAEi_& zifQqsoVoISL(V@_r(bFp;hVl?=s!2o;y<3t3-3G8Kr4IQO^l9LB2VO97_}_w4Tld+ z%KpGWP0fd;SwW{x9K4Uk6&Q!}06ylUWy~W~z@v0@zEJLQ>1?4*BhHe5ug59w?zC8U z03t-mOrZorZoQ_vXg{fMF^sRIlBI`@&$(==Z9A7l)Ar^~h$;NfRCP92KkB{&Z2){M z;FyUWHxm;Ve*?rJ((IK*v&rRG7Uw1LK)9m7TvwBP%J6`y?QJj1{5yW7PyPI}c1`Ha zme6Sh+b_)bxIg*O+1hnp-j~(We}C(^*7)4W%^D3a^f|8DuI7BR0k)%(jO|W2EI~dc z@;opX%Cs=xP?4aJ*&N#W9C$G^-ebecmJiNRJ0dI!_qF!@zk$JJxQY0{ez84+NdQJU zkcxqTwHXd_G&kN^!o|nA zM!$Z%x{_c$v7Sc+#q?5;>7{%cUYasBSk?u1gJjdbHzwNN-(K`!l8T>XkpioFAzs4* z3KJ$e?y86M+jLJ75_@r_s*E2jNTM+A`$v4g2O%n)%3bnpXX^ z*(#s+rcD}^^1c2wF?iVyE!Q$%8#Xo zJy}mC498^gLP|5r3om_x(2*}7aJXbTbnGaChG~yOT{jY6s-UJ&=XPv(P)1Dp&WWqP zNje;euhS;d7x)MmN}M=@JP%{7&*^HHPX zxUl_tXgYM)<;zxMI)Oxq0&DdrrJv!^(cVC|F$rDFi0PnuobeDvd4!8Ah724*S3yZC zUVPl6f}Kt>#LygCwrm8XBQe9AQ`%oL<)@M$7rxD=ZDVBJ#_&QYDAvcEh+Eghxb``i z3F4QsO^a)D{?n^9EXe%Ql#V@&!7j zeMS-gMQ-RsjJ#4j@frmGNQ-EwA`ZVcz)mC@Wjm%BPSAiVqP27@-*6h-7NyLSrK8Il z;Cq-bZCXqAB5GgB?gmJMzz~B#>%ICS1%wdx)n1Xdy2I2#Wyg1!sQ2xwsxUEVcofD( z(cir8$u&shFJ2;~ECk3NnXYbCd|^ySwluaTQB@%>qpvkT_X@9Um(li(rqzY?a`J4W zrWJDjvQ?v$)lo~HXGS>gqSRKxsEvzi*ybN=)Y>5$Q`UBV(TAkdf`WQ0pZDeEa+Lr~ zv6i@=g?J@&1|a^{;uC$R)g7b5pM1RHY=>PZE}3=tSvmc}iEleRJsCenGS^>Hh*D&i zeXdCd#aOv!4R_Z?i^r~ON6|7<*C@Uooomt0*7mT2&J>9XGBot^&f15?MS_5lUHm{EGTj&6B^lWc6?}#;tR<0Re}L(K@-gui*Pp~crRP=` zTK2QW8lKV9{T|qkfOOnykJb-0^J;=ZStHOmNuLC@>gWWe9p{E8Por&z<2Fh@=>9R;gLg0)leIJg|S;=K0=?Y&T&$Qm4y_hL}D~0#4vm>~LB`x|#F;S2~ zJnH+!qg!&CIy5^{H@I=hlbm7CCv?JqkFYUy`o}#b6F~u#Y3KM>7Sr2O+8L~V*GwFYV8sH&(w?9|FBA=!H3phG^{hp|!D+@G~hO5~H<^&x*D-YOFH%5Pqo zf?f33gtm<{mjyA#;F0mnX2Vr&0$Td?QV?w)wf4$yztDPdBxTV}0vTLw1se39(nfhg zTX-3vlqnm0298FRD54#d6uIsD8LwW^LZTz2Ua?v!aa>4FMWQYXgT$Q2E>DY@v(^wU zkAF*^OxM!$1=|nq_yP?8YvwuGr{mgpV;fJnPMJc|%Z0)rm#?9Q{JoXoQB=H~@kH?# zy{dS;LnfdA7X*xshawgCt=61+9j$go2yS>(b1BKV;t2Whf|{z_04gF%Kp>!m9TsgH z12E~UR>`BqeFGZbYn;#{urlb>Vjg{&wa99(vhG2O5{3=mgU(w1-RI=gICZy5z2Y8! z!q1fNoS0A_Y@Cc48B>#pbEtV5o&jUyX-Bv;)>jmQbno7bygY&EpyGX*z>C&`%XIsB zEP;+));=sYJbr4|xOHytvjlu4a}ShDS$#OYV|Y~5)T@_bf)1@{BYZM#v($4@W-Yd% zHgS$=*&*%dc^DL4u;}%|Gz8scF+{KFO2COw_N2;)ijON^;&Ua6Y{rqt0#3;a?-5qE z4~l@k=Y>Pc(utUG@|iSBeDz6g4&K1EfPGa?$D^MA(xCw)9_-flk%xZOk03cbWeF0s z!`;dg9IcRR&q-RL%z_Lh+XTo+76DNz+yasw&Eb_|api;>X`9%X+m;52rV~_KtlpgI z%vXhTgNm_>F*_S911ZzeBC@(2xO8cQr&1B88)p$njmYuHF+=Gp#wRMo!sT}{TI>Vg zbt8~q7*bZ@^vFJdp91j)f%r-3%Ii~wxF^Tp+3B^lv8xBJYSt!T#x{@Sqt9Q=IQ@Ce_0;jT zHNj&yjg%>7Ao?=U;l|^~=O_IXlL~4{IV5f$;Kfo(EZS1_@19>{!=8WoX=`{pX8EEQ zj{?5Fd(nMFm(HCPw5*K<2*^F+=%79j%A~A=btLa!`b(KhQ*s7pFO^A8CK))aiHj@1 z&FO~+z-Pwa#Gm{bJss3rFs6zE4`MTR?%WAHzK_Myu5;%ngUlXx1uJBh_Vl23QB?Yr zWiFaWcGO2F-@SXcQ0)W%O5)^EEUiNG#X&a*3Ab)1%>?}^j`OIFZ?Jc%9oMY?JEmpu zUh!>pml!@E=cp0ZRI>n2ATqNnmy{2<`Xckd-M4US{)Z211QNquE@|-~AwmZ`f2IdT z4;rQ6rE3-;!SeiI_O=9T99XaVpB#*5-gWkqfw2-wM-wEPO6Tb}tt~Ygayde1SeS;y zY$q%eZ2Wb5m=}<> zI2=`rjgA(-Ixar1j5vLjS5!@6mf{dhn){YpT4m@^)7S;I)KsZui>6WIJ>&%dRx$hJ zptr>gU=7wiCxw2W1^@trb_olClO6GaOyV8uS=YIAM8J+G8XfNk8km{w&-`FR-7l9J zP=;(~ig{_EAeF#Eb?|Uo=-$P0+dsWs>pyb2fzUM;9UH;=gHw8!zj-!tLsi}ZipfS{8qE2r*^E##MRmh2`c7G#hCY#5vR0; zSBk8mGzhL|RWO7|lhRcU;FJ>c%s)38MI5>De~lH$l9#u)3W_DX!ArXbFKx*emW%-E z;P~9ya=O*V6W$$2JFTq*R`EoAR07p5IXrd{14Wkp%c~wry5z zIIELR8wkq!24Z|P*R;6QYb;(gKv#ZY-uo9`Tzri0i?r~6$^lNv!ZLWxbwYX_U!xly z45>!AJUDZDDbP33WQ(+N&J`D@7>i6=EJYINk=TQ=nYDW{zH0KEsD|mB z6Q$Xuc`u?SRX|3-eM$zrBqnhTOUynjF;^0rm$Xt`u*yhz&=Ti(ubN+9U-mE1D8mF# zn8k|JE;`z%q7^A~UetS{rvZJQ9KM9hjwLDa$yS4J4o<1tPen1z{kJRl7W?;aP~02j z>hmj3m_?cOu^0GmW=MKoo@Kw;bK5qiAq2C{V3IXQmRh!qm*5%53|jm>UICrb+y^?p z1A&rJJBZsu3$u>;g?KppURkiEXri^cZx4d&u98+uKf5bm37`v}^e=r_Mt;!iWQ!6&yMcieg`R&SgI>s zT*Pe!2ZF<9(0siPrLRdc5|zImBWT5Zz)|thA{p1Nclh3NYujf)-+x@wKqqFxoRp)_R? z6@5tPY|)~9mA7vHd<*246kaYH21)uNJd=#r0T<(|+G!ob8OFDew(0O;Lo|1iivUqY zl_TJsRTr^Mao|uelb&LOv0cva}wUlHjvDETP=w zlO!GA>+U`){DqjpsQ8bMKKSul?Nh+cVF>kqi`axmJNA=g9PwMywd3H z$g-jfiFBQEXhm*HK#&7ghst_dt zrv(z04LBuv$Q|96A-bV{iNaq5+s*Yyl6z+mf`ZrlkiXezj~+jk*%I`2y~+MvJkCs! zkeWY(V~o2hE4MPNDO#d#Zn(BcV?%k++_4M_>izIpqv|hT+TU3Q%=_xqD=rl1i`_tN zzZ3T?+y z+bsFLd-kJMxA~ml%@4_o&yK|>DiR55y)C5c)&ESX_kk6nh*ZkL?iLie^nl&zQ`>8o zt^UZ1kzWp{mheLtRKk1LxT2;=Zqu)BsCp6IU(^kp9t_x)R_s%1%X8PN{NuxchyZWa zM7R03lg`e#E-WKLlKY@{2m8^C>QCi8_tGjgh!at5NFaRnt&7}t8Vpu*r zL9RYZ>#eL5m)p}Nx{7l-!ZDKP33_8WO`0&G=oD-Fmc}(Auuqmo&OhlER{u`pQmon}PBaRIFsah+8iw9KCUUJ$A zved$GE#U={2oB+Hl<|r`$K|G`r)R6S$^?lXUS{63V28Q6l_|Uf^5&TQoC*(=R%+Cz zJvTO;^BcNdSLlR_FW#wcJa6;U zvzdNdu9vLbymICHzAdu35h-gs`o|IypSsM5fO#$p@vWc&83x52@p=lM3!nrX6a$h` zm#5sGWJOZEi|v+E=)LRmsUthlAs7tPj6TM~L@TFA>BM+6-LGS)i__v-47n@6U!5}6pw^IE`zljuJn62tKO>gnmB^f)|rlglZKCPgJ(MOBPO z_R^a7kGc&WdHJ)8WJ>kC1z4G8IC!nn7SVHK%mN>;&D);G#zl~kwBd`(nqwqz`fvz% zS=^*H^F!{+c>`}DHVC{myB=r*u3(v?AFtHS0GS64lEEO17a+e+@_!Q38e-ArZNyFGE$)dT@rd_3Xg%<#05MuGuy`1 zLABpu%0F7cRfMkqv~Vp?jyG{o4}u}Uz(n*RuecdY4}xGJ({qR}!RK1{VTm4)dSvI| zlvY+vJ5lN|*}H$i-@#b2ss0CLq+IW7%A78%wlZUtNI`=g$gXM>&d8$hlV`KAt-8h4XO)S<} zXw>fwg=|0xd=AD3=GTLfqa84B=%XQcqp#N2* zvmC#a$ynemJbcD4fyWh>l%$icAnIjMR7@_!EwBz2yu7}ZR^<@XPx2whsm?mWuWGbGf{M+hhI@*_TiYxjbvV4Yq`tx+~$3~^7z2=H9Tj+ zf?3O*n9D>}>AmAzgmRXojB&y2B$Z4id!)5QZ!D8$8QwFTKpIx6y7y+8D~)1As7=yK zFJ8Gai*P5Dv_{~X@TGw9tsKLLgx02id~)~TwT1JZeCYPq{*n8We*529|If8%lkWWq zf8f`c?^%s7+|;3uLZcA3AN_#g*@1qd(P362F`%@~GRmFHq4G-fcA8O+@s6dvZ9M_R zn=he21e{7sPv6Ng$$cv`rl8tyfI=hhr!8!0>ifd7n~kCj=0P%&R_lm_6c&Jxoh7i= zb-$jdRiAQH?er$Hs>b|(ES(8hkL$X|(`-&fMUOrr|Lbip@w3o772LZg+_)+1|D1PmK`~Z7M%e|c zb|KDs5K^0$zKv$HeVXv6VSZl7xG!}A3NRM>3YxsKQJcSD4Tivf)uGW3?%xMKyqVur zPW$}6d%z#5rFSBeD7P#(Jt^rk18qH0an{7}Sb5e@@ZW<^aC38W>3N)qUj|g#Y699$ zzTL|gx5Y4gPPV__S(SJ2k=*H{S6zh0k>RFb4gkz4Q#m&u_L@e0O|VU-`~vv!-gLrv z%$VNf_bUx^dF_HaLqaQ-fDmLE4-$#S$>~M9q6hOaP(FvKNK8&LPEXue!g#v=vs>_$N~}sn zyM$NDQ4n6P&e@)Ogvz2epj}8NB6c4h?-x%i*P~CLDRiRfNqQET^J|!>=8p}!-R(@n z?wMviKZVx3QQzY7^>d*R#{9wuw9Z8>b#D7P@r^2+3WLe)SP?h;8dj0 zcvIk5(^%DeSm|3qVup-{nwkxbDA&R+VXPW~7=wRIX7c}AZ>q|IS(rI@i{G?&QTIQH z>47f)3ArHI0aBGvjB;`bV*{z)5I-9j7+k!3SvVh1vU(p_t*@?0CvG$Kn0odObCbe( zrfE)QT4E#$53HT1D*{v|0~QJjjc?#?srR-wc4qU_vqtnEF+wco0+;z`+3w_=gGCN! z@{=$WXT8Gw@V=RkhKq(FpRw&8LrhI(IrEuePsCWY%k3TAPA*MbJ`xb?0VYmkmhA!h z*vc3MuRtulT)O21$O7^V+Ta67QfY&+vm!X$t`UtZ?Fz`5Fb$HE6YVKx+#i)*ffDmk zMwD4Iv-iQEIr3N=bCp5a#)W0x(|OmYyn}c_A~Jqs(2~%DEBCd5}t;TK|Bx24dyk+Pe^u zmQjvODWQE~vnEF>io${b7kkEy$nqYuF%>bJIcrxK@+%5oWJh9wk6406>BpD19MSZ} zaamO6_3MfpOZYOtD^V)ZkRZ-^y}b2TbDN{KdsFFs&CE3WmdvmVks8J8mjo6KKKJnY z;2z)cfJG^hc)2#Q$s6%*rd6~fODO?oNVXgt%DSdk#s0D;+lGpLT|yX71$V2P-lp#A zqcn9M2#FHSlMAbvf4?5E*A`>Xfe2v0?t}@vfx+<`H`G@qv|de1yG3AlpqGB-%B(H+ zw#n1SkMZ4`8mBlWdc1ar@o_cU)z?&*0iq)%Of}hC7`O))t@X>^MJi#qLTt(S5}(*@ zhgVwajZw>u;#NAg51sXC;h$m1CEM50D3N&EMh;#LHX)|tXBusk#xqQSOWz7J&xam* z@q_4vw}tRgA_9V;o_R2QAD*=8>gQZq8^%2KSqg5qL$&~V3x6ar^9N#QL8&6!J1{~xZijWizTgqj;Hs8(cRtItugGi)!g~> zk0H4=^2Ss314*1Erj7?)+nU#HVD?eS8L6ZH+gl{T0!l>%1>x~`5xbBrc4gEkc&9F(VPqG6=9~d^k0?uvyEu61^2+wXY?T#VQ{Q} zK$w;f3zd7TV7rV(aAN)8c$L`62eMZW9JBT9#}g+f{XFa_mMB0!#bFLpm?8YA84RE? z?-lM(Z9yD5zv60oC?mKj0j-0P{!{6cVA+UDM$CQCRvncnMxn)Qewv=`eNr3HCIY>_ zm<96$PQCBmsgnyzlW%MLn~oR}g$R?MEv_=ffpUS4NqQBuD%uSIp{elLtuAQ_I{cyKk-MC|>!gRXT}zc1T0Yj{@F=*Bdo7??&P#6eg2 zGg*u!QnQ?&*PbR5W?BsZCvakFIDxoTRP>LYY_4#R+tRKq(gr?G5?@vC`j zhUgDn*gQt@`LFYpPJL8%>@}9*?pxd09S2(a?>+Tw+CVA%<9{m>Zf7H>-|@{lAfSC@ z>#&~SHN@#z$}^dvu+LMO5hlPJJbUMcaQM|7PjS&?1ZVr&?hf7fSxNNX~qUFl*hvpL7 z!^CPh=mZ`AloKa(0N;i4H7tQJXg+=Y*n!=?03Ed4@Ax&V=C^Vz1Sdgf4w<25vQhy` z>t`%+d`*83kdsQDgu z)gX5mf99r~$hWFlBeblrzRZ*6gdCq4T;<-c%cY0!^`thxx%tcPU1nb9Y9bW);~qvW zgrvmt+x+*ODW1@YC*g~Mz37q7&)c&h$?MU;!lnQTR476N@jqpH?CkUUL}+%63nw$C zJJ5)|In;^q=_WwetTJkP*b96Tcz>)h zXXs3{f8ZfYDYeOpQwna~qQ3c>t8-O*rXN^=A@4=heM!`red zNb1ja?gD)S@F}pNGlx6RdO82f#%_B4DFWL;o;tqmPvywQ@-L1Hl+K+$kJ#qOriYj* zDfo@Kg1rpR36KEE$X`Htp+0z=OABN5Z1q=KYFBchZ(X|yuO`+@&eXTm-@DQFDc*ZS zrDVIX&9Fn{k-1YI;XdB7sCxF*nZUB}o!z|svbqZEAod;MHC8_N%lsf%dn2Tq{7<}E zmNO@--y^ke_?d6=q8os1#@C{Hez;@iqmd#h4uITSjiW3DFSlggnzO6i+yp-?_)ua# z#l4$XH*r8%nHIiiqFF9aQT5A*hi&b{q?2r(SG&r$pPu!7Z14L+Gxfy)!uY>mjeEw_ zvibrfsi3%6rTxUQWBELNT=s%W`~}cL7a>GCY_9^q1R;l2XB!m7xl6xP@&hAISZU%h z7fzF0XbA(u{M-&1hb{f(CCU2diwgAh9m&tGur+4JYO8G|7diR-%S7J7J%fCw_M9jO zax>6qF8K_7Cc5I`=;~}!h8P&kJbhzv=Ekl~3_RhbapBUK#)V0#v&zq-??qyV!PJ7xjXO~}8bgPa7Vtr`Wjk zecYHusSc&wf(#@AqAGCTMJ2)dJd_$@uN4R>eF8?|rE4AT?Gg*30G*W?D|kG~Ve(`- z%B6uzzf*fr4RZWHEDG|d=jZRW%_hF zLAIrVVxqCHL&A~V_=M3W=9WO{@pZA_vY~GxQ+AS)3h9=vdv|A_$@ns2Zs6usWYZUT z3JLqF1|JF=T~kvh_2&Ts_n4ngC?Ty(x0%k=a1Y83e4J-|+cJ=CId^Zey}7t}H$)WE z(n3}R5CGd7+d)e9l)+JDEf(<36AE2y2WJ)~K}M0=KeAGQmdnL*wt}=!nS<2vkY;O@ zqtC~2^@`1)q^9(8ICUx!lEUJGBAci`CHs!$p}2{Se6@Honk&>?RPcS6r=-#)0lGDI z8EB$Z2!c2J$gxv<^hi@y>?aS_bcRzV+n^VF$MqGZ9{sz}5&pmV*Mdv7O;@dI;+@wX zj{uZ?)%Q?Rtc0IIq@nSuMd~&~0E_zptmDh9h+ z+FfgJ<{!2F+S=Zj)Tkr5L%C0|O9$nd=QKA?%jqO9(<_NRK0d&!PJel zZ^v24nHG zxYgRZMJLeeSQ0Z$YHDilJVpuRwT*cgu}pE*42r)=Y$*`-AdNnx{D#!X&WI_iE-Ct|L~Bob@j6U4>g4zi3etC$%~S{&))UC+8gVeIsk+bC zH|gCORbm**oKOK#UDy2UUmP~V)3)^9DXXRyrzTgrVBM-|u0QEbET7*S3y+O|@}|&d zL7$9c)w{_Bv{Y&^LKsHu1&5d9F5IcBGX#UX2*#CAlCDXz5)MG%8_1|SGNmadu||Xs z1zbjGq{-kfD4Zn)KMzH?7k$=ZMr9lNDlv!;mJWjJ;-9KF8fhfJ>R@V+eXXKPyzZkM)nqjDfTA9s41!V+uKGbW%x!31{y&qdocpC z2`736r9_=gJtY1iS^1B+*Cfco@9QpHGJO`ToZDlbiFL4q^0MR3*|R%Cw`_ugE%xLH z1FXnWSu%0=@%RUg9rReoz!$0x24)CxEgVsv5T63E)4T=QpLEEs=mLYsktI4N{akbV zLEra!wHl*AjOeQsGVBV!b)UcblAOxXDdsMlUAqNKKmYyVUGao*5!6Luf4b+T9@T4y z8yIxq+j+$&S9y$jx(uGrn0PBfP2{d!E*>5V2E8I&{iaWovI+edd~<=no5}X%dHR|* z(eA}62Oly~&=vVruCw7O33mqRW~>;x)Wzk*dfzynM>hc8rDQ^_U#iU3<*-7nYDF{m zN6>#`k5<5zij_0FziYqnj~aYq2#UzLD`n;6mI4veN(xZSaop7-0d1qknLI@)dOgM0iqW`Z}{#)Pnz7n)R_ z-NsM4-F;X!daB$Dxh>Al5(p2mue^z@>s`InYq%vEv|N7SR5mZ2kCPw%px9rbXS5u zTGQu1ly*41FA|O5>t4Dxic|I(&Ffls$9Kr}j7)>FwmeE3klOP5fW~}PaZ!Gfy#0=ST{`@}pE$phOSb{21 zL@AbcnQ-JL!=Np8Tk*`bh0v5lh*%eMUyHtu76qEo8%3@`jDtnhGj za+>^Wpzgqdq>(_^Q}znbAPm0T1_wBKBjaFUgx^RH!q%cgC7=fCvBa_w~wZwGhMDSs<^ z@ba8!Z5x&&C1qqZg)}-9rN0|J0b(85?1WEND>#u1It8Kkp?9uXwj)3bkqAZ}pVD3^ z4bL0!JxN)L!a)RlVj59vty6N)^l!g zT6+3Ys5AGuQ@JEO5ph7MFvO+g+ZZgk<~Zn$F-kQU&-@oJyh|>>8u?kyztx**kauL0 zkKexw>I+`C?xAV9glg^J_uU4H%8ts0AC=Ga?It5tZJVR0&w9doX?PAhVWZ573iKQ~u+vcey!Pf?u4LraWxXjX+9Q#siYDyKrh=j&T-# z*A|?WIR?FubWMF5>M=@v5WFR^^>x-o>c)43(TTr~dg^8%`18@e8u(-UEld&LA&?i# z?%*$V*OZr*MxtandfD@aso~(koq=U1%EaVcTfG+p1d`f`^%e2MP_B{jX=O!u&dJ9OTOlq8AW=eK%Xo+H_FbX$kt@D`V7b6DQ2$-)7W>It2ij=_P455JxKcyZJC zlUW(eMAZFi2ki}mG=jgzH@E}+AL6N%voEhxnhU3JEr0ID-{)HH-fodww{?0KOBxwc zcj#sL0XB-6Sp^5yIq&^(e_`U2Pr{{`p!(zYxB1jD@?SI27lb17LKrf9)F^p)a&E=c zFPDeUxSpBWgGr3NPjnPp(z-1kIBUn(gmpftBmFo0obco!$&q$Na$A0qN%xH60Fn_W zfC-bt^-`co!t#JJQMjka+aCF-Ucw$d22T35T2Zv&bvE^jE3`!<;0cV(x_NP`Ix*pB zY2JZPY2ECkRI$$jc20~f-SBUXSIpP3QKSS~>FzEZ@FYi%9?kjc&nr88_%Jwo5B9HSOi_iz@x!MOZ5u_FIf*1r z;h`(D3}RW+MmVcKxf;7iJDfz|Hsw~S&Dtqb?z=5K#ZF|3pMLMa-o{S1DSfa6KTayB z$IqVKHmy6fi_3w^d|_he7rx5}Wq1rxd$oEbRR@)_dB?*?C?TMHPMta>VR*rkryLG< z0W)aM)x{I>4tV;h)^+7l0|p$kQM${g<*y;&Hlqn&TRtW1$!TN9eKA3=r4P_&M))W8*PyJ{e)A!wH5A&>2b4 zpeJaoSaQFN{KM$QKU|6v0Ue}sx{k7r4n;~03klxRO*l|voz$ZY2Or)Hr?e#I=j1fCptp93+tHr7iF})$tF49`j+ww$`9&AYpd2etwKH%Tw>Tj|K%p{gODc@d2{F6Kl8fxE9S_kf+3OT^|%p68yTIJL z%vjn#Ji zFe%bw`;;=5O@zxZP*pydEJa;VGQ7Fxu%m<2Jw1XyeEtAo*{eye0+R?cPH9wvCA-ST)CCDpDMq;?%vGEdT(s$&)vb1@s&YmZr3|}c*0DBfDhEGme zM+jl|bn?Id4hG*hKlT{YGby1a;wG5%?h5jT8?o%cht+W}7je91eMg3F(tGFSS5@3F zDdGp!E2k@H?y3vB8&?P0l)YHFV12t-cLt6awSWIMU|%yUD_I15r+lAm@6*`NeD?AV zVs;ypTrb4t!j>Y;QGbvJ10SvsOCXsy%H6-%KOF3#l81B(6}$+XVo%SjveQM6^Yf)x zK;JG!=_Xvbw(IdonrrZw4UZ9kx0|ZmC>p(i^P5;`3+QUy___2R-d#OKv<` zJu{FL^2{kaH&<6(vd;ic})=S}0=DbN15rLpzgmc6=c?CnJ6 zrn((~tXcPB)n}&@$;oW9ltPjn;NH5IqJ0w*%NzT%8tUu+bQ?T1jG_Xo!D;M~yV8C8 z_1)g!u$YA5(CP^jwFC z4jD-CsZz8_QqkJf!-4z^LNk3FZ4ei?4<)1^Mu_Z5kdCyS4WoWYRL=H2JNx`mowIZ& z;ucf9N|Ri-Qc5r&-IZGF^Od59ly5Sf2R+P*t6yvLQ>Y%;wSd4mz&WtUV!=A&3ln^H zZhRe3HLlk^k9Sv=$}G5gA#wdw-RQl0Whh^Tb(}y>lQlBP`=FX#q1D5P>ex|eGJ1-v zAW1T`sK~zb<`xwQ4Hh?4teY))$M`Q@Y|L6uaH}xV6ajJSo0b3^_=NgZcTTUW0zYhw zxb6#&M~rhi+kno5K%7VJ3ufdpsc>f=W6wkAjHYvi$hy#<>9Mg%gY zVU*lYZ$Dg{7I_W~gp6otVj}i?BFm(fPCRx@Y)TeqgnxTz+P{H=P?Iat^~D(N(>R)4 z?-!dDHpJV(5|D-^Xn5PP^dmy8)^+`QWfDIQ^(8mvn6;@Y$i=!y=T&$J;{@KJxs%g= z*H;UEI(BLa}br`{L)x`0}#!9pS zkT-{)y=}P_-H4ZK9fgsofCqkCdad52%YZH;@8tgsPwCrHQo3rnwg_g2+q*q|^ZK;{ z;23=h3Nv*C40NYLPl$$S8itbCeKp88i59i2%-^;^pG(S42mS4_Y*j-zfx*GO%Hz@! z=#!YkC_Uad@8!r~2COg6G0@kn-0Yco?V8=|8oOb)>~xfv^2()B7b~U3DgHJv z96eeMUsl@fFE<(;J+XlaWS*LO=d^(+w=s`DsXT^weV44jnhxu6v-wo?wFF4&j~tdA zvtg}x$%+-Spl`G}H&o2OlA}pg!nE#UTFY*`SAV~!oI7)7BJr3(j+*7|UOgN=kq%ff zbPj*fWyXvrYTwv&CPn#l;EBP{-5uAN>8-G}j7ALD z4U)t(3!`=0b6N>ZF2D>TH1ncEc?q_8TzuGm$WJ46C`dOnu^J(QF} zz?i3{{7YvbBmhqe>%RZH5qk#e#c90)mEgPuLA0rAC5=5zzTu~a9%^bGxr4k9ySQn~ zF3kar%tsn=%I14`ZjnXkry~O5(@WYQ>~Nq!>iZtK|2qn$G(g#UZ}05=fu3Y`G#H|b zC2NWKLqN5T52kx=bLY1TyxSuirG^+h*!}yra7y1D{<>7bHVr-C4t4rg%Wp?W1#(XW*xs}w|i8g z@&IM9nmJci_1v9(=@hTu`rdu({v4Qa!HU$!uV3!~vmrV-?vgJ}jM0=g zn3pCmUKljGO}T-dUPpSI7~h1G?`hW%N6Qr-|7Jm}HzN7<^XEeRsLBU{M{r(Y%!o?- z*MyD~KD2-4@UElOyS;w%=JA_1oyqf*Yn8-KW?xhQ9DR!VYimn0*hU>;1+?(%b+mRk zd5tF{5Gmpug+IXYR#uglM?4lQ2vHsinYl1;+ZCBxzUXXFk;^32BkLstm2-11v`u!5 z+JA>0IT6__#vei|FxI>&v%?&=Vet!fmxtO!-=f&#Bu4W8I(1RyWC{^Ih)jdJu8GO| z5)XSoz2yFd&q|doFna}eIc>AnUqntU4+c3UhND6g>)tl~{XJyX^)(dq>~h#u-rm-T z60X|Rrxw~NRCG=#S??eEB3D0P{CF(pzXlRc*s9WjQ4)Z-rL@dr{f^Qe#6J9-IctA7 z=@VL;#51k+1}rCivxH&U;&G!!ZEtJyFTCzCzBP&Ew?Pbc2rII9vzpIN$h{x_8}Pw* zZx*G)C9pd+n?qCOY@$Ug&f_CK5B5y)fMY|NF5@qEyKXZ5MUQx*J~yy_nKS72smN%< zp^A$J->K_UoS_umwR7i?h=>Sll_A}>30RAYJ~1OBZt~Ydea7OFl=JA30w`6S@_K@YelUY;PFV&b;+*ilS>iM6$LU92=`n-Mg@Z7|U1QnbEJED5YJDIe#ydSoAZGrI6RitUTuwTlRU>`9C* zoDRDB9tAM}Dt`LZ;D0jwp$x!CSC({@G+aBn@LMV#a$C_kaL-s72z2iHcCmrHf6#}& zA5#wPE@@n_FHruk|*cr@TApJ^Vprm_HmsrhO3W!o-s%@qa2A(7y`;(CShy9q-T z=N;+?t2$k2f2!r2M)he>K8Om$TJWA8_AT)c6?-qyREK%~MWP0>|S=m zoV0^fa@6vUu^PO(kF~WYFNZCddMn&qM?&aZDO)8M&KE^|a4Il6)(l{vB^f zEVB`>9_FONzw%+#zl_8R^h;EfNl6v4cR#erf^QI!CW5vR+#~{dRyn1m zzD3z*$&b|QqaB<_m$&ZqTG;Hb(P5wpmx@@)ldzxbvuQu>+MJ*FH^XlPl=q-)v(RC8 z54LS%$LY-Idh*5>Eo%D+KIGhR7l&m!a|>UYMQbycQwJ0$1{oEdYW(*i9il}NkO9A6 z|KE{syL*!B#ZaZGSSq4N^+QRq6~&$27NeRSRNE7|S;$;uLC=Y9tR)hZ6Me^03dx5L zD`T2Df%K4Dd8gPZN%!r0*yb;E`6QrrHWEj2L$pSW=!xtQQ*(*5pZh8@ttwLGYNyvH z_kG&4N$xj_JZYO~k=TV6ro3Fh!=EK@P@n3(>3pJ+!b$wQXZL%lsfB~<*5BBTc@q$U zgiUlzVVRO{1~*Ojm4kh#w#{chg{@Rb@O*_q!pmK3G4i>vpoh=*+pV;J$SiV+Ca!zG zZEkHI!FeEf5(K-_tSwnIOHF5<5dvx#W}U@+ghpGP96CriFZBbSe<^V|=Z@beYJHfVkjW`A2cyoiXB38k4^0Fhxib2~UMDFECbBE9?TG%u-@krUAeWbv)3%Pj zB_<`9bg4vpA}L-jjR=Vo38WGoDbww#(Tfb{J62=8EWwUSleNLSr*kVCJmLO$sJH zt!uBIf{ms)p&WRjy=C$eQViU%3^fmbJ`$-aIKYFmvnm_D+Z{xUk zP_MkkyS0FYGZ7RYU#ao#)X;};@EBR|6s=8Pl~dsX-4VvIbwTYhBYyJsiNM$>2t=jr z<<;QxCFRiBl16U37$iv-nvdghK*H-=nyAutsm`Lo@ zB|}Y2)7!`Am0?V|dCL~TMWe(9sOJvGZf+~}G&Fr@VrZCXlnBCxbU&Czg0v+r6Pp!$ z{=JjVNHKipa2^sZH)mB;!i=Z(ewm^5m6$FT1X04WN_H!Uf*i!|G-aTNV}*})7^QA0 zk3I1+pC_qB!;RjDM0NW^`fr#jZ2b{;B913qT*JN&yiFKk}GTC8^Q$RhV~o z9&3+rr(@eE>TD{ygHI>+9~6*y;X=`X*(qRURBT$~#`Ogs8|BxWcCUO0aTwZINf($+9IAbn@2ynVu0n=8HXzJUnK@+*L-5#ylGB(<#!-*-tqFqf_4k&K1p-@WT< zHEue95~)82y2|z0(qBou)J^S6iGM>EUe|tVX$nop)vnp%R7%e&_M5=TQoso`$;#@^ ze0kWxPGBDN#FMDYcsy2YEuimVTiB>!-MX`J5tu%QyzYAZ+dka31T_k)0lF^sO(K2m zk2kG|Nf`3d5&^L1rg*8TI@>(->Asxd7T_BQh#>du){To!*arR3ya0z-lDo_(ZtTSS zyko&~QCpy!kg@l47$`r~u6-G$kVtb}Er-ohrN3?2v`JM!AeYbN{JGtZwhduduO{QV z?>}_9-LM<6d|V&UV`WRT=Ggt(@#E4W|Gk^h5v`w0LC`s9PFvFvgCJ3AjgFC}rs1!6o(8%yKtc zLh8*V#!z72e49U=+!GTM0;f7cHRqv6kxqk5S^xA!jShIv3lf|*9V7EmT`}T5Wsh_l6guD!64@W3oi7< z3J}V0xWr0kf{nlHR?Zs%(ja66z*F&${iT`E-U|G-6bT|&R}eOX{CnK9!}CY*gs?zo zno~@8tTcIjTyFzarnrEQ9(fe{&7L{)-Px3^;3G$lJQ{dG$TIHSd5=sEw~?cv$5Dmt zfSZ<3O}DPHuk!3j4{AE%bE5IfiOcmmMxK?cdotqu*|Yhi#Z%8iD50X{3|823Lj_jG z6BpD_;mH3d#n}C)#w>=6Y`VBlSFZdzUU8m5A0DTC>~WwIp>7u&uF_3+{~d3)w-xcv zgIIH%LlnevPHY;{S9Xp8a0*Q+xg}(?! zv|;RRH>ung$0!(dr*&0{HwhVdwJf6Yk=>`SUoB8>bEbrCXhQ9+_J-ZJANE=vX*60w z`fR-2`ugTeny4@ysL}ayJ-20M{*7#2D$W_6lN~!2ha#dDi-Q{t2JR=P3)RD{BAh#K zL7_A)YSDeIfBDsF3kwVRw@;q2*&XJOl5P9lRUTU8N)dB;sr)pFy5BGK^!4+gf@!8> z7ar4eiVG(zuxv0`(W3U-H%rc;*kls37x`WoE(pc92T@{14EgxY!X*;bi7wjR#tYe7{*3H7D90Q+| z>IQK|{!H`=tC>{&e4r5?ISbqO>E5GQ%b^Zj2X-YUN_aMN@c1H$CE}I!w$x4=a+Nfb zp!Di^2BNMIBhV#XvILxu~4EV5@8dtJ|=*1cDrX)6Gw5vl`feaYg}Ot`6cbB&g3x>ac(+daM; zurk^mmH?T*d)hR!HE{t%h}p>}mvBKy+VxKq$r0D$yn+I^=#?X0L_aPl=qT#1jT^VJ z@QCHTkrcx9Z_DkD2bZaEhd~}e3$fVi%#ju=SZD-XxY$~6EmTl|^EJSkLN8qS9{G2$ ztI@AkzfOZP2(JAW6*AFkHR{n;xN)h4vH09N$swR1h2tIR|=|UEqBXt_w(l ztH^H9#ff-2(3w`xpSavmHRkdo*fgOXHO;QOmAbe#w|L{niQ%dr=1yKbsYCWZH+nZM z{+fHzwc9()dyN^W>_C#7&{EM|K#TBFKb{L7>$7N+h>%W-xVFi`YFyLtL zo=$XZuYEN0GPJ_bedTMKmLLAO{(6p`GXaf~`a~C$JLn-^&Oq23@!!6Eb80vQ}Cp@TlSYfipt8;Ty&dmlTn;(M~sFj24cw&@RF`l2;K~O zbp{DU+;rl(uDm2FBAyT}fS|yD>bQD)Ff|oEMo+J!WEUETrs{9L8>V9a;y8bPXB?9_ zeyl)LfTT^dc!omY2fe~lS~>w8|4-?|Du`|5=A67d7pvB+JVnNX_}N71cX0iQ{c1c$ zF{~d3Xk>Qxly_WP9oh<%t z{Hz0A2JS~Ii-IC>@>V+qx_hycN9L-82e}$eX)eNB(pAN$Pd3X3m$Oe!Q6tE@`Xqq|D*{6OV<1&aC#yz%RjMln&@6p&SSC>A`!vT9X`o#p@ zDT^BIl=P>6|AhKp#>4Oy#}*5rXo&sEhy|W7@VEI<9tZ`Pz6yUDlYs{r0t??g;kDsR zf?&Ycl^EjtVaYY&MS&>!(9EK=OPA>SYYy%Gm$o1rF}Wrw1{62=-U>v76t@O#J}}LV#kVPL=S^(;VLX_iqpUje<2bnb4;v zs$`tZamJqN$0KMoLT&^L29W z@lW4T6j75&Y|HNuQy`7n!7cyYioopMx!Mx^W3i@Q;?5B-#D;X-b$`p-`*D_-GYq0P z&astqntYX`&VLsq6k4CKk`(3TpSP@E|8t9qoupa0e2i=S{5jSVU2hKfsIkQU?8BBx zW&%BOqB4v^Ko2bz_18<#h>481Jel}6MKXt(YY)Wn-4l{aDdj{_%j@a%^$m?;2#hCE zaUV&;3r@8Q3Ri>jF7M8t?c96kofmpXZ{9q7GV&S$5a?>Z{y}U#%y4p`Q-Wt95g{;C zy54R_-h)5lVhO>1XJUFnhi>#Gynk-}09{?VoNEVdsOULq`1VIqi3`mXtiR~w}o}7n)(ekG0a(@t-&D>YpnB6{( z$h-|6a7KscoDHE9ff&mgDI^g0h7H+PVY_rtq4iY#R6KP%p`!3=Yf7-6<0l~F?W9jF z9i0_cAwz_iR#ZqRjBWCLv~B834ec<1kf4;U`<7m=g{>4>i6nSSC=WXx&hCCXu`!JH zNQhmjrlll!j0_q_xMwxVa^_e)!W-=hfHuZ${#xfa!WH;GW6WCG+RI+I*&<$`yeytq z=c@x=`RLPn{ttknzBORXVIH2jU%Srhs`|fw7dER(2gcn`>1sUZec<%S0~yW$ln^$D zVt*+Lr3pSLxYBFj_c2j!w#JlwiV|p3#r7&NCwYT~Z(hC11#H8WCGoPh2th)DKxa8O zbK{K&K0T*qIQ|6q0SclF#12%2UM^0%;{a6A)Z9W~0EaEi@K8Al1c`b^eZ21+XZPL{ zXo@`$%FmrA&JO;PrRmdBC+{yP|b)b1uCiP7|P*Z^6$S>n(U-1 zJA43-pvTLd@w;E5aSx}`$Va6^O@5bjNb4YB@?mD~rg?I@4FeN@ZRn5dXszLk1t5GY z4xNwLyEkmxHaU<8cHQjykF>dZnNY}8&*N!Pog)yHK5T#FX^CM^#1H7YPCk&us!d?u z2vxbqbw5)mu!$@_UWb|=2_c8+8By^A*??+-(w%;A0}Z!>;q9BBn7LGgqN1TBL7x06 zH(|qPWmH294i%bS+yc_dtgqmVMjq^H_A_U#R_O-Vfc}8{9De%fY3(UMWew?RKOb1$ zMJnF%YxnLIX+sRJ#JuR_OKV1?z2wITpiWju$b%oSWjVZ$h?x#ay z&ymx+Chv_Kwa`nD5_1ToqFCnO4nSWbK<>R}P3yU!n!I){Gnuz~@bv`ll2}}91@cdw zhzCnJ{RbOG7HY?xgqdI&aHS}xiYt|jW6`g$yKpN3g%^aAiRRCpxxAfRmrG(I5N)5> z5HVBYUTX&1-6=wc3Yvc9aqzd;)$_hk`^6 zd%Pg_c?Pa?cki}s(p!UNv%PaoKac(x8L)V@?&=BauD4!X)u*kw{jgHg`%#BOyYI&y z8%0LadYzMEr7J}Rb+Oi87h}~fluej#$TGSYl%AgM_@RVkr^&;qDf*FRCB|NuW1-Br zxbfRO08Cc3b|SqYz&dcrwdt<>w*0t}OIeH=3VuV3I|eMxLlYBH4sYZdvw_TEOeGEd zz1)^BxBR8y&_xo@4K&{ueHvEi=Pb3o7d)WJ z+BWXFj|-=sbCyG^CEaZR8_MMYw}mbeW^iK0WM8|vwi2-ii>MQt_Dy51Sgh@%W)yal z`WkQEyqWR-L4(l90HiyD=`hA58hxH%lD{;H5#FVZPgG4+6%5?I!fPF+m^J}ag21!& z8QTz&U-9lpdy6il#u9h;VbKysHqnBfV(ZLqN}ZO^PT6947}3K=(g#%=wTb8>2=(gS zw&_mMVtNV)TYz4w{C5z$@n7E7!|CUL4z*KjLk}3HNlQvka6M+nAjOLxw*+nvtOf zG%EC=+PNFe1%AfpX1V|0A#LUDe*;j4gGPgb1yju&U(N(NAyOjZb{={nq#jZ{6q=IF zi;{y6*j2{{^=)+bA9uyL;3b$ZLJ#iYk7XaJ9pGzo8`7yI#6aDD+yM=5@Yk=a37fg} zEM$joA#8x+I!joUdh< zRo(3yeBi6klk`67>SC=71fs#yX0PO)0KuJ6y8*fd-gc>gbp-`TsB+BT{q*Tf64!s) z+sMdJ!lv1NP3N&M*)!eakGf5CDBYaUhjIc1LP_nyPoc7^?D+FqZR4#q9Udp|4gB#t z+FR-${{Y0Fz9vDFY3-;>AcSlSdZJUOee00(=ikF5@Z4N;ggtdXoyPk-+tpAJ<{VWy zM5)|KR}Bdp+Sw(@Ux}oFhjz$bZ5g=mW9@0_4)F ziwEi@^FK_=thvz{i6oCwW?q#an|1{#Q+#|4?TMI2!nxSzpA@PFQG6Bl^BSez^2s4U zGNvGu)5l3f+P@oRqVL~t=@Vpny=!^m(J)N zql%6k?C|UNZ!4fV__6#a?pVRd^7$b;x2G-krxx*TeCti0b-b-QuWKg?HAXVzsgMPE zDHObC&g7w&5hM@vK`(ygq!pRc{Wj`F7)-9u%s;!XXmh=@%mjiOn+J8)KmP&Ah1NUs z(JKpcBn!a>%j&y478BH>onqer-$Qr#SH?;J{^htXAOJIR7x2u*{0StmP0$OvCb)ud z9+QL5`1ND@(&sy0nj@CQ2xW(F>#rAJt?xVj9KWx8$L=5?6R}={6YgvjCmKT%J^U1l z_#&V*NZxclN#V(36Wny0TwiDSKCm|e%oK$kEer?l!HlVe=e{>P3|z89_nx1BQonsK ze?*PTZnB`tZgPe)?r&t|d1p4A$0e}}kB4adVY5camZD5LM=|~Z)kN_k5v`bKbu7D?2`w(cpFLljS^$0|SaB%!c{4KLXkt0|f6XJP-;?)?RCk|Z+g{qqYMb!=dc4f5^zV<1t9S6fzO+ByH!0H!89nH9LO9h3{<9} zsMY}#6_oaGpZRKy^Q7sg4j$Y6&}J(DB_%&C2%`C(FH?uwrKH}7)V`20r{z?zjalg= zy=p1MLF3)xXDCD4i4B7n=bY19ZZZDqB3tLu+hS3LfRcgGHe9;tUE2@&Ls!)FtJG93 zl!j{#t9}IuOtKc5F!r;<8emSKLQPLuAflfbQiXF#yLy$yn9B<-kzhZa&^)sVh{pQly(6Q|V@hkunH_|9 zLaBhK02m;gym|mhEb1*aFvX(rX3gg}el;rcmU@bmB{OT)8?#H>fkvoGXey4jRVQ>d zTomn>u6z~|3SS1If5!b4)1#9gucRie{AYX3*RPSJZczl#XUoMDSWu-404eBvUxEGG z+jpY?yGR{QQWdP*>jza9cv7Rt4TNP76c>?pbM5m(uT_Qf`Q? zm2~tCx0vec_&WvngvLK^!3HNqpb0CiAx6C|(1?M2Wt+pP#K?SD8(#M})@Q zRy=jj?~i7a-vB_Trgt7EM=xBkz@nt3(h~tSvO?>`BZhT9eogljWIt2^0vBztDfmItKv-k$cQldfk~`}VK(S=nV$35h|i=tbiJd- zjImcdT(iQI2_#*&ZAPkHfJp{${6xXvkUzon-=>%&Ez-j5_`Xy8WCa5ESgElynihE# z3tWjG{N%dqIx(Ul1^~YsJXwe7BXzb48SYQ^mnDC;ysbKybg{)J!sO}lQHZHfqxrUX zj%+mY{5v*mAf*zTqtwk8N+WxjN>s>g%QxrC$;!!9eEm9hP4xk7n={@2f))6tUTAsO zsc?$5wdRBg8vmP?0#~?&_|^HX;XYVWz>;O=B6&kJ0Lf7+T=r?#$d(RDB#r{UQN zr@7Abh@$?xd9yY0%rbzqfY5>$1z+yoyBl?(N5e6Wt1JO44?a%lle4mJ%vgugj6fqC zwZ>j`S87sCjg=U*`zvGF;%ej4JMSv49o$_Pzscq_r$HbET* zMBG-?JMi_(mk@$>Pdg-c4hMZ=qoRViw1UlIaKYZkSTgd>>|L-b1&M_i3yQgQ8v2RT zHg237*?KiIw3l5kE2EWKwBj9Xq9=xLcaSkxn9=Va>8B!nKzWmZ0Ug^a1gFj|ZFj;9J zIkmM=Vc-Gj@sTlh0Pq47LW#qe`o`HWq=GdQFAQoprZ7Zh>+YID{p!g(5mmy~Z5O@S z%S)4%)qW-czrzLO9t#H4waPv$U03X*0*xYCGDAa;=tCt``aP7DLz#h*P*u@O_!4*- zpoon8=UIxs4B7{2t^jQcYC6euvBH#zM-MDhQ6WO+C7n1Si@Kri_wVYtrkp(#7L;L+ z(t00VJ#v0k*&VJ^o%Ckv{HXshB`TdYgfuyK zVsu*qUh1sSn=q17DRvxTRTx;aj*uw;P>h{7uZAWaG-Sx(m`ZX~FR`!fL?AAqF*~xCZ-#sc5!y>Om7=i_U?R*0rZYGu3n&DXeqzUxn(AtZGK-H5?yFV>BS3Jl zN<}gdpVezC{f!vUqwYOndn;#?M<1rjgue9C?Y5!h8f0-6Y+(j&Wchm-RC#Vmi6RI% z7GSw5i+zK>e_ty`ZN1)jPE-0vqIz-p+6%uQ4m;3SO)ZzZAt>C0;@_$L~}cBHNk zj&snB6JJe62A9`<%;{5oWsf>=NcWbS?Qo60fC5%<4v-<%DxMO8QGrGl3uhs|rp{{{ zzCzC?+JZh(`1Ar$f_nd0rpfJKZy>LyGX#-fjH$F!dnFWs{-N6Pcz>&-=(dPp#3x1l zJunVpgh{A{>1qW$O=%#0Rl&1X zY=W}|iae=t-#2|9nj? z)*12H%Q%JOe0*~Sxmrj`!a7^V$j@ca?N`4=URMGqTeoc*>As_8QlPZiyZDH(N7D!A z{fzD8f-2-5hXM3@MOteno`C9%PELG#jrD4vLs~?!Yz!uTl()B*OG>S$0>EFiqW}O9 zk>!~8W#W=JQrm{VAVB>F-~eYhSUO^bf|$0u@-*J$KF$!bM0s4diCBTH{~MCNk)2VL zMh8Fb!lD-Sm|G7t-rq<$uzMe-KLY(`7m1epzsr})z);W>d6yWi-B-Uf31i~Bw$v;) z84ET?l=$lak~11}L0?K##=Qi9iP~*>@(BoYPn3t9`OSPJW`1Jsy(;35@>RvQYf{QJ zp9UR~nJCzRCaEFMEyz#=lLTj&h=z>TN+QyA#ERbU>_W?b*3Ha4V+d~1n__+rOA_Gz zMeW5&(gg7m@|Sg$vIp$g#x$w}d^l1GG2N>r7nAcRuxI+-B_|(GY$>&qoqp?D)BDW* zPVdXxj}HuV|F%EkxciHe60M)we=}+MTySf#dgECk+nH}q7oK=IB#(6mkpS&ziH^~G z(hiMX(@}{{>SBSaNX39rSziz-I$SRh6cTw9oIvzMJrZ8+mc!_Vol{`R;-oR<7tF*y z)#jkC4gj`$_D3mS?>Q$}^~Jx+1D}k4)`VzHv{sZ>Fr2|*VYkmU4z@D6MPI$UH))v! zp*eJ@ebpK)+W4f5gKkQ=JK@BlLfD|Jm`}6`LQq7!KXn(4awzg4TjzNsX~Nz_jk9P1 zu>h(2@k6*(w6!&6S7z2`DHU`L`*-OeKv-x_FvR~TYM_7Nd6QMrN90oe0+23R{z2<% zz14d6R(zfQ7poE9(TFx{X4pKK4k8Mg<)ZvAdKJU*d0$#_l}Nz#+K{fzsT1!)Zo++*^o z1r!Mp%==I*^e}(WqWL^Yx#6bB(}N5QLQ(tO`w&IS5dJHK*QZN0B8Dz^bbJ)sI!?^Y z;VL+A&(vd&h2Cn@rcKQ24uIanrus=goYPdeT4ELw*jexh48k1x$J_p+*M}WZ|BM+U z+E^kE7=;Bantx+vdB-c=qqRkG1Q7M#%Jzb z2`D>7#6;4u{EIgmZO_e5-_=Pq!^oPbb1=&C<9g~QN|g$%IwkI`nV5Y1xERpAdR%?> zxsivt8$gpJ<&NK4l>av+_HdIz5~5iGzpu>alOa~ermc}ax@;YTHc3E#j+Zc5?TO@m z#_!WQ;D+pES=E60%kOvjHh~u2 zffIcE_H9=p7V?0HD<`;A@7sMW+%EEf8-UAJf{mn<6eRq>lG`YVpAj?O_sCp?5fDu4 zgq6dV`}j1ac|YMx=2I#Qi$)EtU{<7d}_bTM=aR~O4J zDg+qCWRG?3GKOJxr!-z7a?dTCCTSS-YN#(~X3 zsm?wn?N95+sP*WP>;2D|!}g2VU%qm4)yl$R&+3r}wQZt#alM+yvZd`FEKogk zDCkA?@el3%-U8&w5oy^x8GfH9%5msM9qgp6`}8^JmX3sGMgq11{0!~UhK6Q>)(6ni z=5ZHrfG?xnUuLNK^g10~Re5`x_hll<>q@>!J)fP>BCu_@ILl0%j|WK#@)jP-bhc+=D63N@ys#bqu4QG zr;7OOs6J{wsNT$9x@_sNonQO*Q~K+JX`0!fiP7jJ zZmc1!s;R14w_e0p>%pK=hlhZ;RgsIs76rgxw|vj6y@vuoytb5--JKG^&+h>{Cj7!v zt3Ys<+B>ZVpd7r%=be6^e7&iym-M#${`q-%_sWs#^7)VEyc4SoT2k7Zhb0}k&(AKP zfl0W_EiGUuXbB1QQ<<3VhZM{&FJD|G zyO~R;K6aA=xEfQ4LXAiGto~#t6O)i&ZzI!D`1oO2fFVJ5s8Q$%N-OqA_r`v?B5uX7 zL4(Bf7|KUX4!iKK`)SmW?+HcA3o8jvxeyCtQWl3ep$7_DK7(J!1;*R0^RER$$eVPC z%tGJLgYsF}W}t`A?HUZ-7joN0Sh{fMV^{uxfMdFZVd)uy9>yq(U!T-$U!IJX51xVf zhv<84HzD9@2|-8{+%i8sdhud1EnwifuwWPtN!25lS<-!9J9mqO(0}oK;gP@SHMV~L zGD-;x`*6wvy%!bejkF5@ozbdN#trlM2OR|$<{c>%R_5^ICPp2o5<7$WO|-C( zrm(vb$%hq=9jL;wwu?=UsJ3(@;aYy1EJ{hE0KMvRK(X ziP5j`7;>SIXVuw*YtqB2$JH;XoIBiQMK_`i@s$_J*w%ctZY$+1@oy5O?%BI07I7Gg4&!3lSeT-CXRB2^{_i`P`vt7%6_lk85REBGK4kN2fbFYJ(t<{_nGI994U{j z>Cv<22;G`dvtDh%YpVs-&3L^AyJ+nuy!(UVE;8O#Pt7;L&E)l=Lj!DfIT=FK7r^aC zYu`0KL6t~A<70RBA*1T0zT+KKEpBgiN}4}?{A{MA;tn0MqqdEPCiH6VU97@iSmxnj z=mQ{_@LPF!d3Vtzm(K@O`@i{|lE8(NZu1S}06x#)^^>&mhT1x*@nG zoS6vKhI9!sN=W*d#avEM0aC4Soo8E4f-^TxYf1ED@{?Zk=GpMffiH{#?ml~Wdwq>bSY4j_9LBWbU_W3*xiamezBl-I zFvd$_s{#42Y}igRtTu2(;;ydKFr|^}NbTavCBqS57%eFl_XW;pe8hH0(FjiZo;Lymlg(hDb8bX7Umj-Dyb5g-+?-ypUIdLaa!lfr( zhjuXj`S9w1sr5r{FkL2QV8LS6qr@y%X8Dxk$ah2o!bp)IyFVe}_x{n|cH*Cf($4PI zM=XP^j+Oq2u4_C~l3;s;8)C77aA()zJb50 zH_kPV9}3}F#G3OfO>EwIR!PdR%bCYl*RPS?okib7qE{mY~8xsYc0=v!T28pu}I_;u!14E zXCD0>7u6&bA$LV+A!cR*JItGRa>NUe%)&>bt-xACMzk^;<7T1_roaR)Hsbg76&0#H zJ~5D^YWts#Q1M!6e2-1Rhm$nFJ=Es0L*NoaPV})P4PmrV#mZ@>-4TNf&n1@h(}z@B z{YTnint8M^ny>;oi<{@JJMax$*ygLri)j{h)R&zb$TLB_cth%_wm`Ck#6m@(NbfbZ z%-4h^FB0pZcCET{<;RJ=FBVgJ%b-UD0FMKOkP;C14_zR+eeWA)ohl_sK~TTNkGWTBsAl#Fl8A` zds*3P`;Hw#rbh)(v*Q9>FFKg&=NAJF(L8|Zt^%PDmJ`Q!0e(pUm~RL6jco|#xS2~p zwS5co-m6PLHLVwJrI+ep;U2g^A`M)8#svD_Kqw(p%ipUd<8+?-sO;9KC0c3kx9UPg z5?1QDbJjR|0I!L`8}RVIhR5O-J2o!e)KzD&TQ`;ZZ6_tD4)kbf@N_zw%ORjjWMLIg z&ytC?M}RyJAO`#EUj;-V<76x%@aRuDn3T@t(CHjbPxo5rHsXEATyO7^4eQs#@4ER< z@vhr5_W+8*5)z!jyhcB%RVK77)TZx*TPp{ zG`Ki29Q-()4jg@kq3&yl&p7OQ*p%Gd!vEwe-Mo8uPWb9VDfA_KFKjW67Dq+&|m2eB_7OSgX%(t3gw8OwwuwZ5wFbMSfOw%KYTM+ zHt0DEt8TJ;6`>tNk#q(g!fgz^JgjOcdAEvB^+^H%gH z!JCaUagm)V=p6AJFmiD#Ia za`*1Ywxj;s5DS99tq{1x>YLxJ<#m<1WiZi`E}&OqwQA_d{fvHgGG?m8CR)(1Pjv2(rFq$gfxBp`&C*62Mz zHy2>x4SabEREMsHwdwT{k$s_n+aKHP;vkI6I;$HG4E#0WNY_L{1!+J;G%~i9@dA^a zRhDZnU+Jb@3uZ8qx+Tu&KB6j40F2$BUiGD$q`rq`1zQ@onm6tCr9+C=Mkq3Pf67{$uL5CF`RHy7!ph z(`v${sks7Ae)*zdJn0bhIEvN(F##cR7Iayy-+*c(A;Es%d|N%z(O` z>Mri&e_(H2<>1oR6Gk-E8&t5R)u+DaqU$@?+@2_#$DtsLkHd{>MG7$as?R%Fz&FIt z@9H48uj>Z*RW*V_4U9jal^q;EetiFn78E%1UR_x|+UmC!VI?Q+-jgR)q2FfN!X73P zVjMh-KRzOcaA3+xI;KON816Q(Bq1B%O0~gpcM9!sGsV1@so;nJK6->t5sqQeH`*riHGnAYftE zvRT?dZhb(9QTMgGLjE2+Ww7s)*i-cALVtj!E6&)E7vm$7e@t*oe8#ME2rU$!)Vy=~ zWcQ?LVSa{bzY6I8ZX)!T@^OFbTx5EnS#@b8DJq1Pf99?v1tZgfe)q}#l8N$6{wNvG9T|Bq z-|jwgwPm=;v)muL1@wRrbAx_hT0muU8Nu zP7`%?m9;4%`Pi7X8(fy;%wbA7=6w7}23;Mt?lrc**OblsKwD1Yfub=h%g-WS!ZGc( zesYP7F3D=JYBo_v@KXPRs4J7FUEiFO`&)bB*>&;e&jt-u`aDU!a7NOMhndgDaRCM( zBZBd`n)x92nj*FR!iTalh|>gdtvF(%Kjr>BD+1i_fB+_L-RD6L{*@#&Yo+rHa}q+01FS=-qe zg9{uzItQ)H+*enYq~A0!$vcpKzH!WEJ_d!=*BOQ|Mvi90vrAQ7aC~$mcWonHB6$mi zqvZUgYmXi+f8V~R1ouja4vbDaRSsx?ZhX(fdFP<}J**PhBHl0&F1&kd1-RPNNYoxI*51y;A_UU z&#QvgS{^I@XY_mfc^})|{Kt0t)AF5*XN(`cL)Ta2NA2+%AlHZkxWx1KIY-N8n%Kra z5_2=@b0F|h*tDz{VYNucDY`1m+*!Vz$`Ba@!SvIQ$y?@!=oPTFiFv$T_;4)-Ow<^v z+b$l*R2yW0v*kK_w(TnKvD%1;5iq79wWH#q=OZ5vWgCWDJ=N@#H%oT+8 zLQB$frsGmpHjsSFBX_{87Lov;BW&?WItMnbgiz4s5Auv_bpNW9Xy_yO3len(?XJ%W z<tIC)YlRo(u7~pv^exN&59`ErA5r$ z#14G;R~(+Tx&7(T0IdEhpMsbQP_qAU3&JI~99_Tl z?!&|ktc%AXzKuRF|0=twJ*m+hb037(=<3!#9~2nr?^SO}TFvGAd#r+Vq+A&5 z7~pF+Vvn~-I!K!QuAh+~m?*gl#UDN`faurS-$Awckr~}!DMSC2b{0%s7Q`u50yK#8 z`yFpIL$J?-VOoy<`3s53SJv~+zWaZ1luGLAM>5o5MSdW|LH{(l7Pe z?nBBe@$YKiy?f)XEk+h>Ro;o7bALU3$ZCSTvLa~CoQ8Nw+I|2xCB1=2nq6cb z>LJ>+{dZP#YiUfyKl0y_lA@wI|B1_R!ep+LW&30`rqmOlh{Qk=#CQ-)VpN;R=CDrrF|kdgMmEVSt0I;7J}hW#q7%lfS!PQB?EIGK zbDLpmH7{ONHxD-ts^0^kCxFX*7B!Y~bx!Eqt(!U&JEnzuH@=+=aNYfEbg-Vs^WCEq zN8G(`mZg5rS31munOZ^^HWU$0r%$?fPOvE}J9v~AFPg*gLGrD#L-+Fa$YzPFL6Tu3 zD}(+U=G@($srfdJInErRUlWfB%?Dpjy#)Lt=KsXkwLCku5X6Qzfj{JL7;0mq*1eU6 zMMTk=#|x(R@a1m5{qXHpX7x4$Tl-hNqDN8EzWyiqNAvsud?oNEOnLlxd;H@5&aEbB z6GIog&oKf47gZ27E#{d|PuN{h9_$#LGY;CSNGz!FR@=J7~9Je>oosx$CGEG^$SvkA+#rq|V_U&J${JX=w z6?cDSv*NQ4lDJh=Iy{u`*PCoiyJqz_oAm)i5!NCuUE&buWs!{i$LC3zOFRngUX3zf zCQAdfr>dIahYipoi?-?mhVRv#4>yOXDJG?0j7s}9tJm;SR?g@%op{@WFT%#R(r=%M3qiVtDie=mBBT7sFcSdNX=b#Zcv zaP0WJ6#BZ*A4qf>Iy#LBnJA!L^LiX6{075bKMD7Y`}cLvTq`>D|B-a*7e=*ltaF3L zTr846^_{W{Q`a@SwDePJIF&E~q)dchO_Aw!N3ly!4Z0Wti1nRAyWnp{i{|yS+vRL0 z2Zwoi$|vW{o-HQp-Y+iHKW|CBZ5sOWWoKU#i*0VIAN*Q6viw%MAOhV=-hAJ!S{+P_ zj3~r>+5R9(06^iSyO$^4S!MwqOeJ=-eY5V8X~&I=IcselZUAJ92l^&P*RP3aIZgU< zTrq|g7+2=3{5MjoY*J%_EL|HN)#mbr>w&nCIBm9 zrb6BkKQTN~_7)Vqxx3SU&$vqwFO!mz>a1=3w*1z`|I~c4{#dO+gI!}!dY*)?_gDQ$ zCKjv5hl@y9+@l+S09@!HwqJy7ghLIZx18xHK!l^fbYu(71Z~o5hAzGCq|*@bWrn=- zWR=73E8+1DIn@LDwkY6;->^u)z~}^4W5G23#Dw4_$2WnR*_r0YPPS))EsF93 z52U2x8LSVr?b&MxlrGJ>uK1GSS9L0Fm(;UAejEurw@wJf03!o#zPp;$vCI^RLLeAQ z(wo_VRlW9}T>*y)Z}KxsK8zP#1KWClm1MmS1*CwsadD4wU@{AI6%wX69d~w75AINb?8tsiWgGP-0jM3o@W@$ig z(&Cb=N-CE#f9GP5qT#meKIac5jMT3pP&rR$f0gLU1-0i5`QD?@g`$EvRZF{F>vWml z3iTHM;jZVB4gzIU>3J-^R*Lv5Bs~0KOrT9p^Mh{t_UjG#r@XIndRkUVqWOxG+{D3T zBu+igtxtzf4n5sF=`*yIg+PV$6vhaQD{45m2TAUul z*O7I?b7nWd#70ZV{NwtVV}PfI2|!#Wkj9z-up@uEs?nRMB)w9^2nopPUM!K<5OCB z_s_q6I}z#v6`v$jViN$vF6Sm^wR<+J`BVHREo_BwCpC%oQaMBVsjTL#3shsaJM&`X zb!_ec-wKmq!mGG6W~H4-M2V~8@@G=~2u+2uJq0s3fM*GqP)JsPuD3f3;!xJa9;-9P z5B;{qq~|@?!L~LHW;b{!I58CqZu-XMfu1SC5s8V}C>V3XGPUUkyK1lM4YEviF1ju5 zo{*;^UZU1})WC}1Q?bWoZxc4uySljr6LyZ-Gy9xBb@NPo+z6bLFE3JoDK{=ZP9$l) zd*gi8GhydaitEQsL4ZSKO_lh}6E*jNb%9Jl`fs@B5YA_p7(1dCx!o%#k#9U>=1lt! zFEBE`ZJuH^X+*e)fyY*P9Tsk=d6Q|OS*{KHe5p$EjqqfD%3%5*B)qV(dU-zj;+{In z8uPIZZ`+AUJvAr}F6A>89=q!OM zpN1@c9PqRzvzb9s>s94-yeW<#RurM%rh2~Q*d0U8KKkqKWvhtGFa-!J#vo4_ocplp zi1;`|S%q9?ja$gd+D0Xi55wboY}Z9NG;UB0*6M^wHcoE46V`*DWtuSLvg)Rd8*iYS zmZ9W{%1giZ=&olx>q@Iyady7*3NQc5BkL(@9#nS1fj;dPK~E-raGhCvH*(*oUD`bp zWs!+yN#RJO?b~%}jfZ=9bYc)v(s2Z*FM~`2#c>TGQx;Kx z`9Sg5TQzX*oH?QRozNkGbT|C<(bFo0dULt&Dj?%95{}N*^kp(|hwqLBn~81K`i8dQ zWsi^h>63csC1Z95B*QhIF-K)c_C)(<6pv-s%~$lJ@sJz|e@VR5sQqFd?j45*z@W+H zEjrl9ifEyO3*Wo&mJ091y=3q2>X|nJw3--Iyvr$_V|Zgi$eKM%-<$M$Bu$_ARuipA z6tV+JKrg^rh%$y7AToac-dgK6OC1>-y`LE~8n5RC-OssRoBVG^y;j;m8?#(rkKfsX zPZxOVW2uDUckjZ$)3`pO_DAF6^P?>x=lJn1!Z;QpGuaG1I4d;t`nKJCBfBx&HK2LM zi0WV|Fk-*ML=qt&UlLuY*ocBA02&SS(q(Im2=aK?@#DIR6FJgTu+rY2e4{t-*wd`f_pGpX7Ar}5q4PK3g*0ABJ?--bJ zb#)^!WgoZ2QrQGZ1%qvC*hUB=zsO3MM3=wEk#69LyLYD5w1 z=l9cMSqq~sU1T~zK!*;&1kO%WxLw!F-XOZ51wIaP;EH#1d`WuxHw!xEsM zgz{g@-%V%`f;gM7nUj;GcWK9NADK}LJ#K)bH)R2Vw0ga7gn`9T^P1_}H(CK7!psK~ zV*}=c70DB|I;_zx3csk`^O5Y0TjDpmuxOL%{Z?}o5sBXap&rXu6~7+upc44=MLrt8 zcI3&moM5m429Gs^Lv2@@kF=PU+T46glU`~ouG)nt_T04bUzq6lAsO9Ip7mKzT3q4l zxq5qV0!Khz;p#B*CdODPOtXn-!I*s)(ws#+X@!R#6fZGY3Jy3T(7U?&p{&fTti}jB z_Fua{(#{SUuJPj2oj_J|Ze&hQYJo8riONUk-ua6cJ9O+gY~RpE$$7<1Y(a17FvI`_ z&MipA#I~bQYf6{pe%NhgR%&PSX=;Wq%7;(^&1~^Pt>?uuSEgmcPgf`?wJHKn-dcnZ zXT^s@F-M!2DptLH(y;k*EQ!?4-Tif6$}ONbQuq*8*Mf6(d&lidNZ52L`A=(zrQ(!O z8pOC^7{^y|jyE}p+%*~0fUh}j*<%^d8p_om2ZzRTUy(Iz%NohltV4%HpPibkYqmC^ zP>-8yVzqc*-*!YTI6yYgnq<9ZdGYNPJMTB`;L(p}hBu}+`+~aO4dvkNKPQtu*Yh0R z;G0w5{%}ocSccDV6GcT+$My|2&N zY4Ag2iw`BANF!8SCm+0mW?h6U+n+C4y!bR5z>S~EUM^ArH*f(|lWp1Sy6Aqhgn`MM z0O9eukS*9uQa~I2nC=pjXSfzKCZb?wT3?qrO=9_;mK{90%djYQ)XhN&=ETj_Tg;+Zux>+WmN7BIb%+-M8msGaa)$g`r`5ru!CTW8hk4N z<5~}%xh&ACs=9?Y0o7gH)SV1ApmQ}iA1i+W)>AiN+)&;qG2YfWes9Y*`sjPnf8G&E zVErwWPi#5}vw{QXMqIyk&DGQM`vcYM?y3I%`FcIwE%o2_dvTa45o!-o@|M;i)mv$? z?ycCd=&I*a6x} zv1L=h64q#2^LlZ3MfLS;Jd6XveNW>kmiX%jU4U*R6o1~f%wstYslf-Mw&*OZSgqaD z$>hb{N$+3vcZ}5Ov4^jof(V*P8Bk;j@na!5x5=^V|F+A+Vqn~~H**Vr=ml*bXY_oj z-j|4gISX^#HQ^{3Z5RxsL#4az%DarTG{Gq3tZ);Xk87%|1d4@l!1?%i5WVRRd$auo zjbd5T%G)!<`HiYIl#k}vBIG};AyrNvnr;y}0@$#8tquh_UH8mSMtHI+;k(wifB)&& z#DLbVRrTUu4XbDe9O5104svb86bb#=vs({BZ4_x<)VOPC5`abAFxIaT$5@ z>K(mzixb0n#3`*wJhX37L(F+Q8M-#LJ4BM_in{c0JftseT9oIH)BV%)YS`Ew^a6*R$cW zBH#aZm@tG+6OXXQZD)FVibj~qT%myRLn{)R=>brsO21zHEIV)wR6AKAR%S_3q!d+V zNNnfsL4=mk_Wx+<3}*oR$7aZat=mSu(uqi*2C-jDVjSX8FVA~&sFZ@_&hL`x+8_08 zn*zAu*_uijhEezCCINQtsrS@y56)0fb&9SyR3c20 zn9TZ}A=~T1)dnCGngE~b{lajAGxWqKV6=0|bkF^gu@u8iRs;GxEcm*cYJ(hH#?H#!2{lg^WkK+Y^s7%*M*~h; zA6$QHGi8B5pqPQT&2kvIM4Y6{^7cFebJH33!)9RZMZE#aR~qhl*ec2j=OUUTiTcC1JpYl^Y@togROoWzh9^YJG-HWQn0{BH$1@xtPJDX$~?f zSR8l`#jN4|jGt5b_3u9hEDm;+y~`8mE&%s?KPH~0^`MXu2}-f|Wf&Xs?P-#RoNsaO zZwO^12WBq~J?19?r+qa4Z^BaxHhgAQXV8(gZ_Yitux>$*rF2M6Kgu4KE@mnUon?*Z zk>Q|4yoNMH79MTC-5b86sdkfpYijh`jQTP-DR#l6Bd!;qfFM6j7d%@8oOr?rISas? zEm=mVV@FS5CNFJ0C@~}hr{GQ|mR{E}{}cnfygHF3*|D$Z2mNeA<8kA=h3EKXh3+#n z-!-bLzHC1s{kPT#&9=XC$E*KanM-V#`8<0#mt9D~`0KHhh?h~s2^kXWgET-E;tb6C z)UvsA?{*4$ouggLM^Rs(Z%m<~emgFCtd_8*qM}BqkLfnybU|p$TJ4?{t7X@S&4^W* z7pC}}(J+cCM*6W32f`T30GHwo_6)b_KOf}e^bWMFZR`&sCk#Q5_R&|HAc!eQ47vP}2)@83BG z%UCci|*+|JJPqS-dfkhfV=0iy&*+P4Mc~=ILL{v zwf^ttJtkdf1m8~cUB~Xm+}d8<8{%UlO7FC^H`nV$ko3f#mxdB4_L(Lw9xXe(4ba00 zLbF%hOV2L2sW!AT9XsIJh09NuQ9{W=5$c8P+m@Z-`;4I_0&m+}sKpZz@2In97uifS za4Xz-sHxdd3+Jkl6Ch_p6SGf zdM*FiyWuqkMqeW5e}MS`XuuH>aUY20giDU!cBr@&G_LvLH+n4uBNk*1Vg$!)DLgZ4 z98XcMhq}6$?EIQ)p`r2WrqR_YO+CA9($vsUj2@ls6?zVScza40zU*Jl)PUtTmKAvD z177*ORb~aLs*%yrRw@xncw{bK>_7kJ3=lWe6ih1-o#t+_$;Z*``|9duJ#6j`R~xJW zlEG+FSw?a*@9xO_*%R&q!K^;#8~Io4`$I55QeiKCr4ZU%F$tOs)02uk-&>s7)y9|C z-{D;zEiL6^gVTvbTydJ-Gb%bd^J=$g1QhDzubAS5msv025>wWH#e}rc=7sm~clj|V z>wMkEE@!new#+G{Y=Ku5RsI`8z_h}YwKyt?7y^#!K8)y}FKsk&;xh}cJtDNHu^#q( zje#wx=I`Kq*o*VX5Yc}KgMe^iY1eRgPxrife@z; z_*t+Ht`>a?_SoeoIEapH^+V>u;~%qy_a{qX=`(lv)Z0h$k#AILnLmtCKH{x;=Y;GUkIqr=sjo=-W3+K~!N-@BQP&Ss$-Uu~Ps zUKZJMAZE0W9#w>TmJ!+R|Lw6Y7l{l93q!~av~AaRPG^HzBm81-qH?J2zLR2#RNYBM zpXyI2@qlsgY>#AstAK&@J6;}u`|80POD)^0g~a!v&{S}{V1&rlOLOzJaG+1rK_xRv z*c^`@Ilc4tm{afAx3W*fMWOtFLLIn%J-|+>0%Td7{s@}F%jbM9z|AE111K!j`}FZ8 z6CEA(&Z<$M8c<>wMeeK_wSu{Y5M=R;*%q^kl4pO1zjFm0p-=IPL(|+v@m>))fC`0- zXgt!WE2LRjN(9oKQBe*1kpw10X_0$HA0t3brv&uz{ruN|ug^VHX)@u1E}{@xrToR; z40_mxUt02^1scTlG6h+KgwR=ISHkO0*_Uzb?BV8 zWlhoI09ZFQ-NK}su?y7ozCB7JFexKl!KiWgnApvxk?vpIAio)uBT;Emy3qeD%-fPt zS=}P?kd_LMA6Wym?bhJ9GVkI#iJu!K1DRrNdGLts6yoDYv9BnS!x z2~oCY(FO8|pPrrBaN0j@T>bA@!rce@i`n){2MIAdKu?7m56gQp{doKQ+=U=OviJBu zkLa{z`&PXO(d29qSqed>MMibwyAWWPV}Uig#iXa-anNr^(>%noiyqTxx)z^K&Z*4$ z<<0}%!>}zHL|ieF6{e~FTVy29aP$kL2%XU-HL@6p)28of6c4OiS4e;0#+9coUfdZT z0q0Lh@PK7Z-Uo*pINM!3eOmf%%PaMt0|WmhUZhW%2;E2wD-<^<&%m?PIh7PBEb#Sx zvbmeX+mT-~Q*!lR1ozw3u)7MhHwp8Xd@GHic2-w)2gnyjo~)qb1srv27btFr0E4|+ z8~Rm$*?<3`Ggeo!y7ZCG^l*c(_+>zw7HC%Aa~oHyXZgb4#v3RmU1StOk>8%h3l!V2 zxzllBZY1^-D;D|2db>@8%}7_FJbNx(w>z`=0ZKzSLO^yj=L=9FfjHbzAHh?QbbqIy;gVu2wbk0G&KoLHSyy&0hm0r{B-{r~ zIIIIdrG;r$=!%%lJt<@Eiwo+I6D2nW*RA*VjW)-fpHvCG8P&|&7Im4<-HaNBR48jl zwf1#0jTV1sc|6oE3CBr0%Oq zy<~j1*T?USd>vCc7T>TKpZ@oOQ{?2Kj>lf5<-tR>&7x2r3B!PyVG1+MukRmsq5Q3w zn>_1*KA?kB(D9>3F{T?-@Rd*+|G2gN$dREUItj6*)1VtiKO*~^PeonR?&)qlREAO& z12aJJ&`V|f2jW=u$dHZgB(Q}=sq0oes~ty9*gMF>jK5PXks`hgpv00#OJP0xIb;_Y zN3P@p!FG)Le)#;^2DnX3k5ED6m~mkxQ7!pMGdlLHHOZT6RT3GT?f)zodY{Nm@wZ3h z{^oWO259oYQ1f6M61CLT4ps@3M4g?<%fGtc`B)5mSX*25xsTzoUZd+)`|LV={_?-h zj$auVFxVuf;_Tl^VmR&hC-_y$R+tY`G%;SSw#O7yw_HjtA^FF0EAiuWZ zp|KW47A4b5k)*<*(Q2R~djR>5CrdOQENB#I{b&&Bws?^RSd*vO_PITHx6q}Q9v}NW z?!twox1=b(+M!>+=W|Q08LmG(z4J8hhuzfbwCLs{;+qXhv}}!~lAr?1nDR+W`R0jO zkkQVpBUl3-$;=6SQJh^OF4VsbCqcj%sZtPUB-$0%)Ae5|j@*1x7`k$dB=1G8q33_Hf|9@rv!)EZ&g!&n|f zHBEfBFY|tOR)ruZBLZjV?GvZ}6wwXy1>@}vz(`A;-g4vA625=yF@tP`4b<_m#e3akCbB4F$}|nSI{A zP4=2PL4fgWK$>%L$rU;J4IBqk28#ezatWg;ltM&&FW`iQON2}#(QCpOG1+Gz@eFI{DX`r z-k;xm2YO`1tb?P5j_KL2$s@&rlVDzexep;(Z1Q-CvZ*~`{04fDM-CsGSpCxA+qYeK z=So6?_tQ(lZGuh0cHqE!XBc%!28BHIlmg?MRa?zx8-v4V?b>A(WJ#?1x-n&C;0}|3S8+~e^oBg&8l{yWjTXXyCQ@2p7>_?l%4uNl1#vZkX zTFi%;J3Hj$*rWT#9#u4|s_n{T7$%XDfizF}hQdkcR@Z3FXeNV@x_S2~?(?GGe zVI4+BetPIRrcPoacH7x*j8;aY%V7EAosV>S!7Oj1flrc1T z%?bsN51RB!XMks!oNcT*KhAjj;iJ>XXi2#QE$`;6-Wa0GJot4#=MkME#OMWevn*Yw zhL=gpFLd-GFvH{i&zLeakmf)8J%K4p!`b1_E&cWSQrACy8b-IMYO7!GCP5~X%qk;) z+05+gdu58*B__DG$Hrc{bZJn+co>^YCZxT0=2A9G@_W`I&aemxsze2A>(qk*CmF)$ z1=ap`%e;mUxL`aC{U1GhJJkNwPSzJ89NduIO!;QlOI4Iju%LPJ+)o&RY7HAE9zC`v zDr%OCRWzp7qb+Nc2{+jAQh)m@SuHtMcx>xX|7Q*PHjjESlnaB%wP8vF z>oFo65E?2cGx2DE{w`k{{@9%ZNOogB(z|kETV5_W>DoSb_Wms)a;F6ieE+u1 z@c75G<@5k_&pPkoH1jFvN4TDLht6IykeNH=F~{SNx89x+wt2HoW!HHM{taWubPDzb z)wi1Tts2p|Zj9a#i zZgfdV=fKIHh1c>KweT^&q%^UL%9=EdujFMh=%UTqsM@5)o1Q4<{E5(1^lhmB zr+TXSh52?ml`j|RFB-5pdBM7{kMq(uwqn#goOwKGRz|z$IB6k+Rlh!UzSH)x`yFW> zm9%4?pIglNE{j}kJ4Wm44fMN^nJq47|NOHv z)A>&O4$g-0?tQW_PY`|@JS*F&(|(wZG2RY$%G}wf|Bv(4xzEdNrkQyKtL-~FbW`{9 zji;WBST=Qlrftb3&s~}i4vL7`*SDXHwIIzd9N59gs6O?LcJB2Z#*x(67hh-wKcSDf zB~x9J!5Z6jKhFEwe*bQJEjFx^ZrzTWgF8hO!pp+B{{}dycTzskxtQX9@NQCv-$9=k zab@XOygX8RB>yt?UbblT4sJ127sbwsjqZ0 z2LRmqGhV;k08*C&p4)c;`O*mT=E_}BLKX=H)@k4o2gCuwH_ z!$E~r3cabIk~&`YsC2Q@qH9Hfp5njDAaKRgc^<8^2zx|E5}irwO^UyJUcsVTfRUyi z`=YC|#4M<>d9lXzXl=uFv!b{OqA>Bju0v8CpKm_y(96?qp^v{$IOgc^ZA}ch9)Y$h zx_qA_iMQIV8-H9(@zC`)8ms{Ui!s<~Sj5Kz-JZ7X*(B)7bH%1C#hj!)rbyYcjLNmd^pZ&~Dd{p zV&8sk{DxjT+iBQ0JHY{U7QR;z#S)x7o5_=39?AVtQ?nmXHOKf6yyacHcdvCe{8ZEb zGxsWly2}1%COKD?hzvVQ$>iyYKw8tMXQr~!;qYLT_|=9R(WVd*m=E^vHqunnt! z(ZUU^VU=Z98*MtwFnt!5-FjEJ&W9@x8hIx@Lyw14G`(`;(S46+3qlL#GekrA-x;P* zOD4P;6chHZCeh=;CG}6OEvfngYk%fXy5@1j&cdam&%evfi+}y9$gTz*UY~9Gvr#XP zd)m3ZI^7+io(k9<|H@^wzOSDI9|I{aCU?&Oi${}f`tdj2kl1@qAFn%Y&yNcveHC^Y zw_94V>5ys>L23TD=G((&b>*rXOoWh3>n?0Ix{F4BR`Ni4OiSkt+W4mfkzxBZ_fZMB zu*d`96Q5pjubJDC;N|>Ipskg+=jb_D_ukHZ{*8>m!KGd@0TJib$X!_^t{STFB1Obi{%eBAtQOl26(hE4#E#|lgpu;(#4L3>GPH+j6W`aBWP9T$r6W2(+{c^fw#TR z8)a?XyPZ6oDJrU}`e4~G7cjzDX*5d(ejM1EhqK*a4OB@d0;|Y0+hSv_ymrq=1K|ji zk5!vuu6(hk@)@r3I9*AY)kPb6u=sG^?4U#@*vyv2Vnb0-SQtzPuDvO}r+JQu7)9;L zT9;McNoR5f4KOp?p`N-fEFEaUx|s}ud4_{PzR-H{ur#%`XN^AuTP*$e58W|iA1m?) zHMbsfPP;`9W;r+sySyA`Io0NXCbCx^l4&0e1lpG3;dp4Q*TwAi`o3+{ik7!Y*3_KH zzMXm?%R;)LoS+_BaP?Z#S9$IGj{Vgk@bly7lT+S(3K{M0EWuyL&Qp7njf^en#KO(< z8}-o$!gy!p&C)7h144eJd}IS|OkDk3%w_@Zge-07{W&cu=EeODp&tyV{jN9bh}qF` zeG7xk))u;bz4%{KdMY#a8G}!HwM5k-+#ML6Z5vv3+(6$qf=cJXK`Q6!owWnkRZLOR z7*?TIbLHlx&PD%zRy$E&{q*}9SvCT9_V3$Q;>qvQdeyp}`=1Z}a{3MYGiF2EXgvi{ zJ@QvY>*a=-e*MtAEY`hb5CPHOp(z;g9x- zbk50_JioFt@`H8V?-YMU8)0E1 z{{9&)Ua0?>UQO$mcpPc#Ycy_=h->uXQG zkI6ASF?E1nc|BWeYqROoee`!N=2`zQeR=#gYUz7buh00^ncFH%=5*>3VQoFXfqXhs zFpQB2Lu1D`F<;$wZ}+U1D~DQtQ" ] @@ -193,7 +199,7 @@ } ], "source": [ - "n = 14\n", + "n = 15\n", "p = 3 / n\n", "\n", "seed = 1\n", @@ -202,21 +208,20 @@ " seed += 1\n", " G = nx.gnp_random_graph(n, p, seed=seed)\n", "\n", - "pos = nx.spring_layout(G)\n", - "nx.draw(G, pos=pos, with_labels=False)\n", - "plt.show()" + "pos = nx.kamada_kawai_layout(G)\n", + "nx.draw(G, pos=pos, with_labels=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "If we have a reasonable upper bound on the number of colors necessary, we can set it using the optional argument `Kmax`. Otherwise, the default for the model is `Kmax=10`." + "If we have a reasonable upper bound on the number of colors necessary, we can set it using the optional argument `K`. Otherwise, the default for the model is `K=10`." ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -228,7 +233,7 @@ }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "

" ] @@ -238,36 +243,29 @@ } ], "source": [ - "Kmax = 4\n", - "m = graph_coloring(G, Kmax)\n", + "K = 4\n", + "m = graph_coloring(G, K)\n", "print(f\"The chromatic number of G is: {int(m.number_used_colors())}\")\n", - "\n", - "# Plot the graph with the coloring\n", - "tab20 = plt.get_cmap(\"tab20\")\n", - "colors = [tab20(i) for i in range(0, 20, 4)]\n", - "coloring = get_coloring(m)\n", - "nx.draw(\n", - " G, pos=pos, with_labels=False, node_color=[colors[coloring[i]] for i in G.nodes]\n", - ")" + "nx.draw(G, pos=pos, with_labels=False, node_color=get_coloring(m))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Alternatively, especially if we do not have a good guess for the upper bound of colors which are necessary, instead of choosing a very large `Kmax` which would make the MILO much larger and slower to solve, we can take an alternative approach.\n", + "Alternatively, especially if we do not have a good guess for the upper bound of colors which are necessary, instead of choosing a very large `K` which would make the MILO much larger and slower to solve, we can take an alternative approach.\n", "\n", "Let us start by creating a much larger connected graph with the same strategy as before." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -285,14 +283,14 @@ " seed += 1\n", " G = nx.gnp_random_graph(n, p, seed=seed)\n", "\n", - "pos = nx.spring_layout(G)\n", - "nx.draw(G, pos=pos, with_labels=False, node_size=100, width=0.25)\n", + "pos = nx.kamada_kawai_layout(G)\n", + "nx.draw(G, pos=pos, with_labels=False, node_size=150, width=0.4)\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -303,12 +301,12 @@ "3 colors are not enough\n", "4 colors are not enough\n", "The chromatic number of G is: 5\n", - "Time elapsed: 6.99 seconds\n" + "Time elapsed: 6.62 seconds\n" ] }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -319,42 +317,34 @@ ], "source": [ "start_time = pc()\n", - "Kmax = 2\n", + "K = 2\n", "while True:\n", - " results, m = graph_coloring(G, Kmax, catch_infeasibility=True)\n", + " results, m = graph_coloring(G, K, catch_infeasibility=True)\n", " if results.solver.termination_condition == pyo.TerminationCondition.optimal:\n", - " m = graph_coloring(G, Kmax)\n", - " print(f\"The chromatic number of G is: {Kmax}\")\n", + " m = graph_coloring(G, K)\n", + " print(f\"The chromatic number of G is: {K}\")\n", " print(f\"Time elapsed: {pc() - start_time:.2f} seconds\")\n", " break\n", " else:\n", - " print(f\"{Kmax} colors are not enough\")\n", - " Kmax += 1\n", + " print(f\"{K} colors are not enough\")\n", + " K += 1\n", "\n", - "# Plot the graph with the coloring\n", - "tab20 = plt.get_cmap(\"tab20\")\n", - "colors = [tab20(i) for i in range(0, 20, 4)]\n", - "coloring = get_coloring(m)\n", "nx.draw(\n", - " G,\n", - " pos=pos,\n", - " with_labels=False,\n", - " node_size=100,\n", - " width=0.25,\n", - " node_color=[colors[coloring[i]] for i in G.nodes],\n", - ")" + " G, pos=pos, with_labels=False, node_size=150, width=0.4, node_color=get_coloring(m)\n", + ")\n", + "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This approach is much faster than solving the same MILO with a large `Kmax`, say 10, which results in a much larger model, both in terms of number of variables and constraints." + "This approach is much faster than solving the same MILO with a large `K`, say 10, which results in a much larger model, both in terms of number of variables and constraints." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -362,13 +352,13 @@ "output_type": "stream", "text": [ "The chromatic number of G is: 5\n", - "Time elapsed: 75.88 seconds\n" + "Time elapsed: 73.99 seconds\n" ] } ], "source": [ "start_time = pc()\n", - "m = graph_coloring(G, Kmax=10)\n", + "m = graph_coloring(G, K=10)\n", "print(f\"The chromatic number of G is: {int(m.number_used_colors())}\")\n", "print(f\"Time elapsed: {pc() - start_time:.2f} seconds\")" ] @@ -382,27 +372,33 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Upper bound found by networkx: Kmax=6. This will be used as the parameter of the optimization model.\n", + "Upper bound found by networkx: K=6. This will be used as the parameter of the optimization model.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "The chromatic number of G is: 5\n", - "Time elapsed: 7.24 seconds\n" + "Time elapsed: 7.26 seconds\n" ] } ], "source": [ "start_time = pc()\n", "nxcoloring = nx.algorithms.coloring.greedy_color(G)\n", - "Kmax = len(set(nxcoloring.values()))\n", + "K = len(set(nxcoloring.values()))\n", "print(\n", - " f\"Upper bound found by networkx: Kmax={Kmax}. This will be used as the parameter of the optimization model.\"\n", + " f\"Upper bound found by networkx: K={K}. This will be used as the parameter of the optimization model.\"\n", ")\n", - "m = graph_coloring(G, Kmax)\n", + "m = graph_coloring(G, K)\n", "print(f\"The chromatic number of G is: {int(m.number_used_colors())}\")\n", "print(f\"Time elapsed: {pc() - start_time:.2f} seconds\")" ] diff --git a/_sources/notebooks/04/power-network.ipynb b/_sources/notebooks/04/power-network.ipynb index ae8fa166..8495a8ad 100644 --- a/_sources/notebooks/04/power-network.ipynb +++ b/_sources/notebooks/04/power-network.ipynb @@ -20,9 +20,7 @@ "```{index} scenario analysis\n", "```\n", "\n", - "# Extra material: Energy dispatch problem\n", - "\n", - "To meet the energy demand, power plants run day and night across the country to produce electricity from a variety of sources such as fossil fuels and renewable energy. On the short-time scale, the best operating levels for electric power plants are derived every 15 minutes by solving the so-called *Optimal Power Flow (OPF)* model. The OPF model is an optimization problem with the objective of minimizing the total energy dispatching cost, while ensuring that the generation meets the total energy demand. Furthermore, the model takes into account many constraints, among which operational and physical constraints. \n" + "# Extra material: Energy dispatch problem" ] }, { @@ -52,19 +50,26 @@ "outputs": [], "source": [ "import sys\n", - "\n", + " \n", "if 'google.colab' in sys.modules:\n", " !pip install pyomo >/dev/null 2>/dev/null\n", " !pip install highspy >/dev/null 2>/dev/null\n", + " \n", + "solver = 'appsi_highs'\n", + " \n", + "import pyomo.environ as pyo\n", + "SOLVER = pyo.SolverFactory(solver)\n", + " \n", + "assert SOLVER.available(), f\"Solver {solver} is not available.\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Problem description\n", "\n", - " from pyomo.environ import SolverFactory\n", - " SOLVER = SolverFactory('appsi_highs')\n", - " \n", - "else:\n", - " from pyomo.environ import SolverFactory\n", - " SOLVER = SolverFactory('cbc')\n", - "\n", - "assert SOLVER.available(), f\"Solver {SOLVER} is not available.\"" + "To meet the energy demand, power plants run day and night across the country to produce electricity from a variety of sources such as fossil fuels and renewable energy. On the short-time scale, the best operating levels for electric power plants are derived every 15 minutes by solving the so-called *Optimal Power Flow (OPF)* model. The OPF model is an optimization problem with the objective of minimizing the total energy dispatching cost, while ensuring that the generation meets the total energy demand and taking into account operational and physical constraints. " ] }, { @@ -99,7 +104,8 @@ "id": "4ZF8sTiZs7m0" }, "source": [ - "## Optimal Power Flow\n", + "## Optimal Power Flow problem\n", + "\n", "We assumed above that the power injections $\\mathbf{p}$ were given. However, in practice, the power injections need to be determined for each generator in the power network, where some types of generators may be cheaper than others. Moreover, we need to take into account operational constraints, such as the maximum flow and generator limits. \n", "\n", "On the short-time scale, the power injections are calculated for each generator by solving the so-called *Optimal Power Flow (OPF)* problem. The goal of the OPF problem is to determine a solution $(\\mathbf{p}, \\mathbf{f}, \\mathbf{\\theta})$ with minimal costs such that:\n", @@ -109,18 +115,18 @@ "\n", "Let $c_i > 0$ be the cost associated with the production of a unit energy by generator $i$. Then, the OPF problem can be formulated as\n", "\n", - "$$\\begin{align}\n", - "\\begin{array}{llll}\n", - "\\max & \\sum_{i \\in V} c_i p_i \\\\\n", - "\\text{s.t.} & \\sum_{j: (i, j) \\in E} f_{ij} - \\sum_{j: (j, i) \\in E} f_{ji} = p_i - d_i & \\forall \\, i \\in V,\\\\\n", - "& f_{ij} = b_{ij}(\\theta_i - \\theta_j), & \\forall \\, (i, j) \\in E, \\\\\n", - " & |f_{ij}| \\leq f_{ij}^{\\max} & \\forall (i, j) \\in E,\\\\\n", - " & p_{i}^{\\min } \\leq p_{i} \\leq p_{i}^{\\max } & \\forall i \\in V, \\\\\n", - " & p_i \\in \\mathbb{R}_{\\geq 0} & \\forall i \\in V, \\\\\n", - " & \\theta_i \\in \\mathbb{R} & \\forall i \\in V, \\\\\n", - " & f_{ij} \\in \\mathbb{R} & \\forall (i, j) \\in E \\\\\n", - "\\end{array}\n", - "\\end{align}$$\n", + "$$\n", + "\\begin{align*}\n", + "\\min \\, & \\sum_{i \\in V} c_i p_i \\\\\n", + "\\text{s.t.} \\, & \\sum_{j: (i, j) \\in E} f_{ij} - \\sum_{j: (j, i) \\in E} f_{ji} = p_i - d_i & \\forall \\, i \\in V\\\\\n", + " & f_{ij} = b_{ij}(\\theta_i - \\theta_j) & \\forall \\, (i, j) \\in E \\\\\n", + " & |f_{ij}| \\leq f_{ij}^{\\max} & \\forall \\,(i, j) \\in E\\\\\n", + " & p_{i}^{\\min } \\leq p_{i} \\leq p_{i}^{\\max } & \\forall \\,i \\in V \\\\\n", + " & p_i \\geq 0 & \\forall \\,i \\in V \\\\\n", + " & \\theta_i \\in \\mathbb{R} & \\forall \\,i \\in V \\\\\n", + " & f_{ij} \\in \\mathbb{R} & \\forall \\,(i, j) \\in E.\n", + "\\end{align*}\n", + "$$\n", "\n", "For simplicity, you may assume that all load nodes do not produce energy, i.e., $p_i = p_i^{\\min} = p_i^{\\max} = 0$ for all $i \\in \\mathcal{D}$. You may therefore model $p_i$ as decision variables for all nodes (both generator and load nodes). Similarly, you may assume that all generator nodes have no demand, i.e., $d_i = 0$ for all $i \\in \\mathcal{G}$.\n", "\n", @@ -129,7 +135,7 @@ "- $\\theta_i$ phase angles\n", "- $f_{ij}$ power flows\n", "\n", - "All the other quantities are instance dependent parameters." + "All the other quantities are instance-dependent parameters. Each of the 96 instances captures the network in a different moment in time, thus with different energy demand at each node and different realizations for the power produced by renewable energy sources." ] }, { @@ -147,16 +153,16 @@ "id": "-lny_r2OGnsJ" }, "source": [ - "You will solve the OPF problem on the IEEE-118 power network, which is a standard test network consisting of 118 nodes and 179 edges. In the following, we will load the data into the notebook and provide a description of the data. Make sure to run the setup code below. We will first describe the data which are initially provided as `pandas.DataFrames`. We will then provide a new network data structure to easily access the data for the implementation of the optimization model." + "You will solve the OPF problem on the IEEE-118 power network, which is a standard test network consisting of 118 nodes and 179 edges. In the following, we will load the data into the notebook and provide a description of the data. We will first describe the data which are initially provided as `pandas.DataFrames`. We will then provide a new network data structure to easily access the data for the implementation of the optimization model." ] }, { "cell_type": "markdown", "metadata": { - "id": "NBPDMyoUuvxp" + "id": "4BgoE_qSM8aZ" }, "source": [ - "### Setup code" + "### Setup code and data import" ] }, { @@ -164,75 +170,48 @@ "execution_count": 2, "metadata": { "ExecuteTime": { - "end_time": "2022-03-23T18:11:17.642038Z", - "start_time": "2022-03-23T18:11:12.866223Z" + "end_time": "2022-03-23T18:11:17.647734Z", + "start_time": "2022-03-23T18:11:17.647718Z" }, - "id": "bxwjVztvKQpk" + "id": "C98FtckVUESu" }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "WARNING: Failed to create solver with name\n", - " '': Failed to set executable for solver asl. File with\n", - " name= either does not exist or it is not executable. To skip\n", - " this validation, call set_executable with validate=False.\n", - "Traceback (most recent call last):\n", - " File \"/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/opt/base/solvers.py\", line 166, in __call__\n", - " opt = self._cls[_implicit_solvers[mode]](**kwds)\n", - " File \"/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/solvers/plugins/solvers/ASL.py\", line 45, in __init__\n", - " SystemCallSolver.__init__(self, **kwds)\n", - " File \"/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/opt/solver/shellcmd.py\", line 66, in __init__\n", - " self.set_executable(name=executable, validate=validate)\n", - " File \"/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/opt/solver/shellcmd.py\", line 114, in set_executable\n", - " raise ValueError(\n", - "ValueError: Failed to set executable for solver asl. File with name= either does not exist or it is not executable. To skip this validation, call set_executable with validate=False.\n" + "ename": "HTTPError", + "evalue": "HTTP Error 404: Not Found", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mHTTPError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/Users/ale/My Drive/GitHub repositories/MO-book/notebooks/04/power-network.ipynb Cell 10\u001b[0m line \u001b[0;36m9\n\u001b[1;32m 7\u001b[0m \u001b[39m# Download the data\u001b[39;00m\n\u001b[1;32m 8\u001b[0m base_url \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mhttps://raw.githubusercontent.com/mobook/MO-book/main/notebooks/04/data/\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m----> 9\u001b[0m nodes_df \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39;49mread_csv(base_url \u001b[39m+\u001b[39;49m \u001b[39m\"\u001b[39;49m\u001b[39mnodes.csv\u001b[39;49m\u001b[39m\"\u001b[39;49m, index_col\u001b[39m=\u001b[39;49m\u001b[39m0\u001b[39;49m)\n\u001b[1;32m 10\u001b[0m edges_df \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mread_csv(base_url \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39medges.csv\u001b[39m\u001b[39m\"\u001b[39m, index_col\u001b[39m=\u001b[39m\u001b[39m0\u001b[39m)\n\u001b[1;32m 12\u001b[0m \u001b[39m# Read all instances\u001b[39;00m\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/util/_decorators.py:211\u001b[0m, in \u001b[0;36mdeprecate_kwarg.._deprecate_kwarg..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 209\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 210\u001b[0m kwargs[new_arg_name] \u001b[39m=\u001b[39m new_arg_value\n\u001b[0;32m--> 211\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/util/_decorators.py:331\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments..decorate..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 325\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(args) \u001b[39m>\u001b[39m num_allow_args:\n\u001b[1;32m 326\u001b[0m warnings\u001b[39m.\u001b[39mwarn(\n\u001b[1;32m 327\u001b[0m msg\u001b[39m.\u001b[39mformat(arguments\u001b[39m=\u001b[39m_format_argument_list(allow_args)),\n\u001b[1;32m 328\u001b[0m \u001b[39mFutureWarning\u001b[39;00m,\n\u001b[1;32m 329\u001b[0m stacklevel\u001b[39m=\u001b[39mfind_stack_level(),\n\u001b[1;32m 330\u001b[0m )\n\u001b[0;32m--> 331\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:950\u001b[0m, in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, error_bad_lines, warn_bad_lines, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)\u001b[0m\n\u001b[1;32m 935\u001b[0m kwds_defaults \u001b[39m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m 936\u001b[0m dialect,\n\u001b[1;32m 937\u001b[0m delimiter,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 946\u001b[0m defaults\u001b[39m=\u001b[39m{\u001b[39m\"\u001b[39m\u001b[39mdelimiter\u001b[39m\u001b[39m\"\u001b[39m: \u001b[39m\"\u001b[39m\u001b[39m,\u001b[39m\u001b[39m\"\u001b[39m},\n\u001b[1;32m 947\u001b[0m )\n\u001b[1;32m 948\u001b[0m kwds\u001b[39m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m--> 950\u001b[0m \u001b[39mreturn\u001b[39;00m _read(filepath_or_buffer, kwds)\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:605\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 602\u001b[0m _validate_names(kwds\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mnames\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mNone\u001b[39;00m))\n\u001b[1;32m 604\u001b[0m \u001b[39m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 605\u001b[0m parser \u001b[39m=\u001b[39m TextFileReader(filepath_or_buffer, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwds)\n\u001b[1;32m 607\u001b[0m \u001b[39mif\u001b[39;00m chunksize \u001b[39mor\u001b[39;00m iterator:\n\u001b[1;32m 608\u001b[0m \u001b[39mreturn\u001b[39;00m parser\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1442\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 1439\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39moptions[\u001b[39m\"\u001b[39m\u001b[39mhas_index_names\u001b[39m\u001b[39m\"\u001b[39m] \u001b[39m=\u001b[39m kwds[\u001b[39m\"\u001b[39m\u001b[39mhas_index_names\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[1;32m 1441\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles: IOHandles \u001b[39m|\u001b[39m \u001b[39mNone\u001b[39;00m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m-> 1442\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_engine \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_make_engine(f, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mengine)\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1735\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m 1733\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m mode:\n\u001b[1;32m 1734\u001b[0m mode \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m-> 1735\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles \u001b[39m=\u001b[39m get_handle(\n\u001b[1;32m 1736\u001b[0m f,\n\u001b[1;32m 1737\u001b[0m mode,\n\u001b[1;32m 1738\u001b[0m encoding\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mencoding\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m 1739\u001b[0m compression\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mcompression\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m 1740\u001b[0m memory_map\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mmemory_map\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mFalse\u001b[39;49;00m),\n\u001b[1;32m 1741\u001b[0m is_text\u001b[39m=\u001b[39;49mis_text,\n\u001b[1;32m 1742\u001b[0m errors\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mencoding_errors\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mstrict\u001b[39;49m\u001b[39m\"\u001b[39;49m),\n\u001b[1;32m 1743\u001b[0m storage_options\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49moptions\u001b[39m.\u001b[39;49mget(\u001b[39m\"\u001b[39;49m\u001b[39mstorage_options\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39mNone\u001b[39;49;00m),\n\u001b[1;32m 1744\u001b[0m )\n\u001b[1;32m 1745\u001b[0m \u001b[39massert\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m 1746\u001b[0m f \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mhandles\u001b[39m.\u001b[39mhandle\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/common.py:713\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 710\u001b[0m codecs\u001b[39m.\u001b[39mlookup_error(errors)\n\u001b[1;32m 712\u001b[0m \u001b[39m# open URLs\u001b[39;00m\n\u001b[0;32m--> 713\u001b[0m ioargs \u001b[39m=\u001b[39m _get_filepath_or_buffer(\n\u001b[1;32m 714\u001b[0m path_or_buf,\n\u001b[1;32m 715\u001b[0m encoding\u001b[39m=\u001b[39;49mencoding,\n\u001b[1;32m 716\u001b[0m compression\u001b[39m=\u001b[39;49mcompression,\n\u001b[1;32m 717\u001b[0m mode\u001b[39m=\u001b[39;49mmode,\n\u001b[1;32m 718\u001b[0m storage_options\u001b[39m=\u001b[39;49mstorage_options,\n\u001b[1;32m 719\u001b[0m )\n\u001b[1;32m 721\u001b[0m handle \u001b[39m=\u001b[39m ioargs\u001b[39m.\u001b[39mfilepath_or_buffer\n\u001b[1;32m 722\u001b[0m handles: \u001b[39mlist\u001b[39m[BaseBuffer]\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/common.py:363\u001b[0m, in \u001b[0;36m_get_filepath_or_buffer\u001b[0;34m(filepath_or_buffer, encoding, compression, mode, storage_options)\u001b[0m\n\u001b[1;32m 361\u001b[0m \u001b[39m# assuming storage_options is to be interpreted as headers\u001b[39;00m\n\u001b[1;32m 362\u001b[0m req_info \u001b[39m=\u001b[39m urllib\u001b[39m.\u001b[39mrequest\u001b[39m.\u001b[39mRequest(filepath_or_buffer, headers\u001b[39m=\u001b[39mstorage_options)\n\u001b[0;32m--> 363\u001b[0m \u001b[39mwith\u001b[39;00m urlopen(req_info) \u001b[39mas\u001b[39;00m req:\n\u001b[1;32m 364\u001b[0m content_encoding \u001b[39m=\u001b[39m req\u001b[39m.\u001b[39mheaders\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mContent-Encoding\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mNone\u001b[39;00m)\n\u001b[1;32m 365\u001b[0m \u001b[39mif\u001b[39;00m content_encoding \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mgzip\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[1;32m 366\u001b[0m \u001b[39m# Override compression based on Content-Encoding header\u001b[39;00m\n", + "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/common.py:265\u001b[0m, in \u001b[0;36murlopen\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 259\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 260\u001b[0m \u001b[39mLazy-import wrapper for stdlib urlopen, as that imports a big chunk of\u001b[39;00m\n\u001b[1;32m 261\u001b[0m \u001b[39mthe stdlib.\u001b[39;00m\n\u001b[1;32m 262\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 263\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39murllib\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mrequest\u001b[39;00m\n\u001b[0;32m--> 265\u001b[0m \u001b[39mreturn\u001b[39;00m urllib\u001b[39m.\u001b[39;49mrequest\u001b[39m.\u001b[39;49murlopen(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n", + "File \u001b[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:216\u001b[0m, in \u001b[0;36murlopen\u001b[0;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[1;32m 214\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 215\u001b[0m opener \u001b[39m=\u001b[39m _opener\n\u001b[0;32m--> 216\u001b[0m \u001b[39mreturn\u001b[39;00m opener\u001b[39m.\u001b[39;49mopen(url, data, timeout)\n", + "File \u001b[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:525\u001b[0m, in \u001b[0;36mOpenerDirector.open\u001b[0;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[1;32m 523\u001b[0m \u001b[39mfor\u001b[39;00m processor \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mprocess_response\u001b[39m.\u001b[39mget(protocol, []):\n\u001b[1;32m 524\u001b[0m meth \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(processor, meth_name)\n\u001b[0;32m--> 525\u001b[0m response \u001b[39m=\u001b[39m meth(req, response)\n\u001b[1;32m 527\u001b[0m \u001b[39mreturn\u001b[39;00m response\n", + "File \u001b[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:634\u001b[0m, in \u001b[0;36mHTTPErrorProcessor.http_response\u001b[0;34m(self, request, response)\u001b[0m\n\u001b[1;32m 631\u001b[0m \u001b[39m# According to RFC 2616, \"2xx\" code indicates that the client's\u001b[39;00m\n\u001b[1;32m 632\u001b[0m \u001b[39m# request was successfully received, understood, and accepted.\u001b[39;00m\n\u001b[1;32m 633\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39m200\u001b[39m \u001b[39m<\u001b[39m\u001b[39m=\u001b[39m code \u001b[39m<\u001b[39m \u001b[39m300\u001b[39m):\n\u001b[0;32m--> 634\u001b[0m response \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mparent\u001b[39m.\u001b[39;49merror(\n\u001b[1;32m 635\u001b[0m \u001b[39m'\u001b[39;49m\u001b[39mhttp\u001b[39;49m\u001b[39m'\u001b[39;49m, request, response, code, msg, hdrs)\n\u001b[1;32m 637\u001b[0m \u001b[39mreturn\u001b[39;00m response\n", + "File \u001b[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:563\u001b[0m, in \u001b[0;36mOpenerDirector.error\u001b[0;34m(self, proto, *args)\u001b[0m\n\u001b[1;32m 561\u001b[0m \u001b[39mif\u001b[39;00m http_err:\n\u001b[1;32m 562\u001b[0m args \u001b[39m=\u001b[39m (\u001b[39mdict\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mdefault\u001b[39m\u001b[39m'\u001b[39m, \u001b[39m'\u001b[39m\u001b[39mhttp_error_default\u001b[39m\u001b[39m'\u001b[39m) \u001b[39m+\u001b[39m orig_args\n\u001b[0;32m--> 563\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_call_chain(\u001b[39m*\u001b[39;49margs)\n", + "File \u001b[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:496\u001b[0m, in \u001b[0;36mOpenerDirector._call_chain\u001b[0;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[1;32m 494\u001b[0m \u001b[39mfor\u001b[39;00m handler \u001b[39min\u001b[39;00m handlers:\n\u001b[1;32m 495\u001b[0m func \u001b[39m=\u001b[39m \u001b[39mgetattr\u001b[39m(handler, meth_name)\n\u001b[0;32m--> 496\u001b[0m result \u001b[39m=\u001b[39m func(\u001b[39m*\u001b[39;49margs)\n\u001b[1;32m 497\u001b[0m \u001b[39mif\u001b[39;00m result \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m 498\u001b[0m \u001b[39mreturn\u001b[39;00m result\n", + "File \u001b[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:643\u001b[0m, in \u001b[0;36mHTTPDefaultErrorHandler.http_error_default\u001b[0;34m(self, req, fp, code, msg, hdrs)\u001b[0m\n\u001b[1;32m 642\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mhttp_error_default\u001b[39m(\u001b[39mself\u001b[39m, req, fp, code, msg, hdrs):\n\u001b[0;32m--> 643\u001b[0m \u001b[39mraise\u001b[39;00m HTTPError(req\u001b[39m.\u001b[39mfull_url, code, msg, hdrs, fp)\n", + "\u001b[0;31mHTTPError\u001b[0m: HTTP Error 404: Not Found" ] } ], "source": [ - "# Load packages\n", - "\n", - "import pyomo.environ as pyo\n", - "from IPython.display import Markdown, HTML\n", "import numpy as np\n", - "import numpy.random as rnd\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "from ast import literal_eval as make_tuple\n", "import networkx as nx\n", - "import time\n", + "from ast import literal_eval as make_tuple\n", "\n", - "# Load solver\n", - "solver = pyo.SolverFactory(SOLVER)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "4BgoE_qSM8aZ" - }, - "source": [ - "### Data import" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "ExecuteTime": { - "end_time": "2022-03-23T18:11:17.647734Z", - "start_time": "2022-03-23T18:11:17.647718Z" - }, - "id": "C98FtckVUESu" - }, - "outputs": [], - "source": [ "# Download the data\n", - "base_url = \"https://raw.githubusercontent.com/mobook/MO-book/main/notebooks/04/\"\n", + "base_url = \"https://raw.githubusercontent.com/mobook/MO-book/main/notebooks/04/data/\"\n", "nodes_df = pd.read_csv(base_url + \"nodes.csv\", index_col=0)\n", "edges_df = pd.read_csv(base_url + \"edges.csv\", index_col=0)\n", "\n", @@ -260,7 +239,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.649979Z", @@ -271,7 +250,7 @@ "source": [ "def visualize_network(network, edge_flows=None, ax=None):\n", " \"\"\"Visualize a network instance, highlighting the generators in orange and the load buses in green.\"\"\"\n", - " plt.figure(figsize=[12, 10])\n", + " plt.figure(figsize=(12, 10))\n", " g = nx.DiGraph(network[\"edges\"].keys())\n", " pos = nx.layout.kamada_kawai_layout(g, weight=None)\n", "\n", @@ -311,7 +290,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.651737Z", @@ -374,7 +353,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.653899Z", @@ -684,7 +663,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.655599Z", @@ -918,7 +897,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.657053Z", @@ -1078,7 +1057,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.658270Z", @@ -1117,7 +1096,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.660266Z", @@ -1157,43 +1136,35 @@ "The network instances are stored in the variable `I` as a list and can be accessed using indexing, i.e., `I[0]` gives the first network instance and `I[95]` gives the 96th network instance." ] }, - { - "cell_type": "markdown", - "metadata": { - "id": "0GVlpC14Vixu" - }, - "source": [ - "---" - ] - }, { "cell_type": "markdown", "metadata": { "id": "Tejr2cdxtOWx" }, "source": [ - "# Solving OPF\n", + "## Solving the OPF problem\n", + "\n", "Observe that the stated OPF problem contains absolute decision values. We first rewrite the OPF problem into a linear optimization problem.\n", "\n", - "$$\\begin{align}\n", - "\\begin{array}{llll}\n", - "\\min & \\sum_{i \\in V} c_i p_i \\\\\n", - "\\text{s.t.} & \\sum_{j: (i, j) \\in E} f^+_{ij} - f^-_{ij} - \\sum_{j: (j, i) \\in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \\forall \\, i \\in V,\\\\\n", - "& f^+_{ij} - f^-_{ij} = b_{ij}(\\theta_i - \\theta_j), & \\forall \\, (i, j) \\in E, \\\\\n", - " & f^+_{ij} + f^-_{ij} \\leq f_{ij}^{\\max} & \\forall (i, j) \\in E,\\\\\n", - " & p_{i}^{\\min } \\leq p_{i} \\leq p_{i}^{\\max } & \\forall i \\in V, \\\\\n", - " & p_i \\in \\mathbb{R}_{\\geq 0} & \\forall i \\in V, \\\\\n", - " & \\theta_i \\in \\mathbb{R} & \\forall i \\in V, \\\\\n", - " & f_{ij}^+, f_{ij}^- \\in \\mathbb{R} & \\forall (i, j) \\in E \\\\\n", - "\\end{array}\n", - "\\end{align}$$\n", + "$$\n", + "\\begin{align*}\n", + "\\min \\, & \\sum_{i \\in V} c_i p_i \\\\\n", + "\\text{s.t.} \\, & \\sum_{j: (i, j) \\in E} f^+_{ij} - f^-_{ij} - \\sum_{j: (j, i) \\in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \\forall \\, i \\in V,\\\\\n", + " & f^+_{ij} - f^-_{ij} = b_{ij}(\\theta_i - \\theta_j), & \\forall \\, (i, j) \\in E\\\\\n", + " & f^+_{ij} + f^-_{ij} \\leq f_{ij}^{\\max} & \\forall \\,(i, j) \\in E\\\\\n", + " & p_{i}^{\\min } \\leq p_{i} \\leq p_{i}^{\\max } & \\forall \\,i \\in V \\\\\n", + " & p_i \\geq 0 & \\forall \\,i \\in V\\\\\n", + " & \\theta_i \\in \\mathbb{R} & \\forall \\,i \\in V\\\\\n", + " & f_{ij}^+, f_{ij}^- \\in \\mathbb{R} & \\forall \\,(i, j) \\in E.\n", + "\\end{align*}\n", + "$$\n", "\n", "We then implement the model using `pyomo` and solve it for all instances `I[0]` to `I[95]`, reporting the average objective value across all the 96 instances." ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.662132Z", @@ -1286,7 +1257,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -1312,31 +1283,31 @@ "# Strict fossil fuel policy pt.1\n", "Gas and coal plants emit CO2, while renewable energy sources are carbon neutral. For this reason, the Dutch government has decided to constrain the number of active fossil-fuel-based power plants for the generation of electricity. More specifically, a maximum of 2 gas plants and 1 coal plant may be *active* during a single OPF instance. Any plant that is set *inactive* for a specific instance cannot produce any electricity. \n", "\n", - "We first write down the new model. To this end, we introduce new decision variables $x_i, i\\in V$ to the model, which indicate whether a generator $i$ is active or inactive.\n", + "We first write down the new model. To this end, we introduce new decision variables $x_i$, $i\\in V$, to the model, which indicate whether a generator $i$ is active or inactive.\n", "\n", - "$$\\begin{align}\n", - "\\begin{array}{llll}\n", - "\\min & \\sum_{i \\in V} c_i p_i \\\\\n", - "\\text{s.t.} & \\sum_{j: (i, j) \\in E} f^+_{ij} - f^-_{ij} - \\sum_{j: (j, i) \\in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \\forall \\, i \\in V,\\\\\n", - "& f^+_{ij} - f^-_{ij} = b_{ij}(\\theta_i - \\theta_j), & \\forall \\, (i, j) \\in E, \\\\\n", - "& f^{abs}_{ij} = f^+_{ij} + f^-_{ij}, & \\forall \\, (i, j) \\in E, \\\\\n", - " & f_{ij}^{abs} \\leq f_{ij}^{\\max} & \\forall (i, j) \\in E,\\\\\n", - " & p_{i}^{\\min } x_i \\leq p_{i} \\leq p_{i}^{\\max } x_i & \\forall i \\in V, \\\\\n", + "$$\n", + "\\begin{align*}\n", + "\\min \\, & \\sum_{i \\in V} c_i p_i \\\\\n", + "\\text{s.t.} \\, & \\sum_{j: (i, j) \\in E} f^+_{ij} - f^-_{ij} - \\sum_{j: (j, i) \\in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \\forall \\, i \\in V\\\\\n", + " & f^+_{ij} - f^-_{ij} = b_{ij}(\\theta_i - \\theta_j) & \\forall \\, (i, j) \\in E \\\\\n", + " & f^{abs}_{ij} = f^+_{ij} + f^-_{ij} & \\forall \\, (i, j) \\in E \\\\\n", + " & f_{ij}^{abs} \\leq f_{ij}^{\\max} & \\forall \\, (i, j) \\in E\\\\\n", + " & p_{i}^{\\min } x_i \\leq p_{i} \\leq p_{i}^{\\max } x_i & \\forall \\, i \\in V \\\\\n", " & \\sum_{i \\in \\mathcal{G}_{\\text{gas}}} x_i \\leq 2 & \\\\\n", " & \\sum_{i \\in \\mathcal{G}_{\\text{coal}}} x_i \\leq 1 & \\\\\n", - " & p_i \\in \\mathbb{R}_{\\geq 0} & \\forall i \\in V, \\\\\n", - " & \\theta_i \\in \\mathbb{R} & \\forall i \\in V, \\\\\n", - " & f_{ij} \\in \\mathbb{R} & \\forall (i, j) \\in E \\\\\n", - " & x_i \\in \\{0, 1\\} & \\forall i \\in V\\\\\n", - "\\end{array}\n", - "\\end{align}$$\n", + " & p_i \\geq 0 & \\forall \\, i \\in V\\\\\n", + " & \\theta_i \\in \\mathbb{R} & \\forall \\,i \\in V \\\\\n", + " & f_{ij} \\in \\mathbb{R} & \\forall \\,(i, j) \\in E\\\\\n", + " & x_i \\in \\{0, 1\\} & \\forall \\,i \\in V.\n", + "\\end{align*}\n", + "$$\n", "\n", "We then implement the new model using `pyomo` and solve it for all instances `I[0]` to `I[95]`, reporting the average objective value across the instances." ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.666581Z", @@ -1453,7 +1424,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.668379Z", @@ -1491,31 +1462,31 @@ " \n", "We first write down the new model, using big-$M$ constraints to model the either-or constraint.\n", "\n", - "$$\\begin{align}\n", - "\\begin{array}{llll}\n", - "\\min & \\sum_{i \\in V} c_i p_i \\\\\n", - "\\text{s.t.} & \\sum_{j: (i, j) \\in E} f^+_{ij} - f^-_{ij} - \\sum_{j: (j, i) \\in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \\forall \\, i \\in V,\\\\\n", - "& f^+_{ij} - f^-_{ij} = b_{ij}(\\theta_i - \\theta_j), & \\forall \\, (i, j) \\in E, \\\\\n", - "& f^{abs}_{ij} = f^+_{ij} + f^-_{ij}, & \\forall \\, (i, j) \\in E, \\\\\n", - " & f_{ij}^{abs} \\leq f_{ij}^{\\max} & \\forall (i, j) \\in E,\\\\\n", - " & p_{i}^{\\min } x_i \\leq p_{i} \\leq p_{i}^{\\max } x_i & \\forall i \\in V, \\\\\n", + "$$\n", + "\\begin{align*}\n", + "\\min \\, & \\sum_{i \\in V} c_i p_i \\\\\n", + "\\text{s.t.} \\, & \\sum_{j: (i, j) \\in E} f^+_{ij} - f^-_{ij} - \\sum_{j: (j, i) \\in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \\forall \\, i \\in V\\\\\n", + " & f^+_{ij} - f^-_{ij} = b_{ij}(\\theta_i - \\theta_j) & \\forall \\, (i, j) \\in E\\\\\n", + " & f^{abs}_{ij} = f^+_{ij} + f^-_{ij} & \\forall \\, (i, j) \\in E\\\\\n", + " & f_{ij}^{abs} \\leq f_{ij}^{\\max} & \\forall \\,(i, j) \\in E\\\\\n", + " & p_{i}^{\\min } x_i \\leq p_{i} \\leq p_{i}^{\\max } x_i & \\forall \\,i \\in V\\\\\n", " & \\sum_{i \\in \\mathcal{G}_{\\text{gas}}} x_i \\leq 2 + (1-y)M_0 & \\\\\n", - " & \\sum_{i \\in \\mathcal{G}_{\\text{coal}}} x_i \\leq 1 + (1-y)M_1 & \\\\\n", + " & \\sum_{i \\in \\mathcal{G}_{\\text{coal}}} x_i \\leq 1 + (1-y)M_1 & \\\\\n", " & \\sum_{i \\in \\mathcal{G}_\\text{solar}} p_i + \\sum_{i \\in \\mathcal{G}_\\text{wind}} p_i + \\sum_{i \\in \\mathcal{G}_\\text{hydro}} p_i \\leq 1000 + yM_2&\\\\\n", - " & p_i \\in \\mathbb{R}_{\\geq 0} & \\forall i \\in V, \\\\\n", - " & \\theta_i \\in \\mathbb{R} & \\forall i \\in V, \\\\\n", - " & f_{ij} \\in \\mathbb{R} & \\forall (i, j) \\in E \\\\\n", - " & x_i \\in \\{0, 1\\} & \\forall i \\in V\\\\\n", + " & p_i \\geq 0 & \\forall \\,i \\in V\\\\\n", + " & \\theta_i \\in \\mathbb{R} & \\forall \\,i \\in V \\\\\n", + " & f_{ij} \\in \\mathbb{R} & \\forall \\,(i, j) \\in E \\\\\n", + " & x_i \\in \\{0, 1\\} & \\forall \\,i \\in V\\\\\n", " & y \\in \\{0, 1\\} &\\\\\n", - "\\end{array}\n", - "\\end{align}$$\n", + "\\end{align*}\n", + "$$\n", "\n", "We now implement the new model using `pyomo` and solve it for all instances `I[0]` to `I[95]`, reporting the average objective value across the instances." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.670681Z", @@ -1652,7 +1623,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.672765Z", @@ -1691,7 +1662,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -1704,7 +1675,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-03-23T18:11:17.676081Z", @@ -1755,13 +1726,6 @@ "- OPF2 does only uses 1000 renewable energy power, because then it may keep using all the gas and coal generators. \n", "- OPF1 uses all renewable energy at all times, because it has the flexibility to use all generators in order to mitigate operational restrictions due to line flows." ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -1780,7 +1744,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.16" + "version": "3.10.10" }, "toc": { "base_numbering": 1, diff --git a/genindex.html b/genindex.html index be372bdd..dca859ac 100644 --- a/genindex.html +++ b/genindex.html @@ -217,7 +217,6 @@ -
  • Forex Arbitrage
    • diff --git a/intro.html b/intro.html index f7c2815d..dd1d38c6 100644 --- a/intro.html +++ b/intro.html @@ -219,7 +219,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/01/01.00.html b/notebooks/01/01.00.html index beb33696..a338e766 100644 --- a/notebooks/01/01.00.html +++ b/notebooks/01/01.00.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/01/production-planning-advanced.html b/notebooks/01/production-planning-advanced.html index c40aa367..e5752c4a 100644 --- a/notebooks/01/production-planning-advanced.html +++ b/notebooks/01/production-planning-advanced.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/01/production-planning-basic.html b/notebooks/01/production-planning-basic.html index 4eddb3da..f1c2f0ae 100644 --- a/notebooks/01/production-planning-basic.html +++ b/notebooks/01/production-planning-basic.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/01/production-planning.html b/notebooks/01/production-planning.html index d5475774..dde0e5a4 100644 --- a/notebooks/01/production-planning.html +++ b/notebooks/01/production-planning.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/02.00.html b/notebooks/02/02.00.html index a9f42c8a..72d1ca5c 100644 --- a/notebooks/02/02.00.html +++ b/notebooks/02/02.00.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/L1-regression-wine-quality.html b/notebooks/02/L1-regression-wine-quality.html index 65050b02..1accf923 100644 --- a/notebooks/02/L1-regression-wine-quality.html +++ b/notebooks/02/L1-regression-wine-quality.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/bim-dual.html b/notebooks/02/bim-dual.html index 09b97662..a10e239c 100644 --- a/notebooks/02/bim-dual.html +++ b/notebooks/02/bim-dual.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/bim-fractional.html b/notebooks/02/bim-fractional.html index 1e408f67..87d30054 100644 --- a/notebooks/02/bim-fractional.html +++ b/notebooks/02/bim-fractional.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/bim-maxmin.html b/notebooks/02/bim-maxmin.html index 0899c2c7..1774ec5e 100644 --- a/notebooks/02/bim-maxmin.html +++ b/notebooks/02/bim-maxmin.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/bim-rawmaterialplanning.html b/notebooks/02/bim-rawmaterialplanning.html index 225a360e..b33a60f1 100644 --- a/notebooks/02/bim-rawmaterialplanning.html +++ b/notebooks/02/bim-rawmaterialplanning.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/bim.html b/notebooks/02/bim.html index 6715abe1..adb9cba0 100644 --- a/notebooks/02/bim.html +++ b/notebooks/02/bim.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/lad-regression.html b/notebooks/02/lad-regression.html index 613cf520..65a2c989 100644 --- a/notebooks/02/lad-regression.html +++ b/notebooks/02/lad-regression.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/mad-portfolio-optimization.html b/notebooks/02/mad-portfolio-optimization.html index b3631633..fa3071c8 100644 --- a/notebooks/02/mad-portfolio-optimization.html +++ b/notebooks/02/mad-portfolio-optimization.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/02/multiproductionfaciliity_worstcase.html b/notebooks/02/multiproductionfaciliity_worstcase.html index 2cb5282c..558ad0bc 100644 --- a/notebooks/02/multiproductionfaciliity_worstcase.html +++ b/notebooks/02/multiproductionfaciliity_worstcase.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/03.00.html b/notebooks/03/03.00.html index 91ad63c6..70ec1e02 100644 --- a/notebooks/03/03.00.html +++ b/notebooks/03/03.00.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/bim-perturbed.html b/notebooks/03/bim-perturbed.html index 65f9bae3..6a80564f 100644 --- a/notebooks/03/bim-perturbed.html +++ b/notebooks/03/bim-perturbed.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/bim-production-revisited.html b/notebooks/03/bim-production-revisited.html index 974f7419..a0165b30 100644 --- a/notebooks/03/bim-production-revisited.html +++ b/notebooks/03/bim-production-revisited.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/cryptarithms.html b/notebooks/03/cryptarithms.html index c5f02df7..54663a01 100644 --- a/notebooks/03/cryptarithms.html +++ b/notebooks/03/cryptarithms.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/facility-location.html b/notebooks/03/facility-location.html index 5194c07a..b47d97e1 100644 --- a/notebooks/03/facility-location.html +++ b/notebooks/03/facility-location.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/job-shop-scheduling.html b/notebooks/03/job-shop-scheduling.html index a0ac4ca8..fbbd6f4d 100644 --- a/notebooks/03/job-shop-scheduling.html +++ b/notebooks/03/job-shop-scheduling.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/machine-scheduling.html b/notebooks/03/machine-scheduling.html index 28d4f7c4..95690a46 100644 --- a/notebooks/03/machine-scheduling.html +++ b/notebooks/03/machine-scheduling.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/maintenance-planning.html b/notebooks/03/maintenance-planning.html index 045009fa..c0b1f3da 100644 --- a/notebooks/03/maintenance-planning.html +++ b/notebooks/03/maintenance-planning.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/recharging-electric-vehicle.html b/notebooks/03/recharging-electric-vehicle.html index 40f1c03f..6f7b98ee 100644 --- a/notebooks/03/recharging-electric-vehicle.html +++ b/notebooks/03/recharging-electric-vehicle.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/shift-scheduling.html b/notebooks/03/shift-scheduling.html index b01c709c..2ad0369f 100644 --- a/notebooks/03/shift-scheduling.html +++ b/notebooks/03/shift-scheduling.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/simple-production-model-gdp.html b/notebooks/03/simple-production-model-gdp.html index ffcf3d1b..447e9b37 100644 --- a/notebooks/03/simple-production-model-gdp.html +++ b/notebooks/03/simple-production-model-gdp.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/03/strip-packing.html b/notebooks/03/strip-packing.html index 7ca4c01a..f6620744 100644 --- a/notebooks/03/strip-packing.html +++ b/notebooks/03/strip-packing.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/04.00.html b/notebooks/04/04.00.html index e9f18218..cac4be54 100644 --- a/notebooks/04/04.00.html +++ b/notebooks/04/04.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/cryptocurrency-arbitrage.html b/notebooks/04/cryptocurrency-arbitrage.html index d401081e..024ab5aa 100644 --- a/notebooks/04/cryptocurrency-arbitrage.html +++ b/notebooks/04/cryptocurrency-arbitrage.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/dinner-seat-allocation.html b/notebooks/04/dinner-seat-allocation.html index 4feef98e..cd61c949 100644 --- a/notebooks/04/dinner-seat-allocation.html +++ b/notebooks/04/dinner-seat-allocation.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/forex-arbitrage.html b/notebooks/04/forex-arbitrage.html index e217f85e..4733efa1 100644 --- a/notebooks/04/forex-arbitrage.html +++ b/notebooks/04/forex-arbitrage.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/gasoline-distribution.html b/notebooks/04/gasoline-distribution.html index 91a1c30e..63463094 100644 --- a/notebooks/04/gasoline-distribution.html +++ b/notebooks/04/gasoline-distribution.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/graph-coloring.html b/notebooks/04/graph-coloring.html index 802e8e6e..11c8045a 100644 --- a/notebooks/04/graph-coloring.html +++ b/notebooks/04/graph-coloring.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • @@ -568,9 +567,9 @@

    Mathematical formulation\(G\) and corresponds to the minimum number of time slots needed to schedule all exams.

    -

    In the rest of the notebook, for simplicity, we will use the graph terminology. The interested reader can easily interpret variables, constraints, and other considerations into the scheduling context.

    -

    The following cell defines the graph coloring problem in Pyomo. The function graph_coloring besides the graph G takes as optional argument the maximum number Kmax of colors to use in the model. Note that this might result in an infeasible model if Kmax is too small. The other optional argument catch_infeasibility is used precisely to diagnose the model infeasibility without raising errors.

    +

    In this formulation, the objective function tries to minimize the number of colors used, while the constraints ensure that (i) two connected nodes do not share the same color, (ii) only a color \(k\) that is being used can be assigned to a node \(i\), and (iii) each node has to be assigned exactly one color. The optimal solution of this problem is known as the chromatic number of the graph \(G\) and corresponds to the minimum number of time slots needed to schedule all exams.

    +

    In the rest of the notebook, for simplicity, we will use the graph terminology but an interested reader should be able easily interpret the results back in the scheduling context.

    +

    The following cell defines the graph coloring problem in Pyomo. The function graph_coloring besides a networkx graph object G takes as optional argument the maximum number K of colors to use in the model. Note that this might result in an infeasible model if K is too small. The other optional argument catch_infeasibility is used precisely to diagnose the model infeasibility without raising errors.

    import networkx as nx
@@ -578,10 +577,10 @@ 
    Mathematical formulationfrom time import perf_counter as pc
 
 
-def graph_coloring(G, Kmax=7, catch_infeasibility=False):
+def graph_coloring(G, K=7, catch_infeasibility=False):
     m = pyo.ConcreteModel("Graph Coloring")
 
-    m.colors = pyo.RangeSet(0, Kmax - 1)
+    m.colors = pyo.RangeSet(0, K - 1)
     m.nodes = pyo.Set(initialize=list(G.nodes))
     m.edges = pyo.Set(initialize=list(G.edges), dimen=2)
 
@@ -621,7 +620,13 @@ 
    Mathematical formulationfor k in m.colors:
             if round(m.x[i, k]()) == 1:
                 coloring[i] = k
-    return coloring
+    unique_labels = set(coloring.values())
+    tab20 = plt.get_cmap("tab20")
+    color_palette = [tab20(i) for i in range(0, 20, 2)]
+    label_to_color = {
+        label: color for label, color in zip(unique_labels, color_palette)
+    }
+    return [label_to_color[coloring[key]] for key in sorted(coloring.keys())]
    @@ -629,7 +634,7 @@

    Mathematical formulation\((n,p)\) model. Since we are interested in a connected graph, we keep generating random graphs changing the random seed until we obtained a connected one.

    -
    n = 14
+
    n = 15
 p = 3 / n
 
 seed = 1
@@ -638,30 +643,22 @@ 
    Mathematical formulationseed += 1
     G = nx.gnp_random_graph(n, p, seed=seed)
 
-pos = nx.spring_layout(G)
+pos = nx.kamada_kawai_layout(G)
 nx.draw(G, pos=pos, with_labels=False)
-plt.show()
    -../../_images/012c0ac7fc1ef68266b235563008020d2d0d8956166b1c2a0f4249e483bb05b6.png +../../_images/4a958f6164537dc50c0238eafd06a158d8db082511c4cea0e4da68e13694f8f2.png
    -

    If we have a reasonable upper bound on the number of colors necessary, we can set it using the optional argument Kmax. Otherwise, the default for the model is Kmax=10.

    +

    If we have a reasonable upper bound on the number of colors necessary, we can set it using the optional argument K. Otherwise, the default for the model is K=10.

    -
    Kmax = 4
-m = graph_coloring(G, Kmax)
+
    K = 4
+m = graph_coloring(G, K)
 print(f"The chromatic number of G is: {int(m.number_used_colors())}")
-
-# Plot the graph with the coloring
-tab20 = plt.get_cmap("tab20")
-colors = [tab20(i) for i in range(0, 20, 4)]
-coloring = get_coloring(m)
-nx.draw(
-    G, pos=pos, with_labels=False, node_color=[colors[coloring[i]] for i in G.nodes]
-)
+nx.draw(G, pos=pos, with_labels=False, node_color=get_coloring(m))
    @@ -669,10 +666,10 @@

    Mathematical formulation
    The chromatic number of G is: 3

    -../../_images/8b81c2a184c076c22ffa803d1d8ea294a5a37b812824dd1cffab7845b1aed61c.png +../../_images/7b5ab8c778114aa5f3811e14abc6a3432a0a14b7f0dd44b84e807b42a82bb443.png
    -

    Alternatively, especially if we do not have a good guess for the upper bound of colors which are necessary, instead of choosing a very large Kmax which would make the MILO much larger and slower to solve, we can take an alternative approach.

    +

    Alternatively, especially if we do not have a good guess for the upper bound of colors which are necessary, instead of choosing a very large K which would make the MILO much larger and slower to solve, we can take an alternative approach.

    Let us start by creating a much larger connected graph with the same strategy as before.

    @@ -684,43 +681,35 @@

    Mathematical formulationseed += 1 G = nx.gnp_random_graph(n, p, seed=seed) -pos = nx.spring_layout(G) -nx.draw(G, pos=pos, with_labels=False, node_size=100, width=0.25) +pos = nx.kamada_kawai_layout(G) +nx.draw(G, pos=pos, with_labels=False, node_size=150, width=0.4) plt.show()

    -../../_images/eea2e649c26e8415e05af2dc7aea168b29d2ba3be8955fc81e9bd4beba2661f2.png +../../_images/65af28bac15dc33c59e44d5c77fcc66bff62565f31fb07f17c7eb445a15bcd61.png 
    start_time = pc()
-Kmax = 2
+K = 2
 while True:
-    results, m = graph_coloring(G, Kmax, catch_infeasibility=True)
+    results, m = graph_coloring(G, K, catch_infeasibility=True)
     if results.solver.termination_condition == pyo.TerminationCondition.optimal:
-        m = graph_coloring(G, Kmax)
-        print(f"The chromatic number of G is: {Kmax}")
+        m = graph_coloring(G, K)
+        print(f"The chromatic number of G is: {K}")
         print(f"Time elapsed: {pc() - start_time:.2f} seconds")
         break
     else:
-        print(f"{Kmax} colors are not enough")
-        Kmax += 1
+        print(f"{K} colors are not enough")
+        K += 1
 
-# Plot the graph with the coloring
-tab20 = plt.get_cmap("tab20")
-colors = [tab20(i) for i in range(0, 20, 4)]
-coloring = get_coloring(m)
 nx.draw(
-    G,
-    pos=pos,
-    with_labels=False,
-    node_size=100,
-    width=0.25,
-    node_color=[colors[coloring[i]] for i in G.nodes],
+    G, pos=pos, with_labels=False, node_size=150, width=0.4, node_color=get_coloring(m)
 )
+plt.show()
    @@ -729,17 +718,17 @@

    Mathematical formulation +../../_images/a14d32935b261690016cda1f27ca562e1f9f7c0666d018f3afdba61ab61253c3.png

    -

    This approach is much faster than solving the same MILO with a large Kmax, say 10, which results in a much larger model, both in terms of number of variables and constraints.

    +

    This approach is much faster than solving the same MILO with a large K, say 10, which results in a much larger model, both in terms of number of variables and constraints.

    start_time = pc()
-m = graph_coloring(G, Kmax=10)
+m = graph_coloring(G, K=10)
 print(f"The chromatic number of G is: {int(m.number_used_colors())}")
 print(f"Time elapsed: {pc() - start_time:.2f} seconds")
    @@ -747,7 +736,7 @@

    Mathematical formulation 
    The chromatic number of G is: 5
-Time elapsed: 75.88 seconds
+Time elapsed: 73.99 seconds

    @@ -757,20 +746,22 @@

    Mathematical formulation 
    start_time = pc()
 nxcoloring = nx.algorithms.coloring.greedy_color(G)
-Kmax = len(set(nxcoloring.values()))
+K = len(set(nxcoloring.values()))
 print(
-    f"Upper bound found by networkx: Kmax={Kmax}. This will be used as the parameter of the optimization model."
+    f"Upper bound found by networkx: K={K}. This will be used as the parameter of the optimization model."
 )
-m = graph_coloring(G, Kmax)
+m = graph_coloring(G, K)
 print(f"The chromatic number of G is: {int(m.number_used_colors())}")
 print(f"Time elapsed: {pc() - start_time:.2f} seconds")

    -
    Upper bound found by networkx: Kmax=6. This will be used as the parameter of the optimization model.
-The chromatic number of G is: 5
-Time elapsed: 7.24 seconds
+
    Upper bound found by networkx: K=6. This will be used as the parameter of the optimization model.
+
    
+
    
+
    The chromatic number of G is: 5
+Time elapsed: 7.26 seconds
    diff --git a/notebooks/04/mincost-flow.html b/notebooks/04/mincost-flow.html index fcac2171..35f2f857 100644 --- a/notebooks/04/mincost-flow.html +++ b/notebooks/04/mincost-flow.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/04/power-network.html b/notebooks/04/power-network.html index 4f5c4170..8de9ff3a 100644 --- a/notebooks/04/power-network.html +++ b/notebooks/04/power-network.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • @@ -504,20 +503,20 @@

    Contents

    +
    +

    Problem description#

    +

    To meet the energy demand, power plants run day and night across the country to produce electricity from a variety of sources such as fossil fuels and renewable energy. On the short-time scale, the best operating levels for electric power plants are derived every 15 minutes by solving the so-called Optimal Power Flow (OPF) model. The OPF model is an optimization problem with the objective of minimizing the total energy dispatching cost, while ensuring that the generation meets the total energy demand and taking into account operational and physical constraints.

    +

    Background: Power networks and power flow physics#

    We model the nation-wide transmission power network as a directed graph \(G=(V, E)\), where \(V\) represents the set of nodes (e.g., cities, industrial districts, power plants) and \(E\) denotes the set of directed edges (e.g., physical transmission lines).

    @@ -578,8 +578,8 @@

    Background: Power networks and power flow physicsThe first set of constraints ensures flow conservation and the second set of constrations captures the flow dependency on susceptances and angle differences. The DC power flow equations admit a unique power flow solution \(\mathbf{f}\) given matched power injections \(\mathbf{p}\) and demand \(\mathbf{d}\).

    For a given matched supply and demand vector \(\mathbf{p}\) and \(\mathbf{d}\), we can compute the power flows on the network by solving the linear equations as described above. There are exactly \(|V|\) and \(|E|\) equations for the \(\theta_i\) variables and \(f_{ij}\) variables, meaning that this system of equations admit a solution.

    -
    -

    Optimal Power Flow#

    +
    +

    Optimal Power Flow problem#

    We assumed above that the power injections \(\mathbf{p}\) were given. However, in practice, the power injections need to be determined for each generator in the power network, where some types of generators may be cheaper than others. Moreover, we need to take into account operational constraints, such as the maximum flow and generator limits.

    On the short-time scale, the power injections are calculated for each generator by solving the so-called Optimal Power Flow (OPF) problem. The goal of the OPF problem is to determine a solution \((\mathbf{p}, \mathbf{f}, \mathbf{\theta})\) with minimal costs such that:

    For simplicity, you may assume that all load nodes do not produce energy, i.e., \(p_i = p_i^{\min} = p_i^{\max} = 0\) for all \(i \in \mathcal{D}\). You may therefore model \(p_i\) as decision variables for all nodes (both generator and load nodes). Similarly, you may assume that all generator nodes have no demand, i.e., \(d_i = 0\) for all \(i \in \mathcal{G}\).

    To summarize, the decision variables in the OPF problem are:

     -

    All the other quantities are instance dependent parameters.

    +

    All the other quantities are instance-dependent parameters. Each of the 96 instances captures the network in a different moment in time, thus with different energy demand at each node and different realizations for the power produced by renewable energy sources.

    Data#

    -

    You will solve the OPF problem on the IEEE-118 power network, which is a standard test network consisting of 118 nodes and 179 edges. In the following, we will load the data into the notebook and provide a description of the data. Make sure to run the setup code below. We will first describe the data which are initially provided as pandas.DataFrames. We will then provide a new network data structure to easily access the data for the implementation of the optimization model.

    -
    -

    Setup code#

    +

    You will solve the OPF problem on the IEEE-118 power network, which is a standard test network consisting of 118 nodes and 179 edges. In the following, we will load the data into the notebook and provide a description of the data. We will first describe the data which are initially provided as pandas.DataFrames. We will then provide a new network data structure to easily access the data for the implementation of the optimization model.

    +
    +

    Setup code and data import#

    -
    # Load packages
-
-import pyomo.environ as pyo
-from IPython.display import Markdown, HTML
-import numpy as np
-import numpy.random as rnd
+
    import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
-from ast import literal_eval as make_tuple
 import networkx as nx
-import time
+from ast import literal_eval as make_tuple
 
-# Load solver
-solver = pyo.SolverFactory(SOLVER)
-
    
-
    
-
    -
    -
    WARNING: Failed to create solver with name
-    '<pyomo.solvers.plugins.solvers.CBCplugin.CBCSHELL object at
-    0x7f7a85e3d880>': Failed to set executable for solver asl. File with
-    name=<pyomo.solvers.plugins.solvers.CBCplugin.CBCSHELL object at
-    0x7f7a85e3d880> either does not exist or it is not executable. To skip
-    this validation, call set_executable with validate=False.
-Traceback (most recent call last):
-  File "/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/opt/base/solvers.py", line 166, in __call__
-    opt = self._cls[_implicit_solvers[mode]](**kwds)
-  File "/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/solvers/plugins/solvers/ASL.py", line 45, in __init__
-    SystemCallSolver.__init__(self, **kwds)
-  File "/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/opt/solver/shellcmd.py", line 66, in __init__
-    self.set_executable(name=executable, validate=validate)
-  File "/Users/jeff/opt/anaconda3/lib/python3.9/site-packages/pyomo/opt/solver/shellcmd.py", line 114, in set_executable
-    raise ValueError(
-ValueError: Failed to set executable for solver asl. File with name=<pyomo.solvers.plugins.solvers.CBCplugin.CBCSHELL object at 0x7f7a85e3d880> either does not exist or it is not executable. To skip this validation, call set_executable with validate=False.
-
    -
    -
    -
    -
    -
    -

    Data import#

    -
    -
    -
    # Download the data
-base_url = "https://raw.githubusercontent.com/mobook/MO-book/main/notebooks/04/"
+# Download the data
+base_url = "https://raw.githubusercontent.com/mobook/MO-book/main/notebooks/04/data/"
 nodes_df = pd.read_csv(base_url + "nodes.csv", index_col=0)
 edges_df = pd.read_csv(base_url + "edges.csv", index_col=0)
 
@@ -679,6 +642,136 @@ 
    Data import
+
    ---------------------------------------------------------------------------
+HTTPError                                 Traceback (most recent call last)
+/Users/ale/My Drive/GitHub repositories/MO-book/notebooks/04/power-network.ipynb Cell 10 line 9
+      <a href='vscode-notebook-cell:/Users/ale/My%20Drive/GitHub%20repositories/MO-book/notebooks/04/power-network.ipynb#X13sZmlsZQ%3D%3D?line=6'>7</a> # Download the data
+      <a href='vscode-notebook-cell:/Users/ale/My%20Drive/GitHub%20repositories/MO-book/notebooks/04/power-network.ipynb#X13sZmlsZQ%3D%3D?line=7'>8</a> base_url = "https://raw.githubusercontent.com/mobook/MO-book/main/notebooks/04/data/"
+----> <a href='vscode-notebook-cell:/Users/ale/My%20Drive/GitHub%20repositories/MO-book/notebooks/04/power-network.ipynb#X13sZmlsZQ%3D%3D?line=8'>9</a> nodes_df = pd.read_csv(base_url + "nodes.csv", index_col=0)
+     <a href='vscode-notebook-cell:/Users/ale/My%20Drive/GitHub%20repositories/MO-book/notebooks/04/power-network.ipynb#X13sZmlsZQ%3D%3D?line=9'>10</a> edges_df = pd.read_csv(base_url + "edges.csv", index_col=0)
+     <a href='vscode-notebook-cell:/Users/ale/My%20Drive/GitHub%20repositories/MO-book/notebooks/04/power-network.ipynb#X13sZmlsZQ%3D%3D?line=11'>12</a> # Read all instances
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/util/_decorators.py:211, in deprecate_kwarg.<locals>._deprecate_kwarg.<locals>.wrapper(*args, **kwargs)
+    209     else:
+    210         kwargs[new_arg_name] = new_arg_value
+--> 211 return func(*args, **kwargs)
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/util/_decorators.py:331, in deprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper(*args, **kwargs)
+    325 if len(args) > num_allow_args:
+    326     warnings.warn(
+    327         msg.format(arguments=_format_argument_list(allow_args)),
+    328         FutureWarning,
+    329         stacklevel=find_stack_level(),
+    330     )
+--> 331 return func(*args, **kwargs)
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:950, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, error_bad_lines, warn_bad_lines, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options)
+    935 kwds_defaults = _refine_defaults_read(
+    936     dialect,
+    937     delimiter,
+   (...)
+    946     defaults={"delimiter": ","},
+    947 )
+    948 kwds.update(kwds_defaults)
+--> 950 return _read(filepath_or_buffer, kwds)
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:605, in _read(filepath_or_buffer, kwds)
+    602 _validate_names(kwds.get("names", None))
+    604 # Create the parser.
+--> 605 parser = TextFileReader(filepath_or_buffer, **kwds)
+    607 if chunksize or iterator:
+    608     return parser
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1442, in TextFileReader.__init__(self, f, engine, **kwds)
+   1439     self.options["has_index_names"] = kwds["has_index_names"]
+   1441 self.handles: IOHandles | None = None
+-> 1442 self._engine = self._make_engine(f, self.engine)
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/parsers/readers.py:1735, in TextFileReader._make_engine(self, f, engine)
+   1733     if "b" not in mode:
+   1734         mode += "b"
+-> 1735 self.handles = get_handle(
+   1736     f,
+   1737     mode,
+   1738     encoding=self.options.get("encoding", None),
+   1739     compression=self.options.get("compression", None),
+   1740     memory_map=self.options.get("memory_map", False),
+   1741     is_text=is_text,
+   1742     errors=self.options.get("encoding_errors", "strict"),
+   1743     storage_options=self.options.get("storage_options", None),
+   1744 )
+   1745 assert self.handles is not None
+   1746 f = self.handles.handle
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/common.py:713, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)
+    710     codecs.lookup_error(errors)
+    712 # open URLs
+--> 713 ioargs = _get_filepath_or_buffer(
+    714     path_or_buf,
+    715     encoding=encoding,
+    716     compression=compression,
+    717     mode=mode,
+    718     storage_options=storage_options,
+    719 )
+    721 handle = ioargs.filepath_or_buffer
+    722 handles: list[BaseBuffer]
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/common.py:363, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options)
+    361 # assuming storage_options is to be interpreted as headers
+    362 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options)
+--> 363 with urlopen(req_info) as req:
+    364     content_encoding = req.headers.get("Content-Encoding", None)
+    365     if content_encoding == "gzip":
+    366         # Override compression based on Content-Encoding header
+
+File ~/Library/Caches/pypoetry/virtualenvs/mo-book-rd3A6LPh-py3.10/lib/python3.10/site-packages/pandas/io/common.py:265, in urlopen(*args, **kwargs)
+    259 """
+    260 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of
+    261 the stdlib.
+    262 """
+    263 import urllib.request
+--> 265 return urllib.request.urlopen(*args, **kwargs)
+
+File ~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:216, in urlopen(url, data, timeout, cafile, capath, cadefault, context)
+    214 else:
+    215     opener = _opener
+--> 216 return opener.open(url, data, timeout)
+
+File ~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:525, in OpenerDirector.open(self, fullurl, data, timeout)
+    523 for processor in self.process_response.get(protocol, []):
+    524     meth = getattr(processor, meth_name)
+--> 525     response = meth(req, response)
+    527 return response
+
+File ~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:634, in HTTPErrorProcessor.http_response(self, request, response)
+    631 # According to RFC 2616, "2xx" code indicates that the client's
+    632 # request was successfully received, understood, and accepted.
+    633 if not (200 <= code < 300):
+--> 634     response = self.parent.error(
+    635         'http', request, response, code, msg, hdrs)
+    637 return response
+
+File ~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:563, in OpenerDirector.error(self, proto, *args)
+    561 if http_err:
+    562     args = (dict, 'default', 'http_error_default') + orig_args
+--> 563     return self._call_chain(*args)
+
+File ~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:496, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args)
+    494 for handler in handlers:
+    495     func = getattr(handler, meth_name)
+--> 496     result = func(*args)
+    497     if result is not None:
+    498         return result
+
+File ~/.pyenv/versions/3.10.10/lib/python3.10/urllib/request.py:643, in HTTPDefaultErrorHandler.http_error_default(self, req, fp, code, msg, hdrs)
+    642 def http_error_default(self, req, fp, code, msg, hdrs):
+--> 643     raise HTTPError(req.full_url, code, msg, hdrs, fp)
+
+HTTPError: HTTP Error 404: Not Found
+
    
+
    
+
    @@ -687,7 +780,7 @@

    Network data 
    def visualize_network(network, edge_flows=None, ax=None):
     """Visualize a network instance, highlighting the generators in orange and the load buses in green."""
-    plt.figure(figsize=[12, 10])
+    plt.figure(figsize=(12, 10))
     g = nx.DiGraph(network["edges"].keys())
     pos = nx.layout.kamada_kawai_layout(g, weight=None)
 
@@ -1314,24 +1407,22 @@ 
    InstancesI as a list and can be accessed using indexing, i.e., I[0] gives the first network instance and I[95] gives the 96th network instance.

    -
    -
    -
    -

    Solving OPF#

    +
    +

    Solving the OPF problem#

    Observe that the stated OPF problem contains absolute decision values. We first rewrite the OPF problem into a linear optimization problem.

    -\[\begin{split}\begin{align} -\begin{array}{llll} -\min & \sum_{i \in V} c_i p_i \\ -\text{s.t.} & \sum_{j: (i, j) \in E} f^+_{ij} - f^-_{ij} - \sum_{j: (j, i) \in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \forall \, i \in V,\\ -& f^+_{ij} - f^-_{ij} = b_{ij}(\theta_i - \theta_j), & \forall \, (i, j) \in E, \\ - & f^+_{ij} + f^-_{ij} \leq f_{ij}^{\max} & \forall (i, j) \in E,\\ - & p_{i}^{\min } \leq p_{i} \leq p_{i}^{\max } & \forall i \in V, \\ - & p_i \in \mathbb{R}_{\geq 0} & \forall i \in V, \\ - & \theta_i \in \mathbb{R} & \forall i \in V, \\ - & f_{ij}^+, f_{ij}^- \in \mathbb{R} & \forall (i, j) \in E \\ -\end{array} -\end{align}\end{split}\]
    +\[\begin{split} +\begin{align*} +\min \, & \sum_{i \in V} c_i p_i \\ +\text{s.t.} \, & \sum_{j: (i, j) \in E} f^+_{ij} - f^-_{ij} - \sum_{j: (j, i) \in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \forall \, i \in V,\\ + & f^+_{ij} - f^-_{ij} = b_{ij}(\theta_i - \theta_j), & \forall \, (i, j) \in E\\ + & f^+_{ij} + f^-_{ij} \leq f_{ij}^{\max} & \forall \,(i, j) \in E\\ + & p_{i}^{\min } \leq p_{i} \leq p_{i}^{\max } & \forall \,i \in V \\ + & p_i \geq 0 & \forall \,i \in V\\ + & \theta_i \in \mathbb{R} & \forall \,i \in V\\ + & f_{ij}^+, f_{ij}^- \in \mathbb{R} & \forall \,(i, j) \in E. +\end{align*} +\end{split}\]

    We then implement the model using pyomo and solve it for all instances I[0] to I[95], reporting the average objective value across all the 96 instances.

    @@ -1433,27 +1524,28 @@

    Solving OPF

    Strict fossil fuel policy pt.1#

    Gas and coal plants emit CO2, while renewable energy sources are carbon neutral. For this reason, the Dutch government has decided to constrain the number of active fossil-fuel-based power plants for the generation of electricity. More specifically, a maximum of 2 gas plants and 1 coal plant may be active during a single OPF instance. Any plant that is set inactive for a specific instance cannot produce any electricity.

    -

    We first write down the new model. To this end, we introduce new decision variables \(x_i, i\in V\) to the model, which indicate whether a generator \(i\) is active or inactive.

    +

    We first write down the new model. To this end, we introduce new decision variables \(x_i\), \(i\in V\), to the model, which indicate whether a generator \(i\) is active or inactive.

    -\[\begin{split}\begin{align} -\begin{array}{llll} -\min & \sum_{i \in V} c_i p_i \\ -\text{s.t.} & \sum_{j: (i, j) \in E} f^+_{ij} - f^-_{ij} - \sum_{j: (j, i) \in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \forall \, i \in V,\\ -& f^+_{ij} - f^-_{ij} = b_{ij}(\theta_i - \theta_j), & \forall \, (i, j) \in E, \\ -& f^{abs}_{ij} = f^+_{ij} + f^-_{ij}, & \forall \, (i, j) \in E, \\ - & f_{ij}^{abs} \leq f_{ij}^{\max} & \forall (i, j) \in E,\\ - & p_{i}^{\min } x_i \leq p_{i} \leq p_{i}^{\max } x_i & \forall i \in V, \\ +\[\begin{split} +\begin{align*} +\min \, & \sum_{i \in V} c_i p_i \\ +\text{s.t.} \, & \sum_{j: (i, j) \in E} f^+_{ij} - f^-_{ij} - \sum_{j: (j, i) \in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \forall \, i \in V\\ + & f^+_{ij} - f^-_{ij} = b_{ij}(\theta_i - \theta_j) & \forall \, (i, j) \in E \\ + & f^{abs}_{ij} = f^+_{ij} + f^-_{ij} & \forall \, (i, j) \in E \\ + & f_{ij}^{abs} \leq f_{ij}^{\max} & \forall \, (i, j) \in E\\ + & p_{i}^{\min } x_i \leq p_{i} \leq p_{i}^{\max } x_i & \forall \, i \in V \\ & \sum_{i \in \mathcal{G}_{\text{gas}}} x_i \leq 2 & \\ & \sum_{i \in \mathcal{G}_{\text{coal}}} x_i \leq 1 & \\ - & p_i \in \mathbb{R}_{\geq 0} & \forall i \in V, \\ - & \theta_i \in \mathbb{R} & \forall i \in V, \\ - & f_{ij} \in \mathbb{R} & \forall (i, j) \in E \\ - & x_i \in \{0, 1\} & \forall i \in V\\ -\end{array} -\end{align}\end{split}\]
    + & p_i \geq 0 & \forall \, i \in V\\ + & \theta_i \in \mathbb{R} & \forall \,i \in V \\ + & f_{ij} \in \mathbb{R} & \forall \,(i, j) \in E\\ + & x_i \in \{0, 1\} & \forall \,i \in V. +\end{align*} +\end{split}\]

    We then implement the new model using pyomo and solve it for all instances I[0] to I[95], reporting the average objective value across the instances.

    @@ -1584,24 +1676,24 @@

    Strict fossil fuel policy pt.2\(M\) constraints to model the either-or constraint.

    -\[\begin{split}\begin{align} -\begin{array}{llll} -\min & \sum_{i \in V} c_i p_i \\ -\text{s.t.} & \sum_{j: (i, j) \in E} f^+_{ij} - f^-_{ij} - \sum_{j: (j, i) \in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \forall \, i \in V,\\ -& f^+_{ij} - f^-_{ij} = b_{ij}(\theta_i - \theta_j), & \forall \, (i, j) \in E, \\ -& f^{abs}_{ij} = f^+_{ij} + f^-_{ij}, & \forall \, (i, j) \in E, \\ - & f_{ij}^{abs} \leq f_{ij}^{\max} & \forall (i, j) \in E,\\ - & p_{i}^{\min } x_i \leq p_{i} \leq p_{i}^{\max } x_i & \forall i \in V, \\ +\[\begin{split} +\begin{align*} +\min \, & \sum_{i \in V} c_i p_i \\ +\text{s.t.} \, & \sum_{j: (i, j) \in E} f^+_{ij} - f^-_{ij} - \sum_{j: (j, i) \in E} f^+_{ji} - f_{ji}^- = p_i - d_i & \forall \, i \in V\\ + & f^+_{ij} - f^-_{ij} = b_{ij}(\theta_i - \theta_j) & \forall \, (i, j) \in E\\ + & f^{abs}_{ij} = f^+_{ij} + f^-_{ij} & \forall \, (i, j) \in E\\ + & f_{ij}^{abs} \leq f_{ij}^{\max} & \forall \,(i, j) \in E\\ + & p_{i}^{\min } x_i \leq p_{i} \leq p_{i}^{\max } x_i & \forall \,i \in V\\ & \sum_{i \in \mathcal{G}_{\text{gas}}} x_i \leq 2 + (1-y)M_0 & \\ - & \sum_{i \in \mathcal{G}_{\text{coal}}} x_i \leq 1 + (1-y)M_1 & \\ + & \sum_{i \in \mathcal{G}_{\text{coal}}} x_i \leq 1 + (1-y)M_1 & \\ & \sum_{i \in \mathcal{G}_\text{solar}} p_i + \sum_{i \in \mathcal{G}_\text{wind}} p_i + \sum_{i \in \mathcal{G}_\text{hydro}} p_i \leq 1000 + yM_2&\\ - & p_i \in \mathbb{R}_{\geq 0} & \forall i \in V, \\ - & \theta_i \in \mathbb{R} & \forall i \in V, \\ - & f_{ij} \in \mathbb{R} & \forall (i, j) \in E \\ - & x_i \in \{0, 1\} & \forall i \in V\\ + & p_i \geq 0 & \forall \,i \in V\\ + & \theta_i \in \mathbb{R} & \forall \,i \in V \\ + & f_{ij} \in \mathbb{R} & \forall \,(i, j) \in E \\ + & x_i \in \{0, 1\} & \forall \,i \in V\\ & y \in \{0, 1\} &\\ -\end{array} -\end{align}\end{split}\]
    +\end{align*} +\end{split}\]

    We now implement the new model using pyomo and solve it for all instances I[0] to I[95], reporting the average objective value across the instances.

    @@ -1853,20 +1945,20 @@

    Comparing the three models
  • Extra material: Energy dispatch problem
    • -
  • Solving OPF
  • Strict fossil fuel policy pt.1
  • Strict fossil fuel policy pt.2
  • Comparing the three models
    • diff --git a/notebooks/05/05.00.html b/notebooks/05/05.00.html index 2b4c1aa8..38fc18f0 100644 --- a/notebooks/05/05.00.html +++ b/notebooks/05/05.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/05/cutting-stock.html b/notebooks/05/cutting-stock.html index 8cf55bb4..c0aadb03 100644 --- a/notebooks/05/cutting-stock.html +++ b/notebooks/05/cutting-stock.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/05/markowitz_portfolio.html b/notebooks/05/markowitz_portfolio.html index 11ae1825..fcdbc717 100644 --- a/notebooks/05/markowitz_portfolio.html +++ b/notebooks/05/markowitz_portfolio.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/05/milk-pooling.html b/notebooks/05/milk-pooling.html index 02933dbe..aa2ceb9c 100644 --- a/notebooks/05/milk-pooling.html +++ b/notebooks/05/milk-pooling.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/05/ols-regression.html b/notebooks/05/ols-regression.html index abd359cf..b76107e8 100644 --- a/notebooks/05/ols-regression.html +++ b/notebooks/05/ols-regression.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/05/refinery-production.html b/notebooks/05/refinery-production.html index e3bf447f..950f94aa 100644 --- a/notebooks/05/refinery-production.html +++ b/notebooks/05/refinery-production.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/05/svm.html b/notebooks/05/svm.html index 37c0df86..e69814aa 100644 --- a/notebooks/05/svm.html +++ b/notebooks/05/svm.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/06.00.html b/notebooks/06/06.00.html index e71ddf9c..68ca3f70 100644 --- a/notebooks/06/06.00.html +++ b/notebooks/06/06.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/building-insulation.html b/notebooks/06/building-insulation.html index 4691d705..578f12f7 100644 --- a/notebooks/06/building-insulation.html +++ b/notebooks/06/building-insulation.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/economic-order-quantity.html b/notebooks/06/economic-order-quantity.html index 64088410..0cfcb58a 100644 --- a/notebooks/06/economic-order-quantity.html +++ b/notebooks/06/economic-order-quantity.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/investment-wheel.html b/notebooks/06/investment-wheel.html index e5e17e5d..6b2335aa 100644 --- a/notebooks/06/investment-wheel.html +++ b/notebooks/06/investment-wheel.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/kelly-criterion.html b/notebooks/06/kelly-criterion.html index 6a42ea7b..d81f2229 100644 --- a/notebooks/06/kelly-criterion.html +++ b/notebooks/06/kelly-criterion.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/markowitz_portfolio_revisited.html b/notebooks/06/markowitz_portfolio_revisited.html index ce26268d..8a2af21b 100644 --- a/notebooks/06/markowitz_portfolio_revisited.html +++ b/notebooks/06/markowitz_portfolio_revisited.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/optimal-growth-portfolios.html b/notebooks/06/optimal-growth-portfolios.html index 4622b0fd..af17a221 100644 --- a/notebooks/06/optimal-growth-portfolios.html +++ b/notebooks/06/optimal-growth-portfolios.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/06/svm-conic.html b/notebooks/06/svm-conic.html index 0c36f467..ce1920ec 100644 --- a/notebooks/06/svm-conic.html +++ b/notebooks/06/svm-conic.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/07/07.00.html b/notebooks/07/07.00.html index f8c4d8dc..343f213f 100644 --- a/notebooks/07/07.00.html +++ b/notebooks/07/07.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/07/bim-robustness-analysis.html b/notebooks/07/bim-robustness-analysis.html index d45fde2d..120dfb03 100644 --- a/notebooks/07/bim-robustness-analysis.html +++ b/notebooks/07/bim-robustness-analysis.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/07/fleet-assignment.html b/notebooks/07/fleet-assignment.html index 8b6bc197..dfc28ec0 100644 --- a/notebooks/07/fleet-assignment.html +++ b/notebooks/07/fleet-assignment.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/08/08.00.html b/notebooks/08/08.00.html index a492937d..daecda5d 100644 --- a/notebooks/08/08.00.html +++ b/notebooks/08/08.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/08/bim-robust-optimization.html b/notebooks/08/bim-robust-optimization.html index bd020859..11dc4dcb 100644 --- a/notebooks/08/bim-robust-optimization.html +++ b/notebooks/08/bim-robust-optimization.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/09/09.00.html b/notebooks/09/09.00.html index 34ef0618..f9dca5b1 100644 --- a/notebooks/09/09.00.html +++ b/notebooks/09/09.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/09/economicdispatch.html b/notebooks/09/economicdispatch.html index b18e1d35..a7ed0166 100644 --- a/notebooks/09/economicdispatch.html +++ b/notebooks/09/economicdispatch.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/09/markowitz_portfolio_with_chance_constraint.html b/notebooks/09/markowitz_portfolio_with_chance_constraint.html index 43b8bd62..30f31fc5 100644 --- a/notebooks/09/markowitz_portfolio_with_chance_constraint.html +++ b/notebooks/09/markowitz_portfolio_with_chance_constraint.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/09/pop-up_shop.html b/notebooks/09/pop-up_shop.html index 19fb06cb..12287072 100644 --- a/notebooks/09/pop-up_shop.html +++ b/notebooks/09/pop-up_shop.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/09/seafood.html b/notebooks/09/seafood.html index 2dc36bdb..53aa28a0 100644 --- a/notebooks/09/seafood.html +++ b/notebooks/09/seafood.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/10/10.00.html b/notebooks/10/10.00.html index 24d569e1..3af0e704 100644 --- a/notebooks/10/10.00.html +++ b/notebooks/10/10.00.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/10/airline-seating.html b/notebooks/10/airline-seating.html index 58061cf1..2299fd40 100644 --- a/notebooks/10/airline-seating.html +++ b/notebooks/10/airline-seating.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/10/ccg.html b/notebooks/10/ccg.html index 9dc49632..83b8c9c0 100644 --- a/notebooks/10/ccg.html +++ b/notebooks/10/ccg.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/10/farmer.html b/notebooks/10/farmer.html index e62c6bcc..8efdff52 100644 --- a/notebooks/10/farmer.html +++ b/notebooks/10/farmer.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/10/opf-ldr.html b/notebooks/10/opf-ldr.html index 35ac4e47..87e52e7b 100644 --- a/notebooks/10/opf-ldr.html +++ b/notebooks/10/opf-ldr.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/10/opf-wind-curtailment.html b/notebooks/10/opf-wind-curtailment.html index 1bf9ec2e..e3e91707 100644 --- a/notebooks/10/opf-wind-curtailment.html +++ b/notebooks/10/opf-wind-curtailment.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/appendix/appendix.html b/notebooks/appendix/appendix.html index b7694987..7893bbc2 100644 --- a/notebooks/appendix/appendix.html +++ b/notebooks/appendix/appendix.html @@ -220,7 +220,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/appendix/functional-programming-pyomo.html b/notebooks/appendix/functional-programming-pyomo.html index d5e09588..98be3d50 100644 --- a/notebooks/appendix/functional-programming-pyomo.html +++ b/notebooks/appendix/functional-programming-pyomo.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/notebooks/appendix/pyomo-style-guide.html b/notebooks/appendix/pyomo-style-guide.html index 93b13ede..b8b4282d 100644 --- a/notebooks/appendix/pyomo-style-guide.html +++ b/notebooks/appendix/pyomo-style-guide.html @@ -222,7 +222,6 @@ -
  • Forex Arbitrage
    • diff --git a/search.html b/search.html index 354104c8..de6fe2b6 100644 --- a/search.html +++ b/search.html @@ -219,7 +219,6 @@ -
  • Forex Arbitrage
    • diff --git a/searchindex.js b/searchindex.js index abbe7e30..c71f4f84 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["genindex", "intro", "notebooks/01/01.00", "notebooks/01/production-planning", "notebooks/01/production-planning-advanced", "notebooks/01/production-planning-basic", "notebooks/02/02.00", "notebooks/02/L1-regression-wine-quality", "notebooks/02/bim", "notebooks/02/bim-dual", "notebooks/02/bim-fractional", "notebooks/02/bim-maxmin", "notebooks/02/bim-rawmaterialplanning", "notebooks/02/lad-regression", "notebooks/02/mad-portfolio-optimization", "notebooks/02/multiproductionfaciliity_worstcase", "notebooks/03/03.00", "notebooks/03/bim-perturbed", "notebooks/03/bim-production-revisited", "notebooks/03/cryptarithms", "notebooks/03/facility-location", "notebooks/03/job-shop-scheduling", "notebooks/03/machine-scheduling", "notebooks/03/maintenance-planning", "notebooks/03/recharging-electric-vehicle", "notebooks/03/shift-scheduling", "notebooks/03/simple-production-model-gdp", "notebooks/03/strip-packing", "notebooks/04/04.00", "notebooks/04/cryptocurrency-arbitrage", "notebooks/04/dinner-seat-allocation", "notebooks/04/forex-arbitrage", "notebooks/04/gasoline-distribution", "notebooks/04/graph-coloring", "notebooks/04/mincost-flow", "notebooks/04/power-network", "notebooks/05/05.00", "notebooks/05/cutting-stock", "notebooks/05/markowitz_portfolio", "notebooks/05/milk-pooling", "notebooks/05/ols-regression", "notebooks/05/refinery-production", "notebooks/05/svm", "notebooks/06/06.00", "notebooks/06/building-insulation", "notebooks/06/economic-order-quantity", "notebooks/06/investment-wheel", "notebooks/06/kelly-criterion", "notebooks/06/markowitz_portfolio_revisited", "notebooks/06/optimal-growth-portfolios", "notebooks/06/svm-conic", "notebooks/07/07.00", "notebooks/07/bim-robustness-analysis", "notebooks/07/fleet-assignment", "notebooks/08/08.00", "notebooks/08/bim-robust-optimization", "notebooks/09/09.00", "notebooks/09/economicdispatch", "notebooks/09/markowitz_portfolio_with_chance_constraint", "notebooks/09/pop-up_shop", "notebooks/09/seafood", "notebooks/10/10.00", "notebooks/10/airline-seating", "notebooks/10/ccg", "notebooks/10/farmer", "notebooks/10/opf-ldr", "notebooks/10/opf-wind-curtailment", "notebooks/appendix/appendix", "notebooks/appendix/functional-programming-pyomo", "notebooks/appendix/pyomo-style-guide"], "filenames": ["genindex.md", "intro.md", "notebooks/01/01.00.md", "notebooks/01/production-planning.ipynb", "notebooks/01/production-planning-advanced.ipynb", "notebooks/01/production-planning-basic.ipynb", "notebooks/02/02.00.md", "notebooks/02/L1-regression-wine-quality.ipynb", "notebooks/02/bim.ipynb", "notebooks/02/bim-dual.ipynb", "notebooks/02/bim-fractional.ipynb", "notebooks/02/bim-maxmin.ipynb", "notebooks/02/bim-rawmaterialplanning.ipynb", "notebooks/02/lad-regression.ipynb", "notebooks/02/mad-portfolio-optimization.ipynb", "notebooks/02/multiproductionfaciliity_worstcase.ipynb", "notebooks/03/03.00.md", "notebooks/03/bim-perturbed.ipynb", "notebooks/03/bim-production-revisited.ipynb", "notebooks/03/cryptarithms.ipynb", "notebooks/03/facility-location.ipynb", "notebooks/03/job-shop-scheduling.ipynb", "notebooks/03/machine-scheduling.ipynb", "notebooks/03/maintenance-planning.ipynb", "notebooks/03/recharging-electric-vehicle.ipynb", "notebooks/03/shift-scheduling.ipynb", "notebooks/03/simple-production-model-gdp.ipynb", "notebooks/03/strip-packing.ipynb", "notebooks/04/04.00.md", "notebooks/04/cryptocurrency-arbitrage.ipynb", "notebooks/04/dinner-seat-allocation.ipynb", "notebooks/04/forex-arbitrage.ipynb", "notebooks/04/gasoline-distribution.ipynb", "notebooks/04/graph-coloring.ipynb", "notebooks/04/mincost-flow.ipynb", "notebooks/04/power-network.ipynb", "notebooks/05/05.00.md", "notebooks/05/cutting-stock.ipynb", "notebooks/05/markowitz_portfolio.ipynb", "notebooks/05/milk-pooling.ipynb", "notebooks/05/ols-regression.ipynb", "notebooks/05/refinery-production.ipynb", "notebooks/05/svm.ipynb", "notebooks/06/06.00.md", "notebooks/06/building-insulation.ipynb", "notebooks/06/economic-order-quantity.ipynb", "notebooks/06/investment-wheel.ipynb", "notebooks/06/kelly-criterion.ipynb", "notebooks/06/markowitz_portfolio_revisited.ipynb", "notebooks/06/optimal-growth-portfolios.ipynb", "notebooks/06/svm-conic.ipynb", "notebooks/07/07.00.md", "notebooks/07/bim-robustness-analysis.ipynb", "notebooks/07/fleet-assignment.ipynb", "notebooks/08/08.00.md", "notebooks/08/bim-robust-optimization.ipynb", "notebooks/09/09.00.md", "notebooks/09/economicdispatch.ipynb", "notebooks/09/markowitz_portfolio_with_chance_constraint.ipynb", "notebooks/09/pop-up_shop.ipynb", "notebooks/09/seafood.ipynb", "notebooks/10/10.00.md", "notebooks/10/airline-seating.ipynb", "notebooks/10/ccg.ipynb", "notebooks/10/farmer.ipynb", "notebooks/10/opf-ldr.ipynb", "notebooks/10/opf-wind-curtailment.ipynb", "notebooks/appendix/appendix.md", "notebooks/appendix/functional-programming-pyomo.ipynb", "notebooks/appendix/pyomo-style-guide.md"], "titles": ["Index", "Hands-On Optimization with Python", "1. Mathematical Optimization", "A first production planning problem", "A data-driven Pyomo Model", "A basic Pyomo model", "2. Linear Optimization", "Extra material: Wine quality prediction with \\(L_1\\) regression", "BIM production", "Dual of the BIM production problem", "BIM production variants", "BIM production for worst case", "BIM production using demand forecasts", "Least Absolute Deviation (LAD) Regression", "Mean Absolute Deviation (MAD) portfolio optimization", "Extra material: Multi-product facility production", "3. Mixed Integer Linear Optimization", "BIM production with perturbed data", "BIM production revisited", "Extra material: Cryptarithms puzzle", "Facility location problem", "Extra material: Job shop scheduling", "Machine Scheduling", "Extra material: Maintenance planning", "Recharging strategy for an electric vehicle", "Workforce shift scheduling", "Production model using disjunctions", "Extra material: Strip packing", "4. Network Optimization", "Cryptocurrency arbitrage search", "Dinner seating arrangement", "Forex Arbitrage", "Gasoline distribution", "Scheduling as a graph coloring problem", "Minimum-Cost Flow Problem", "Extra material: Energy dispatch problem", "5. Convex Optimization", "Extra Material: Cutting Stock", "Markowitz portfolio optimization", "Milk pooling and blending", "Ordinary Least Squares (OLS) Regression", "Extra material: Refinery production and shadow pricing with CVXPY", "Support Vector Machines for Binary Classification", "6. Conic Optimization", "Optimal Design of Multilayered Building Insulation", "Economic Order Quantity", "Extra material: Luenberger\u2019s Investment Wheel", "The Kelly Criterion", "Markowitz portfolio optimization revisited", "Extra material: Optimal Growth Portfolios with Risk Aversion", "Training Support Vector Machines with Conic Optimization", "7. Accounting for Uncertainty: Optimization Meets Reality", "Robustness analysis of BIM production plan via simulations", "Fleet assignment problem", "8. Robust Optimization - Single Stage Problems", "Robust BIM microchip production problem", "9. Stochastic Optimization - Single Stage Problems", "Economic dispatch in energy systems", "Markowitz portfolio optimization with chance constraints", "Pop-up shop", "Stock optimization for seafood distribution center", "10. Two-Stage Problems", "Airline seat allocation problem", "Two-stage Production Planning", "Extra: The farmer\u2019s problem and its variants", "Optimal power flow problem with recourse actions", "Extra: Two-stage energy dispatch optimization with wind curtailment", "Appendix: Working with Pyomo", "Functional Programming with Pyomo", "Pyomo style guide"], "terms": {"welcom": [1, 5, 69], "thi": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69], "repositori": [1, 7, 25, 55, 57], "companion": [1, 5, 6, 16, 28, 36, 43, 54, 56, 61], "notebook": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 47, 48, 49, 50, 52, 55, 57, 60, 63, 65, 66, 67, 68], "book": [1, 8, 15, 20, 22, 35, 42, 46, 47, 50, 57, 63, 65, 66, 69], "which": [1, 2, 3, 4, 5, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 35, 36, 37, 38, 39, 40, 42, 44, 45, 47, 48, 50, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "publish": 1, "cambridg": [1, 20], "univers": [1, 20, 25, 33], "press": [1, 20, 21], "2024": [1, 20], "introduc": [1, 2, 3, 4, 5, 9, 10, 11, 13, 18, 20, 21, 22, 23, 26, 27, 30, 32, 34, 35, 37, 39, 40, 42, 45, 46, 47, 49, 50, 57, 59, 62, 63, 66, 69], "concept": [1, 45, 46, 49, 50, 68], "tool": [1, 2, 5, 8, 13, 29, 30, 32, 40, 50, 53], "mathemat": [1, 5, 15, 20, 23, 29, 30, 32, 36, 37, 39, 44, 48, 49, 53, 59, 69], "exampl": [1, 2, 3, 4, 5, 6, 7, 8, 12, 16, 19, 20, 22, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 36, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 59, 60, 61, 62, 63, 64, 66, 69], "from": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 30, 31, 32, 33, 34, 35, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 61, 62, 63, 64, 65, 66, 68, 69], "rang": [1, 5, 7, 8, 12, 13, 14, 20, 21, 23, 24, 25, 27, 30, 33, 37, 38, 39, 42, 45, 46, 47, 48, 50, 52, 53, 55, 57, 58, 60, 63, 65, 66, 68, 69], "disciplin": [1, 41, 46, 47, 49], "The": [1, 2, 3, 6, 7, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 46, 48, 49, 52, 53, 55, 57, 58, 60, 62, 65, 66, 67, 69], "goal": [1, 2, 3, 5, 8, 18, 22, 27, 29, 30, 31, 33, 34, 35, 42, 57, 62, 66, 68], "ar": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 40, 42, 44, 45, 46, 47, 49, 50, 51, 52, 53, 55, 57, 59, 62, 63, 64, 65, 66, 68, 69], "provid": [1, 4, 5, 7, 8, 12, 13, 14, 15, 18, 22, 23, 24, 29, 30, 31, 32, 35, 39, 40, 42, 45, 46, 47, 48, 49, 50, 57, 59, 62, 68, 69], "foundat": 1, "learn": [1, 7, 13, 30, 40, 42, 64], "demonstr": [1, 4, 5, 7, 8, 22, 24, 25, 32, 35, 37, 39, 41, 42, 45, 46, 49, 50, 57, 62, 63, 65, 66, 67, 68], "practic": [1, 4, 5, 18, 27, 29, 32, 35, 37, 39, 42, 45, 46, 49, 50, 53, 57, 66, 68, 69], "reader": [1, 4, 7, 29, 33, 63, 68], "develop": [1, 3, 4, 5, 26, 29, 32, 37, 39, 42, 45, 50, 69], "skill": [1, 2, 26], "need": [1, 2, 3, 4, 5, 8, 9, 10, 12, 14, 16, 18, 21, 23, 24, 25, 26, 27, 29, 30, 33, 35, 37, 39, 42, 43, 45, 50, 52, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 68, 69], "build": [1, 4, 5, 18, 20, 25, 29, 37, 42, 43, 50, 52, 55, 62, 63, 66, 68, 69], "model": [1, 2, 6, 8, 9, 10, 16, 22, 28, 30, 33, 34, 36, 39, 43, 51, 52, 54, 56, 57, 58, 59, 60, 61, 63, 65, 66, 67], "solv": [1, 2, 3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 61, 64, 65, 66, 68, 69], "problem": [1, 2, 4, 5, 6, 13, 14, 15, 16, 19, 21, 26, 28, 36, 40, 42, 43, 49, 50, 51, 58, 66, 69], "state": [1, 3, 11, 18, 24, 29, 32, 35, 39, 55, 59, 68, 69], "art": [1, 7, 39], "languag": [1, 5, 41, 69], "solver": [1, 28, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 53, 58, 59, 62, 63, 64, 65], "make": [1, 2, 4, 8, 12, 14, 15, 16, 18, 21, 23, 24, 25, 29, 30, 32, 33, 35, 36, 37, 41, 55, 57, 58, 63, 65, 68, 69], "extens": [1, 7, 20, 23, 26, 27, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 50, 55, 57, 58, 60, 68, 69], "pyomo": [1, 2, 3, 6, 16, 28, 36, 37, 39, 40, 43, 46, 47, 54, 56, 58, 59, 61, 62, 63, 64], "complet": [1, 3, 18, 21, 22, 23, 29, 31, 39, 42, 45, 49, 50, 53, 62, 63, 66], "versatil": 1, "packag": [1, 3, 20, 21, 22, 27, 29, 30, 31, 35, 44, 46, 47, 49, 57, 65], "ecosystem": 1, "mean": [1, 5, 6, 8, 9, 12, 13, 17, 18, 25, 29, 30, 34, 35, 37, 38, 40, 42, 45, 46, 47, 52, 53, 57, 58, 60, 62, 65, 66, 68], "decis": [1, 2, 3, 4, 6, 8, 9, 13, 14, 16, 17, 18, 21, 22, 23, 24, 26, 27, 30, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 59, 60, 61, 62, 63, 65, 66, 68, 69], "variabl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 55, 57, 59, 60, 61, 62, 63, 64, 65, 66, 68], "constraint": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 46, 47, 48, 49, 50, 52, 53, 55, 56, 57, 59, 60, 64, 65, 66, 68], "object": [1, 2, 3, 4, 6, 7, 8, 9, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "transform": [1, 4, 5, 8, 13, 17, 18, 23, 26, 37, 42, 47, 50, 69], "gener": [1, 2, 3, 4, 5, 6, 7, 8, 11, 14, 16, 19, 20, 21, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 35, 38, 44, 45, 48, 50, 51, 55, 57, 58, 60, 66, 68, 69], "solut": [1, 2, 3, 4, 8, 9, 10, 12, 13, 15, 16, 17, 18, 20, 22, 23, 24, 26, 27, 28, 29, 30, 33, 34, 35, 36, 38, 41, 42, 45, 47, 48, 49, 50, 51, 53, 58, 68, 69], "open": [1, 2, 3, 5, 20, 25, 29], "sourc": [1, 3, 5, 20, 29, 30, 32, 35, 37, 39, 53, 66, 69], "commerci": [1, 3, 5, 20, 37, 45, 55], "all": [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 14, 15, 16, 17, 18, 20, 21, 22, 25, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 42, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "can": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "run": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 47, 48, 49, 52, 55, 57, 60, 62, 66], "googl": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "colab": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "A": [1, 2, 6, 8, 13, 14, 15, 16, 17, 18, 21, 22, 23, 25, 26, 28, 29, 31, 32, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 58, 59, 60, 62, 63, 69], "launch": 1, "icon": 1, "appear": [1, 3, 4, 5, 7, 10, 13, 18, 19, 26, 29, 30, 31, 37, 39, 42, 44, 46, 48, 50, 53, 59, 62, 68, 69], "top": [1, 6, 8, 13, 16, 21, 22, 29, 37, 38, 40, 42, 47, 48, 50, 58, 63], "page": 1, "look": [1, 9, 12, 14, 27, 29, 50, 57, 63], "rocket": 1, "indic": [1, 4, 8, 11, 13, 16, 18, 22, 23, 26, 27, 29, 32, 35, 37, 39, 42, 44, 49, 50, 53, 60, 62, 63, 65, 66, 69], "an": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 57, 58, 59, 62, 63, 65, 66, 67, 68, 69], "execut": [1, 7, 21, 22, 29, 30, 31, 35, 59], "document": [1, 55, 69], "select": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 41, 48, 49, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "reopen": 1, "cell": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 65, 66, 68], "insid": [1, 29, 68], "perform": [1, 5, 19, 20, 21, 22, 27, 29, 30, 46, 47, 51, 55, 59, 60, 62, 63, 64, 65, 66, 68], "ani": [1, 3, 4, 5, 6, 8, 13, 14, 15, 16, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 35, 37, 42, 45, 47, 49, 50, 59, 60, 62, 63, 64, 65, 68, 69], "necessari": [1, 4, 27, 28, 29, 33, 39, 51, 57, 68], "instal": [1, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 53, 58, 59, 63, 64, 65, 68], "code": [1, 4, 5, 7, 8, 9, 12, 13, 17, 18, 19, 20, 24, 25, 27, 29, 30, 42, 45, 47, 49, 50, 63, 68], "within": [1, 5, 15, 20, 27, 29, 35, 55, 59, 63, 66, 68], "your": [1, 20, 23, 39, 46, 62, 64], "journei": [1, 29], "first": [1, 2, 4, 5, 6, 8, 9, 10, 12, 14, 15, 18, 21, 23, 24, 26, 27, 28, 29, 30, 31, 32, 34, 35, 37, 38, 39, 42, 44, 45, 48, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "chapter": [1, 2, 5, 6, 15, 16, 18, 20, 22, 28, 36, 40, 43, 46, 48, 51, 53, 54, 56, 61, 63, 65, 66], "we": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "seek": [1, 2, 9, 42, 50, 62, 66], "feedback": [1, 69], "If": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 39, 42, 45, 46, 47, 48, 50, 52, 55, 57, 58, 60, 62, 63, 65, 66, 68, 69], "you": [1, 4, 8, 15, 20, 23, 27, 29, 35, 38, 39, 45, 48, 50, 55, 57, 58, 63, 64, 66, 69], "encount": [1, 4, 15, 58], "issu": [1, 14, 19, 21, 27, 29, 30, 37, 39, 44, 63, 65], "have": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "suggest": [1, 7, 25, 37, 49, 59, 69], "how": [1, 2, 3, 4, 8, 13, 17, 18, 20, 22, 23, 24, 25, 26, 27, 29, 30, 31, 37, 38, 39, 41, 42, 44, 45, 47, 49, 50, 51, 55, 58, 59, 60, 62, 63, 64, 65, 66, 67, 68], "better": [1, 27, 28, 29, 30, 32, 39, 42, 48, 51, 53, 63, 66, 69], "pleas": [1, 50, 65], "link": [1, 27, 29, 31, 39, 45, 53], "everi": [1, 2, 4, 5, 13, 14, 20, 21, 27, 29, 33, 34, 35, 37, 39, 47, 55, 57, 62, 63, 65, 66, 68], "github": [1, 20, 25, 29], "cat": [1, 14, 49], "group": [1, 6, 8, 25, 32, 52, 57], "research": [1, 21, 27, 29, 37, 39, 45, 63], "educ": 1, "who": [1, 4, 14, 25, 30, 32, 37], "came": 1, "togeth": [1, 4, 18, 27, 42, 57, 59, 63, 65, 68, 69], "common": [1, 2, 4, 5, 8, 15, 20, 21, 22, 27, 29, 31, 32, 37, 39, 42, 45, 50, 62, 68, 69], "purpos": [1, 4, 21, 22, 35, 42, 45, 57, 62, 63, 65, 68], "materi": [1, 3, 4, 5, 6, 8, 16, 17, 18, 26, 28, 29, 36, 39, 43, 44, 52, 63, 69], "our": [1, 2, 8, 12, 18, 21, 22, 25, 26, 29, 30, 31, 35, 36, 42, 44, 50, 51, 53, 55, 57, 58, 59, 63, 65, 66], "classroom": 1, "teach": [1, 64, 69], "hopefulli": [1, 39, 63], "find": [1, 2, 3, 7, 9, 13, 14, 15, 20, 22, 23, 24, 27, 28, 30, 31, 32, 33, 34, 37, 39, 42, 44, 46, 49, 53, 55, 57, 59, 60, 63, 64, 65, 68], "other": [1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 35, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 55, 59, 62, 63, 66, 68, 69], "most": [1, 5, 6, 9, 15, 19, 21, 22, 23, 27, 29, 31, 32, 34, 35, 37, 39, 42, 47, 49, 53, 55, 57, 60, 63, 69], "importantli": [1, 57, 65], "those": [1, 3, 4, 8, 11, 12, 21, 27, 34, 42, 50, 60, 62, 63, 65], "entri": [1, 31, 39, 42, 50, 62, 69], "world": [1, 2, 31, 36, 39, 46, 49, 51, 62], "data": [1, 3, 5, 12, 16, 20, 21, 24, 26, 27, 29, 30, 34, 39, 51, 52, 55, 59, 60, 63, 68], "rich": 1, "applic": [1, 2, 4, 5, 7, 22, 25, 26, 27, 29, 31, 32, 37, 39, 42, 44, 45, 49, 50, 53, 57, 63, 65, 68, 69], "krzysztof": 1, "postek": 1, "boston": 1, "consult": [1, 45, 64], "formerli": 1, "tu": 1, "delft": 1, "alessandro": 1, "zocca": 1, "vu": 1, "amsterdam": [1, 62], "joaquim": 1, "gromicho": 1, "ortec": 1, "jeffrei": 1, "kantor": 1, "notr": 1, "dame": 1, "wish": [1, 4, 14, 21, 39, 42, 62], "cite": [1, 29, 39, 45, 49], "work": [1, 5, 6, 8, 11, 20, 22, 25, 29, 30, 31, 37, 42, 45, 46, 47, 49, 50, 57, 65, 68, 69], "postekzocca2024": 1, "titl": [1, 5, 14, 20, 22, 35, 37, 40, 42, 46, 49, 50, 53, 62, 68], "author": 1, "year": [1, 12, 18, 45, 49, 52, 64, 69], "onlin": [1, 29, 39, 66], "url": [1, 37], "http": [1, 7, 20, 29, 31, 35, 37, 39, 42, 44, 45, 46, 47, 48, 49, 50, 57, 64, 65, 66, 68], "mobook": [1, 29, 35, 42, 50, 57, 65, 66], "io": [1, 12, 18, 20, 31, 52], "mo": [1, 29, 35, 42, 50, 57, 65, 66], "broad": 2, "term": [2, 3, 4, 13, 17, 18, 20, 21, 25, 26, 29, 32, 33, 37, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 57, 59, 60, 63, 65, 66], "describ": [2, 3, 4, 6, 8, 12, 18, 21, 22, 23, 24, 25, 27, 29, 32, 34, 35, 37, 38, 41, 42, 44, 45, 48, 49, 57, 58, 59, 62, 66, 69], "wai": [2, 3, 4, 5, 8, 11, 13, 16, 20, 21, 22, 23, 28, 29, 30, 31, 32, 34, 35, 38, 45, 46, 48, 49, 50, 53, 57, 58, 63, 65, 66, 68, 69], "them": [2, 4, 5, 8, 9, 16, 18, 24, 29, 30, 36, 38, 39, 49, 53, 55, 58, 62, 63, 65, 66], "us": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20, 21, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 34, 35, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 59, 61, 64, 65, 66, 67], "dedic": [2, 55], "algorithm": [2, 3, 27, 29, 33, 45, 53, 63], "consist": [2, 5, 7, 13, 14, 20, 21, 25, 29, 31, 33, 35, 40, 42, 49, 50, 62, 68, 69], "three": [2, 4, 18, 21, 22, 25, 27, 31, 39, 49, 51, 59, 60, 62, 64, 68], "part": [2, 3, 21, 37, 42, 45, 50, 55, 63, 64, 65], "correspond": [2, 3, 4, 8, 9, 11, 12, 13, 14, 17, 18, 19, 22, 23, 25, 27, 29, 33, 35, 37, 42, 44, 45, 48, 50, 53, 55, 60, 62, 63, 65, 66, 69], "action": [2, 61, 66], "choic": [2, 4, 15, 21, 24, 26, 35, 37, 39, 42, 44, 57, 68, 69], "whether": [2, 8, 22, 24, 26, 27, 29, 31, 33, 35, 36, 44, 45, 53, 57, 63, 66], "new": [2, 4, 5, 7, 8, 13, 17, 21, 23, 25, 26, 27, 29, 30, 32, 35, 37, 39, 41, 42, 45, 48, 55, 59, 62, 63, 66, 68, 69], "manufactur": [2, 8, 17, 27, 34, 41, 63], "facil": [2, 6, 16, 21, 26, 27, 34, 39, 45], "suppli": [2, 4, 30, 32, 34, 35, 39, 57, 66], "rout": [2, 29, 51, 53, 62], "price": [2, 3, 4, 10, 11, 12, 18, 29, 31, 32, 37, 39, 49, 52, 59, 60, 62, 63, 64, 68, 69], "should": [2, 3, 8, 14, 15, 18, 22, 23, 24, 25, 26, 29, 34, 36, 37, 39, 42, 47, 50, 53, 55, 57, 59, 63, 64, 65, 66, 68, 69], "sell": [2, 3, 11, 15, 18, 26, 29, 31, 32, 38, 39, 59, 60, 62, 63, 64], "product": [2, 5, 6, 16, 20, 23, 34, 35, 36, 37, 39, 42, 45, 46, 50, 51, 54, 57, 61, 64, 65, 66], "function": [2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 20, 21, 22, 25, 26, 27, 29, 30, 32, 33, 34, 36, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 67, 69], "evalu": [2, 5, 13, 42, 50, 63], "specif": [2, 3, 5, 6, 8, 10, 13, 14, 15, 17, 20, 25, 29, 30, 34, 35, 37, 38, 39, 41, 42, 45, 48, 53, 55, 57, 59, 60, 62, 63, 65, 67, 68, 69], "i": [2, 5, 6, 7, 8, 9, 12, 13, 14, 15, 16, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 40, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 60, 62, 63, 65, 66, 69], "e": [2, 5, 7, 18, 19, 21, 22, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 40, 41, 42, 44, 45, 46, 47, 49, 50, 53, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "valu": [2, 3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 60, 62, 63, 65, 66, 68, 69], "earlier": [2, 5, 10, 21, 42, 45, 48, 52, 57, 59], "For": [2, 3, 5, 8, 10, 14, 16, 18, 20, 21, 22, 24, 27, 29, 30, 31, 34, 35, 36, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "specifi": [2, 4, 5, 8, 13, 21, 24, 27, 29, 30, 31, 34, 37, 38, 39, 42, 45, 46, 48, 50, 58, 66, 68, 69], "either": [2, 3, 4, 5, 20, 21, 22, 23, 24, 26, 27, 29, 35, 50, 59, 63, 65, 69], "maxim": [2, 3, 4, 5, 6, 8, 9, 10, 17, 18, 20, 23, 26, 29, 30, 31, 35, 37, 38, 39, 41, 46, 47, 48, 49, 55, 58, 60, 62, 63, 64, 68, 69], "minim": [2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 18, 20, 21, 22, 24, 25, 27, 29, 33, 34, 35, 37, 40, 42, 44, 45, 50, 52, 53, 55, 57, 64, 65, 66, 69], "In": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 18, 20, 21, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69], "oper": [2, 3, 15, 21, 22, 27, 29, 35, 37, 39, 41, 42, 44, 45, 53, 59, 62, 63, 65, 66, 68], "cost": [2, 3, 4, 5, 6, 11, 12, 14, 15, 18, 20, 26, 28, 29, 30, 31, 33, 35, 37, 39, 41, 44, 45, 52, 53, 57, 59, 60, 63, 64, 65, 66, 68], "number": [2, 3, 4, 5, 8, 9, 10, 13, 16, 17, 18, 19, 20, 22, 24, 25, 27, 29, 31, 33, 35, 37, 38, 40, 42, 43, 44, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 69], "satisfi": [2, 3, 9, 15, 16, 18, 19, 20, 27, 29, 30, 31, 32, 34, 39, 42, 46, 47, 49, 57, 59, 62, 65], "custom": [2, 20, 21, 29, 32, 37, 39, 42, 51, 57, 62, 69], "restrict": [2, 16, 25, 30, 33, 35, 46, 49, 53, 55, 68, 69], "possibl": [2, 4, 5, 6, 9, 13, 15, 16, 17, 18, 19, 20, 21, 24, 27, 29, 30, 32, 33, 34, 35, 38, 39, 40, 42, 47, 50, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 68, 69], "condit": [2, 3, 8, 15, 18, 23, 24, 26, 27, 29, 30, 42, 44, 50, 55, 59, 64, 68, 69], "must": [2, 3, 5, 19, 21, 23, 26, 27, 29, 31, 32, 35, 38, 39, 44, 53, 63, 64, 65, 66, 68], "requir": [2, 3, 4, 8, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 37, 39, 45, 47, 52, 53, 57, 59, 62, 63, 64, 66, 68, 69], "maximum": [2, 3, 8, 11, 15, 18, 23, 24, 25, 29, 33, 34, 35, 39, 44, 47, 48, 49, 53, 55, 57, 63, 66, 68], "allow": [2, 4, 8, 18, 23, 24, 27, 29, 31, 32, 35, 41, 45, 48, 49, 53, 55, 57, 65, 68], "budget": [2, 12, 37, 52, 63], "demand": [2, 3, 4, 6, 18, 20, 26, 30, 32, 34, 35, 37, 39, 45, 51, 52, 57, 59, 63, 64, 65, 66, 68, 69], "import": [2, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 34, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 58, 59, 60, 63, 64, 69], "met": [2, 35, 57], "capac": [2, 12, 18, 23, 24, 30, 34, 35, 41, 52, 57, 62, 66, 69], "warehous": [2, 18, 45, 51, 60, 69], "exceed": [2, 29, 30, 39, 57], "both": [2, 4, 5, 8, 12, 13, 17, 20, 23, 24, 26, 27, 29, 33, 35, 39, 42, 45, 47, 50, 55, 61, 62, 63], "express": [2, 3, 4, 7, 8, 9, 10, 11, 12, 16, 18, 19, 22, 26, 29, 30, 32, 34, 35, 39, 41, 42, 44, 45, 46, 49, 50, 52, 55, 57, 60, 64, 65, 66, 68, 69], "defin": [2, 4, 5, 8, 9, 12, 13, 14, 16, 20, 22, 25, 26, 27, 32, 33, 35, 37, 39, 40, 41, 42, 45, 46, 50, 53, 55, 57, 62, 63, 65, 66, 68, 69], "feasibl": [2, 5, 8, 9, 17, 20, 30, 35, 37, 41, 44, 46, 47, 49, 53, 60, 63, 65, 66], "region": [2, 8, 20, 32, 35], "set": [2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 52, 53, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "candid": [2, 3, 7, 21, 37], "meet": [2, 3, 5, 12, 18, 22, 25, 29, 30, 32, 35, 37, 39, 43, 52, 57, 59, 65, 66], "best": [2, 5, 7, 8, 29, 30, 35, 44, 57, 63, 66, 69], "global": [2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 46, 48, 52, 55, 57, 60, 62, 66, 69], "optimum": [2, 41, 44], "among": [2, 3, 7, 11, 14, 15, 21, 22, 26, 31, 32, 33, 35, 47, 48, 49, 62, 64, 65, 69], "appli": [2, 4, 5, 18, 24, 35, 37, 39, 42, 44, 45, 49, 65, 66, 68], "type": [2, 3, 4, 5, 6, 8, 12, 16, 17, 19, 21, 25, 29, 30, 35, 37, 42, 45, 50, 52, 55, 57, 65, 66, 68], "relat": [2, 5, 18, 23, 26, 29, 33, 39, 50, 55, 57, 62, 63, 65], "fundament": [2, 14, 39, 68], "question": [2, 8, 15, 22, 42, 45, 51, 59, 64, 65], "translat": [2, 4, 5, 18, 22, 29, 32, 37, 44], "real": [2, 4, 5, 7, 13, 16, 21, 30, 31, 35, 36, 37, 40, 46, 47, 49, 51, 53, 55, 57, 59, 62, 63, 65], "abstract": [2, 4, 8, 68], "represent": [2, 21, 42, 44, 50], "Not": [2, 29], "aspect": [2, 6, 8, 14, 16, 28, 36, 43, 54, 56, 61], "taken": [2, 29, 33, 63, 65, 69], "account": [2, 10, 18, 23, 24, 29, 31, 35, 43, 46, 47, 55, 59, 60, 63, 65, 66, 68], "so": [2, 3, 4, 5, 8, 9, 13, 18, 21, 23, 24, 25, 27, 29, 30, 35, 36, 37, 38, 39, 40, 42, 44, 48, 50, 51, 53, 55, 57, 62, 63, 66, 68], "mani": [2, 3, 4, 8, 16, 19, 20, 22, 23, 27, 29, 30, 31, 33, 35, 37, 42, 45, 46, 47, 49, 50, 52, 53, 55, 59, 62, 63, 65, 66, 69], "made": [2, 3, 10, 12, 18, 20, 24, 29, 52, 59, 63, 66], "step": [2, 3, 4, 8, 9, 12, 14, 15, 18, 21, 29, 45, 46, 52, 53, 62, 63, 68, 69], "typic": [2, 21, 35, 57, 59, 63, 68, 69], "signific": [2, 5, 8, 41, 45, 46, 47, 49, 50], "impact": [2, 7, 39, 51, 64], "approach": [2, 5, 7, 8, 10, 13, 14, 17, 19, 20, 22, 26, 27, 30, 33, 37, 39, 44, 46, 49, 57, 63, 65, 68], "There": [2, 5, 18, 19, 22, 25, 26, 29, 30, 35, 37, 39, 44, 45, 59, 63, 68, 69], "multipl": [2, 3, 12, 15, 18, 27, 29, 31, 32, 34, 37, 39, 69], "equival": [2, 5, 8, 18, 20, 22, 33, 42, 44, 45, 53, 55, 58, 62, 69], "formul": [2, 3, 4, 6, 8, 9, 11, 13, 14, 15, 16, 18, 22, 23, 26, 27, 28, 29, 30, 32, 35, 36, 39, 40, 44, 49, 51, 55, 57, 59, 60, 62, 65, 66, 69], "conceptu": 2, "same": [2, 3, 4, 5, 10, 11, 13, 14, 15, 18, 19, 21, 22, 25, 27, 29, 30, 31, 32, 33, 34, 40, 42, 45, 46, 50, 53, 55, 57, 60, 63, 65, 66, 68, 69], "comput": [2, 4, 5, 7, 8, 14, 15, 18, 22, 23, 29, 30, 31, 35, 37, 39, 42, 45, 46, 49, 50, 52, 59, 62, 64, 65, 66, 68, 69], "complex": [2, 4, 5, 15, 21, 22, 23, 29, 31, 37, 68, 69], "mai": [2, 3, 4, 5, 10, 11, 12, 15, 16, 17, 18, 20, 21, 23, 27, 29, 31, 32, 35, 37, 39, 41, 42, 45, 46, 50, 52, 55, 57, 58, 64, 68], "differ": [2, 3, 5, 8, 10, 11, 12, 13, 14, 15, 17, 18, 19, 27, 29, 30, 32, 33, 34, 35, 37, 39, 40, 41, 42, 44, 45, 48, 49, 50, 51, 53, 55, 57, 59, 60, 63, 64, 65, 66, 69], "interpret": [2, 4, 15, 33, 41], "s": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 43, 44, 45, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "after": [2, 5, 13, 23, 29, 30, 31, 40, 47, 53, 55, 59, 63, 64, 65, 66, 68], "ha": [2, 3, 4, 5, 7, 10, 12, 14, 18, 21, 22, 24, 25, 26, 27, 29, 30, 31, 33, 35, 36, 37, 38, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 65, 66, 68], "back": [2, 5, 13, 23, 29, 31, 42, 50, 63, 68], "origin": [2, 3, 4, 8, 9, 10, 13, 14, 17, 25, 27, 30, 35, 37, 39, 45, 48], "These": [2, 4, 15, 25, 27, 29, 34, 35, 39, 42, 45, 47, 49, 53, 57, 59, 62, 68, 69], "treat": [2, 21, 30, 51, 66], "continu": [2, 12, 18, 22, 23, 39, 42, 44, 50, 52, 60, 66], "process": [2, 4, 23, 29, 39, 41, 42, 45, 50, 53, 55, 68, 69], "sequenti": 2, "final": [2, 4, 5, 12, 14, 21, 22, 23, 29, 39, 45, 62, 65], "turn": [2, 3, 16, 21, 30, 36, 39, 42, 50, 53, 57, 66], "out": [2, 3, 23, 24, 27, 29, 30, 32, 36, 37, 39, 53, 57, 65, 66], "impract": [2, 29], "adjust": [2, 4, 14, 29, 35, 41, 57, 62, 65, 66], "certain": [2, 16, 29, 30, 32, 42, 45, 50, 55, 57, 62, 66], "desir": [2, 3, 12, 18, 25, 30, 36, 52, 68], "properti": [2, 8, 30, 36, 44, 46, 48, 49, 57], "cannot": [2, 8, 12, 16, 21, 22, 25, 29, 33, 35, 44, 52, 53, 60, 62, 63, 66], "effici": [2, 10, 14, 21, 27, 29, 30, 48, 49, 50, 55, 69], "perhap": [2, 19, 32, 37], "re": [2, 69], "includ": [2, 5, 6, 14, 16, 18, 19, 21, 22, 23, 24, 27, 28, 29, 31, 32, 36, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 53, 57, 58, 62, 63, 64, 65, 66, 67, 68, 69], "well": [2, 5, 7, 13, 14, 19, 22, 27, 29, 36, 37, 44, 46, 47, 60, 64, 69], "except": [2, 20, 25, 33, 66, 68, 69], "mathematician": 2, "studi": [2, 15, 21, 27, 37, 39, 44, 57, 60, 69], "alwai": [2, 4, 10, 12, 17, 24, 35, 38, 40, 42, 46, 47, 48, 50, 51, 55, 58, 62, 68], "flaw": 2, "challeng": [2, 8, 19, 27, 31, 37, 39, 42], "follow": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 45, 46, 47, 49, 50, 51, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "given": [2, 3, 4, 5, 7, 8, 9, 11, 13, 14, 15, 17, 18, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 35, 37, 39, 42, 44, 45, 46, 47, 49, 50, 51, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "f": [2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "x": [2, 4, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 18, 20, 23, 24, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 47, 48, 50, 52, 53, 55, 57, 58, 59, 60, 63, 64, 65, 66, 68, 69], "mathbb": [2, 6, 8, 13, 16, 17, 18, 26, 35, 37, 38, 40, 42, 45, 46, 47, 49, 50, 55, 57, 58, 59, 60, 62, 65, 66], "r": [2, 4, 6, 8, 13, 14, 16, 18, 19, 21, 22, 24, 25, 27, 29, 31, 32, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 58, 59, 60, 62, 63, 64, 65, 66, 68], "subseteq": [2, 16, 33, 35, 53], "n": [2, 6, 7, 8, 9, 13, 16, 17, 18, 19, 20, 21, 23, 24, 25, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 40, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 60, 62, 63, 69], "being": [2, 5, 6, 8, 35, 38, 39, 50, 53, 66], "y": [2, 4, 7, 8, 9, 13, 14, 18, 19, 20, 23, 24, 26, 27, 29, 30, 31, 32, 34, 35, 38, 39, 40, 41, 42, 44, 45, 47, 48, 49, 50, 55, 57, 59, 60, 63, 64, 66, 68, 69], "geq": [2, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 60, 62, 63, 65, 66, 68], "foral": [2, 4, 7, 11, 12, 13, 14, 15, 18, 19, 20, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 45, 46, 48, 49, 50, 53, 55, 57, 59, 62, 63, 65, 66], "least": [2, 6, 7, 12, 18, 22, 24, 33, 35, 36, 37, 39, 52, 53, 63, 64], "good": [2, 4, 5, 7, 15, 20, 27, 29, 33, 34, 38, 46, 49, 59, 63, 64, 69], "similarli": [2, 8, 13, 18, 35, 40], "chang": [2, 4, 5, 10, 14, 15, 21, 23, 24, 27, 29, 30, 32, 33, 35, 38, 39, 40, 41, 48, 51, 53, 55, 57, 58, 62, 63, 65, 68, 69], "last": [2, 12, 18, 22, 23, 24, 29, 35, 38, 39, 52, 53, 55, 64, 66], "leq": [2, 3, 4, 8, 9, 10, 11, 12, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58, 59, 62, 63, 65, 66, 69], "case": [2, 3, 4, 5, 7, 8, 13, 16, 20, 21, 25, 26, 27, 29, 30, 32, 37, 40, 42, 46, 47, 49, 50, 55, 57, 59, 60, 66, 68, 69], "refer": [2, 3, 4, 6, 8, 13, 16, 20, 24, 27, 29, 32, 34, 39, 40, 42, 47, 50, 65, 69], "begin": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "align": [2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "min": [2, 6, 7, 8, 9, 11, 13, 14, 16, 18, 20, 22, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 39, 40, 42, 44, 45, 46, 50, 53, 55, 57, 59, 60, 63, 65, 66, 69], "quad": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 20, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 37, 38, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 58, 59, 60, 62, 63, 65, 68, 69], "text": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "t": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "end": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "lead": [2, 14, 17, 18, 19, 20, 21, 22, 26, 29, 36, 39, 42, 44, 50, 55, 57, 63, 66, 69], "techniqu": [2, 7, 11, 13, 21, 22, 23, 26, 32, 42, 45, 49, 57, 63, 65], "introductori": [2, 61], "present": [2, 4, 5, 7, 8, 13, 14, 24, 29, 31, 32, 35, 37, 39, 40, 41, 42, 46, 47, 48, 49, 50, 53, 62, 64, 66, 68, 69], "simpl": [2, 3, 4, 5, 12, 21, 26, 30, 31, 36, 37, 39, 41, 42, 45, 50, 55, 68, 69], "context": [2, 15, 25, 33, 34, 58, 63, 66], "plan": [2, 4, 5, 10, 11, 15, 16, 18, 24, 25, 27, 39, 45, 51, 59, 61], "explain": [2, 7, 35, 39, 50, 57, 66], "structur": [2, 4, 8, 17, 26, 28, 30, 37, 44, 62, 63, 65, 66, 68, 69], "formal": [2, 16], "implement": [2, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 19, 22, 24, 27, 28, 29, 32, 35, 36, 37, 38, 39, 43, 44, 45, 46, 51, 54, 56, 57, 58, 59, 61, 62, 63, 68, 69], "second": [2, 4, 5, 10, 13, 18, 21, 27, 29, 31, 32, 33, 35, 37, 38, 39, 42, 50, 60, 61, 62, 63, 64, 65, 66], "also": [2, 3, 4, 5, 8, 11, 12, 14, 15, 18, 20, 22, 23, 25, 29, 30, 35, 36, 38, 39, 41, 42, 45, 53, 55, 58, 62, 63, 65, 66, 69], "serv": [2, 4, 5, 20, 34, 53, 63], "tutori": [2, 25, 37, 46, 47, 69], "lastli": [2, 3, 62, 63, 66], "discuss": [2, 32, 39, 42, 45, 50, 51, 63], "some": [2, 3, 4, 5, 7, 8, 13, 16, 21, 23, 27, 29, 30, 32, 33, 35, 39, 40, 41, 42, 44, 46, 47, 49, 50, 55, 57, 63, 65, 66, 68, 69], "advanc": [2, 3, 5, 23, 39, 45, 51, 63, 65, 66], "featur": [2, 4, 5, 6, 8, 13, 16, 20, 21, 22, 23, 27, 34, 39, 40, 47, 49, 60, 62, 68, 69], "third": [2, 4, 5, 32], "go": [2, 6, 8, 13, 14, 16, 21, 28, 30, 35, 36, 39, 40, 43, 51, 53, 54, 56, 63, 64, 65, 68], "next": [2, 3, 4, 5, 6, 7, 8, 12, 15, 16, 18, 21, 22, 23, 25, 28, 29, 30, 32, 34, 36, 38, 43, 46, 50, 51, 53, 54, 56, 57, 60, 64, 65, 66], "about": [2, 6, 8, 16, 20, 24, 28, 29, 30, 36, 39, 43, 51, 54, 56, 57, 59, 62, 63, 65], "linear": [2, 3, 5, 7, 8, 10, 11, 12, 13, 14, 15, 17, 19, 20, 22, 23, 26, 29, 31, 35, 36, 39, 40, 41, 55, 57, 60, 61, 62, 63, 65], "compani": [3, 6, 8, 12, 17, 18, 34, 39, 45, 51, 52, 53, 55, 63], "produc": [3, 4, 7, 8, 10, 12, 15, 17, 21, 23, 26, 29, 31, 32, 35, 37, 39, 42, 46, 47, 52, 53, 55, 57, 63, 65, 66, 68], "two": [3, 4, 5, 6, 8, 12, 13, 14, 16, 17, 19, 20, 21, 23, 25, 26, 29, 30, 31, 32, 33, 37, 39, 42, 45, 47, 50, 53, 55, 56, 57, 59, 60, 65, 68, 69], "version": [3, 4, 5, 10, 18, 20, 29, 30, 35, 39, 45, 53, 54, 55, 63, 65, 66, 69], "each": [3, 4, 5, 8, 9, 12, 13, 14, 18, 19, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 42, 46, 47, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "raw": [3, 5, 8, 12, 18, 26, 29, 35, 39, 42, 50, 52, 57, 63, 65, 66], "10": [3, 4, 5, 7, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "per": [3, 8, 10, 12, 14, 18, 23, 24, 25, 26, 29, 32, 34, 37, 44, 45, 52, 60, 63, 64, 65], "gram": [3, 18, 42, 50], "special": [3, 4, 11, 12, 13, 16, 28, 30, 37, 40, 45, 62, 69], "labor": [3, 4, 26, 63, 68], "finish": [3, 12, 18, 21, 22, 23, 26, 37, 52, 53, 69], "u": [3, 4, 5, 14, 18, 23, 29, 34, 42, 44, 45, 46, 49, 50, 53, 55, 57, 63, 68, 69], "higher": [3, 14, 26, 29, 39, 42, 47, 50, 52, 57, 59, 63, 65], "270": [3, 4, 5, 26, 29, 63, 66, 68], "unit": [3, 4, 5, 10, 12, 14, 15, 18, 23, 24, 26, 29, 31, 32, 34, 35, 39, 44, 45, 47, 52, 57, 58, 59, 60, 62, 63, 64, 65, 68], "one": [3, 4, 5, 6, 8, 9, 13, 14, 15, 17, 18, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 62, 63, 64, 65, 66], "hour": [3, 4, 21, 24, 25, 26, 53, 63], "b": [3, 4, 5, 6, 7, 8, 13, 15, 16, 18, 19, 21, 22, 25, 26, 29, 32, 34, 35, 37, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 60, 62, 63, 65, 66, 68, 69], "due": [3, 4, 12, 14, 18, 29, 35, 38, 39, 51, 52, 55, 59, 62, 64, 65, 69], "market": [3, 4, 14, 15, 29, 31, 39, 46, 47, 49, 62, 63, 64], "limit": [3, 5, 12, 18, 20, 21, 24, 25, 26, 29, 32, 35, 37, 39, 41, 44, 46, 49, 52, 57, 63, 65, 66, 69], "40": [3, 4, 5, 7, 24, 25, 26, 29, 32, 33, 37, 44, 45, 46, 59, 62, 63, 64, 68, 69], "week": [3, 25, 33, 62], "v": [3, 4, 5, 14, 20, 21, 24, 29, 30, 33, 34, 35, 39, 42, 45, 46, 50, 53, 57, 63, 65, 66, 68, 69], "lower": [3, 4, 5, 12, 14, 21, 29, 31, 32, 37, 39, 40, 55, 59, 62, 64, 65, 69], "unlimit": [3, 4, 26, 37, 39, 63], "210": [3, 4, 5, 26, 62, 63, 64, 68], "9": [3, 4, 5, 7, 8, 9, 10, 11, 12, 14, 15, 17, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 41, 42, 45, 50, 51, 52, 53, 55, 62, 63, 66, 68], "1": [3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 33, 34, 37, 38, 40, 41, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 61, 63, 65, 66, 68, 69], "summar": [3, 4, 25, 32, 35, 39, 42, 50, 59, 62, 63, 64], "tabl": [3, 4, 18, 21, 22, 24, 26, 27, 31, 42, 46, 52, 53, 55, 59, 60, 62, 64, 69], "g": [3, 4, 5, 8, 14, 18, 20, 22, 27, 29, 30, 31, 32, 33, 34, 35, 39, 40, 42, 44, 45, 50, 53, 55, 60, 65, 66, 68], "hr": [3, 4, 24, 53], "2": [3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 33, 34, 37, 38, 40, 41, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 63, 65, 66, 68, 69], "weekli": [3, 25], "avail": [3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 41, 42, 45, 46, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 66, 68], "inventori": [3, 12, 18, 29, 45, 52, 59, 60], "shelf": 3, "life": [3, 22, 30, 36, 44, 53], "order": [3, 4, 10, 12, 18, 21, 22, 25, 30, 32, 35, 37, 41, 42, 43, 50, 52, 53, 59, 63], "left": [3, 7, 8, 9, 10, 12, 13, 21, 22, 23, 24, 25, 27, 30, 32, 37, 39, 40, 42, 44, 45, 47, 49, 50, 52, 53, 57, 60, 62, 63, 65], "over": [3, 4, 10, 11, 14, 18, 21, 23, 25, 29, 30, 35, 37, 39, 41, 42, 45, 47, 50, 52, 59, 62, 63, 64, 68, 69], "discard": 3, "detail": [3, 8, 20, 25, 42, 44, 50, 59], "resourc": [3, 4, 15, 21, 25, 27, 29, 30, 37, 52, 64, 65, 68], "amount": [3, 4, 12, 15, 16, 17, 18, 21, 22, 25, 29, 31, 32, 34, 38, 39, 51, 52, 55, 57, 58, 60, 63, 64, 65, 69], "80": [3, 4, 5, 26, 29, 32, 35, 41, 47, 49, 50, 63, 64, 66, 68], "50": [3, 4, 5, 9, 14, 18, 24, 26, 29, 31, 32, 35, 37, 39, 42, 44, 45, 52, 55, 60, 62, 63, 64, 66, 68, 69], "100": [3, 4, 5, 10, 18, 19, 20, 22, 24, 26, 29, 31, 32, 33, 35, 37, 39, 41, 42, 45, 47, 49, 50, 52, 55, 57, 60, 62, 63, 64, 65, 66, 68, 69], "want": [3, 14, 17, 18, 20, 29, 32, 33, 38, 40, 42, 48, 55, 58, 62, 63, 69], "its": [3, 5, 7, 8, 9, 13, 14, 20, 22, 30, 34, 40, 42, 45, 50, 55, 63, 65, 68, 69], "gross": [3, 46, 47, 49], "profit": [3, 4, 5, 6, 8, 9, 10, 17, 23, 26, 29, 32, 37, 39, 41, 55, 62, 63, 64, 68, 69], "much": [3, 8, 12, 13, 17, 18, 23, 24, 27, 30, 33, 37, 44, 47, 51, 63, 65, 66], "abov": [3, 4, 6, 8, 11, 12, 13, 14, 17, 18, 22, 23, 24, 29, 30, 32, 33, 35, 37, 39, 40, 44, 45, 46, 48, 49, 50, 52, 55, 57, 60, 62, 63, 65, 69], "optim": [3, 4, 5, 9, 10, 11, 13, 17, 20, 21, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 40, 41, 45, 46, 52, 53, 55, 57, 59, 61, 67, 69], "reformul": [3, 5, 10, 13, 14, 44, 46, 47, 49, 50, 55, 62], "involv": [3, 5, 6, 8, 11, 21, 31, 39, 42, 45, 46, 47, 49], "few": [3, 4, 5, 32, 33, 42, 62, 68], "crucial": [3, 35], "element": [3, 4, 5, 8, 25, 30, 32, 42, 44, 47, 50, 65, 68, 69], "start": [3, 5, 7, 8, 13, 14, 18, 21, 22, 23, 24, 27, 29, 31, 33, 37, 49, 55, 62, 63], "point": [3, 4, 7, 8, 13, 16, 20, 23, 27, 29, 34, 39, 40, 41, 42, 45, 47, 50, 55, 60, 62, 66, 69], "list": [3, 4, 8, 14, 19, 21, 24, 25, 26, 29, 30, 31, 33, 35, 37, 42, 44, 46, 49, 50, 52, 53, 57, 60, 62, 63, 65, 68, 69], "relev": [3, 4, 18, 20, 27, 29, 66, 68, 69], "hand": [3, 4, 8, 9, 17, 20, 24, 25, 29, 30, 31, 42, 50, 55, 57, 59], "quantiti": [3, 8, 11, 12, 18, 34, 35, 37, 39, 43, 51, 52, 55, 63], "modifi": [3, 5, 17, 20, 21, 23, 29, 31, 42, 55, 57, 62, 65, 66, 68, 69], "achiev": [3, 11, 14, 23, 25, 38, 42, 50, 65, 68], "outcom": [3, 15, 32, 42, 46, 50, 57, 59, 63], "while": [3, 5, 8, 9, 12, 14, 17, 18, 20, 21, 24, 25, 26, 29, 33, 34, 35, 37, 42, 48, 49, 50, 51, 52, 53, 55, 57, 59, 62, 63, 65, 66], "stage": [3, 5, 27, 39, 46, 47, 60, 64, 65, 68, 69], "prove": [3, 8], "redund": [3, 69], "later": [3, 4, 5, 15, 21, 24, 27, 45, 47, 66, 69], "creat": [3, 12, 13, 14, 15, 19, 21, 22, 23, 27, 29, 30, 31, 33, 35, 37, 39, 42, 45, 46, 49, 50, 57, 59, 62, 63, 64, 68, 69], "comprehens": [3, 7, 42, 50], "below": [3, 5, 9, 11, 12, 14, 17, 20, 21, 24, 29, 30, 35, 37, 39, 42, 44, 45, 46, 50, 55, 57, 60, 62, 63, 66, 69], "symbol": [3, 14, 22, 29, 31, 32, 49, 59, 68, 69], "descript": [3, 15, 21, 32, 35, 42, 51, 55, 66], "upper": [3, 4, 5, 9, 12, 14, 21, 22, 23, 24, 29, 32, 33, 37, 38, 39, 40, 44, 45, 52, 55, 60, 68, 69], "bound": [3, 4, 5, 9, 14, 19, 21, 22, 23, 24, 26, 29, 30, 31, 33, 37, 38, 39, 42, 44, 53, 55, 57, 63, 64, 66, 68], "known": [3, 4, 5, 7, 13, 14, 19, 21, 22, 23, 27, 33, 38, 39, 40, 42, 44, 45, 47, 49, 50, 53, 57, 59, 63, 64, 65, 66], "x_m": [3, 5, 60], "0": [3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "x_a": [3, 5], "x_b": [3, 5], "y_u": [3, 5], "y_v": [3, 5], "measur": [3, 7, 10, 14, 23, 24, 25, 29, 39, 42, 50, 51], "max": [3, 4, 7, 8, 9, 10, 11, 14, 15, 17, 21, 22, 23, 24, 25, 26, 27, 29, 35, 37, 38, 39, 41, 42, 44, 46, 47, 48, 50, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "equal": [3, 5, 6, 7, 8, 10, 12, 15, 16, 23, 25, 26, 27, 29, 30, 32, 33, 34, 38, 39, 40, 41, 44, 45, 46, 47, 49, 53, 55, 57, 59, 60, 62, 63, 65, 66], "between": [3, 4, 5, 8, 10, 13, 14, 20, 21, 24, 25, 27, 29, 31, 32, 34, 35, 36, 38, 39, 40, 42, 44, 46, 47, 48, 50, 53, 57, 64, 65, 66, 68, 69], "revenu": [3, 4, 5, 10, 11, 41, 59, 62, 64, 68], "written": [3, 4, 5, 15, 42, 45, 58, 59, 62, 68, 69], "As": [3, 4, 5, 8, 14, 18, 21, 25, 29, 30, 31, 39, 42, 45, 46, 50, 53, 59, 60, 63, 66, 69], "shown": [3, 5, 39, 42, 45, 46, 69], "here": [3, 4, 5, 10, 12, 13, 21, 22, 24, 25, 26, 29, 31, 39, 40, 42, 45, 46, 47, 49, 52, 53, 55, 57, 58, 59, 62, 63, 66, 68, 69], "algebra": [3, 5, 19, 41, 42, 45], "combin": [3, 4, 5, 18, 19, 29, 39, 44, 53, 57, 63, 65, 68, 69], "name": [3, 4, 5, 9, 10, 12, 13, 14, 15, 17, 18, 20, 21, 22, 24, 25, 29, 30, 32, 35, 37, 40, 41, 42, 48, 50, 59, 60, 62, 65, 66], "when": [3, 4, 5, 7, 8, 12, 13, 16, 20, 21, 22, 23, 24, 25, 29, 31, 32, 35, 39, 41, 42, 43, 45, 46, 47, 50, 57, 59, 60, 63, 64, 65, 66, 67, 68], "place": [3, 4, 29, 30, 31, 35, 39, 45, 46, 59, 68, 69], "break": [3, 4, 29, 33, 53, 57, 63, 66], "up": [3, 4, 5, 12, 16, 17, 18, 19, 21, 23, 29, 37, 42, 46, 47, 50, 52, 56, 57, 62, 63, 64], "longer": [3, 20, 21, 30, 45, 50, 53, 57, 62, 68], "smaller": [3, 4, 10, 16, 27, 51, 57], "simplifi": [3, 5, 24, 27, 50, 62, 68, 69], "relationship": [3, 5, 13, 22, 24, 25, 27, 29, 31, 44, 45, 46, 69], "inequ": [3, 6, 8, 9, 39, 47, 55, 65], "overal": [3, 8, 15, 25, 39, 44], "now": [3, 4, 5, 7, 8, 12, 14, 18, 20, 21, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 42, 45, 46, 47, 48, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68], "readi": [3, 29, 31, 45, 50, 63], "full": [3, 7, 13, 20, 23, 24, 32, 37, 39, 40, 42, 44, 49, 50, 55, 62, 63, 69], "canon": [3, 6, 38], "nonumb": [3, 4, 30], "textbook": [3, 20, 63, 64], "customari": [3, 8, 50], "under": [3, 14, 15, 18, 20, 25, 26, 52, 57, 59, 62, 63, 64, 68], "clearli": [3, 4, 7, 18, 20, 23, 25, 39, 53, 63, 66], "distinguish": [3, 29, 66, 69], "paramet": [3, 4, 5, 18, 21, 23, 29, 32, 33, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 50, 51, 55, 57, 59, 60, 62, 63, 65, 66, 68], "might": [3, 15, 16, 27, 29, 31, 33, 35, 36, 39, 42, 51, 59, 65, 68], "letter": [3, 19, 45, 63], "throughout": [3, 8, 29, 63, 69], "websit": 3, "howev": [3, 4, 8, 13, 15, 16, 17, 18, 20, 28, 29, 30, 31, 33, 35, 36, 39, 42, 44, 45, 48, 49, 50, 53, 55, 57, 59, 62, 63, 65, 66, 69], "stick": 3, "convent": [3, 5, 6, 8, 57, 65, 66], "onli": [3, 4, 7, 8, 9, 16, 18, 20, 21, 24, 25, 26, 27, 29, 30, 32, 35, 37, 39, 42, 45, 49, 53, 55, 57, 59, 62, 63, 64, 65, 69], "explicitli": [3, 8, 17, 29, 30, 31, 50, 53, 62, 64, 69], "domain": [3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 48, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68], "vector": [3, 6, 8, 11, 12, 13, 35, 36, 38, 40, 41, 43, 58, 62, 63], "minimum": [3, 11, 12, 14, 16, 21, 24, 25, 28, 29, 33, 35, 37, 39, 44, 53, 62, 64], "even": [3, 5, 20, 25, 29, 30, 39, 42, 48, 50, 53, 62, 63, 65, 66], "like": [3, 4, 8, 9, 11, 12, 14, 18, 29, 30, 31, 32, 37, 39, 42, 50, 52, 62, 63, 65, 66], "immedi": [3, 21, 29], "clear": [3, 9, 17, 36, 57, 63, 69], "what": [3, 8, 15, 21, 22, 25, 29, 31, 39, 41, 43, 46, 47, 51, 55, 57, 59, 62, 63, 64, 66, 68], "exactli": [3, 14, 34, 35, 45, 50, 51, 53, 55, 62, 63, 66], "where": [3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 15, 16, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 59, 60, 62, 63, 65, 66, 68, 69], "come": [3, 4, 14, 15, 30, 36, 42, 50, 63], "plai": [3, 8, 36, 46, 50, 53, 63], "thei": [3, 5, 8, 16, 18, 22, 24, 29, 30, 31, 32, 36, 37, 39, 42, 49, 51, 53, 57, 62, 63, 65, 66, 68, 69], "procedur": [3, 37, 55, 63], "long": [3, 4, 14, 16, 22, 25, 29, 46, 47, 60, 63, 69], "standard": [3, 5, 6, 8, 13, 14, 22, 29, 35, 39, 41, 42, 50, 58, 62, 69], "fashion": [3, 4, 53], "practition": [3, 49], "often": [3, 4, 16, 21, 28, 32, 35, 51, 63, 66, 69], "boil": 3, "down": [3, 17, 23, 29, 30, 35, 47, 62, 63, 64], "pass": [3, 4, 5, 18, 20, 21, 24, 28, 42, 50, 68], "softwar": [3, 26], "regardless": [3, 4, 8, 12, 18, 29, 46, 52, 60], "wa": [3, 7, 14, 25, 29, 30, 32, 35, 36, 37, 39, 45, 46, 47, 48, 49, 53, 55, 59, 63, 65], "stori": [3, 46, 47], "behind": 3, "To": [3, 5, 8, 18, 21, 22, 23, 24, 25, 27, 29, 30, 35, 37, 39, 42, 44, 45, 49, 50, 53, 55, 57, 59, 60, 62, 63, 65, 66, 68], "do": [3, 4, 8, 20, 23, 25, 29, 30, 31, 33, 35, 39, 41, 45, 53, 55, 57, 62, 63, 65, 66, 68, 69], "interfac": [3, 4, 5, 14, 45, 69], "commun": [3, 5, 7, 20, 25, 27, 64], "adopt": [3, 8, 26, 32, 42, 44, 47, 55], "python": [3, 5, 8, 13, 17, 20, 21, 25, 29, 30, 32, 37, 40, 41, 42, 45, 50, 53, 57, 66, 68, 69], "base": [3, 5, 7, 12, 13, 19, 21, 26, 29, 32, 35, 40, 41, 42, 47, 49, 50, 51, 52, 57, 63, 65, 68, 69], "carri": [3, 24, 35], "ll": [4, 31, 39], "revisit": [4, 16, 25, 43, 61], "time": [4, 5, 6, 8, 14, 18, 20, 23, 24, 25, 26, 27, 30, 31, 33, 35, 36, 37, 39, 40, 42, 45, 46, 49, 50, 51, 52, 53, 57, 59, 62, 63, 65, 66, 68, 69], "capabl": [4, 7, 26, 39, 55], "scale": [4, 7, 29, 30, 35, 37, 39, 42, 57, 60, 62, 63, 66], "enabl": [4, 5, 28, 29, 45, 50, 68], "vari": [4, 12, 38, 50, 52, 55, 57, 64], "addit": [4, 6, 7, 12, 15, 18, 21, 23, 25, 27, 29, 37, 42, 45, 47, 49, 50, 59, 62, 63, 66, 68, 69], "compon": [4, 5, 8, 13, 14, 18, 22, 26, 38, 45, 50, 58, 69], "index": [4, 5, 8, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 35, 37, 39, 40, 41, 42, 44, 45, 49, 50, 52, 53, 57, 59, 62, 64, 65, 68], "essenti": [4, 22, 29, 30, 37, 42, 50, 53, 55, 63], "scalabl": [4, 6], "maintain": [4, 5, 8, 27, 29, 45, 66, 69], "more": [4, 5, 8, 10, 11, 13, 14, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 31, 32, 35, 37, 38, 39, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "analysi": [4, 7, 8, 12, 13, 21, 29, 32, 39, 42, 46, 47, 50, 51, 53, 55, 62, 69], "examin": [4, 7, 17, 39, 49], "identifi": [4, 5, 16, 18, 24, 27, 29, 31, 34, 37, 39, 42, 44, 45, 47, 50, 62, 66, 69], "underli": [4, 40, 63], "verifi": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 50, 52, 53, 55, 57, 59, 60, 62, 66], "high": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 39, 42, 44, 49, 50, 52, 55, 57, 59, 60, 63, 65, 66, 69], "via": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 50, 51, 55, 57, 60, 66], "appsi": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 52, 55, 60, 66], "modul": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "elsewher": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 38, 48, 52, 55, 57, 60, 66, 69], "assum": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 42, 44, 45, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "cbc": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 37, 39, 41, 42, 52, 53, 55, 59, 60, 62, 63, 64, 65, 66, 68], "been": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 64, 66, 68, 69], "previous": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 38, 47, 48, 50, 52, 53, 55, 57, 60, 62, 65, 66, 68, 69], "solverfactori": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "It": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, 35, 38, 45, 48, 52, 55, 57, 60, 63, 65, 66], "sy": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "pip": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "dev": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66], "null": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66], "highspi": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 41, 52, 53, 55, 59, 60, 62, 63, 64, 65, 66], "environ": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "appsi_high": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 41, 53, 55, 59, 60, 62, 63, 64, 65, 66], "els": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 31, 33, 34, 35, 38, 42, 44, 45, 47, 48, 49, 50, 52, 53, 55, 60, 62, 63, 65, 66, 68, 69], "assert": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60], "basic": [4, 16, 17, 21, 27, 42, 55, 65, 68, 69], "previou": [4, 9, 12, 15, 18, 28, 29, 35, 42, 45, 50, 51, 63], "were": [4, 18, 27, 30, 35, 42, 49, 62, 65], "distinct": [4, 22, 29], "evid": [4, 20], "compris": [4, 21, 23, 25, 31, 37, 40, 59, 68, 69], "abbrevi": [4, 29, 68], "m": [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "factor": [4, 7, 20, 42, 44, 48, 50, 55, 62, 65, 69], "attribut": [4, 5, 7, 14, 29, 35, 37, 45, 65, 68, 69], "built": [4, 20, 57], "librari": [4, 5, 8, 13, 21, 29, 30, 32, 33, 40, 41, 44, 45, 47, 49, 50, 69], "handl": [4, 23, 26, 45, 68], "tabular": [4, 5], "sever": [4, 5, 6, 7, 11, 16, 19, 24, 26, 28, 29, 36, 37, 39, 42, 49, 57, 69], "option": [4, 5, 14, 21, 27, 29, 33, 41, 42, 50, 63, 65, 68, 69], "would": [4, 7, 8, 12, 15, 17, 18, 19, 21, 25, 26, 29, 31, 32, 33, 35, 39, 42, 45, 48, 49, 50, 52, 53, 55, 57, 59, 62, 63, 64, 65, 66, 68], "appropri": [4, 5, 42, 50], "task": [4, 16, 20, 24, 29, 30, 32, 37, 42, 53], "nest": [4, 37, 63, 68, 69], "dictionari": [4, 18, 21, 29, 34, 35, 37, 42, 45, 50, 53, 57, 63, 69], "column": [4, 5, 7, 12, 14, 15, 18, 20, 22, 24, 25, 29, 30, 31, 32, 35, 39, 42, 45, 49, 50, 52, 53, 62, 64, 66, 69], "show": [4, 5, 7, 9, 12, 13, 14, 18, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 40, 42, 44, 45, 47, 48, 49, 51, 52, 53, 55, 57, 59, 60, 62, 63, 66, 68, 69], "repres": [4, 6, 8, 18, 19, 22, 23, 25, 31, 33, 34, 35, 37, 39, 42, 44, 45, 46, 47, 49, 50, 57, 59, 68, 69], "kei": [4, 5, 8, 14, 20, 21, 29, 32, 34, 35, 37, 40, 46, 49, 52, 53, 57, 59, 60, 63, 65, 66, 68, 69], "outermost": 4, "inner": [4, 42, 50], "float": [4, 30, 42, 50, 52, 60, 69], "none": [4, 5, 7, 20, 21, 27, 29, 30, 32, 34, 35, 40, 42, 45, 47, 50, 52, 57, 66, 68], "print": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 22, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "item": [4, 21, 30, 32, 34, 35, 37, 50, 53, 57, 59, 60, 65, 66, 69], "consum": [4, 21, 35, 57, 65, 69], "8s": [4, 29, 49], "row": [4, 5, 7, 8, 22, 29, 31, 35, 42, 53, 63, 66, 69], "label": [4, 7, 13, 15, 24, 27, 29, 31, 32, 34, 35, 37, 39, 40, 41, 42, 44, 45, 50, 52, 53, 57, 60, 66, 69], "4s": 4, "By": [4, 5, 7, 14, 30, 31, 32, 55, 69], "rearrang": [4, 42], "straightforward": [4, 18, 55, 69], "becom": [4, 8, 9, 14, 19, 20, 22, 25, 38, 39, 41, 42, 45, 47, 49, 50, 57, 58, 59, 60, 65, 66], "collect": [4, 5, 6, 7, 11, 13, 15, 20, 21, 27, 31, 32, 33, 35, 40, 42, 50, 62, 63, 69], "compar": [4, 7, 8, 13, 14, 19, 20, 22, 30, 37, 39, 40, 42, 45, 47, 50, 59, 60, 62, 64, 66], "adapt": [4, 15, 49, 57, 62, 63, 65], "let": [4, 7, 8, 9, 11, 12, 15, 19, 20, 21, 25, 27, 29, 30, 33, 34, 35, 37, 38, 39, 44, 45, 47, 50, 52, 55, 57, 58, 59, 62, 63, 65, 68], "cal": [4, 50], "p": [4, 11, 12, 18, 23, 24, 26, 33, 35, 37, 39, 41, 42, 44, 46, 47, 49, 50, 52, 53, 57, 58, 60, 62, 65, 66, 68], "respect": [4, 5, 8, 14, 18, 21, 26, 27, 29, 30, 32, 34, 35, 37, 39, 42, 46, 55, 57, 62, 63, 64, 66, 68], "x_r": [4, 39], "y_p": 4, "denot": [4, 8, 12, 15, 18, 19, 21, 23, 26, 27, 29, 30, 31, 35, 37, 39, 40, 49, 53, 57, 62, 65, 69], "constrain": [4, 12, 15, 16, 29, 35, 39, 45, 46, 49], "zero": [4, 13, 19, 29, 35, 37, 40, 41, 42, 44, 45, 50, 52, 60, 63, 65, 66], "b_r": 4, "b_p": 4, "b_q": 4, "don": [4, 8, 29, 57, 66, 69], "insert": [4, 5, 32, 45, 47], "larger": [4, 8, 20, 27, 30, 33, 37, 42, 47, 50, 53, 59], "than": [4, 5, 8, 10, 12, 15, 16, 17, 20, 21, 23, 24, 25, 27, 29, 30, 32, 33, 35, 37, 39, 42, 46, 47, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 65], "ever": [4, 42, 50], "design": [4, 5, 14, 19, 22, 27, 32, 39, 40, 42, 43, 66, 68], "caus": [4, 5, 39, 68], "ignor": [4, 35, 42, 50, 57], "befor": [4, 13, 20, 21, 22, 30, 33, 39, 40, 42, 46, 53, 57, 59, 60, 62, 63, 65, 66], "sum_": [4, 7, 12, 13, 14, 15, 18, 20, 23, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 57, 58, 59, 62, 63, 65, 66, 69], "c_p": 4, "c_r": 4, "a_": [4, 15, 25, 29, 31, 37], "put": [4, 42, 59, 63, 65], "piec": [4, 21, 37], "flexibl": [4, 32, 35, 36, 63, 68], "particular": [4, 14, 16, 21, 25, 30, 33, 35, 37, 39, 40, 45, 55, 62, 63, 65, 66, 69], "hold": [4, 5, 8, 9, 12, 14, 16, 18, 24, 27, 29, 35, 45, 52, 57, 59, 60, 62, 63, 65, 66], "scienc": [4, 5, 25, 32, 44, 45, 46, 62, 64], "see": [4, 5, 20, 21, 25, 26, 30, 31, 40, 44, 45, 46, 48, 50, 55, 57, 60, 63, 64, 65, 66, 68], "facilit": [4, 8, 14, 69], "construct": [4, 5, 7, 9, 14, 18, 21, 29, 32, 37, 42, 44, 45, 50, 53, 65, 66, 68, 69], "pyo": [4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "initi": [4, 7, 8, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 40, 41, 42, 46, 48, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "assign": [4, 5, 15, 16, 19, 22, 24, 25, 29, 30, 31, 32, 33, 37, 41, 42, 50, 51, 66], "decor": [4, 5, 8, 9, 25, 32, 62], "declar": [4, 5, 35, 65, 66, 69], "return": [4, 5, 7, 8, 9, 10, 11, 12, 13, 15, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "form": [4, 6, 22, 23, 36, 44, 45, 51, 58, 60, 63, 65, 68], "param": [4, 7, 12, 14, 15, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 39, 42, 52, 57, 60, 65, 68, 69], "omit": [4, 69], "emb": 4, "extern": [4, 21, 44, 55], "directli": [4, 5, 7, 14, 22, 23, 32, 35, 44, 45, 50, 59], "effect": [4, 5, 21, 23, 34, 44, 46, 47, 53, 68], "doe": [4, 5, 15, 21, 23, 25, 27, 29, 30, 35, 37, 40, 42, 45, 50, 55, 62, 66], "keep": [4, 12, 18, 25, 33, 35, 39, 50, 53, 63, 65, 69], "shorter": 4, "remov": [4, 6, 8, 15, 29, 37, 42, 53], "overhead": 4, "blur": [4, 29], "boundari": [4, 27, 69], "statement": [4, 30, 32, 62], "edit": [4, 37, 46], "locat": [4, 16, 24, 29, 32, 34, 39, 41, 42, 57, 59, 69], "portion": [4, 49], "therebi": 4, "significantli": [4, 8, 27, 30, 39, 42, 50], "improv": [4, 5, 25, 42, 44, 45, 47, 64], "maintainabi": 4, "concern": [4, 30], "overkil": 4, "small": [4, 5, 8, 12, 25, 26, 29, 30, 31, 33, 34, 37, 39, 41, 63, 65, 69], "consider": [4, 14, 15, 21, 25, 32, 33, 42, 59, 69], "note": [4, 5, 9, 11, 12, 13, 14, 15, 17, 18, 20, 24, 25, 29, 32, 33, 34, 35, 37, 40, 41, 42, 48, 55, 57, 60, 62, 66, 68, 69], "becaus": [4, 8, 11, 18, 21, 25, 27, 29, 30, 32, 35, 37, 39, 42, 45, 50, 53, 55, 57, 63, 65, 68, 69], "take": [4, 5, 7, 8, 9, 11, 16, 17, 18, 21, 22, 23, 24, 27, 29, 31, 33, 35, 38, 39, 42, 45, 47, 48, 50, 51, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68], "logic": [4, 5, 8, 12, 17, 18, 19, 22, 26, 29, 52, 55, 69], "def": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "coeffici": [4, 6, 7, 8, 13, 15, 17, 18, 29, 40, 42, 44, 50, 55, 62, 63], "cp": [4, 41], "cr": 4, "argumentn": 4, "var": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 48, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "fix": [4, 5, 6, 7, 12, 14, 24, 25, 27, 30, 32, 35, 39, 40, 44, 45, 46, 47, 49, 57, 60, 62, 63, 64, 65, 66, 68], "done": [4, 5, 21, 22, 29, 39, 42, 59, 63], "parlanc": 4, "sometim": [4, 36, 46, 58], "call": [4, 8, 24, 27, 29, 31, 32, 35, 38, 39, 40, 42, 48, 49, 50, 53, 59, 62, 66, 68], "rule": [4, 12, 29, 39, 45, 60, 61, 63, 65, 69], "lambda": [4, 18, 19, 20, 21, 22, 25, 27, 29, 31, 35, 39, 42, 44, 46, 47, 49, 50, 52, 53, 55, 57, 60, 65, 66, 68, 69], "argument": [4, 5, 18, 33, 42, 50, 55, 62, 63, 65, 68, 69], "member": [4, 30, 32], "tupl": [4, 5, 8, 21, 25, 29, 37, 68], "quicksum": [4, 12, 18, 30, 33, 52, 55], "accept": [4, 5, 21, 22, 29, 32, 42, 46, 49, 57, 63, 69], "success": [4, 7, 47, 68, 69], "sum": [4, 7, 8, 9, 13, 14, 15, 19, 20, 21, 22, 23, 25, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "sens": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 46, 47, 48, 49, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "Then": [4, 22, 33, 34, 35, 42, 50, 53, 55, 62, 65, 66, 68], "associ": [4, 21, 24, 26, 32, 34, 35, 37, 40, 68, 69], "manner": [4, 32], "block": [4, 25, 37, 39, 44, 45, 46, 47, 49, 50, 55, 63, 68], "materials_us": [4, 68], "report": [4, 14, 18, 29, 30, 35, 37, 39, 42, 50, 52, 55, 57, 60, 62, 68, 69], "access": [4, 21, 32, 35, 45, 57, 68], "iter": [4, 5, 18, 29, 55, 63, 68, 69], "pprint": [4, 69], "nproduct": 4, "nresourc": 4, "3": [4, 7, 11, 12, 14, 15, 18, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 33, 34, 35, 37, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 58, 59, 60, 63, 66, 69], "size": [4, 5, 7, 12, 13, 14, 22, 24, 25, 27, 29, 32, 37, 38, 40, 42, 45, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 69], "dimen": [4, 21, 32, 33], "a_index": 4, "true": [4, 5, 7, 12, 13, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66, 68, 69], "6": [4, 7, 9, 10, 12, 14, 18, 19, 20, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 41, 42, 44, 45, 46, 49, 50, 52, 53, 55, 57, 58, 59, 63, 64, 66], "5": [4, 7, 9, 10, 12, 14, 18, 19, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 48, 49, 50, 52, 53, 55, 58, 63, 65, 66, 68, 69], "default": [4, 5, 8, 14, 21, 24, 25, 32, 33, 39, 42, 50, 66, 69], "mutabl": [4, 14, 25, 27, 32, 57, 60, 69], "fals": [4, 5, 8, 14, 20, 21, 22, 25, 26, 30, 32, 33, 35, 37, 40, 42, 45, 50, 52, 53, 55, 57, 60, 62, 63, 65, 66, 68], "stale": [4, 5, 32, 40], "activ": [4, 5, 25, 26, 29, 32, 35, 55, 66], "bodi": [4, 5, 32, 50], "inf": [4, 5, 63], "12": [4, 5, 7, 8, 9, 10, 11, 12, 14, 15, 17, 18, 20, 21, 23, 24, 25, 27, 29, 30, 31, 32, 35, 37, 38, 42, 45, 47, 48, 50, 53, 55, 59, 62, 63, 69], "2600": [4, 5, 26, 63], "20": [4, 5, 7, 14, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 33, 37, 38, 42, 44, 45, 46, 48, 49, 53, 55, 57, 62, 63, 64, 66, 68, 69], "60": [4, 5, 7, 24, 26, 29, 35, 49, 59, 64, 65, 66, 68], "740": [4, 5, 55, 63, 68], "experienc": [4, 7], "class": [4, 5, 6, 8, 11, 22, 25, 27, 28, 30, 42, 50, 62, 68, 69], "extend": [4, 14, 27, 39, 42, 46, 49, 66, 68, 69], "productionmodel": 4, "inherit": 4, "method": [4, 5, 13, 14, 22, 23, 26, 28, 29, 37, 42, 44, 50, 63, 65, 68, 69], "displai": [4, 5, 7, 8, 12, 13, 14, 15, 18, 22, 24, 25, 27, 29, 30, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 48, 50, 52, 53, 58, 59, 62, 63, 64, 65, 68], "__init__": [4, 35, 42, 50, 68], "self": [4, 35, 42, 50, 68], "instanc": [4, 5, 8, 12, 20, 30, 34, 37, 42, 47, 50, 57, 59, 66, 68, 69], "contain": [4, 5, 13, 20, 25, 26, 29, 35, 37, 40, 42, 50, 55, 57, 66, 68, 69], "inform": [4, 14, 15, 20, 21, 22, 25, 29, 32, 37, 47, 52, 57, 63, 64], "super": 4, "save": [4, 29, 32, 44, 55], "flag": [4, 21, 63, 68], "monitor": [4, 29], "statu": [4, 20, 30, 38, 48, 55, 58, 60, 68], "build_model": [4, 69], "buildth": 4, "integr": [5, 17, 41, 53, 67, 68, 69], "program": [5, 7, 15, 19, 23, 27, 37, 43, 45, 46, 49, 50, 62, 64, 67, 69], "user": [5, 30, 31, 35, 41, 42, 50, 64, 69], "varieti": [5, 35], "project": [5, 39, 42, 45, 50, 67, 69], "ti": 5, "vendor": 5, "constantli": 5, "evolv": 5, "through": [5, 13, 21, 29, 32, 34, 35, 42, 44, 53, 57, 65, 68], "contribut": [5, 7, 14, 19], "parti": [5, 29, 32], "direct": [5, 9, 13, 27, 31, 32, 34, 35, 37, 45, 53, 55], "simplic": [5, 33, 35], "reus": [5, 18, 21], "anoth": [5, 11, 12, 16, 18, 19, 21, 22, 29, 31, 38, 41, 42, 50, 53, 55, 58, 66], "write": [5, 21, 29, 31, 32, 35, 39, 55, 62, 67, 69], "driven": [5, 51], "unfamiliar": [5, 69], "current": [5, 8, 15, 24, 26, 29, 32, 39, 46, 51, 55, 63, 66, 68], "offer": [5, 8, 18, 20, 29, 31, 32, 46, 47, 57, 63, 69], "readabl": [5, 8, 25, 32], "rel": [5, 8, 24, 25, 26, 29, 31, 48, 63, 68], "recent": [5, 29, 35, 37, 39, 44, 46, 47, 49, 69], "intend": [5, 25, 69], "cloud": 5, "person": [5, 7, 21, 45], "session": [5, 20], "mix": [5, 6, 17, 23, 26, 36, 37, 39, 55, 57], "integ": [5, 6, 7, 12, 17, 18, 19, 20, 23, 26, 30, 36, 37, 39, 57, 59, 62, 69], "coin": 5, "OR": [5, 21, 23, 27, 45], "branch": 5, "cut": [5, 20, 23, 26, 27, 36, 45, 57], "suitabl": [5, 22, 33, 42, 50, 68], "glpk": 5, "cplex": [5, 20, 55], "gurobi": [5, 20, 30, 45, 55], "mosek": [5, 38, 45, 47, 48, 49, 50, 57], "check": [5, 8, 29, 31, 38, 39, 45, 48, 50, 51, 55, 58, 65, 66, 68, 69], "quiet": 5, "test": [5, 19, 21, 29, 35, 37, 39, 42, 49, 50, 68, 69], "store": [5, 18, 21, 22, 29, 30, 32, 35, 42, 45, 50, 52, 59, 60, 63, 65, 66, 68, 69], "commonli": [5, 14, 26, 39, 42, 50, 69], "prefix": 5, "short": [5, 14, 21, 29, 31, 35, 38, 39, 45, 49, 57, 68], "sinc": [5, 8, 9, 18, 20, 24, 25, 27, 30, 33, 35, 37, 40, 42, 44, 45, 48, 50, 51, 55, 57, 60, 62, 63, 65, 66], "string": [5, 29, 32, 42, 50, 68], "subsequ": [5, 7, 13, 14, 21, 29, 35, 37, 39, 40, 53, 59, 62, 69], "altern": [5, 7, 8, 10, 13, 15, 26, 32, 33, 47, 50, 66, 69], "abstractmodel": 5, "But": [5, 15, 21, 32, 37, 39, 42, 50, 66], "normal": [5, 14, 29, 31, 39, 42, 46, 49, 50, 53, 58, 62, 69], "content": [5, 29, 39, 45, 46, 47], "At": [5, 12, 21, 24, 25, 27, 31, 47, 52, 64], "major": [5, 32], "empti": 5, "valid": [5, 35, 42, 47, 50, 69], "dot": [5, 7, 8, 12, 13, 14, 15, 16, 18, 23, 29, 32, 33, 38, 40, 42, 44, 45, 47, 48, 50, 52, 57, 58, 62, 65], "notat": [5, 19, 29, 31, 42, 63, 65], "chosen": [5, 38], "reflect": [5, 10], "keyword": [5, 42, 50, 69], "nonnegativer": [5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 22, 24, 26, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 48, 52, 55, 57, 58, 60, 63, 65, 66, 68, 69], "nonnegativeinteg": [5, 17, 18, 30, 37, 55, 59, 62], "binari": [5, 16, 19, 20, 22, 23, 25, 26, 27, 30, 33, 35, 36, 37, 39, 44, 50, 53, 57, 61, 62, 63, 66], "placehold": [5, 30], "unknown": [5, 38, 39, 42, 58, 60, 63, 65], "yet": [5, 29, 55], "updat": [5, 21, 22, 24, 29, 38, 41, 42, 45, 48, 50, 51, 52, 55], "formula": [5, 42, 46, 47, 60], "could": [5, 8, 14, 15, 16, 17, 21, 23, 29, 30, 31, 37, 38, 39, 45, 48, 55, 57, 59, 62, 63, 64, 66, 69], "expr": [5, 8, 9, 10, 11, 17, 39, 50, 55, 60, 63, 65, 69], "releas": [5, 22, 53], "With": [5, 12, 18, 26, 29, 39, 47, 50, 63, 66], "behavior": [5, 39, 49], "line": [5, 8, 13, 14, 20, 22, 29, 35, 41, 44, 60, 66, 69], "add": [5, 8, 11, 12, 20, 21, 22, 23, 25, 29, 30, 31, 32, 37, 39, 41, 42, 46, 47, 53, 55, 57, 60, 62, 63, 69], "tag": [5, 53, 69], "syntax": [5, 45, 55, 69], "error": [5, 13, 19, 29, 33, 40, 51, 57, 66, 68, 69], "numer": [5, 13, 29, 36, 41, 45, 48, 50, 60, 69], "core": [5, 20, 21, 55, 57, 66, 69], "scalarvar": 5, "No": [5, 23, 25, 37, 55, 59, 63], "uniniti": 5, "numericvalu": 5, "scalarobject": 5, "separ": [5, 20, 21, 29, 35, 36, 39, 42, 44, 50, 57, 65, 66, 69], "less": [5, 20, 21, 25, 27, 29, 46, 49, 50, 57, 63, 69], "greater": [5, 15, 17, 25, 49], "raw_materi": 5, "labor_a": [5, 69], "labor_b": [5, 69], "output": [5, 18, 20, 35, 42, 50, 53, 65, 66, 68], "whenev": [5, 21, 25, 33, 63], "fulli": [5, 8, 30, 55, 57], "tee": [5, 8], "debug": 5, "aris": [5, 31, 39], "result": [5, 7, 8, 14, 15, 18, 20, 23, 24, 25, 29, 30, 31, 33, 35, 37, 38, 39, 42, 45, 46, 47, 48, 49, 50, 52, 55, 57, 58, 59, 62, 63, 64, 65, 66, 68, 69], "milp": [5, 53], "date": [5, 13, 14, 18, 25, 26, 49], "apr": [5, 12, 18, 52], "2023": [5, 18, 20, 23, 24, 25, 26, 27, 29, 30, 57], "command": [5, 29, 45], "opt": [5, 29, 31, 35, 44, 45], "homebrew": 5, "bin": [5, 7, 13, 14, 29, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 62, 63], "printingopt": 5, "folder": 5, "zb": [5, 29], "k0pc77yj6c3gv6gr6jj41g1r0000gn": 5, "tmp2_hwem4f": 5, "lp": [5, 7, 11, 15, 42, 53], "stat": [5, 14, 46, 49, 57, 58, 60, 62], "solu": 5, "soln": [5, 27, 30, 68], "strategi": [5, 14, 16, 17, 19, 22, 26, 29, 31, 33, 34, 46, 49, 59, 62], "coinlpio": 5, "readlp": 5, "coin0009i": 5, "switch": [5, 66], "get": [5, 12, 13, 17, 18, 20, 21, 29, 30, 34, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 63, 68], "correct": [5, 42, 45, 62], "dual": [5, 6, 32, 41, 55], "etc": [5, 18], "presolv": [5, 20], "statist": [5, 7, 13, 40, 42, 49, 50], "singleton": 5, "breakdown": 5, "lo": [5, 6, 9, 14, 16, 17, 28, 39], "free": [5, 7, 29, 33, 38, 45, 58, 63], "l": [5, 8, 19, 29, 37, 39, 42, 44, 45, 46, 48, 49, 63, 69], "obj": [5, 9, 20, 35], "480": [5, 12, 18, 52], "002": [5, 14, 45], "total": [5, 7, 8, 12, 14, 18, 21, 22, 23, 25, 27, 29, 30, 35, 37, 38, 39, 42, 44, 45, 49, 50, 52, 55, 57, 62, 65, 66, 69], "cpu": [5, 30], "00": [5, 7, 9, 10, 11, 12, 20, 25, 26, 29, 31, 32, 35, 37, 39, 46, 49, 52, 55, 60, 62, 63, 64], "wallclock": 5, "format": [5, 8, 10, 17, 21, 23, 45, 52], "graphic": [5, 37, 41, 44, 60], "overview": [5, 31, 39], "visual": [5, 8, 12, 14, 18, 20, 22, 24, 30, 32, 34, 35, 42, 55], "appendix": 5, "entir": [5, 8, 32, 34, 35, 62], "individu": [5, 14, 21, 25, 29, 30, 32, 39, 55, 57, 69], "whole": [5, 44, 62], "successfulli": [5, 7, 20, 39, 42], "conveni": [5, 13, 22, 25, 32, 65, 68], "2f": [5, 9, 10, 11, 13, 18, 20, 26, 29, 31, 32, 33, 35, 38, 39, 45, 46, 48, 49, 52, 55, 58, 60, 62, 63, 64, 65, 66], "18000": [5, 32, 64], "15400": 5, "shortcut": 5, "wide": [5, 27, 29, 35], "seri": [5, 7, 8, 14, 15, 21, 32, 42, 45, 49, 50, 52, 62, 64, 68], "matplotlib": [5, 7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66], "bar": [5, 7, 13, 14, 15, 22, 23, 29, 32, 39, 40, 42, 45, 50, 55, 60, 63, 65], "chart": [5, 14, 25, 29, 32, 45, 57, 62], "pd": [5, 7, 12, 14, 15, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 35, 37, 39, 41, 42, 44, 45, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "dtype": [5, 15, 50, 60, 62, 68], "float64": [5, 15, 50, 62, 68], "pyplot": [5, 7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66], "plt": [5, 7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66], "1x2": 5, "grid": [5, 7, 12, 13, 14, 15, 18, 21, 24, 29, 35, 39, 40, 44, 45, 46, 47, 49, 52, 64, 66, 68], "subplot": [5, 7, 13, 14, 20, 21, 22, 23, 24, 25, 27, 29, 32, 34, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 57, 60, 62, 63], "configur": [5, 27, 62, 65], "fig": [5, 7, 13, 14, 21, 22, 23, 24, 25, 27, 29, 32, 34, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 60, 62, 63], "ax": [5, 7, 12, 13, 14, 15, 19, 20, 21, 22, 23, 24, 25, 27, 29, 32, 34, 35, 37, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 60, 62, 63, 64, 68], "figsiz": [5, 7, 12, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 34, 35, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 60, 62, 63], "rcparam": [5, 7, 12, 13, 14, 22, 24, 25, 30, 38, 45, 48, 52, 55], "font": [5, 7, 12, 13, 14, 22, 24, 25, 38, 45, 48, 52, 55], "color": [5, 7, 8, 12, 13, 14, 15, 21, 22, 23, 24, 25, 27, 28, 29, 32, 34, 35, 37, 38, 39, 40, 41, 42, 46, 47, 48, 50, 52, 53, 55, 57, 60], "cm": [5, 21, 25, 38, 48, 52], "tab20c": [5, 7, 12, 25, 38, 48, 52], "color_set": 5, "16": [5, 7, 18, 22, 24, 25, 26, 29, 30, 37, 38, 44, 45, 48, 49, 50, 53, 62, 64, 65, 66], "dataset": [5, 7, 13, 29, 40, 42, 50, 57], "plot": [5, 7, 12, 13, 14, 15, 18, 20, 21, 22, 24, 29, 30, 32, 33, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 66, 68], "enumer": [5, 9, 14, 20, 21, 22, 25, 29, 37, 50, 60, 62], "zip": [5, 7, 12, 14, 18, 21, 27, 29, 30, 52, 57], "kind": [5, 7, 15, 29, 32, 37, 42, 45, 50, 62, 63], "barh": [5, 14, 62], "alpha": [5, 7, 13, 18, 21, 22, 24, 25, 26, 27, 32, 34, 37, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 58, 60, 62, 63, 65], "set_xlabel": [5, 7, 12, 13, 14, 21, 22, 23, 24, 25, 27, 29, 39, 41, 44, 45, 46, 47, 49, 52, 62, 63], "invert_yaxi": 5, "tight_layout": [5, 7, 12, 13, 14, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 38, 44, 45, 46, 48, 49, 52, 60, 62], "discov": [5, 29], "simplest": [6, 53], "adher": [6, 8], "nonneg": [6, 8, 16, 38, 55, 62], "word": [6, 8, 19, 22, 29, 35, 49, 55, 68, 69], "c": [6, 8, 9, 11, 15, 16, 18, 21, 22, 23, 24, 25, 26, 27, 29, 30, 34, 37, 38, 39, 41, 42, 44, 45, 46, 48, 49, 50, 53, 55, 58, 59, 60, 62, 63, 64, 65, 68, 69], "matrix": [6, 12, 19, 31, 38, 40, 41, 42, 48, 49, 50, 53, 58, 62, 63], "ii": [6, 8, 21, 37], "iii": [6, 8, 41], "unbound": [6, 8], "non": [6, 8, 9, 17, 18, 19, 21, 27, 29, 31, 34, 37, 39, 42, 45, 46, 47, 50, 55, 57, 59, 62, 65, 68, 69], "posit": [6, 8, 18, 24, 25, 27, 29, 37, 38, 40, 42, 48, 50, 58, 59, 60, 62], "x_i": [6, 7, 8, 11, 16, 35, 38, 42, 45, 48, 50, 58, 66], "fact": [6, 8, 9, 17, 20, 30, 32, 34, 36, 38, 39, 42, 44, 45, 48, 50, 55, 59, 62, 63, 65], "easili": [6, 8, 11, 18, 31, 33, 35, 38, 44, 45, 52, 57, 63, 68, 69], "convert": [6, 8, 21, 29, 31, 37, 41, 42, 50, 68], "ad": [6, 8, 9, 30, 37, 39, 41, 45, 53, 55, 65, 66, 68, 69], "multipli": [6, 8, 9, 29, 42, 45], "explor": [6, 8, 16, 26, 28, 29, 36, 37, 39, 42, 43, 53, 54, 56, 57, 61], "variou": [6, 8, 16, 22, 26, 28, 30, 36, 37, 39, 43, 51, 52, 54, 55, 56, 61, 68, 69], "microchip": [6, 11, 17], "bim": [6, 15, 16, 51, 54], "absolut": [6, 11, 29, 35, 40, 42, 57, 65], "deviat": [6, 40, 55, 57, 58, 62, 63, 65, 66, 69], "lad": 6, "regress": [6, 36, 42], "mad": 6, "portfolio": [6, 31, 36, 43, 46, 47, 56], "variant": [6, 27, 58, 65, 66], "lowest": [6, 15, 29, 30], "fraction": [6, 12, 14, 17, 23, 29, 42, 46, 47, 49, 55, 58, 62, 65], "forecast": [6, 7, 51, 52, 62, 66], "extra": [6, 16, 18, 25, 28, 30, 36, 43, 44, 57, 59, 61, 63, 65], "wine": 6, "qualiti": [6, 39, 62], "predict": [6, 12, 13, 42, 50, 52, 62, 66], "l_1": [6, 13], "multi": [6, 29, 43, 45, 61], "aim": [7, 10, 12, 13, 20, 29, 32, 34, 36, 45, 48, 52, 53, 64], "valuabl": 7, "coupl": [7, 68], "physicochem": 7, "machin": [7, 8, 13, 16, 21, 36, 40, 43, 69], "2009": [7, 39, 46], "articl": [7, 25, 44, 45, 49, 68], "cortez": 7, "et": [7, 45], "al": [7, 45], "physic": [7, 37, 42, 66], "chemic": [7, 21, 37, 39, 51, 68], "sensori": 7, "metric": [7, 13, 21, 22], "gather": 7, "red": [7, 8, 13, 14, 15, 29, 34, 44, 53, 57], "white": [7, 21, 22, 34, 35, 37, 53, 68], "portug": 7, "uci": [7, 42, 50], "download": [7, 20, 35, 39, 49, 65, 66], "panda": [7, 12, 14, 15, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 35, 37, 39, 41, 42, 44, 45, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "numpi": [7, 8, 12, 13, 14, 18, 20, 23, 24, 29, 30, 31, 35, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 69], "np": [7, 8, 12, 13, 14, 18, 20, 23, 24, 27, 29, 30, 31, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66], "read_csv": [7, 12, 18, 29, 31, 35, 37, 42, 50, 52, 57, 65, 66], "archiv": [7, 42, 50], "ic": [7, 42, 50], "edu": [7, 42, 45, 46, 49, 50, 64], "ml": [7, 42, 50, 51], "databas": [7, 29], "winequ": 7, "csv": [7, 29, 35, 37, 57, 65, 66], "sep": [7, 12, 18, 31, 52], "acid": 7, "volatil": [7, 14], "citric": 7, "residu": [7, 13, 40, 41, 60], "sugar": [7, 64, 68], "chlorid": 7, "sulfur": [7, 39], "dioxid": 7, "densiti": [7, 57], "ph": 7, "sulphat": 7, "alcohol": 7, "7": [7, 10, 11, 13, 18, 19, 20, 21, 22, 24, 25, 27, 29, 31, 32, 33, 34, 37, 38, 39, 42, 45, 49, 50, 52, 53, 60, 64, 66], "4": [7, 8, 9, 10, 11, 12, 17, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 61, 63, 65, 66, 68, 69], "700": [7, 18, 32, 45], "076": 7, "11": [7, 11, 15, 18, 21, 22, 24, 25, 29, 31, 34, 35, 37, 38, 44, 45, 48, 53, 62, 66], "34": [7, 21, 29, 32, 52, 66], "99780": 7, "51": [7, 20, 22, 29, 37, 40, 47], "56": [7, 18, 29, 49, 64, 65], "8": [7, 11, 14, 15, 18, 19, 20, 21, 22, 24, 25, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 49, 50, 52, 53, 55, 57, 59, 60, 62, 65, 66, 69], "880": 7, "098": [7, 32], "25": [7, 21, 22, 24, 25, 29, 32, 33, 35, 37, 38, 39, 42, 46, 47, 48, 49, 53, 55, 58, 60, 62, 63, 64, 65, 66], "67": [7, 10, 12, 18, 29, 35, 37, 52, 66], "99680": 7, "68": [7, 12, 18, 22, 29, 35, 37, 52, 66], "760": 7, "04": [7, 17, 29, 35, 38, 39, 48, 63, 65], "092": 7, "15": [7, 14, 18, 21, 22, 24, 25, 29, 31, 34, 35, 37, 38, 42, 44, 45, 48, 50, 53, 58, 60, 62, 63, 66, 69], "54": [7, 18, 29, 32, 37, 49, 52, 60, 64], "99700": 7, "26": [7, 21, 25, 29, 53, 55], "65": [7, 12, 18, 27, 29, 35, 37, 50, 52, 60, 65, 66], "280": [7, 45], "075": [7, 32, 55], "17": [7, 21, 24, 25, 29, 31, 37, 38, 42, 45, 48, 49, 53, 62, 66], "99800": 7, "58": [7, 29, 35, 64, 65, 66], "1594": 7, "600": [7, 18, 66], "08": [7, 14, 29, 32, 34, 38, 48, 52, 60, 63], "090": 7, "32": [7, 21, 22, 25, 29, 37], "44": [7, 18, 20, 29, 37, 41, 49, 57, 65, 66], "99490": 7, "45": [7, 21, 29, 30, 31, 32, 35, 39, 41, 66], "1595": 7, "550": 7, "062": [7, 14], "39": [7, 13, 29, 30, 65], "99512": 7, "52": [7, 12, 29, 39, 44, 45, 64], "76": [7, 29, 35, 39], "1596": 7, "510": [7, 64], "13": [7, 14, 18, 21, 22, 24, 25, 29, 30, 31, 37, 38, 42, 44, 48, 52, 53, 60, 65], "29": [7, 25, 29, 37, 49, 53], "99574": 7, "42": [7, 21, 29, 37, 39, 62], "75": [7, 29, 32, 33, 37, 38, 40, 42, 45, 55, 60, 62, 64, 65], "1597": [7, 24], "645": [7, 62], "99547": 7, "57": [7, 24, 29, 37, 52, 63, 65], "71": [7, 27, 29, 60], "1598": 7, "310": [7, 12, 18, 52, 64], "47": [7, 12, 18, 29, 37, 50, 52, 62, 63], "067": [7, 29], "18": [7, 24, 25, 29, 32, 35, 37, 38, 39, 46, 48, 53, 62, 65, 66, 69], "99549": 7, "66": [7, 12, 13, 18, 29, 35, 52, 62, 65], "1599": [7, 45], "repeat": [7, 15, 21, 46, 47, 55, 63], "observ": [7, 13, 25, 32, 35, 39, 40, 42, 49, 55, 57, 60, 63, 65, 66, 69], "respons": [7, 66], "y_i": [7, 42, 45, 50, 53, 55], "frac": [7, 10, 14, 24, 27, 29, 31, 42, 44, 45, 47, 49, 50, 57, 60, 62, 63, 65, 68], "df": [7, 20, 30, 31, 37, 42, 44, 45, 49, 50, 52, 55, 59, 62, 64, 68], "ab": [7, 14, 35, 42, 44, 45, 46, 47, 49, 63, 65], "5f": [7, 14, 29, 44, 46, 47, 49], "14": [7, 12, 13, 14, 18, 22, 24, 25, 27, 29, 31, 33, 37, 38, 39, 41, 48, 50, 52, 53, 66, 69], "get_cmap": [7, 12, 13, 14, 23, 24, 27, 33, 37], "axhlin": [7, 14, 15, 24, 25, 27, 39, 41, 60], "ls": [7, 14, 24, 27], "lw": [7, 12, 14, 21, 22, 24, 25, 27, 37, 44, 45, 46, 47, 49, 52, 53, 60, 62], "legend": [7, 12, 13, 14, 15, 22, 24, 27, 32, 35, 40, 41, 44, 45, 46, 49, 52, 57, 60, 62, 66], "set_ylabel": [7, 12, 13, 14, 21, 22, 23, 24, 25, 27, 29, 39, 41, 44, 45, 46, 47, 49, 52, 62], "68318": 7, "599": 7, "eleven": 7, "characterist": [7, 8, 68], "plu": [7, 10, 18], "record": [7, 49, 51], "histogram": [7, 13, 14, 29, 40, 62, 63], "insight": [7, 13, 42, 50], "sharei": [7, 14], "flatten": [7, 14], "hist": [7, 13, 14, 29, 40, 62, 63], "30": [7, 13, 18, 21, 22, 24, 25, 26, 29, 32, 35, 37, 41, 44, 45, 49, 53, 59, 62, 63, 66, 69], "axvlin": [7, 14, 24, 25, 27, 29, 39, 41, 53], "set_titl": [7, 14, 20, 21, 23, 24, 29, 32, 37, 39, 41, 44, 46, 47, 49, 52, 57, 62], "explanatori": [7, 13, 40], "interest": [7, 9, 31, 33, 42, 45, 50, 60, 63], "deep": [7, 52], "knowledg": [7, 44, 49, 59, 63], "area": [7, 27, 44, 57], "onenologist": 7, "head": [7, 42, 49, 50, 53], "naiv": [7, 17, 55, 59], "scientist": 7, "absenc": 7, "experi": [7, 46], "proce": [7, 68], "correl": [7, 42, 50], "_": [7, 8, 11, 12, 13, 18, 20, 21, 22, 25, 26, 29, 31, 34, 35, 37, 38, 39, 40, 46, 47, 48, 49, 50, 53, 55, 57, 59, 62, 63, 64, 65, 69], "corr": 7, "000000": [7, 24, 29, 31, 35, 42, 66], "022026": 7, "202288": 7, "390558": 7, "496180": [7, 42], "174919": 7, "476166": 7, "figur": [7, 20, 29, 30, 35, 37, 40, 45, 52, 53, 55, 57, 62], "strong": [7, 9, 20], "singl": [7, 8, 13, 14, 15, 20, 22, 26, 29, 33, 35, 39, 53, 57, 63, 65, 66, 68, 69], "determin": [7, 12, 24, 25, 27, 30, 35, 36, 37, 42, 44, 45, 47, 50, 53, 57, 58, 59, 60, 63, 64, 65, 66, 69], "largest": [7, 29, 37], "reduc": [7, 14, 15, 20, 26, 27, 32, 37, 39, 42, 44, 45, 47, 50, 64, 69], "right": [7, 8, 9, 10, 12, 13, 14, 20, 21, 22, 23, 25, 27, 30, 37, 39, 40, 42, 44, 45, 47, 50, 53, 55, 60, 62, 63, 65], "prior": [7, 21, 23, 24, 32, 59, 62], "lad_fit_1": 7, "y_col": 7, "x_col": 7, "concretemodel": [7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 48, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "len": [7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 29, 30, 33, 37, 40, 41, 42, 45, 49, 52, 53, 55, 57, 62, 63, 64, 65, 66], "rangeset": [7, 13, 14, 23, 24, 29, 31, 33, 37, 40], "loc": [7, 12, 14, 15, 18, 21, 22, 24, 27, 29, 30, 31, 32, 37, 39, 41, 42, 44, 45, 49, 52, 53, 57, 60, 64], "e_po": 7, "e_neg": 7, "prediction_error": 7, "54117": 7, "calcul": [7, 13, 14, 21, 27, 30, 31, 35, 39, 40, 42, 44, 45, 47, 50, 55, 59, 60, 63, 65, 66, 68, 69], "fig1": 7, "ax1": 7, "count": [7, 13, 18, 29, 40, 42, 50, 66], "fig2": [7, 13], "ax2": [7, 13], "scatter": [7, 13, 14, 40, 42, 50, 57], "set_aspect": [7, 27, 44], "box": 7, "min_val": [7, 14], "get_xlim": [7, 27], "get_ylim": [7, 21, 62], "max_val": [7, 14], "set_xlim": [7, 14, 23, 25, 27, 41, 44, 45, 46, 53, 57, 62], "set_ylim": [7, 21, 22, 24, 25, 27, 32, 41, 44, 45, 46, 47, 49, 57], "m_j": [7, 13, 40, 57], "hat": [7, 12, 52, 59, 65], "min_": [7, 39, 40, 42, 45], "_i": [7, 22, 50, 65], "j": [7, 8, 12, 13, 14, 15, 18, 20, 21, 22, 25, 27, 29, 30, 31, 33, 34, 35, 37, 40, 41, 42, 44, 45, 50, 52, 53, 57, 62, 63, 65, 66, 69], "x_": [7, 12, 18, 19, 20, 23, 27, 29, 30, 31, 32, 33, 34, 37, 39, 42, 50, 53, 59], "care": [7, 14, 18, 29, 63, 69], "l1_fit": 7, "l1": 7, "49980": 7, "34242": 7, "98062": 7, "28928": 7, "90609": 7, "00219": 7, "50083": 7, "06382": 7, "substanti": [7, 14, 41], "reduct": [7, 8, 64, 65], "benchmark": [7, 21, 39], "tabul": 7, "regressor": [7, 13], "683": [7, 45], "541": 7, "500": [7, 12, 18, 30, 32, 40, 41, 45, 46, 49, 52, 53, 55, 57, 64], "enough": [7, 8, 17, 25, 26, 29, 33, 36, 39, 59], "replac": [7, 20, 29, 30, 31, 39, 42, 46, 50, 57, 62], "human": 7, "judgment": 7, "judg": 7, "intern": [8, 12, 18, 44, 46, 49, 52, 69], "chip": [8, 10, 12, 17, 18, 52, 55], "1g": 8, "silicon": [8, 9, 10, 11, 12, 15, 17, 18, 52, 55], "plastic": [8, 9, 10, 11, 12, 15, 17, 18, 52, 55], "4g": 8, "copper": [8, 9, 10, 11, 12, 15, 17, 18, 52], "memori": [8, 12, 14, 17, 18, 52, 55, 69], "germanium": [8, 9, 10, 11, 12, 15, 17, 18, 52, 55], "2g": 8, "sold": [8, 29, 39, 59, 60, 62, 64], "stock": [8, 12, 18, 36, 39, 46, 47, 49, 51, 52, 56], "1000g": 8, "1500g": 8, "1750g": 8, "4800g": 8, "euro": [8, 31, 64], "12x": 8, "9y": 8, "know": [8, 29, 30, 39, 45, 50, 51, 55, 59, 62, 66], "joint": 8, "usag": [8, 69], "4x": 8, "exce": [8, 25, 30, 39, 66], "1000": [8, 9, 10, 11, 12, 13, 15, 17, 18, 19, 20, 26, 29, 35, 45, 46, 52, 55, 57, 60, 62, 63, 64, 66], "deduc": 8, "role": [8, 29, 36, 39, 53, 55, 63], "1500": [8, 9, 10, 11, 12, 15, 17, 18, 29, 52, 55, 60, 64], "1750": [8, 9, 10, 11, 12, 15, 17, 18, 29, 32, 52, 55], "2y": [8, 69], "4800": [8, 9, 10, 11, 12, 17, 18, 45, 52, 55, 64], "leverag": [8, 30, 31, 45, 49, 55], "dimension": [8, 21, 27, 37, 42, 44, 50, 55, 62], "grai": [8, 24, 34, 35, 53], "enclos": 8, "solid": [8, 34, 65], "isolin": [8, 44], "parallel": [8, 33], "dash": [8, 21, 22], "blue": [8, 13, 21, 35], "increas": [8, 14, 20, 21, 23, 27, 29, 31, 39, 41, 46, 47, 59, 60, 66], "intens": [8, 31, 39], "intuit": [8, 17, 47, 65], "alreadi": [8, 18, 20, 29, 31, 32, 50, 58, 66], "guess": [8, 33], "mark": [8, 24, 29, 46, 50], "easi": [8, 9, 53, 55], "imagin": [8, 29, 30], "complic": [8, 11, 50, 69], "matter": 8, "expand": [8, 63], "obfusc": 8, "discern": 8, "analyz": [8, 28, 62, 66], "matric": [8, 63], "close": [8, 13, 14, 29, 39, 44, 49, 60], "greatli": 8, "identif": [8, 29, 31], "similar": [8, 14, 20, 39, 42, 63, 65, 69], "food": [8, 21, 25, 39], "refresh": 8, "equat": [8, 13, 18, 19, 20, 27, 29, 35, 37, 42, 45, 50, 68], "toward": [8, 25, 27], "renam": 8, "x_1": [8, 9, 10, 17, 38, 42, 44, 48, 50, 55, 58], "x_2": [8, 9, 10, 17, 38, 42, 48, 50, 55, 58], "obtain": [8, 9, 12, 13, 17, 22, 27, 29, 30, 33, 35, 38, 39, 40, 42, 44, 45, 47, 48, 50, 55, 57, 59, 60, 62, 63, 65, 66], "pmatrix": [8, 63], "just": [8, 11, 21, 29, 32, 34, 37, 39, 44, 55, 59, 63, 65], "rewrit": [8, 13, 17, 29, 35, 40, 44, 45, 47, 48, 58, 63], "12x_1": [8, 10, 17, 55], "9x_2": [8, 10, 17, 55], "bmatrix": [8, 19, 22, 24, 26, 27, 42, 45, 50], "system": [8, 18, 29, 31, 35, 39, 46, 47, 56, 63, 66], "read": [8, 14, 21, 23, 29, 35, 37, 44, 49, 57, 62, 63, 66, 68, 69], "correctli": [8, 18, 25, 42, 55, 66], "replic": 8, "4x_1": [8, 10, 55], "longleftrightarrow": [8, 44, 45], "arrai": [8, 13, 35, 38, 40, 42, 44, 45, 48, 49, 50, 55, 57, 58, 62, 63, 65, 66, 69], "2x_2": [8, 10, 55], "x1": [8, 9, 10, 11, 17, 27, 44], "x2": [8, 9, 10, 11, 17, 27], "1f": [8, 10, 11, 15, 21, 42, 46, 50, 60], "650": [8, 10, 55, 59], "1100": [8, 10, 18, 29, 55], "17700": [8, 9, 10, 55], "emploi": [8, 13, 25, 42], "enhanc": [8, 27, 39, 69], "thu": [8, 17, 18, 25, 29, 30, 33, 35, 40, 48, 57, 60, 62, 63, 66], "util": [8, 27, 29, 32, 46, 47, 49, 53, 68], "encompass": 8, "advantag": [8, 18, 28, 30, 31, 42, 50, 68], "concis": [8, 20], "space": [8, 16, 44, 45, 53, 62, 68], "clariti": 8, "reveal": [8, 39, 50], "across": [8, 29, 34, 35, 63, 65], "uniform": [8, 23, 32, 39, 45, 46, 60, 63, 65, 69], "furthermor": [8, 18, 23, 35, 44, 69], "unnecessari": [8, 69], "theoret": [8, 52, 60], "streamlin": [8, 21, 69], "Is": [8, 15, 30, 39, 46], "answer": [8, 42, 59], "textit": 8, "sign": [8, 42, 50], "onc": [8, 22, 23, 37, 42, 50, 62, 66], "commit": [8, 31, 65], "deriv": [8, 22, 27, 35, 41, 42, 45, 50, 62], "sort": [8, 14, 20, 21, 25, 29, 42, 46, 50], "consid": [8, 11, 13, 14, 15, 18, 20, 21, 22, 24, 27, 28, 29, 30, 31, 32, 33, 37, 38, 39, 40, 42, 44, 46, 47, 48, 49, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 68], "anywai": [8, 30, 63], "without": [8, 15, 23, 27, 32, 33, 37, 39, 42, 46, 47, 50, 53, 59, 63, 68, 69], "Of": [8, 16, 63], "cours": [8, 16, 17, 22, 33, 39, 63, 69], "illustr": [8, 12, 18, 20, 21, 26, 27, 29, 30, 37, 44, 45, 52, 55, 60, 65, 66], "shall": [8, 18, 29, 45, 50, 65], "upon": [8, 21, 57], "had": [8, 17, 18, 29, 42, 50, 59, 65], "mention": [8, 11], "neg": [8, 9, 17, 18, 21, 29, 34, 35, 37, 42, 45, 47, 50, 51, 57, 59, 62, 69], "therefor": [8, 14, 27, 32, 35, 38, 42, 45, 50, 62, 63, 66], "overlin": 8, "side": [8, 9, 14, 25, 29, 30, 42, 55, 57, 68], "One": [8, 9, 15, 19, 21, 22, 27, 29, 30, 35, 37, 38, 63, 65, 68], "inde": [8, 20, 25, 44, 50, 57, 63, 65], "yield": [8, 10, 17, 18, 27, 29, 39, 41, 45, 50, 52, 53, 55, 57, 63, 64, 68], "n_var": 8, "n_constraint": 8, "constraintlist": [8, 11, 60], "optimal_x": 8, "round": [8, 12, 14, 17, 18, 24, 25, 30, 31, 32, 33, 34, 37, 38, 39, 41, 44, 45, 48, 52, 55, 62, 64, 65], "addition": [8, 58, 63], "avoid": [8, 12, 18, 19, 21, 22, 27, 32, 33, 42, 52, 66, 68, 69], "hard": [8, 27, 29, 42, 50, 63], "doc": [8, 37, 45, 48, 69], "lambda_1": 9, "lambda_2": 9, "lambda_3": 9, "lambda_4": 9, "four": [9, 24, 39, 41, 42, 50, 63], "rh": [9, 50], "tight": [9, 20, 22, 24, 29, 52, 58], "Such": [9, 55, 57, 65, 66], "tightest": 9, "y1": [9, 10, 27, 63], "y2": [9, 10, 27, 63], "y3": [9, 63], "y4": 9, "dualiti": [9, 55], "primal": 9, "coincid": [9, 30], "ask": [9, 29, 31, 64], "suffix": [9, 32, 37, 55, 69], "component_object": [9, 55], "y_": [9, 18, 20, 23, 27, 39, 42, 50, 53, 59, 62], "y_1": [9, 10, 42, 50, 55, 63], "y_2": [9, 10, 42, 50, 55, 63], "y_3": [9, 63], "y_4": 9, "recal": [10, 12, 18, 35, 47, 48, 52, 60, 63], "pair": [10, 18, 19, 21, 22, 25, 27, 29, 31, 32, 34, 42, 53, 55, 66], "sale": [10, 14, 29, 59], "suppos": [10, 11, 13, 26, 40, 41, 55, 63], "independ": [10, 13, 35, 39, 40, 47, 49, 55, 62], "6x_1": 10, "6x_2": 10, "reason": [10, 18, 27, 29, 30, 33, 35, 36, 42, 45, 46, 49, 50, 53, 55, 57, 60, 63, 64, 68, 69], "bim_with_revenues_minus_cost": 10, "minu": [10, 18, 34, 57, 66], "variable_cost": 10, "fixed_cost": 10, "bim_linear": 10, "3f": [10, 14, 17, 29, 38, 42, 46, 47, 48, 50, 52, 57, 58, 68], "15925": 10, "000": [10, 14, 17, 32, 39, 45, 46, 55, 58, 62, 64], "1775": 10, "ratio": 10, "dfrac": 10, "deal": [10, 55], "auxiliari": [10, 11, 12, 14, 18, 22, 34, 42, 45, 47, 50, 55, 63], "12y_1": 10, "9y_2": 10, "cdot": [10, 18, 25, 26, 29, 30, 47, 50, 60, 62, 65, 66], "4y_1": 10, "2y_2": 10, "100y": 10, "despit": 10, "recov": [10, 30, 46, 65], "bim_with_revenues_over_cost": 10, "bim_fract": 10, "250": [10, 24, 35, 45, 55, 60, 64, 69], "051": [10, 29], "16500": 10, "1641": 10, "667": [10, 42, 58], "972": 10, "strictli": [10, 53], "seemingli": 11, "rewritten": [11, 58], "maxima": [11, 39], "finit": [11, 13, 29, 33, 40, 62, 63], "k": [11, 13, 18, 21, 22, 23, 24, 25, 27, 29, 30, 31, 33, 34, 37, 40, 42, 44, 45, 46, 47, 49, 50, 60, 63], "c_k": 11, "minimax": 11, "max_": [11, 15, 39, 46, 47, 49, 59, 62, 69], "top_": 11, "latter": [11, 24, 66], "z": [11, 15, 16, 18, 22, 26, 29, 37, 39, 42, 44, 45, 47, 50, 55, 57, 59, 60, 62, 63], "qquad": [11, 15, 20, 23, 25, 39, 40, 42, 45, 53, 62, 65], "guarante": [11, 14, 15, 32, 33, 38, 44, 48, 55, 57, 58, 62, 63, 65], "vice": [11, 63], "versa": [11, 63], "henc": [11, 35, 62, 66], "uncertainti": [11, 15, 43, 44, 52, 61, 63, 65, 66], "regard": [11, 15, 25, 39, 42, 45, 50, 51, 55, 64], "instead": [11, 16, 20, 29, 30, 33, 35, 36, 41, 55, 57, 62, 63, 65, 66, 68], "nomin": [11, 52, 55, 63, 64, 65, 66], "estim": [11, 13, 39, 51, 57, 60, 63], "trick": [11, 45], "bim_maxmin": 11, "maxmin": [11, 15], "c1": [11, 21], "c2": [11, 21], "583": [11, 15, 29], "1166": [11, 15, 55], "17500": [11, 15], "carefulli": [12, 39, 52], "manag": [12, 44, 45, 46, 47, 49, 51, 52, 56, 69], "led": [12, 52], "monthli": [12, 18, 52], "jan": [12, 18, 52], "feb": [12, 18, 52], "mar": [12, 18, 52], "jun": [12, 18, 52], "jul": [12, 18, 52], "aug": [12, 18, 52], "oct": [12, 18, 52], "nov": [12, 18, 52], "dec": [12, 18, 52, 63], "88": [12, 18, 20, 29, 33, 35, 37, 42, 50, 52, 62, 66], "125": [12, 18, 35, 37, 49, 52, 55, 62, 66], "260": [12, 18, 32, 52, 64], "217": [12, 18, 29, 52, 66], "238": [12, 17, 18, 29, 52, 64], "286": [12, 18, 52], "248": [12, 18, 52], "265": [12, 18, 52, 55, 66], "293": [12, 18, 29, 52], "259": [12, 18, 27, 45, 52], "244": [12, 18, 45, 52], "62": [12, 18, 29, 37, 52, 65], "81": [12, 18, 29, 32, 35, 39, 52, 63], "95": [12, 18, 29, 32, 35, 42, 47, 52, 62, 65], "118": [12, 18, 24, 29, 31, 35, 46, 47, 49, 52, 66], "86": [12, 18, 24, 29, 35, 37, 42, 44, 52, 66], "89": [12, 18, 29, 50, 52], "82": [12, 18, 29, 52, 60], "84": [12, 18, 29, 37, 42, 45, 52, 60, 66], "200": [12, 14, 18, 20, 27, 31, 35, 39, 44, 45, 52, 55, 59, 62, 64, 66, 69], "acquir": [12, 18, 39, 52], "month": [12, 18, 52], "9000": [12, 52, 64], "05": [12, 18, 22, 24, 25, 26, 29, 37, 38, 39, 42, 44, 45, 46, 48, 49, 50, 52, 55, 58, 60, 62, 65, 66], "spend": [12, 52], "5000": [12, 23, 45, 46, 52, 60, 64], "kept": [12, 18, 52], "datafram": [12, 14, 15, 18, 20, 21, 22, 24, 25, 27, 29, 30, 31, 32, 35, 37, 39, 41, 42, 44, 45, 49, 50, 52, 53, 55, 57, 59, 62, 63, 64, 66, 68, 69], "stringio": [12, 18, 31, 52], "ipython": [12, 30, 32, 34, 35, 38, 48, 58, 65], "demand_data": [12, 18, 52], "price_data": [12, 52], "demand_chip": [12, 18, 52], "index_col": [12, 18, 29, 31, 35, 52, 57, 65, 66], "consumpt": [12, 41], "dict": [12, 18, 20, 31, 37, 39, 42, 45, 50, 52, 57, 60], "from_dict": [12, 18, 52, 57, 59, 68], "fillna": [12, 14, 18, 39, 52, 64], "astyp": [12, 18, 25, 30, 37, 52], "int": [12, 13, 18, 19, 27, 29, 30, 33, 37, 40, 47, 49, 52, 53, 60, 68], "135": [12, 18, 29, 32, 49, 60, 65, 69], "187": [12, 18], "341": [12, 18], "282": [12, 18], "333": [12, 15, 18, 45, 46], "404": [12, 18], "334": [12, 18, 37], "327": [12, 18, 45, 52], "347": [12, 18, 29], "375": [12, 18, 45, 52, 55, 64, 69], "343": [12, 18, 29, 52, 55], "446": [12, 18], "624": [12, 18], "1202": [12, 18], "998": [12, 18, 29], "1142": [12, 18, 46, 49], "1380": [12, 18, 37], "1164": [12, 18, 52], "1130": [12, 18], "1224": [12, 18], "1336": [12, 18], "1204": [12, 18], "1108": [12, 18], "pt": [12, 18, 52], "s_": [12, 14, 18, 32, 37], "uniqu": [12, 19, 21, 22, 25, 29, 35, 42, 50, 59, 66, 69], "eas": [12, 65], "pi_": [12, 18, 37], "h_": [12, 20], "happen": [12, 25, 39, 43, 55, 62, 65, 66, 68], "constant": [12, 19, 24, 26, 29, 30, 40, 44, 45, 57, 59, 60, 62, 66, 69], "focu": [12, 30, 42], "beta": [12, 18, 26, 44, 58], "further": [12, 13, 18, 21, 29, 37, 40, 45, 46, 50, 53, 60, 62], "storag": 12, "ell": [12, 55], "balanc": [12, 18, 29, 30, 31, 34, 39, 41, 42, 52, 55, 57, 64, 65, 66], "delta_": [12, 18], "impli": [12, 35, 41, 42, 45, 63], "period": [12, 14, 18, 21, 25, 29, 46, 52, 66], "texttt": 12, "januari": 12, "captur": [12, 35, 38, 62, 68], "level": [12, 14, 18, 21, 24, 35, 44, 48, 51, 52, 53, 57, 58, 60, 62, 65, 66], "decemb": 12, "textrm": [12, 18], "omega_p": [12, 18], "bimproductacquisitionandinventori": [12, 52], "acquisition_pric": [12, 52], "exist": [12, 18, 22, 29, 30, 31, 32, 35, 42, 46, 50, 52, 66, 68, 69], "stock_limit": [12, 18, 52], "month_budget": [12, 52], "prev": [12, 18, 52], "bloat": [12, 18, 52], "pi": [12, 18, 45, 52], "h": [12, 25, 27, 29, 37, 44, 45, 46, 49, 52, 53, 60, 68, 69], "delta": [12, 14, 18, 29, 52, 55, 57, 65], "acquisition_cost": [12, 18, 52], "inventory_cost": [12, 18, 52], "total_cost": [12, 18, 32, 52], "2000": [12, 18, 20, 21, 22, 24, 31, 37, 41, 45, 49, 52, 55, 57, 64], "show_table_of_pyomo_vari": 12, "from_record": [12, 18, 52], "report_pyomo_solut": 12, "nthe": 12, "equidistant_color": 12, "drawstyl": [12, 18, 52], "mid": [12, 18, 52], "set_xtick": [12, 25, 53], "tick": [12, 37, 52], "set_xticklabel": [12, 25], "965": 12, "1078": 12, "266": [12, 18, 52], "1310": [12, 18, 52], "3548": 12, "962": 12, "4312": 12, "912": [12, 18, 52], "787": [12, 18, 60], "527": [12, 18], "1275": [12, 55], "1037": 12, "751": 12, "503": 12, "785": 12, "744": [12, 52], "1615": [12, 18, 52], "1428": [12, 18, 52], "1087": [12, 18, 45, 52], "805": [12, 18, 52], "472": [12, 18, 52], "4354": [12, 18], "3730": [12, 18], "6076": 12, "5078": 12, "3936": 12, "2556": 12, "1392": 12, "262": [12, 41], "3108": 12, "1453": [12, 18, 52], "1391": [12, 18, 52], "1245": [12, 18, 52], "1150": [12, 18, 52], "1032": [12, 18, 52], "946": [12, 18, 29, 52], "857": [12, 18, 52], "775": [12, 18, 52], "693": [12, 18, 52], "609": [12, 18, 52], "543": [12, 18, 52], "situat": [12, 15, 16, 21, 23, 26, 27, 29, 30, 31, 36, 42, 50, 53, 63, 64, 68], "444": 12, "559": [12, 62], "666": [12, 52], "400": [12, 18, 35, 55, 59, 62, 66], "1065": 12, "221": 12, "33": [12, 29, 37, 39, 46, 52, 60, 62, 66], "323": [12, 45, 65], "983": 12, "695": 12, "934": [12, 27], "1356": 12, "1790": 12, "1530": [12, 18], "1980": 12, "1742": 12, "1856": 12, "1673": 12, "38": [12, 29, 35, 37, 60, 62, 65, 66], "1435": 12, "1296": [12, 52], "1003": [12, 52], "718": 12, "4575": 12, "4274": 12, "5072": 12, "4074": 12, "3932": 12, "2552": 12, "1388": 12, "1241": 12, "98": [12, 29, 49, 60, 62, 66], "713": [12, 17, 29], "1377": 12, "2173": 12, "remain": [12, 13, 16, 18, 22, 35, 37, 45, 55, 57, 59, 62, 65, 69], "forc": [12, 25], "infeas": [12, 33, 57, 58, 63, 65, 66], "fewer": [12, 37, 53], "variabel": 12, "rid": 12, "bimproductacquisitionandinventory_v2": 12, "non_negative_stock": 12, "supervis": [13, 42], "19th": 13, "centuri": [13, 49], "cornerston": 13, "modern": [13, 14, 22], "depend": [13, 21, 22, 33, 35, 39, 40, 47, 62, 63, 64, 66, 69], "tradit": 13, "unlik": 13, "squar": [13, 36, 42, 44, 45], "focus": [13, 66], "norm": [13, 42, 50, 58, 62], "robust": [13, 46, 49, 51, 56, 65, 66], "against": [13, 27, 40, 63], "outlier": 13, "methodolog": 13, "survei": [13, 37, 39], "paper": [13, 14, 21, 29, 37, 44, 45, 46, 47, 49, 57], "subash": 13, "narula": 13, "john": [13, 21, 41, 47, 64, 69], "wellington": 13, "scikit": [13, 40], "make_regress": [13, 40], "synthet": [13, 40], "n_sampl": [13, 40], "n_featur": [13, 40], "sklearn": [13, 40, 42, 50], "nois": [13, 40], "random": [13, 20, 23, 24, 27, 30, 33, 35, 38, 40, 45, 46, 47, 48, 49, 52, 53, 55, 57, 58, 60, 62, 63, 65, 66], "seed": [13, 20, 24, 30, 33, 40, 52, 53, 55, 57, 60, 62, 63, 65, 66], "2021": [13, 29, 44, 46, 49], "prepar": [13, 25, 40, 62, 66, 68], "versu": [13, 39, 40], "coolwarm": [13, 14], "sqrt": [13, 29, 40, 42, 44, 45, 50, 53, 62], "edgecolor": [13, 25, 27], "black": [13, 45], "e_i": [13, 40], "quantifi": [13, 38, 48], "diverg": 13, "_j": [13, 14, 22, 40, 42, 50, 55, 57, 65], "m_1": [13, 35, 40], "m_k": [13, 40], "criterion": [13, 15, 29, 40, 43, 46, 49], "attempt": [13, 29, 32, 37, 39, 68], "intercept": [13, 40, 50], "approxim": [13, 42, 46, 49, 62, 63, 65], "m_i": [13, 40], "nonlinear": [13, 36, 37, 44, 45, 55, 68], "wors": [13, 63], "differenti": [13, 29, 30, 42, 68], "lad_regress": [13, 40], "dimens": [13, 20, 42, 50], "shape": [13, 27, 32, 40, 42, 50, 60, 66], "style": [13, 21, 32, 34, 40, 67, 68], "ep": [13, 40, 57], "em": [13, 40, 49], "sum_of_abs_error": [13, 40], "24276": 13, "nativ": [13, 26, 69], "inclus": [13, 47, 49, 69], "fit": [13, 27, 37, 40, 42, 45, 50, 62, 68], "found": [13, 21, 27, 29, 33, 35, 37, 39, 47, 49, 51, 52, 55, 59, 63, 64], "actual": [13, 17, 39, 42, 47, 50, 51, 53, 55, 59, 63, 65, 68], "y_fit": [13, 40], "distribut": [13, 14, 21, 24, 28, 29, 34, 46, 47, 49, 55, 56, 58, 63, 66, 69], "theori": [14, 46, 49, 58, 68], "histori": [14, 39], "financ": [14, 29, 45, 46, 47, 49], "invest": [14, 29, 38, 41, 43, 44, 47, 48, 49, 58], "princip": 14, "idea": [14, 15, 20, 22, 27, 45, 46, 47, 53, 55, 57, 63, 65], "blend": [14, 25, 36], "financi": [14, 29, 31, 41, 59, 65], "secur": 14, "trade": [14, 31, 42, 44, 48, 49, 50], "off": [14, 20, 42, 44, 45, 48, 50, 63, 66, 68], "introduct": [14, 25, 46, 47, 62, 64, 68], "1952": 14, "doctor": 14, "thesi": [14, 29], "harri": [14, 45, 49], "markowitz": [14, 36, 43, 49, 56], "award": 14, "share": [14, 33], "1990": [14, 21], "nobel": 14, "prize": 14, "econom": [14, 27, 29, 39, 41, 43, 44, 56], "hi": [14, 19, 24, 46, 47], "field": [14, 63, 66], "covari": [14, 38, 48, 58, 62], "constitu": 14, "varianc": [14, 38, 42, 46, 48, 50, 62], "quadrat": [14, 37, 38, 39, 48, 50, 55], "subject": [14, 24, 26, 30, 31, 32, 37, 38, 44, 46, 47, 51, 53, 59, 63, 64, 69], "alloc": [14, 27, 30, 32, 33, 37, 45, 47, 61, 64], "wealth": [14, 29, 31, 46, 47], "remark": [14, 42, 50], "1991": [14, 21, 37], "konno": 14, "yamazaki": 14, "propos": [14, 32, 37, 47, 49, 62, 68], "incorpor": [14, 23, 29, 37, 49, 69], "larg": [14, 15, 20, 22, 23, 25, 26, 29, 30, 32, 33, 35, 37, 39, 41, 42, 49, 50, 62, 63, 65, 69], "yahoo": [14, 49], "web": [14, 29, 45, 46, 49, 64], "servic": [14, 20, 29, 31, 32, 53, 62], "notori": 14, "fickl": 14, "colaboratori": 14, "upgrad": [14, 29, 31, 49, 62], "q": [14, 29, 41, 42, 44, 45, 46, 49, 50, 53, 60, 62, 63, 65, 66, 68], "mdate": 14, "scipi": [14, 20, 58, 60, 62], "datetim": [14, 29, 49], "yf": [14, 20, 49], "n_year": 14, "load": [14, 20, 21, 33, 35, 50, 65, 66, 68], "consolid": 14, "split": [14, 20, 25, 29, 42, 61], "dividend": 14, "ticker": 14, "axp": [14, 49], "aapl": [14, 49], "amgn": [14, 49], "ba": [14, 49], "crm": 14, "csco": 14, "cvx": [14, 49], "di": 14, "dow": [14, 49], "gs": 14, "hd": 14, "ibm": 14, "intc": 14, "jnj": 14, "jpm": [14, 49], "ko": 14, "mcd": [14, 49], "mmm": [14, 49], "mrk": 14, "msft": [14, 49], "nke": 14, "pg": [14, 49], "trv": 14, "unh": 14, "vz": 14, "wba": 14, "wmt": 14, "xom": [14, 49], "end_dat": 14, "todai": [14, 49], "start_dat": 14, "timedelta": [14, 49], "365": [14, 49, 55, 59], "progress": [14, 44], "adj": [14, 49], "bfill": 14, "inplac": [14, 21, 45, 49, 53, 64], "ffill": 14, "logi": [14, 49], "bbox_to_anchor": [14, 22, 24, 46, 49], "log": [14, 29, 37, 46, 49, 55, 57, 66, 68], "preserv": [14, 26], "arithmet": [14, 19], "logarithm": [14, 29, 47], "assets_sc": 14, "div": 14, "iloc": [14, 49, 50, 52], "dai": [14, 25, 26, 29, 35, 59, 60], "r_": [14, 24, 32, 47, 49], "daily_return": 14, "diff": 14, "shift": [14, 16, 49], "sharex": [14, 24, 49], "xaxi": 14, "set_major_loc": 14, "yearloc": 14, "set_major_formatt": 14, "dateformatt": 14, "delta_j": [14, 65], "depict": [14, 37], "interv": [14, 21, 22, 53, 60, 68], "whose": [14, 18, 27, 38, 40, 47, 57, 58], "green": [14, 21, 29, 34, 35, 44, 53, 57], "mean_return": 14, "mean_absolute_devi": 14, "linestyl": [14, 15, 24, 39, 41, 57, 60], "comparison": [14, 20, 22, 23, 42, 63], "vs": [14, 23, 36, 48, 49, 62], "scalarformatt": 14, "gradient_barplot": 14, "color_map": [14, 35], "range_v": 14, "val": 14, "normalized_v": 14, "35": [14, 18, 29, 37, 48, 58, 65, 66], "choos": [14, 15, 18, 23, 26, 33, 42, 44, 47, 50, 55, 59], "map": [14, 19, 37, 42, 50, 66], "color_map2": 14, "revers": [14, 29, 69], "color_map3": 14, "ylgn": 14, "set_ytick": [14, 21, 22, 25, 37], "arang": [14, 18, 52], "set_yticklabel": [14, 21, 25], "0005": [14, 45], "0021": 14, "formatt": 14, "usemathtext": 14, "set_scientif": 14, "set_powerlimit": 14, "001": [14, 29, 45], "02": [14, 17, 18, 29, 38, 48, 57, 62], "ms": [14, 24, 29, 30, 35, 37, 39, 41, 44, 45, 46, 60, 68], "03": [14, 29, 31, 38, 39, 48], "formatterx": 14, "formatteri": 14, "yaxi": [14, 23], "w_t": 14, "t_": [14, 21, 24, 62], "w_": [14, 27, 29, 33, 42, 46, 47, 62], "n_": [14, 19, 25, 29, 32], "jn_": 14, "weight": [14, 18, 21, 22, 25, 27, 29, 34, 35, 37, 42, 46, 49, 50, 53], "w_j": [14, 31], "investor": [14, 29, 38, 46, 47, 48, 49], "impos": [14, 22, 23, 25, 30, 42, 46, 55], "horizon": [14, 22, 23, 24, 52], "w": [14, 22, 23, 25, 27, 31, 33, 37, 39, 42, 44, 45, 46, 47, 49, 50, 53, 55, 59, 66], "big": [14, 18, 22, 23, 25, 26, 29, 35, 45, 57, 62], "ub": [14, 21, 27, 44, 50, 69], "enforc": [14, 25, 29, 53, 65], "diversif": 14, "u_t": [14, 23, 49], "v_t": 14, "mad_portfolio": 14, "w_lb": [14, 27], "w_ub": [14, 27], "portfolio_return": 14, "sum_of_weight": 14, "mean_portfolio_return": 14, "no_short": [14, 29], "diversifi": 14, "024": [14, 45, 68], "101": [14, 24, 29], "027": [14, 45], "004": [14, 45], "115": [14, 35, 44, 45, 49, 66], "141": [14, 37, 49], "104": [14, 29, 42], "012": [14, 29, 45, 62], "01": [14, 29, 31, 32, 37, 38, 46, 47, 48, 55], "199": [14, 62], "00740": 14, "mad_visu": 14, "mad_portfolio_weight": 14, "color_map1": 14, "grei": [14, 37], "97": [14, 21, 29, 42, 49, 50, 66], "005": [14, 38, 45, 48, 55, 62], "21": [14, 20, 22, 24, 25, 29, 35, 42, 44, 49, 53, 55, 62, 65], "000015": [14, 29], "0028": 14, "toler": [14, 38, 42, 48, 55, 57, 66], "central": [14, 36], "linspac": [14, 39, 41, 44, 45, 46, 47, 49, 55, 57, 60, 64, 66], "portfolio_mean_return": 14, "portfolio_mean_absolute_devi": 14, "ro": [14, 39, 41, 45], "_0": 14, "w_0": [14, 46, 47], "mad_portfolio_withriskfreeasset": 14, "rf": [14, 49], "138": [14, 27, 42, 49], "049": 14, "139": [14, 27, 38, 49], "117": [14, 27, 35, 62, 66], "037": 14, "906": 14, "00731": 14, "instruct": 14, "mpt": 14, "frontier": [14, 48, 49], "capit": [14, 37, 38, 44, 46, 47, 48, 49, 58], "minor": [14, 17], "veri": [14, 23, 28, 30, 33, 36, 50, 51, 53, 55, 63, 66], "depart": [14, 34, 53], "c_j": [15, 20], "x_j": [15, 20, 42], "ij": [15, 20, 22, 34, 35, 65, 66], "b_i": [15, 45], "net": [15, 26, 29, 31, 34, 39, 60, 65, 66], "margin": [15, 32, 37, 42, 50, 55, 64, 66], "uncertain": [15, 48, 55, 59, 63, 65, 66], "thorni": 15, "reserv": [15, 31], "plausibl": 15, "plant": [15, 16, 23, 35, 66], "_s": 15, "deem": 15, "probabilist": [15, 62], "conserv": [15, 34, 35, 44, 66], "bim_scenario": 15, "nprofit": [15, 39], "bim_resourc": 15, "4000": [15, 39, 45, 64], "set_index": [15, 21, 32, 35, 45, 53, 57, 65, 66], "navail": 15, "tolist": [15, 39], "scenario_profit": [15, 64], "resource_limit": 15, "worst_case_profit": [15, 63, 64], "nworst": 15, "worst_case_plan": 15, "33333": 15, "66670": 15, "outlook": 15, "worth": [15, 35, 39, 64], "investig": [15, 63, 66], "simpli": [15, 29, 32, 45, 53, 59, 62, 66], "max_profit": 15, "mean_cas": 15, "mean_case_profit": 15, "mean_case_plan": 15, "nmean": [15, 62], "17833": 15, "750": [15, 29], "expect": [15, 31, 35, 38, 46, 47, 48, 50, 51, 55, 57, 58, 60, 62, 63, 64, 65], "prefer": [15, 25, 42, 49, 65], "mean_case_outcom": 15, "worst_case_outcom": 15, "concat": [15, 52], "axi": [15, 24, 30, 37, 39, 42, 45, 52, 57, 59, 62, 66], "ylim": [15, 41, 42, 50, 55, 60], "15000": [15, 41, 64], "20000": [15, 31, 32, 64], "orang": [15, 35], "penalti": [15, 42, 48, 50, 59], "bad": [15, 22, 46, 49, 51, 63, 64], "payout": [15, 46], "favor": [15, 46], "occur": [15, 23, 29, 45, 46, 47], "why": [15, 29, 49, 57, 69], "peopl": [16, 30], "power": [16, 42, 50, 51, 57, 61, 66], "threshold": [16, 29, 30, 38, 42, 55, 57, 58, 66], "neither": [16, 30, 32], "seen": [16, 57], "still": [16, 59, 65, 66], "although": [16, 30, 55], "milo": [16, 17, 22, 23, 28, 29, 30, 33, 37, 65], "mathcal": [16, 35, 42, 48, 50, 53, 62, 65, 66], "subset": [16, 25, 42, 50, 69], "tacitli": 16, "perturb": [16, 55, 63, 65], "workforc": 16, "schedul": [16, 23, 27, 28, 65, 66], "recharg": 16, "electr": [16, 35, 51, 66], "vehicl": [16, 51], "disjunct": [16, 19, 21, 24, 27, 64, 69], "cryptarithm": 16, "puzzl": 16, "strip": [16, 20, 68], "pack": [16, 37], "job": 16, "shop": [16, 56], "mainten": [16, 32], "network": [16, 29, 31, 32, 34, 39, 65], "realiz": [17, 23, 29, 30, 32, 39, 48, 52, 55, 59, 62, 63, 65, 66], "wast": [17, 63], "gr": [17, 55], "accordingli": 17, "approx": [17, 39, 60, 62], "626": [17, 27, 62], "1123": 17, "762": [17, 50], "roughli": 17, "17628": 17, "loss": [17, 29, 31, 37, 42, 58, 59, 64], "ineffici": 17, "627": 17, "1124": 17, "unfeas": 17, "potenti": [17, 26, 29, 39, 42, 50, 63, 66], "intric": 17, "difficult": [17, 27, 36, 66], "safer": 17, "outlin": [17, 22, 67], "again": [18, 29, 30, 31, 35, 42, 48, 50, 63], "sophist": [18, 29], "acquisit": [18, 52], "protocol": 18, "supplier": [18, 20, 32, 59], "deliv": [18, 22, 32, 35, 39], "sheet": [18, 21], "unitari": 18, "batch": 18, "half": 18, "discount": [18, 44], "purchas": [18, 29, 31, 37, 39, 52, 62, 63, 64], "summari": [18, 29], "incur": [18, 20, 45, 66], "pai": [18, 32, 63], "kilogram": 18, "moment": [18, 23, 31, 35, 65], "usual": [18, 21, 22, 34, 42], "track": [18, 25, 27, 29, 62], "bui": [18, 29, 60, 64], "volum": [18, 29, 32, 35, 65], "ts": 18, "u_": [18, 34, 63], "tricki": 18, "b_": [18, 34, 35, 37, 65, 66], "r_t": [18, 49], "p_t": 18, "sure": [18, 25, 35, 46, 47, 58, 63, 65], "p_": [18, 35, 57, 59, 65, 66], "cent": [18, 32], "alpha_": 18, "setminu": [18, 65, 66], "h_p": 18, "ensur": [18, 30, 35, 38, 48, 53, 57, 62, 65, 66], "natur": [18, 25, 34, 36, 37, 39, 45, 51, 55, 59, 63, 69], "give": [18, 35, 39, 42, 44, 45, 47, 50, 53, 63, 66], "gamma_": 18, "textup": [18, 22, 25], "10000": [18, 19, 22, 24, 26, 29, 45], "automat": [18, 65], "input": [18, 35, 38, 42, 48, 50, 53, 58, 60, 62, 63, 65, 68], "bimproduction_v1": 18, "supplying_copp": 18, "supplying_batch": 18, "price_copper_sheet": 18, "price_batch": 18, "discounted_pric": 18, "batch_siz": 18, "copper_sheet_mass": 18, "copper_bucket_s": 18, "unitary_product": 18, "unitary_holding_cost": 18, "kappa": 18, "gamma": [18, 25, 38, 42, 48, 50, 55, 63], "omega": [18, 57], "units_in_batch": 18, "copper_in_bucket": 18, "inventory_capac": 18, "pairs_in_batch": 18, "pairs_in_sheet": 18, "bought": [18, 59, 60], "quickli": [18, 29, 31], "pars": [18, 30], "table1d": 18, "retriev": [18, 29], "table2d": 18, "table3d": 18, "multiindex": [18, 53], "from_product": 18, "m1": 18, "300": [18, 22, 24, 44, 45, 52, 55, 59, 62, 64], "0f": [18, 20, 27, 32, 34, 60, 66], "xtick": [18, 30, 52], "git": [18, 25, 26], "hash": [18, 25, 26], "594fa5a9d": [18, 25, 26], "copyright": [18, 25, 26], "mit": [18, 25, 26], "licenc": [18, 25, 26], "110216": 18, "1102": 18, "228": [18, 29, 45], "233": [18, 55], "274": [18, 44], "349": [18, 44, 65], "257": 18, "690": [18, 29], "326": 18, "371": [18, 45, 65, 66], "351": [18, 27], "1200": [18, 64, 66], "1300": [18, 45], "3100": 18, "72": [18, 20, 24, 29, 37, 41, 49, 60], "36": [18, 29, 37, 41, 60, 62, 64], "24": [18, 24, 25, 29, 32, 33, 35, 39, 42, 45, 49, 53, 62, 64, 65, 66], "2528": 18, "388": 18, "90": [18, 23, 26, 27, 29, 42, 50, 62, 63, 64], "2042": [18, 45], "bimproduction_v2": 18, "in_batch": 18, "m2": [18, 40], "1427": [18, 35], "1086": 18, "804": 18, "471": 18, "juli": 19, "1924": 19, "famou": [19, 30, 49, 59], "british": 19, "magazin": 19, "strand": 19, "henri": 19, "dudenei": 19, "regular": [19, 42, 50], "perplex": 19, "digit": [19, 29], "d": [19, 21, 22, 24, 25, 27, 32, 34, 35, 37, 39, 40, 42, 45, 46, 49, 50, 53, 57, 58, 59, 63, 65, 66, 68, 69], "o": [19, 20, 32, 44, 46, 47, 49, 50, 53, 57, 68], "along": [19, 24, 27, 29, 42, 50, 51, 68], "n_a": 19, "n_e": 19, "n_n": 19, "n_d": [19, 32], "n_m": 19, "n_o": 19, "n_r": 19, "n_y": 19, "n_b": 19, "lt": 19, "veebar": [19, 21, 22, 23, 24, 26, 27], "gdp": [19, 21, 22, 23, 24, 26, 27, 64], "filter": [19, 21, 22, 25, 27, 29, 31, 35, 53, 69], "messag": [19, 20, 30, 57, 66, 68], "leading_digit_nonzero": 19, "unique_assign": 19, "dummi": [19, 30, 53], "dummy_object": 19, "transformationfactori": [19, 21, 22, 23, 24, 26, 27, 64, 68], "bigm": [19, 21, 22, 23, 24, 26, 27, 62, 64], "apply_to": [19, 21, 22, 23, 24, 26, 27, 64, 68], "letters2num": 19, "join": [19, 25, 29, 31, 34, 49], "send": [19, 30], "monei": [19, 29, 32, 44, 49, 59], "gdpopt": [19, 20], "mip": 19, "gecod": 19, "refactor": 19, "On": [20, 21, 23, 24, 35, 46, 49, 55, 59], "notic": [20, 55, 63, 68], "exercis": [20, 35, 62], "face": [20, 22, 38], "strike": 20, "speedup": 20, "apt": 20, "qq": 20, "coinor": 20, "fulfil": [20, 37], "simultan": [20, 21, 31, 37, 47], "decid": [20, 22, 32, 35, 59, 62, 63, 66], "otherwis": [20, 25, 30, 33, 35, 42, 47, 50, 55, 57, 63], "sum_j": [20, 22, 65], "sum_i": 20, "relax": [20, 24, 37, 39, 42, 50, 57], "inadvert": 20, "around": [20, 30, 31, 52, 53, 55], "weaker": 20, "itertool": 20, "perf_count": [20, 30, 33], "pc": [20, 30, 33], "tqdm": [20, 30], "subprocess": 20, "listavailablesolv": 20, "shell_command": 20, "help": [20, 35, 57, 63, 65], "check_output": 20, "shell": 20, "decod": 20, "startswith": 20, "endswith": 20, "getsolvernam": 20, "try": [20, 25, 38, 50, 53, 63, 66, 68], "switchcutsoff": 20, "solver_nam": 20, "elif": [20, 24, 34], "mip_cuts_bqp": 20, "mip_cuts_cliqu": 20, "mip_cuts_cov": 20, "mip_cuts_disjunct": 20, "mip_cuts_flowcov": 20, "mip_cuts_pathcut": 20, "mip_cuts_gomori": 20, "mip_cuts_gubcov": 20, "mip_cuts_impli": 20, "mip_cuts_localimpli": 20, "mip_cuts_liftproj": 20, "mip_cuts_mircut": 20, "mip_cuts_mcfcut": 20, "mip_cuts_rlt": 20, "mip_cuts_zerohalfcut": 20, "ergo": 20, "definit": [20, 38, 40, 42, 48, 50, 58, 63], "xpress": [20, 21, 22, 55], "cutstrategi": 20, "switchpresolveoff": 20, "preprocessing_presolv": 20, "limitsolvetim": 20, "max_in_second": 20, "timelimit": 20, "time_limit": 20, "maxtim": [20, 22], "closureformaxtim": 20, "compos": [20, 68], "arg": [20, 37, 42, 45, 50, 68], "kwarg": [20, 42, 50], "func": [20, 68], "initial_solv": 20, "appsi_cbc": 20, "gloa": 20, "lbb": 20, "loa": 20, "ric": 20, "mindtpi": 20, "ecp": 20, "fp": [20, 35, 37, 42], "goa": 20, "oa": [20, 46, 47], "mpec_minlp": 20, "mpec_nlp": 20, "multistart": 20, "fsolv": 20, "newton": 20, "root": 20, "secant": 20, "trustregion": 20, "facilitylocationcommon": 20, "chooseonefacil": 20, "facilitylocationweak": 20, "weak": 20, "serveifopen": 20, "facilitylocationstrong": 20, "getsolut": 20, "generatefacilitylocationinst": 20, "noffacil": 20, "nofcustum": 20, "xc": [20, 27], "randint": [20, 27, 30, 45, 57], "yc": [20, 27], "xf": [20, 21], "dist": [20, 24], "showfacilityloc": 20, "gca": [20, 29, 35, 55], "proper": [20, 48, 52, 65], "hood": 20, "clever": 20, "gurobipi": 20, "cp310": 20, "manylinux2014_x86_64": 20, "whl": 20, "mb": 20, "2k": 20, "90m": 20, "0m": 20, "32m12": 20, "31m48": 20, "eta": 20, "36m0": 20, "25hinstal": 20, "22": [20, 22, 24, 25, 29, 30, 35, 37, 39, 53, 62, 66], "manylinux1_x86_64": 20, "32m44": 20, "31m20": 20, "32m72": 20, "31m8": 20, "25hrequir": 20, "0a0": 20, "usr": 20, "local": [20, 39, 68, 69], "lib": [20, 29, 31, 35], "python3": [20, 29, 31, 35], "23": [20, 24, 25, 29, 35, 37, 42, 45, 53, 58, 62, 66, 69], "available_solv": 20, "appsi_cplex": 20, "appsi_gurobi": 20, "cplex_direct": 20, "cplex_persist": 20, "gurobi_direct": [20, 30, 39, 45], "gurobi_persist": 20, "xpress_direct": 20, "xpress_persist": 20, "subplots_adjust": 20, "hspace": 20, "licens": [20, 45], "path": [20, 29, 31, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58], "file": [20, 35, 68], "init": 20, "fico": 20, "xpauth": 20, "xpr": 20, "increasingli": [20, 30, 51, 66], "faster": [20, 23, 30, 33, 48, 63], "solveinst": 20, "fromkei": 20, "leav": [20, 27, 50, 59, 60], "rfind": 20, "warn": [20, 30, 35, 42, 50, 57, 66], "solverresult": 20, "abort": 20, "classic": [21, 22, 37, 40, 47], "hous": [21, 46, 47, 49], "patient": 21, "hospit": 21, "meal": 21, "fast": [21, 29], "restaur": [21, 22], "devic": [21, 42, 51, 63], "durat": [21, 22], "makespan": 21, "christel": [21, 22], "gueret": [21, 22], "christian": [21, 22, 25], "prin": [21, 22], "marc": [21, 22], "sevaux": [21, 22], "mp": [21, 22], "flow": [21, 28, 29, 39, 61, 66], "minut": [21, 24, 35, 62], "yellow": [21, 35], "28": [21, 25, 29, 35, 37, 39, 45, 49, 53, 62, 66], "decompos": 21, "until": [21, 22, 23, 33, 37, 39, 42, 47, 55, 59, 63], "prerequisit": 21, "json": 21, "dur": [21, 53], "paper_1": 21, "prec": 21, "paper_2": 21, "paper_3": 21, "preced": [21, 29], "start_": 21, "wise": 21, "conflict": [21, 33, 42], "jobshopmodel": 21, "jobshop_model": 21, "cross": [21, 29, 31, 39], "taskord": 21, "establish": [21, 29, 62], "minimize_makespan": 21, "finish_task": 21, "no_overlap": [21, 23, 27], "pyomomodel": 21, "0x7f90cf08ad60": 21, "jobshop_solv": 21, "jobshop": 21, "87": [21, 29, 31, 42, 62], "64": [21, 29, 32, 35, 65, 66], "59": [21, 29, 49], "nschedul": 21, "sort_valu": [21, 22, 25, 53], "mpl": 21, "bar_styl": [21, 53], "solid_capstyl": [21, 22, 24, 37, 53], "butt": [21, 22, 24, 37, 53], "text_styl": [21, 53], "bold": [21, 22, 27, 34, 37, 53], "center": [21, 22, 24, 25, 27, 34, 37, 42, 46, 49, 53, 55, 56], "va": [21, 22, 25, 27, 37, 47, 53], "dark2": 21, "jdx": 21, "mdx": 21, "xs": [21, 24], "idx": [21, 30, 42, 50], "attent": [21, 50], "dunn": 21, "2013": [21, 39, 63], "recip": 21, "mixer": 21, "reactor": 21, "recipe_to_task": 21, "recipea": 21, "recipeb": 21, "recipec": 21, "a1": 21, "a2": 21, "a3": 21, "a4": 21, "took": [21, 29], "gain": [21, 29, 30, 31], "append": [21, 29, 31, 37, 38, 48, 50, 52, 55, 57, 63, 68], "b1": 21, "b2": 21, "equip": 21, "vee": [21, 26], "jobshopmodel_clean": 21, "jobshop_model_clean": 21, "tclean": 21, "hull": [21, 23], "intermedi": [21, 39, 68], "vessel": 21, "precid": 21, "sequenc": [21, 22, 23, 29, 31, 53, 68], "zw": 21, "basi": [21, 29, 57, 62], "jobshop_model_clean_zw": 21, "mode": [21, 23, 34, 35, 57], "appleg": 21, "david": [21, 46, 69], "william": [21, 46, 47], "cook": 21, "orsa": 21, "journal": [21, 29, 37, 44, 46, 47, 49], "149": [21, 62], "156": [21, 27], "pdf": [21, 29, 37, 39, 45, 46, 47, 49, 60, 64], "beaslei": 21, "electron": 21, "mail": 21, "societi": [21, 44], "41": [21, 29, 37, 49, 62, 63, 65], "1069": 21, "1072": 21, "gu\u00e9ret": 21, "contract": [21, 32], "1999": [21, 37, 44, 45], "00034": 21, "mann": 21, "alan": 21, "1960": 21, "219": 21, "223": [21, 24], "slow": 21, "frequent": [21, 42, 50, 69], "accommod": [21, 23, 29, 33], "descreas": 21, "consequ": [21, 39, 42, 50, 62], "busi": [22, 24, 37, 45, 62, 64], "student": [22, 33, 45, 69], "courier": 22, "server": 22, "wait": [22, 29], "thread": 22, "assembl": 22, "heurist": [22, 27, 29], "address": [22, 32, 37, 47, 64], "past": [22, 62], "scenario": [22, 29, 55, 57, 60, 64, 66, 68, 69], "schedule_job": 22, "seq": [22, 45], "27": [22, 25, 29, 53, 65], "line2d": 22, "width": [22, 29, 33, 34, 35, 39, 45, 53, 55], "window": [22, 35], "fill_between": [22, 25, 27, 37, 41, 45], "total_past_du": 22, "spine": [22, 37], "set_vis": [22, 37, 53], "custom_lin": 22, "savefig": [22, 24, 29, 52], "machinescheduling_": 22, "svg": [22, 24, 52], "dpi": [22, 24, 52], "bbox_inch": [22, 24, 29, 52], "31": [22, 25, 29, 65, 66], "priorit": 22, "familiar": [22, 24, 37, 41, 45, 68], "homework": 22, "circumst": [22, 69], "late": 22, "longest": 22, "twice": [22, 29, 65], "famili": [22, 24, 30, 50], "disjuct": 22, "machine_schedul": 22, "orderd": 22, "job_releas": 22, "job_dur": 22, "past_due_constraint": 22, "xor": [22, 23, 24, 26, 27, 64], "machine_deconflict": 22, "job_a": 22, "job_b": 22, "minimize_past": 22, "optimalschedul": 22, "extract_valu": [22, 57], "outperform": 22, "nonetheless": 22, "tackl": [22, 30], "z_": [22, 39, 44, 50, 62], "slower": [22, 33], "machine_schedulemilo": 22, "machine_deconflict_a": 22, "machine_deconflict_b": 22, "optimalschedule_milo": 22, "c_t": [23, 30], "shut": 23, "dure": [23, 25, 33, 35, 39, 64, 69], "x_t": 23, "abl": [23, 29, 30, 45], "earn": [23, 39], "y_t": [23, 30], "overlap": [23, 25, 27], "consecut": [23, 25], "ldot": [23, 25, 27, 29, 30, 31, 33, 37, 42, 44, 50, 53, 62, 63, 65], "sai": [23, 29, 30, 31, 33, 35, 55, 65], "exclus": [23, 24, 26, 27, 37], "convex": [23, 28, 29, 37, 38, 41, 45, 46, 47, 49, 50, 55, 58], "plane": [23, 45, 53, 62], "maintenance_plan": 23, "required_mainten": 23, "required_shutdown": 23, "plot_schedul": 23, "tab20": [23, 24, 27, 33], "daili": [23, 25, 26], "set_tick": 23, "set_ticklabel": 23, "length": [23, 24, 29, 31, 37, 50], "rng": [23, 27, 52, 55, 62, 63, 65, 66], "default_rng": [23, 52, 55, 62, 63, 65, 66], "shutdown": 23, "safe": 23, "decreas": [23, 45, 66], "_t": 23, "upos_max": 23, "3334": 23, "uneg_max": 23, "maintenance_planning_ramp": 23, "upo": 23, "uneg": 23, "skip": [23, 24, 35, 37, 68, 69], "frequenc": [23, 49, 62, 66], "particularli": [23, 30, 32, 66, 69], "revis": [23, 39], "postpon": 23, "wedg": 23, "summat": [23, 39, 41, 53, 64], "termin": [23, 30, 32, 39, 55, 59], "paradox": [23, 47], "maintenance_planning_ramp_oper": 23, "sumi": 23, "sprd": 23, "comment": [23, 29, 63, 69], "disj": 23, "rather": [23, 29, 32, 37, 40, 45, 50, 62, 65], "hint": 23, "z_t": 23, "systemat": 23, "effort": [23, 27], "visit": 24, "sightse": 24, "tour": 24, "road": [24, 34, 51], "trip": [24, 31], "routin": [24, 69], "pre": [24, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 63, 65, 69], "rest": [24, 25, 33, 65], "stop": [24, 46, 55, 63], "batteri": 24, "driver": 24, "ahead": 24, "rate": [24, 29, 31, 38, 42, 47, 48, 58, 66], "distanc": [24, 42, 50, 69], "arbitrari": [24, 41, 53], "drive": 24, "littl": [24, 32, 35, 63, 68, 69], "c_": [24, 29, 34, 37], "150": [24, 29, 31, 32, 37, 44, 55, 60, 62, 64], "kw": [24, 42, 50], "unforeseen": 24, "event": [24, 29, 59], "never": [24, 42, 50, 55], "drop": [24, 37, 46, 66], "comfort": 24, "lost": [24, 30, 46, 63], "assumpt": [24, 29, 55, 57, 58, 62], "travel": [24, 29, 51, 62], "speed": [24, 42, 50, 66], "km": 24, "discharg": 24, "kwh": 24, "elaps": [24, 33], "d_i": [24, 27, 35, 45, 57, 65, 66], "c_i": [24, 35, 45, 57, 65, 66], "arriv": [24, 29, 32, 34, 50, 53, 55, 63], "arr": [24, 53], "dep": [24, 53], "d_": [24, 29, 59], "r_i": [24, 27, 38, 47, 48, 58, 65], "t_i": [24, 44, 45], "script": [24, 29, 62], "departur": [24, 53], "opportun": [24, 31, 59, 63, 68], "That": [24, 42, 46, 50, 53, 62, 66], "heterogen": 24, "n_charging_st": 24, "randomli": 24, "cumsum": [24, 27, 46], "triangular": 24, "02d": [24, 25, 53], "s00": 24, "112": [24, 45, 49, 57, 60], "s01": 24, "294": 24, "s02": 24, "439": 24, "s03": 24, "517": 24, "s04": 24, "598": 24, "s05": 24, "729": 24, "s06": 24, "773": 24, "s07": 24, "933": 24, "s08": 24, "1070": 24, "s09": 24, "1210": [24, 55], "s10": 24, "1340": 24, "s11": 24, "1475": 24, "s12": 24, "s13": 24, "1680": 24, "s14": 24, "1798": 24, "s15": 24, "1883": 24, "s16": 24, "1998": [24, 37, 45], "s17": 24, "2087": 24, "s18": 24, "2208": 24, "19": [24, 25, 29, 32, 37, 38, 39, 41, 48, 53, 62, 65, 66], "s19": 24, "2259": 24, "plot_stat": 24, "ys": 24, "fontsiz": [24, 27, 30, 32, 37, 39, 45, 53], "275": [24, 55], "c_max": 24, "c_min": 24, "veloc": 24, "t_lost": 24, "t_rest": 24, "r_max": 24, "ev_plan": 24, "on_rout": 24, "ev": [24, 59], "segment": 24, "c_arr": 24, "c_dep": 24, "t_arr": 24, "t_dep": 24, "r_arr": 24, "r_dep": 24, "min_tim": [24, 53], "drive_tim": 24, "rest_tim": 24, "drive_dist": 24, "thtat": 24, "disjunct_1": 24, "disjunct_2": 24, "t_stop": 24, "nan": [24, 35, 64, 66], "122000": 24, "123": [24, 27], "072000": 24, "949000": 24, "157187": 24, "79": [24, 29, 35, 49, 66], "224000": 24, "83": [24, 29, 42], "376000": 24, "208187": 24, "603187": 24, "48": [24, 29, 35, 37, 39, 45, 64, 65, 66], "672000": 24, "381187": 24, "162973": 24, "91": [24, 29, 31, 42, 50], "512000": 24, "781787": 24, "972973": 24, "284973": 24, "584000": 24, "725973": 24, "605680": 24, "304000": 24, "879707": 24, "199680": 24, "63": [24, 29, 41, 44, 60, 62, 63], "048000": 24, "576680": 24, "079107": 24, "576000": 24, "502427": 24, "478107": 24, "124773": 24, "646666": 24, "421773": 24, "872000": 24, "772773": 24, "941662": 24, "448000": 24, "781333": 24, "168889": 24, "161662": 24, "501333": 24, "992662": 24, "433747": 24, "37": [24, 29, 37, 39, 49, 55, 62], "557333": 24, "78": [24, 29, 52, 63], "720000": [24, 29], "441085": 24, "609747": 24, "496000": 24, "463747": 24, "742253": 24, "960000": 24, "278506": 24, "887253": 24, "480000": [24, 29], "907253": 24, "visualizeevplan": 24, "xv": 24, "cv": 24, "linewidth": [24, 35], "ev_result": 24, "entitl": [25, 50], "carballo": 25, "lozano": 25, "post": [25, 53, 69], "campu": 25, "primarili": 25, "eight": 25, "morn": [25, 62], "night": [25, 35], "sundai": 25, "employe": 25, "saturdai": 25, "principl": [25, 63, 69], "ten": [25, 65], "predetermin": [25, 37], "staf": [25, 63], "seven": 25, "weekend": [25, 62], "recap": 25, "w_1": 25, "w_2": 25, "w_n": [25, 46, 47, 49], "mon": 25, "tue": 25, "sun": [25, 44, 46, 49], "slot": [25, 33], "e_": [25, 62], "fill": [25, 32, 55, 57, 64], "n_w": 25, "e_w": 25, "loop": [25, 29, 37, 55, 69], "24h": 25, "d_1": 25, "s_1": 25, "d_2": 25, "s_2": 25, "d_3": 25, "s_3": 25, "mind": [25, 63], "beyond": 25, "shift_schedul": 25, "avaiabl": 25, "wed": [25, 30], "fri": 25, "sat": 25, "suffici": [25, 29, 32, 37, 63], "required_work": 25, "forti": 25, "forty_hour_limit": 25, "required_rest": 25, "d1": 25, "s1": 25, "d2": 25, "s2": 25, "d3": 25, "s3": 25, "is_need": 25, "is__weekend": 25, "minimize_work": 25, "particip": [25, 32, 65], "patch": [25, 27, 45, 55], "rectangl": [25, 27, 32, 45, 55], "bw": [25, 47], "colormap": 25, "add_patch": [25, 27, 45, 55], "id": [25, 37, 53, 66], "categori": [25, 57, 62, 68], "categoricaldtyp": 25, "worker_typ": 25, "day_typ": 25, "shift_typ": 25, "w06": 25, "w07": 25, "w01": 25, "w03": 25, "w04": 25, "w02": 25, "w05": 25, "receiv": [25, 29, 31, 32, 37, 39, 45, 46, 51], "worker_schedul": 25, "groupbi": [25, 35, 52, 57], "nwork": 25, "to_str": 25, "w08": 25, "w09": 25, "w10": 25, "day_schedul": 25, "nshift": 25, "discret": [26, 39, 46, 57, 62], "proposit": 26, "truth": 26, "technolog": [26, 39], "production_x": [26, 69], "production_i": [26, 69], "maximize_profit": 26, "labora": 26, "laborb": 26, "highli": [26, 32, 68], "assess": [26, 42, 52, 60], "benefici": 26, "underbrac": [26, 31, 39, 59], "40x": [26, 69], "30y": [26, 69], "60x": 26, "embed": [26, 29, 42, 45, 50, 68], "old": [26, 32], "profit_constr_1": 26, "profit_constr_2": 26, "laborb_1": 26, "laborb_2": 26, "3600": [26, 59], "benefit": [26, 32, 39, 65, 68, 69], "intellig": [26, 29], "partit": [26, 62], "sub": 26, "support": [26, 29, 36, 43, 45, 46, 49, 55, 68, 69], "sp": [27, 37], "onto": [27, 50], "shortest": [27, 29], "edg": [27, 29, 30, 32, 33, 34, 53, 65, 66], "guillotin": 27, "rectangular": 27, "motiv": [27, 32, 37], "industri": [27, 35, 39, 49, 57], "placement": 27, "macro": 27, "semiconductor": 27, "layout": [27, 34, 35, 45], "wood": 27, "textil": 27, "lai": 27, "workstat": 27, "bandwidth": 27, "endpoint": 27, "co_2": 27, "oil": [27, 39], "recoveri": 27, "combinatori": 27, "belong": 27, "grow": [27, 46, 64], "exponenti": [27, 46, 47, 49], "though": [27, 47], "depth": 27, "w_i": 27, "concret": 27, "millimet": 27, "generate_box": 27, "max_width": 27, "max_depth": 27, "deepest": 27, "154": [27, 50, 52], "176": [27, 35, 66], "121": [27, 49], "175": [27, 35, 49, 55, 60, 62, 66], "196": [27, 57], "186": [27, 49], "85": [27, 29, 35, 42, 62, 66], "126": [27, 31], "99": [27, 29, 31, 33, 35, 49, 66], "352": 27, "divid": [27, 42, 46, 49, 50], "lb": [27, 44, 45, 46, 47, 49, 50, 55, 69], "front": 27, "coordin": [27, 45], "corner": 27, "degre": [27, 29, 37, 49, 50, 57, 63], "frame": 27, "trivial": [27, 46, 65], "arrang": [27, 28, 32, 42], "pack_boxes_v0": 27, "copi": [27, 37, 39, 52, 53, 63], "show_box": 27, "facecolor": [27, 45], "annot": [27, 39, 45], "292": 27, "431": [27, 55], "552": 27, "748": 27, "1060": 27, "1125": 27, "370": 27, "occupi": 27, "vertic": [27, 33, 42, 55], "drawn": 27, "reproduc": [27, 42], "lineup": 27, "prevent": 27, "doesn": [27, 30], "assur": [27, 69], "pack_boxes_v1": 27, "minimize_width": 27, "bounding_box": 27, "987": 27, "833": [27, 52], "694": 27, "573": 27, "377": 27, "191": [27, 44], "surpris": [27, 37], "did": [27, 30, 39, 50, 66], "tightli": [27, 41], "orient": [27, 57], "pack_boxes_v2": 27, "yloc": 27, "743": 27, "814": 27, "487": 27, "366": 27, "249": [27, 44], "164": 27, "obvious": 27, "closer": 27, "stack": [27, 50, 62], "deeper": 27, "pack_boxes_v3": 27, "height": 27, "376": 27, "239": [27, 45], "256": [27, 55, 62], "307": 27, "382": 27, "338": 27, "372": [27, 29], "unchang": [27, 62], "especi": [27, 29, 33, 69], "suscept": [27, 35, 65, 66], "trespalacio": 27, "grossmann": 27, "modif": [27, 55, 63], "2017": [27, 46, 47, 49], "annal": 27, "258": 27, "747": [27, 29, 52], "759": 27, "doi": [27, 29, 39], "1007": [27, 39], "s10479": 27, "016": [27, 45], "2112": 27, "pack_boxes_v4": 27, "261": 27, "267": 27, "253": [27, 35, 44], "243": [27, 55], "dealt": 28, "oblivi": 28, "dinner": 28, "seat": [28, 61], "transport": [28, 32, 34, 39, 64], "franchis": 28, "gasolin": [28, 41], "graph": [28, 30, 32, 34, 35, 53], "cryptocurr": 28, "arbitrag": 28, "energi": [28, 44, 51, 56, 61, 65], "dispatch": [28, 56, 61, 65], "forex": 28, "liquid": 29, "owner": [29, 42], "currenc": [29, 31], "wallet": 29, "transact": [29, 31], "risk": [29, 31, 38, 42, 48, 50, 57, 58, 63, 65, 66], "hypothesi": [29, 39], "exploit": [29, 30, 31], "reach": [29, 30, 39, 55], "equilibrium": [29, 66], "fleet": [29, 51], "rapid": [29, 31], "trader": [29, 31], "march": 29, "propag": 29, "diagram": [29, 39, 45], "restart": 29, "kernel": [29, 44, 45, 46, 47, 49, 55, 57], "jeff": [29, 31, 35], "anaconda3": [29, 31, 35], "site": [29, 31, 35], "api": 29, "aiodn": 29, "aiohttp": 29, "setuptool": 29, "certifi": 29, "2018": [29, 45, 46, 49], "2022": [29, 31, 39, 40, 46, 49], "request": 29, "yarl": 29, "cryptographi": 29, "pycar": 29, "aiosign": 29, "frozenlist": 29, "charset": 29, "multidict": 29, "async": 29, "timeout": 29, "0a3": 29, "attr": 29, "cffi": 29, "urllib3": 29, "idna": 29, "pycpars": 29, "os": [29, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 66], "timeit": [29, 37], "default_tim": 29, "timer": 29, "nx": [29, 30, 31, 33, 35, 53, 65, 66], "3d": [29, 45], "ljust": 29, "ac": [29, 45], "alpaca": 29, "ascendex": 29, "bequant": 29, "bigon": 29, "binanc": 29, "binancecoinm": 29, "binanceu": 29, "binanceusdm": 29, "bit2c": 29, "bitbank": 29, "bitbai": 29, "bitbn": 29, "bitcoincom": 29, "bitfinex": 29, "bitfinex2": 29, "bitflyer": 29, "bitforex": 29, "bitget": 29, "bithumb": 29, "bitmart": 29, "bitmex": 29, "bitopro": 29, "bitpanda": 29, "bitru": 29, "bitso": 29, "bitstamp": 29, "bitstamp1": 29, "bittrex": 29, "bitvavo": 29, "bkex": 29, "bl3p": 29, "blockchaincom": 29, "btcalpha": 29, "btcbox": 29, "btcex": 29, "btcmarket": 29, "btctradeua": 29, "btcturk": 29, "buda": 29, "bybit": 29, "cex": 29, "43": [29, 37, 45, 52], "coinbas": 29, "coinbaseprim": 29, "coinbasepro": 29, "46": 29, "coincheck": 29, "coinex": 29, "coinfalcon": 29, "49": [29, 37, 49], "coinmat": 29, "coinon": 29, "coinspot": 29, "cryptocom": 29, "53": [29, 35, 37, 40, 65, 66], "currencycom": 29, "55": [29, 32, 49, 60], "deribit": 29, "digifinex": 29, "exmo": 29, "flowbtc": 29, "fmfwio": 29, "gate": 29, "61": [29, 45, 63], "gateio": 29, "gemini": 29, "hitbtc": 29, "hitbtc3": 29, "hollaex": 29, "huobi": 29, "huobijp": 29, "huobipro": 29, "69": [29, 65], "idex": 29, "70": [29, 37, 62], "independentreserv": 29, "indodax": 29, "itbit": 29, "73": [29, 32, 35, 37, 60, 65], "kraken": 29, "74": 29, "krakenfutur": 29, "kucoin": 29, "kucoinfutur": 29, "77": [29, 52, 66], "kuna": 29, "latoken": 29, "lbank": 29, "lbank2": 29, "luno": 29, "lykk": 29, "mercado": 29, "mexc": 29, "mexc3": 29, "ndax": 29, "novadax": 29, "oceanex": 29, "okcoin": 29, "okex": 29, "okex5": 29, "92": [29, 37, 50], "okx": 29, "93": [29, 31, 34, 45, 50, 63], "paymium": 29, "94": [29, 42, 50], "phemex": 29, "poloniex": 29, "96": [29, 35, 37, 42], "poloniexfutur": 29, "probit": 29, "ripio": 29, "stex": 29, "tidex": 29, "timex": 29, "102": [29, 32, 35, 50, 66], "tokocrypto": 29, "103": [29, 44, 60], "upbit": 29, "wavesexchang": 29, "105": [29, 37, 60], "wazirx": 29, "106": 29, "whitebit": 29, "107": [29, 49, 62, 64], "woo": 29, "108": [29, 35, 41, 64], "yobit": 29, "109": [29, 48, 49], "zaif": 29, "110": [29, 35, 44, 49, 66], "111": [29, 39, 42, 49, 53], "zonda": 29, "terminolog": [29, 33], "host": 29, "slash": 29, "quot": 29, "denomin": [29, 44], "eth": 29, "btc": 29, "ethereum": 29, "bitcoin": 29, "bid": [29, 31], "node": [29, 30, 31, 32, 33, 34, 35, 53, 57, 65, 66], "destin": [29, 32, 69], "sampl": [29, 42, 50, 55, 57, 62, 65, 66], "get_exchange_dg": 29, "minimum_in_degre": 29, "load_market": 29, "dg": [29, 53], "digraph": [29, 30, 31, 32, 34, 35, 53], "add_edg": [29, 31, 53], "in_degre": 29, "remove_nod": 29, "out_degre": 29, "topological_sort": 29, "gold": [29, 32], "lightblu": [29, 31, 32, 34], "draw_dg": 29, "rad": 29, "draw": [29, 33, 34, 45, 47, 53], "n_node": 29, "po": [29, 31, 33, 34, 35, 41, 53], "circular_layout": [29, 53], "draw_networkx": [29, 31], "with_label": [29, 31, 33, 34], "node_color": [29, 31, 33, 35], "edge_color": [29, 34, 35, 53], "node_s": [29, 31, 33, 35, 53], "font_siz": [29, 34], "arrows": [29, 31], "connectionstyl": 29, "arc3": 29, "draw_networkx_edge_label": [29, 31, 34], "edge_label": [29, 31, 34], "src": [29, 32, 69], "dst": [29, 32, 69], "exchange_dg": 29, "170": [29, 37, 49, 64], "522": 29, "match": [29, 30, 35, 57, 66], "buyer": 29, "incom": [29, 30, 31, 39, 53, 65], "highest": [29, 47], "binance_us_orderbook_20230313_152616": 29, "order_book": 29, "githubusercont": [29, 35, 42, 50, 57, 65, 66], "com": [29, 31, 35, 37, 39, 42, 44, 45, 46, 47, 48, 49, 50, 57, 65, 66, 68], "main": [29, 35, 42, 50, 57, 65, 66], "glob": 29, "fname": 29, "orderbook": 29, "nread": 29, "binance_us_orderbook_sav": 29, "timestamp": 29, "bid_pric": 29, "bid_volum": 29, "ask_pric": 29, "ask_volum": 29, "06": [29, 38, 48, 60, 65], "529": 29, "069735": 29, "012000": 29, "069759": 29, "050000": 29, "bnb": 29, "012743": 29, "012755": 29, "ada": 29, "637": [29, 45, 63], "2168": 29, "sol": [29, 57], "000935": 29, "420000": 29, "000936": 29, "120000": [29, 39], "matic": 29, "000052": 29, "200000": [29, 35, 39], "mana": 29, "848": 29, "000027": 29, "831": 29, "1409": 29, "trx": 29, "905": 29, "000003": 29, "25352": 29, "960": 29, "000214": 29, "994": 29, "900000": 29, "891": 29, "600000": [29, 35], "usdt": 29, "07": [29, 38, 48], "23373": 29, "920000": 29, "118619": 29, "23376": 29, "045275": 29, "065": 29, "1630": 29, "950000": 29, "770000": 29, "500000": [29, 32], "297": 29, "857700": 29, "800000": [29, 35], "891900": 29, "172": [29, 62], "348630": 29, "348750": 29, "511": 29, "busd": 29, "226": 29, "999500": 29, "293433": 29, "930000": 29, "999600": 29, "317175": 29, "730000": 29, "288": [29, 64], "857000": 29, "870000": 29, "863500": 29, "usdc": 29, "342": [29, 49], "000100": 29, "307657": 29, "000200": 29, "299181": 29, "394": 29, "203000": 29, "1664": 29, "205000": 29, "5405": 29, "447": 29, "631000": 29, "157": [29, 46, 49, 50], "632200": 29, "571": 29, "501": 29, "069280": 29, "10824": 29, "069330": 29, "10818": 29, "612": [29, 35, 55], "23371": 29, "440000": 29, "021500": 29, "830000": 29, "665": 29, "763000": 29, "670000": 29, "952500": 29, "340000": 29, "719": 29, "210000": 29, "510000": 29, "760000": 29, "255000": 29, "772": 29, "203410": 29, "623": 29, "100000": [29, 32, 45], "204540": 29, "415": [29, 44, 45, 66], "893": 29, "999900": 29, "329027": 29, "279879": 29, "620000": 29, "950": 29, "630700": 29, "632100": 29, "3054": 29, "003": [29, 45], "348000": 29, "6582": 29, "349000": 29, "997": 29, "056": [29, 62], "390000": 29, "181": [29, 49], "090000": 29, "114": [29, 35, 66], "069290": 29, "10823": 29, "069390": 29, "25220": 29, "400000": [29, 35], "660000": 29, "020000": 29, "990000": 29, "051000": 29, "160000": 29, "810000": 29, "215000": 29, "298": [29, 65, 66], "520000": 29, "880000": 29, "201": [29, 44, 45], "080000": 29, "368": [29, 52], "348200": 29, "8615": 29, "349400": 29, "2433": 29, "433": [29, 45], "23366": 29, "049540": 29, "23394": 29, "360000": 29, "049500": 29, "485": 29, "1629": 29, "890000": 29, "497400": 29, "1631": 29, "490000": 29, "usd": [29, 31], "010000": 29, "007463": 29, "048805": 29, "675": 29, "564550": 29, "740000": 29, "580700": 29, "730": 29, "10407": 29, "954839": 29, "680000": 29, "782": 29, "900200": 29, "342000": 29, "835": 29, "348800": 29, "348900": 29, "3000": [29, 45, 64], "942": 29, "79157": 29, "795593": 29, "204000": 29, "937": 29, "204500": 29, "09": [29, 32, 38, 48, 57], "5050": 29, "300000": 29, "517682": 29, "170000": 29, "631600": 29, "572": 29, "155": [29, 31, 50, 62], "999100": 29, "4534": 29, "7591": 29, "820000": 29, "858100": 29, "865900": 29, "290000": 29, "069200": 29, "225602": 29, "069400": 29, "224245": 29, "prospect": 29, "counter": 29, "rightarrow": [29, 31, 40, 42, 46, 50, 68], "v_b": 29, "v_q": 29, "held": [29, 59], "convers": [29, 31, 41, 44], "arc": [29, 30, 31, 34, 53], "chanc": [29, 46, 56, 65], "highlight": [29, 35, 44, 53], "order_book_to_dg": 29, "dg_order_book": 29, "isnan": 29, "order_book_dg": 29, "5s": 29, "16f": 29, "4668": 29, "534080": 29, "190981": 29, "335068": 29, "003488": 29, "403701": 29, "038263": 29, "66844": 29, "919786": 29, "032433": 29, "1068": 29, "261938": 29, "014154": 29, "19391": 29, "118868": 29, "007746": 29, "36968": 29, "576710": 29, "038113": 29, "335570": 29, "469799": 29, "075549": 29, "000043": 29, "1058": 29, "348400": 29, "000613": 29, "815": 29, "385000": 29, "003357": 29, "313520": 29, "867384": 29, "178": [29, 35, 49, 66], "281000": 29, "000400": 29, "317048": 29, "859708": 29, "045738": 29, "502": 29, "860500": 29, "999800": 29, "299240": 29, "836200": 29, "829876": 29, "6513": 29, "748000": 29, "581778": 29, "360": [29, 35, 45, 64, 66], "986200": 29, "423770": 29, "053538": 29, "601845": 29, "003356": 29, "399": [29, 45, 59], "256350": 29, "843800": 29, "830192": 29, "499": 29, "884100": 29, "582028": 29, "1930": [29, 37], "433400": 29, "865330": 29, "953000": 29, "045662": 29, "3965": 29, "871000": 29, "411298": 29, "043556": 29, "1192": [29, 52], "226490": 29, "350": [29, 55], "624150": 29, "045704": 29, "4399": 29, "630400": 29, "862049": 29, "850": 29, "125140": 29, "1158": 29, "020820": 29, "2431": 29, "396900": 29, "1140": 29, "900820": 29, "970718": 29, "954935": 29, "163968": 29, "852255": 29, "866151": 29, "1046": 29, "700000": 29, "795513": 29, "920652": 29, "830220": 29, "1129": 29, "218750": 29, "583281": 29, "361": 29, "489944": 29, "7592": 29, "579182": 29, "045733": 29, "927311": 29, "409222": 29, "15562": 29, "637700": 29, "itself": [29, 63], "unifi": 29, "treatment": [29, 31, 39, 62, 64], "pose": [29, 35], "i_0": 29, "i_1": [29, 63], "i_2": [29, 63], "i_": 29, "i_n": 29, "prod_": [29, 47], "i_k": 29, "limits_": [29, 30, 53, 63, 65], "becam": 29, "cyclic": 29, "permut": 29, "daunt": 29, "bellman": [29, 30], "ford": [29, 30, 45], "negative_edge_cycl": 29, "luckili": [29, 36], "find_negative_cycl": 29, "bp": [29, 37], "thicker": 29, "sum_weight": 29, "arb": [29, 31], "exp": [29, 46, 47, 49, 50], "dollar": 29, "smallest": [29, 33, 39], "crude": [29, 39], "pick": [29, 47, 65], "accord": [29, 31, 55], "whatev": 29, "prohibit": [29, 31, 42, 50], "nevertheless": [29, 59], "understand": [29, 63, 65, 69], "simple_cycl": 29, "overlaid": 29, "connect": [29, 33, 53], "203147": 29, "974": 29, "n_cycles_to_list": 29, "774": 29, "699": 29, "673": 29, "n_cycles_to_show": 29, "fresh": 29, "crypto3": 29, "reli": [29, 45, 66, 68], "secondli": 29, "adjac": [29, 33], "o_j": 29, "outgo": [29, 30, 31, 53, 65], "i_j": 29, "v_j": 29, "v_": [29, 37, 66], "v_0": 29, "crypto_model": 29, "v0": 29, "chain": [29, 31, 68], "t0": [29, 30, 31], "t1": [29, 30, 31, 47], "total_trad": 29, "edge_capac": 29, "out_nod": [29, 53], "in_nod": [29, 53], "vt": 29, "weath": 29, "2d": [29, 42, 45, 50], "10009": 29, "007": [29, 45], "evolut": [29, 52], "visibl": 29, "scheme": 29, "alon": [29, 42, 50], "00000": [29, 44, 49], "00004": 29, "9998": 29, "02600": 29, "97433": 29, "10003": 29, "02700": 29, "97482": 29, "10008": 29, "03000": 29, "10002": 29, "97472": 29, "10007": 29, "97424": 29, "00700": 29, "transcat": 29, "ntransact": 29, "1e": [29, 31, 42, 50], "6f": [29, 49], "9999": 29, "025800": 29, "025997": 29, "974235": 29, "026000": 29, "026811": 29, "974333": 29, "974723": 29, "027000": 29, "027203": 29, "029812": 29, "974820": 29, "697500": 29, "277320": 29, "030000": 29, "000030": 29, "000012": 29, "030703": 29, "000042": 29, "976057": 29, "remind": [29, 31], "0000002": 29, "precis": [29, 33, 42, 45, 50, 60], "printout": 29, "00746": 29, "28100": 29, "69750": 29, "85971": 29, "20002": 29, "20010": 29, "031012": 29, "05354": 29, "27732": 29, "87000": 29, "62000": 29, "03100": 29, "031000": 29, "20011": 29, "00600": 29, "006000": 29, "16397": 29, "02580": 29, "17000": [29, 64], "xlabel": [29, 30, 35, 38, 40, 46, 48, 53, 55, 57, 64, 66, 68], "ylabel": [29, 30, 35, 38, 40, 46, 48, 55, 57, 64, 66, 68], "gcf": 29, "realiti": [29, 43], "presenc": [29, 39, 47, 50], "affect": [29, 51, 53, 55, 60, 61, 63], "streamlit": 29, "detect": [29, 30, 31, 42, 50], "fetch_order_book": 29, "criteria": [29, 44], "get_order_book": 29, "get_ord": 29, "millisecond": 29, "fetch": 29, "to_datetim": 29, "mininum_in_degre": 29, "888": [29, 37], "065550": 29, "900000e": 29, "065834": 29, "035": 29, "009385": 29, "400000e": 29, "009415": 29, "029000e": 29, "ltc": 29, "002904": 29, "270000e": 29, "002925": 29, "000000e": 29, "328": 29, "000010": 29, "002000e": 29, "120000e": 29, "401": 29, "000208": 29, "705000e": 29, "000210": 29, "710000e": 29, "311": 29, "iost": 29, "006830": 29, "652040e": 29, "007860": 29, "254300e": 29, "312": 29, "855": 29, "961000": 29, "520000e": 29, "079900": 29, "474000e": 29, "313": [29, 32], "floki": 29, "927": 29, "000022": 29, "834030e": 29, "502476e": 29, "314": 29, "xec": 29, "000016": 29, "356363e": 29, "000021": 29, "642790e": 29, "315": [29, 35], "283000": 29, "990000e": 29, "305000": 29, "910000e": 29, "316": [29, 35, 45], "search_tim": 29, "arb_threshold": 29, "utcnow": 29, "strftime": 29, "to_csv": 29, "068": 29, "makarov": 29, "schoar": 29, "2020": [29, 44, 46, 47, 49], "319": 29, "cr\u00e9pelli\u00e8r": 29, "zeisberg": 29, "ssrn": [29, 46, 49], "3606053": 29, "sol3": [29, 46, 49], "cfm": [29, 46, 49], "abstract_id": [29, 46, 49], "academ": [29, 39, 45, 49], "literatur": [29, 39, 44], "peduzzi": 29, "jame": 29, "xu": [29, 44, 60], "septemb": 29, "jack": 29, "THE": 29, "rippler": 29, "decentr": 29, "xrp": 29, "ledger": 29, "3rd": 29, "confer": 29, "blockchain": 29, "innov": [29, 69], "brain": 29, "pp": [29, 45, 46, 47, 49], "ieee": [29, 35], "arxiv": [29, 39, 46, 47, 49], "org": [29, 37, 39, 45, 46, 47, 49], "2106": 29, "16158": 29, "bruzg\u0117": 29, "\u0161apkauskien\u0117": 29, "north": [29, 46, 47, 49], "american": [29, 49], "101562": 29, "1016": 29, "najef": 29, "brief": [29, 68], "107731": 29, "anilpai": 29, "medium": [29, 69], "8938dcea56ea": 29, "crypto": [29, 31], "nbviewer": 29, "rcroessmann": 29, "sharing_publ": 29, "blob": 29, "master": [29, 55, 63], "arbitrage_identif": 29, "ipynb": 29, "byrn": 29, "novel": 29, "decentralis": 29, "www": [29, 31, 37, 39, 44, 45, 46, 47, 49, 64, 68], "scss": 29, "tcd": 29, "ie": 29, "donal": 29, "omahoni": 29, "bfg": 29, "202021": 29, "stephenbyrnedissert": 29, "levu": 29, "berko": 29, "chyrun": 29, "panasyuk": 29, "hrubel": 29, "ceur": 29, "workshop": 29, "proceed": 29, "407": 29, "440": [29, 66], "ws": 29, "vol": [29, 46, 49], "2917": 29, "paper32": 29, "crypocurr": 29, "angeri": 29, "agraw": 29, "evan": 29, "chitra": 29, "boyd": [29, 45, 46, 47, 49], "maker": [29, 57], "asset": [29, 38, 41, 46, 47, 48, 49, 58], "preprint": [29, 46, 47, 49], "2107": 29, "12484": 29, "baincapitalcrypto": 29, "organ": [30, 69], "guest": 30, "mingl": 30, "k_": [30, 46, 49], "sit": 30, "m_f": 30, "far": [30, 36, 63], "ft": 30, "fail": [30, 32, 35, 37], "networkx": [30, 31, 33, 34, 35, 53, 65, 66], "seat_alloc": 30, "kmax": [30, 33], "get_solut": 30, "verbos": [30, 42, 50, 69], "termination_condit": [30, 33, 38, 48, 55, 57, 58, 59, 60, 66], "six": [30, 41, 45], "five": 30, "seatplan": 30, "peculiar": 30, "divers": 30, "bring": [30, 42], "seat_allocation_minimize_group_s": 30, "unfortun": 30, "seat_allocation_minimize_t": 30, "necessarili": 30, "team": [30, 53, 69], "realli": [30, 63], "stand": 30, "arrow": [30, 39], "think": [30, 39, 51, 62, 65], "rephras": 30, "everyon": [30, 32], "seating_allocation_maximize_flow_to_t": 30, "slightli": [30, 35, 40, 45, 48, 51, 53, 55, 65], "door": 30, "target": [30, 42, 50, 62], "nor": [30, 62], "unimpress": 30, "sound": 30, "implicitli": 30, "invok": 30, "model_as_network": 30, "digraphi": 30, "add_edges_from": 30, "flow_valu": 30, "flow_dict": 30, "maximum_flow": 30, "f0": 30, "f1": 30, "f2": 30, "f3": 30, "f4": 30, "f5": 30, "t2": [30, 47], "t3": 30, "t4": 30, "tailor": 30, "magnitud": [30, 42, 55, 63], "405": [30, 62], "\u00b5s": 30, "413": 30, "wall": [30, 44, 46, 47, 49], "414": 30, "max_flow": 30, "reset": 30, "component_data_object": 30, "ctype": 30, "descend_into": 30, "set_valu": 30, "nmax": 30, "mmax": 30, "runtim": 30, "fastest": 30, "transpos": [30, 52], "rotat": [30, 37, 44, 45, 50, 53], "rotation_mod": 30, "anchor": 30, "exchang": 31, "framework": [31, 32, 46, 49], "graphviz": 31, "bank": [31, 49], "japanes": 31, "yen": 31, "jpy": 31, "00761": 31, "eur": 31, "140": [31, 63, 64], "131": 31, "585": 31, "longrightarrow": [31, 68], "9954": 31, "fee": [31, 32], "broker": 31, "needless": 31, "reliabl": [31, 42, 48, 50], "eager": [31, 32], "foreign": 31, "globe": 31, "almost": [31, 42, 46, 47, 57, 63], "autom": 31, "0075": [31, 32], "133": 31, "leftarrow": 31, "0100": [31, 35, 66], "333333": 31, "0000": [31, 32, 39], "tell": 31, "ourselv": 31, "phase": [31, 35, 37], "unencumb": 31, "ne": 31, "credit": 31, "spread": 31, "initial_condit": 31, "max_trad": 31, "nt": 31, "display_graph": 31, "add_nod": [31, 53], "nodelist": 31, "spring_layout": [31, 33], "node_shap": 31, "bloomberg": 31, "tradingview": 31, "extract": [31, 32, 42, 63, 66, 68], "gbp": 31, "chf": 31, "cad": 31, "aud": 31, "hkd": 31, "1096": 31, "0084": 31, "3148": 31, "0677": 31, "7915": 31, "7376": 31, "1279": 31, "9012": 31, "0076": 31, "1849": 31, "9622": 31, "7133": 31, "6647": 31, "1153": 31, "6100": 31, "6097": 31, "9484": 31, "6389": 31, "8816": 31, "4867": 31, "1724": 31, "7606": 31, "8439": 31, "0064": 31, "8121": 31, "6020": 31, "5610": 31, "0973": 31, "9366": 31, "0393": 31, "0079": 31, "2314": 31, "7413": 31, "6908": 31, "1198": 31, "2634": 31, "4019": [31, 52], "0107": 31, "6611": 31, "3489": 31, "9319": 31, "1616": 31, "3557": 31, "5043": 31, "0114": 31, "7825": 31, "4475": 31, "0731": 31, "1734": 31, "8175": 31, "6743": 31, "0659": 31, "2784": 31, "3467": 31, "1877": 31, "7662": 31, "11861": 31, "0527111e": 31, "2486206357100001e": 31, "91269999999999": 31, "9127": 31, "45140205": 31, "1066836e": 31, "41079536e": 31, "4514": 31, "commod": [32, 41, 64], "invit": [32, 45], "pitfal": 32, "uneven": 32, "refin": [32, 37, 39], "didact": [32, 45], "shadow": 32, "yaya": 32, "ga": [32, 35, 39, 65, 66], "grub": 32, "franchisor": 32, "own": [32, 41], "franchise": 32, "truck": [32, 45], "gallon": 32, "charg": [32, 45], "0875": 32, "boost": [32, 50], "alic": 32, "badri": 32, "cara": 32, "dan": 32, "emma": 32, "fujita": 32, "grace": 32, "helen": 32, "subscript": 32, "ship": [32, 69], "d_d": 32, "shipment": [32, 39], "html": [32, 34, 35, 38, 45, 48, 58, 65], "30000": [32, 41], "40000": 32, "50000": 32, "45000": 32, "80000": 32, "br": 32, "to_fram": 32, "cost_to_destin": 32, "shipped_to_destin": 32, "shipped_from_sourc": 32, "supply_constraint": 32, "demand_constraint": [32, 69], "8000": [32, 45], "model1_result": 32, "27387": 32, "26113": 32, "2625": 32, "2490": 32, "3500": [32, 39], "3240": 32, "12000": 32, "38000": 32, "4375": 32, "4321": 32, "1600": 32, "3937": 32, "60000": 32, "7000": 32, "6550": 32, "450": [32, 55, 66], "1575": 32, "1350": 32, "225": [32, 52, 55, 64, 69], "goe": [32, 50], "enthusiasm": 32, "rho": [32, 52, 62], "transport_v2": 32, "delivery_r": 32, "rate_to_destin": 32, "49754": 32, "245": [32, 55], "difficulti": 32, "remedi": 32, "paid": 32, "distributor": [32, 39], "surprisingli": 32, "inspect": [32, 42, 51, 57, 63], "payment": [32, 63], "imposs": [32, 57], "incent": 32, "transport_v3": 32, "allocate_cost": 32, "model3_result": 32, "2502": 32, "122": [32, 39], "3337": 32, "162": 32, "4171": 32, "203": [32, 62], "1668": 32, "3754": 32, "183": [32, 49], "6674": 32, "325": [32, 55], "1501": 32, "inadequ": 32, "marker": [32, 46, 57], "470": 32, "negoti": 32, "rates_index": 32, "083": 32, "081": 32, "09300000000000001": 32, "10099999999999999": 32, "133000": 32, "x_index": 32, "nobject": 32, "nconstraint": 32, "ndecis": 32, "sensit": [32, 42, 50, 51, 69], "0045": 32, "0855": 32, "0795": 32, "node_attr": 32, "edge_attr": 32, "nsuppli": 32, "nship": 32, "nsen": 32, "fillcolor": 32, "ndemand": 32, "lectur": [33, 45], "hall": 33, "exam": 33, "indirect": 33, "hire": 33, "temporari": 33, "staff": 33, "invigil": 33, "obei": 33, "undirect": 33, "th": [33, 38, 44, 57, 58, 65], "ik": [33, 63], "w_k": 33, "jk": [33, 63], "chromat": 33, "graph_color": 33, "besid": [33, 65, 66], "too": [33, 37, 58, 63, 66], "catch_infeas": 33, "diagnos": 33, "rais": [33, 35, 45, 64], "edge_constraint": 33, "node_constraint": 33, "used_color_constraint": 33, "number_used_color": 33, "catch": [33, 66], "load_solut": 33, "get_color": [33, 41, 46, 60], "erdo": 33, "renyi": 33, "gnp_random_graph": 33, "is_connect": 33, "start_tim": 33, "terminationcondit": 33, "greedi": 33, "nxcolor": 33, "greedy_color": 33, "logist": [34, 39], "retail": [34, 60], "contin": 34, "outlet": 34, "correspondingli": 34, "character": [34, 37], "b_j": 34, "transship": 34, "rail": 34, "airwai": 34, "sent": [34, 51], "cheapest": 34, "mcf": 34, "draw_networkx_label": [34, 53], "draw_label": 34, "draw_edge_label": 34, "draw_networkx_edg": [34, 35, 53], "draw_edg": 34, "markdown": [34, 35, 38, 48, 58, 65], "draw_network": 34, "edge_flow": [34, 35], "kamada_kawai_layout": [34, 35], "font_color": [34, 53], "edgelist": 34, "arrowstyl": 34, "shifted_po": 34, "font_weight": 34, "mincostflow": 34, "incoming_flow": [34, 35, 65, 66], "outgoing_flow": [34, 35, 65, 66], "flow_conserv": [34, 35, 65, 66], "flow_upper_bound": 34, "noptim": 34, "countri": 35, "renew": [35, 44, 65, 66], "nation": [35, 65], "transmiss": [35, 47], "citi": [35, 44, 57], "district": [35, 57], "inject": 35, "p_i": [35, 47, 57, 65, 66], "f_": [35, 59, 65, 66], "easier": [35, 57, 63], "ji": [35, 65, 66], "control": [35, 41, 57, 66], "school": [35, 39, 69], "law": 35, "theta_": 35, "angl": [35, 66], "mathbf": [35, 47], "theta": [35, 40, 63, 65, 66], "theta_i": [35, 65, 66], "theta_j": [35, 65, 66], "constrat": 35, "dc": 35, "admit": 35, "cheaper": [35, 65], "moreov": [35, 42, 48, 50], "llll": [35, 57, 65, 66], "179": [35, 45, 49, 62, 66], "rnd": [35, 65], "ast": [35, 65, 66], "literal_ev": [35, 65, 66], "make_tupl": [35, 65, 66], "plugin": 35, "cbcplugin": 35, "cbcshell": 35, "0x7f7a85e3d880": 35, "asl": 35, "set_execut": 35, "traceback": 35, "py": [35, 68], "166": 35, "__call__": [35, 42, 50, 68], "_cl": 35, "_implicit_solv": 35, "kwd": 35, "systemcallsolv": 35, "shellcmd": 35, "valueerror": 35, "base_url": [35, 57, 65, 66], "nodes_df": [35, 57, 65, 66], "edges_df": [35, 65, 66], "node_id": [35, 57, 65, 66], "to_dict": [35, 42, 50, 57, 65, 66], "edge_id": [35, 65, 66], "example_nod": 35, "example_edg": 35, "visualize_network": 35, "buse": 35, "solar": [35, 65, 66], "ffcb36": 35, "wind": [35, 51, 57, 61, 65], "hydro": [35, 65, 66], "a5efff": 35, "coal": [35, 65, 66], "686868": 35, "00ab4": 35, "b6b6b6": 35, "vertex2color": 35, "energy_typ": [35, 65, 66], "v2c_list": 35, "draw_networkx_nod": [35, 53], "595959": 35, "set_edgecolor": 35, "set_axis_off": 35, "cyan": 35, "dark": 35, "solarfarm": 35, "windmil": 35, "p_min": [35, 57, 65, 66], "p_max": [35, 57, 65, 66], "c_var": [35, 57, 65, 66], "is_gener": [35, 65, 66], "boolean": [35, 63], "397": 35, "948321": 35, "873": 35, "220980": 35, "993982": 35, "720": 35, "202306": 35, "484861": 35, "180": [35, 44, 45, 62, 64, 69], "602933": 35, "916": 35, "330000": 35, "1146": 35, "1175": 35, "194": [35, 45], "142": [35, 38], "186145": 35, "921628": 35, "884795": 35, "961682": 35, "113": [35, 49, 60, 62, 66], "396000": 35, "864042": 35, "311328": 35, "116": [35, 45, 66], "703998": 35, "242759": 35, "f_max": [35, 65, 66], "271": 35, "5849": [35, 66], "3133": [35, 66], "2593": [35, 66], "5185": [35, 66], "174": [35, 49, 62, 66], "9059": [35, 66], "177": [35, 49, 62, 66], "8216": [35, 66], "246": [35, 45, 66], "9136": [35, 66], "12992": 35, "easiest": [35, 38, 48, 58], "lab": 35, "attr1": 35, "attr2": 35, "bit": 35, "confus": [35, 42, 50], "921627803299574": 35, "realist": [35, 66], "pattern": [35, 63], "96th": 35, "averag": [35, 39, 45, 52, 64, 65, 66], "opf1": 35, "power_gener": 35, "power_flow": 35, "q1": [35, 47], "fab": 35, "fm": 35, "abs_flow": 35, "flows_upper_bound": [35, 65], "generation_upper_bound": [35, 65, 66], "generation_lower_bound": [35, 65, 66], "102898": 35, "emit": 35, "co2": 35, "carbon": 35, "neutral": 35, "dutch": 35, "govern": 35, "inact": 35, "opf2": 35, "q2": [35, 47], "generation_upperound": 35, "max_gas_pl": 35, "max_coal_pl": 35, "53120": 35, "threat": 35, "lift": [35, 68], "m_0": 35, "ym_2": 35, "opf3": 35, "q3": 35, "max_total_renewable_product": 35, "renewable_energy_product": 35, "41608": 35, "view": [35, 58, 62, 65], "wherea": [35, 57, 63, 66], "f_1": [35, 53], "f_2": [35, 53], "f_3": 35, "expens": [35, 39, 42, 44, 50, 63, 64, 65, 66], "mitig": [35, 63], "solvabl": [36, 68], "milk": 36, "pool": 36, "ordinari": 36, "ol": 36, "classif": [36, 50], "refineri": [36, 39], "conic": [36, 44, 46, 48, 49, 55, 58], "anyon": 37, "broadli": 37, "ida": [37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 68], "pse": [37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 68], "solver_milo": 37, "solver_minlo": [37, 55], "couenn": 37, "d_f": 37, "f_f": 37, "gilmor": 37, "gamori": 37, "1961": 37, "rapidli": 37, "s_p": 37, "pf": 37, "make_pattern": 37, "partial": [37, 42], "num_cut": 37, "cuts_dict": 37, "plot_pattern": 37, "cmap": 37, "tab10": 37, "background": 37, "y_lo": 37, "y_hi": 37, "overlai": 37, "xa": 37, "xb": 37, "clean": [37, 69], "bottom": 37, "cut_pattern": 37, "plot_nonzero_pattern": 37, "wrapper": 37, "unus": [37, 41, 63], "_2": [37, 40, 42, 44, 45, 48, 50, 55, 58, 63], "n_p": 37, "x_p": 37, "symmetri": 37, "substitut": [37, 45, 63, 69], "cone": [37, 46, 47, 48, 49, 50], "minlo": [37, 39], "bilinear_cut_stock": 37, "f_total_demand": 37, "a_bound": 37, "assign_each_stock_to_pattern": 37, "feasible_pattern": 37, "max_pattern": 37, "shouldn": 37, "_f": [37, 53], "generate_pattern_bilinear": 37, "xp": [37, 60], "ap": 37, "sum_to_on": 37, "add_pattern": 37, "new_pattern": 37, "pi_f": 37, "sf": [37, 69], "generate_pattern_du": 37, "subprob": 37, "marginal_valu": 37, "stock_length": 37, "reduced_valu": 37, "somewhat": [37, 68], "generate_patterns_bilinear": 37, "generate_patterns_du": 37, "std": [37, 42, 62], "137": [37, 42, 49, 62], "exhaust": [37, 39], "empir": [37, 55, 62, 65], "cut_stock": 37, "non_zero_indic": 37, "jl": 37, "stabl": [37, 45, 50], "cutting_stock_column_gener": 37, "en": [37, 46, 47], "wiki": [37, 46, 47], "cutting_stock_problem": 37, "roll": 37, "5600": [37, 59], "1520": 37, "1560": 37, "1710": 37, "1820": 37, "1880": 37, "2050": 37, "2100": 37, "2140": [37, 63], "2150": 37, "2200": 37, "2x4": 37, "lumber": 37, "arm": 37, "outdoor": 37, "sofa": 37, "ana": 37, "imag": [37, 42, 50], "spreadsheet": 37, "1zx7kj2kwtggyqev_a3log0nqsxsc38ykk53a7vgwafu": 37, "gid": 37, "1104632299": 37, "read_google_sheet": 37, "sheet_id": 37, "sheet_nam": 37, "lowercas": [37, 69], "str": [37, 42, 50, 52, 55], "gviz": 37, "tq": 37, "tqx": 37, "settings_df": 37, "nset": 37, "finish_df": 37, "nfinish": 37, "stocks_df": 37, "nstock": 37, "kerf": 37, "120": [37, 44, 63, 64], "144": 37, "168": 37, "192": [37, 64], "216": 37, "240": [37, 45, 64], "2x6": 37, "pivot_t": [37, 39], "aggfunc": 37, "sort_index": 37, "gomori": 37, "trim": [37, 68], "849": 37, "859": 37, "jstor": [37, 45], "1963": 37, "863": [37, 62], "haessler": 37, "sweenei": 37, "european": [37, 64, 66], "delorm": 37, "iori": 37, "martello": 37, "2016": [37, 41, 44, 46, 47, 49], "exact": [37, 45, 51, 66], "255": [37, 45, 58], "sciencedirect": [37, 44, 45], "implemen": 37, "mathwork": 37, "matlab": 37, "aimm": 37, "scip": 37, "pulp": 37, "harjunkoski": 37, "westerlund": 37, "p\u00f6rn": 37, "skrifvar": 37, "minlp": [37, 39], "594": 37, "603": 37, "abo": 37, "fi": 37, "engin": [37, 39, 44, 64], "s471": 37, "s474": 37, "ipopt": [38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 68], "mosek_direct": [38, 44, 45, 46, 47, 48, 49, 50, 57, 58], "stochast": [38, 51, 52, 54, 57, 60, 63, 66], "she": 38, "riski": [38, 49, 58], "tild": [38, 40, 48, 58], "mu": [38, 48, 58, 62], "sigma": [38, 48, 58, 62], "mathrm": [38, 47], "compromis": [38, 46], "willing": [38, 57], "undertak": 38, "exclud": [38, 69], "semidefinit": [38, 48], "semi": [38, 40, 42, 48, 50, 58], "linalg": [38, 42, 48, 50], "eigval": [38, 42, 48, 50], "rand": [38, 48, 53, 58], "xtild": [38, 48, 58], "bounded_vari": [38, 48], "total_asset": [38, 48, 58], "x_3": [38, 48, 58], "ok": [38, 48, 55, 58, 60], "158": 38, "561": 38, "gamma_valu": 38, "stream": 39, "mixtur": 39, "petroleum": 39, "sector": [39, 46], "tankag": 39, "train": [39, 43, 49], "pipelin": 39, "agricultur": 39, "mine": 39, "wastewat": 39, "composit": [39, 44], "solver_lo": [39, 40, 42], "solver_gnlo": 39, "bulk": 39, "fat": 39, "farm": [39, 51, 64], "afford": 39, "distant": 39, "grade": 39, "tank": 39, "station": 39, "noth": [39, 47], "min_fat": 39, "045": 39, "6000": [39, 41, 45, 64], "030": [39, 44], "2500": [39, 41, 52, 60], "040": 39, "033": 39, "050": [39, 55], "local_suppli": 39, "remote_suppli": 39, "ncustom": 39, "nsupplier": 39, "_c": 39, "_l": 39, "flowrat": 39, "fat_cont": 39, "81000": 39, "2666": 39, "1333": 39, "justifi": [39, 47], "122441": 39, "1764": 39, "4235": 39, "2352": 39, "1647": 39, "extent": [39, 65], "giveawai": 39, "surpass": 39, "parameter": 39, "y_c": 39, "_r": [39, 50], "enter": 39, "implic": 39, "profound": 39, "customer_demand": 39, "pool_bal": 39, "pool_qual": 39, "customer_qu": 39, "p_plot": 39, "025": [39, 45, 55], "055": 39, "f_plot": 39, "contrast": [39, 41], "minima": 39, "thee": 39, "w_c": [39, 46], "incomplet": 39, "isn": 39, "concentr": [39, 51, 68], "conc": 39, "underlin": 39, "mccormick": 39, "envelop": 39, "milk_pooling_convex": 39, "hh": 39, "lh": 39, "hl": 39, "report_solut": 39, "npool": 39, "m_convex": 39, "111411": 39, "112500": 39, "1029": 39, "4118": 39, "43235": 39, "2956": 39, "4852": 39, "9412": 39, "179558": 39, "8244": 39, "4117": [39, 45], "6471": 39, "185294": 39, "1195": 39, "0421": 39, "312000": 39, "1470": 39, "5882": 39, "0359": 39, "0400": 39, "412": 39, "search": [39, 55, 63], "xy": [39, 45], "xytext": [39, 45], "036": 39, "106000": 39, "arrowprop": [39, 45], "shrink": [39, 45], "headwidth": [39, 45], "miss": [39, 52], "scan": [39, 53], "m_est": 39, "105000": 39, "088": 39, "fall": 39, "441": 39, "100088": 39, "270000": 39, "3823": 39, "5294": 39, "141470": 39, "5878": 39, "2676": 39, "4706": 39, "120441": 39, "1770": 39, "discrep": 39, "compil": 39, "ampl": 39, "milk_pooling_bilinear": 39, "m_global": 39, "bo": 39, "95000": 39, "102833": 39, "2333": 39, "3333": [39, 46], "8333": 39, "375000": 39, "4166": 39, "6667": 39, "154166": 39, "1666": 39, "augment": [39, 46, 50], "awai": [39, 68], "bonmin": [39, 55], "prototyp": 39, "feed": [39, 64, 68], "un": 39, "haverli": 39, "1978": 39, "fuel": [39, 41], "recurs": [39, 68], "acm": 39, "sigmap": 39, "bulletin": 39, "dl": 39, "1145": 39, "1111237": 39, "1111238": 39, "encyclopedia": 39, "patholog": [39, 47], "visweswaran": 39, "springer": [39, 45, 62, 64], "referenceworkentri": 39, "978": 39, "387": [39, 55], "74759": 39, "0_375": 39, "misen": 39, "flouda": 39, "researchg": 39, "profil": [39, 49], "ruth": 39, "public": 39, "242290955_advances_for_the_pooling_problem_modeling_global_optimization_and_computational_studies_survei": 39, "0046352e7d1dfeb40f000000": 39, "gupt": 39, "ahm": 39, "dei": 39, "cheon": 39, "georgia": 39, "institut": 39, "atlanta": 39, "exxonmobil": [39, 49], "annandal": 39, "nj": 39, "db_file": 39, "2012": [39, 44], "3658": 39, "ceccon": 39, "galini": 39, "107660": 39, "2105": 39, "01687": 39, "probabl": [39, 46, 47, 49, 57, 59, 60, 62, 63], "underappreci": 39, "programm": 39, "wfp": 39, "clp": 40, "solver_qo": 40, "tri": 40, "ols_regress": 40, "sum_of_square_error": 40, "49847313217242": 40, "42809468044768995": 40, "cccc": 40, "unconstrain": 40, "hessian": 40, "nabla": 40, "42857640061373": 40, "4130268125089274": 40, "y_fit2": 40, "explan": [41, 50], "unusu": 41, "seborg": 41, "edgar": 41, "mellichamp": 41, "doyl": 41, "dale": 41, "thoma": 41, "duncan": 41, "franci": 41, "dynam": [41, 69], "wilei": 41, "son": 41, "24000": 41, "28000": 41, "volumetr": 41, "feed_cost": 41, "process_cost": 41, "860275": 41, "8317999997": 41, "explicit": [41, 53, 66, 69], "implicit": 41, "sharp": 41, "cxvpy": 41, "to_numpi": [41, 42, 50], "8620663473": 41, "results_crud": 41, "dual_valu": 41, "26206": 41, "6896": 41, "results_product": 41, "5103": 41, "896": 41, "xlim": [41, 42, 50], "32000": 41, "xplot": 41, "regim": 41, "doubl": 41, "kerosen": 41, "hydrocarbon": 41, "hyperplan": [42, 46, 49, 50], "banknot": [42, 50], "solver_nlo": [42, 55], "medic": 42, "diseas": 42, "enjoi": 42, "movi": 42, "photo": 42, "car": [42, 45], "genuin": [42, 50], "counterfeit": [42, 50], "vend": 42, "accur": [42, 63, 66], "reject": 42, "ones": [42, 50, 60, 63], "tp": 42, "fn": 42, "tn": 42, "frustrat": 42, "incorrectli": [42, 45], "low": [42, 44, 45, 47, 48, 60, 63, 69], "innoc": 42, "proven": 42, "guilti": 42, "unless": 42, "perspect": [42, 65], "specimen": [42, 50], "wavelet": [42, 50], "skew": [42, 50], "curtosi": [42, 50], "entropi": [42, 50], "authent": [42, 50], "model_select": [42, 50], "train_test_split": [42, 50], "data_banknote_authent": [42, 50], "txt": [42, 50], "header": [42, 50], "62160": 42, "6661": 42, "8073": 42, "44699": 42, "54590": 42, "1674": 42, "4586": 42, "46210": 42, "86600": [42, 64], "6383": 42, "9242": 42, "10645": 42, "45660": 42, "5228": 42, "0112": 42, "59440": 42, "32924": 42, "4552": 42, "5718": 42, "98880": 42, "1372": 42, "433735": 42, "922353": 42, "397627": 42, "191657": 42, "444606": 42, "842763": 42, "869047": 42, "310030": 42, "101013": [42, 49], "497103": 42, "042100": 42, "773100": 42, "286100": 42, "548200": 42, "773000": 42, "708200": 42, "574975": 42, "413450": 42, "319650": 42, "616630": 42, "586650": 42, "821475": 42, "814625": 42, "179250": 42, "394810": 42, "824800": 42, "951600": 42, "927400": 42, "449500": 42, "exposit": [42, 50], "df_train": [42, 50], "df_test": [42, 50], "test_siz": [42, 50], "x_train": [42, 50], "y_train": [42, 50], "x_test": [42, 50], "y_test": [42, 50], "scatter_labeled_data": [42, 50], "prepend": [42, 50], "catch_warn": [42, 50], "filterwarn": [42, 50], "pred": [42, 50], "sgn": [42, 50], "scalar": 42, "linearsvm": [42, 50], "bia": [42, 50], "__repr__": [42, 50], "surfac": [42, 44], "accuraci": [42, 45, 50], "score": [42, 50], "estima": 42, "y_pred": [42, 50], "scatter_comparison": [42, 50], "xmin": [42, 50], "ymin": [42, 50], "xmax": [42, 50], "ymax": [42, 50], "topic": [42, 50, 68], "recommend": [42, 50, 69], "matthew": [42, 50], "mcc": [42, 50], "y_true": [42, 50], "bool": [42, 50], "true_posit": [42, 50], "false_neg": [42, 50], "false_posit": [42, 50], "true_neg": [42, 50], "mcc_numer": [42, 50], "mcc_denomin": [42, 50], "confusion_matrix": [42, 50], "134": [42, 46, 47, 49, 62, 65], "pm": [42, 50, 55, 63, 66], "ambigu": 42, "perfectli": [42, 49, 57, 66], "z_i": [42, 45, 50], "misclassifi": [42, 50], "hing": 42, "poorli": 42, "penal": [42, 46], "_1": [42, 50, 55, 63], "lasso": 42, "spars": 42, "neglect": [42, 49], "2n": 42, "recast": [42, 49], "factori": [42, 45, 50], "svm_factory_lp": 42, "lambd": [42, 46, 47, 49], "wp": [42, 46, 47], "wn": 42, "hingeloss": 42, "svm_lp": 42, "24607501": 42, "053474389": 42, "0058897667": 42, "716": 42, "143": [42, 49], "slack": [42, 50], "settl": [42, 50, 68], "soft": [42, 50], "misclassif": [42, 50], "accompani": [42, 50, 69], "svm_factory_qp": 42, "qp": 42, "svm_qp": 42, "3705558690404267": 42, "12373970025774439": 42, "1493160233858407": 42, "702": 42, "lagrangian": 42, "alpha_i": [42, 50, 65], "beta_i": 42, "saddl": 42, "alpha_j": [42, 50], "y_j": [42, 50, 55], "symmetr": [42, 50, 55, 62], "y_n": [42, 44, 50], "x_n": [42, 44, 50], "vdot": [42, 50], "ddot": [42, 50], "dens": [42, 50], "sim": [42, 44, 45, 50, 62, 66], "rank": [42, 48, 50], "defici": [42, 50], "elimin": [42, 45, 50, 53, 63, 69], "ff": [42, 50], "complementar": 42, "svm_factory_du": 42, "mul": 42, "interior": [42, 44, 45], "closest": 42, "argmin": 42, "svm_dual": 42, "3705560469152364": 42, "12373974216158136": 42, "1493161249124506": 42, "phi": [42, 50, 58, 62], "machineri": 42, "mercer": [42, 50], "theorem": [42, 50], "spectral": [42, 50], "diagon": [42, 50], "eigenvalu": [42, 50], "i_q": [42, 50], "kernal": [42, 50], "sv": [42, 50], "kernelsvm": [42, 50], "svm_factory_kernel": 42, "tol": [42, 50], "callabl": [42, 68], "eigvec": 42, "eigh": [42, 50], "diag": [42, 50, 62], "y_support": [42, 50], "svm_kernel": 42, "__main__": 42, "0x2a9271d80": 42, "0x2a92f6170": 42, "757": 42, "cubic": [42, 44], "0x2a94613f0": 42, "807": 42, "kelli": [43, 46, 49], "layer": [43, 63], "insul": 43, "luenberg": 43, "wheel": 43, "growth": [43, 46], "thermal": 44, "annual": [44, 45, 49], "heat": 44, "air": [44, 62], "pmo": [44, 45, 46, 47, 49, 50], "temperatur": 44, "t_o": 44, "conduct": 44, "ua": 44, "transfer": [44, 68], "invers": [44, 58, 60, 62], "serial": 44, "resist": 44, "r_0": 44, "r_n": [44, 46, 47], "k_n": 44, "thick": 44, "proport": [44, 57], "affin": 44, "a_n": 44, "b_n": [44, 46], "ty_n": 44, "bx": 44, "sq": 44, "meter": 44, "r0": [44, 47], "watt": 44, "xopt": 44, "4f": [44, 46, 47, 60], "9962": 44, "2864": 44, "z_n": 44, "r_1": [44, 45, 46, 47], "r_2": [44, 45, 47], "z_0": 44, "z_1": [44, 45, 55], "rotated_quadrat": [44, 50], "as_domain": [44, 46, 47, 49, 50], "99615": 44, "28640": 44, "resort": [44, 65], "overcom": 44, "ru": 44, "2ru": 44, "middl": 44, "isol": 44, "a_ny_n": 44, "b_nx_n": 44, "variable_dict": [44, 45, 46, 49], "constraint_dict": 44, "miner": 44, "wool": 44, "rigid": 44, "foam": 44, "015": [44, 45], "1549": 44, "19361": 44, "010": [44, 45], "2299": 44, "06276": 44, "08724": 44, "x_0": 44, "curv": [44, 66], "x0": 44, "meshgrid": 44, "contour": [44, 45], "my": [44, 68], "hasan": 44, "cycl": 44, "124": [44, 45, 49], "pii": [44, 45], "s0306261999000239": 44, "kaynakli": 44, "review": [44, 69], "sustain": 44, "425": [44, 55, 64], "s1364032111004163": 44, "nyer": 44, "kajtar": 44, "tomi\u0107": 44, "2015": 44, "268": 44, "s0378778814008688": 44, "gori": 44, "guattari": 44, "evangelisti": 44, "asdrubali": 44, "mass": [44, 49], "359": 44, "s0017931016303647": 44, "huang": 44, "zhou": 44, "wu": 44, "chines": 44, "zone": 44, "humid": 44, "subtrop": 44, "climat": 44, "101840": 44, "s221067071931457x": 44, "s\u00f6ylemez": 44, "\u00fcnsal": 44, "refriger": 44, "s0196890498001253": 44, "a\u00e7\u0131kkalp": 44, "kandemir": 44, "2019": [44, 49], "environment": 44, "s2451904918305377": 44, "ylm\u00e9n": 44, "mj\u00f6rnell": 44, "berlin": 44, "arfvidsson": 44, "optimis": [44, 45], "107544": 44, "s0360132320309112": 44, "mba": 45, "1915": 45, "deplet": 45, "hx": 45, "modulo": 45, "analyt": [45, 47, 66], "fopt": 45, "3651": 45, "2738": 45, "tangent": 45, "yopt": 45, "0006": 45, "3200": 45, "0008": 45, "elementari": 45, "geometri": 45, "hyperbola": 45, "intersect": 45, "lorenz": 45, "lobo": 45, "iff": [45, 47, 50], "2w": 45, "tilt": 45, "displac": [45, 62], "stretch": 45, "geometr": [45, 47], "4xy": 45, "mpl_toolkit": 45, "mplot3d": 45, "art3d": 45, "t_max": 45, "co": 45, "sin": 45, "plot3d": 45, "arcco": 45, "text3d": 45, "view_init": 45, "elev": 45, "azim": 45, "pathpatch_2d_to_3d": 45, "zdir": 45, "set_zlim": 45, "simpler": 45, "cd": 45, "experiment": 45, "u_eq": 45, "neoq": 45, "3654": 45, "stumbl": 45, "sledgehamm": 45, "swat": 45, "fly": 45, "compet": 45, "he": [45, 46], "perish": 45, "b_0": 45, "lb_i": 45, "ub_i": 45, "h_i": 45, "deliveri": [45, 63], "hypothet": [45, 59], "tire": 45, "weather": [45, 59, 64], "heavi": 45, "duti": 45, "block_dict": [45, 46, 49], "b_cap": 45, "eoq_display_result": 45, "req": 45, "306": 45, "918": 45, "153": 45, "1225": 45, "151": 45, "754": 45, "367": 45, "1101": 45, "df_larg": 45, "03d": 45, "688059": 45, "329": 45, "1220": 45, "110966": 45, "452672": 45, "2671": 45, "984745": 45, "4851": 45, "180476": 45, "364": 45, "3286": 45, "560933": 45, "1955": 45, "727272": 45, "458": 45, "2010": [45, 46, 47, 49], "006": 45, "911743": 45, "408": 45, "410": 45, "621799": 45, "478": [45, 48], "008": 45, "317468": 45, "335": [45, 49], "1056": 45, "009": 45, "460362": 45, "339": [45, 59], "2996": 45, "960022": 45, "801": 45, "011": 45, "926136": 45, "381": 45, "2800": 45, "688914": 45, "422": [45, 66], "3076": 45, "013": 45, "545538": 45, "014": 45, "668708": 45, "2260": 45, "755557": 45, "322": 45, "4872": 45, "587431": 45, "640": 45, "017": [45, 62], "801025": 45, "445": [45, 66], "1693": 45, "018": 45, "636593": 45, "473": 45, "4066": 45, "019": 45, "717248": 45, "476": [45, 52], "2194": 45, "020": 45, "053587": 45, "324": 45, "1518": 45, "021": 45, "318844": 45, "2681": 45, "022": 45, "625933": 45, "746": 45, "023": 45, "995664": 45, "3192": 45, "338183": 45, "468": 45, "2830": 45, "679697": 45, "354": 45, "2449": 45, "026": 45, "780842": 45, "358": 45, "926": 45, "236800": 45, "411": 45, "4618": 45, "028": 45, "252901": 45, "455": 45, "3022": [45, 49], "029": 45, "039994": 45, "423": [45, 46], "4253": 45, "132": [45, 49], "2274": 45, "3327": 45, "4801": 45, "3905": 45, "169": 45, "2901": 45, "3443": 45, "1449": 45, "1982": 45, "2121": 45, "209": [45, 62], "3588": 45, "1922": 45, "213": [45, 65], "3659": 45, "236": [45, 62], "4046": 45, "3068": 45, "4445": 45, "3079": 45, "291": 45, "4982": 45, "214": 45, "3668": 45, "146": 45, "2508": 45, "224": 45, "3842": 45, "3915": 45, "4102": 45, "193": 45, "3307": 45, "119": 45, "287": [45, 62], "4917": 45, "4184": 45, "4797": 45, "curiou": 45, "twist": 45, "1931": 45, "citat": 45, "shaw": 45, "chap": 45, "iv": 45, "chicago": 45, "ziegler": 45, "singli": 45, "252": [45, 49], "016763778290030x": 45, "bretthauer": 45, "shetti": 45, "1995": 45, "670": 45, "171693": 45, "kuo": 45, "mittleman": 45, "2004": 45, "mittelmann": 45, "285": 45, "1023": 45, "coap": 45, "0000033964": 45, "95511": 45, "vandenbergh": 45, "lebret": 45, "284": [45, 66], "stanford": [45, 46, 49], "socp": [45, 58], "letchford": 45, "park": [45, 66], "guid": [45, 67], "rairo": 45, "1106": 45, "cs": 45, "nott": 45, "uk": 45, "pszajp": 45, "pub": 45, "el": 45, "ghaoui": 45, "laurent": 45, "inst": 45, "eec": 45, "berkelei": [45, 46, 49], "ee127": 45, "fa19": 45, "12_socp": 45, "cookbook": [45, 48], "section": [45, 62, 68], "cqo": 45, "bypass": 45, "6cm": 45, "4pt": 45, "u_i": [45, 47], "v_i": [45, 66], "solver_con": 46, "wager": [46, 47], "spin": 46, "game": 46, "indefinit": 46, "interact": [46, 68, 69], "w_a": 46, "w_b": 46, "stake": 46, "bisect": 46, "ipywidget": 46, "widget": 46, "wheel_sim": 46, "odd": [46, 47], "quantil": [46, 52, 58, 60, 62], "semilog": [46, 47], "bisect_left": 46, "wealth_next": 46, "elogr": [46, 47, 49], "interact_manu": 46, "floatslid": 46, "wb": 46, "wc": [46, 64], "wheel_interact1": 46, "p_n": 46, "q_n": 46, "wheel_model": 46, "expression_dict": [46, 49], "sum_w": 46, "primal_exponenti": [46, 47, 49], "06758": 46, "218": 46, "167": 46, "128": [46, 49, 62, 69], "suffer": 46, "drawdown": 46, "busseti": [46, 47, 49], "ryu": [46, 47, 49], "gambl": [46, 47, 49], "infti": [46, 55, 60], "admiss": 46, "p_1": [46, 47], "u_n": 46, "wheel_rc_model": 46, "sum_u": 46, "06025": 46, "36329": 46, "26547": 46, "1667": 46, "12575": 46, "wheel_interact2": 46, "semilogx": [46, 49], "determinist": [46, 63, 65, 66], "popular": [46, 47], "poundston": [46, 47], "fortun": [46, 47], "untold": [46, 47], "scientif": [46, 47, 49], "bet": [46, 47, 49], "beat": [46, 47, 49], "casino": [46, 47], "street": [46, 47, 49], "hill": [46, 47], "wang": [46, 47], "onlinecasinoground": [46, 47], "nl": [46, 47], "upload": [46, 47], "boek": [46, 47], "van": [46, 47, 69], "thorp": [46, 47, 49], "man": [46, 47, 49], "la": [46, 47, 49, 69], "vega": [46, 47, 49], "dealer": [46, 47, 49], "2008": [46, 47, 49], "blackjack": [46, 47, 49], "sport": [46, 47, 49], "handbook": [46, 47, 49], "liabil": [46, 47, 49], "385": [46, 47, 49], "428": [46, 47, 49], "holland": [46, 47, 49], "palmislandtrad": [46, 47, 49], "econ136": [46, 47, 49], "thorpe_kelly_crit": [46, 47, 49], "maclean": [46, 49], "ziemba": [46, 49], "aldou": [46, 49], "good_bad_kelli": [46, 49], "2011": [46, 49, 62, 64], "worldscientif": [46, 49], "worldscibook": [46, 49], "7598": [46, 49], "aboutbook": [46, 49], "wikipedia": [46, 47, 68], "kelly_criterion": [46, 47], "oup": 46, "catalogu": 46, "ush": 46, "9780199740086": 46, "caja": [46, 49], "3833617": [46, 49], "1603": [46, 47, 49], "06183": [46, 47, 49], "fu": [46, 47, 49], "narasimhan": [46, 47, 49], "cvxr": [46, 47, 49], "1711": [46, 47, 49], "07582": [46, 47, 49], "1812": [46, 49], "10371": [46, 49], "robust_kelli": [46, 49], "ch": [46, 49], "hsieh": [46, 49], "2202": [46, 49, 52], "03858": [46, 49], "1956": 47, "bell": 47, "laboratori": 47, "analog": 47, "claud": 47, "shannon": 47, "encod": [47, 62, 69], "noisi": 47, "channel": 47, "gambler": 47, "predat": 47, "1738": 47, "daniel": 47, "bernoulli": 47, "resolut": 47, "st": 47, "petersburg": 47, "cousin": 47, "nichola": 47, "adventur": 47, "earli": [47, 69], "laid": 47, "obscur": 47, "cowork": [47, 49], "avers": 47, "ident": [47, 49, 53, 63, 68], "polici": 47, "q_1": 47, "q_2": 47, "w_conic": 47, "w_analyt": 47, "1180": 47, "p_2": 47, "q_i": 47, "u_1": [47, 50], "u_2": [47, 50], "kelly_rc": 47, "u1": 47, "u2": 47, "r1": [47, 69], "r2": [47, 69], "w_rc": 47, "constrainend": 47, "0589": 47, "kelly_sim": 47, "mont": 47, "carlo": 47, "binomi": 47, "cumprod": [47, 49], "logr": 47, "transax": 47, "1e6": 47, "choleski": 48, "lorentz": 48, "2_2": [48, 55], "practiv": 48, "qcqo": 48, "markowitz_revisit": 48, "283": 48, "130": 48, "alpha_valu": 48, "critiqu": 49, "economist": 49, "20th": 49, "paul": 49, "samuelson": 49, "ground": 49, "lack": [49, 59], "controversi": 49, "didn": 49, "fund": 49, "histor": [49, 57, 59], "yfinanc": 49, "holidai": 49, "elabor": 49, "gspc": 49, "ixic": 49, "nasdaq": 49, "dji": 49, "jone": 49, "rut": 49, "russel": 49, "amgen": 49, "appl": 49, "boe": 49, "caterpillar": 49, "chevron": 49, "jpmorgan": 49, "chase": 49, "mcdonald": 49, "microsoft": 49, "proctor": 49, "n_test": 49, "n_train": 49, "dropna": 49, "prop": 49, "r_f": 49, "futur": [49, 51, 59, 62], "borrow": 49, "e_m": 49, "q_t": 49, "equiprob": [49, 57, 62], "kelly_portfolio": 49, "u_sum": 49, "w_sum": 49, "kelly_report": 49, "247": 49, "190366": 49, "564623": 49, "480615": 49, "500638": 49, "152": 49, "966799": 49, "056351": 49, "132849": 49, "303171": 49, "247408": 49, "071398": 49, "924581": 49, "324833": 49, "955780": 49, "664067": 49, "665347": 49, "512189": 49, "226212": 49, "793304": 49, "976357": 49, "340": [49, 64, 69], "524902": 49, "859108": 49, "259621": 49, "789543": 49, "749512": 49, "810425": 49, "666946": 49, "046753": 49, "898674": 49, "26805": 49, "529297": 49, "3010": 49, "290039": 49, "8185": 49, "799805": 49, "1548": 49, "489990": 49, "955654": 49, "784424": 49, "724091": 49, "860046": 49, "127": [49, 65], "212341": 49, "170517": 49, "675674": 49, "463715": 49, "385712": 49, "427185": 49, "651657": 49, "028133": 49, "26958": 49, "060547": 49, "550049": 49, "8243": 49, "120117": 49, "1558": 49, "709961": 49, "556232": 49, "519867": 49, "026421": 49, "336": [49, 65], "897766": 49, "512772": 49, "011734": 49, "883026": 49, "913925": 49, "756805": 49, "860023": 49, "534607": 49, "27090": 49, "720703": 49, "3039": 49, "419922": 49, "8325": 49, "990234": 49, "1571": 49, "930054": 49, "155693": 49, "185": 49, "043839": 49, "930519": 49, "344": 49, "853729": 49, "668976": 49, "719246": 49, "030106": 49, "649017": 49, "701126": 49, "448059": 49, "968727": 49, "372787": 49, "27071": 49, "460938": 49, "3036": 49, "889893": 49, "8276": 49, "849609": 49, "1577": 49, "069946": 49, "148396": 49, "717285": 49, "544601": 49, "017273": 49, "767677": 49, "240089": 49, "409836": 49, "542816": 49, "326614": 49, "160965": 49, "182632": 49, "790260": 49, "27186": 49, "689453": 49, "3046": 49, "770020": 49, "8303": 49, "980469": 49, "1572": 49, "849976": 49, "carta": 49, "conversano": 49, "rebalanc": 49, "577050": 49, "frontiersin": 49, "3389": 49, "fam": 49, "thing": [50, 55, 63, 65, 66, 68], "move": [50, 62], "trail": 50, "classifi": 50, "rescal": [50, 68], "wrong": [50, 68], "unnecessarili": [50, 66], "orthogon": 50, "_n": 50, "m_r": 50, "2u_1u_2": 50, "u_3": 50, "u_m": 50, "conicsvmfactori": 50, "variable_list": [50, 55], "qr": 50, "constraint_list": [50, 55], "svm_v2": 50, "546234": 50, "152174": 50, "21435828724315473": 50, "769": 50, "q_r": 50, "computation": 50, "rememb": [50, 65], "conicdualsvmfactori": 50, "w_bar": 50, "svm_v3": 50, "546247": 50, "152194": 50, "21435778397469038": 50, "room": 50, "onward": 50, "alpha_ik": 50, "y_nk": 50, "kernelsvmfactori": 50, "hstack": 50, "nz": 50, "pz": 50, "rbf": 50, "881": 50, "encourag": 50, "poli": 50, "438": 50, "argu": [51, 65], "trust": 51, "substanc": 51, "ingredi": 51, "antenna": 51, "simul": [51, 55, 62, 66], "contrib": 52, "only_child_var": 52, "material_demand": 52, "eot_inventori": 52, "fold": 52, "initialize_problem_data": 52, "problem_data": 52, "demand_chips_ref": 52, "demand_chips_simul": 52, "showtableofpyomovari": 52, "decim": 52, "23580": 52, "722": 52, "1823": 52, "1233": 52, "2465": 52, "682": 52, "1620": 52, "1586": 52, "1964": 52, "1678": 52, "1430": 52, "5020": 52, "4396": 52, "5017": 52, "3187": 52, "1807": 52, "643": 52, "2425": 52, "minimize_missed_demand_in_period": 52, "missed_demand": 52, "nb": 52, "resource_constraint": 52, "produced_plus_unmet": 52, "total_unmet": 52, "simulation_per_trajectori": 52, "simulate_perform": 52, "perturbed_demand": 52, "applymap": 52, "inv": 52, "md": 52, "missing_demand": 52, "missingdemand": 52, "swaplevel": 52, "inventoryevolut": 52, "average_missed_demand": 52, "bim_robust_missed_demand": 52, "realized_inv_cost": 52, "trajectori": 52, "n_sim": 52, "simresult": 52, "sllighli": 52, "nonzero": 52, "20309": 52, "3270": 52, "3309": 52, "flown": 53, "airlin": [53, 61], "airplan": [53, 62], "randomst": 53, "airport": 53, "generate_flight": 53, "n_flight": 53, "min_dur": 53, "max_dur": 53, "max_departur": 53, "rs": 53, "end_flight": 53, "start_flight": 53, "floor": 53, "ceil": 53, "flightdata": 53, "draw_flight": 53, "add_subplot": 53, "get_yaxi": 53, "iterrow": 53, "1h": 53, "feasible_flight_pair": 53, "turnaound": 53, "turnaround": [53, 68], "flight_pair": 53, "reassign": 53, "unexpect": 53, "delai": [53, 63], "sink": 53, "bigcup_": 53, "cup": [53, 65, 66], "eq": 53, "71a": 53, "71b": 53, "71c": 53, "71d": 53, "71e": 53, "eqref": 53, "drawback": 53, "blind": 53, "swap": 53, "lot": 53, "huge": [53, 65], "altogeth": 53, "flight1": 53, "flight2": 53, "p_f": 53, "unassign": 53, "q_f": 53, "minimize_airplan": 53, "redraw": 53, "dg_soln": 53, "layov": 53, "flightschedul": 53, "travers": 53, "a01": 53, "a04": 53, "a03": 53, "a02": 53, "a12": 53, "a05": 53, "a06": 53, "a07": 53, "a08": 53, "a13": 53, "a09": 53, "a11": 53, "a10": 53, "a14": 53, "aircraftschedul": 53, "from_fram": 53, "nplane": 53, "n_plane": 53, "minimize_risk": 53, "nlo": 55, "rrcrcl": 55, "gemanium": 55, "showdual": 55, "feel": 55, "lognorm": 55, "somehow": [55, 59], "currentaxi": 55, "922766922829344": 55, "9701110863753781": 55, "061793174956137": 55, "0328386701386703": 55, "z_2": 55, "infinit": 55, "robustifi": 55, "rrr": 55, "rrl": 55, "bimwithboxuncertainti": 55, "robustcopp": 55, "pervari": 55, "1137": 55, "17587": 55, "tune": [55, 57], "bimwithsymmetricalboxuncertainti": 55, "606": 55, "1143": 55, "17568": 55, "gave": 55, "1138": 55, "17586": 55, "behav": 55, "17634": 55, "628": 55, "1122": 55, "1144": 55, "17502": 55, "584": [55, 62], "17436": 55, "562": 55, "1188": 55, "17370": 55, "540": 55, "17304": 55, "518": 55, "1232": 55, "17238": 55, "496": 55, "1254": 55, "17175": 55, "475": 55, "17109": 55, "453": 55, "1297": 55, "17043": 55, "1319": 55, "16977": 55, "409": 55, "1341": 55, "16911": 55, "1363": 55, "16845": 55, "1385": 55, "16779": 55, "1407": 55, "16713": 55, "321": 55, "1429": 55, "16650": 55, "1450": 55, "16584": 55, "278": 55, "1472": 55, "16518": 55, "1494": 55, "16416": 55, "16296": 55, "16001": 55, "17999": 55, "z_j": 55, "lagrang": 55, "rrcrcrcrcrcrcl": 55, "t_1": 55, "t_2": 55, "bimwithbudgetuncertainti": 55, "lam": 55, "up_rul": 55, "down_rul": 55, "641": 55, "1109": 55, "17673": 55, "violat": [55, 57, 63], "bimwithsetofscenario": 55, "worst": [55, 57, 63, 65], "bimpessim": 55, "pessim": [55, 63], "absolute_value_1": 55, "absolute_value_2": 55, "absolute_value_less_than_on": 55, "budget_constraint": 55, "worst_z": 55, "wrap": 55, "gradual": [55, 63], "reoptim": 55, "adversarial_converg": 55, "stopping_precis": [55, 63], "max_iter": [55, 63], "adversarial_iter": 55, "niter": [55, 63], "constraint_viol": 55, "baselin": [55, 66], "viabl": 55, "polytop": 55, "ellipsoid": 55, "extrem": [55, 63], "minuscul": 55, "radiu": 55, "_1x_1": 55, "_2x_2": 55, "newli": [55, 63, 65], "pyk": 55, "bimwithballuncertainti": 55, "domain_typ": 55, "realset": 55, "idxchip": 55, "xtow": 55, "617": 55, "755": 55, "1132": 55, "17603": 55, "integerset": 55, "1133": 55, "17601": 55, "bimwithballuncertaintyassquaredsecondordercon": 55, "soc": 55, "pop": 56, "seafood": 56, "offshor": 57, "turbin": [57, 65, 66], "fluctuat": [57, 65, 66], "intermitt": 57, "mismatch": 57, "varepsilon": [57, 60], "fine": 57, "saa": [57, 61], "seaborn": 57, "sn": 57, "read_economic_dispatch_data": 57, "wind_production_samples_df": 57, "discrete_wind": 57, "wind_production_sampl": 57, "fifth": 57, "94632359541376": 57, "set_styl": 57, "darkgrid": 57, "histplot": 57, "kde": 57, "kde_kw": 57, "23034433319671": 57, "bubbl": 57, "df_node": 57, "showinst": 57, "zorder": 57, "u_j": 57, "thank": [57, 58], "omega_j": 57, "u_jm_j": 57, "deactiv": [57, 66], "incorrect": 57, "certainli": 57, "repeatedli": 57, "economic_dispatch": 57, "supply_demand_leq": 57, "supply_demand_geq": 57, "success_prob": 57, "sum_product": 57, "sum_demand": 57, "3007": 57, "1733": 57, "393": 57, "7850": 57, "601": 57, "reward": 57, "tradeoff": [57, 63, 64], "getlogg": [57, 66], "setlevel": [57, 66], "fixed_delta": 57, "feas_ep": 57, "feas_obj": 57, "num": 57, "epsilon": 57, "fixed_ep": 57, "feas_delta": 57, "tighter": 57, "flat": 57, "multivari": [58, 62], "gaussian": 58, "cdf": [58, 60, 62], "ppf": [58, 60, 62], "dramat": [58, 65], "markowitz_chanceconstraint": 58, "chance_constraint": 58, "078": 58, "commemor": 59, "unsold": [59, 60, 62], "salvag": 59, "sunni": 59, "ski": 59, "poor": [59, 64, 66], "dilemma": 59, "expected_demand": 59, "10220": 59, "165": [59, 64], "3950": 59, "8339": 59, "satisfactori": 59, "lesser": 59, "operation": 59, "sales_less_than_ord": 59, "sales_less_than_demand": 59, "11200": [59, 64], "8920": 59, "920": 59, "581": 59, "compens": [59, 65], "unfold": 59, "probablist": 59, "transpir": 59, "varaibl": 59, "variat": 59, "18200": 59, "evss": 59, "hypother": 59, "220": [59, 69], "vpi": 59, "math": [60, 64], "ton": [60, 64], "tuna": 60, "whom": 60, "fish": 60, "leftov": 60, "cold": 60, "cx": 60, "cumul": [60, 68], "pareto": 60, "expon": 60, "weibul": [60, 66], "5357": 60, "weibull_min": 60, "838": 60, "extratick": 60, "x_opt": 60, "ytick": 60, "parametr": [60, 69], "mean_demand": 60, "first_stage_profit": 60, "cant_sell_fish_i_dont_hav": 60, "fish_do_not_disappear": 60, "second_stage_profit": 60, "total_profit": 60, "determist": 60, "naiveseafoodstocksaa": 60, "distributiontyp": 60, "indices_rul": 60, "xi": 60, "cantsoldthingsfishdonthav": 60, "fishdonotdisappear": 60, "total_expected_profit": 60, "7500": [60, 64], "naiveprofit_uniform": 60, "xm": 60, "naiveprofit_pareto": 60, "naiveprofit_weibul": 60, "966": [60, 62], "910": [60, 62], "vss": 60, "seafoodstocksaa": 60, "printflag": 60, "cantsoldfishidonthav": 60, "smartprofit_uniform": 60, "smartprofit_pareto": 60, "smartprofit_weibul": 60, "979": 60, "890": 60, "919": 60, "profit_uniform": 60, "profit_pareto": 60, "profit_weibul": 60, "xw": 60, "recours": [61, 62, 66], "ccg": [61, 63], "farmer": 61, "land": [61, 64], "curtail": [61, 65], "birg": [62, 64], "louveaux": [62, 64], "media": [62, 64], "bueno": 62, "economi": 62, "passeng": 62, "ticket": 62, "weekdai": 62, "traffic": 62, "middai": 62, "overbook": 62, "downgrad": 62, "unavail": 62, "revenue_factor": 62, "seat_factor": 62, "seat_report": 62, "unsatisfi": 62, "spillag": 62, "equivalent_seat": 62, "nseat": 62, "nticket": 62, "unmet": 62, "nspillag": 62, "unfulfil": 62, "nexpect": 62, "rot": 62, "trial": 62, "seats_all_economi": 62, "eev": 62, "evm": 62, "s_c": 62, "t_c": 62, "r_c": 62, "f_c": 62, "mu_c": 62, "bm": [62, 63], "airline_determinist": 62, "plane_seat": 62, "demand_limit": 62, "seat_limit": 62, "airline_solv": 62, "model_eev": 62, "seats_eev": 62, "boldsymbol": 62, "z_c": 62, "tuplic": 62, "airline_stochast": 62, "model_stochast": 62, "seats_stochast": 62, "client": [62, 64], "enrol": 62, "loyalti": 62, "cover": [62, 63, 65], "z_f": 62, "mu_f": 62, "sigma_f": 62, "z_b": [62, 63], "mu_b": 62, "sigma_b": 62, "mu_": 62, "sigma_": 62, "s_f": 62, "s_b": 62, "054": 62, "counterpart": [62, 65], "qo": 62, "airline_cc": 62, "qosf": 62, "qosfb": 62, "first_class": 62, "business_class": 62, "model_cc": 62, "seats_cc": 62, "z_e": 62, "sigma_c": 62, "simplif": 62, "anymor": 62, "sake": [62, 63], "nmodel": 62, "nearest": 62, "multivariate_norm": 62, "demand_saa": 62, "demand_saa_stat": 62, "ci": 62, "889": 62, "088936": 62, "051534": 62, "839669": 62, "seat_report_saa": 62, "model_ssa": 62, "seats_saa": 62, "148": 62, "764": 62, "416": 62, "147": 62, "944": 62, "211": 62, "mu_e": 62, "ccc": 62, "rho_": 62, "fb": 62, "fe": 62, "bf": 62, "BE": 62, "ef": 62, "eb": 62, "truncat": 62, "nsampl": 62, "cov": 62, "cj": 62, "convari": 62, "590": 62, "301": 62, "951388": 62, "139984": 62, "147365": 62, "613469": 62, "044965": 62, "434823": 62, "229": 62, "219119": 62, "216627": 62, "916315": 62, "303": 62, "184": 62, "697": 62, "816": 62, "airline_fin": 62, "first_class_loy": 62, "first_class_loyality_r": 62, "business_class_loy": 62, "business_class_loyality_r": 62, "995": 62, "031": 62, "969": 62, "startup": 63, "announc": 63, "campaign": 63, "chief": 63, "offic": 63, "coo": 63, "z_a": 63, "z_d": 63, "attain": 63, "subtract": 63, "p_u": 63, "p_v": 63, "preorder": 63, "10x": 63, "50z_a": 63, "80z_b": 63, "40z_b": 63, "tau": [63, 69], "model_param": 63, "uniformli": [63, 65], "z_sampl": 63, "max_min_profit": 63, "stage_net_profit": 63, "model_constraint": 63, "nsolut": 63, "883": 63, "547": 63, "slight": 63, "max_avg_profit": 63, "avg_profit": 63, "avg_case_p": 63, "2305": 63, "max_profit_fixed_x": 63, "fixed_x_valu": 63, "worst_cas": 63, "fixed_x": [63, 66], "xopt_rob": 63, "nsolv": 63, "worst_case_p": 63, "xopt_avg": 63, "underperform": 63, "narrow": 63, "stabler": 63, "phenomenon": 63, "unsur": 63, "downsid": 63, "i_3": 63, "_3": 63, "i1": 63, "i2": 63, "i3": 63, "i4": 63, "subproblem_param": 63, "hack": 63, "converg": 63, "proxi": 63, "acceler": 63, "freeli": 63, "hurt": 63, "pessimization_problem": 63, "master_solut": 63, "z_a_max": 63, "z_b_max": 63, "z_d_max": 63, "big_m": 63, "z_indic": 63, "z_ab": 63, "a_ub": 63, "a_lb": 63, "a_ab": 63, "b_lb": 63, "b_ub": 63, "b_ab": 63, "d_lb": 63, "d_ub": 63, "d_ab": 63, "z_budget": 63, "blockwis": 63, "at_least_one_viol": 63, "max_viol": 63, "subproblem": 63, "seem": [63, 65, 68], "hundr": 63, "ccg_converg": 63, "ccg_iter": 63, "export": 63, "single_solut": 63, "x_kei": 63, "y_kei": 63, "theta_opt": 63, "560": 63, "555": 63, "zeng": 63, "zhao": 63, "457": 63, "461": 63, "francoi": 64, "acr": 64, "crop": 64, "wheat": 64, "corn": 64, "beet": 64, "230": 64, "cattl": 64, "wholesal": 64, "decad": 64, "quota": 64, "excess": [64, 69], "interview": 64, "stai": 64, "advic": 64, "total_land": 64, "limit_on_planted_land": 64, "crop_yield": 64, "under_quota": 64, "over_quota": 64, "farm_report": 64, "nscenario": 64, "118600": 64, "18400": 64, "216000": 64, "78000": 64, "138000": 64, "analys": 64, "hear": 64, "108390": 64, "167000": 64, "52700": 64, "25500": 64, "27200": 64, "7200": 64, "65000": 64, "151000": 64, "109350": 64, "38250": 64, "12750": 64, "180000": 64, "115000": 64, "48820": 64, "23800": 64, "1700": 64, "28480": 64, "144000": 64, "79000": 64, "lower_bound_profit": 64, "59950": 64, "113250": 64, "37250": 64, "246000": 64, "97500": 64, "148500": 64, "8500": 64, "6500": 64, "40400": 64, "4975": 64, "2525": 64, "204350": 64, "106850": 64, "43550": 64, "118500": 64, "231000": 64, "133500": 64, "00000000055": 64, "min_profit": 64, "56750": 64, "56820": 64, "820": 64, "800": 64, "980": 64, "390": 64, "290": 64, "56800": 64, "107100": 64, "147000": 64, "23000": 64, "228000": 64, "150000": 64, "117500": 64, "14000": 64, "172800": 64, "94800": 64, "uiowa": 64, "dbricker": 64, "stacks_pdf1": 64, "slpwr_farmer": 64, "uh": 64, "rohop": 64, "spring_15": 64, "chapter1": 64, "surplu": 65, "shortag": 65, "opf": [65, 66], "panel": 65, "p_j": 65, "lllll": [65, 66], "delta_i": 65, "respond": 65, "jointli": 65, "adversari": 65, "costli": 65, "rework": 65, "opf_participationfactor": 65, "totalimbal": 65, "abstotalimbal": 65, "uniformparticipationfactor": 65, "swh": 65, "cg": 65, "ng": 65, "isna": 65, "abs_total_imbal": 65, "total_imbal": 65, "windsolarhydro_nopartecipationfactor": 65, "load_nopartecipationfactor": 65, "sum_on": 65, "equal_participationfactor": 65, "power_withrecours": 65, "generation_upper_bound_withrecours": 65, "generation_lower_bound_withrecours": 65, "flows_lower_bound": 65, "sw": 65, "sw_df": 65, "isin": 65, "zeroimbal": 65, "zerototalimbal": 65, "zeroabstotalimbal": 65, "firststagecost": 65, "40385": 65, "227": [65, 66], "235": [65, 66], "asid": 65, "proportion": 65, "averagerecoursecost": 65, "averagetotalcost": 65, "5354": 65, "45739": 65, "nfirst": 65, "205": 65, "276": 65, "41719": 65, "47073": 65, "cascad": 65, "failur": 65, "blackout": [65, 66], "damag": 65, "infrastructur": 65, "societ": 65, "unafford": 65, "281": 65, "40446": 65, "5969": 65, "46415": 65, "hertz": 66, "mainli": 66, "disconnect": 66, "offlin": 66, "advent": 66, "fairli": 66, "hydropow": 66, "former": 66, "predic": 66, "uc": [66, 69], "kappa_i": 66, "c_fix": 66, "nontrivi": 66, "g_i": 66, "shore": 66, "Being": 66, "g_": 66, "16563": 66, "4718": 66, "18007": 66, "72049": 66, "_v": 66, "705509": 66, "734756": 66, "273978": 66, "159230": 66, "852748": 66, "602": 66, "814908": 66, "230344": 66, "690399": 66, "514209": 66, "248977": 66, "784856": 66, "664045": 66, "163": 66, "009206": 66, "175633": 66, "504459": 66, "086431": 66, "1689": 66, "384370": 66, "1057": 66, "306239": 66, "1837": 66, "349675": 66, "1456": 66, "262510": 66, "526012": 66, "753966": 66, "693808": 66, "050352": 66, "747257": 66, "554867": 66, "1504": 66, "397099": 66, "1751": 66, "390683": 66, "2450": 66, "534057": 66, "2184": 66, "454": 66, "660581": 66, "1617": 66, "451": 66, "133883": 66, "1627": 66, "g_offshor": 66, "piecewis": 66, "g_onshor": 66, "uc_windcurtail": 66, "vmax": 66, "nw": 66, "voltag": 66, "term2": 66, "term1": 66, "wind_speed_to_pow": 66, "wind_curtail": 66, "scale64": 66, "shape64": 66, "scale65": 66, "shape65": 66, "turbineact": 66, "tubin": 66, "29662": 66, "uc_windcurtailment_fixed_x": 66, "mean_sampl": 66, "m_nomin": 66, "15101": 66, "mechan": 66, "n_infeas": 66, "m_singl": 66, "workflow": 67, "thon": 68, "ptimiz": 68, "odel": 68, "bject": 68, "stateless": 68, "immut": [68, 69], "mutat": 68, "incompat": 68, "glanc": 68, "encapsul": 68, "forward": 68, "invoc": 68, "concurr": 68, "exclaim": 68, "exclam": 68, "lawn": 68, "circ": 68, "enthus": 68, "hello": 68, "someth": 68, "bind": 68, "contains_valu": 68, "boilerpl": 68, "push": 68, "attributeerror": 68, "spe": 68, "ca": 68, "clone": 68, "_solver": 68, "new_model": 68, "_transform": 68, "overridden": 68, "rtype": 68, "__rshift__": 68, "production_model": 68, "2400": 68, "dae": 68, "reaction": 68, "stackrel": 68, "k_1": 68, "k_2": 68, "isotherm": 68, "ultim": 68, "t_f": 68, "max_t": 68, "da": 68, "dt": 68, "db": 68, "tractabl": 68, "t_ff": 68, "ode_model_build": 68, "k1": 68, "k2": 68, "continuousset": 68, "tf": 68, "dadt": 68, "derivativevar": 68, "dbdt": 68, "max_b": 68, "odea": 68, "odeb": 68, "colloc": 68, "669": 68, "15767005981401438": 68, "8541314382648219": 68, "ode_solv": 68, "023594361612317": 68, "6687402900841761": 68, "philliam": 68, "codeproject": 68, "5290753": 68, "deploy": 69, "guidelin": 69, "supplement": 69, "pep": 69, "emphas": 69, "modular": 69, "strongli": 69, "discourag": 69, "gen": 69, "r1bi": 69, "r3": 69, "r4": 69, "filter_rul": 69, "r5": 69, "trace": 69, "creation": 69, "time_period": 69, "ny": 69, "cariabl": 69, "callback": 69, "p1": 69, "p2": 69, "validate_param": 69, "p3": 69, "param_a": 69, "param_b": 69, "intent": 69, "scope": 69, "inconsist": 69, "redefin": 69, "cognit": 69, "burden": 69, "lower_bound": 69, "upper_bound": 69, "_rule": 69, "new_constraint_rul": 69, "new_constraint": 69, "bahavior": 69, "capacity_constraint": 69, "underscor": 69, "finish_tim": 69, "total_tim": 69, "camelcas": 69, "snake_cas": 69, "2x": 69, "manipul": 69, "promot": 69, "semant": 69, "suit": 69, "doubli": 69, "primari": 69, "secondari": 69, "referenc": 69, "ob": 69, "slice": 69, "254": 69, "173": 69, "330": 69, "430": 69, "reorgan": 69, "wrangl": 69, "colleagu": 69, "draft": 69, "woodruff": 69, "davi": 69, "javier": 69, "salmeron": 69, "medrano": 69, "naval": 69, "postgradu": 69, "bethani": 69, "nicholson": 69, "siirola": 69, "michael": 69, "bynum": 69, "jasper": 69, "doorn": 69, "leon": 69, "lan": 69}, "objects": {}, "objtypes": {}, "objnames": {}, "titleterms": {"index": [0, 69], "hand": 1, "On": 1, "optim": [1, 2, 6, 8, 12, 14, 15, 16, 18, 22, 26, 28, 35, 36, 37, 38, 39, 42, 43, 44, 47, 48, 49, 50, 51, 54, 56, 58, 60, 62, 63, 65, 66, 68], "python": [1, 4], "get": 1, "start": 1, "help": 1, "us": [1, 12, 18, 22, 26, 37, 55, 60, 62, 63, 68, 69], "about": 1, "citat": 1, "1": [2, 5, 27, 32, 35, 39, 44, 62, 64], "mathemat": [2, 3, 4, 33, 34, 68], "what": 2, "A": [3, 4, 5, 7, 12, 27, 30, 37, 68], "first": [3, 20, 22], "product": [3, 4, 8, 9, 10, 11, 12, 15, 17, 18, 21, 26, 41, 52, 55, 63, 68], "plan": [3, 12, 23, 32, 52, 55, 63, 68], "problem": [3, 7, 8, 9, 10, 11, 12, 17, 18, 20, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 41, 44, 45, 46, 47, 48, 52, 53, 54, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65, 68], "statement": [3, 23, 24, 25, 46, 63, 64, 68], "model": [3, 4, 5, 7, 12, 13, 14, 15, 18, 19, 20, 21, 23, 24, 25, 26, 27, 29, 31, 32, 35, 37, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 62, 64, 68, 69], "data": [4, 7, 13, 14, 15, 17, 18, 22, 25, 31, 32, 35, 37, 40, 41, 42, 49, 50, 53, 57, 62, 64, 65, 66, 69], "driven": 4, "pyomo": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 41, 42, 44, 45, 48, 49, 50, 52, 53, 55, 57, 60, 65, 66, 67, 68, 69], "preambl": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60, 66], "instal": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60, 62, 66], "solver": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60, 66, 68], "represent": 4, "The": [4, 5, 8, 12, 20, 42, 45, 47, 50, 59, 63, 64, 68], "For": 4, "expert": 4, "creat": [4, 5, 25, 53], "subclass": 4, "concretemodel": [4, 5, 69], "basic": 5, "step": 5, "import": [5, 18, 29, 35, 57, 62, 65, 66, 68], "2": [5, 6, 27, 32, 35, 39, 44, 62, 64], "object": [5, 10, 11, 23, 25, 45, 69], "3": [5, 16, 27, 32, 39, 62, 64], "decis": [5, 25], "variabl": [5, 25, 69], "4": [5, 28, 62, 64], "express": 5, "5": [5, 36, 62, 64], "6": [5, 43, 62], "constraint": [5, 23, 25, 29, 44, 45, 58, 62, 63, 69], "7": [5, 51], "solv": [5, 35, 62, 63], "8": [5, 54], "report": [5, 7, 25, 32], "solut": [5, 19, 25, 32, 37, 39, 44, 46, 52, 55, 57, 59, 60, 62, 63, 64, 65, 66], "pprint": 5, "access": 5, "valu": [5, 59], "pyo": [5, 69], "panda": [5, 32, 69], "linear": [6, 16, 37, 42, 45, 50], "extra": [7, 15, 19, 21, 23, 27, 35, 37, 41, 46, 49, 64, 66], "materi": [7, 12, 15, 19, 21, 23, 27, 35, 37, 41, 46, 49], "wine": 7, "qualiti": [7, 66], "predict": 7, "l_1": 7, "regress": [7, 13, 40], "descript": [7, 8, 17, 18, 20, 22, 30, 33, 34, 38, 44, 48, 52, 53, 60, 62, 63, 65, 69], "mean": [7, 14, 15, 59, 64], "absolut": [7, 13, 14], "deviat": [7, 13, 14], "mad": [7, 14], "preliminari": [7, 66], "look": 7, "which": 7, "featur": [7, 42, 50], "influenc": 7, "lad": [7, 13, 40], "line": [7, 27], "fit": 7, "identifi": 7, "multivari": 7, "how": [7, 46], "do": 7, "perform": [7, 42, 50, 52], "bim": [8, 9, 10, 11, 12, 17, 18, 52, 55], "microchip": [8, 55], "build": [8, 44, 64], "matrix": 8, "reformul": [8, 30, 37, 45, 57], "canon": 8, "form": [8, 42, 62], "lo": [8, 30], "dual": [9, 37, 42, 50], "deriv": 9, "variant": [10, 11, 55, 64], "two": [10, 27, 61, 62, 63, 66], "fraction": 10, "addit": [10, 14, 39], "fix": [10, 69], "cost": [10, 32, 34], "worst": [11, 15, 64], "case": [11, 15, 44, 62, 63, 64, 65], "minmax": 11, "function": [11, 50, 68], "maxim": [11, 15, 59], "lowest": 11, "possibl": 11, "profit": [11, 15, 59, 60], "demand": [12, 60, 62], "forecast": [12, 65], "acquisit": 12, "more": [12, 30], "parsimoni": 12, "least": [13, 40], "gener": [13, 37, 40, 53, 62, 63, 65], "visual": [13, 21, 25, 40, 53, 57, 69], "result": [13, 21, 32, 40, 41, 60], "portfolio": [14, 38, 48, 49, 58], "yfinanc": 14, "download": [14, 29], "histor": 14, "stock": [14, 37, 60], "price": [14, 41], "analysi": [14, 52, 57], "asset": 14, "scale": 14, "statist": 14, "daili": 14, "return": [14, 64], "risk": [14, 46, 47, 49, 64], "versu": [14, 64], "free": [14, 49, 53], "multi": [15, 26, 44, 69], "facil": [15, 20], "scenario": [15, 59, 62, 63, 65], "summari": [15, 59, 64], "mix": [16, 44], "integ": [16, 44, 55], "perturb": 17, "revisit": [18, 48], "implement": [18, 21, 23, 25, 26, 30, 42, 49, 50, 55, 65], "altern": 18, "block": [18, 69], "cryptarithm": 19, "puzzl": 19, "suggest": [19, 39, 41], "exercis": [19, 21, 23, 39, 41, 46], "locat": 20, "milo": [20, 26, 57], "formul": [20, 21, 25, 33, 34, 37, 38, 42, 45, 48, 50, 53, 63], "second": [20, 45, 55], "option": [20, 39], "job": [21, 22], "shop": [21, 59], "schedul": [21, 22, 25, 33, 53], "exampl": [21, 37, 68], "task": 21, "decomposit": 21, "print": 21, "gantt": [21, 22], "chart": [21, 22], "applic": 21, "batch": [21, 68], "process": [21, 22], "singl": [21, 44, 45, 54, 56], "strategi": [21, 24, 27, 64], "multipl": [21, 44, 45], "overlap": 21, "ad": [21, 46, 62], "time": [21, 22, 29], "unit": [21, 66], "clean": 21, "out": [21, 22], "zero": 21, "wait": 21, "polici": [21, 35], "refer": [21, 37, 68], "specif": 21, "cleanout": 21, "comput": 21, "impact": 21, "machin": [22, 42, 50], "empir": 22, "rule": 22, "fifo": 22, "earliest": 22, "due": 22, "date": 22, "edd": 22, "shortest": 22, "spt": 22, "disjunct": [22, 23, 26], "program": [22, 26, 42, 68], "mainten": 23, "ramp": 23, "specifi": 23, "minimum": [23, 34], "number": [23, 30], "oper": [23, 32], "dai": 23, "between": [23, 30, 62], "period": 23, "recharg": 24, "an": [24, 29, 39], "electr": 24, "vehicl": 24, "charg": 24, "station": 24, "inform": [24, 59], "rout": 24, "car": 24, "workforc": 25, "shift": 25, "set": [25, 42, 50, 55, 69], "paramet": [25, 49, 69], "master": 25, "categor": 25, "worker": 25, "store": 25, "manag": 25, "factori": 26, "strip": 27, "pack": 27, "statment": 27, "lower": 27, "upper": 27, "bound": [27, 69], "shelf": 27, "width": 27, "version": [27, 47], "up": [27, 59], "box": [27, 55], "rotat": 27, "place": 27, "dimens": 27, "advanc": 27, "topic": 27, "symmetri": [27, 53], "break": 27, "network": [28, 30, 35, 66], "cryptocurr": 29, "arbitrag": [29, 31], "search": 29, "networkx": 29, "ccxt": 29, "exchang": 29, "repres": 29, "direct": 29, "graph": [29, 31, 33], "order": [29, 45, 55], "book": 29, "trade": 29, "find": 29, "demonstr": [29, 31], "opportun": 29, "brute": 29, "forc": 29, "simpl": 29, "cycl": 29, "capac": 29, "question": 29, "user": 29, "real": 29, "from": [29, 37, 39, 60], "dinner": 30, "seat": [30, 62], "arrang": 30, "minim": [30, 32], "maximum": 30, "group": 30, "size": 30, "tabl": 30, "max": 30, "flow": [30, 34, 35, 65], "systemat": 30, "comparison": [30, 40], "algorithm": [30, 37], "forex": 31, "triangular": 31, "displai": [31, 32, 69], "gasolin": 32, "distribut": [32, 39, 60, 62], "franchis": 32, "total": [32, 53], "deliveri": [32, 39], "entri": 32, "rate": [32, 49], "owner": 32, "share": [32, 45], "compar": [32, 35], "appendix": [32, 45, 67], "method": [32, 45, 60, 62], "manual": 32, "format": 32, "graphviz": 32, "color": 33, "energi": [35, 57, 66], "dispatch": [35, 57, 66], "background": 35, "power": [35, 65], "physic": 35, "setup": 35, "code": [35, 69], "edg": 35, "structur": 35, "instanc": 35, "opf": 35, "strict": 35, "fossil": 35, "fuel": 35, "pt": 35, "three": 35, "convex": [36, 39, 40], "cut": 37, "pattern": 37, "known": [37, 69], "bilinear": [37, 39], "hybrid": 37, "jump": 37, "document": 37, "column": [37, 63], "wikipedia": 37, "woodwork": 37, "googl": 37, "sheet": 37, "markowitz": [38, 48, 58], "milk": 39, "pool": 39, "blend": 39, "wholesal": 39, "busi": 39, "usual": 39, "bui": 39, "truck": 39, "remot": 39, "supplier": 39, "why": [39, 41, 68], "ar": 39, "hard": 39, "approxim": [39, 60], "global": 39, "nonlinear": [39, 42, 50], "gnlo": 39, "couenn": 39, "conclud": 39, "remark": 39, "bibliograph": [39, 44, 45, 46, 47, 49, 63, 64], "note": [39, 44, 45, 46, 47, 49, 63, 64], "ordinari": 40, "squar": 40, "ol": 40, "refineri": 41, "shadow": 41, "cvxpy": 41, "crude": 41, "oil": 41, "feed": 41, "kerosin": 41, "so": 41, "high": 41, "support": [42, 50], "vector": [42, 50], "binari": [42, 47], "classif": 42, "read": [42, 50], "select": [42, 50], "train": [42, 50], "svm": [42, 50], "classifi": 42, "metric": [42, 50], "quadrat": [42, 44, 45], "primal": [42, 50], "kernel": [42, 50], "space": [42, 50], "trick": [42, 50], "polynomi": [42, 50], "conic": [43, 45, 47, 50], "design": [44, 49], "multilay": 44, "insul": 44, "analyt": [44, 60, 62], "n": 44, "layer": 44, "miqco": 44, "econom": [45, 57], "quantiti": 45, "usag": 45, "eoq": 45, "classic": 45, "item": 45, "hyperbol": 45, "cone": [45, 55], "as_domain": 45, "simplifi": 45, "rotated_quadrat": 45, "extend": 45, "resourc": 45, "test": 45, "larger": 45, "soco": 45, "luenberg": 46, "s": [46, 47, 64], "invest": 46, "wheel": 46, "simul": [46, 47, 52], "avers": [46, 49], "doe": 46, "chang": 46, "kelli": 47, "criterion": 47, "log": 47, "growth": [47, 49], "game": 47, "outcom": 47, "constrain": [47, 55, 57], "financi": 49, "effect": 49, "equiti": 49, "multipli": 49, "interest": 49, "extens": [49, 62], "radial": 50, "basi": 50, "account": 51, "uncertainti": [51, 55], "meet": 51, "realiti": 51, "robust": [52, 54, 55, 63], "via": 52, "actual": 52, "fleet": 53, "assign": 53, "flight": 53, "naiv": 53, "unimodular": 53, "aircraft": 53, "reduc": [53, 68], "riski": 53, "stage": [54, 56, 61, 62, 63, 66], "origin": 55, "copper": 55, "consumpt": 55, "counterpart": 55, "cardin": 55, "adversari": 55, "approach": 55, "budget": 55, "ball": 55, "environ": 55, "9": 56, "stochast": [56, 59, 62, 64, 65], "system": 57, "chanc": [57, 58, 62], "ed": 57, "understand": 57, "sensit": 57, "pop": 59, "net": 59, "expect": 59, "evm": 59, "vss": 59, "perfect": [59, 65], "evpi": 59, "seafood": 60, "center": 60, "explicit": 60, "determinist": [60, 62], "averag": [60, 62, 63], "sampl": [60, 63], "converg": 60, "saa": [60, 62, 63, 65], "10": 61, "airlin": 62, "alloc": 62, "attribut": 62, "its": [62, 64], "continu": 62, "uncorrel": 62, "correl": 62, "differ": 62, "type": 62, "tackl": 62, "farmer": 64, "recommend": 64, "plant": 64, "recours": 65, "action": 65, "imbal": 65, "nonzero": 65, "wind": 66, "curtail": 66, "commit": 66, "packag": 66, "assess": 66, "work": 67, "workflow": [68, 69], "monad": 68, "pure": 68, "composit": 68, "map": 68, "filter": 68, "functool": 68, "mayb": 68, "failur": 68, "wrap": 68, "transform": 68, "pyomomonad": 68, "reactor": 68, "builder": 68, "execut": 68, "alternt": 68, "syntax": 68, "style": 69, "guid": 69, "convent": 69, "namespac": 69, "instead": 69, "abstractmodel": 69, "rangeset": 69, "domain": 69, "rather": 69, "than": 69, "within": 69, "when": 69, "prefer": 69, "constraintlist": 69, "decor": 69, "improv": 69, "readabl": 69, "name": 69, "short": 69, "mai": 69, "all": 69, "cap": 69, "capit": 69, "tidi": 69, "dimension": 69, "acknowledg": 69}, "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.ext.intersphinx": 1, "sphinxcontrib.bibtex": 9, "sphinx": 56}}) \ No newline at end of file +Search.setIndex({"docnames": ["genindex", "intro", "notebooks/01/01.00", "notebooks/01/production-planning", "notebooks/01/production-planning-advanced", "notebooks/01/production-planning-basic", "notebooks/02/02.00", "notebooks/02/L1-regression-wine-quality", "notebooks/02/bim", "notebooks/02/bim-dual", "notebooks/02/bim-fractional", "notebooks/02/bim-maxmin", "notebooks/02/bim-rawmaterialplanning", "notebooks/02/lad-regression", "notebooks/02/mad-portfolio-optimization", "notebooks/02/multiproductionfaciliity_worstcase", "notebooks/03/03.00", "notebooks/03/bim-perturbed", "notebooks/03/bim-production-revisited", "notebooks/03/cryptarithms", "notebooks/03/facility-location", "notebooks/03/job-shop-scheduling", "notebooks/03/machine-scheduling", "notebooks/03/maintenance-planning", "notebooks/03/recharging-electric-vehicle", "notebooks/03/shift-scheduling", "notebooks/03/simple-production-model-gdp", "notebooks/03/strip-packing", "notebooks/04/04.00", "notebooks/04/cryptocurrency-arbitrage", "notebooks/04/dinner-seat-allocation", "notebooks/04/forex-arbitrage", "notebooks/04/gasoline-distribution", "notebooks/04/graph-coloring", "notebooks/04/mincost-flow", "notebooks/04/power-network", "notebooks/05/05.00", "notebooks/05/cutting-stock", "notebooks/05/markowitz_portfolio", "notebooks/05/milk-pooling", "notebooks/05/ols-regression", "notebooks/05/refinery-production", "notebooks/05/svm", "notebooks/06/06.00", "notebooks/06/building-insulation", "notebooks/06/economic-order-quantity", "notebooks/06/investment-wheel", "notebooks/06/kelly-criterion", "notebooks/06/markowitz_portfolio_revisited", "notebooks/06/optimal-growth-portfolios", "notebooks/06/svm-conic", "notebooks/07/07.00", "notebooks/07/bim-robustness-analysis", "notebooks/07/fleet-assignment", "notebooks/08/08.00", "notebooks/08/bim-robust-optimization", "notebooks/09/09.00", "notebooks/09/economicdispatch", "notebooks/09/markowitz_portfolio_with_chance_constraint", "notebooks/09/pop-up_shop", "notebooks/09/seafood", "notebooks/10/10.00", "notebooks/10/airline-seating", "notebooks/10/ccg", "notebooks/10/farmer", "notebooks/10/opf-ldr", "notebooks/10/opf-wind-curtailment", "notebooks/appendix/appendix", "notebooks/appendix/functional-programming-pyomo", "notebooks/appendix/pyomo-style-guide"], "filenames": ["genindex.md", "intro.md", "notebooks/01/01.00.md", "notebooks/01/production-planning.ipynb", "notebooks/01/production-planning-advanced.ipynb", "notebooks/01/production-planning-basic.ipynb", "notebooks/02/02.00.md", "notebooks/02/L1-regression-wine-quality.ipynb", "notebooks/02/bim.ipynb", "notebooks/02/bim-dual.ipynb", "notebooks/02/bim-fractional.ipynb", "notebooks/02/bim-maxmin.ipynb", "notebooks/02/bim-rawmaterialplanning.ipynb", "notebooks/02/lad-regression.ipynb", "notebooks/02/mad-portfolio-optimization.ipynb", "notebooks/02/multiproductionfaciliity_worstcase.ipynb", "notebooks/03/03.00.md", "notebooks/03/bim-perturbed.ipynb", "notebooks/03/bim-production-revisited.ipynb", "notebooks/03/cryptarithms.ipynb", "notebooks/03/facility-location.ipynb", "notebooks/03/job-shop-scheduling.ipynb", "notebooks/03/machine-scheduling.ipynb", "notebooks/03/maintenance-planning.ipynb", "notebooks/03/recharging-electric-vehicle.ipynb", "notebooks/03/shift-scheduling.ipynb", "notebooks/03/simple-production-model-gdp.ipynb", "notebooks/03/strip-packing.ipynb", "notebooks/04/04.00.md", "notebooks/04/cryptocurrency-arbitrage.ipynb", "notebooks/04/dinner-seat-allocation.ipynb", "notebooks/04/forex-arbitrage.ipynb", "notebooks/04/gasoline-distribution.ipynb", "notebooks/04/graph-coloring.ipynb", "notebooks/04/mincost-flow.ipynb", "notebooks/04/power-network.ipynb", "notebooks/05/05.00.md", "notebooks/05/cutting-stock.ipynb", "notebooks/05/markowitz_portfolio.ipynb", "notebooks/05/milk-pooling.ipynb", "notebooks/05/ols-regression.ipynb", "notebooks/05/refinery-production.ipynb", "notebooks/05/svm.ipynb", "notebooks/06/06.00.md", "notebooks/06/building-insulation.ipynb", "notebooks/06/economic-order-quantity.ipynb", "notebooks/06/investment-wheel.ipynb", "notebooks/06/kelly-criterion.ipynb", "notebooks/06/markowitz_portfolio_revisited.ipynb", "notebooks/06/optimal-growth-portfolios.ipynb", "notebooks/06/svm-conic.ipynb", "notebooks/07/07.00.md", "notebooks/07/bim-robustness-analysis.ipynb", "notebooks/07/fleet-assignment.ipynb", "notebooks/08/08.00.md", "notebooks/08/bim-robust-optimization.ipynb", "notebooks/09/09.00.md", "notebooks/09/economicdispatch.ipynb", "notebooks/09/markowitz_portfolio_with_chance_constraint.ipynb", "notebooks/09/pop-up_shop.ipynb", "notebooks/09/seafood.ipynb", "notebooks/10/10.00.md", "notebooks/10/airline-seating.ipynb", "notebooks/10/ccg.ipynb", "notebooks/10/farmer.ipynb", "notebooks/10/opf-ldr.ipynb", "notebooks/10/opf-wind-curtailment.ipynb", "notebooks/appendix/appendix.md", "notebooks/appendix/functional-programming-pyomo.ipynb", "notebooks/appendix/pyomo-style-guide.md"], "titles": ["Index", "Hands-On Optimization with Python", "1. Mathematical Optimization", "A first production planning problem", "A data-driven Pyomo Model", "A basic Pyomo model", "2. Linear Optimization", "Extra material: Wine quality prediction with \\(L_1\\) regression", "BIM production", "Dual of the BIM production problem", "BIM production variants", "BIM production for worst case", "BIM production using demand forecasts", "Least Absolute Deviation (LAD) Regression", "Mean Absolute Deviation (MAD) portfolio optimization", "Extra material: Multi-product facility production", "3. Mixed Integer Linear Optimization", "BIM production with perturbed data", "BIM production revisited", "Extra material: Cryptarithms puzzle", "Facility location problem", "Extra material: Job shop scheduling", "Machine Scheduling", "Extra material: Maintenance planning", "Recharging strategy for an electric vehicle", "Workforce shift scheduling", "Production model using disjunctions", "Extra material: Strip packing", "4. Network Optimization", "Cryptocurrency arbitrage search", "Dinner seating arrangement", "Forex Arbitrage", "Gasoline distribution", "Scheduling as a graph coloring problem", "Minimum-Cost Flow Problem", "Extra material: Energy dispatch problem", "5. Convex Optimization", "Extra Material: Cutting Stock", "Markowitz portfolio optimization", "Milk pooling and blending", "Ordinary Least Squares (OLS) Regression", "Extra material: Refinery production and shadow pricing with CVXPY", "Support Vector Machines for Binary Classification", "6. Conic Optimization", "Optimal Design of Multilayered Building Insulation", "Economic Order Quantity", "Extra material: Luenberger\u2019s Investment Wheel", "The Kelly Criterion", "Markowitz portfolio optimization revisited", "Extra material: Optimal Growth Portfolios with Risk Aversion", "Training Support Vector Machines with Conic Optimization", "7. Accounting for Uncertainty: Optimization Meets Reality", "Robustness analysis of BIM production plan via simulations", "Fleet assignment problem", "8. Robust Optimization - Single Stage Problems", "Robust BIM microchip production problem", "9. Stochastic Optimization - Single Stage Problems", "Economic dispatch in energy systems", "Markowitz portfolio optimization with chance constraints", "Pop-up shop", "Stock optimization for seafood distribution center", "10. Two-Stage Problems", "Airline seat allocation problem", "Two-stage Production Planning", "Extra: The farmer\u2019s problem and its variants", "Optimal power flow problem with recourse actions", "Extra: Two-stage energy dispatch optimization with wind curtailment", "Appendix: Working with Pyomo", "Functional Programming with Pyomo", "Pyomo style guide"], "terms": {"welcom": [1, 5, 69], "thi": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69], "repositori": [1, 7, 25, 35, 55, 57], "companion": [1, 5, 6, 16, 28, 36, 43, 54, 56, 61], "notebook": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 47, 48, 49, 50, 52, 55, 57, 60, 63, 65, 66, 67, 68], "book": [1, 8, 15, 20, 22, 35, 42, 46, 47, 50, 57, 63, 65, 66, 69], "which": [1, 2, 3, 4, 5, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 35, 36, 37, 38, 39, 40, 42, 44, 45, 47, 48, 50, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "publish": 1, "cambridg": [1, 20], "univers": [1, 20, 25, 33], "press": [1, 20, 21], "2024": [1, 20], "introduc": [1, 2, 3, 4, 5, 9, 10, 11, 13, 18, 20, 21, 22, 23, 26, 27, 30, 32, 34, 35, 37, 39, 40, 42, 45, 46, 47, 49, 50, 57, 59, 62, 63, 66, 69], "concept": [1, 45, 46, 49, 50, 68], "tool": [1, 2, 5, 8, 13, 29, 30, 32, 40, 50, 53], "mathemat": [1, 5, 15, 20, 23, 29, 30, 32, 36, 37, 39, 44, 48, 49, 53, 59, 69], "exampl": [1, 2, 3, 4, 5, 6, 7, 8, 12, 16, 19, 20, 22, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 36, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 59, 60, 61, 62, 63, 64, 66, 69], "from": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 30, 31, 32, 33, 34, 35, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 61, 62, 63, 64, 65, 66, 68, 69], "rang": [1, 5, 7, 8, 12, 13, 14, 20, 21, 23, 24, 25, 27, 30, 33, 37, 38, 39, 42, 45, 46, 47, 48, 50, 52, 53, 55, 57, 58, 60, 63, 65, 66, 68, 69], "disciplin": [1, 41, 46, 47, 49], "The": [1, 2, 3, 6, 7, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 46, 48, 49, 52, 53, 55, 57, 58, 60, 62, 65, 66, 67, 69], "goal": [1, 2, 3, 5, 8, 18, 22, 27, 29, 30, 31, 33, 34, 35, 42, 57, 62, 66, 68], "ar": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 40, 42, 44, 45, 46, 47, 49, 50, 51, 52, 53, 55, 57, 59, 62, 63, 64, 65, 66, 68, 69], "provid": [1, 4, 5, 7, 8, 12, 13, 14, 15, 18, 22, 23, 24, 29, 30, 31, 32, 35, 39, 40, 42, 45, 46, 47, 48, 49, 50, 57, 59, 62, 68, 69], "foundat": 1, "learn": [1, 7, 13, 30, 40, 42, 64], "demonstr": [1, 4, 5, 7, 8, 22, 24, 25, 32, 35, 37, 39, 41, 42, 45, 46, 49, 50, 57, 62, 63, 65, 66, 67, 68], "practic": [1, 4, 5, 18, 27, 29, 32, 35, 37, 39, 42, 45, 46, 49, 50, 53, 57, 66, 68, 69], "reader": [1, 4, 7, 29, 33, 35, 63, 68], "develop": [1, 3, 4, 5, 26, 29, 32, 37, 39, 42, 45, 50, 69], "skill": [1, 2, 26], "need": [1, 2, 3, 4, 5, 8, 9, 10, 12, 14, 16, 18, 21, 23, 24, 25, 26, 27, 29, 30, 33, 35, 37, 39, 42, 43, 45, 50, 52, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 68, 69], "build": [1, 4, 5, 18, 20, 25, 29, 37, 42, 43, 50, 52, 55, 62, 63, 66, 68, 69], "model": [1, 2, 6, 8, 9, 10, 16, 22, 28, 30, 33, 34, 36, 39, 43, 51, 52, 54, 56, 57, 58, 59, 60, 61, 63, 65, 66, 67], "solv": [1, 2, 3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 61, 64, 65, 66, 68, 69], "problem": [1, 2, 4, 5, 6, 13, 14, 15, 16, 19, 21, 26, 28, 36, 40, 42, 43, 49, 50, 51, 58, 66, 69], "state": [1, 3, 11, 18, 24, 29, 32, 35, 39, 55, 59, 68, 69], "art": [1, 7, 39], "languag": [1, 5, 41, 69], "solver": [1, 28, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 53, 58, 59, 62, 63, 64, 65], "make": [1, 2, 4, 8, 12, 14, 15, 16, 18, 21, 23, 24, 25, 29, 30, 32, 33, 35, 36, 37, 41, 55, 57, 58, 63, 65, 68, 69], "extens": [1, 7, 20, 23, 26, 27, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 50, 55, 57, 58, 60, 68, 69], "pyomo": [1, 2, 3, 6, 16, 28, 36, 37, 39, 40, 43, 46, 47, 54, 56, 58, 59, 61, 62, 63, 64], "complet": [1, 3, 18, 21, 22, 23, 29, 31, 39, 42, 45, 49, 50, 53, 62, 63, 66], "versatil": 1, "packag": [1, 3, 20, 21, 22, 27, 29, 30, 31, 35, 44, 46, 47, 49, 57, 65], "ecosystem": 1, "mean": [1, 5, 6, 8, 9, 12, 13, 17, 18, 25, 29, 30, 34, 35, 37, 38, 40, 42, 45, 46, 47, 52, 53, 57, 58, 60, 62, 65, 66, 68], "decis": [1, 2, 3, 4, 6, 8, 9, 13, 14, 16, 17, 18, 21, 22, 23, 24, 26, 27, 30, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 59, 60, 61, 62, 63, 65, 66, 68, 69], "variabl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 55, 57, 59, 60, 61, 62, 63, 64, 65, 66, 68], "constraint": [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 26, 27, 28, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 46, 47, 48, 49, 50, 52, 53, 55, 56, 57, 59, 60, 64, 65, 66, 68], "object": [1, 2, 3, 4, 6, 7, 8, 9, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "transform": [1, 4, 5, 8, 13, 17, 18, 23, 26, 37, 42, 47, 50, 69], "gener": [1, 2, 3, 4, 5, 6, 7, 8, 11, 14, 16, 19, 20, 21, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 35, 38, 44, 45, 48, 50, 51, 55, 57, 58, 60, 66, 68, 69], "solut": [1, 2, 3, 4, 8, 9, 10, 12, 13, 15, 16, 17, 18, 20, 22, 23, 24, 26, 27, 28, 29, 30, 33, 34, 35, 36, 38, 41, 42, 45, 47, 48, 49, 50, 51, 53, 58, 68, 69], "open": [1, 2, 3, 5, 20, 25, 29, 35], "sourc": [1, 3, 5, 20, 29, 30, 32, 35, 37, 39, 53, 66, 69], "commerci": [1, 3, 5, 20, 37, 45, 55], "all": [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 14, 15, 16, 17, 18, 20, 21, 22, 25, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 42, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "can": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "run": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 47, 48, 49, 52, 55, 57, 60, 62, 66], "googl": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "colab": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "A": [1, 2, 6, 8, 13, 14, 15, 16, 17, 18, 21, 22, 23, 25, 26, 28, 29, 31, 32, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 58, 59, 60, 62, 63, 69], "launch": 1, "icon": 1, "appear": [1, 3, 4, 5, 7, 10, 13, 18, 19, 26, 29, 30, 31, 37, 39, 42, 44, 46, 48, 50, 53, 59, 62, 68, 69], "top": [1, 6, 8, 13, 16, 21, 22, 29, 37, 38, 40, 42, 47, 48, 50, 58, 63], "page": 1, "look": [1, 9, 12, 14, 27, 29, 50, 57, 63], "rocket": 1, "indic": [1, 4, 8, 11, 13, 16, 18, 22, 23, 26, 27, 29, 32, 35, 37, 39, 42, 44, 49, 50, 53, 60, 62, 63, 65, 66, 69], "an": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53, 55, 57, 58, 59, 62, 63, 65, 66, 67, 68, 69], "execut": [1, 7, 21, 22, 29, 30, 31, 59], "document": [1, 55, 69], "select": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 41, 48, 49, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "reopen": 1, "cell": [1, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 65, 66, 68], "insid": [1, 29, 68], "perform": [1, 5, 19, 20, 21, 22, 27, 29, 30, 46, 47, 51, 55, 59, 60, 62, 63, 64, 65, 66, 68], "ani": [1, 3, 4, 5, 6, 8, 13, 14, 15, 16, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 35, 37, 42, 45, 47, 49, 50, 59, 60, 62, 63, 64, 65, 68, 69], "necessari": [1, 4, 27, 28, 29, 33, 39, 51, 57, 68], "instal": [1, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 53, 58, 59, 63, 64, 65, 68], "code": [1, 4, 5, 7, 8, 9, 12, 13, 17, 18, 19, 20, 24, 25, 27, 29, 30, 42, 45, 47, 49, 50, 63, 68], "within": [1, 5, 15, 20, 27, 29, 35, 55, 59, 63, 66, 68], "your": [1, 20, 23, 39, 46, 62, 64], "journei": [1, 29], "first": [1, 2, 4, 5, 6, 8, 9, 10, 12, 14, 15, 18, 21, 23, 24, 26, 27, 28, 29, 30, 31, 32, 34, 35, 37, 38, 39, 42, 44, 45, 48, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "chapter": [1, 2, 5, 6, 15, 16, 18, 20, 22, 28, 36, 40, 43, 46, 48, 51, 53, 54, 56, 61, 63, 65, 66], "we": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "seek": [1, 2, 9, 42, 50, 62, 66], "feedback": [1, 69], "If": [1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 39, 42, 45, 46, 47, 48, 50, 52, 55, 57, 58, 60, 62, 63, 65, 66, 68, 69], "you": [1, 4, 8, 15, 20, 23, 27, 29, 35, 38, 39, 45, 48, 50, 55, 57, 58, 63, 64, 66, 69], "encount": [1, 4, 15, 58], "issu": [1, 14, 19, 21, 27, 29, 30, 37, 39, 44, 63, 65], "have": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 48, 49, 50, 51, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "suggest": [1, 7, 25, 37, 49, 59, 69], "how": [1, 2, 3, 4, 8, 13, 17, 18, 20, 22, 23, 24, 25, 26, 27, 29, 30, 31, 37, 38, 39, 41, 42, 44, 45, 47, 49, 50, 51, 55, 58, 59, 60, 62, 63, 64, 65, 66, 67, 68], "better": [1, 27, 28, 29, 30, 32, 39, 42, 48, 51, 53, 63, 66, 69], "pleas": [1, 50, 65], "link": [1, 27, 29, 31, 39, 45, 53], "everi": [1, 2, 4, 5, 13, 14, 20, 21, 27, 29, 33, 34, 35, 37, 39, 47, 55, 57, 62, 63, 65, 66, 68], "github": [1, 20, 25, 29, 35], "cat": [1, 14, 49], "group": [1, 6, 8, 25, 32, 52, 57], "research": [1, 21, 27, 29, 37, 39, 45, 63], "educ": 1, "who": [1, 4, 14, 25, 30, 32, 37], "came": 1, "togeth": [1, 4, 18, 27, 42, 57, 59, 63, 65, 68, 69], "common": [1, 2, 4, 5, 8, 15, 20, 21, 22, 27, 29, 31, 32, 35, 37, 39, 42, 45, 50, 62, 68, 69], "purpos": [1, 4, 21, 22, 35, 42, 45, 57, 62, 63, 65, 68], "materi": [1, 3, 4, 5, 6, 8, 16, 17, 18, 26, 28, 29, 36, 39, 43, 44, 52, 63, 69], "our": [1, 2, 8, 12, 18, 21, 22, 25, 26, 29, 30, 31, 35, 36, 42, 44, 50, 51, 53, 55, 57, 58, 59, 63, 65, 66], "classroom": 1, "teach": [1, 64, 69], "hopefulli": [1, 39, 63], "find": [1, 2, 3, 7, 9, 13, 14, 15, 20, 22, 23, 24, 27, 28, 30, 31, 32, 33, 34, 37, 39, 42, 44, 46, 49, 53, 55, 57, 59, 60, 63, 64, 65, 68], "other": [1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 35, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 55, 59, 62, 63, 66, 68, 69], "most": [1, 5, 6, 9, 15, 19, 21, 22, 23, 27, 29, 31, 32, 34, 35, 37, 39, 42, 47, 49, 53, 55, 57, 60, 63, 69], "importantli": [1, 57, 65], "those": [1, 3, 4, 8, 11, 12, 21, 27, 34, 42, 50, 60, 62, 63, 65], "entri": [1, 31, 39, 42, 50, 62, 69], "world": [1, 2, 31, 36, 39, 46, 49, 51, 62], "data": [1, 3, 5, 12, 16, 20, 21, 24, 26, 27, 29, 30, 34, 39, 51, 52, 55, 59, 60, 63, 68], "rich": 1, "applic": [1, 2, 4, 5, 7, 22, 25, 26, 27, 29, 31, 32, 37, 39, 42, 44, 45, 49, 50, 53, 57, 63, 65, 68, 69], "krzysztof": 1, "postek": 1, "boston": 1, "consult": [1, 45, 64], "formerli": 1, "tu": 1, "delft": 1, "alessandro": 1, "zocca": 1, "vu": 1, "amsterdam": [1, 62], "joaquim": 1, "gromicho": 1, "ortec": 1, "jeffrei": 1, "kantor": 1, "notr": 1, "dame": 1, "wish": [1, 4, 14, 21, 39, 42, 62], "cite": [1, 29, 39, 45, 49], "work": [1, 5, 6, 8, 11, 20, 22, 25, 29, 30, 31, 37, 42, 45, 46, 47, 49, 50, 57, 65, 68, 69], "postekzocca2024": 1, "titl": [1, 5, 14, 20, 22, 35, 37, 40, 42, 46, 49, 50, 53, 62, 68], "author": 1, "year": [1, 12, 18, 45, 49, 52, 64, 69], "onlin": [1, 29, 39, 66], "url": [1, 35, 37], "http": [1, 7, 20, 29, 31, 35, 37, 39, 42, 44, 45, 46, 47, 48, 49, 50, 57, 64, 65, 66, 68], "mobook": [1, 29, 35, 42, 50, 57, 65, 66], "io": [1, 12, 18, 20, 31, 35, 52], "mo": [1, 29, 35, 42, 50, 57, 65, 66], "broad": 2, "term": [2, 3, 4, 13, 17, 18, 20, 21, 25, 26, 29, 32, 33, 37, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 57, 59, 60, 63, 65, 66], "describ": [2, 3, 4, 6, 8, 12, 18, 21, 22, 23, 24, 25, 27, 29, 32, 34, 35, 37, 38, 41, 42, 44, 45, 48, 49, 57, 58, 59, 62, 66, 69], "wai": [2, 3, 4, 5, 8, 11, 13, 16, 20, 21, 22, 23, 28, 29, 30, 31, 32, 34, 35, 38, 45, 46, 48, 49, 50, 53, 57, 58, 63, 65, 66, 68, 69], "them": [2, 4, 5, 8, 9, 16, 18, 24, 29, 30, 36, 38, 39, 49, 53, 55, 58, 62, 63, 65, 66], "us": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20, 21, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 34, 35, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 59, 61, 64, 65, 66, 67], "dedic": [2, 55], "algorithm": [2, 3, 27, 29, 33, 45, 53, 63], "consist": [2, 5, 7, 13, 14, 20, 21, 25, 29, 31, 33, 35, 40, 42, 49, 50, 62, 68, 69], "three": [2, 4, 18, 21, 22, 25, 27, 31, 39, 49, 51, 59, 60, 62, 64, 68], "part": [2, 3, 21, 37, 42, 45, 50, 55, 63, 64, 65], "correspond": [2, 3, 4, 8, 9, 11, 12, 13, 14, 17, 18, 19, 22, 23, 25, 27, 29, 33, 35, 37, 42, 44, 45, 48, 50, 53, 55, 60, 62, 63, 65, 66, 69], "action": [2, 61, 66], "choic": [2, 4, 15, 21, 24, 26, 35, 37, 39, 42, 44, 57, 68, 69], "whether": [2, 8, 22, 24, 26, 27, 29, 31, 33, 35, 36, 44, 45, 53, 57, 63, 66], "new": [2, 4, 5, 7, 8, 13, 17, 21, 23, 25, 26, 27, 29, 30, 32, 35, 37, 39, 41, 42, 45, 48, 55, 59, 62, 63, 66, 68, 69], "manufactur": [2, 8, 17, 27, 34, 41, 63], "facil": [2, 6, 16, 21, 26, 27, 34, 39, 45], "suppli": [2, 4, 30, 32, 34, 35, 39, 57, 66], "rout": [2, 29, 51, 53, 62], "price": [2, 3, 4, 10, 11, 12, 18, 29, 31, 32, 37, 39, 49, 52, 59, 60, 62, 63, 64, 68, 69], "should": [2, 3, 8, 14, 15, 18, 22, 23, 24, 25, 26, 29, 33, 34, 36, 37, 39, 42, 47, 50, 53, 55, 57, 59, 63, 64, 65, 66, 68, 69], "sell": [2, 3, 11, 15, 18, 26, 29, 31, 32, 38, 39, 59, 60, 62, 63, 64], "product": [2, 5, 6, 16, 20, 23, 34, 35, 36, 37, 39, 42, 45, 46, 50, 51, 54, 57, 61, 64, 65, 66], "function": [2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 20, 21, 22, 25, 26, 27, 29, 30, 32, 33, 34, 36, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 67, 69], "evalu": [2, 5, 13, 42, 50, 63], "specif": [2, 3, 5, 6, 8, 10, 13, 14, 15, 17, 20, 25, 29, 30, 34, 35, 37, 38, 39, 41, 42, 45, 48, 53, 55, 57, 59, 60, 62, 63, 65, 67, 68, 69], "i": [2, 5, 6, 7, 8, 9, 12, 13, 14, 15, 16, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 40, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 60, 62, 63, 65, 66, 69], "e": [2, 5, 7, 18, 19, 21, 22, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 40, 41, 42, 44, 45, 46, 47, 49, 50, 53, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "valu": [2, 3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 60, 62, 63, 65, 66, 68, 69], "earlier": [2, 5, 10, 21, 42, 45, 48, 52, 57, 59], "For": [2, 3, 5, 8, 10, 14, 16, 18, 20, 21, 22, 24, 27, 29, 30, 31, 34, 35, 36, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "specifi": [2, 4, 5, 8, 13, 21, 24, 27, 29, 30, 31, 34, 37, 38, 39, 42, 45, 46, 48, 50, 58, 66, 68, 69], "either": [2, 3, 4, 5, 20, 21, 22, 23, 24, 26, 27, 29, 35, 50, 59, 63, 65, 69], "maxim": [2, 3, 4, 5, 6, 8, 9, 10, 17, 18, 20, 23, 26, 29, 30, 31, 35, 37, 38, 39, 41, 46, 47, 48, 49, 55, 58, 60, 62, 63, 64, 68, 69], "minim": [2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 18, 20, 21, 22, 24, 25, 27, 29, 33, 34, 35, 37, 40, 42, 44, 45, 50, 52, 53, 55, 57, 64, 65, 66, 69], "In": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 18, 20, 21, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65, 66, 68, 69], "oper": [2, 3, 15, 21, 22, 27, 29, 35, 37, 39, 41, 42, 44, 45, 53, 59, 62, 63, 65, 66, 68], "cost": [2, 3, 4, 5, 6, 11, 12, 14, 15, 18, 20, 26, 28, 29, 30, 31, 33, 35, 37, 39, 41, 44, 45, 52, 53, 57, 59, 60, 63, 64, 65, 66, 68], "number": [2, 3, 4, 5, 8, 9, 10, 13, 16, 17, 18, 19, 20, 22, 24, 25, 27, 29, 31, 33, 35, 37, 38, 40, 42, 43, 44, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 69], "satisfi": [2, 3, 9, 15, 16, 18, 19, 20, 27, 29, 30, 31, 32, 34, 39, 42, 46, 47, 49, 57, 59, 62, 65], "custom": [2, 20, 21, 29, 32, 37, 39, 42, 51, 57, 62, 69], "restrict": [2, 16, 25, 30, 33, 35, 46, 49, 53, 55, 68, 69], "possibl": [2, 4, 5, 6, 9, 13, 15, 16, 17, 18, 19, 20, 21, 24, 27, 29, 30, 32, 33, 34, 35, 38, 39, 40, 42, 47, 50, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 68, 69], "condit": [2, 3, 8, 15, 18, 23, 24, 26, 27, 29, 30, 42, 44, 50, 55, 59, 64, 68, 69], "must": [2, 3, 5, 19, 21, 23, 26, 27, 29, 31, 32, 35, 38, 39, 44, 53, 63, 64, 65, 66, 68], "requir": [2, 3, 4, 8, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 37, 39, 45, 47, 52, 53, 57, 59, 62, 63, 64, 66, 68, 69], "maximum": [2, 3, 8, 11, 15, 18, 23, 24, 25, 29, 33, 34, 35, 39, 44, 47, 48, 49, 53, 55, 57, 63, 66, 68], "allow": [2, 4, 8, 18, 23, 24, 27, 29, 31, 32, 35, 41, 45, 48, 49, 53, 55, 57, 65, 68], "budget": [2, 12, 37, 52, 63], "demand": [2, 3, 4, 6, 18, 20, 26, 30, 32, 34, 35, 37, 39, 45, 51, 52, 57, 59, 63, 64, 65, 66, 68, 69], "import": [2, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 34, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 58, 59, 60, 63, 64, 69], "met": [2, 35, 57], "capac": [2, 12, 18, 23, 24, 30, 34, 35, 41, 52, 57, 62, 66, 69], "warehous": [2, 18, 45, 51, 60, 69], "exceed": [2, 29, 30, 39, 57], "both": [2, 4, 5, 8, 12, 13, 17, 20, 23, 24, 26, 27, 29, 33, 35, 39, 42, 45, 47, 50, 55, 61, 62, 63], "express": [2, 3, 4, 7, 8, 9, 10, 11, 12, 16, 18, 19, 22, 26, 29, 30, 32, 34, 35, 39, 41, 42, 44, 45, 46, 49, 50, 52, 55, 57, 60, 64, 65, 66, 68, 69], "defin": [2, 4, 5, 8, 9, 12, 13, 14, 16, 20, 22, 25, 26, 27, 32, 33, 35, 37, 39, 40, 41, 42, 45, 46, 50, 53, 55, 57, 62, 63, 65, 66, 68, 69], "feasibl": [2, 5, 8, 9, 17, 20, 30, 35, 37, 41, 44, 46, 47, 49, 53, 60, 63, 65, 66], "region": [2, 8, 20, 32, 35], "set": [2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 44, 45, 46, 47, 48, 49, 52, 53, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "candid": [2, 3, 7, 21, 37], "meet": [2, 3, 5, 12, 18, 22, 25, 29, 30, 32, 35, 37, 39, 43, 52, 57, 59, 65, 66], "best": [2, 5, 7, 8, 29, 30, 35, 44, 57, 63, 66, 69], "global": [2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 46, 48, 52, 55, 57, 60, 62, 66, 69], "optimum": [2, 41, 44], "among": [2, 3, 7, 11, 14, 15, 21, 22, 26, 31, 32, 33, 47, 48, 49, 62, 64, 65, 69], "appli": [2, 4, 5, 18, 24, 35, 37, 39, 42, 44, 45, 49, 65, 66, 68], "type": [2, 3, 4, 5, 6, 8, 12, 16, 17, 19, 21, 25, 29, 30, 35, 37, 42, 45, 50, 52, 55, 57, 65, 66, 68], "relat": [2, 5, 18, 23, 26, 29, 33, 39, 50, 55, 57, 62, 63, 65], "fundament": [2, 14, 39, 68], "question": [2, 8, 15, 22, 42, 45, 51, 59, 64, 65], "translat": [2, 4, 5, 18, 22, 29, 32, 37, 44], "real": [2, 4, 5, 7, 13, 16, 21, 30, 31, 35, 36, 37, 40, 46, 47, 49, 51, 53, 55, 57, 59, 62, 63, 65], "abstract": [2, 4, 8, 68], "represent": [2, 21, 42, 44, 50], "Not": [2, 29, 35], "aspect": [2, 6, 8, 14, 16, 28, 36, 43, 54, 56, 61], "taken": [2, 29, 33, 63, 65, 69], "account": [2, 10, 18, 23, 24, 29, 31, 35, 43, 46, 47, 55, 59, 60, 63, 65, 66, 68], "so": [2, 3, 4, 5, 8, 9, 13, 18, 21, 23, 24, 25, 27, 29, 30, 35, 36, 37, 38, 39, 40, 42, 44, 48, 50, 51, 53, 55, 57, 62, 63, 66, 68], "mani": [2, 3, 4, 8, 16, 19, 20, 22, 23, 27, 29, 30, 31, 33, 37, 42, 45, 46, 47, 49, 50, 52, 53, 55, 59, 62, 63, 65, 66, 69], "made": [2, 3, 10, 12, 18, 20, 24, 29, 52, 59, 63, 66], "step": [2, 3, 4, 8, 9, 12, 14, 15, 18, 21, 29, 45, 46, 52, 53, 62, 63, 68, 69], "typic": [2, 21, 35, 57, 59, 63, 68, 69], "signific": [2, 5, 8, 41, 45, 46, 47, 49, 50], "impact": [2, 7, 39, 51, 64], "approach": [2, 5, 7, 8, 10, 13, 14, 17, 19, 20, 22, 26, 27, 30, 33, 37, 39, 44, 46, 49, 57, 63, 65, 68], "There": [2, 5, 18, 19, 22, 25, 26, 29, 30, 35, 37, 39, 44, 45, 59, 63, 68, 69], "multipl": [2, 3, 12, 15, 18, 27, 29, 31, 32, 34, 37, 39, 69], "equival": [2, 5, 8, 18, 20, 22, 33, 42, 44, 45, 53, 55, 58, 62, 69], "formul": [2, 3, 4, 6, 8, 9, 11, 13, 14, 15, 16, 18, 22, 23, 26, 27, 28, 29, 30, 32, 35, 36, 39, 40, 44, 49, 51, 55, 57, 59, 60, 62, 65, 66, 69], "conceptu": 2, "same": [2, 3, 4, 5, 10, 11, 13, 14, 15, 18, 19, 21, 22, 25, 27, 29, 30, 31, 32, 33, 34, 40, 42, 45, 46, 50, 53, 55, 57, 60, 63, 65, 66, 68, 69], "comput": [2, 4, 5, 7, 8, 14, 15, 18, 22, 23, 29, 30, 31, 35, 37, 39, 42, 45, 46, 49, 50, 52, 59, 62, 64, 65, 66, 68, 69], "complex": [2, 4, 5, 15, 21, 22, 23, 29, 31, 37, 68, 69], "mai": [2, 3, 4, 5, 10, 11, 12, 15, 16, 17, 18, 20, 21, 23, 27, 29, 31, 32, 35, 37, 39, 41, 42, 45, 46, 50, 52, 55, 57, 58, 64, 68], "differ": [2, 3, 5, 8, 10, 11, 12, 13, 14, 15, 17, 18, 19, 27, 29, 30, 32, 33, 34, 35, 37, 39, 40, 41, 42, 44, 45, 48, 49, 50, 51, 53, 55, 57, 59, 60, 63, 64, 65, 66, 69], "interpret": [2, 4, 15, 33, 35, 41], "s": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 43, 44, 45, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "after": [2, 5, 13, 23, 29, 30, 31, 40, 47, 53, 55, 59, 63, 64, 65, 66, 68], "ha": [2, 3, 4, 5, 7, 10, 12, 14, 18, 21, 22, 24, 25, 26, 27, 29, 30, 31, 33, 35, 36, 37, 38, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 65, 66, 68], "back": [2, 5, 13, 23, 29, 31, 33, 42, 50, 63, 68], "origin": [2, 3, 4, 8, 9, 10, 13, 14, 17, 25, 27, 30, 35, 37, 39, 45, 48], "These": [2, 4, 15, 25, 27, 29, 34, 35, 39, 42, 45, 47, 49, 53, 57, 59, 62, 68, 69], "treat": [2, 21, 30, 51, 66], "continu": [2, 12, 18, 22, 23, 39, 42, 44, 50, 52, 60, 66], "process": [2, 4, 23, 29, 39, 41, 42, 45, 50, 53, 55, 68, 69], "sequenti": 2, "final": [2, 4, 5, 12, 14, 21, 22, 23, 29, 39, 45, 62, 65], "turn": [2, 3, 16, 21, 30, 36, 39, 42, 50, 53, 57, 66], "out": [2, 3, 23, 24, 27, 29, 30, 32, 36, 37, 39, 53, 57, 65, 66], "impract": [2, 29], "adjust": [2, 4, 14, 29, 35, 41, 57, 62, 65, 66], "certain": [2, 16, 29, 30, 32, 42, 45, 50, 55, 57, 62, 66], "desir": [2, 3, 12, 18, 25, 30, 36, 52, 68], "properti": [2, 8, 30, 36, 44, 46, 48, 49, 57], "cannot": [2, 8, 12, 16, 21, 22, 25, 29, 33, 35, 44, 52, 53, 60, 62, 63, 66], "effici": [2, 10, 14, 21, 27, 29, 30, 48, 49, 50, 55, 69], "perhap": [2, 19, 32, 37], "re": [2, 69], "includ": [2, 5, 6, 14, 16, 18, 19, 21, 22, 23, 24, 27, 28, 29, 31, 32, 36, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 53, 57, 58, 62, 63, 64, 65, 66, 67, 68, 69], "well": [2, 5, 7, 13, 14, 19, 22, 27, 29, 36, 37, 44, 46, 47, 60, 64, 69], "except": [2, 20, 25, 33, 66, 68, 69], "mathematician": 2, "studi": [2, 15, 21, 27, 37, 39, 44, 57, 60, 69], "alwai": [2, 4, 10, 12, 17, 24, 35, 38, 40, 42, 46, 47, 48, 50, 51, 55, 58, 62, 68], "flaw": 2, "challeng": [2, 8, 19, 27, 31, 37, 39, 42], "follow": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 45, 46, 47, 49, 50, 51, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "given": [2, 3, 4, 5, 7, 8, 9, 11, 13, 14, 15, 17, 18, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 35, 37, 39, 42, 44, 45, 46, 47, 49, 50, 51, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "f": [2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "x": [2, 4, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 18, 20, 23, 24, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 47, 48, 50, 52, 53, 55, 57, 58, 59, 60, 63, 64, 65, 66, 68, 69], "mathbb": [2, 6, 8, 13, 16, 17, 18, 26, 35, 37, 38, 40, 42, 45, 46, 47, 49, 50, 55, 57, 58, 59, 60, 62, 65, 66], "r": [2, 4, 6, 8, 13, 14, 16, 18, 19, 21, 22, 24, 25, 27, 29, 31, 32, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 58, 59, 60, 62, 63, 64, 65, 66, 68], "subseteq": [2, 16, 33, 35, 53], "n": [2, 6, 7, 8, 9, 13, 16, 17, 18, 19, 20, 21, 23, 24, 25, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 40, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 60, 62, 63, 69], "being": [2, 5, 6, 8, 33, 35, 38, 39, 50, 53, 66], "y": [2, 4, 7, 8, 9, 13, 14, 18, 19, 20, 23, 24, 26, 27, 29, 30, 31, 32, 34, 35, 38, 39, 40, 41, 42, 44, 45, 47, 48, 49, 50, 55, 57, 59, 60, 63, 64, 66, 68, 69], "geq": [2, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 60, 62, 63, 65, 66, 68], "foral": [2, 4, 7, 11, 12, 13, 14, 15, 18, 19, 20, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 45, 46, 48, 49, 50, 53, 55, 57, 59, 62, 63, 65, 66], "least": [2, 6, 7, 12, 18, 22, 24, 33, 35, 36, 37, 39, 52, 53, 63, 64], "good": [2, 4, 5, 7, 15, 20, 27, 29, 33, 34, 38, 46, 49, 59, 63, 64, 69], "similarli": [2, 8, 13, 18, 35, 40], "chang": [2, 4, 5, 10, 14, 15, 21, 23, 24, 27, 29, 30, 32, 33, 35, 38, 39, 40, 41, 48, 51, 53, 55, 57, 58, 62, 63, 65, 68, 69], "last": [2, 12, 18, 22, 23, 24, 29, 35, 38, 39, 52, 53, 55, 64, 66], "leq": [2, 3, 4, 8, 9, 10, 11, 12, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58, 59, 62, 63, 65, 66, 69], "case": [2, 3, 4, 5, 7, 8, 13, 16, 20, 21, 25, 26, 27, 29, 30, 32, 37, 40, 42, 46, 47, 49, 50, 55, 57, 59, 60, 66, 68, 69], "refer": [2, 3, 4, 6, 8, 13, 16, 20, 24, 27, 29, 32, 34, 39, 40, 42, 47, 50, 65, 69], "begin": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "align": [2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "min": [2, 6, 7, 8, 9, 11, 13, 14, 16, 18, 20, 22, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 39, 40, 42, 44, 45, 46, 50, 53, 55, 57, 59, 60, 63, 65, 66, 69], "quad": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 20, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 37, 38, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 58, 59, 60, 62, 63, 65, 68, 69], "text": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "t": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "end": [2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "lead": [2, 14, 17, 18, 19, 20, 21, 22, 26, 29, 36, 39, 42, 44, 50, 55, 57, 63, 66, 69], "techniqu": [2, 7, 11, 13, 21, 22, 23, 26, 32, 42, 45, 49, 57, 63, 65], "introductori": [2, 61], "present": [2, 4, 5, 7, 8, 13, 14, 24, 29, 31, 32, 35, 37, 39, 40, 41, 42, 46, 47, 48, 49, 50, 53, 62, 64, 66, 68, 69], "simpl": [2, 3, 4, 5, 12, 21, 26, 30, 31, 36, 37, 39, 41, 42, 45, 50, 55, 68, 69], "context": [2, 15, 25, 33, 34, 35, 58, 63, 66], "plan": [2, 4, 5, 10, 11, 15, 16, 18, 24, 25, 27, 39, 45, 51, 59, 61], "explain": [2, 7, 35, 39, 50, 57, 66], "structur": [2, 4, 8, 17, 26, 28, 30, 37, 44, 62, 63, 65, 66, 68, 69], "formal": [2, 16], "implement": [2, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 19, 22, 24, 27, 28, 29, 32, 35, 36, 37, 38, 39, 43, 44, 45, 46, 51, 54, 56, 57, 58, 59, 61, 62, 63, 68, 69], "second": [2, 4, 5, 10, 13, 18, 21, 27, 29, 31, 32, 33, 35, 37, 38, 39, 42, 50, 60, 61, 62, 63, 64, 65, 66], "also": [2, 3, 4, 5, 8, 11, 12, 14, 15, 18, 20, 22, 23, 25, 29, 30, 35, 36, 38, 39, 41, 42, 45, 53, 55, 58, 62, 63, 65, 66, 69], "serv": [2, 4, 5, 20, 34, 53, 63], "tutori": [2, 25, 37, 46, 47, 69], "lastli": [2, 3, 62, 63, 66], "discuss": [2, 32, 39, 42, 45, 50, 51, 63], "some": [2, 3, 4, 5, 7, 8, 13, 16, 21, 23, 27, 29, 30, 32, 33, 35, 39, 40, 41, 42, 44, 46, 47, 49, 50, 55, 57, 63, 65, 66, 68, 69], "advanc": [2, 3, 5, 23, 39, 45, 51, 63, 65, 66], "featur": [2, 4, 5, 6, 8, 13, 16, 20, 21, 22, 23, 27, 34, 39, 40, 47, 49, 60, 62, 68, 69], "third": [2, 4, 5, 32], "go": [2, 6, 8, 13, 14, 16, 21, 28, 30, 35, 36, 39, 40, 43, 51, 53, 54, 56, 63, 64, 65, 68], "next": [2, 3, 4, 5, 6, 7, 8, 12, 15, 16, 18, 21, 22, 23, 25, 28, 29, 30, 32, 34, 36, 38, 43, 46, 50, 51, 53, 54, 56, 57, 60, 64, 65, 66], "about": [2, 6, 8, 16, 20, 24, 28, 29, 30, 36, 39, 43, 51, 54, 56, 57, 59, 62, 63, 65], "linear": [2, 3, 5, 7, 8, 10, 11, 12, 13, 14, 15, 17, 19, 20, 22, 23, 26, 29, 31, 35, 36, 39, 40, 41, 55, 57, 60, 61, 62, 63, 65], "compani": [3, 6, 8, 12, 17, 18, 34, 39, 45, 51, 52, 53, 55, 63], "produc": [3, 4, 7, 8, 10, 12, 15, 17, 21, 23, 26, 29, 31, 32, 35, 37, 39, 42, 46, 47, 52, 53, 55, 57, 63, 65, 66, 68], "two": [3, 4, 5, 6, 8, 12, 13, 14, 16, 17, 19, 20, 21, 23, 25, 26, 29, 30, 31, 32, 33, 37, 39, 42, 45, 47, 50, 53, 55, 56, 57, 59, 60, 65, 68, 69], "version": [3, 4, 5, 10, 18, 20, 29, 30, 35, 39, 45, 53, 54, 55, 63, 65, 66, 69], "each": [3, 4, 5, 8, 9, 12, 13, 14, 18, 19, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 42, 46, 47, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "raw": [3, 5, 8, 12, 18, 26, 29, 35, 39, 42, 50, 52, 57, 63, 65, 66], "10": [3, 4, 5, 7, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "per": [3, 8, 10, 12, 14, 18, 23, 24, 25, 26, 29, 32, 34, 37, 44, 45, 52, 60, 63, 64, 65], "gram": [3, 18, 42, 50], "special": [3, 4, 11, 12, 13, 16, 28, 30, 37, 40, 45, 62, 69], "labor": [3, 4, 26, 63, 68], "finish": [3, 12, 18, 21, 22, 23, 26, 37, 52, 53, 69], "u": [3, 4, 5, 14, 18, 23, 29, 34, 42, 44, 45, 46, 49, 50, 53, 55, 57, 63, 68, 69], "higher": [3, 14, 26, 29, 39, 42, 47, 50, 52, 57, 59, 63, 65], "270": [3, 4, 5, 26, 29, 63, 66, 68], "unit": [3, 4, 5, 10, 12, 14, 15, 18, 23, 24, 26, 29, 31, 32, 34, 35, 39, 44, 45, 47, 52, 57, 58, 59, 60, 62, 63, 64, 65, 68], "one": [3, 4, 5, 6, 8, 9, 13, 14, 15, 17, 18, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 62, 63, 64, 65, 66], "hour": [3, 4, 21, 24, 25, 26, 53, 63], "b": [3, 4, 5, 6, 7, 8, 13, 15, 16, 18, 19, 21, 22, 25, 26, 29, 32, 34, 35, 37, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 60, 62, 63, 65, 66, 68, 69], "due": [3, 4, 12, 14, 18, 29, 35, 38, 39, 51, 52, 55, 59, 62, 64, 65, 69], "market": [3, 4, 14, 15, 29, 31, 39, 46, 47, 49, 62, 63, 64], "limit": [3, 5, 12, 18, 20, 21, 24, 25, 26, 29, 32, 35, 37, 39, 41, 44, 46, 49, 52, 57, 63, 65, 66, 69], "40": [3, 4, 5, 7, 24, 25, 26, 29, 32, 33, 37, 44, 45, 46, 59, 62, 63, 64, 68, 69], "week": [3, 25, 33, 62], "v": [3, 4, 5, 14, 20, 21, 24, 29, 30, 33, 34, 35, 39, 42, 45, 46, 50, 53, 57, 63, 65, 66, 68, 69], "lower": [3, 4, 5, 12, 14, 21, 29, 31, 32, 37, 39, 40, 55, 59, 62, 64, 65, 69], "unlimit": [3, 4, 26, 37, 39, 63], "210": [3, 4, 5, 26, 35, 62, 63, 64, 68], "9": [3, 4, 5, 7, 8, 9, 10, 11, 12, 14, 15, 17, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 41, 42, 45, 50, 51, 52, 53, 55, 62, 63, 66, 68], "1": [3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 33, 34, 37, 38, 40, 41, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 61, 63, 65, 66, 68, 69], "summar": [3, 4, 25, 32, 35, 39, 42, 50, 59, 62, 63, 64], "tabl": [3, 4, 18, 21, 22, 24, 26, 27, 31, 42, 46, 52, 53, 55, 59, 60, 62, 64, 69], "g": [3, 4, 5, 8, 14, 18, 20, 22, 27, 29, 30, 31, 32, 33, 34, 35, 39, 40, 42, 44, 45, 50, 53, 55, 60, 65, 66, 68], "hr": [3, 4, 24, 53], "2": [3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 33, 34, 37, 38, 40, 41, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 63, 65, 66, 68, 69], "weekli": [3, 25], "avail": [3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 41, 42, 45, 46, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 66, 68], "inventori": [3, 12, 18, 29, 45, 52, 59, 60], "shelf": 3, "life": [3, 22, 30, 36, 44, 53], "order": [3, 4, 10, 12, 18, 21, 22, 25, 30, 32, 35, 37, 41, 42, 43, 50, 52, 53, 59, 63], "left": [3, 7, 8, 9, 10, 12, 13, 21, 22, 23, 24, 25, 27, 30, 32, 37, 39, 40, 42, 44, 45, 47, 49, 50, 52, 53, 57, 60, 62, 63, 65], "over": [3, 4, 10, 11, 14, 18, 21, 23, 25, 29, 30, 35, 37, 39, 41, 42, 45, 47, 50, 52, 59, 62, 63, 64, 68, 69], "discard": 3, "detail": [3, 8, 20, 25, 42, 44, 50, 59], "resourc": [3, 4, 15, 21, 25, 27, 29, 30, 37, 52, 64, 65, 68], "amount": [3, 4, 12, 15, 16, 17, 18, 21, 22, 25, 29, 31, 32, 34, 38, 39, 51, 52, 55, 57, 58, 60, 63, 64, 65, 69], "80": [3, 4, 5, 26, 29, 32, 35, 41, 47, 49, 50, 63, 64, 66, 68], "50": [3, 4, 5, 9, 14, 18, 24, 26, 29, 31, 32, 35, 37, 39, 42, 44, 45, 52, 55, 60, 62, 63, 64, 66, 68, 69], "100": [3, 4, 5, 10, 18, 19, 20, 22, 24, 26, 29, 31, 32, 35, 37, 39, 41, 42, 45, 47, 49, 50, 52, 55, 57, 60, 62, 63, 64, 65, 66, 68, 69], "want": [3, 14, 17, 18, 20, 29, 32, 33, 38, 40, 42, 48, 55, 58, 62, 63, 69], "its": [3, 5, 7, 8, 9, 13, 14, 20, 22, 30, 34, 40, 42, 45, 50, 55, 63, 65, 68, 69], "gross": [3, 46, 47, 49], "profit": [3, 4, 5, 6, 8, 9, 10, 17, 23, 26, 29, 32, 37, 39, 41, 55, 62, 63, 64, 68, 69], "much": [3, 8, 12, 13, 17, 18, 23, 24, 27, 30, 33, 37, 44, 47, 51, 63, 65, 66], "abov": [3, 4, 6, 8, 11, 12, 13, 14, 17, 18, 22, 23, 24, 29, 30, 32, 33, 35, 37, 39, 40, 44, 45, 46, 48, 49, 50, 52, 55, 57, 60, 62, 63, 65, 69], "optim": [3, 4, 5, 9, 10, 11, 13, 17, 20, 21, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 40, 41, 45, 46, 52, 53, 55, 57, 59, 61, 67, 69], "reformul": [3, 5, 10, 13, 14, 44, 46, 47, 49, 50, 55, 62], "involv": [3, 5, 6, 8, 11, 21, 31, 39, 42, 45, 46, 47, 49], "few": [3, 4, 5, 32, 33, 42, 62, 68], "crucial": [3, 35], "element": [3, 4, 5, 8, 25, 30, 32, 42, 44, 47, 50, 65, 68, 69], "start": [3, 5, 7, 8, 13, 14, 18, 21, 22, 23, 24, 27, 29, 31, 33, 37, 49, 55, 62, 63], "point": [3, 4, 7, 8, 13, 16, 20, 23, 27, 29, 34, 39, 40, 41, 42, 45, 47, 50, 55, 60, 62, 66, 69], "list": [3, 4, 8, 14, 19, 21, 24, 25, 26, 29, 30, 31, 33, 35, 37, 42, 44, 46, 49, 50, 52, 53, 57, 60, 62, 63, 65, 68, 69], "relev": [3, 4, 18, 20, 27, 29, 66, 68, 69], "hand": [3, 4, 8, 9, 17, 20, 24, 25, 29, 30, 31, 42, 50, 55, 57, 59], "quantiti": [3, 8, 11, 12, 18, 34, 35, 37, 39, 43, 51, 52, 55, 63], "modifi": [3, 5, 17, 20, 21, 23, 29, 31, 42, 55, 57, 62, 65, 66, 68, 69], "achiev": [3, 11, 14, 23, 25, 38, 42, 50, 65, 68], "outcom": [3, 15, 32, 42, 46, 50, 57, 59, 63], "while": [3, 5, 8, 9, 12, 14, 17, 18, 20, 21, 24, 25, 26, 29, 33, 34, 35, 37, 42, 48, 49, 50, 51, 52, 53, 55, 57, 59, 62, 63, 65, 66], "stage": [3, 5, 27, 39, 46, 47, 60, 64, 65, 68, 69], "prove": [3, 8], "redund": [3, 69], "later": [3, 4, 5, 15, 21, 24, 27, 45, 47, 66, 69], "creat": [3, 12, 13, 14, 15, 19, 21, 22, 23, 27, 29, 30, 31, 33, 35, 37, 39, 42, 45, 46, 49, 50, 57, 59, 62, 63, 64, 68, 69], "comprehens": [3, 7, 42, 50], "below": [3, 5, 9, 11, 12, 14, 17, 20, 21, 24, 29, 30, 35, 37, 39, 42, 44, 45, 46, 50, 55, 57, 60, 62, 63, 66, 69], "symbol": [3, 14, 22, 29, 31, 32, 49, 59, 68, 69], "descript": [3, 15, 21, 32, 42, 51, 55, 66], "upper": [3, 4, 5, 9, 12, 14, 21, 22, 23, 24, 29, 32, 33, 37, 38, 39, 40, 44, 45, 52, 55, 60, 68, 69], "bound": [3, 4, 5, 9, 14, 19, 21, 22, 23, 24, 26, 29, 30, 31, 33, 37, 38, 39, 42, 44, 53, 55, 57, 63, 64, 66, 68], "known": [3, 4, 5, 7, 13, 14, 19, 21, 22, 23, 27, 33, 38, 39, 40, 42, 44, 45, 47, 49, 50, 53, 57, 59, 63, 64, 65, 66], "x_m": [3, 5, 60], "0": [3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "x_a": [3, 5], "x_b": [3, 5], "y_u": [3, 5], "y_v": [3, 5], "measur": [3, 7, 10, 14, 23, 24, 25, 29, 39, 42, 50, 51], "max": [3, 4, 7, 8, 9, 10, 11, 14, 15, 17, 21, 22, 23, 24, 25, 26, 27, 29, 35, 37, 38, 39, 41, 42, 44, 46, 47, 48, 50, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "equal": [3, 5, 6, 7, 8, 10, 12, 15, 16, 23, 25, 26, 27, 29, 30, 32, 33, 34, 38, 39, 40, 41, 44, 45, 46, 47, 49, 53, 55, 57, 59, 60, 62, 63, 65, 66], "between": [3, 4, 5, 8, 10, 13, 14, 20, 21, 24, 25, 27, 29, 31, 32, 34, 35, 36, 38, 39, 40, 42, 44, 46, 47, 48, 50, 53, 57, 64, 65, 66, 68, 69], "revenu": [3, 4, 5, 10, 11, 41, 59, 62, 64, 68], "written": [3, 4, 5, 15, 42, 45, 58, 59, 62, 68, 69], "As": [3, 4, 5, 8, 14, 18, 21, 25, 29, 30, 31, 39, 42, 45, 46, 50, 53, 59, 60, 63, 66, 69], "shown": [3, 5, 39, 42, 45, 46, 69], "here": [3, 4, 5, 10, 12, 13, 21, 22, 24, 25, 26, 29, 31, 39, 40, 42, 45, 46, 47, 49, 52, 53, 55, 57, 58, 59, 62, 63, 66, 68, 69], "algebra": [3, 5, 19, 41, 42, 45], "combin": [3, 4, 5, 18, 19, 29, 39, 44, 53, 57, 63, 65, 68, 69], "name": [3, 4, 5, 9, 10, 12, 13, 14, 15, 17, 18, 20, 21, 22, 24, 25, 29, 30, 32, 35, 37, 40, 41, 42, 48, 50, 59, 60, 62, 65, 66], "when": [3, 4, 5, 7, 8, 12, 13, 16, 20, 21, 22, 23, 24, 25, 29, 31, 32, 35, 39, 41, 42, 43, 45, 46, 47, 50, 57, 59, 60, 63, 64, 65, 66, 67, 68], "place": [3, 4, 29, 30, 31, 35, 39, 45, 46, 59, 68, 69], "break": [3, 4, 29, 33, 53, 57, 63, 66], "up": [3, 4, 5, 12, 16, 17, 18, 19, 21, 23, 29, 37, 42, 46, 47, 50, 52, 56, 57, 62, 63, 64], "longer": [3, 20, 21, 30, 45, 50, 53, 57, 62, 68], "smaller": [3, 4, 10, 16, 27, 51, 57], "simplifi": [3, 5, 24, 27, 50, 62, 68, 69], "relationship": [3, 5, 13, 22, 24, 25, 27, 29, 31, 44, 45, 46, 69], "inequ": [3, 6, 8, 9, 39, 47, 55, 65], "overal": [3, 8, 15, 25, 39, 44], "now": [3, 4, 5, 7, 8, 12, 14, 18, 20, 21, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 42, 45, 46, 47, 48, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68], "readi": [3, 29, 31, 45, 50, 63], "full": [3, 7, 13, 20, 23, 24, 32, 37, 39, 40, 42, 44, 49, 50, 55, 62, 63, 69], "canon": [3, 6, 38], "nonumb": [3, 4, 30], "textbook": [3, 20, 63, 64], "customari": [3, 8, 50], "under": [3, 14, 15, 18, 20, 25, 26, 52, 57, 59, 62, 63, 64, 68], "clearli": [3, 4, 7, 18, 20, 23, 25, 39, 53, 63, 66], "distinguish": [3, 29, 66, 69], "paramet": [3, 4, 5, 18, 21, 23, 29, 32, 33, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 50, 51, 55, 57, 59, 60, 62, 63, 65, 66, 68], "might": [3, 15, 16, 27, 29, 31, 33, 35, 36, 39, 42, 51, 59, 65, 68], "letter": [3, 19, 45, 63], "throughout": [3, 8, 29, 63, 69], "websit": 3, "howev": [3, 4, 8, 13, 15, 16, 17, 18, 20, 28, 29, 30, 31, 33, 35, 36, 39, 42, 44, 45, 48, 49, 50, 53, 55, 57, 59, 62, 63, 65, 66, 69], "stick": 3, "convent": [3, 5, 6, 8, 57, 65, 66], "onli": [3, 4, 7, 8, 9, 16, 18, 20, 21, 24, 25, 26, 27, 29, 30, 32, 33, 35, 37, 39, 42, 45, 49, 53, 55, 57, 59, 62, 63, 64, 65, 69], "explicitli": [3, 8, 17, 29, 30, 31, 50, 53, 62, 64, 69], "domain": [3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 48, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68], "vector": [3, 6, 8, 11, 12, 13, 35, 36, 38, 40, 41, 43, 58, 62, 63], "minimum": [3, 11, 12, 14, 16, 21, 24, 25, 28, 29, 33, 35, 37, 39, 44, 53, 62, 64], "even": [3, 5, 20, 25, 29, 30, 39, 42, 48, 50, 53, 62, 63, 65, 66], "like": [3, 4, 8, 9, 11, 12, 14, 18, 29, 30, 31, 32, 37, 39, 42, 50, 52, 62, 63, 65, 66], "immedi": [3, 21, 29], "clear": [3, 9, 17, 36, 57, 63, 69], "what": [3, 8, 15, 21, 22, 25, 29, 31, 39, 41, 43, 46, 47, 51, 55, 57, 59, 62, 63, 64, 66, 68], "exactli": [3, 14, 33, 34, 35, 45, 50, 51, 53, 55, 62, 63, 66], "where": [3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 15, 16, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 59, 60, 62, 63, 65, 66, 68, 69], "come": [3, 4, 14, 15, 30, 36, 42, 50, 63], "plai": [3, 8, 36, 46, 50, 53, 63], "thei": [3, 5, 8, 16, 18, 22, 24, 29, 30, 31, 32, 36, 37, 39, 42, 49, 51, 53, 57, 62, 63, 65, 66, 68, 69], "procedur": [3, 37, 55, 63], "long": [3, 4, 14, 16, 22, 25, 29, 46, 47, 60, 63, 69], "standard": [3, 5, 6, 8, 13, 14, 22, 29, 35, 39, 41, 42, 50, 58, 62, 69], "fashion": [3, 4, 53], "practition": [3, 49], "often": [3, 4, 16, 21, 28, 32, 35, 51, 63, 66, 69], "boil": 3, "down": [3, 17, 23, 29, 30, 35, 47, 62, 63, 64], "pass": [3, 4, 5, 18, 20, 21, 24, 28, 42, 50, 68], "softwar": [3, 26], "regardless": [3, 4, 8, 12, 18, 29, 46, 52, 60], "wa": [3, 7, 14, 25, 29, 30, 32, 35, 36, 37, 39, 45, 46, 47, 48, 49, 53, 55, 59, 63, 65], "stori": [3, 46, 47], "behind": 3, "To": [3, 5, 8, 18, 21, 22, 23, 24, 25, 27, 29, 30, 35, 37, 39, 42, 44, 45, 49, 50, 53, 55, 57, 59, 60, 62, 63, 65, 66, 68], "do": [3, 4, 8, 20, 23, 25, 29, 30, 31, 33, 35, 39, 41, 45, 53, 55, 57, 62, 63, 65, 66, 68, 69], "interfac": [3, 4, 5, 14, 45, 69], "commun": [3, 5, 7, 20, 25, 27, 64], "adopt": [3, 8, 26, 32, 42, 44, 47, 55], "python": [3, 5, 8, 13, 17, 20, 21, 25, 29, 30, 32, 37, 40, 41, 42, 45, 50, 53, 57, 66, 68, 69], "base": [3, 5, 7, 12, 13, 19, 21, 26, 29, 32, 35, 40, 41, 42, 47, 49, 50, 51, 52, 57, 63, 65, 68, 69], "carri": [3, 24, 35], "ll": [4, 31, 39], "revisit": [4, 16, 25, 43, 61], "time": [4, 5, 6, 8, 14, 18, 20, 23, 24, 25, 26, 27, 30, 31, 33, 35, 36, 37, 39, 40, 42, 45, 46, 49, 50, 51, 52, 53, 57, 59, 62, 63, 65, 66, 68, 69], "capabl": [4, 7, 26, 39, 55], "scale": [4, 7, 29, 30, 35, 37, 39, 42, 57, 60, 62, 63, 66], "enabl": [4, 5, 28, 29, 45, 50, 68], "vari": [4, 12, 38, 50, 52, 55, 57, 64], "addit": [4, 6, 7, 12, 15, 18, 21, 23, 25, 27, 29, 37, 42, 45, 47, 49, 50, 59, 62, 63, 66, 68, 69], "compon": [4, 5, 8, 13, 14, 18, 22, 26, 38, 45, 50, 58, 69], "index": [4, 5, 8, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 35, 37, 39, 40, 41, 42, 44, 45, 49, 50, 52, 53, 57, 59, 62, 64, 65, 68], "essenti": [4, 22, 29, 30, 37, 42, 50, 53, 55, 63], "scalabl": [4, 6], "maintain": [4, 5, 8, 27, 29, 45, 66, 69], "more": [4, 5, 8, 10, 11, 13, 14, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 31, 32, 35, 37, 38, 39, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68, 69], "analysi": [4, 7, 8, 12, 13, 21, 29, 32, 39, 42, 46, 47, 50, 51, 53, 55, 62, 69], "examin": [4, 7, 17, 39, 49], "identifi": [4, 5, 16, 18, 24, 27, 29, 31, 34, 37, 39, 42, 44, 45, 47, 50, 62, 66, 69], "underli": [4, 40, 63], "verifi": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 50, 52, 53, 55, 57, 59, 60, 62, 66], "high": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 39, 42, 44, 49, 50, 52, 55, 57, 59, 60, 63, 65, 66, 69], "via": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 50, 51, 55, 57, 60, 66], "appsi": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 52, 55, 60, 66], "modul": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "elsewher": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 38, 48, 52, 55, 57, 60, 66, 69], "assum": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 42, 44, 45, 48, 49, 50, 51, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "cbc": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 37, 39, 41, 42, 52, 53, 55, 59, 60, 62, 63, 64, 65, 66, 68], "been": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39, 42, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 64, 66, 68, 69], "previous": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 35, 38, 47, 48, 50, 52, 53, 55, 57, 60, 62, 65, 66, 68, 69], "solverfactori": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "It": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, 35, 38, 45, 48, 52, 55, 57, 60, 63, 65, 66], "sy": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "pip": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "dev": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66], "null": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66], "highspi": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 41, 52, 53, 55, 59, 60, 62, 63, 64, 65, 66], "environ": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "appsi_high": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 41, 53, 55, 59, 60, 62, 63, 64, 65, 66], "els": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 31, 33, 34, 35, 38, 42, 44, 45, 47, 48, 49, 50, 52, 53, 55, 60, 62, 63, 65, 66, 68, 69], "assert": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60], "basic": [4, 16, 17, 21, 27, 42, 55, 65, 68, 69], "previou": [4, 9, 12, 15, 18, 28, 29, 35, 42, 45, 50, 51, 63], "were": [4, 18, 27, 30, 35, 42, 49, 62, 65], "distinct": [4, 22, 29], "evid": [4, 20], "compris": [4, 21, 23, 25, 31, 37, 40, 59, 68, 69], "abbrevi": [4, 29, 68], "m": [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "factor": [4, 7, 20, 42, 44, 48, 50, 55, 62, 65, 69], "attribut": [4, 5, 7, 14, 29, 35, 37, 45, 65, 68, 69], "built": [4, 20, 57], "librari": [4, 5, 8, 13, 21, 29, 30, 32, 33, 35, 40, 41, 44, 45, 47, 49, 50, 69], "handl": [4, 23, 26, 35, 45, 68], "tabular": [4, 5], "sever": [4, 5, 6, 7, 11, 16, 19, 24, 26, 28, 29, 36, 37, 39, 42, 49, 57, 69], "option": [4, 5, 14, 21, 27, 29, 33, 35, 41, 42, 50, 63, 65, 68, 69], "would": [4, 7, 8, 12, 15, 17, 18, 19, 21, 25, 26, 29, 31, 32, 33, 35, 39, 42, 45, 48, 49, 50, 52, 53, 55, 57, 59, 62, 63, 64, 65, 66, 68], "appropri": [4, 5, 42, 50], "task": [4, 16, 20, 24, 29, 30, 32, 37, 42, 53], "nest": [4, 37, 63, 68, 69], "dictionari": [4, 18, 21, 29, 34, 35, 37, 42, 45, 50, 53, 57, 63, 69], "column": [4, 5, 7, 12, 14, 15, 18, 20, 22, 24, 25, 29, 30, 31, 32, 35, 39, 42, 45, 49, 50, 52, 53, 62, 64, 66, 69], "show": [4, 5, 7, 9, 12, 13, 14, 18, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 40, 42, 44, 45, 47, 48, 49, 51, 52, 53, 55, 57, 59, 60, 62, 63, 66, 68, 69], "repres": [4, 6, 8, 18, 19, 22, 23, 25, 31, 33, 34, 35, 37, 39, 42, 44, 45, 46, 47, 49, 50, 57, 59, 68, 69], "kei": [4, 5, 8, 14, 20, 21, 29, 32, 33, 34, 35, 37, 40, 46, 49, 52, 53, 57, 59, 60, 63, 65, 66, 68, 69], "outermost": 4, "inner": [4, 42, 50], "float": [4, 30, 42, 50, 52, 60, 69], "none": [4, 5, 7, 20, 21, 27, 29, 30, 32, 34, 35, 40, 42, 45, 47, 50, 52, 57, 66, 68], "print": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 22, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "item": [4, 21, 30, 32, 34, 35, 37, 50, 53, 57, 59, 60, 65, 66, 69], "consum": [4, 21, 35, 57, 65, 69], "8s": [4, 29, 49], "row": [4, 5, 7, 8, 22, 29, 31, 35, 42, 53, 63, 66, 69], "label": [4, 7, 13, 15, 24, 27, 29, 31, 32, 33, 34, 35, 37, 39, 40, 41, 42, 44, 45, 50, 52, 53, 57, 60, 66, 69], "4s": 4, "By": [4, 5, 7, 14, 30, 31, 32, 55, 69], "rearrang": [4, 42], "straightforward": [4, 18, 55, 69], "becom": [4, 8, 9, 14, 19, 20, 22, 25, 38, 39, 41, 42, 45, 47, 49, 50, 57, 58, 59, 60, 65, 66], "collect": [4, 5, 6, 7, 11, 13, 15, 20, 21, 27, 31, 32, 33, 35, 40, 42, 50, 62, 63, 69], "compar": [4, 7, 8, 13, 14, 19, 20, 22, 30, 37, 39, 40, 42, 45, 47, 50, 59, 60, 62, 64, 66], "adapt": [4, 15, 49, 57, 62, 63, 65], "let": [4, 7, 8, 9, 11, 12, 15, 19, 20, 21, 25, 27, 29, 30, 33, 34, 35, 37, 38, 39, 44, 45, 47, 50, 52, 55, 57, 58, 59, 62, 63, 65, 68], "cal": [4, 50], "p": [4, 11, 12, 18, 23, 24, 26, 33, 35, 37, 39, 41, 42, 44, 46, 47, 49, 50, 52, 53, 57, 58, 60, 62, 65, 66, 68], "respect": [4, 5, 8, 14, 18, 21, 26, 27, 29, 30, 32, 34, 35, 37, 39, 42, 46, 55, 57, 62, 63, 64, 66, 68], "x_r": [4, 39], "y_p": 4, "denot": [4, 8, 12, 15, 18, 19, 21, 23, 26, 27, 29, 30, 31, 35, 37, 39, 40, 49, 53, 57, 62, 65, 69], "constrain": [4, 12, 15, 16, 29, 35, 39, 45, 46, 49], "zero": [4, 13, 19, 29, 35, 37, 40, 41, 42, 44, 45, 50, 52, 60, 63, 65, 66], "b_r": 4, "b_p": 4, "b_q": 4, "don": [4, 8, 29, 57, 66, 69], "insert": [4, 5, 32, 45, 47], "larger": [4, 8, 20, 27, 30, 33, 37, 42, 47, 50, 53, 59], "than": [4, 5, 8, 10, 12, 15, 16, 17, 20, 21, 23, 24, 25, 27, 29, 30, 32, 33, 35, 37, 39, 42, 46, 47, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 65], "ever": [4, 42, 50], "design": [4, 5, 14, 19, 22, 27, 32, 39, 40, 42, 43, 66, 68], "caus": [4, 5, 39, 68], "ignor": [4, 35, 42, 50, 57], "befor": [4, 13, 20, 21, 22, 30, 33, 39, 40, 42, 46, 53, 57, 59, 60, 62, 63, 65, 66], "sum_": [4, 7, 12, 13, 14, 15, 18, 20, 23, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 57, 58, 59, 62, 63, 65, 66, 69], "c_p": 4, "c_r": 4, "a_": [4, 15, 25, 29, 31, 37], "put": [4, 42, 59, 63, 65], "piec": [4, 21, 37], "flexibl": [4, 32, 35, 36, 63, 68], "particular": [4, 14, 16, 21, 25, 30, 33, 35, 37, 39, 40, 45, 55, 62, 63, 65, 66, 69], "hold": [4, 5, 8, 9, 12, 14, 16, 18, 24, 27, 29, 35, 45, 52, 57, 59, 60, 62, 63, 65, 66], "scienc": [4, 5, 25, 32, 44, 45, 46, 62, 64], "see": [4, 5, 20, 21, 25, 26, 30, 31, 40, 44, 45, 46, 48, 50, 55, 57, 60, 63, 64, 65, 66, 68], "facilit": [4, 8, 14, 69], "construct": [4, 5, 7, 9, 14, 18, 21, 29, 32, 37, 42, 44, 45, 50, 53, 65, 66, 68, 69], "pyo": [4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "initi": [4, 7, 8, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 35, 37, 38, 39, 40, 41, 42, 46, 48, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "assign": [4, 5, 15, 16, 19, 22, 24, 25, 29, 30, 31, 32, 33, 37, 41, 42, 50, 51, 66], "decor": [4, 5, 8, 9, 25, 32, 35, 62], "declar": [4, 5, 35, 65, 66, 69], "return": [4, 5, 7, 8, 9, 10, 11, 12, 13, 15, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68, 69], "form": [4, 6, 22, 23, 36, 44, 45, 51, 58, 60, 63, 65, 68], "param": [4, 7, 12, 14, 15, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 39, 42, 52, 57, 60, 65, 68, 69], "omit": [4, 69], "emb": 4, "extern": [4, 21, 44, 55], "directli": [4, 5, 7, 14, 22, 23, 32, 35, 44, 45, 50, 59], "effect": [4, 5, 21, 23, 34, 44, 46, 47, 53, 68], "doe": [4, 5, 15, 21, 23, 25, 27, 29, 30, 35, 37, 40, 42, 45, 50, 55, 62, 66], "keep": [4, 12, 18, 25, 33, 35, 39, 50, 53, 63, 65, 69], "shorter": 4, "remov": [4, 6, 8, 15, 29, 37, 42, 53], "overhead": 4, "blur": [4, 29], "boundari": [4, 27, 69], "statement": [4, 30, 32, 62], "edit": [4, 37, 46], "locat": [4, 16, 24, 29, 32, 34, 39, 41, 42, 57, 59, 69], "portion": [4, 49], "therebi": 4, "significantli": [4, 8, 27, 30, 39, 42, 50], "improv": [4, 5, 25, 42, 44, 45, 47, 64], "maintainabi": 4, "concern": [4, 30], "overkil": 4, "small": [4, 5, 8, 12, 25, 26, 29, 30, 31, 33, 34, 37, 39, 41, 63, 65, 69], "consider": [4, 14, 15, 21, 25, 32, 42, 59, 69], "note": [4, 5, 9, 11, 12, 13, 14, 15, 17, 18, 20, 24, 25, 29, 32, 33, 34, 35, 37, 40, 41, 42, 48, 55, 57, 60, 62, 66, 68, 69], "becaus": [4, 8, 11, 18, 21, 25, 27, 29, 30, 32, 35, 37, 39, 42, 45, 50, 53, 55, 57, 63, 65, 68, 69], "take": [4, 5, 7, 8, 9, 11, 16, 17, 18, 21, 22, 23, 24, 27, 29, 31, 33, 35, 38, 39, 42, 45, 47, 48, 50, 51, 53, 55, 57, 58, 59, 60, 62, 63, 65, 66, 68], "logic": [4, 5, 8, 12, 17, 18, 19, 22, 26, 29, 52, 55, 69], "def": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "coeffici": [4, 6, 7, 8, 13, 15, 17, 18, 29, 40, 42, 44, 50, 55, 62, 63], "cp": [4, 41], "cr": 4, "argumentn": 4, "var": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 48, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "fix": [4, 5, 6, 7, 12, 14, 24, 25, 27, 30, 32, 35, 39, 40, 44, 45, 46, 47, 49, 57, 60, 62, 63, 64, 65, 66, 68], "done": [4, 5, 21, 22, 29, 39, 42, 59, 63], "parlanc": 4, "sometim": [4, 36, 46, 58], "call": [4, 8, 24, 27, 29, 31, 32, 35, 38, 39, 40, 42, 48, 49, 50, 53, 59, 62, 66, 68], "rule": [4, 12, 29, 39, 45, 60, 61, 63, 65, 69], "lambda": [4, 18, 19, 20, 21, 22, 25, 27, 29, 31, 35, 39, 42, 44, 46, 47, 49, 50, 52, 53, 55, 57, 60, 65, 66, 68, 69], "argument": [4, 5, 18, 33, 35, 42, 50, 55, 62, 63, 65, 68, 69], "member": [4, 30, 32], "tupl": [4, 5, 8, 21, 25, 29, 37, 68], "quicksum": [4, 12, 18, 30, 33, 52, 55], "accept": [4, 5, 21, 22, 29, 32, 35, 42, 46, 49, 57, 63, 69], "success": [4, 7, 47, 68, 69], "sum": [4, 7, 8, 9, 13, 14, 15, 19, 20, 21, 22, 23, 25, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "sens": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 46, 47, 48, 49, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68, 69], "Then": [4, 22, 33, 34, 35, 42, 50, 53, 55, 62, 65, 66, 68], "associ": [4, 21, 24, 26, 32, 34, 35, 37, 40, 68, 69], "manner": [4, 32], "block": [4, 25, 37, 39, 44, 45, 46, 47, 49, 50, 55, 63, 68], "materials_us": [4, 68], "report": [4, 14, 18, 29, 30, 35, 37, 39, 42, 50, 52, 55, 57, 60, 62, 68, 69], "access": [4, 21, 32, 35, 45, 57, 68], "iter": [4, 5, 18, 29, 35, 55, 63, 68, 69], "pprint": [4, 69], "nproduct": 4, "nresourc": 4, "3": [4, 7, 11, 12, 14, 15, 18, 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 33, 34, 35, 37, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 58, 59, 60, 63, 66, 69], "size": [4, 5, 7, 12, 13, 14, 22, 24, 25, 27, 29, 32, 37, 38, 40, 42, 45, 47, 48, 49, 50, 52, 53, 55, 57, 59, 60, 62, 69], "dimen": [4, 21, 32, 33], "a_index": 4, "true": [4, 5, 7, 12, 13, 14, 15, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 39, 40, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66, 68, 69], "6": [4, 7, 9, 10, 12, 14, 18, 19, 20, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 41, 42, 44, 45, 46, 49, 50, 52, 53, 55, 57, 58, 59, 63, 64, 66], "5": [4, 7, 9, 10, 12, 14, 18, 19, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 48, 49, 50, 52, 53, 55, 58, 63, 65, 66, 68, 69], "default": [4, 5, 8, 14, 21, 24, 25, 32, 33, 35, 39, 42, 50, 66, 69], "mutabl": [4, 14, 25, 27, 32, 57, 60, 69], "fals": [4, 5, 8, 14, 20, 21, 22, 25, 26, 30, 32, 33, 35, 37, 40, 42, 45, 50, 52, 53, 55, 57, 60, 62, 63, 65, 66, 68], "stale": [4, 5, 32, 40], "activ": [4, 5, 25, 26, 29, 32, 35, 55, 66], "bodi": [4, 5, 32, 50], "inf": [4, 5, 63], "12": [4, 5, 7, 8, 9, 10, 11, 12, 14, 15, 17, 18, 20, 21, 23, 24, 25, 27, 29, 30, 31, 32, 35, 37, 38, 42, 45, 47, 48, 50, 53, 55, 59, 62, 63, 69], "2600": [4, 5, 26, 63], "20": [4, 5, 7, 14, 18, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 33, 37, 38, 42, 44, 45, 46, 48, 49, 53, 55, 57, 62, 63, 64, 66, 68, 69], "60": [4, 5, 7, 24, 26, 29, 35, 49, 59, 64, 65, 66, 68], "740": [4, 5, 55, 63, 68], "experienc": [4, 7], "class": [4, 5, 6, 8, 11, 22, 25, 27, 28, 30, 42, 50, 62, 68, 69], "extend": [4, 14, 27, 39, 42, 46, 49, 66, 68, 69], "productionmodel": 4, "inherit": 4, "method": [4, 5, 13, 14, 22, 23, 26, 28, 29, 37, 42, 44, 50, 63, 65, 68, 69], "displai": [4, 5, 7, 8, 12, 13, 14, 15, 18, 22, 24, 25, 27, 29, 30, 34, 37, 38, 39, 40, 41, 42, 44, 45, 48, 50, 52, 53, 58, 59, 62, 63, 64, 65, 68], "__init__": [4, 35, 42, 50, 68], "self": [4, 35, 42, 50, 68], "instanc": [4, 5, 8, 12, 20, 30, 34, 37, 42, 47, 50, 57, 59, 66, 68, 69], "contain": [4, 5, 13, 20, 25, 26, 29, 35, 37, 40, 42, 50, 55, 57, 66, 68, 69], "inform": [4, 14, 15, 20, 21, 22, 25, 29, 32, 37, 47, 52, 57, 63, 64], "super": 4, "save": [4, 29, 32, 44, 55], "flag": [4, 21, 63, 68], "monitor": [4, 29], "statu": [4, 20, 30, 38, 48, 55, 58, 60, 68], "build_model": [4, 69], "buildth": 4, "integr": [5, 17, 41, 53, 67, 68, 69], "program": [5, 7, 15, 19, 23, 27, 37, 43, 45, 46, 49, 50, 62, 64, 67, 69], "user": [5, 30, 31, 35, 41, 42, 50, 64, 69], "varieti": [5, 35], "project": [5, 39, 42, 45, 50, 67, 69], "ti": 5, "vendor": 5, "constantli": 5, "evolv": 5, "through": [5, 13, 21, 29, 32, 34, 35, 42, 44, 53, 57, 65, 68], "contribut": [5, 7, 14, 19], "parti": [5, 29, 32], "direct": [5, 9, 13, 27, 31, 32, 34, 35, 37, 45, 53, 55], "simplic": [5, 33, 35], "reus": [5, 18, 21], "anoth": [5, 11, 12, 16, 18, 19, 21, 22, 29, 31, 38, 41, 42, 50, 53, 55, 58, 66], "write": [5, 21, 29, 31, 32, 35, 39, 55, 62, 67, 69], "driven": [5, 51], "unfamiliar": [5, 69], "current": [5, 8, 15, 24, 26, 29, 32, 39, 46, 51, 55, 63, 66, 68], "offer": [5, 8, 18, 20, 29, 31, 32, 46, 47, 57, 63, 69], "readabl": [5, 8, 25, 32], "rel": [5, 8, 24, 25, 26, 29, 31, 48, 63, 68], "recent": [5, 29, 35, 37, 39, 44, 46, 47, 49, 69], "intend": [5, 25, 69], "cloud": 5, "person": [5, 7, 21, 45], "session": [5, 20], "mix": [5, 6, 17, 23, 26, 36, 37, 39, 55, 57], "integ": [5, 6, 7, 12, 17, 18, 19, 20, 23, 26, 30, 36, 37, 39, 57, 59, 62, 69], "coin": 5, "OR": [5, 21, 23, 27, 45], "branch": 5, "cut": [5, 20, 23, 26, 27, 36, 45, 57], "suitabl": [5, 22, 33, 42, 50, 68], "glpk": 5, "cplex": [5, 20, 55], "gurobi": [5, 20, 30, 45, 55], "mosek": [5, 38, 45, 47, 48, 49, 50, 57], "check": [5, 8, 29, 31, 38, 39, 45, 48, 50, 51, 55, 58, 65, 66, 68, 69], "quiet": 5, "test": [5, 19, 21, 29, 35, 37, 39, 42, 49, 50, 68, 69], "store": [5, 18, 21, 22, 29, 30, 32, 35, 42, 45, 50, 52, 59, 60, 63, 65, 66, 68, 69], "commonli": [5, 14, 26, 39, 42, 50, 69], "prefix": [5, 35], "short": [5, 14, 21, 29, 31, 35, 38, 39, 45, 49, 57, 68], "sinc": [5, 8, 9, 18, 20, 24, 25, 27, 30, 33, 35, 37, 40, 42, 44, 45, 48, 50, 51, 55, 57, 60, 62, 63, 65, 66], "string": [5, 29, 32, 42, 50, 68], "subsequ": [5, 7, 13, 14, 21, 29, 35, 37, 39, 40, 53, 59, 62, 69], "altern": [5, 7, 8, 10, 13, 15, 26, 32, 33, 47, 50, 66, 69], "abstractmodel": 5, "But": [5, 15, 21, 32, 37, 39, 42, 50, 66], "normal": [5, 14, 29, 31, 39, 42, 46, 49, 50, 53, 58, 62, 69], "content": [5, 29, 35, 39, 45, 46, 47], "At": [5, 12, 21, 24, 25, 27, 31, 47, 52, 64], "major": [5, 32], "empti": 5, "valid": [5, 42, 47, 50, 69], "dot": [5, 7, 8, 12, 13, 14, 15, 16, 18, 23, 29, 32, 33, 38, 40, 42, 44, 45, 47, 48, 50, 52, 57, 58, 62, 65], "notat": [5, 19, 29, 31, 42, 63, 65], "chosen": [5, 38], "reflect": [5, 10], "keyword": [5, 42, 50, 69], "nonnegativer": [5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 22, 24, 26, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 48, 52, 55, 57, 58, 60, 63, 65, 66, 68, 69], "nonnegativeinteg": [5, 17, 18, 30, 37, 55, 59, 62], "binari": [5, 16, 19, 20, 22, 23, 25, 26, 27, 30, 33, 35, 36, 37, 39, 44, 50, 53, 57, 61, 62, 63, 66], "placehold": [5, 30], "unknown": [5, 38, 39, 42, 58, 60, 63, 65], "yet": [5, 29, 55], "updat": [5, 21, 22, 24, 29, 35, 38, 41, 42, 45, 48, 50, 51, 52, 55], "formula": [5, 42, 46, 47, 60], "could": [5, 8, 14, 15, 16, 17, 21, 23, 29, 30, 31, 37, 38, 39, 45, 48, 55, 57, 59, 62, 63, 64, 66, 69], "expr": [5, 8, 9, 10, 11, 17, 39, 50, 55, 60, 63, 65, 69], "releas": [5, 22, 53], "With": [5, 12, 18, 26, 29, 39, 47, 50, 63, 66], "behavior": [5, 39, 49], "line": [5, 8, 13, 14, 20, 22, 29, 35, 41, 44, 60, 66, 69], "add": [5, 8, 11, 12, 20, 21, 22, 23, 25, 29, 30, 31, 32, 37, 39, 41, 42, 46, 47, 53, 55, 57, 60, 62, 63, 69], "tag": [5, 53, 69], "syntax": [5, 45, 55, 69], "error": [5, 13, 19, 29, 33, 35, 40, 51, 57, 66, 68, 69], "numer": [5, 13, 29, 36, 41, 45, 48, 50, 60, 69], "core": [5, 20, 21, 55, 57, 66, 69], "scalarvar": 5, "No": [5, 23, 25, 37, 55, 59, 63], "uniniti": 5, "numericvalu": 5, "scalarobject": 5, "separ": [5, 20, 21, 29, 35, 36, 39, 42, 44, 50, 57, 65, 66, 69], "less": [5, 20, 21, 25, 27, 29, 46, 49, 50, 57, 63, 69], "greater": [5, 15, 17, 25, 49], "raw_materi": 5, "labor_a": [5, 69], "labor_b": [5, 69], "output": [5, 18, 20, 35, 42, 50, 53, 65, 66, 68], "whenev": [5, 21, 25, 33, 63], "fulli": [5, 8, 30, 55, 57], "tee": [5, 8], "debug": 5, "aris": [5, 31, 39], "result": [5, 7, 8, 14, 15, 18, 20, 23, 24, 25, 29, 30, 31, 33, 35, 37, 38, 39, 42, 45, 46, 47, 48, 49, 50, 52, 55, 57, 58, 59, 62, 63, 64, 65, 66, 68, 69], "milp": [5, 53], "date": [5, 13, 14, 18, 25, 26, 49], "apr": [5, 12, 18, 52], "2023": [5, 18, 20, 23, 24, 25, 26, 27, 29, 30, 57], "command": [5, 29, 45], "opt": [5, 29, 31, 44, 45], "homebrew": 5, "bin": [5, 7, 13, 14, 29, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 62, 63], "printingopt": 5, "folder": 5, "zb": [5, 29], "k0pc77yj6c3gv6gr6jj41g1r0000gn": 5, "tmp2_hwem4f": 5, "lp": [5, 7, 11, 15, 42, 53], "stat": [5, 14, 46, 49, 57, 58, 60, 62], "solu": 5, "soln": [5, 27, 30, 68], "strategi": [5, 14, 16, 17, 19, 22, 26, 29, 31, 33, 34, 46, 49, 59, 62], "coinlpio": 5, "readlp": 5, "coin0009i": 5, "switch": [5, 66], "get": [5, 12, 13, 17, 18, 20, 21, 29, 30, 34, 35, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 63, 68], "correct": [5, 42, 45, 62], "dual": [5, 6, 32, 41, 55], "etc": [5, 18], "presolv": [5, 20], "statist": [5, 7, 13, 40, 42, 49, 50], "singleton": 5, "breakdown": 5, "lo": [5, 6, 9, 14, 16, 17, 28, 39], "free": [5, 7, 29, 33, 38, 45, 58, 63], "l": [5, 8, 19, 29, 37, 39, 42, 44, 45, 46, 48, 49, 63, 69], "obj": [5, 9, 20, 35], "480": [5, 12, 18, 52], "002": [5, 14, 45], "total": [5, 7, 8, 12, 14, 18, 21, 22, 23, 25, 27, 29, 30, 35, 37, 38, 39, 42, 44, 45, 49, 50, 52, 55, 57, 62, 65, 66, 69], "cpu": [5, 30], "00": [5, 7, 9, 10, 11, 12, 20, 25, 26, 29, 31, 32, 35, 37, 39, 46, 49, 52, 55, 60, 62, 63, 64], "wallclock": 5, "format": [5, 8, 10, 17, 21, 23, 35, 45, 52], "graphic": [5, 37, 41, 44, 60], "overview": [5, 31, 39], "visual": [5, 8, 12, 14, 18, 20, 22, 24, 30, 32, 34, 35, 42, 55], "appendix": 5, "entir": [5, 8, 32, 34, 35, 62], "individu": [5, 14, 21, 25, 29, 30, 32, 39, 55, 57, 69], "whole": [5, 44, 62], "successfulli": [5, 7, 20, 35, 39, 42], "conveni": [5, 13, 22, 25, 32, 65, 68], "2f": [5, 9, 10, 11, 13, 18, 20, 26, 29, 31, 32, 33, 35, 38, 39, 45, 46, 48, 49, 52, 55, 58, 60, 62, 63, 64, 65, 66], "18000": [5, 32, 64], "15400": 5, "shortcut": 5, "wide": [5, 27, 29, 35], "seri": [5, 7, 8, 14, 15, 21, 32, 42, 45, 49, 50, 52, 62, 64, 68], "matplotlib": [5, 7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66], "bar": [5, 7, 13, 14, 15, 22, 23, 29, 32, 39, 40, 42, 45, 50, 55, 60, 63, 65], "chart": [5, 14, 25, 29, 32, 45, 57, 62], "pd": [5, 7, 12, 14, 15, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 32, 35, 37, 39, 41, 42, 44, 45, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "dtype": [5, 15, 35, 50, 60, 62, 68], "float64": [5, 15, 50, 62, 68], "pyplot": [5, 7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66], "plt": [5, 7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 65, 66], "1x2": 5, "grid": [5, 7, 12, 13, 14, 15, 18, 21, 24, 29, 35, 39, 40, 44, 45, 46, 47, 49, 52, 64, 66, 68], "subplot": [5, 7, 13, 14, 20, 21, 22, 23, 24, 25, 27, 29, 32, 34, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 57, 60, 62, 63], "configur": [5, 27, 62, 65], "fig": [5, 7, 13, 14, 21, 22, 23, 24, 25, 27, 29, 32, 34, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 60, 62, 63], "ax": [5, 7, 12, 13, 14, 15, 19, 20, 21, 22, 23, 24, 25, 27, 29, 32, 34, 35, 37, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 60, 62, 63, 64, 68], "figsiz": [5, 7, 12, 14, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 32, 34, 35, 37, 39, 41, 42, 44, 45, 46, 47, 49, 50, 52, 53, 57, 60, 62, 63], "rcparam": [5, 7, 12, 13, 14, 22, 24, 25, 30, 38, 45, 48, 52, 55], "font": [5, 7, 12, 13, 14, 22, 24, 25, 38, 45, 48, 52, 55], "color": [5, 7, 8, 12, 13, 14, 15, 21, 22, 23, 24, 25, 27, 28, 29, 32, 34, 35, 37, 38, 39, 40, 41, 42, 46, 47, 48, 50, 52, 53, 55, 57, 60], "cm": [5, 21, 25, 38, 48, 52], "tab20c": [5, 7, 12, 25, 38, 48, 52], "color_set": 5, "16": [5, 7, 18, 22, 24, 25, 26, 29, 30, 37, 38, 44, 45, 48, 49, 50, 53, 62, 64, 65, 66], "dataset": [5, 7, 13, 29, 40, 42, 50, 57], "plot": [5, 7, 12, 13, 14, 15, 18, 20, 21, 22, 24, 29, 30, 32, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 62, 63, 64, 66, 68], "enumer": [5, 9, 14, 20, 21, 22, 25, 29, 37, 50, 60, 62], "zip": [5, 7, 12, 14, 18, 21, 27, 29, 30, 33, 52, 57], "kind": [5, 7, 15, 29, 32, 35, 37, 42, 45, 50, 62, 63], "barh": [5, 14, 62], "alpha": [5, 7, 13, 18, 21, 22, 24, 25, 26, 27, 32, 34, 37, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 57, 58, 60, 62, 63, 65], "set_xlabel": [5, 7, 12, 13, 14, 21, 22, 23, 24, 25, 27, 29, 39, 41, 44, 45, 46, 47, 49, 52, 62, 63], "invert_yaxi": 5, "tight_layout": [5, 7, 12, 13, 14, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 38, 44, 45, 46, 48, 49, 52, 60, 62], "discov": [5, 29], "simplest": [6, 53], "adher": [6, 8], "nonneg": [6, 8, 16, 38, 55, 62], "word": [6, 8, 19, 22, 29, 35, 49, 55, 68, 69], "c": [6, 8, 9, 11, 15, 16, 18, 21, 22, 23, 24, 25, 26, 27, 29, 30, 34, 37, 38, 39, 41, 42, 44, 45, 46, 48, 49, 50, 53, 55, 58, 59, 60, 62, 63, 64, 65, 68, 69], "matrix": [6, 12, 19, 31, 38, 40, 41, 42, 48, 49, 50, 53, 58, 62, 63], "ii": [6, 8, 21, 33, 37], "iii": [6, 8, 33, 41], "unbound": [6, 8], "non": [6, 8, 9, 17, 18, 19, 21, 27, 29, 31, 34, 37, 39, 42, 45, 46, 47, 50, 55, 57, 59, 62, 65, 68, 69], "posit": [6, 8, 18, 24, 25, 27, 29, 37, 38, 40, 42, 48, 50, 58, 59, 60, 62], "x_i": [6, 7, 8, 11, 16, 35, 38, 42, 45, 48, 50, 58, 66], "fact": [6, 8, 9, 17, 20, 30, 32, 34, 36, 38, 39, 42, 44, 45, 48, 50, 55, 59, 62, 63, 65], "easili": [6, 8, 11, 18, 31, 33, 35, 38, 44, 45, 52, 57, 63, 68, 69], "convert": [6, 8, 21, 29, 31, 35, 37, 41, 42, 50, 68], "ad": [6, 8, 9, 30, 37, 39, 41, 45, 53, 55, 65, 66, 68, 69], "multipli": [6, 8, 9, 29, 42, 45], "explor": [6, 8, 16, 26, 28, 29, 36, 37, 39, 42, 43, 53, 54, 56, 57, 61], "variou": [6, 8, 16, 22, 26, 28, 30, 36, 37, 39, 43, 51, 52, 54, 55, 56, 61, 68, 69], "microchip": [6, 11, 17], "bim": [6, 15, 16, 51, 54], "absolut": [6, 11, 29, 35, 40, 42, 57, 65], "deviat": [6, 40, 55, 57, 58, 62, 63, 65, 66, 69], "lad": 6, "regress": [6, 36, 42], "mad": 6, "portfolio": [6, 31, 36, 43, 46, 47, 56], "variant": [6, 27, 58, 65, 66], "lowest": [6, 15, 29, 30], "fraction": [6, 12, 14, 17, 23, 29, 42, 46, 47, 49, 55, 58, 62, 65], "forecast": [6, 7, 51, 52, 62, 66], "extra": [6, 16, 18, 25, 28, 30, 36, 43, 44, 57, 59, 61, 63, 65], "wine": 6, "qualiti": [6, 39, 62], "predict": [6, 12, 13, 42, 50, 52, 62, 66], "l_1": [6, 13], "multi": [6, 29, 43, 45, 61], "aim": [7, 10, 12, 13, 20, 29, 32, 34, 36, 45, 48, 52, 53, 64], "valuabl": 7, "coupl": [7, 68], "physicochem": 7, "machin": [7, 8, 13, 16, 21, 36, 40, 43, 69], "2009": [7, 39, 46], "articl": [7, 25, 44, 45, 49, 68], "cortez": 7, "et": [7, 45], "al": [7, 35, 45], "physic": [7, 37, 42, 66], "chemic": [7, 21, 37, 39, 51, 68], "sensori": 7, "metric": [7, 13, 21, 22], "gather": 7, "red": [7, 8, 13, 14, 15, 29, 34, 44, 53, 57], "white": [7, 21, 22, 34, 35, 37, 53, 68], "portug": 7, "uci": [7, 42, 50], "download": [7, 20, 35, 39, 49, 65, 66], "panda": [7, 12, 14, 15, 18, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31, 35, 37, 39, 41, 42, 44, 45, 49, 50, 52, 53, 55, 57, 59, 60, 62, 63, 64, 65, 66, 68], "numpi": [7, 8, 12, 13, 14, 18, 20, 23, 24, 29, 30, 31, 35, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 69], "np": [7, 8, 12, 13, 14, 18, 20, 23, 24, 27, 29, 30, 31, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66], "read_csv": [7, 12, 18, 29, 31, 35, 37, 42, 50, 52, 57, 65, 66], "archiv": [7, 42, 50], "ic": [7, 42, 50], "edu": [7, 42, 45, 46, 49, 50, 64], "ml": [7, 42, 50, 51], "databas": [7, 29], "winequ": 7, "csv": [7, 29, 35, 37, 57, 65, 66], "sep": [7, 12, 18, 31, 35, 52], "acid": 7, "volatil": [7, 14], "citric": 7, "residu": [7, 13, 40, 41, 60], "sugar": [7, 64, 68], "chlorid": 7, "sulfur": [7, 39], "dioxid": 7, "densiti": [7, 57], "ph": 7, "sulphat": 7, "alcohol": 7, "7": [7, 10, 11, 13, 18, 19, 20, 21, 22, 24, 25, 27, 29, 31, 32, 33, 34, 35, 37, 38, 39, 42, 45, 49, 50, 52, 53, 60, 64, 66], "4": [7, 8, 9, 10, 11, 12, 17, 18, 21, 22, 23, 24, 25, 27, 29, 30, 32, 33, 34, 35, 37, 38, 39, 41, 42, 44, 45, 46, 47, 48, 49, 50, 52, 53, 55, 57, 60, 61, 63, 65, 66, 68, 69], "700": [7, 18, 32, 45], "076": 7, "11": [7, 11, 15, 18, 21, 22, 24, 25, 29, 31, 34, 35, 37, 38, 44, 45, 48, 53, 62, 66], "34": [7, 21, 29, 32, 52, 66], "99780": 7, "51": [7, 20, 22, 29, 37, 40, 47], "56": [7, 18, 29, 49, 64, 65], "8": [7, 11, 14, 15, 18, 19, 20, 21, 22, 24, 25, 27, 29, 30, 31, 32, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 49, 50, 52, 53, 55, 57, 59, 60, 62, 65, 66, 69], "880": 7, "098": [7, 32], "25": [7, 21, 22, 24, 25, 29, 32, 35, 37, 38, 39, 42, 46, 47, 48, 49, 53, 55, 58, 60, 62, 63, 64, 65, 66], "67": [7, 10, 12, 18, 29, 35, 37, 52, 66], "99680": 7, "68": [7, 12, 18, 22, 29, 35, 37, 52, 66], "760": 7, "04": [7, 17, 29, 35, 38, 39, 48, 63, 65], "092": 7, "15": [7, 14, 18, 21, 22, 24, 25, 29, 31, 33, 34, 35, 37, 38, 42, 44, 45, 48, 50, 53, 58, 60, 62, 63, 66, 69], "54": [7, 18, 29, 32, 37, 49, 52, 60, 64], "99700": 7, "26": [7, 21, 25, 29, 33, 53, 55], "65": [7, 12, 18, 27, 29, 35, 37, 50, 52, 60, 65, 66], "280": [7, 45], "075": [7, 32, 55], "17": [7, 21, 24, 25, 29, 31, 37, 38, 42, 45, 48, 49, 53, 62, 66], "99800": 7, "58": [7, 29, 35, 64, 65, 66], "1594": 7, "600": [7, 18, 66], "08": [7, 14, 29, 32, 34, 38, 48, 52, 60, 63], "090": 7, "32": [7, 21, 22, 25, 29, 37], "44": [7, 18, 20, 29, 37, 41, 49, 57, 65, 66], "99490": 7, "45": [7, 21, 29, 30, 31, 32, 35, 39, 41, 66], "1595": 7, "550": 7, "062": [7, 14], "39": [7, 13, 29, 30, 65], "99512": 7, "52": [7, 12, 29, 39, 44, 45, 64], "76": [7, 29, 35, 39], "1596": 7, "510": [7, 64], "13": [7, 14, 18, 21, 22, 24, 25, 29, 30, 31, 37, 38, 42, 44, 48, 52, 53, 60, 65], "29": [7, 25, 29, 37, 49, 53], "99574": 7, "42": [7, 21, 29, 37, 39, 62], "75": [7, 29, 32, 37, 38, 40, 42, 45, 55, 60, 62, 64, 65], "1597": [7, 24], "645": [7, 62], "99547": 7, "57": [7, 24, 29, 37, 52, 63, 65], "71": [7, 27, 29, 60], "1598": 7, "310": [7, 12, 18, 52, 64], "47": [7, 12, 18, 29, 37, 50, 52, 62, 63], "067": [7, 29], "18": [7, 24, 25, 29, 32, 35, 37, 38, 39, 46, 48, 53, 62, 65, 66, 69], "99549": 7, "66": [7, 12, 13, 18, 29, 52, 62, 65], "1599": [7, 45], "repeat": [7, 15, 21, 46, 47, 55, 63], "observ": [7, 13, 25, 32, 35, 39, 40, 42, 49, 55, 57, 60, 63, 65, 66, 69], "respons": [7, 35, 66], "y_i": [7, 42, 45, 50, 53, 55], "frac": [7, 10, 14, 24, 27, 29, 31, 42, 44, 45, 47, 49, 50, 57, 60, 62, 63, 65, 68], "df": [7, 20, 30, 31, 37, 42, 44, 45, 49, 50, 52, 55, 59, 62, 64, 68], "ab": [7, 14, 35, 42, 44, 45, 46, 47, 49, 63, 65], "5f": [7, 14, 29, 44, 46, 47, 49], "14": [7, 12, 13, 14, 18, 22, 24, 25, 27, 29, 31, 37, 38, 39, 41, 48, 50, 52, 53, 66, 69], "get_cmap": [7, 12, 13, 14, 23, 24, 27, 33, 37], "axhlin": [7, 14, 15, 24, 25, 27, 39, 41, 60], "ls": [7, 14, 24, 27], "lw": [7, 12, 14, 21, 22, 24, 25, 27, 37, 44, 45, 46, 47, 49, 52, 53, 60, 62], "legend": [7, 12, 13, 14, 15, 22, 24, 27, 32, 35, 40, 41, 44, 45, 46, 49, 52, 57, 60, 62, 66], "set_ylabel": [7, 12, 13, 14, 21, 22, 23, 24, 25, 27, 29, 39, 41, 44, 45, 46, 47, 49, 52, 62], "68318": 7, "599": 7, "eleven": 7, "characterist": [7, 8, 68], "plu": [7, 10, 18], "record": [7, 49, 51], "histogram": [7, 13, 14, 29, 40, 62, 63], "insight": [7, 13, 42, 50], "sharei": [7, 14], "flatten": [7, 14], "hist": [7, 13, 14, 29, 40, 62, 63], "30": [7, 13, 18, 21, 22, 24, 25, 26, 29, 32, 35, 37, 41, 44, 45, 49, 53, 59, 62, 63, 66, 69], "axvlin": [7, 14, 24, 25, 27, 29, 39, 41, 53], "set_titl": [7, 14, 20, 21, 23, 24, 29, 32, 37, 39, 41, 44, 46, 47, 49, 52, 57, 62], "explanatori": [7, 13, 40], "interest": [7, 9, 31, 33, 42, 45, 50, 60, 63], "deep": [7, 52], "knowledg": [7, 44, 49, 59, 63], "area": [7, 27, 44, 57], "onenologist": 7, "head": [7, 42, 49, 50, 53], "naiv": [7, 17, 55, 59], "scientist": 7, "absenc": 7, "experi": [7, 46], "proce": [7, 68], "correl": [7, 42, 50], "_": [7, 8, 11, 12, 13, 18, 20, 21, 22, 25, 26, 29, 31, 34, 35, 37, 38, 39, 40, 46, 47, 48, 49, 50, 53, 55, 57, 59, 62, 63, 64, 65, 69], "corr": 7, "000000": [7, 24, 29, 31, 35, 42, 66], "022026": 7, "202288": 7, "390558": 7, "496180": [7, 42], "174919": 7, "476166": 7, "figur": [7, 20, 29, 30, 35, 37, 40, 45, 52, 53, 55, 57, 62], "strong": [7, 9, 20], "singl": [7, 8, 13, 14, 15, 20, 22, 26, 29, 33, 35, 39, 53, 57, 63, 65, 66, 68, 69], "determin": [7, 12, 24, 25, 27, 30, 35, 36, 37, 42, 44, 45, 47, 50, 53, 57, 58, 59, 60, 63, 64, 65, 66, 69], "largest": [7, 29, 37], "reduc": [7, 14, 15, 20, 26, 27, 32, 37, 39, 42, 44, 45, 47, 50, 64, 69], "right": [7, 8, 9, 10, 12, 13, 14, 20, 21, 22, 23, 25, 27, 30, 37, 39, 40, 42, 44, 45, 47, 50, 53, 55, 60, 62, 63, 65], "prior": [7, 21, 23, 24, 32, 59, 62], "lad_fit_1": 7, "y_col": 7, "x_col": 7, "concretemodel": [7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 48, 52, 53, 55, 57, 58, 59, 60, 62, 63, 64, 65, 66, 68], "len": [7, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 29, 30, 33, 35, 37, 40, 41, 42, 45, 49, 52, 53, 55, 57, 62, 63, 64, 65, 66], "rangeset": [7, 13, 14, 23, 24, 29, 31, 33, 37, 40], "loc": [7, 12, 14, 15, 18, 21, 22, 24, 27, 29, 30, 31, 32, 37, 39, 41, 42, 44, 45, 49, 52, 53, 57, 60, 64], "e_po": 7, "e_neg": 7, "prediction_error": 7, "54117": 7, "calcul": [7, 13, 14, 21, 27, 30, 31, 35, 39, 40, 42, 44, 45, 47, 50, 55, 59, 60, 63, 65, 66, 68, 69], "fig1": 7, "ax1": 7, "count": [7, 13, 18, 29, 40, 42, 50, 66], "fig2": [7, 13], "ax2": [7, 13], "scatter": [7, 13, 14, 40, 42, 50, 57], "set_aspect": [7, 27, 44], "box": 7, "min_val": [7, 14], "get_xlim": [7, 27], "get_ylim": [7, 21, 62], "max_val": [7, 14], "set_xlim": [7, 14, 23, 25, 27, 41, 44, 45, 46, 53, 57, 62], "set_ylim": [7, 21, 22, 24, 25, 27, 32, 41, 44, 45, 46, 47, 49, 57], "m_j": [7, 13, 40, 57], "hat": [7, 12, 52, 59, 65], "min_": [7, 39, 40, 42, 45], "_i": [7, 22, 50, 65], "j": [7, 8, 12, 13, 14, 15, 18, 20, 21, 22, 25, 27, 29, 30, 31, 33, 34, 35, 37, 40, 41, 42, 44, 45, 50, 52, 53, 57, 62, 63, 65, 66, 69], "x_": [7, 12, 18, 19, 20, 23, 27, 29, 30, 31, 32, 33, 34, 37, 39, 42, 50, 53, 59], "care": [7, 14, 18, 29, 63, 69], "l1_fit": 7, "l1": 7, "49980": 7, "34242": 7, "98062": 7, "28928": 7, "90609": 7, "00219": 7, "50083": 7, "06382": 7, "substanti": [7, 14, 41], "reduct": [7, 8, 64, 65], "benchmark": [7, 21, 39], "tabul": 7, "regressor": [7, 13], "683": [7, 45], "541": 7, "500": [7, 12, 18, 30, 32, 40, 41, 45, 46, 49, 52, 53, 55, 57, 64], "enough": [7, 8, 17, 25, 26, 29, 33, 36, 39, 59], "replac": [7, 20, 29, 30, 31, 39, 42, 46, 50, 57, 62], "human": 7, "judgment": 7, "judg": 7, "intern": [8, 12, 18, 44, 46, 49, 52, 69], "chip": [8, 10, 12, 17, 18, 52, 55], "1g": 8, "silicon": [8, 9, 10, 11, 12, 15, 17, 18, 52, 55], "plastic": [8, 9, 10, 11, 12, 15, 17, 18, 52, 55], "4g": 8, "copper": [8, 9, 10, 11, 12, 15, 17, 18, 52], "memori": [8, 12, 14, 17, 18, 52, 55, 69], "germanium": [8, 9, 10, 11, 12, 15, 17, 18, 52, 55], "2g": 8, "sold": [8, 29, 39, 59, 60, 62, 64], "stock": [8, 12, 18, 36, 39, 46, 47, 49, 51, 52, 56], "1000g": 8, "1500g": 8, "1750g": 8, "4800g": 8, "euro": [8, 31, 64], "12x": 8, "9y": 8, "know": [8, 29, 30, 39, 45, 50, 51, 55, 59, 62, 66], "joint": 8, "usag": [8, 69], "4x": 8, "exce": [8, 25, 30, 39, 66], "1000": [8, 9, 10, 11, 12, 13, 15, 17, 18, 19, 20, 26, 29, 35, 45, 46, 52, 55, 57, 60, 62, 63, 64, 66], "deduc": 8, "role": [8, 29, 36, 39, 53, 55, 63], "1500": [8, 9, 10, 11, 12, 15, 17, 18, 29, 52, 55, 60, 64], "1750": [8, 9, 10, 11, 12, 15, 17, 18, 29, 32, 52, 55], "2y": [8, 69], "4800": [8, 9, 10, 11, 12, 17, 18, 45, 52, 55, 64], "leverag": [8, 30, 31, 45, 49, 55], "dimension": [8, 21, 27, 37, 42, 44, 50, 55, 62], "grai": [8, 24, 34, 35, 53], "enclos": 8, "solid": [8, 34, 65], "isolin": [8, 44], "parallel": [8, 33], "dash": [8, 21, 22], "blue": [8, 13, 21, 35], "increas": [8, 14, 20, 21, 23, 27, 29, 31, 39, 41, 46, 47, 59, 60, 66], "intens": [8, 31, 39], "intuit": [8, 17, 47, 65], "alreadi": [8, 18, 20, 29, 31, 32, 50, 58, 66], "guess": [8, 33], "mark": [8, 24, 29, 46, 50], "easi": [8, 9, 53, 55], "imagin": [8, 29, 30], "complic": [8, 11, 50, 69], "matter": 8, "expand": [8, 63], "obfusc": 8, "discern": 8, "analyz": [8, 28, 62, 66], "matric": [8, 63], "close": [8, 13, 14, 29, 39, 44, 49, 60], "greatli": 8, "identif": [8, 29, 31], "similar": [8, 14, 20, 39, 42, 63, 65, 69], "food": [8, 21, 25, 39], "refresh": 8, "equat": [8, 13, 18, 19, 20, 27, 29, 35, 37, 42, 45, 50, 68], "toward": [8, 25, 27], "renam": 8, "x_1": [8, 9, 10, 17, 38, 42, 44, 48, 50, 55, 58], "x_2": [8, 9, 10, 17, 38, 42, 48, 50, 55, 58], "obtain": [8, 9, 12, 13, 17, 22, 27, 29, 30, 33, 35, 38, 39, 40, 42, 44, 45, 47, 48, 50, 55, 57, 59, 60, 62, 63, 65, 66], "pmatrix": [8, 63], "just": [8, 11, 21, 29, 32, 34, 37, 39, 44, 55, 59, 63, 65], "rewrit": [8, 13, 17, 29, 35, 40, 44, 45, 47, 48, 58, 63], "12x_1": [8, 10, 17, 55], "9x_2": [8, 10, 17, 55], "bmatrix": [8, 19, 22, 24, 26, 27, 42, 45, 50], "system": [8, 18, 29, 31, 35, 39, 46, 47, 56, 63, 66], "read": [8, 14, 21, 23, 29, 35, 37, 44, 49, 57, 62, 63, 66, 68, 69], "correctli": [8, 18, 25, 42, 55, 66], "replic": 8, "4x_1": [8, 10, 55], "longleftrightarrow": [8, 44, 45], "arrai": [8, 13, 38, 40, 42, 44, 45, 48, 49, 50, 55, 57, 58, 62, 63, 65, 66, 69], "2x_2": [8, 10, 55], "x1": [8, 9, 10, 11, 17, 27, 44], "x2": [8, 9, 10, 11, 17, 27], "1f": [8, 10, 11, 15, 21, 42, 46, 50, 60], "650": [8, 10, 55, 59], "1100": [8, 10, 18, 29, 55], "17700": [8, 9, 10, 55], "emploi": [8, 13, 25, 42], "enhanc": [8, 27, 39, 69], "thu": [8, 17, 18, 25, 29, 30, 33, 35, 40, 48, 57, 60, 62, 63, 66], "util": [8, 27, 29, 32, 35, 46, 47, 49, 53, 68], "encompass": 8, "advantag": [8, 18, 28, 30, 31, 42, 50, 68], "concis": [8, 20], "space": [8, 16, 44, 45, 53, 62, 68], "clariti": 8, "reveal": [8, 39, 50], "across": [8, 29, 34, 35, 63, 65], "uniform": [8, 23, 32, 39, 45, 46, 60, 63, 65, 69], "furthermor": [8, 18, 23, 44, 69], "unnecessari": [8, 69], "theoret": [8, 52, 60], "streamlin": [8, 21, 69], "Is": [8, 15, 30, 39, 46], "answer": [8, 42, 59], "textit": 8, "sign": [8, 42, 50], "onc": [8, 22, 23, 37, 42, 50, 62, 66], "commit": [8, 31, 65], "deriv": [8, 22, 27, 35, 41, 42, 45, 50, 62], "sort": [8, 14, 20, 21, 25, 29, 33, 42, 46, 50], "consid": [8, 11, 13, 14, 15, 18, 20, 21, 22, 24, 27, 28, 29, 30, 31, 32, 33, 37, 38, 39, 40, 42, 44, 46, 47, 48, 49, 53, 55, 57, 58, 60, 62, 63, 64, 65, 66, 68], "anywai": [8, 30, 63], "without": [8, 15, 23, 27, 32, 33, 37, 39, 42, 46, 47, 50, 53, 59, 63, 68, 69], "Of": [8, 16, 63], "cours": [8, 16, 17, 22, 33, 39, 63, 69], "illustr": [8, 12, 18, 20, 21, 26, 27, 29, 30, 37, 44, 45, 52, 55, 60, 65, 66], "shall": [8, 18, 29, 45, 50, 65], "upon": [8, 21, 57], "had": [8, 17, 18, 29, 42, 50, 59, 65], "mention": [8, 11], "neg": [8, 9, 17, 18, 21, 29, 34, 35, 37, 42, 45, 47, 50, 51, 57, 59, 62, 69], "therefor": [8, 14, 27, 32, 35, 38, 42, 45, 50, 62, 63, 66], "overlin": 8, "side": [8, 9, 14, 25, 29, 30, 42, 55, 57, 68], "One": [8, 9, 15, 19, 21, 22, 27, 29, 30, 35, 37, 38, 63, 65, 68], "inde": [8, 20, 25, 44, 50, 57, 63, 65], "yield": [8, 10, 17, 18, 27, 29, 39, 41, 45, 50, 52, 53, 55, 57, 63, 64, 68], "n_var": 8, "n_constraint": 8, "constraintlist": [8, 11, 60], "optimal_x": 8, "round": [8, 12, 14, 17, 18, 24, 25, 30, 31, 32, 33, 34, 37, 38, 39, 41, 44, 45, 48, 52, 55, 62, 64, 65], "addition": [8, 58, 63], "avoid": [8, 12, 18, 19, 21, 22, 27, 32, 33, 42, 52, 66, 68, 69], "hard": [8, 27, 29, 42, 50, 63], "doc": [8, 37, 45, 48, 69], "lambda_1": 9, "lambda_2": 9, "lambda_3": 9, "lambda_4": 9, "four": [9, 24, 39, 41, 42, 50, 63], "rh": [9, 50], "tight": [9, 20, 22, 24, 29, 52, 58], "Such": [9, 55, 57, 65, 66], "tightest": 9, "y1": [9, 10, 27, 63], "y2": [9, 10, 27, 63], "y3": [9, 63], "y4": 9, "dualiti": [9, 55], "primal": 9, "coincid": [9, 30], "ask": [9, 29, 31, 64], "suffix": [9, 32, 37, 55, 69], "component_object": [9, 55], "y_": [9, 18, 20, 23, 27, 39, 42, 50, 53, 59, 62], "y_1": [9, 10, 42, 50, 55, 63], "y_2": [9, 10, 42, 50, 55, 63], "y_3": [9, 63], "y_4": 9, "recal": [10, 12, 18, 35, 47, 48, 52, 60, 63], "pair": [10, 18, 19, 21, 22, 25, 27, 29, 31, 32, 34, 42, 53, 55, 66], "sale": [10, 14, 29, 59], "suppos": [10, 11, 13, 26, 40, 41, 55, 63], "independ": [10, 13, 35, 39, 40, 47, 49, 55, 62], "6x_1": 10, "6x_2": 10, "reason": [10, 18, 27, 29, 30, 33, 35, 36, 42, 45, 46, 49, 50, 53, 55, 57, 60, 63, 64, 68, 69], "bim_with_revenues_minus_cost": 10, "minu": [10, 18, 34, 57, 66], "variable_cost": 10, "fixed_cost": 10, "bim_linear": 10, "3f": [10, 14, 17, 29, 38, 42, 46, 47, 48, 50, 52, 57, 58, 68], "15925": 10, "000": [10, 14, 17, 32, 39, 45, 46, 55, 58, 62, 64], "1775": 10, "ratio": 10, "dfrac": 10, "deal": [10, 55], "auxiliari": [10, 11, 12, 14, 18, 22, 34, 42, 45, 47, 50, 55, 63], "12y_1": 10, "9y_2": 10, "cdot": [10, 18, 25, 26, 29, 30, 47, 50, 60, 62, 65, 66], "4y_1": 10, "2y_2": 10, "100y": 10, "despit": 10, "recov": [10, 30, 46, 65], "bim_with_revenues_over_cost": 10, "bim_fract": 10, "250": [10, 24, 35, 45, 55, 60, 64, 69], "051": [10, 29], "16500": 10, "1641": 10, "667": [10, 42, 58], "972": 10, "strictli": [10, 53], "seemingli": 11, "rewritten": [11, 58], "maxima": [11, 39], "finit": [11, 13, 29, 33, 40, 62, 63], "k": [11, 13, 18, 21, 22, 23, 24, 25, 27, 29, 30, 31, 33, 34, 37, 40, 42, 44, 45, 46, 47, 49, 50, 60, 63], "c_k": 11, "minimax": 11, "max_": [11, 15, 39, 46, 47, 49, 59, 62, 69], "top_": 11, "latter": [11, 24, 66], "z": [11, 15, 16, 18, 22, 26, 29, 37, 39, 42, 44, 45, 47, 50, 55, 57, 59, 60, 62, 63], "qquad": [11, 15, 20, 23, 25, 39, 40, 42, 45, 53, 62, 65], "guarante": [11, 14, 15, 32, 33, 38, 44, 48, 55, 57, 58, 62, 63, 65], "vice": [11, 63], "versa": [11, 63], "henc": [11, 35, 62, 66], "uncertainti": [11, 15, 43, 44, 52, 61, 63, 65, 66], "regard": [11, 15, 25, 39, 42, 45, 50, 51, 55, 64], "instead": [11, 16, 20, 29, 30, 33, 35, 36, 41, 55, 57, 62, 63, 65, 66, 68], "nomin": [11, 52, 55, 63, 64, 65, 66], "estim": [11, 13, 39, 51, 57, 60, 63], "trick": [11, 45], "bim_maxmin": 11, "maxmin": [11, 15], "c1": [11, 21], "c2": [11, 21], "583": [11, 15, 29], "1166": [11, 15, 55], "17500": [11, 15], "carefulli": [12, 39, 52], "manag": [12, 44, 45, 46, 47, 49, 51, 52, 56, 69], "led": [12, 52], "monthli": [12, 18, 52], "jan": [12, 18, 52], "feb": [12, 18, 52], "mar": [12, 18, 52], "jun": [12, 18, 52], "jul": [12, 18, 52], "aug": [12, 18, 52], "oct": [12, 18, 52], "nov": [12, 18, 52], "dec": [12, 18, 52, 63], "88": [12, 18, 20, 29, 35, 37, 42, 50, 52, 62, 66], "125": [12, 18, 35, 37, 49, 52, 55, 62, 66], "260": [12, 18, 32, 35, 52, 64], "217": [12, 18, 29, 52, 66], "238": [12, 17, 18, 29, 52, 64], "286": [12, 18, 52], "248": [12, 18, 52], "265": [12, 18, 35, 52, 55, 66], "293": [12, 18, 29, 52], "259": [12, 18, 27, 35, 45, 52], "244": [12, 18, 45, 52], "62": [12, 18, 29, 33, 37, 52, 65], "81": [12, 18, 29, 32, 35, 39, 52, 63], "95": [12, 18, 29, 32, 35, 42, 47, 52, 62, 65], "118": [12, 18, 24, 29, 31, 35, 46, 47, 49, 52, 66], "86": [12, 18, 24, 29, 35, 37, 42, 44, 52, 66], "89": [12, 18, 29, 50, 52], "82": [12, 18, 29, 52, 60], "84": [12, 18, 29, 37, 42, 45, 52, 60, 66], "200": [12, 14, 18, 20, 27, 31, 35, 39, 44, 45, 52, 55, 59, 62, 64, 66, 69], "acquir": [12, 18, 39, 52], "month": [12, 18, 52], "9000": [12, 52, 64], "05": [12, 18, 22, 24, 25, 26, 29, 37, 38, 39, 42, 44, 45, 46, 48, 49, 50, 52, 55, 58, 60, 62, 65, 66], "spend": [12, 52], "5000": [12, 23, 45, 46, 52, 60, 64], "kept": [12, 18, 52], "datafram": [12, 14, 15, 18, 20, 21, 22, 24, 25, 27, 29, 30, 31, 32, 35, 37, 39, 41, 42, 44, 45, 49, 50, 52, 53, 55, 57, 59, 62, 63, 64, 66, 68, 69], "stringio": [12, 18, 31, 52], "ipython": [12, 30, 32, 34, 38, 48, 58, 65], "demand_data": [12, 18, 52], "price_data": [12, 52], "demand_chip": [12, 18, 52], "index_col": [12, 18, 29, 31, 35, 52, 57, 65, 66], "consumpt": [12, 41], "dict": [12, 18, 20, 31, 35, 37, 39, 42, 45, 50, 52, 57, 60], "from_dict": [12, 18, 52, 57, 59, 68], "fillna": [12, 14, 18, 39, 52, 64], "astyp": [12, 18, 25, 30, 37, 52], "int": [12, 13, 18, 19, 27, 29, 30, 33, 37, 40, 47, 49, 52, 53, 60, 68], "135": [12, 18, 29, 32, 49, 60, 65, 69], "187": [12, 18], "341": [12, 18], "282": [12, 18], "333": [12, 15, 18, 45, 46], "404": [12, 18, 35], "334": [12, 18, 37], "327": [12, 18, 35, 45, 52], "347": [12, 18, 29], "375": [12, 18, 45, 52, 55, 64, 69], "343": [12, 18, 29, 52, 55], "446": [12, 18], "624": [12, 18], "1202": [12, 18], "998": [12, 18, 29], "1142": [12, 18, 46, 49], "1380": [12, 18, 37], "1164": [12, 18, 52], "1130": [12, 18], "1224": [12, 18], "1336": [12, 18], "1204": [12, 18], "1108": [12, 18], "pt": [12, 18, 52], "s_": [12, 14, 18, 32, 37], "uniqu": [12, 19, 21, 22, 25, 29, 35, 42, 50, 59, 66, 69], "eas": [12, 65], "pi_": [12, 18, 37], "h_": [12, 20], "happen": [12, 25, 39, 43, 55, 62, 65, 66, 68], "constant": [12, 19, 24, 26, 29, 30, 40, 44, 45, 57, 59, 60, 62, 66, 69], "focu": [12, 30, 42], "beta": [12, 18, 26, 44, 58], "further": [12, 13, 18, 21, 29, 37, 40, 45, 46, 50, 53, 60, 62], "storag": 12, "ell": [12, 55], "balanc": [12, 18, 29, 30, 31, 34, 39, 41, 42, 52, 55, 57, 64, 65, 66], "delta_": [12, 18], "impli": [12, 35, 41, 42, 45, 63], "period": [12, 14, 18, 21, 25, 29, 46, 52, 66], "texttt": 12, "januari": 12, "captur": [12, 35, 38, 62, 68], "level": [12, 14, 18, 21, 24, 35, 44, 48, 51, 52, 53, 57, 58, 60, 62, 65, 66], "decemb": 12, "textrm": [12, 18], "omega_p": [12, 18], "bimproductacquisitionandinventori": [12, 52], "acquisition_pric": [12, 52], "exist": [12, 18, 22, 29, 30, 31, 32, 42, 46, 50, 52, 66, 68, 69], "stock_limit": [12, 18, 52], "month_budget": [12, 52], "prev": [12, 18, 52], "bloat": [12, 18, 52], "pi": [12, 18, 45, 52], "h": [12, 25, 27, 29, 37, 44, 45, 46, 49, 52, 53, 60, 68, 69], "delta": [12, 14, 18, 29, 52, 55, 57, 65], "acquisition_cost": [12, 18, 52], "inventory_cost": [12, 18, 52], "total_cost": [12, 18, 32, 52], "2000": [12, 18, 20, 21, 22, 24, 31, 37, 41, 45, 49, 52, 55, 57, 64], "show_table_of_pyomo_vari": 12, "from_record": [12, 18, 52], "report_pyomo_solut": 12, "nthe": 12, "equidistant_color": 12, "drawstyl": [12, 18, 52], "mid": [12, 18, 52], "set_xtick": [12, 25, 53], "tick": [12, 37, 52], "set_xticklabel": [12, 25], "965": 12, "1078": 12, "266": [12, 18, 52], "1310": [12, 18, 52], "3548": 12, "962": 12, "4312": 12, "912": [12, 18, 52], "787": [12, 18, 60], "527": [12, 18, 35], "1275": [12, 55], "1037": 12, "751": 12, "503": 12, "785": 12, "744": [12, 52], "1615": [12, 18, 52], "1428": [12, 18, 52], "1087": [12, 18, 45, 52], "805": [12, 18, 52], "472": [12, 18, 52], "4354": [12, 18], "3730": [12, 18], "6076": 12, "5078": 12, "3936": 12, "2556": 12, "1392": 12, "262": [12, 35, 41], "3108": 12, "1453": [12, 18, 52], "1391": [12, 18, 52], "1245": [12, 18, 52], "1150": [12, 18, 52], "1032": [12, 18, 52], "946": [12, 18, 29, 35, 52], "857": [12, 18, 52], "775": [12, 18, 52], "693": [12, 18, 52], "609": [12, 18, 52], "543": [12, 18, 52], "situat": [12, 15, 16, 21, 23, 26, 27, 29, 30, 31, 36, 42, 50, 53, 63, 64, 68], "444": 12, "559": [12, 62], "666": [12, 52], "400": [12, 18, 35, 55, 59, 62, 66], "1065": 12, "221": 12, "33": [12, 29, 37, 39, 46, 52, 60, 62, 66], "323": [12, 45, 65], "983": 12, "695": 12, "934": [12, 27], "1356": 12, "1790": 12, "1530": [12, 18], "1980": 12, "1742": [12, 35], "1856": 12, "1673": 12, "38": [12, 29, 35, 37, 60, 62, 65, 66], "1435": 12, "1296": [12, 52], "1003": [12, 52], "718": [12, 35], "4575": 12, "4274": 12, "5072": 12, "4074": 12, "3932": 12, "2552": 12, "1388": 12, "1241": 12, "98": [12, 29, 49, 60, 62, 66], "713": [12, 17, 29, 35], "1377": 12, "2173": 12, "remain": [12, 13, 16, 18, 22, 35, 37, 45, 55, 57, 59, 62, 65, 69], "forc": [12, 25], "infeas": [12, 33, 57, 58, 63, 65, 66], "fewer": [12, 37, 53], "variabel": 12, "rid": 12, "bimproductacquisitionandinventory_v2": 12, "non_negative_stock": 12, "supervis": [13, 42], "19th": 13, "centuri": [13, 49], "cornerston": 13, "modern": [13, 14, 22], "depend": [13, 21, 22, 33, 35, 39, 40, 47, 62, 63, 64, 66, 69], "tradit": 13, "unlik": 13, "squar": [13, 36, 42, 44, 45], "focus": [13, 66], "norm": [13, 42, 50, 58, 62], "robust": [13, 46, 49, 51, 56, 65, 66], "against": [13, 27, 40, 63], "outlier": 13, "methodolog": 13, "survei": [13, 37, 39], "paper": [13, 14, 21, 29, 37, 44, 45, 46, 47, 49, 57], "subash": 13, "narula": 13, "john": [13, 21, 41, 47, 64, 69], "wellington": 13, "scikit": [13, 40], "make_regress": [13, 40], "synthet": [13, 40], "n_sampl": [13, 40], "n_featur": [13, 40], "sklearn": [13, 40, 42, 50], "nois": [13, 40], "random": [13, 20, 23, 24, 27, 30, 33, 38, 40, 45, 46, 47, 48, 49, 52, 53, 55, 57, 58, 60, 62, 63, 65, 66], "seed": [13, 20, 24, 30, 33, 40, 52, 53, 55, 57, 60, 62, 63, 65, 66], "2021": [13, 29, 44, 46, 49], "prepar": [13, 25, 40, 62, 66, 68], "versu": [13, 39, 40], "coolwarm": [13, 14], "sqrt": [13, 29, 40, 42, 44, 45, 50, 53, 62], "edgecolor": [13, 25, 27], "black": [13, 45], "e_i": [13, 40], "quantifi": [13, 38, 48], "diverg": 13, "_j": [13, 14, 22, 40, 42, 50, 55, 57, 65], "m_1": [13, 35, 40], "m_k": [13, 40], "criterion": [13, 15, 29, 40, 43, 46, 49], "attempt": [13, 29, 32, 37, 39, 68], "intercept": [13, 40, 50], "approxim": [13, 42, 46, 49, 62, 63, 65], "m_i": [13, 40], "nonlinear": [13, 36, 37, 44, 45, 55, 68], "wors": [13, 63], "differenti": [13, 29, 30, 42, 68], "lad_regress": [13, 40], "dimens": [13, 20, 42, 50], "shape": [13, 27, 32, 40, 42, 50, 60, 66], "style": [13, 21, 32, 34, 40, 67, 68], "ep": [13, 40, 57], "em": [13, 40, 49], "sum_of_abs_error": [13, 40], "24276": 13, "nativ": [13, 26, 69], "inclus": [13, 47, 49, 69], "fit": [13, 27, 37, 40, 42, 45, 50, 62, 68], "found": [13, 21, 27, 29, 33, 35, 37, 39, 47, 49, 51, 52, 55, 59, 63, 64], "actual": [13, 17, 39, 42, 47, 50, 51, 53, 55, 59, 63, 65, 68], "y_fit": [13, 40], "distribut": [13, 14, 21, 24, 28, 29, 34, 46, 47, 49, 55, 56, 58, 63, 66, 69], "theori": [14, 46, 49, 58, 68], "histori": [14, 39], "financ": [14, 29, 45, 46, 47, 49], "invest": [14, 29, 38, 41, 43, 44, 47, 48, 49, 58], "princip": 14, "idea": [14, 15, 20, 22, 27, 45, 46, 47, 53, 55, 57, 63, 65], "blend": [14, 25, 36], "financi": [14, 29, 31, 41, 59, 65], "secur": 14, "trade": [14, 31, 42, 44, 48, 49, 50], "off": [14, 20, 42, 44, 45, 48, 50, 63, 66, 68], "introduct": [14, 25, 46, 47, 62, 64, 68], "1952": 14, "doctor": 14, "thesi": [14, 29], "harri": [14, 45, 49], "markowitz": [14, 36, 43, 49, 56], "award": 14, "share": [14, 33], "1990": [14, 21], "nobel": 14, "prize": 14, "econom": [14, 27, 29, 39, 41, 43, 44, 56], "hi": [14, 19, 24, 46, 47], "field": [14, 63, 66], "covari": [14, 38, 48, 58, 62], "constitu": 14, "varianc": [14, 38, 42, 46, 48, 50, 62], "quadrat": [14, 37, 38, 39, 48, 50, 55], "subject": [14, 24, 26, 30, 31, 32, 37, 38, 44, 46, 47, 51, 53, 59, 63, 64, 69], "alloc": [14, 27, 30, 32, 33, 37, 45, 47, 61, 64], "wealth": [14, 29, 31, 46, 47], "remark": [14, 42, 50], "1991": [14, 21, 37], "konno": 14, "yamazaki": 14, "propos": [14, 32, 37, 47, 49, 62, 68], "incorpor": [14, 23, 29, 37, 49, 69], "larg": [14, 15, 20, 22, 23, 25, 26, 29, 30, 32, 33, 35, 37, 39, 41, 42, 49, 50, 62, 63, 65, 69], "yahoo": [14, 49], "web": [14, 29, 45, 46, 49, 64], "servic": [14, 20, 29, 31, 32, 53, 62], "notori": 14, "fickl": 14, "colaboratori": 14, "upgrad": [14, 29, 31, 49, 62], "q": [14, 29, 41, 42, 44, 45, 46, 49, 50, 53, 60, 62, 63, 65, 66, 68], "mdate": 14, "scipi": [14, 20, 58, 60, 62], "datetim": [14, 29, 49], "yf": [14, 20, 49], "n_year": 14, "load": [14, 20, 21, 33, 35, 50, 65, 66, 68], "consolid": 14, "split": [14, 20, 25, 29, 42, 61], "dividend": 14, "ticker": 14, "axp": [14, 49], "aapl": [14, 49], "amgn": [14, 49], "ba": [14, 49], "crm": 14, "csco": 14, "cvx": [14, 49], "di": 14, "dow": [14, 49], "gs": 14, "hd": 14, "ibm": 14, "intc": 14, "jnj": 14, "jpm": [14, 49], "ko": 14, "mcd": [14, 49], "mmm": [14, 49], "mrk": 14, "msft": [14, 49], "nke": 14, "pg": [14, 49], "trv": 14, "unh": 14, "vz": 14, "wba": 14, "wmt": 14, "xom": [14, 49], "end_dat": 14, "todai": [14, 49], "start_dat": 14, "timedelta": [14, 49], "365": [14, 35, 49, 55, 59], "progress": [14, 44], "adj": [14, 49], "bfill": 14, "inplac": [14, 21, 45, 49, 53, 64], "ffill": 14, "logi": [14, 49], "bbox_to_anchor": [14, 22, 24, 46, 49], "log": [14, 29, 37, 46, 49, 55, 57, 66, 68], "preserv": [14, 26], "arithmet": [14, 19], "logarithm": [14, 29, 47], "assets_sc": 14, "div": 14, "iloc": [14, 49, 50, 52], "dai": [14, 25, 26, 29, 35, 59, 60], "r_": [14, 24, 32, 47, 49], "daily_return": 14, "diff": 14, "shift": [14, 16, 49], "sharex": [14, 24, 49], "xaxi": 14, "set_major_loc": 14, "yearloc": 14, "set_major_formatt": 14, "dateformatt": 14, "delta_j": [14, 65], "depict": [14, 37], "interv": [14, 21, 22, 53, 60, 68], "whose": [14, 18, 27, 38, 40, 47, 57, 58], "green": [14, 21, 29, 34, 35, 44, 53, 57], "mean_return": 14, "mean_absolute_devi": 14, "linestyl": [14, 15, 24, 39, 41, 57, 60], "comparison": [14, 20, 22, 23, 42, 63], "vs": [14, 23, 36, 48, 49, 62], "scalarformatt": 14, "gradient_barplot": 14, "color_map": [14, 35], "range_v": 14, "val": 14, "normalized_v": 14, "35": [14, 18, 29, 37, 48, 58, 65, 66], "choos": [14, 15, 18, 23, 26, 33, 42, 44, 47, 50, 55, 59], "map": [14, 19, 37, 42, 50, 66], "color_map2": 14, "revers": [14, 29, 69], "color_map3": 14, "ylgn": 14, "set_ytick": [14, 21, 22, 25, 37], "arang": [14, 18, 52], "set_yticklabel": [14, 21, 25], "0005": [14, 45], "0021": 14, "formatt": 14, "usemathtext": 14, "set_scientif": 14, "set_powerlimit": 14, "001": [14, 29, 45], "02": [14, 17, 18, 29, 38, 48, 57, 62], "ms": [14, 24, 29, 30, 35, 37, 39, 41, 44, 45, 46, 60, 68], "03": [14, 29, 31, 38, 39, 48], "formatterx": 14, "formatteri": 14, "yaxi": [14, 23], "w_t": 14, "t_": [14, 21, 24, 62], "w_": [14, 27, 29, 33, 42, 46, 47, 62], "n_": [14, 19, 25, 29, 32], "jn_": 14, "weight": [14, 18, 21, 22, 25, 27, 29, 34, 35, 37, 42, 46, 49, 50, 53], "w_j": [14, 31], "investor": [14, 29, 38, 46, 47, 48, 49], "impos": [14, 22, 23, 25, 30, 42, 46, 55], "horizon": [14, 22, 23, 24, 52], "w": [14, 22, 23, 25, 27, 31, 33, 37, 39, 42, 44, 45, 46, 47, 49, 50, 53, 55, 59, 66], "big": [14, 18, 22, 23, 25, 26, 29, 35, 45, 57, 62], "ub": [14, 21, 27, 44, 50, 69], "enforc": [14, 25, 29, 53, 65], "diversif": 14, "u_t": [14, 23, 49], "v_t": 14, "mad_portfolio": 14, "w_lb": [14, 27], "w_ub": [14, 27], "portfolio_return": 14, "sum_of_weight": 14, "mean_portfolio_return": 14, "no_short": [14, 29], "diversifi": 14, "024": [14, 45, 68], "101": [14, 24, 29], "027": [14, 45], "004": [14, 45], "115": [14, 35, 44, 45, 49, 66], "141": [14, 37, 49], "104": [14, 29, 42], "012": [14, 29, 45, 62], "01": [14, 29, 31, 32, 37, 38, 46, 47, 48, 55], "199": [14, 62], "00740": 14, "mad_visu": 14, "mad_portfolio_weight": 14, "color_map1": 14, "grei": [14, 37], "97": [14, 21, 29, 42, 49, 50, 66], "005": [14, 38, 45, 48, 55, 62], "21": [14, 20, 22, 24, 25, 29, 35, 42, 44, 49, 53, 55, 62, 65], "000015": [14, 29], "0028": 14, "toler": [14, 38, 42, 48, 55, 57, 66], "central": [14, 36], "linspac": [14, 39, 41, 44, 45, 46, 47, 49, 55, 57, 60, 64, 66], "portfolio_mean_return": 14, "portfolio_mean_absolute_devi": 14, "ro": [14, 39, 41, 45], "_0": 14, "w_0": [14, 46, 47], "mad_portfolio_withriskfreeasset": 14, "rf": [14, 49], "138": [14, 27, 42, 49], "049": 14, "139": [14, 27, 38, 49], "117": [14, 27, 35, 62, 66], "037": 14, "906": 14, "00731": 14, "instruct": 14, "mpt": 14, "frontier": [14, 48, 49], "capit": [14, 37, 38, 44, 46, 47, 48, 49, 58], "minor": [14, 17], "veri": [14, 23, 28, 30, 33, 36, 50, 51, 53, 55, 63, 66], "depart": [14, 34, 53], "c_j": [15, 20], "x_j": [15, 20, 42], "ij": [15, 20, 22, 34, 35, 65, 66], "b_i": [15, 45], "net": [15, 26, 29, 31, 34, 39, 60, 65, 66], "margin": [15, 32, 37, 42, 50, 55, 64, 66], "uncertain": [15, 48, 55, 59, 63, 65, 66], "thorni": 15, "reserv": [15, 31], "plausibl": 15, "plant": [15, 16, 23, 35, 66], "_s": 15, "deem": 15, "probabilist": [15, 62], "conserv": [15, 34, 35, 44, 66], "bim_scenario": 15, "nprofit": [15, 39], "bim_resourc": 15, "4000": [15, 39, 45, 64], "set_index": [15, 21, 32, 35, 45, 53, 57, 65, 66], "navail": 15, "tolist": [15, 39], "scenario_profit": [15, 64], "resource_limit": 15, "worst_case_profit": [15, 63, 64], "nworst": 15, "worst_case_plan": 15, "33333": 15, "66670": 15, "outlook": 15, "worth": [15, 35, 39, 64], "investig": [15, 63, 66], "simpli": [15, 29, 32, 45, 53, 59, 62, 66], "max_profit": 15, "mean_cas": 15, "mean_case_profit": 15, "mean_case_plan": 15, "nmean": [15, 62], "17833": 15, "750": [15, 29], "expect": [15, 31, 35, 38, 46, 47, 48, 50, 51, 55, 57, 58, 60, 62, 63, 64, 65], "prefer": [15, 25, 42, 49, 65], "mean_case_outcom": 15, "worst_case_outcom": 15, "concat": [15, 52], "axi": [15, 24, 30, 37, 39, 42, 45, 52, 57, 59, 62, 66], "ylim": [15, 41, 42, 50, 55, 60], "15000": [15, 41, 64], "20000": [15, 31, 32, 64], "orang": [15, 35], "penalti": [15, 42, 48, 50, 59], "bad": [15, 22, 46, 49, 51, 63, 64], "payout": [15, 46], "favor": [15, 46], "occur": [15, 23, 29, 45, 46, 47], "why": [15, 29, 49, 57, 69], "peopl": [16, 30], "power": [16, 42, 50, 51, 57, 61, 66], "threshold": [16, 29, 30, 38, 42, 55, 57, 58, 66], "neither": [16, 30, 32], "seen": [16, 57], "still": [16, 59, 65, 66], "although": [16, 30, 55], "milo": [16, 17, 22, 23, 28, 29, 30, 33, 37, 65], "mathcal": [16, 35, 42, 48, 50, 53, 62, 65, 66], "subset": [16, 25, 42, 50, 69], "tacitli": 16, "perturb": [16, 55, 63, 65], "workforc": 16, "schedul": [16, 23, 27, 28, 65, 66], "recharg": 16, "electr": [16, 35, 51, 66], "vehicl": [16, 51], "disjunct": [16, 19, 21, 24, 27, 64, 69], "cryptarithm": 16, "puzzl": 16, "strip": [16, 20, 68], "pack": [16, 37], "job": 16, "shop": [16, 56], "mainten": [16, 32], "network": [16, 29, 31, 32, 34, 39, 65], "realiz": [17, 23, 29, 30, 32, 35, 39, 48, 52, 55, 59, 62, 63, 65, 66], "wast": [17, 63], "gr": [17, 55], "accordingli": 17, "approx": [17, 39, 60, 62], "626": [17, 27, 62], "1123": 17, "762": [17, 50], "roughli": 17, "17628": 17, "loss": [17, 29, 31, 37, 42, 58, 59, 64], "ineffici": 17, "627": 17, "1124": 17, "unfeas": 17, "potenti": [17, 26, 29, 39, 42, 50, 63, 66], "intric": 17, "difficult": [17, 27, 36, 66], "safer": 17, "outlin": [17, 22, 67], "again": [18, 29, 30, 31, 35, 42, 48, 50, 63], "sophist": [18, 29], "acquisit": [18, 52], "protocol": [18, 35], "supplier": [18, 20, 32, 59], "deliv": [18, 22, 32, 35, 39], "sheet": [18, 21], "unitari": 18, "batch": 18, "half": 18, "discount": [18, 44], "purchas": [18, 29, 31, 37, 39, 52, 62, 63, 64], "summari": [18, 29], "incur": [18, 20, 45, 66], "pai": [18, 32, 63], "kilogram": 18, "moment": [18, 23, 31, 35, 65], "usual": [18, 21, 22, 34, 42], "track": [18, 25, 27, 29, 62], "bui": [18, 29, 60, 64], "volum": [18, 29, 32, 35, 65], "ts": 18, "u_": [18, 34, 63], "tricki": 18, "b_": [18, 34, 35, 37, 65, 66], "r_t": [18, 49], "p_t": 18, "sure": [18, 25, 46, 47, 58, 63, 65], "p_": [18, 35, 57, 59, 65, 66], "cent": [18, 32], "alpha_": 18, "setminu": [18, 65, 66], "h_p": 18, "ensur": [18, 30, 33, 35, 38, 48, 53, 57, 62, 65, 66], "natur": [18, 25, 34, 36, 37, 39, 45, 51, 55, 59, 63, 69], "give": [18, 35, 39, 42, 44, 45, 47, 50, 53, 63, 66], "gamma_": 18, "textup": [18, 22, 25], "10000": [18, 19, 22, 24, 26, 29, 45], "automat": [18, 65], "input": [18, 35, 38, 42, 48, 50, 53, 58, 60, 62, 63, 65, 68], "bimproduction_v1": 18, "supplying_copp": 18, "supplying_batch": 18, "price_copper_sheet": 18, "price_batch": 18, "discounted_pric": 18, "batch_siz": 18, "copper_sheet_mass": 18, "copper_bucket_s": 18, "unitary_product": 18, "unitary_holding_cost": 18, "kappa": 18, "gamma": [18, 25, 38, 42, 48, 50, 55, 63], "omega": [18, 57], "units_in_batch": 18, "copper_in_bucket": 18, "inventory_capac": 18, "pairs_in_batch": 18, "pairs_in_sheet": 18, "bought": [18, 59, 60], "quickli": [18, 29, 31], "pars": [18, 30], "table1d": 18, "retriev": [18, 29], "table2d": 18, "table3d": 18, "multiindex": [18, 53], "from_product": 18, "m1": 18, "300": [18, 22, 24, 35, 44, 45, 52, 55, 59, 62, 64], "0f": [18, 20, 27, 32, 34, 60, 66], "xtick": [18, 30, 52], "git": [18, 25, 26], "hash": [18, 25, 26], "594fa5a9d": [18, 25, 26], "copyright": [18, 25, 26], "mit": [18, 25, 26], "licenc": [18, 25, 26], "110216": 18, "1102": 18, "228": [18, 29, 45], "233": [18, 55], "274": [18, 44], "349": [18, 44, 65], "257": 18, "690": [18, 29], "326": [18, 35], "371": [18, 45, 65, 66], "351": [18, 27], "1200": [18, 64, 66], "1300": [18, 45], "3100": 18, "72": [18, 20, 24, 29, 37, 41, 49, 60], "36": [18, 29, 37, 41, 60, 62, 64], "24": [18, 24, 25, 29, 32, 35, 39, 42, 45, 49, 53, 62, 64, 65, 66], "2528": 18, "388": 18, "90": [18, 23, 26, 27, 29, 42, 50, 62, 63, 64], "2042": [18, 45], "bimproduction_v2": 18, "in_batch": 18, "m2": [18, 40], "1427": [18, 35], "1086": 18, "804": 18, "471": 18, "juli": 19, "1924": 19, "famou": [19, 30, 49, 59], "british": 19, "magazin": 19, "strand": 19, "henri": 19, "dudenei": 19, "regular": [19, 42, 50], "perplex": 19, "digit": [19, 29], "d": [19, 21, 22, 24, 25, 27, 32, 34, 35, 37, 39, 40, 42, 45, 46, 49, 50, 53, 57, 58, 59, 63, 65, 66, 68, 69], "o": [19, 20, 32, 44, 46, 47, 49, 50, 53, 57, 68], "along": [19, 24, 27, 29, 42, 50, 51, 68], "n_a": 19, "n_e": 19, "n_n": 19, "n_d": [19, 32], "n_m": 19, "n_o": 19, "n_r": 19, "n_y": 19, "n_b": 19, "lt": 19, "veebar": [19, 21, 22, 23, 24, 26, 27], "gdp": [19, 21, 22, 23, 24, 26, 27, 64], "filter": [19, 21, 22, 25, 27, 29, 31, 35, 53, 69], "messag": [19, 20, 30, 57, 66, 68], "leading_digit_nonzero": 19, "unique_assign": 19, "dummi": [19, 30, 53], "dummy_object": 19, "transformationfactori": [19, 21, 22, 23, 24, 26, 27, 64, 68], "bigm": [19, 21, 22, 23, 24, 26, 27, 62, 64], "apply_to": [19, 21, 22, 23, 24, 26, 27, 64, 68], "letters2num": 19, "join": [19, 25, 29, 31, 34, 49], "send": [19, 30], "monei": [19, 29, 32, 44, 49, 59], "gdpopt": [19, 20], "mip": 19, "gecod": 19, "refactor": 19, "On": [20, 21, 23, 24, 35, 46, 49, 55, 59], "notic": [20, 55, 63, 68], "exercis": [20, 35, 62], "face": [20, 22, 38], "strike": 20, "speedup": 20, "apt": 20, "qq": 20, "coinor": 20, "fulfil": [20, 37], "simultan": [20, 21, 31, 37, 47], "decid": [20, 22, 32, 35, 59, 62, 63, 66], "otherwis": [20, 25, 30, 33, 35, 42, 47, 50, 55, 57, 63], "sum_j": [20, 22, 65], "sum_i": 20, "relax": [20, 24, 37, 39, 42, 50, 57], "inadvert": 20, "around": [20, 30, 31, 52, 53, 55], "weaker": 20, "itertool": 20, "perf_count": [20, 30, 33], "pc": [20, 30, 33], "tqdm": [20, 30], "subprocess": 20, "listavailablesolv": 20, "shell_command": 20, "help": [20, 35, 57, 63, 65], "check_output": 20, "shell": 20, "decod": 20, "startswith": 20, "endswith": 20, "getsolvernam": 20, "try": [20, 25, 38, 50, 53, 63, 66, 68], "switchcutsoff": 20, "solver_nam": 20, "elif": [20, 24, 34], "mip_cuts_bqp": 20, "mip_cuts_cliqu": 20, "mip_cuts_cov": 20, "mip_cuts_disjunct": 20, "mip_cuts_flowcov": 20, "mip_cuts_pathcut": 20, "mip_cuts_gomori": 20, "mip_cuts_gubcov": 20, "mip_cuts_impli": 20, "mip_cuts_localimpli": 20, "mip_cuts_liftproj": 20, "mip_cuts_mircut": 20, "mip_cuts_mcfcut": 20, "mip_cuts_rlt": 20, "mip_cuts_zerohalfcut": 20, "ergo": 20, "definit": [20, 38, 40, 42, 48, 50, 58, 63], "xpress": [20, 21, 22, 55], "cutstrategi": 20, "switchpresolveoff": 20, "preprocessing_presolv": 20, "limitsolvetim": 20, "max_in_second": 20, "timelimit": 20, "time_limit": 20, "maxtim": [20, 22], "closureformaxtim": 20, "compos": [20, 68], "arg": [20, 35, 37, 42, 45, 50, 68], "kwarg": [20, 35, 42, 50], "func": [20, 35, 68], "initial_solv": 20, "appsi_cbc": 20, "gloa": 20, "lbb": 20, "loa": 20, "ric": 20, "mindtpi": 20, "ecp": 20, "fp": [20, 35, 37, 42], "goa": 20, "oa": [20, 46, 47], "mpec_minlp": 20, "mpec_nlp": 20, "multistart": 20, "fsolv": 20, "newton": 20, "root": 20, "secant": 20, "trustregion": 20, "facilitylocationcommon": 20, "chooseonefacil": 20, "facilitylocationweak": 20, "weak": 20, "serveifopen": 20, "facilitylocationstrong": 20, "getsolut": 20, "generatefacilitylocationinst": 20, "noffacil": 20, "nofcustum": 20, "xc": [20, 27], "randint": [20, 27, 30, 45, 57], "yc": [20, 27], "xf": [20, 21], "dist": [20, 24], "showfacilityloc": 20, "gca": [20, 29, 35, 55], "proper": [20, 48, 52, 65], "hood": 20, "clever": 20, "gurobipi": 20, "cp310": 20, "manylinux2014_x86_64": 20, "whl": 20, "mb": 20, "2k": 20, "90m": 20, "0m": 20, "32m12": 20, "31m48": 20, "eta": 20, "36m0": 20, "25hinstal": 20, "22": [20, 22, 24, 25, 29, 30, 35, 37, 39, 53, 62, 66], "manylinux1_x86_64": 20, "32m44": 20, "31m20": 20, "32m72": 20, "31m8": 20, "25hrequir": 20, "0a0": 20, "usr": 20, "local": [20, 35, 39, 68, 69], "lib": [20, 29, 31, 35], "python3": [20, 29, 31, 35], "23": [20, 24, 25, 29, 35, 37, 42, 45, 53, 58, 62, 66, 69], "available_solv": 20, "appsi_cplex": 20, "appsi_gurobi": 20, "cplex_direct": 20, "cplex_persist": 20, "gurobi_direct": [20, 30, 39, 45], "gurobi_persist": 20, "xpress_direct": 20, "xpress_persist": 20, "subplots_adjust": 20, "hspace": 20, "licens": [20, 45], "path": [20, 29, 31, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 57, 58], "file": [20, 35, 68], "init": 20, "fico": 20, "xpauth": 20, "xpr": 20, "increasingli": [20, 30, 51, 66], "faster": [20, 23, 30, 33, 48, 63], "solveinst": 20, "fromkei": 20, "leav": [20, 27, 50, 59, 60], "rfind": 20, "warn": [20, 30, 35, 42, 50, 57, 66], "solverresult": 20, "abort": 20, "classic": [21, 22, 37, 40, 47], "hous": [21, 46, 47, 49], "patient": 21, "hospit": 21, "meal": 21, "fast": [21, 29], "restaur": [21, 22], "devic": [21, 42, 51, 63], "durat": [21, 22], "makespan": 21, "christel": [21, 22], "gueret": [21, 22], "christian": [21, 22, 25], "prin": [21, 22], "marc": [21, 22], "sevaux": [21, 22], "mp": [21, 22], "flow": [21, 28, 29, 39, 61, 66], "minut": [21, 24, 35, 62], "yellow": [21, 35], "28": [21, 25, 29, 35, 37, 39, 45, 49, 53, 62, 66], "decompos": 21, "until": [21, 22, 23, 33, 37, 39, 42, 47, 55, 59, 63], "prerequisit": 21, "json": 21, "dur": [21, 53], "paper_1": 21, "prec": 21, "paper_2": 21, "paper_3": 21, "preced": [21, 29], "start_": 21, "wise": 21, "conflict": [21, 33, 42], "jobshopmodel": 21, "jobshop_model": 21, "cross": [21, 29, 31, 39], "taskord": 21, "establish": [21, 29, 62], "minimize_makespan": 21, "finish_task": 21, "no_overlap": [21, 23, 27], "pyomomodel": 21, "0x7f90cf08ad60": 21, "jobshop_solv": 21, "jobshop": 21, "87": [21, 29, 31, 42, 62], "64": [21, 29, 32, 35, 65, 66], "59": [21, 29, 49], "nschedul": 21, "sort_valu": [21, 22, 25, 53], "mpl": 21, "bar_styl": [21, 53], "solid_capstyl": [21, 22, 24, 37, 53], "butt": [21, 22, 24, 37, 53], "text_styl": [21, 53], "bold": [21, 22, 27, 34, 37, 53], "center": [21, 22, 24, 25, 27, 34, 37, 42, 46, 49, 53, 55, 56], "va": [21, 22, 25, 27, 37, 47, 53], "dark2": 21, "jdx": 21, "mdx": 21, "xs": [21, 24], "idx": [21, 30, 42, 50], "attent": [21, 50], "dunn": 21, "2013": [21, 39, 63], "recip": 21, "mixer": 21, "reactor": 21, "recipe_to_task": 21, "recipea": 21, "recipeb": 21, "recipec": 21, "a1": 21, "a2": 21, "a3": 21, "a4": 21, "took": [21, 29], "gain": [21, 29, 30, 31], "append": [21, 29, 31, 37, 38, 48, 50, 52, 55, 57, 63, 68], "b1": 21, "b2": 21, "equip": 21, "vee": [21, 26], "jobshopmodel_clean": 21, "jobshop_model_clean": 21, "tclean": 21, "hull": [21, 23], "intermedi": [21, 39, 68], "vessel": 21, "precid": 21, "sequenc": [21, 22, 23, 29, 31, 53, 68], "zw": 21, "basi": [21, 29, 57, 62], "jobshop_model_clean_zw": 21, "mode": [21, 23, 34, 35, 57], "appleg": 21, "david": [21, 46, 69], "william": [21, 46, 47], "cook": 21, "orsa": 21, "journal": [21, 29, 37, 44, 46, 47, 49], "149": [21, 62], "156": [21, 27], "pdf": [21, 29, 37, 39, 45, 46, 47, 49, 60, 64], "beaslei": 21, "electron": 21, "mail": 21, "societi": [21, 44], "41": [21, 29, 37, 49, 62, 63, 65], "1069": 21, "1072": 21, "gu\u00e9ret": 21, "contract": [21, 32], "1999": [21, 37, 44, 45], "00034": 21, "mann": 21, "alan": 21, "1960": 21, "219": 21, "223": [21, 24], "slow": 21, "frequent": [21, 42, 50, 69], "accommod": [21, 23, 29, 33], "descreas": 21, "consequ": [21, 39, 42, 50, 62], "busi": [22, 24, 37, 45, 62, 64], "student": [22, 33, 45, 69], "courier": 22, "server": 22, "wait": [22, 29], "thread": 22, "assembl": 22, "heurist": [22, 27, 29], "address": [22, 32, 37, 47, 64], "past": [22, 62], "scenario": [22, 29, 55, 57, 60, 64, 66, 68, 69], "schedule_job": 22, "seq": [22, 45], "27": [22, 25, 29, 53, 65], "line2d": 22, "width": [22, 29, 33, 34, 35, 39, 45, 53, 55], "window": [22, 35], "fill_between": [22, 25, 27, 37, 41, 45], "total_past_du": 22, "spine": [22, 37], "set_vis": [22, 37, 53], "custom_lin": 22, "savefig": [22, 24, 29, 52], "machinescheduling_": 22, "svg": [22, 24, 52], "dpi": [22, 24, 52], "bbox_inch": [22, 24, 29, 52], "31": [22, 25, 29, 65, 66], "priorit": 22, "familiar": [22, 24, 37, 41, 45, 68], "homework": 22, "circumst": [22, 69], "late": 22, "longest": 22, "twice": [22, 29, 65], "famili": [22, 24, 30, 50], "disjuct": 22, "machine_schedul": 22, "orderd": 22, "job_releas": 22, "job_dur": 22, "past_due_constraint": 22, "xor": [22, 23, 24, 26, 27, 64], "machine_deconflict": 22, "job_a": 22, "job_b": 22, "minimize_past": 22, "optimalschedul": 22, "extract_valu": [22, 57], "outperform": 22, "nonetheless": 22, "tackl": [22, 30], "z_": [22, 39, 44, 50, 62], "slower": [22, 33], "machine_schedulemilo": 22, "machine_deconflict_a": 22, "machine_deconflict_b": 22, "optimalschedule_milo": 22, "c_t": [23, 30], "shut": 23, "dure": [23, 25, 33, 35, 39, 64, 69], "x_t": 23, "abl": [23, 29, 30, 33, 45], "earn": [23, 39], "y_t": [23, 30], "overlap": [23, 25, 27], "consecut": [23, 25], "ldot": [23, 25, 27, 29, 30, 31, 33, 37, 42, 44, 50, 53, 62, 63, 65], "sai": [23, 29, 30, 31, 33, 35, 55, 65], "exclus": [23, 24, 26, 27, 37], "convex": [23, 28, 29, 37, 38, 41, 45, 46, 47, 49, 50, 55, 58], "plane": [23, 45, 53, 62], "maintenance_plan": 23, "required_mainten": 23, "required_shutdown": 23, "plot_schedul": 23, "tab20": [23, 24, 27, 33], "daili": [23, 25, 26], "set_tick": 23, "set_ticklabel": 23, "length": [23, 24, 29, 31, 37, 50], "rng": [23, 27, 52, 55, 62, 63, 65, 66], "default_rng": [23, 52, 55, 62, 63, 65, 66], "shutdown": 23, "safe": 23, "decreas": [23, 45, 66], "_t": 23, "upos_max": 23, "3334": 23, "uneg_max": 23, "maintenance_planning_ramp": 23, "upo": 23, "uneg": 23, "skip": [23, 24, 37, 68, 69], "frequenc": [23, 49, 62, 66], "particularli": [23, 30, 32, 66, 69], "revis": [23, 39], "postpon": 23, "wedg": 23, "summat": [23, 39, 41, 53, 64], "termin": [23, 30, 32, 39, 55, 59], "paradox": [23, 47], "maintenance_planning_ramp_oper": 23, "sumi": 23, "sprd": 23, "comment": [23, 29, 35, 63, 69], "disj": 23, "rather": [23, 29, 32, 37, 40, 45, 50, 62, 65], "hint": 23, "z_t": 23, "systemat": 23, "effort": [23, 27], "visit": 24, "sightse": 24, "tour": 24, "road": [24, 34, 51], "trip": [24, 31], "routin": [24, 69], "pre": [24, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 63, 65, 69], "rest": [24, 25, 33, 65], "stop": [24, 46, 55, 63], "batteri": 24, "driver": 24, "ahead": 24, "rate": [24, 29, 31, 38, 42, 47, 48, 58, 66], "distanc": [24, 42, 50, 69], "arbitrari": [24, 41, 53], "drive": [24, 35], "littl": [24, 32, 35, 63, 68, 69], "c_": [24, 29, 34, 37], "150": [24, 29, 31, 32, 33, 37, 44, 55, 60, 62, 64], "kw": [24, 42, 50], "unforeseen": 24, "event": [24, 29, 59], "never": [24, 42, 50, 55], "drop": [24, 37, 46, 66], "comfort": 24, "lost": [24, 30, 46, 63], "assumpt": [24, 29, 55, 57, 58, 62], "travel": [24, 29, 51, 62], "speed": [24, 42, 50, 66], "km": 24, "discharg": 24, "kwh": 24, "elaps": [24, 33], "d_i": [24, 27, 35, 45, 57, 65, 66], "c_i": [24, 35, 45, 57, 65, 66], "arriv": [24, 29, 32, 34, 50, 53, 55, 63], "arr": [24, 53], "dep": [24, 53], "d_": [24, 29, 59], "r_i": [24, 27, 38, 47, 48, 58, 65], "t_i": [24, 44, 45], "script": [24, 29, 62], "departur": [24, 53], "opportun": [24, 31, 59, 63, 68], "That": [24, 42, 46, 50, 53, 62, 66], "heterogen": 24, "n_charging_st": 24, "randomli": 24, "cumsum": [24, 27, 46], "triangular": 24, "02d": [24, 25, 53], "s00": 24, "112": [24, 45, 49, 57, 60], "s01": 24, "294": 24, "s02": 24, "439": 24, "s03": 24, "517": 24, "s04": 24, "598": 24, "s05": 24, "729": 24, "s06": 24, "773": 24, "s07": 24, "933": 24, "s08": 24, "1070": 24, "s09": 24, "1210": [24, 55], "s10": 24, "1340": 24, "s11": 24, "1475": 24, "s12": 24, "s13": 24, "1680": 24, "s14": 24, "1798": 24, "s15": 24, "1883": 24, "s16": 24, "1998": [24, 37, 45], "s17": 24, "2087": 24, "s18": 24, "2208": 24, "19": [24, 25, 29, 32, 37, 38, 39, 41, 48, 53, 62, 65, 66], "s19": 24, "2259": 24, "plot_stat": 24, "ys": 24, "fontsiz": [24, 27, 30, 32, 37, 39, 45, 53], "275": [24, 55], "c_max": 24, "c_min": 24, "veloc": 24, "t_lost": 24, "t_rest": 24, "r_max": 24, "ev_plan": 24, "on_rout": 24, "ev": [24, 59], "segment": 24, "c_arr": 24, "c_dep": 24, "t_arr": 24, "t_dep": 24, "r_arr": 24, "r_dep": 24, "min_tim": [24, 53], "drive_tim": 24, "rest_tim": 24, "drive_dist": 24, "thtat": 24, "disjunct_1": 24, "disjunct_2": 24, "t_stop": 24, "nan": [24, 35, 64, 66], "122000": 24, "123": [24, 27], "072000": 24, "949000": 24, "157187": 24, "79": [24, 29, 35, 49, 66], "224000": 24, "83": [24, 29, 42], "376000": 24, "208187": 24, "603187": 24, "48": [24, 29, 35, 37, 39, 45, 64, 65, 66], "672000": 24, "381187": 24, "162973": 24, "91": [24, 29, 31, 42, 50], "512000": 24, "781787": 24, "972973": 24, "284973": 24, "584000": 24, "725973": 24, "605680": 24, "304000": 24, "879707": 24, "199680": 24, "63": [24, 29, 41, 44, 60, 62, 63], "048000": 24, "576680": 24, "079107": 24, "576000": 24, "502427": 24, "478107": 24, "124773": 24, "646666": 24, "421773": 24, "872000": 24, "772773": 24, "941662": 24, "448000": 24, "781333": 24, "168889": 24, "161662": 24, "501333": 24, "992662": 24, "433747": 24, "37": [24, 29, 37, 39, 49, 55, 62], "557333": 24, "78": [24, 29, 52, 63], "720000": [24, 29], "441085": 24, "609747": 24, "496000": 24, "463747": 24, "742253": 24, "960000": 24, "278506": 24, "887253": 24, "480000": [24, 29], "907253": 24, "visualizeevplan": 24, "xv": 24, "cv": 24, "linewidth": [24, 35], "ev_result": 24, "entitl": [25, 50], "carballo": 25, "lozano": 25, "post": [25, 53, 69], "campu": 25, "primarili": 25, "eight": 25, "morn": [25, 62], "night": [25, 35], "sundai": 25, "employe": 25, "saturdai": 25, "principl": [25, 63, 69], "ten": [25, 65], "predetermin": [25, 37], "staf": [25, 63], "seven": 25, "weekend": [25, 62], "recap": 25, "w_1": 25, "w_2": 25, "w_n": [25, 46, 47, 49], "mon": 25, "tue": 25, "sun": [25, 44, 46, 49], "slot": [25, 33], "e_": [25, 62], "fill": [25, 32, 55, 57, 64], "n_w": 25, "e_w": 25, "loop": [25, 29, 37, 55, 69], "24h": 25, "d_1": 25, "s_1": 25, "d_2": 25, "s_2": 25, "d_3": 25, "s_3": 25, "mind": [25, 63], "beyond": 25, "shift_schedul": 25, "avaiabl": 25, "wed": [25, 30], "fri": 25, "sat": 25, "suffici": [25, 29, 32, 37, 63], "required_work": 25, "forti": 25, "forty_hour_limit": 25, "required_rest": 25, "d1": 25, "s1": 25, "d2": 25, "s2": 25, "d3": 25, "s3": 25, "is_need": 25, "is__weekend": 25, "minimize_work": 25, "particip": [25, 32, 65], "patch": [25, 27, 45, 55], "rectangl": [25, 27, 32, 45, 55], "bw": [25, 47], "colormap": 25, "add_patch": [25, 27, 45, 55], "id": [25, 37, 53, 66], "categori": [25, 57, 62, 68], "categoricaldtyp": 25, "worker_typ": 25, "day_typ": 25, "shift_typ": 25, "w06": 25, "w07": 25, "w01": 25, "w03": 25, "w04": 25, "w02": 25, "w05": 25, "receiv": [25, 29, 31, 32, 35, 37, 39, 45, 46, 51], "worker_schedul": 25, "groupbi": [25, 35, 52, 57], "nwork": 25, "to_str": 25, "w08": 25, "w09": 25, "w10": 25, "day_schedul": 25, "nshift": 25, "discret": [26, 39, 46, 57, 62], "proposit": 26, "truth": 26, "technolog": [26, 39], "production_x": [26, 69], "production_i": [26, 69], "maximize_profit": 26, "labora": 26, "laborb": 26, "highli": [26, 32, 68], "assess": [26, 42, 52, 60], "benefici": 26, "underbrac": [26, 31, 39, 59], "40x": [26, 69], "30y": [26, 69], "60x": 26, "embed": [26, 29, 42, 45, 50, 68], "old": [26, 32], "profit_constr_1": 26, "profit_constr_2": 26, "laborb_1": 26, "laborb_2": 26, "3600": [26, 59], "benefit": [26, 32, 39, 65, 68, 69], "intellig": [26, 29], "partit": [26, 62], "sub": 26, "support": [26, 29, 36, 43, 45, 46, 49, 55, 68, 69], "sp": [27, 37], "onto": [27, 50], "shortest": [27, 29], "edg": [27, 29, 30, 32, 33, 34, 53, 65, 66], "guillotin": 27, "rectangular": 27, "motiv": [27, 32, 37], "industri": [27, 35, 39, 49, 57], "placement": 27, "macro": 27, "semiconductor": 27, "layout": [27, 34, 35, 45], "wood": 27, "textil": 27, "lai": 27, "workstat": 27, "bandwidth": 27, "endpoint": 27, "co_2": 27, "oil": [27, 39], "recoveri": 27, "combinatori": 27, "belong": 27, "grow": [27, 46, 64], "exponenti": [27, 46, 47, 49], "though": [27, 47], "depth": 27, "w_i": 27, "concret": 27, "millimet": 27, "generate_box": 27, "max_width": 27, "max_depth": 27, "deepest": 27, "154": [27, 50, 52], "176": [27, 35, 66], "121": [27, 49], "175": [27, 35, 49, 55, 60, 62, 66], "196": [27, 57], "186": [27, 49], "85": [27, 29, 35, 42, 62, 66], "126": [27, 31], "99": [27, 29, 31, 33, 35, 49, 66], "352": 27, "divid": [27, 42, 46, 49, 50], "lb": [27, 44, 45, 46, 47, 49, 50, 55, 69], "front": 27, "coordin": [27, 45], "corner": 27, "degre": [27, 29, 37, 49, 50, 57, 63], "frame": 27, "trivial": [27, 46, 65], "arrang": [27, 28, 32, 42], "pack_boxes_v0": 27, "copi": [27, 37, 39, 52, 53, 63], "show_box": 27, "facecolor": [27, 45], "annot": [27, 39, 45], "292": 27, "431": [27, 55], "552": 27, "748": 27, "1060": 27, "1125": 27, "370": 27, "occupi": 27, "vertic": [27, 33, 42, 55], "drawn": 27, "reproduc": [27, 42], "lineup": 27, "prevent": 27, "doesn": [27, 30], "assur": [27, 69], "pack_boxes_v1": 27, "minimize_width": 27, "bounding_box": 27, "987": 27, "833": [27, 52], "694": 27, "573": 27, "377": 27, "191": [27, 44], "surpris": [27, 37], "did": [27, 30, 39, 50, 66], "tightli": [27, 41], "orient": [27, 57], "pack_boxes_v2": 27, "yloc": 27, "743": 27, "814": 27, "487": 27, "366": [27, 35], "249": [27, 44], "164": 27, "obvious": 27, "closer": 27, "stack": [27, 50, 62], "deeper": 27, "pack_boxes_v3": 27, "height": 27, "376": 27, "239": [27, 45], "256": [27, 55, 62], "307": 27, "382": 27, "338": 27, "372": [27, 29], "unchang": [27, 62], "especi": [27, 29, 33, 69], "suscept": [27, 35, 65, 66], "trespalacio": 27, "grossmann": 27, "modif": [27, 55, 63], "2017": [27, 46, 47, 49], "annal": 27, "258": 27, "747": [27, 29, 52], "759": 27, "doi": [27, 29, 39], "1007": [27, 39], "s10479": 27, "016": [27, 45], "2112": 27, "pack_boxes_v4": 27, "261": [27, 35], "267": 27, "253": [27, 35, 44], "243": [27, 55], "dealt": 28, "oblivi": 28, "dinner": 28, "seat": [28, 61], "transport": [28, 32, 34, 39, 64], "franchis": 28, "gasolin": [28, 41], "graph": [28, 30, 32, 34, 35, 53], "cryptocurr": 28, "arbitrag": 28, "energi": [28, 44, 51, 56, 61, 65], "dispatch": [28, 56, 61, 65], "forex": 28, "liquid": 29, "owner": [29, 42], "currenc": [29, 31], "wallet": 29, "transact": [29, 31], "risk": [29, 31, 38, 42, 48, 50, 57, 58, 63, 65, 66], "hypothesi": [29, 39], "exploit": [29, 30, 31], "reach": [29, 30, 39, 55], "equilibrium": [29, 66], "fleet": [29, 51], "rapid": [29, 31], "trader": [29, 31], "march": 29, "propag": 29, "diagram": [29, 39, 45], "restart": 29, "kernel": [29, 44, 45, 46, 47, 49, 55, 57], "jeff": [29, 31], "anaconda3": [29, 31], "site": [29, 31, 35], "api": 29, "aiodn": 29, "aiohttp": 29, "setuptool": 29, "certifi": 29, "2018": [29, 45, 46, 49], "2022": [29, 31, 39, 40, 46, 49], "request": [29, 35], "yarl": 29, "cryptographi": 29, "pycar": 29, "aiosign": 29, "frozenlist": 29, "charset": 29, "multidict": 29, "async": 29, "timeout": [29, 35], "0a3": 29, "attr": 29, "cffi": 29, "urllib3": 29, "idna": 29, "pycpars": 29, "os": [29, 37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 66], "timeit": [29, 37], "default_tim": 29, "timer": 29, "nx": [29, 30, 31, 33, 35, 53, 65, 66], "3d": [29, 35, 45], "ljust": 29, "ac": [29, 45], "alpaca": 29, "ascendex": 29, "bequant": 29, "bigon": 29, "binanc": 29, "binancecoinm": 29, "binanceu": 29, "binanceusdm": 29, "bit2c": 29, "bitbank": 29, "bitbai": 29, "bitbn": 29, "bitcoincom": 29, "bitfinex": 29, "bitfinex2": 29, "bitflyer": 29, "bitforex": 29, "bitget": 29, "bithumb": 29, "bitmart": 29, "bitmex": 29, "bitopro": 29, "bitpanda": 29, "bitru": 29, "bitso": 29, "bitstamp": 29, "bitstamp1": 29, "bittrex": 29, "bitvavo": 29, "bkex": 29, "bl3p": 29, "blockchaincom": 29, "btcalpha": 29, "btcbox": 29, "btcex": 29, "btcmarket": 29, "btctradeua": 29, "btcturk": 29, "buda": 29, "bybit": 29, "cex": 29, "43": [29, 37, 45, 52], "coinbas": 29, "coinbaseprim": 29, "coinbasepro": 29, "46": 29, "coincheck": 29, "coinex": 29, "coinfalcon": 29, "49": [29, 37, 49], "coinmat": 29, "coinon": 29, "coinspot": 29, "cryptocom": 29, "53": [29, 35, 37, 40, 65, 66], "currencycom": 29, "55": [29, 32, 49, 60], "deribit": 29, "digifinex": 29, "exmo": 29, "flowbtc": 29, "fmfwio": 29, "gate": 29, "61": [29, 45, 63], "gateio": 29, "gemini": 29, "hitbtc": 29, "hitbtc3": 29, "hollaex": 29, "huobi": 29, "huobijp": 29, "huobipro": 29, "69": [29, 65], "idex": 29, "70": [29, 37, 62], "independentreserv": 29, "indodax": 29, "itbit": 29, "73": [29, 32, 33, 35, 37, 60, 65], "kraken": 29, "74": 29, "krakenfutur": 29, "kucoin": 29, "kucoinfutur": 29, "77": [29, 52, 66], "kuna": 29, "latoken": 29, "lbank": 29, "lbank2": 29, "luno": 29, "lykk": 29, "mercado": 29, "mexc": 29, "mexc3": 29, "ndax": 29, "novadax": 29, "oceanex": 29, "okcoin": 29, "okex": 29, "okex5": 29, "92": [29, 37, 50], "okx": 29, "93": [29, 31, 34, 45, 50, 63], "paymium": 29, "94": [29, 42, 50], "phemex": 29, "poloniex": 29, "96": [29, 35, 37, 42], "poloniexfutur": 29, "probit": 29, "ripio": 29, "stex": 29, "tidex": 29, "timex": 29, "102": [29, 32, 35, 50, 66], "tokocrypto": 29, "103": [29, 44, 60], "upbit": 29, "wavesexchang": 29, "105": [29, 37, 60], "wazirx": 29, "106": 29, "whitebit": 29, "107": [29, 49, 62, 64], "woo": 29, "108": [29, 35, 41, 64], "yobit": 29, "109": [29, 48, 49], "zaif": 29, "110": [29, 35, 44, 49, 66], "111": [29, 39, 42, 49, 53], "zonda": 29, "terminolog": [29, 33], "host": 29, "slash": 29, "quot": [29, 35], "denomin": [29, 44], "eth": 29, "btc": 29, "ethereum": 29, "bitcoin": 29, "bid": [29, 31], "node": [29, 30, 31, 32, 33, 34, 35, 53, 57, 65, 66], "destin": [29, 32, 69], "sampl": [29, 42, 50, 55, 57, 62, 65, 66], "get_exchange_dg": 29, "minimum_in_degre": 29, "load_market": 29, "dg": [29, 53], "digraph": [29, 30, 31, 32, 34, 35, 53], "add_edg": [29, 31, 53], "in_degre": 29, "remove_nod": 29, "out_degre": 29, "topological_sort": 29, "gold": [29, 32], "lightblu": [29, 31, 32, 34], "draw_dg": 29, "rad": 29, "draw": [29, 33, 34, 45, 47, 53], "n_node": 29, "po": [29, 31, 33, 34, 35, 41, 53], "circular_layout": [29, 53], "draw_networkx": [29, 31], "with_label": [29, 31, 33, 34], "node_color": [29, 31, 33, 35], "edge_color": [29, 34, 35, 53], "node_s": [29, 31, 33, 35, 53], "font_siz": [29, 34], "arrows": [29, 31], "connectionstyl": 29, "arc3": 29, "draw_networkx_edge_label": [29, 31, 34], "edge_label": [29, 31, 34], "src": [29, 32, 69], "dst": [29, 32, 69], "exchange_dg": 29, "170": [29, 37, 49, 64], "522": 29, "match": [29, 30, 35, 57, 66], "buyer": 29, "incom": [29, 30, 31, 39, 53, 65], "highest": [29, 47], "binance_us_orderbook_20230313_152616": 29, "order_book": 29, "githubusercont": [29, 35, 42, 50, 57, 65, 66], "com": [29, 31, 35, 37, 39, 42, 44, 45, 46, 47, 48, 49, 50, 57, 65, 66, 68], "main": [29, 35, 42, 50, 57, 65, 66], "glob": 29, "fname": 29, "orderbook": 29, "nread": 29, "binance_us_orderbook_sav": 29, "timestamp": 29, "bid_pric": 29, "bid_volum": 29, "ask_pric": 29, "ask_volum": 29, "06": [29, 38, 48, 60, 65], "529": 29, "069735": 29, "012000": 29, "069759": 29, "050000": 29, "bnb": 29, "012743": 29, "012755": 29, "ada": 29, "637": [29, 35, 45, 63], "2168": 29, "sol": [29, 57], "000935": 29, "420000": 29, "000936": 29, "120000": [29, 39], "matic": 29, "000052": 29, "200000": [29, 35, 39], "mana": 29, "848": 29, "000027": 29, "831": 29, "1409": 29, "trx": 29, "905": 29, "000003": 29, "25352": 29, "960": 29, "000214": 29, "994": 29, "900000": 29, "891": 29, "600000": [29, 35], "usdt": 29, "07": [29, 38, 48], "23373": 29, "920000": 29, "118619": 29, "23376": 29, "045275": 29, "065": 29, "1630": 29, "950000": 29, "770000": 29, "500000": [29, 32], "297": 29, "857700": 29, "800000": [29, 35], "891900": 29, "172": [29, 62], "348630": 29, "348750": 29, "511": 29, "busd": 29, "226": 29, "999500": 29, "293433": 29, "930000": 29, "999600": 29, "317175": 29, "730000": 29, "288": [29, 64], "857000": 29, "870000": 29, "863500": 29, "usdc": 29, "342": [29, 49], "000100": 29, "307657": 29, "000200": 29, "299181": 29, "394": 29, "203000": 29, "1664": 29, "205000": 29, "5405": 29, "447": 29, "631000": 29, "157": [29, 46, 49, 50], "632200": 29, "571": 29, "501": 29, "069280": 29, "10824": 29, "069330": 29, "10818": 29, "612": [29, 35, 55], "23371": 29, "440000": 29, "021500": 29, "830000": 29, "665": 29, "763000": 29, "670000": 29, "952500": 29, "340000": 29, "719": [29, 35], "210000": 29, "510000": 29, "760000": 29, "255000": 29, "772": 29, "203410": 29, "623": 29, "100000": [29, 32, 45], "204540": 29, "415": [29, 44, 45, 66], "893": 29, "999900": 29, "329027": 29, "279879": 29, "620000": 29, "950": [29, 35], "630700": 29, "632100": 29, "3054": 29, "003": [29, 45], "348000": 29, "6582": 29, "349000": 29, "997": 29, "056": [29, 62], "390000": 29, "181": [29, 49], "090000": 29, "114": [29, 35, 66], "069290": 29, "10823": 29, "069390": 29, "25220": 29, "400000": [29, 35], "660000": 29, "020000": 29, "990000": 29, "051000": 29, "160000": 29, "810000": 29, "215000": 29, "298": [29, 65, 66], "520000": 29, "880000": 29, "201": [29, 44, 45], "080000": 29, "368": [29, 52], "348200": 29, "8615": 29, "349400": 29, "2433": 29, "433": [29, 45], "23366": 29, "049540": 29, "23394": 29, "360000": 29, "049500": 29, "485": 29, "1629": 29, "890000": 29, "497400": 29, "1631": 29, "490000": 29, "usd": [29, 31], "010000": 29, "007463": 29, "048805": 29, "675": 29, "564550": 29, "740000": 29, "580700": 29, "730": 29, "10407": 29, "954839": 29, "680000": 29, "782": 29, "900200": 29, "342000": 29, "835": 29, "348800": 29, "348900": 29, "3000": [29, 45, 64], "942": 29, "79157": 29, "795593": 29, "204000": 29, "937": [29, 35], "204500": 29, "09": [29, 32, 38, 48, 57], "5050": 29, "300000": 29, "517682": 29, "170000": 29, "631600": 29, "572": 29, "155": [29, 31, 50, 62], "999100": 29, "4534": 29, "7591": 29, "820000": 29, "858100": 29, "865900": 29, "290000": 29, "069200": 29, "225602": 29, "069400": 29, "224245": 29, "prospect": 29, "counter": 29, "rightarrow": [29, 31, 40, 42, 46, 50, 68], "v_b": 29, "v_q": 29, "held": [29, 59], "convers": [29, 31, 41, 44], "arc": [29, 30, 31, 34, 53], "chanc": [29, 46, 56, 65], "highlight": [29, 35, 44, 53], "order_book_to_dg": 29, "dg_order_book": 29, "isnan": 29, "order_book_dg": 29, "5s": 29, "16f": 29, "4668": 29, "534080": 29, "190981": 29, "335068": 29, "003488": 29, "403701": 29, "038263": 29, "66844": 29, "919786": 29, "032433": 29, "1068": 29, "261938": 29, "014154": 29, "19391": 29, "118868": 29, "007746": 29, "36968": 29, "576710": 29, "038113": 29, "335570": 29, "469799": 29, "075549": 29, "000043": 29, "1058": 29, "348400": 29, "000613": 29, "815": 29, "385000": 29, "003357": 29, "313520": 29, "867384": 29, "178": [29, 35, 49, 66], "281000": 29, "000400": 29, "317048": 29, "859708": 29, "045738": 29, "502": 29, "860500": 29, "999800": 29, "299240": 29, "836200": 29, "829876": 29, "6513": 29, "748000": 29, "581778": 29, "360": [29, 35, 45, 64, 66], "986200": 29, "423770": 29, "053538": 29, "601845": 29, "003356": 29, "399": [29, 45, 59], "256350": 29, "843800": 29, "830192": 29, "499": 29, "884100": 29, "582028": 29, "1930": [29, 37], "433400": 29, "865330": 29, "953000": 29, "045662": 29, "3965": 29, "871000": 29, "411298": 29, "043556": 29, "1192": [29, 52], "226490": 29, "350": [29, 55], "624150": 29, "045704": 29, "4399": 29, "630400": 29, "862049": 29, "850": 29, "125140": 29, "1158": 29, "020820": 29, "2431": 29, "396900": 29, "1140": 29, "900820": 29, "970718": 29, "954935": 29, "163968": 29, "852255": 29, "866151": 29, "1046": 29, "700000": 29, "795513": 29, "920652": 29, "830220": 29, "1129": 29, "218750": 29, "583281": 29, "361": [29, 35], "489944": 29, "7592": 29, "579182": 29, "045733": 29, "927311": 29, "409222": 29, "15562": 29, "637700": 29, "itself": [29, 63], "unifi": 29, "treatment": [29, 31, 39, 62, 64], "pose": [29, 35], "i_0": 29, "i_1": [29, 63], "i_2": [29, 63], "i_": 29, "i_n": 29, "prod_": [29, 47], "i_k": 29, "limits_": [29, 30, 53, 63, 65], "becam": 29, "cyclic": 29, "permut": 29, "daunt": 29, "bellman": [29, 30], "ford": [29, 30, 45], "negative_edge_cycl": 29, "luckili": [29, 36], "find_negative_cycl": 29, "bp": [29, 37], "thicker": 29, "sum_weight": 29, "arb": [29, 31], "exp": [29, 46, 47, 49, 50], "dollar": 29, "smallest": [29, 33, 39], "crude": [29, 39], "pick": [29, 47, 65], "accord": [29, 31, 35, 55], "whatev": 29, "prohibit": [29, 31, 42, 50], "nevertheless": [29, 59], "understand": [29, 63, 65, 69], "simple_cycl": 29, "overlaid": 29, "connect": [29, 33, 53], "203147": 29, "974": 29, "n_cycles_to_list": 29, "774": 29, "699": 29, "673": 29, "n_cycles_to_show": 29, "fresh": 29, "crypto3": 29, "reli": [29, 45, 66, 68], "secondli": 29, "adjac": [29, 33], "o_j": 29, "outgo": [29, 30, 31, 53, 65], "i_j": 29, "v_j": 29, "v_": [29, 37, 66], "v_0": 29, "crypto_model": 29, "v0": 29, "chain": [29, 31, 35, 68], "t0": [29, 30, 31], "t1": [29, 30, 31, 47], "total_trad": 29, "edge_capac": 29, "out_nod": [29, 53], "in_nod": [29, 53], "vt": 29, "weath": 29, "2d": [29, 42, 45, 50], "10009": 29, "007": [29, 45], "evolut": [29, 52], "visibl": 29, "scheme": 29, "alon": [29, 42, 50], "00000": [29, 44, 49], "00004": 29, "9998": 29, "02600": 29, "97433": 29, "10003": 29, "02700": 29, "97482": 29, "10008": 29, "03000": 29, "10002": 29, "97472": 29, "10007": 29, "97424": 29, "00700": 29, "transcat": 29, "ntransact": 29, "1e": [29, 31, 42, 50], "6f": [29, 49], "9999": 29, "025800": 29, "025997": 29, "974235": 29, "026000": 29, "026811": 29, "974333": 29, "974723": 29, "027000": 29, "027203": 29, "029812": 29, "974820": 29, "697500": 29, "277320": 29, "030000": 29, "000030": 29, "000012": 29, "030703": 29, "000042": 29, "976057": 29, "remind": [29, 31], "0000002": 29, "precis": [29, 33, 42, 45, 50, 60], "printout": 29, "00746": 29, "28100": 29, "69750": 29, "85971": 29, "20002": 29, "20010": 29, "031012": 29, "05354": 29, "27732": 29, "87000": 29, "62000": 29, "03100": 29, "031000": 29, "20011": 29, "00600": 29, "006000": 29, "16397": 29, "02580": 29, "17000": [29, 64], "xlabel": [29, 30, 35, 38, 40, 46, 48, 53, 55, 57, 64, 66, 68], "ylabel": [29, 30, 35, 38, 40, 46, 48, 55, 57, 64, 66, 68], "gcf": 29, "realiti": [29, 43], "presenc": [29, 39, 47, 50], "affect": [29, 51, 53, 55, 60, 61, 63], "streamlit": 29, "detect": [29, 30, 31, 42, 50], "fetch_order_book": 29, "criteria": [29, 44], "get_order_book": 29, "get_ord": 29, "millisecond": 29, "fetch": 29, "to_datetim": 29, "mininum_in_degre": 29, "888": [29, 37], "065550": 29, "900000e": 29, "065834": 29, "035": 29, "009385": 29, "400000e": 29, "009415": 29, "029000e": 29, "ltc": 29, "002904": 29, "270000e": 29, "002925": 29, "000000e": 29, "328": [29, 35], "000010": 29, "002000e": 29, "120000e": 29, "401": 29, "000208": 29, "705000e": 29, "000210": 29, "710000e": 29, "311": 29, "iost": 29, "006830": 29, "652040e": 29, "007860": 29, "254300e": 29, "312": 29, "855": 29, "961000": 29, "520000e": 29, "079900": 29, "474000e": 29, "313": [29, 32], "floki": 29, "927": 29, "000022": 29, "834030e": 29, "502476e": 29, "314": 29, "xec": 29, "000016": 29, "356363e": 29, "000021": 29, "642790e": 29, "315": [29, 35], "283000": 29, "990000e": 29, "305000": 29, "910000e": 29, "316": [29, 35, 45], "search_tim": 29, "arb_threshold": 29, "utcnow": 29, "strftime": 29, "to_csv": 29, "068": 29, "makarov": 29, "schoar": 29, "2020": [29, 44, 46, 47, 49], "319": 29, "cr\u00e9pelli\u00e8r": 29, "zeisberg": 29, "ssrn": [29, 46, 49], "3606053": 29, "sol3": [29, 46, 49], "cfm": [29, 46, 49], "abstract_id": [29, 46, 49], "academ": [29, 39, 45, 49], "literatur": [29, 39, 44], "peduzzi": 29, "jame": 29, "xu": [29, 44, 60], "septemb": 29, "jack": 29, "THE": 29, "rippler": 29, "decentr": 29, "xrp": 29, "ledger": 29, "3rd": 29, "confer": 29, "blockchain": 29, "innov": [29, 69], "brain": 29, "pp": [29, 45, 46, 47, 49], "ieee": [29, 35], "arxiv": [29, 39, 46, 47, 49], "org": [29, 37, 39, 45, 46, 47, 49], "2106": 29, "16158": 29, "bruzg\u0117": 29, "\u0161apkauskien\u0117": 29, "north": [29, 46, 47, 49], "american": [29, 49], "101562": 29, "1016": 29, "najef": 29, "brief": [29, 68], "107731": 29, "anilpai": 29, "medium": [29, 69], "8938dcea56ea": 29, "crypto": [29, 31], "nbviewer": 29, "rcroessmann": 29, "sharing_publ": 29, "blob": 29, "master": [29, 55, 63], "arbitrage_identif": 29, "ipynb": [29, 35], "byrn": 29, "novel": 29, "decentralis": 29, "www": [29, 31, 37, 39, 44, 45, 46, 47, 49, 64, 68], "scss": 29, "tcd": 29, "ie": 29, "donal": 29, "omahoni": 29, "bfg": 29, "202021": 29, "stephenbyrnedissert": 29, "levu": 29, "berko": 29, "chyrun": 29, "panasyuk": 29, "hrubel": 29, "ceur": 29, "workshop": 29, "proceed": 29, "407": 29, "440": [29, 66], "ws": 29, "vol": [29, 46, 49], "2917": 29, "paper32": 29, "crypocurr": 29, "angeri": 29, "agraw": 29, "evan": 29, "chitra": 29, "boyd": [29, 45, 46, 47, 49], "maker": [29, 57], "asset": [29, 38, 41, 46, 47, 48, 49, 58], "preprint": [29, 46, 47, 49], "2107": 29, "12484": 29, "baincapitalcrypto": 29, "organ": [30, 69], "guest": 30, "mingl": 30, "k_": [30, 46, 49], "sit": 30, "m_f": 30, "far": [30, 36, 63], "ft": 30, "fail": [30, 32, 35, 37], "networkx": [30, 31, 33, 34, 35, 53, 65, 66], "seat_alloc": 30, "kmax": 30, "get_solut": 30, "verbos": [30, 35, 42, 50, 69], "termination_condit": [30, 33, 38, 48, 55, 57, 58, 59, 60, 66], "six": [30, 41, 45], "five": 30, "seatplan": 30, "peculiar": 30, "divers": 30, "bring": [30, 42], "seat_allocation_minimize_group_s": 30, "unfortun": 30, "seat_allocation_minimize_t": 30, "necessarili": 30, "team": [30, 53, 69], "realli": [30, 63], "stand": 30, "arrow": [30, 39], "think": [30, 39, 51, 62, 65], "rephras": 30, "everyon": [30, 32], "seating_allocation_maximize_flow_to_t": 30, "slightli": [30, 35, 40, 45, 48, 51, 53, 55, 65], "door": 30, "target": [30, 42, 50, 62], "nor": [30, 62], "unimpress": 30, "sound": 30, "implicitli": 30, "invok": 30, "model_as_network": 30, "digraphi": 30, "add_edges_from": 30, "flow_valu": 30, "flow_dict": 30, "maximum_flow": 30, "f0": 30, "f1": 30, "f2": 30, "f3": 30, "f4": 30, "f5": 30, "t2": [30, 47], "t3": 30, "t4": 30, "tailor": 30, "magnitud": [30, 42, 55, 63], "405": [30, 62], "\u00b5s": 30, "413": 30, "wall": [30, 44, 46, 47, 49], "414": 30, "max_flow": 30, "reset": 30, "component_data_object": 30, "ctype": 30, "descend_into": 30, "set_valu": 30, "nmax": 30, "mmax": 30, "runtim": 30, "fastest": 30, "transpos": [30, 52], "rotat": [30, 37, 44, 45, 50, 53], "rotation_mod": 30, "anchor": 30, "exchang": 31, "framework": [31, 32, 46, 49], "graphviz": 31, "bank": [31, 49], "japanes": 31, "yen": 31, "jpy": 31, "00761": 31, "eur": 31, "140": [31, 63, 64], "131": 31, "585": 31, "longrightarrow": [31, 68], "9954": 31, "fee": [31, 32], "broker": 31, "needless": 31, "reliabl": [31, 42, 48, 50], "eager": [31, 32], "foreign": 31, "globe": 31, "almost": [31, 42, 46, 47, 57, 63], "autom": 31, "0075": [31, 32], "133": 31, "leftarrow": 31, "0100": [31, 35, 66], "333333": 31, "0000": [31, 32, 39], "tell": 31, "ourselv": 31, "phase": [31, 35, 37], "unencumb": 31, "ne": 31, "credit": 31, "spread": 31, "initial_condit": 31, "max_trad": 31, "nt": 31, "display_graph": 31, "add_nod": [31, 53], "nodelist": 31, "spring_layout": 31, "node_shap": 31, "bloomberg": 31, "tradingview": 31, "extract": [31, 32, 42, 63, 66, 68], "gbp": 31, "chf": 31, "cad": 31, "aud": 31, "hkd": 31, "1096": 31, "0084": 31, "3148": 31, "0677": 31, "7915": 31, "7376": 31, "1279": 31, "9012": 31, "0076": 31, "1849": 31, "9622": 31, "7133": 31, "6647": 31, "1153": 31, "6100": 31, "6097": 31, "9484": 31, "6389": 31, "8816": 31, "4867": 31, "1724": 31, "7606": 31, "8439": 31, "0064": 31, "8121": 31, "6020": 31, "5610": 31, "0973": 31, "9366": 31, "0393": 31, "0079": 31, "2314": 31, "7413": 31, "6908": 31, "1198": 31, "2634": 31, "4019": [31, 52], "0107": 31, "6611": 31, "3489": 31, "9319": 31, "1616": 31, "3557": 31, "5043": 31, "0114": 31, "7825": 31, "4475": 31, "0731": 31, "1734": [31, 35], "8175": 31, "6743": 31, "0659": 31, "2784": 31, "3467": 31, "1877": 31, "7662": 31, "11861": 31, "0527111e": 31, "2486206357100001e": 31, "91269999999999": 31, "9127": 31, "45140205": 31, "1066836e": 31, "41079536e": 31, "4514": 31, "commod": [32, 41, 64], "invit": [32, 45], "pitfal": 32, "uneven": 32, "refin": [32, 37, 39], "didact": [32, 45], "shadow": 32, "yaya": 32, "ga": [32, 35, 39, 65, 66], "grub": 32, "franchisor": 32, "own": [32, 41], "franchise": 32, "truck": [32, 45], "gallon": 32, "charg": [32, 45], "0875": 32, "boost": [32, 50], "alic": 32, "badri": 32, "cara": 32, "dan": 32, "emma": 32, "fujita": 32, "grace": 32, "helen": 32, "subscript": 32, "ship": [32, 69], "d_d": 32, "shipment": [32, 39], "html": [32, 34, 38, 45, 48, 58, 65], "30000": [32, 41], "40000": 32, "50000": 32, "45000": 32, "80000": 32, "br": 32, "to_fram": 32, "cost_to_destin": 32, "shipped_to_destin": 32, "shipped_from_sourc": 32, "supply_constraint": 32, "demand_constraint": [32, 69], "8000": [32, 45], "model1_result": 32, "27387": 32, "26113": 32, "2625": 32, "2490": 32, "3500": [32, 39], "3240": 32, "12000": 32, "38000": 32, "4375": 32, "4321": 32, "1600": 32, "3937": 32, "60000": 32, "7000": 32, "6550": 32, "450": [32, 55, 66], "1575": 32, "1350": 32, "225": [32, 52, 55, 64, 69], "goe": [32, 50], "enthusiasm": 32, "rho": [32, 52, 62], "transport_v2": 32, "delivery_r": 32, "rate_to_destin": 32, "49754": 32, "245": [32, 55], "difficulti": 32, "remedi": 32, "paid": 32, "distributor": [32, 39], "surprisingli": 32, "inspect": [32, 42, 51, 57, 63], "payment": [32, 63], "imposs": [32, 57], "incent": 32, "transport_v3": 32, "allocate_cost": 32, "model3_result": 32, "2502": 32, "122": [32, 39], "3337": 32, "162": 32, "4171": 32, "203": [32, 62], "1668": 32, "3754": 32, "183": [32, 49], "6674": 32, "325": [32, 35, 55], "1501": 32, "inadequ": 32, "marker": [32, 46, 57], "470": 32, "negoti": 32, "rates_index": 32, "083": 32, "081": 32, "09300000000000001": 32, "10099999999999999": 32, "133000": 32, "x_index": 32, "nobject": 32, "nconstraint": 32, "ndecis": 32, "sensit": [32, 42, 50, 51, 69], "0045": 32, "0855": 32, "0795": 32, "node_attr": 32, "edge_attr": 32, "nsuppli": 32, "nship": 32, "nsen": 32, "fillcolor": 32, "ndemand": 32, "lectur": [33, 45], "hall": 33, "exam": 33, "indirect": 33, "hire": 33, "temporari": 33, "staff": 33, "invigil": 33, "obei": 33, "undirect": 33, "th": [33, 38, 44, 57, 58, 65], "ik": [33, 63], "w_k": 33, "jk": [33, 63], "tri": [33, 40], "chromat": 33, "graph_color": 33, "besid": [33, 65, 66], "too": [33, 37, 58, 63, 66], "catch_infeas": 33, "diagnos": 33, "rais": [33, 35, 45, 64], "edge_constraint": 33, "node_constraint": 33, "used_color_constraint": 33, "number_used_color": 33, "catch": [33, 66], "load_solut": 33, "get_color": [33, 41, 46, 60], "unique_label": 33, "color_palett": 33, "label_to_color": 33, "erdo": 33, "renyi": 33, "gnp_random_graph": 33, "is_connect": 33, "kamada_kawai_layout": [33, 34, 35], "start_tim": 33, "terminationcondit": 33, "greedi": 33, "nxcolor": 33, "greedy_color": 33, "logist": [34, 39], "retail": [34, 60], "contin": 34, "outlet": 34, "correspondingli": 34, "character": [34, 37], "b_j": 34, "transship": 34, "rail": 34, "airwai": 34, "sent": [34, 51], "cheapest": 34, "mcf": 34, "draw_networkx_label": [34, 53], "draw_label": 34, "draw_edge_label": 34, "draw_networkx_edg": [34, 35, 53], "draw_edg": 34, "markdown": [34, 38, 48, 58, 65], "draw_network": 34, "edge_flow": [34, 35], "font_color": [34, 53], "edgelist": 34, "arrowstyl": 34, "shifted_po": 34, "font_weight": 34, "mincostflow": 34, "incoming_flow": [34, 35, 65, 66], "outgoing_flow": [34, 35, 65, 66], "flow_conserv": [34, 35, 65, 66], "flow_upper_bound": 34, "noptim": 34, "countri": 35, "renew": [35, 44, 65, 66], "nation": [35, 65], "transmiss": [35, 47], "citi": [35, 44, 57], "district": [35, 57], "inject": 35, "p_i": [35, 47, 57, 65, 66], "f_": [35, 59, 65, 66], "easier": [35, 57, 63], "ji": [35, 65, 66], "control": [35, 41, 57, 66], "school": [35, 39, 69], "law": 35, "theta_": 35, "angl": [35, 66], "mathbf": [35, 47], "theta": [35, 40, 63, 65, 66], "theta_i": [35, 65, 66], "theta_j": [35, 65, 66], "constrat": 35, "dc": 35, "admit": 35, "cheaper": [35, 65], "moreov": [35, 42, 48, 50], "179": [35, 45, 49, 62, 66], "ast": [35, 65, 66], "literal_ev": [35, 65, 66], "make_tupl": [35, 65, 66], "base_url": [35, 57, 65, 66], "nodes_df": [35, 57, 65, 66], "edges_df": [35, 65, 66], "node_id": [35, 57, 65, 66], "to_dict": [35, 42, 50, 57, 65, 66], "edge_id": [35, 65, 66], "example_nod": 35, "example_edg": 35, "httperror": 35, "traceback": 35, "my": [35, 44, 68], "href": 35, "vscode": 35, "20drive": 35, "20repositori": 35, "x13szmlszq": 35, "cach": 35, "pypoetri": 35, "virtualenv": 35, "rd3a6lph": 35, "py3": 35, "_decor": 35, "py": [35, 68], "211": [35, 62], "deprecate_kwarg": 35, "_deprecate_kwarg": 35, "wrapper": [35, 37], "209": [35, 45, 62], "new_arg_nam": 35, "new_arg_valu": 35, "331": 35, "deprecate_nonkeyword_argu": 35, "num_allow_arg": 35, "msg": 35, "_format_argument_list": 35, "allow_arg": 35, "futurewarn": 35, "329": [35, 45], "stacklevel": 35, "find_stack_level": 35, "330": [35, 69], "parser": 35, "filepath_or_buff": 35, "delimit": 35, "header": [35, 42, 50], "usecol": 35, "squeez": 35, "mangle_dupe_col": 35, "engin": [35, 37, 39, 44, 64], "true_valu": 35, "false_valu": 35, "skipinitialspac": 35, "skiprow": 35, "skipfoot": 35, "nrow": 35, "na_valu": 35, "keep_default_na": 35, "na_filt": 35, "skip_blank_lin": 35, "parse_d": 35, "infer_datetime_format": 35, "keep_date_col": 35, "date_pars": 35, "dayfirst": 35, "cache_d": 35, "chunksiz": 35, "compress": 35, "thousand": 35, "decim": [35, 52], "linetermin": 35, "quotechar": 35, "doublequot": 35, "escapechar": 35, "encod": [35, 47, 62, 69], "encoding_error": 35, "dialect": 35, "error_bad_lin": 35, "warn_bad_lin": 35, "on_bad_lin": 35, "delim_whitespac": 35, "low_memori": 35, "memory_map": 35, "float_precis": 35, "storage_opt": 35, "935": 35, "kwds_default": 35, "_refine_defaults_read": 35, "936": 35, "947": 35, "948": 35, "kwd": 35, "_read": 35, "605": 35, "602": [35, 66], "_validate_nam": 35, "604": 35, "textfileread": 35, "607": 35, "608": 35, "1442": 35, "1439": 35, "has_index_nam": 35, "1441": 35, "iohandl": 35, "_engin": 35, "_make_engin": 35, "1735": 35, "1733": [35, 57], "get_handl": 35, "1736": 35, "1737": 35, "1738": [35, 47], "1739": 35, "1740": 35, "1741": 35, "is_text": 35, "1743": 35, "1744": 35, "1745": 35, "1746": 35, "path_or_buf": 35, "710": 35, "codec": 35, "lookup_error": 35, "712": 35, "ioarg": 35, "_get_filepath_or_buff": 35, "714": 35, "715": 35, "716": [35, 42], "717": 35, "721": 35, "722": [35, 52], "basebuff": 35, "363": 35, "362": 35, "req_info": 35, "urllib": 35, "urlopen": 35, "req": [35, 45], "364": [35, 45], "content_encod": 35, "gzip": 35, "overrid": 35, "lazi": 35, "stdlib": 35, "chunk": 35, "263": 35, "pyenv": 35, "216": [35, 37], "cafil": 35, "capath": 35, "cadefault": 35, "214": [35, 45], "215": 35, "_open": 35, "525": 35, "openerdirector": 35, "fullurl": 35, "523": 35, "processor": 35, "process_respons": 35, "524": 35, "meth": 35, "getattr": 35, "meth_nam": 35, "634": 35, "httperrorprocessor": 35, "http_respons": 35, "631": 35, "rfc": 35, "2616": 35, "2xx": 35, "client": [35, 62, 64], "632": 35, "understood": 35, "633": 35, "parent": 35, "635": 35, "hdr": 35, "563": 35, "proto": 35, "561": [35, 38], "http_err": 35, "562": [35, 55], "http_error_default": 35, "orig_arg": 35, "_call_chain": 35, "496": [35, 55], "494": 35, "handler": 35, "495": 35, "497": 35, "498": 35, "643": [35, 52], "httpdefaulterrorhandl": 35, "642": 35, "full_url": 35, "visualize_network": 35, "buse": 35, "solar": [35, 65, 66], "ffcb36": 35, "wind": [35, 51, 57, 61, 65], "hydro": [35, 65, 66], "a5efff": 35, "coal": [35, 65, 66], "686868": 35, "00ab4": 35, "b6b6b6": 35, "vertex2color": 35, "energy_typ": [35, 65, 66], "v2c_list": 35, "draw_networkx_nod": [35, 53], "595959": 35, "set_edgecolor": 35, "set_axis_off": 35, "cyan": 35, "dark": 35, "solarfarm": 35, "windmil": 35, "p_min": [35, 57, 65, 66], "p_max": [35, 57, 65, 66], "c_var": [35, 57, 65, 66], "is_gener": [35, 65, 66], "boolean": [35, 63], "397": 35, "948321": 35, "873": 35, "220980": 35, "993982": 35, "720": 35, "202306": 35, "484861": 35, "180": [35, 44, 45, 62, 64, 69], "602933": 35, "916": 35, "330000": 35, "1146": 35, "1175": 35, "194": [35, 45], "142": [35, 38], "186145": 35, "921628": 35, "884795": 35, "961682": 35, "113": [35, 49, 60, 62, 66], "396000": 35, "864042": 35, "311328": 35, "116": [35, 45, 66], "703998": 35, "242759": 35, "f_max": [35, 65, 66], "271": 35, "5849": [35, 66], "3133": [35, 66], "2593": [35, 66], "5185": [35, 66], "174": [35, 49, 62, 66], "9059": [35, 66], "177": [35, 49, 62, 66], "8216": [35, 66], "246": [35, 45, 66], "9136": [35, 66], "12992": 35, "easiest": [35, 38, 48, 58], "lab": 35, "attr1": 35, "attr2": 35, "bit": 35, "confus": [35, 42, 50], "921627803299574": 35, "realist": [35, 66], "pattern": [35, 63], "96th": 35, "averag": [35, 39, 45, 52, 64, 65, 66], "opf1": 35, "power_gener": 35, "power_flow": 35, "q1": [35, 47], "fab": 35, "fm": 35, "abs_flow": 35, "flows_upper_bound": [35, 65], "generation_upper_bound": [35, 65, 66], "generation_lower_bound": [35, 65, 66], "102898": 35, "emit": 35, "co2": 35, "carbon": 35, "neutral": 35, "dutch": 35, "govern": 35, "inact": 35, "opf2": 35, "q2": [35, 47], "generation_upperound": 35, "max_gas_pl": 35, "max_coal_pl": 35, "53120": 35, "threat": 35, "lift": [35, 68], "m_0": 35, "ym_2": 35, "opf3": 35, "q3": 35, "max_total_renewable_product": 35, "renewable_energy_product": 35, "41608": 35, "view": [35, 58, 62, 65], "wherea": [35, 57, 63, 66], "f_1": [35, 53], "f_2": [35, 53], "f_3": 35, "expens": [35, 39, 42, 44, 50, 63, 64, 65, 66], "mitig": [35, 63], "solvabl": [36, 68], "milk": 36, "pool": 36, "ordinari": 36, "ol": 36, "classif": [36, 50], "refineri": [36, 39], "conic": [36, 44, 46, 48, 49, 55, 58], "anyon": 37, "broadli": 37, "ida": [37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 68], "pse": [37, 38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 68], "solver_milo": 37, "solver_minlo": [37, 55], "couenn": 37, "d_f": 37, "f_f": 37, "gilmor": 37, "gamori": 37, "1961": 37, "rapidli": 37, "s_p": 37, "pf": 37, "make_pattern": 37, "partial": [37, 42], "num_cut": 37, "cuts_dict": 37, "plot_pattern": 37, "cmap": 37, "tab10": 37, "background": 37, "y_lo": 37, "y_hi": 37, "overlai": 37, "xa": 37, "xb": 37, "clean": [37, 69], "bottom": 37, "cut_pattern": 37, "plot_nonzero_pattern": 37, "unus": [37, 41, 63], "_2": [37, 40, 42, 44, 45, 48, 50, 55, 58, 63], "n_p": 37, "x_p": 37, "symmetri": 37, "substitut": [37, 45, 63, 69], "cone": [37, 46, 47, 48, 49, 50], "minlo": [37, 39], "bilinear_cut_stock": 37, "f_total_demand": 37, "a_bound": 37, "assign_each_stock_to_pattern": 37, "feasible_pattern": 37, "max_pattern": 37, "shouldn": 37, "_f": [37, 53], "generate_pattern_bilinear": 37, "xp": [37, 60], "ap": 37, "sum_to_on": 37, "add_pattern": 37, "new_pattern": 37, "pi_f": 37, "sf": [37, 69], "generate_pattern_du": 37, "subprob": 37, "marginal_valu": 37, "stock_length": 37, "reduced_valu": 37, "somewhat": [37, 68], "generate_patterns_bilinear": 37, "generate_patterns_du": 37, "std": [37, 42, 62], "137": [37, 42, 49, 62], "exhaust": [37, 39], "empir": [37, 55, 62, 65], "cut_stock": 37, "non_zero_indic": 37, "jl": 37, "stabl": [37, 45, 50], "cutting_stock_column_gener": 37, "en": [37, 46, 47], "wiki": [37, 46, 47], "cutting_stock_problem": 37, "roll": 37, "5600": [37, 59], "1520": 37, "1560": 37, "1710": 37, "1820": 37, "1880": 37, "2050": 37, "2100": 37, "2140": [37, 63], "2150": 37, "2200": 37, "2x4": 37, "lumber": 37, "arm": 37, "outdoor": 37, "sofa": 37, "ana": 37, "imag": [37, 42, 50], "spreadsheet": 37, "1zx7kj2kwtggyqev_a3log0nqsxsc38ykk53a7vgwafu": 37, "gid": 37, "1104632299": 37, "read_google_sheet": 37, "sheet_id": 37, "sheet_nam": 37, "lowercas": [37, 69], "str": [37, 42, 50, 52, 55], "gviz": 37, "tq": 37, "tqx": 37, "settings_df": 37, "nset": 37, "finish_df": 37, "nfinish": 37, "stocks_df": 37, "nstock": 37, "kerf": 37, "120": [37, 44, 63, 64], "144": 37, "168": 37, "192": [37, 64], "240": [37, 45, 64], "2x6": 37, "pivot_t": [37, 39], "aggfunc": 37, "sort_index": 37, "gomori": 37, "trim": [37, 68], "849": 37, "859": 37, "jstor": [37, 45], "1963": 37, "863": [37, 62], "haessler": 37, "sweenei": 37, "european": [37, 64, 66], "delorm": 37, "iori": 37, "martello": 37, "2016": [37, 41, 44, 46, 47, 49], "exact": [37, 45, 51, 66], "255": [37, 45, 58], "sciencedirect": [37, 44, 45], "implemen": 37, "mathwork": 37, "matlab": 37, "aimm": 37, "scip": 37, "pulp": 37, "harjunkoski": 37, "westerlund": 37, "p\u00f6rn": 37, "skrifvar": 37, "minlp": [37, 39], "594": 37, "603": 37, "abo": 37, "fi": 37, "s471": 37, "s474": 37, "ipopt": [38, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 55, 57, 58, 68], "mosek_direct": [38, 44, 45, 46, 47, 48, 49, 50, 57, 58], "stochast": [38, 51, 52, 54, 57, 60, 63, 66], "she": 38, "riski": [38, 49, 58], "tild": [38, 40, 48, 58], "mu": [38, 48, 58, 62], "sigma": [38, 48, 58, 62], "mathrm": [38, 47], "compromis": [38, 46], "willing": [38, 57], "undertak": 38, "exclud": [38, 69], "semidefinit": [38, 48], "semi": [38, 40, 42, 48, 50, 58], "linalg": [38, 42, 48, 50], "eigval": [38, 42, 48, 50], "rand": [38, 48, 53, 58], "xtild": [38, 48, 58], "bounded_vari": [38, 48], "total_asset": [38, 48, 58], "x_3": [38, 48, 58], "ok": [38, 48, 55, 58, 60], "158": 38, "gamma_valu": 38, "stream": 39, "mixtur": 39, "petroleum": 39, "sector": [39, 46], "tankag": 39, "train": [39, 43, 49], "pipelin": 39, "agricultur": 39, "mine": 39, "wastewat": 39, "composit": [39, 44], "solver_lo": [39, 40, 42], "solver_gnlo": 39, "bulk": 39, "fat": 39, "farm": [39, 51, 64], "afford": 39, "distant": 39, "grade": 39, "tank": 39, "station": 39, "noth": [39, 47], "min_fat": 39, "045": 39, "6000": [39, 41, 45, 64], "030": [39, 44], "2500": [39, 41, 52, 60], "040": 39, "033": 39, "050": [39, 55], "local_suppli": 39, "remote_suppli": 39, "ncustom": 39, "nsupplier": 39, "_c": 39, "_l": 39, "flowrat": 39, "fat_cont": 39, "81000": 39, "2666": 39, "1333": 39, "justifi": [39, 47], "122441": 39, "1764": 39, "4235": 39, "2352": 39, "1647": 39, "extent": [39, 65], "giveawai": 39, "surpass": 39, "parameter": 39, "y_c": 39, "_r": [39, 50], "enter": 39, "implic": 39, "profound": 39, "customer_demand": 39, "pool_bal": 39, "pool_qual": 39, "customer_qu": 39, "p_plot": 39, "025": [39, 45, 55], "055": 39, "f_plot": 39, "contrast": [39, 41], "minima": 39, "thee": 39, "w_c": [39, 46], "incomplet": 39, "isn": 39, "concentr": [39, 51, 68], "conc": 39, "underlin": 39, "mccormick": 39, "envelop": 39, "milk_pooling_convex": 39, "hh": 39, "lh": 39, "hl": 39, "report_solut": 39, "npool": 39, "m_convex": 39, "111411": 39, "112500": 39, "1029": 39, "4118": 39, "43235": 39, "2956": 39, "4852": 39, "9412": 39, "179558": 39, "8244": 39, "4117": [39, 45], "6471": 39, "185294": 39, "1195": 39, "0421": 39, "312000": 39, "1470": 39, "5882": 39, "0359": 39, "0400": 39, "412": 39, "search": [39, 55, 63], "xy": [39, 45], "xytext": [39, 45], "036": 39, "106000": 39, "arrowprop": [39, 45], "shrink": [39, 45], "headwidth": [39, 45], "miss": [39, 52], "scan": [39, 53], "m_est": 39, "105000": 39, "088": 39, "fall": 39, "441": 39, "100088": 39, "270000": 39, "3823": 39, "5294": 39, "141470": 39, "5878": 39, "2676": 39, "4706": 39, "120441": 39, "1770": 39, "discrep": 39, "compil": 39, "ampl": 39, "milk_pooling_bilinear": 39, "m_global": 39, "bo": 39, "95000": 39, "102833": 39, "2333": 39, "3333": [39, 46], "8333": 39, "375000": 39, "4166": 39, "6667": 39, "154166": 39, "1666": 39, "augment": [39, 46, 50], "awai": [39, 68], "bonmin": [39, 55], "prototyp": 39, "feed": [39, 64, 68], "un": 39, "haverli": 39, "1978": 39, "fuel": [39, 41], "recurs": [39, 68], "acm": 39, "sigmap": 39, "bulletin": 39, "dl": 39, "1145": 39, "1111237": 39, "1111238": 39, "encyclopedia": 39, "patholog": [39, 47], "visweswaran": 39, "springer": [39, 45, 62, 64], "referenceworkentri": 39, "978": 39, "387": [39, 55], "74759": 39, "0_375": 39, "misen": 39, "flouda": 39, "researchg": 39, "profil": [39, 49], "ruth": 39, "public": 39, "242290955_advances_for_the_pooling_problem_modeling_global_optimization_and_computational_studies_survei": 39, "0046352e7d1dfeb40f000000": 39, "gupt": 39, "ahm": 39, "dei": 39, "cheon": 39, "georgia": 39, "institut": 39, "atlanta": 39, "exxonmobil": [39, 49], "annandal": 39, "nj": 39, "db_file": 39, "2012": [39, 44], "3658": 39, "ceccon": 39, "galini": 39, "107660": 39, "2105": 39, "01687": 39, "probabl": [39, 46, 47, 49, 57, 59, 60, 62, 63], "underappreci": 39, "programm": 39, "wfp": 39, "clp": 40, "solver_qo": 40, "ols_regress": 40, "sum_of_square_error": 40, "49847313217242": 40, "42809468044768995": 40, "cccc": 40, "unconstrain": 40, "hessian": 40, "nabla": 40, "42857640061373": 40, "4130268125089274": 40, "y_fit2": 40, "explan": [41, 50], "unusu": 41, "seborg": 41, "edgar": 41, "mellichamp": 41, "doyl": 41, "dale": 41, "thoma": 41, "duncan": 41, "franci": 41, "dynam": [41, 69], "wilei": 41, "son": 41, "24000": 41, "28000": 41, "volumetr": 41, "feed_cost": 41, "process_cost": 41, "860275": 41, "8317999997": 41, "explicit": [41, 53, 66, 69], "implicit": 41, "sharp": 41, "cxvpy": 41, "to_numpi": [41, 42, 50], "8620663473": 41, "results_crud": 41, "dual_valu": 41, "26206": 41, "6896": 41, "results_product": 41, "5103": 41, "896": 41, "xlim": [41, 42, 50], "32000": 41, "xplot": 41, "regim": 41, "doubl": 41, "kerosen": 41, "hydrocarbon": 41, "hyperplan": [42, 46, 49, 50], "banknot": [42, 50], "solver_nlo": [42, 55], "medic": 42, "diseas": 42, "enjoi": 42, "movi": 42, "photo": 42, "car": [42, 45], "genuin": [42, 50], "counterfeit": [42, 50], "vend": 42, "accur": [42, 63, 66], "reject": 42, "ones": [42, 50, 60, 63], "tp": 42, "fn": 42, "tn": 42, "frustrat": 42, "incorrectli": [42, 45], "low": [42, 44, 45, 47, 48, 60, 63, 69], "innoc": 42, "proven": 42, "guilti": 42, "unless": 42, "perspect": [42, 65], "specimen": [42, 50], "wavelet": [42, 50], "skew": [42, 50], "curtosi": [42, 50], "entropi": [42, 50], "authent": [42, 50], "model_select": [42, 50], "train_test_split": [42, 50], "data_banknote_authent": [42, 50], "txt": [42, 50], "62160": 42, "6661": 42, "8073": 42, "44699": 42, "54590": 42, "1674": 42, "4586": 42, "46210": 42, "86600": [42, 64], "6383": 42, "9242": 42, "10645": 42, "45660": 42, "5228": 42, "0112": 42, "59440": 42, "32924": 42, "4552": 42, "5718": 42, "98880": 42, "1372": 42, "433735": 42, "922353": 42, "397627": 42, "191657": 42, "444606": 42, "842763": 42, "869047": 42, "310030": 42, "101013": [42, 49], "497103": 42, "042100": 42, "773100": 42, "286100": 42, "548200": 42, "773000": 42, "708200": 42, "574975": 42, "413450": 42, "319650": 42, "616630": 42, "586650": 42, "821475": 42, "814625": 42, "179250": 42, "394810": 42, "824800": 42, "951600": 42, "927400": 42, "449500": 42, "exposit": [42, 50], "df_train": [42, 50], "df_test": [42, 50], "test_siz": [42, 50], "x_train": [42, 50], "y_train": [42, 50], "x_test": [42, 50], "y_test": [42, 50], "scatter_labeled_data": [42, 50], "prepend": [42, 50], "catch_warn": [42, 50], "filterwarn": [42, 50], "pred": [42, 50], "sgn": [42, 50], "scalar": 42, "linearsvm": [42, 50], "bia": [42, 50], "__call__": [42, 50, 68], "__repr__": [42, 50], "surfac": [42, 44], "accuraci": [42, 45, 50], "score": [42, 50], "estima": 42, "y_pred": [42, 50], "scatter_comparison": [42, 50], "xmin": [42, 50], "ymin": [42, 50], "xmax": [42, 50], "ymax": [42, 50], "topic": [42, 50, 68], "recommend": [42, 50, 69], "matthew": [42, 50], "mcc": [42, 50], "y_true": [42, 50], "bool": [42, 50], "true_posit": [42, 50], "false_neg": [42, 50], "false_posit": [42, 50], "true_neg": [42, 50], "mcc_numer": [42, 50], "mcc_denomin": [42, 50], "confusion_matrix": [42, 50], "134": [42, 46, 47, 49, 62, 65], "pm": [42, 50, 55, 63, 66], "ambigu": 42, "perfectli": [42, 49, 57, 66], "z_i": [42, 45, 50], "misclassifi": [42, 50], "hing": 42, "poorli": 42, "penal": [42, 46], "_1": [42, 50, 55, 63], "lasso": 42, "spars": 42, "neglect": [42, 49], "2n": 42, "recast": [42, 49], "factori": [42, 45, 50], "svm_factory_lp": 42, "lambd": [42, 46, 47, 49], "wp": [42, 46, 47], "wn": 42, "hingeloss": 42, "svm_lp": 42, "24607501": 42, "053474389": 42, "0058897667": 42, "143": [42, 49], "slack": [42, 50], "settl": [42, 50, 68], "soft": [42, 50], "misclassif": [42, 50], "accompani": [42, 50, 69], "svm_factory_qp": 42, "qp": 42, "svm_qp": 42, "3705558690404267": 42, "12373970025774439": 42, "1493160233858407": 42, "702": 42, "lagrangian": 42, "alpha_i": [42, 50, 65], "beta_i": 42, "saddl": 42, "alpha_j": [42, 50], "y_j": [42, 50, 55], "symmetr": [42, 50, 55, 62], "y_n": [42, 44, 50], "x_n": [42, 44, 50], "vdot": [42, 50], "ddot": [42, 50], "dens": [42, 50], "sim": [42, 44, 45, 50, 62, 66], "rank": [42, 48, 50], "defici": [42, 50], "elimin": [42, 45, 50, 53, 63, 69], "ff": [42, 50], "complementar": 42, "svm_factory_du": 42, "mul": 42, "interior": [42, 44, 45], "closest": 42, "argmin": 42, "svm_dual": 42, "3705560469152364": 42, "12373974216158136": 42, "1493161249124506": 42, "phi": [42, 50, 58, 62], "machineri": 42, "mercer": [42, 50], "theorem": [42, 50], "spectral": [42, 50], "diagon": [42, 50], "eigenvalu": [42, 50], "i_q": [42, 50], "kernal": [42, 50], "sv": [42, 50], "kernelsvm": [42, 50], "svm_factory_kernel": 42, "tol": [42, 50], "callabl": [42, 68], "eigvec": 42, "eigh": [42, 50], "diag": [42, 50, 62], "y_support": [42, 50], "svm_kernel": 42, "__main__": 42, "0x2a9271d80": 42, "0x2a92f6170": 42, "757": 42, "cubic": [42, 44], "0x2a94613f0": 42, "807": 42, "kelli": [43, 46, 49], "layer": [43, 63], "insul": 43, "luenberg": 43, "wheel": 43, "growth": [43, 46], "thermal": 44, "annual": [44, 45, 49], "heat": 44, "air": [44, 62], "pmo": [44, 45, 46, 47, 49, 50], "temperatur": 44, "t_o": 44, "conduct": 44, "ua": 44, "transfer": [44, 68], "invers": [44, 58, 60, 62], "serial": 44, "resist": 44, "r_0": 44, "r_n": [44, 46, 47], "k_n": 44, "thick": 44, "proport": [44, 57], "affin": 44, "a_n": 44, "b_n": [44, 46], "ty_n": 44, "bx": 44, "sq": 44, "meter": 44, "r0": [44, 47], "watt": 44, "xopt": 44, "4f": [44, 46, 47, 60], "9962": 44, "2864": 44, "z_n": 44, "r_1": [44, 45, 46, 47], "r_2": [44, 45, 47], "z_0": 44, "z_1": [44, 45, 55], "rotated_quadrat": [44, 50], "as_domain": [44, 46, 47, 49, 50], "99615": 44, "28640": 44, "resort": [44, 65], "overcom": 44, "ru": 44, "2ru": 44, "middl": 44, "isol": 44, "a_ny_n": 44, "b_nx_n": 44, "variable_dict": [44, 45, 46, 49], "constraint_dict": 44, "miner": 44, "wool": 44, "rigid": 44, "foam": 44, "015": [44, 45], "1549": 44, "19361": 44, "010": [44, 45], "2299": 44, "06276": 44, "08724": 44, "x_0": 44, "curv": [44, 66], "x0": 44, "meshgrid": 44, "contour": [44, 45], "hasan": 44, "cycl": 44, "124": [44, 45, 49], "pii": [44, 45], "s0306261999000239": 44, "kaynakli": 44, "review": [44, 69], "sustain": 44, "425": [44, 55, 64], "s1364032111004163": 44, "nyer": 44, "kajtar": 44, "tomi\u0107": 44, "2015": 44, "268": 44, "s0378778814008688": 44, "gori": 44, "guattari": 44, "evangelisti": 44, "asdrubali": 44, "mass": [44, 49], "359": 44, "s0017931016303647": 44, "huang": 44, "zhou": 44, "wu": 44, "chines": 44, "zone": 44, "humid": 44, "subtrop": 44, "climat": 44, "101840": 44, "s221067071931457x": 44, "s\u00f6ylemez": 44, "\u00fcnsal": 44, "refriger": 44, "s0196890498001253": 44, "a\u00e7\u0131kkalp": 44, "kandemir": 44, "2019": [44, 49], "environment": 44, "s2451904918305377": 44, "ylm\u00e9n": 44, "mj\u00f6rnell": 44, "berlin": 44, "arfvidsson": 44, "optimis": [44, 45], "107544": 44, "s0360132320309112": 44, "mba": 45, "1915": 45, "deplet": 45, "hx": 45, "modulo": 45, "analyt": [45, 47, 66], "fopt": 45, "3651": 45, "2738": 45, "tangent": 45, "yopt": 45, "0006": 45, "3200": 45, "0008": 45, "elementari": 45, "geometri": 45, "hyperbola": 45, "intersect": 45, "lorenz": 45, "lobo": 45, "iff": [45, 47, 50], "2w": 45, "tilt": 45, "displac": [45, 62], "stretch": 45, "geometr": [45, 47], "4xy": 45, "mpl_toolkit": 45, "mplot3d": 45, "art3d": 45, "t_max": 45, "co": 45, "sin": 45, "plot3d": 45, "arcco": 45, "text3d": 45, "view_init": 45, "elev": 45, "azim": 45, "pathpatch_2d_to_3d": 45, "zdir": 45, "set_zlim": 45, "simpler": 45, "cd": 45, "experiment": 45, "u_eq": 45, "neoq": 45, "3654": 45, "stumbl": 45, "sledgehamm": 45, "swat": 45, "fly": 45, "compet": 45, "he": [45, 46], "perish": 45, "b_0": 45, "lb_i": 45, "ub_i": 45, "h_i": 45, "deliveri": [45, 63], "hypothet": [45, 59], "tire": 45, "weather": [45, 59, 64], "heavi": 45, "duti": 45, "block_dict": [45, 46, 49], "b_cap": 45, "eoq_display_result": 45, "306": 45, "918": 45, "153": 45, "1225": 45, "151": 45, "754": 45, "367": 45, "1101": 45, "df_larg": 45, "03d": 45, "688059": 45, "1220": 45, "110966": 45, "452672": 45, "2671": 45, "984745": 45, "4851": 45, "180476": 45, "3286": 45, "560933": 45, "1955": 45, "727272": 45, "458": 45, "2010": [45, 46, 47, 49], "006": 45, "911743": 45, "408": 45, "410": 45, "621799": 45, "478": [45, 48], "008": 45, "317468": 45, "335": [45, 49], "1056": 45, "009": 45, "460362": 45, "339": [45, 59], "2996": 45, "960022": 45, "801": 45, "011": 45, "926136": 45, "381": 45, "2800": 45, "688914": 45, "422": [45, 66], "3076": 45, "013": 45, "545538": 45, "014": 45, "668708": 45, "2260": 45, "755557": 45, "322": 45, "4872": 45, "587431": 45, "640": 45, "017": [45, 62], "801025": 45, "445": [45, 66], "1693": 45, "018": 45, "636593": 45, "473": 45, "4066": 45, "019": 45, "717248": 45, "476": [45, 52], "2194": 45, "020": 45, "053587": 45, "324": 45, "1518": 45, "021": 45, "318844": 45, "2681": 45, "022": 45, "625933": 45, "746": 45, "023": 45, "995664": 45, "3192": 45, "338183": 45, "468": 45, "2830": 45, "679697": 45, "354": 45, "2449": 45, "026": 45, "780842": 45, "358": 45, "926": 45, "236800": 45, "411": 45, "4618": 45, "028": 45, "252901": 45, "455": 45, "3022": [45, 49], "029": 45, "039994": 45, "423": [45, 46], "4253": 45, "132": [45, 49], "2274": 45, "3327": 45, "4801": 45, "3905": 45, "169": 45, "2901": 45, "3443": 45, "1449": 45, "1982": 45, "2121": 45, "3588": 45, "1922": 45, "213": [45, 65], "3659": 45, "236": [45, 62], "4046": 45, "3068": 45, "4445": 45, "3079": 45, "291": 45, "4982": 45, "3668": 45, "146": 45, "2508": 45, "224": 45, "3842": 45, "3915": 45, "4102": 45, "193": 45, "3307": 45, "119": 45, "287": [45, 62], "4917": 45, "4184": 45, "4797": 45, "curiou": 45, "twist": 45, "1931": 45, "citat": 45, "shaw": 45, "chap": 45, "iv": 45, "chicago": 45, "ziegler": 45, "singli": 45, "252": [45, 49], "016763778290030x": 45, "bretthauer": 45, "shetti": 45, "1995": 45, "670": 45, "171693": 45, "kuo": 45, "mittleman": 45, "2004": 45, "mittelmann": 45, "285": 45, "1023": 45, "coap": 45, "0000033964": 45, "95511": 45, "vandenbergh": 45, "lebret": 45, "284": [45, 66], "stanford": [45, 46, 49], "socp": [45, 58], "letchford": 45, "park": [45, 66], "guid": [45, 67], "rairo": 45, "1106": 45, "cs": 45, "nott": 45, "uk": 45, "pszajp": 45, "pub": 45, "el": 45, "ghaoui": 45, "laurent": 45, "inst": 45, "eec": 45, "berkelei": [45, 46, 49], "ee127": 45, "fa19": 45, "12_socp": 45, "cookbook": [45, 48], "section": [45, 62, 68], "cqo": 45, "bypass": 45, "6cm": 45, "4pt": 45, "u_i": [45, 47], "v_i": [45, 66], "solver_con": 46, "wager": [46, 47], "spin": 46, "game": 46, "indefinit": 46, "interact": [46, 68, 69], "w_a": 46, "w_b": 46, "stake": 46, "bisect": 46, "ipywidget": 46, "widget": 46, "wheel_sim": 46, "odd": [46, 47], "quantil": [46, 52, 58, 60, 62], "semilog": [46, 47], "bisect_left": 46, "wealth_next": 46, "elogr": [46, 47, 49], "interact_manu": 46, "floatslid": 46, "wb": 46, "wc": [46, 64], "wheel_interact1": 46, "p_n": 46, "q_n": 46, "wheel_model": 46, "expression_dict": [46, 49], "sum_w": 46, "primal_exponenti": [46, 47, 49], "06758": 46, "218": 46, "167": 46, "128": [46, 49, 62, 69], "suffer": 46, "drawdown": 46, "busseti": [46, 47, 49], "ryu": [46, 47, 49], "gambl": [46, 47, 49], "infti": [46, 55, 60], "admiss": 46, "p_1": [46, 47], "u_n": 46, "wheel_rc_model": 46, "sum_u": 46, "06025": 46, "36329": 46, "26547": 46, "1667": 46, "12575": 46, "wheel_interact2": 46, "semilogx": [46, 49], "determinist": [46, 63, 65, 66], "popular": [46, 47], "poundston": [46, 47], "fortun": [46, 47], "untold": [46, 47], "scientif": [46, 47, 49], "bet": [46, 47, 49], "beat": [46, 47, 49], "casino": [46, 47], "street": [46, 47, 49], "hill": [46, 47], "wang": [46, 47], "onlinecasinoground": [46, 47], "nl": [46, 47], "upload": [46, 47], "boek": [46, 47], "van": [46, 47, 69], "thorp": [46, 47, 49], "man": [46, 47, 49], "la": [46, 47, 49, 69], "vega": [46, 47, 49], "dealer": [46, 47, 49], "2008": [46, 47, 49], "blackjack": [46, 47, 49], "sport": [46, 47, 49], "handbook": [46, 47, 49], "liabil": [46, 47, 49], "385": [46, 47, 49], "428": [46, 47, 49], "holland": [46, 47, 49], "palmislandtrad": [46, 47, 49], "econ136": [46, 47, 49], "thorpe_kelly_crit": [46, 47, 49], "maclean": [46, 49], "ziemba": [46, 49], "aldou": [46, 49], "good_bad_kelli": [46, 49], "2011": [46, 49, 62, 64], "worldscientif": [46, 49], "worldscibook": [46, 49], "7598": [46, 49], "aboutbook": [46, 49], "wikipedia": [46, 47, 68], "kelly_criterion": [46, 47], "oup": 46, "catalogu": 46, "ush": 46, "9780199740086": 46, "caja": [46, 49], "3833617": [46, 49], "1603": [46, 47, 49], "06183": [46, 47, 49], "fu": [46, 47, 49], "narasimhan": [46, 47, 49], "cvxr": [46, 47, 49], "1711": [46, 47, 49], "07582": [46, 47, 49], "1812": [46, 49], "10371": [46, 49], "robust_kelli": [46, 49], "ch": [46, 49], "hsieh": [46, 49], "2202": [46, 49, 52], "03858": [46, 49], "1956": 47, "bell": 47, "laboratori": 47, "analog": 47, "claud": 47, "shannon": 47, "noisi": 47, "channel": 47, "gambler": 47, "predat": 47, "daniel": 47, "bernoulli": 47, "resolut": 47, "st": 47, "petersburg": 47, "cousin": 47, "nichola": 47, "adventur": 47, "earli": [47, 69], "laid": 47, "obscur": 47, "cowork": [47, 49], "avers": 47, "ident": [47, 49, 53, 63, 68], "polici": 47, "q_1": 47, "q_2": 47, "w_conic": 47, "w_analyt": 47, "1180": 47, "p_2": 47, "q_i": 47, "u_1": [47, 50], "u_2": [47, 50], "kelly_rc": 47, "u1": 47, "u2": 47, "r1": [47, 69], "r2": [47, 69], "w_rc": 47, "constrainend": 47, "0589": 47, "kelly_sim": 47, "mont": 47, "carlo": 47, "binomi": 47, "cumprod": [47, 49], "logr": 47, "transax": 47, "1e6": 47, "choleski": 48, "lorentz": 48, "2_2": [48, 55], "practiv": 48, "qcqo": 48, "markowitz_revisit": 48, "283": 48, "130": 48, "alpha_valu": 48, "critiqu": 49, "economist": 49, "20th": 49, "paul": 49, "samuelson": 49, "ground": 49, "lack": [49, 59], "controversi": 49, "didn": 49, "fund": 49, "histor": [49, 57, 59], "yfinanc": 49, "holidai": 49, "elabor": 49, "gspc": 49, "ixic": 49, "nasdaq": 49, "dji": 49, "jone": 49, "rut": 49, "russel": 49, "amgen": 49, "appl": 49, "boe": 49, "caterpillar": 49, "chevron": 49, "jpmorgan": 49, "chase": 49, "mcdonald": 49, "microsoft": 49, "proctor": 49, "n_test": 49, "n_train": 49, "dropna": 49, "prop": 49, "r_f": 49, "futur": [49, 51, 59, 62], "borrow": 49, "e_m": 49, "q_t": 49, "equiprob": [49, 57, 62], "kelly_portfolio": 49, "u_sum": 49, "w_sum": 49, "kelly_report": 49, "247": 49, "190366": 49, "564623": 49, "480615": 49, "500638": 49, "152": 49, "966799": 49, "056351": 49, "132849": 49, "303171": 49, "247408": 49, "071398": 49, "924581": 49, "324833": 49, "955780": 49, "664067": 49, "665347": 49, "512189": 49, "226212": 49, "793304": 49, "976357": 49, "340": [49, 64, 69], "524902": 49, "859108": 49, "259621": 49, "789543": 49, "749512": 49, "810425": 49, "666946": 49, "046753": 49, "898674": 49, "26805": 49, "529297": 49, "3010": 49, "290039": 49, "8185": 49, "799805": 49, "1548": 49, "489990": 49, "955654": 49, "784424": 49, "724091": 49, "860046": 49, "127": [49, 65], "212341": 49, "170517": 49, "675674": 49, "463715": 49, "385712": 49, "427185": 49, "651657": 49, "028133": 49, "26958": 49, "060547": 49, "550049": 49, "8243": 49, "120117": 49, "1558": 49, "709961": 49, "556232": 49, "519867": 49, "026421": 49, "336": [49, 65], "897766": 49, "512772": 49, "011734": 49, "883026": 49, "913925": 49, "756805": 49, "860023": 49, "534607": 49, "27090": 49, "720703": 49, "3039": 49, "419922": 49, "8325": 49, "990234": 49, "1571": 49, "930054": 49, "155693": 49, "185": 49, "043839": 49, "930519": 49, "344": 49, "853729": 49, "668976": 49, "719246": 49, "030106": 49, "649017": 49, "701126": 49, "448059": 49, "968727": 49, "372787": 49, "27071": 49, "460938": 49, "3036": 49, "889893": 49, "8276": 49, "849609": 49, "1577": 49, "069946": 49, "148396": 49, "717285": 49, "544601": 49, "017273": 49, "767677": 49, "240089": 49, "409836": 49, "542816": 49, "326614": 49, "160965": 49, "182632": 49, "790260": 49, "27186": 49, "689453": 49, "3046": 49, "770020": 49, "8303": 49, "980469": 49, "1572": 49, "849976": 49, "carta": 49, "conversano": 49, "rebalanc": 49, "577050": 49, "frontiersin": 49, "3389": 49, "fam": 49, "thing": [50, 55, 63, 65, 66, 68], "move": [50, 62], "trail": 50, "classifi": 50, "rescal": [50, 68], "wrong": [50, 68], "unnecessarili": [50, 66], "orthogon": 50, "_n": 50, "m_r": 50, "2u_1u_2": 50, "u_3": 50, "u_m": 50, "conicsvmfactori": 50, "variable_list": [50, 55], "qr": 50, "constraint_list": [50, 55], "svm_v2": 50, "546234": 50, "152174": 50, "21435828724315473": 50, "769": 50, "q_r": 50, "computation": 50, "rememb": [50, 65], "conicdualsvmfactori": 50, "w_bar": 50, "svm_v3": 50, "546247": 50, "152194": 50, "21435778397469038": 50, "room": 50, "onward": 50, "alpha_ik": 50, "y_nk": 50, "kernelsvmfactori": 50, "hstack": 50, "nz": 50, "pz": 50, "rbf": 50, "881": 50, "encourag": 50, "poli": 50, "438": 50, "argu": [51, 65], "trust": 51, "substanc": 51, "ingredi": 51, "antenna": 51, "simul": [51, 55, 62, 66], "contrib": 52, "only_child_var": 52, "material_demand": 52, "eot_inventori": 52, "fold": 52, "initialize_problem_data": 52, "problem_data": 52, "demand_chips_ref": 52, "demand_chips_simul": 52, "showtableofpyomovari": 52, "23580": 52, "1823": 52, "1233": 52, "2465": 52, "682": 52, "1620": 52, "1586": 52, "1964": 52, "1678": 52, "1430": 52, "5020": 52, "4396": 52, "5017": 52, "3187": 52, "1807": 52, "2425": 52, "minimize_missed_demand_in_period": 52, "missed_demand": 52, "nb": 52, "resource_constraint": 52, "produced_plus_unmet": 52, "total_unmet": 52, "simulation_per_trajectori": 52, "simulate_perform": 52, "perturbed_demand": 52, "applymap": 52, "inv": 52, "md": 52, "missing_demand": 52, "missingdemand": 52, "swaplevel": 52, "inventoryevolut": 52, "average_missed_demand": 52, "bim_robust_missed_demand": 52, "realized_inv_cost": 52, "trajectori": 52, "n_sim": 52, "simresult": 52, "sllighli": 52, "nonzero": 52, "20309": 52, "3270": 52, "3309": 52, "flown": 53, "airlin": [53, 61], "airplan": [53, 62], "randomst": 53, "airport": 53, "generate_flight": 53, "n_flight": 53, "min_dur": 53, "max_dur": 53, "max_departur": 53, "rs": 53, "end_flight": 53, "start_flight": 53, "floor": 53, "ceil": 53, "flightdata": 53, "draw_flight": 53, "add_subplot": 53, "get_yaxi": 53, "iterrow": 53, "1h": 53, "feasible_flight_pair": 53, "turnaound": 53, "turnaround": [53, 68], "flight_pair": 53, "reassign": 53, "unexpect": 53, "delai": [53, 63], "sink": 53, "bigcup_": 53, "cup": [53, 65, 66], "eq": 53, "71a": 53, "71b": 53, "71c": 53, "71d": 53, "71e": 53, "eqref": 53, "drawback": 53, "blind": 53, "swap": 53, "lot": 53, "huge": [53, 65], "altogeth": 53, "flight1": 53, "flight2": 53, "p_f": 53, "unassign": 53, "q_f": 53, "minimize_airplan": 53, "redraw": 53, "dg_soln": 53, "layov": 53, "flightschedul": 53, "travers": 53, "a01": 53, "a04": 53, "a03": 53, "a02": 53, "a12": 53, "a05": 53, "a06": 53, "a07": 53, "a08": 53, "a13": 53, "a09": 53, "a11": 53, "a10": 53, "a14": 53, "aircraftschedul": 53, "from_fram": 53, "nplane": 53, "n_plane": 53, "minimize_risk": 53, "nlo": 55, "rrcrcl": 55, "gemanium": 55, "showdual": 55, "feel": 55, "lognorm": 55, "somehow": [55, 59], "currentaxi": 55, "922766922829344": 55, "9701110863753781": 55, "061793174956137": 55, "0328386701386703": 55, "z_2": 55, "infinit": 55, "robustifi": 55, "rrr": 55, "rrl": 55, "bimwithboxuncertainti": 55, "robustcopp": 55, "pervari": 55, "1137": 55, "17587": 55, "tune": [55, 57], "bimwithsymmetricalboxuncertainti": 55, "606": 55, "1143": 55, "17568": 55, "gave": 55, "1138": 55, "17586": 55, "behav": 55, "17634": 55, "628": 55, "1122": 55, "1144": 55, "17502": 55, "584": [55, 62], "17436": 55, "1188": 55, "17370": 55, "540": 55, "17304": 55, "518": 55, "1232": 55, "17238": 55, "1254": 55, "17175": 55, "475": 55, "17109": 55, "453": 55, "1297": 55, "17043": 55, "1319": 55, "16977": 55, "409": 55, "1341": 55, "16911": 55, "1363": 55, "16845": 55, "1385": 55, "16779": 55, "1407": 55, "16713": 55, "321": 55, "1429": 55, "16650": 55, "1450": 55, "16584": 55, "278": 55, "1472": 55, "16518": 55, "1494": 55, "16416": 55, "16296": 55, "16001": 55, "17999": 55, "z_j": 55, "lagrang": 55, "rrcrcrcrcrcrcl": 55, "t_1": 55, "t_2": 55, "bimwithbudgetuncertainti": 55, "lam": 55, "up_rul": 55, "down_rul": 55, "641": 55, "1109": 55, "17673": 55, "violat": [55, 57, 63], "bimwithsetofscenario": 55, "worst": [55, 57, 63, 65], "bimpessim": 55, "pessim": [55, 63], "absolute_value_1": 55, "absolute_value_2": 55, "absolute_value_less_than_on": 55, "budget_constraint": 55, "worst_z": 55, "wrap": 55, "gradual": [55, 63], "reoptim": 55, "adversarial_converg": 55, "stopping_precis": [55, 63], "max_iter": [55, 63], "adversarial_iter": 55, "niter": [55, 63], "constraint_viol": 55, "baselin": [55, 66], "viabl": 55, "polytop": 55, "ellipsoid": 55, "extrem": [55, 63], "minuscul": 55, "radiu": 55, "_1x_1": 55, "_2x_2": 55, "newli": [55, 63, 65], "pyk": 55, "bimwithballuncertainti": 55, "domain_typ": 55, "realset": 55, "idxchip": 55, "xtow": 55, "617": 55, "755": 55, "1132": 55, "17603": 55, "integerset": 55, "1133": 55, "17601": 55, "bimwithballuncertaintyassquaredsecondordercon": 55, "soc": 55, "pop": 56, "seafood": 56, "llll": [57, 65, 66], "offshor": 57, "turbin": [57, 65, 66], "fluctuat": [57, 65, 66], "intermitt": 57, "mismatch": 57, "varepsilon": [57, 60], "fine": 57, "saa": [57, 61], "seaborn": 57, "sn": 57, "read_economic_dispatch_data": 57, "wind_production_samples_df": 57, "discrete_wind": 57, "wind_production_sampl": 57, "fifth": 57, "94632359541376": 57, "set_styl": 57, "darkgrid": 57, "histplot": 57, "kde": 57, "kde_kw": 57, "23034433319671": 57, "bubbl": 57, "df_node": 57, "showinst": 57, "zorder": 57, "u_j": 57, "thank": [57, 58], "omega_j": 57, "u_jm_j": 57, "deactiv": [57, 66], "incorrect": 57, "certainli": 57, "repeatedli": 57, "economic_dispatch": 57, "supply_demand_leq": 57, "supply_demand_geq": 57, "success_prob": 57, "sum_product": 57, "sum_demand": 57, "3007": 57, "393": 57, "7850": 57, "601": 57, "reward": 57, "tradeoff": [57, 63, 64], "getlogg": [57, 66], "setlevel": [57, 66], "fixed_delta": 57, "feas_ep": 57, "feas_obj": 57, "num": 57, "epsilon": 57, "fixed_ep": 57, "feas_delta": 57, "tighter": 57, "flat": 57, "multivari": [58, 62], "gaussian": 58, "cdf": [58, 60, 62], "ppf": [58, 60, 62], "dramat": [58, 65], "markowitz_chanceconstraint": 58, "chance_constraint": 58, "078": 58, "commemor": 59, "unsold": [59, 60, 62], "salvag": 59, "sunni": 59, "ski": 59, "poor": [59, 64, 66], "dilemma": 59, "expected_demand": 59, "10220": 59, "165": [59, 64], "3950": 59, "8339": 59, "satisfactori": 59, "lesser": 59, "operation": 59, "sales_less_than_ord": 59, "sales_less_than_demand": 59, "11200": [59, 64], "8920": 59, "920": 59, "581": 59, "compens": [59, 65], "unfold": 59, "probablist": 59, "transpir": 59, "varaibl": 59, "variat": 59, "18200": 59, "evss": 59, "hypother": 59, "220": [59, 69], "vpi": 59, "math": [60, 64], "ton": [60, 64], "tuna": 60, "whom": 60, "fish": 60, "leftov": 60, "cold": 60, "cx": 60, "cumul": [60, 68], "pareto": 60, "expon": 60, "weibul": [60, 66], "5357": 60, "weibull_min": 60, "838": 60, "extratick": 60, "x_opt": 60, "ytick": 60, "parametr": [60, 69], "mean_demand": 60, "first_stage_profit": 60, "cant_sell_fish_i_dont_hav": 60, "fish_do_not_disappear": 60, "second_stage_profit": 60, "total_profit": 60, "determist": 60, "naiveseafoodstocksaa": 60, "distributiontyp": 60, "indices_rul": 60, "xi": 60, "cantsoldthingsfishdonthav": 60, "fishdonotdisappear": 60, "total_expected_profit": 60, "7500": [60, 64], "naiveprofit_uniform": 60, "xm": 60, "naiveprofit_pareto": 60, "naiveprofit_weibul": 60, "966": [60, 62], "910": [60, 62], "vss": 60, "seafoodstocksaa": 60, "printflag": 60, "cantsoldfishidonthav": 60, "smartprofit_uniform": 60, "smartprofit_pareto": 60, "smartprofit_weibul": 60, "979": 60, "890": 60, "919": 60, "profit_uniform": 60, "profit_pareto": 60, "profit_weibul": 60, "xw": 60, "recours": [61, 62, 66], "ccg": [61, 63], "farmer": 61, "land": [61, 64], "curtail": [61, 65], "birg": [62, 64], "louveaux": [62, 64], "media": [62, 64], "bueno": 62, "economi": 62, "passeng": 62, "ticket": 62, "weekdai": 62, "traffic": 62, "middai": 62, "overbook": 62, "downgrad": 62, "unavail": 62, "revenue_factor": 62, "seat_factor": 62, "seat_report": 62, "unsatisfi": 62, "spillag": 62, "equivalent_seat": 62, "nseat": 62, "nticket": 62, "unmet": 62, "nspillag": 62, "unfulfil": 62, "nexpect": 62, "rot": 62, "trial": 62, "seats_all_economi": 62, "eev": 62, "evm": 62, "s_c": 62, "t_c": 62, "r_c": 62, "f_c": 62, "mu_c": 62, "bm": [62, 63], "airline_determinist": 62, "plane_seat": 62, "demand_limit": 62, "seat_limit": 62, "airline_solv": 62, "model_eev": 62, "seats_eev": 62, "boldsymbol": 62, "z_c": 62, "tuplic": 62, "airline_stochast": 62, "model_stochast": 62, "seats_stochast": 62, "enrol": 62, "loyalti": 62, "cover": [62, 63, 65], "z_f": 62, "mu_f": 62, "sigma_f": 62, "z_b": [62, 63], "mu_b": 62, "sigma_b": 62, "mu_": 62, "sigma_": 62, "s_f": 62, "s_b": 62, "054": 62, "counterpart": [62, 65], "qo": 62, "airline_cc": 62, "qosf": 62, "qosfb": 62, "first_class": 62, "business_class": 62, "model_cc": 62, "seats_cc": 62, "z_e": 62, "sigma_c": 62, "simplif": 62, "anymor": 62, "sake": [62, 63], "nmodel": 62, "nearest": 62, "multivariate_norm": 62, "demand_saa": 62, "demand_saa_stat": 62, "ci": 62, "889": 62, "088936": 62, "051534": 62, "839669": 62, "seat_report_saa": 62, "model_ssa": 62, "seats_saa": 62, "148": 62, "764": 62, "416": 62, "147": 62, "944": 62, "mu_e": 62, "ccc": 62, "rho_": 62, "fb": 62, "fe": 62, "bf": 62, "BE": 62, "ef": 62, "eb": 62, "truncat": 62, "nsampl": 62, "cov": 62, "cj": 62, "convari": 62, "590": 62, "301": 62, "951388": 62, "139984": 62, "147365": 62, "613469": 62, "044965": 62, "434823": 62, "229": 62, "219119": 62, "216627": 62, "916315": 62, "303": 62, "184": 62, "697": 62, "816": 62, "airline_fin": 62, "first_class_loy": 62, "first_class_loyality_r": 62, "business_class_loy": 62, "business_class_loyality_r": 62, "995": 62, "031": 62, "969": 62, "startup": 63, "announc": 63, "campaign": 63, "chief": 63, "offic": 63, "coo": 63, "z_a": 63, "z_d": 63, "attain": 63, "subtract": 63, "p_u": 63, "p_v": 63, "preorder": 63, "10x": 63, "50z_a": 63, "80z_b": 63, "40z_b": 63, "tau": [63, 69], "model_param": 63, "uniformli": [63, 65], "z_sampl": 63, "max_min_profit": 63, "stage_net_profit": 63, "model_constraint": 63, "nsolut": 63, "883": 63, "547": 63, "slight": 63, "max_avg_profit": 63, "avg_profit": 63, "avg_case_p": 63, "2305": 63, "max_profit_fixed_x": 63, "fixed_x_valu": 63, "worst_cas": 63, "fixed_x": [63, 66], "xopt_rob": 63, "nsolv": 63, "worst_case_p": 63, "xopt_avg": 63, "underperform": 63, "narrow": 63, "stabler": 63, "phenomenon": 63, "unsur": 63, "downsid": 63, "i_3": 63, "_3": 63, "i1": 63, "i2": 63, "i3": 63, "i4": 63, "subproblem_param": 63, "hack": 63, "converg": 63, "proxi": 63, "acceler": 63, "freeli": 63, "hurt": 63, "pessimization_problem": 63, "master_solut": 63, "z_a_max": 63, "z_b_max": 63, "z_d_max": 63, "big_m": 63, "z_indic": 63, "z_ab": 63, "a_ub": 63, "a_lb": 63, "a_ab": 63, "b_lb": 63, "b_ub": 63, "b_ab": 63, "d_lb": 63, "d_ub": 63, "d_ab": 63, "z_budget": 63, "blockwis": 63, "at_least_one_viol": 63, "max_viol": 63, "subproblem": 63, "seem": [63, 65, 68], "hundr": 63, "ccg_converg": 63, "ccg_iter": 63, "export": 63, "single_solut": 63, "x_kei": 63, "y_kei": 63, "theta_opt": 63, "560": 63, "555": 63, "zeng": 63, "zhao": 63, "457": 63, "461": 63, "francoi": 64, "acr": 64, "crop": 64, "wheat": 64, "corn": 64, "beet": 64, "230": 64, "cattl": 64, "wholesal": 64, "decad": 64, "quota": 64, "excess": [64, 69], "interview": 64, "stai": 64, "advic": 64, "total_land": 64, "limit_on_planted_land": 64, "crop_yield": 64, "under_quota": 64, "over_quota": 64, "farm_report": 64, "nscenario": 64, "118600": 64, "18400": 64, "216000": 64, "78000": 64, "138000": 64, "analys": 64, "hear": 64, "108390": 64, "167000": 64, "52700": 64, "25500": 64, "27200": 64, "7200": 64, "65000": 64, "151000": 64, "109350": 64, "38250": 64, "12750": 64, "180000": 64, "115000": 64, "48820": 64, "23800": 64, "1700": 64, "28480": 64, "144000": 64, "79000": 64, "lower_bound_profit": 64, "59950": 64, "113250": 64, "37250": 64, "246000": 64, "97500": 64, "148500": 64, "8500": 64, "6500": 64, "40400": 64, "4975": 64, "2525": 64, "204350": 64, "106850": 64, "43550": 64, "118500": 64, "231000": 64, "133500": 64, "00000000055": 64, "min_profit": 64, "56750": 64, "56820": 64, "820": 64, "800": 64, "980": 64, "390": 64, "290": 64, "56800": 64, "107100": 64, "147000": 64, "23000": 64, "228000": 64, "150000": 64, "117500": 64, "14000": 64, "172800": 64, "94800": 64, "uiowa": 64, "dbricker": 64, "stacks_pdf1": 64, "slpwr_farmer": 64, "uh": 64, "rohop": 64, "spring_15": 64, "chapter1": 64, "surplu": 65, "shortag": 65, "opf": [65, 66], "panel": 65, "p_j": 65, "lllll": [65, 66], "delta_i": 65, "respond": 65, "jointli": 65, "adversari": 65, "costli": 65, "rnd": 65, "rework": 65, "opf_participationfactor": 65, "totalimbal": 65, "abstotalimbal": 65, "uniformparticipationfactor": 65, "swh": 65, "cg": 65, "ng": 65, "isna": 65, "abs_total_imbal": 65, "total_imbal": 65, "windsolarhydro_nopartecipationfactor": 65, "load_nopartecipationfactor": 65, "sum_on": 65, "equal_participationfactor": 65, "power_withrecours": 65, "generation_upper_bound_withrecours": 65, "generation_lower_bound_withrecours": 65, "flows_lower_bound": 65, "sw": 65, "sw_df": 65, "isin": 65, "zeroimbal": 65, "zerototalimbal": 65, "zeroabstotalimbal": 65, "firststagecost": 65, "40385": 65, "227": [65, 66], "235": [65, 66], "asid": 65, "proportion": 65, "averagerecoursecost": 65, "averagetotalcost": 65, "5354": 65, "45739": 65, "nfirst": 65, "205": 65, "276": 65, "41719": 65, "47073": 65, "cascad": 65, "failur": 65, "blackout": [65, 66], "damag": 65, "infrastructur": 65, "societ": 65, "unafford": 65, "281": 65, "40446": 65, "5969": 65, "46415": 65, "hertz": 66, "mainli": 66, "disconnect": 66, "offlin": 66, "advent": 66, "fairli": 66, "hydropow": 66, "former": 66, "predic": 66, "uc": [66, 69], "kappa_i": 66, "c_fix": 66, "nontrivi": 66, "g_i": 66, "shore": 66, "Being": 66, "g_": 66, "16563": 66, "4718": 66, "18007": 66, "72049": 66, "_v": 66, "705509": 66, "734756": 66, "273978": 66, "159230": 66, "852748": 66, "814908": 66, "230344": 66, "690399": 66, "514209": 66, "248977": 66, "784856": 66, "664045": 66, "163": 66, "009206": 66, "175633": 66, "504459": 66, "086431": 66, "1689": 66, "384370": 66, "1057": 66, "306239": 66, "1837": 66, "349675": 66, "1456": 66, "262510": 66, "526012": 66, "753966": 66, "693808": 66, "050352": 66, "747257": 66, "554867": 66, "1504": 66, "397099": 66, "1751": 66, "390683": 66, "2450": 66, "534057": 66, "2184": 66, "454": 66, "660581": 66, "1617": 66, "451": 66, "133883": 66, "1627": 66, "g_offshor": 66, "piecewis": 66, "g_onshor": 66, "uc_windcurtail": 66, "vmax": 66, "nw": 66, "voltag": 66, "term2": 66, "term1": 66, "wind_speed_to_pow": 66, "wind_curtail": 66, "scale64": 66, "shape64": 66, "scale65": 66, "shape65": 66, "turbineact": 66, "tubin": 66, "29662": 66, "uc_windcurtailment_fixed_x": 66, "mean_sampl": 66, "m_nomin": 66, "15101": 66, "mechan": 66, "n_infeas": 66, "m_singl": 66, "workflow": 67, "thon": 68, "ptimiz": 68, "odel": 68, "bject": 68, "stateless": 68, "immut": [68, 69], "mutat": 68, "incompat": 68, "glanc": 68, "encapsul": 68, "forward": 68, "invoc": 68, "concurr": 68, "exclaim": 68, "exclam": 68, "lawn": 68, "circ": 68, "enthus": 68, "hello": 68, "someth": 68, "bind": 68, "contains_valu": 68, "boilerpl": 68, "push": 68, "attributeerror": 68, "spe": 68, "ca": 68, "clone": 68, "_solver": 68, "new_model": 68, "_transform": 68, "overridden": 68, "rtype": 68, "__rshift__": 68, "production_model": 68, "2400": 68, "dae": 68, "reaction": 68, "stackrel": 68, "k_1": 68, "k_2": 68, "isotherm": 68, "ultim": 68, "t_f": 68, "max_t": 68, "da": 68, "dt": 68, "db": 68, "tractabl": 68, "t_ff": 68, "ode_model_build": 68, "k1": 68, "k2": 68, "continuousset": 68, "tf": 68, "dadt": 68, "derivativevar": 68, "dbdt": 68, "max_b": 68, "odea": 68, "odeb": 68, "colloc": 68, "669": 68, "15767005981401438": 68, "8541314382648219": 68, "ode_solv": 68, "023594361612317": 68, "6687402900841761": 68, "philliam": 68, "codeproject": 68, "5290753": 68, "deploy": 69, "guidelin": 69, "supplement": 69, "pep": 69, "emphas": 69, "modular": 69, "strongli": 69, "discourag": 69, "gen": 69, "r1bi": 69, "r3": 69, "r4": 69, "filter_rul": 69, "r5": 69, "trace": 69, "creation": 69, "time_period": 69, "ny": 69, "cariabl": 69, "callback": 69, "p1": 69, "p2": 69, "validate_param": 69, "p3": 69, "param_a": 69, "param_b": 69, "intent": 69, "scope": 69, "inconsist": 69, "redefin": 69, "cognit": 69, "burden": 69, "lower_bound": 69, "upper_bound": 69, "_rule": 69, "new_constraint_rul": 69, "new_constraint": 69, "bahavior": 69, "capacity_constraint": 69, "underscor": 69, "finish_tim": 69, "total_tim": 69, "camelcas": 69, "snake_cas": 69, "2x": 69, "manipul": 69, "promot": 69, "semant": 69, "suit": 69, "doubli": 69, "primari": 69, "secondari": 69, "referenc": 69, "ob": 69, "slice": 69, "254": 69, "173": 69, "430": 69, "reorgan": 69, "wrangl": 69, "colleagu": 69, "draft": 69, "woodruff": 69, "davi": 69, "javier": 69, "salmeron": 69, "medrano": 69, "naval": 69, "postgradu": 69, "bethani": 69, "nicholson": 69, "siirola": 69, "michael": 69, "bynum": 69, "jasper": 69, "doorn": 69, "leon": 69, "lan": 69}, "objects": {}, "objtypes": {}, "objnames": {}, "titleterms": {"index": [0, 69], "hand": 1, "On": 1, "optim": [1, 2, 6, 8, 12, 14, 15, 16, 18, 22, 26, 28, 35, 36, 37, 38, 39, 42, 43, 44, 47, 48, 49, 50, 51, 54, 56, 58, 60, 62, 63, 65, 66, 68], "python": [1, 4], "get": 1, "start": 1, "help": 1, "us": [1, 12, 18, 22, 26, 37, 55, 60, 62, 63, 68, 69], "about": 1, "citat": 1, "1": [2, 5, 27, 32, 35, 39, 44, 62, 64], "mathemat": [2, 3, 4, 33, 34, 68], "what": 2, "A": [3, 4, 5, 7, 12, 27, 30, 37, 68], "first": [3, 20, 22], "product": [3, 4, 8, 9, 10, 11, 12, 15, 17, 18, 21, 26, 41, 52, 55, 63, 68], "plan": [3, 12, 23, 32, 52, 55, 63, 68], "problem": [3, 7, 8, 9, 10, 11, 12, 17, 18, 20, 22, 23, 24, 25, 27, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39, 41, 44, 45, 46, 47, 48, 52, 53, 54, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65, 68], "statement": [3, 23, 24, 25, 46, 63, 64, 68], "model": [3, 4, 5, 7, 12, 13, 14, 15, 18, 19, 20, 21, 23, 24, 25, 26, 27, 29, 31, 32, 35, 37, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 53, 55, 62, 64, 68, 69], "data": [4, 7, 13, 14, 15, 17, 18, 22, 25, 31, 32, 35, 37, 40, 41, 42, 49, 50, 53, 57, 62, 64, 65, 66, 69], "driven": 4, "pyomo": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 41, 42, 44, 45, 48, 49, 50, 52, 53, 55, 57, 60, 65, 66, 67, 68, 69], "preambl": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60, 66], "instal": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60, 62, 66], "solver": [4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 38, 48, 52, 55, 57, 60, 66, 68], "represent": 4, "The": [4, 5, 8, 12, 20, 42, 45, 47, 50, 59, 63, 64, 68], "For": 4, "expert": 4, "creat": [4, 5, 25, 53], "subclass": 4, "concretemodel": [4, 5, 69], "basic": 5, "step": 5, "import": [5, 18, 29, 35, 57, 62, 65, 66, 68], "2": [5, 6, 27, 32, 35, 39, 44, 62, 64], "object": [5, 10, 11, 23, 25, 45, 69], "3": [5, 16, 27, 32, 39, 62, 64], "decis": [5, 25], "variabl": [5, 25, 69], "4": [5, 28, 62, 64], "express": 5, "5": [5, 36, 62, 64], "6": [5, 43, 62], "constraint": [5, 23, 25, 29, 44, 45, 58, 62, 63, 69], "7": [5, 51], "solv": [5, 35, 62, 63], "8": [5, 54], "report": [5, 7, 25, 32], "solut": [5, 19, 25, 32, 37, 39, 44, 46, 52, 55, 57, 59, 60, 62, 63, 64, 65, 66], "pprint": 5, "access": 5, "valu": [5, 59], "pyo": [5, 69], "panda": [5, 32, 69], "linear": [6, 16, 37, 42, 45, 50], "extra": [7, 15, 19, 21, 23, 27, 35, 37, 41, 46, 49, 64, 66], "materi": [7, 12, 15, 19, 21, 23, 27, 35, 37, 41, 46, 49], "wine": 7, "qualiti": [7, 66], "predict": 7, "l_1": 7, "regress": [7, 13, 40], "descript": [7, 8, 17, 18, 20, 22, 30, 33, 34, 35, 38, 44, 48, 52, 53, 60, 62, 63, 65, 69], "mean": [7, 14, 15, 59, 64], "absolut": [7, 13, 14], "deviat": [7, 13, 14], "mad": [7, 14], "preliminari": [7, 66], "look": 7, "which": 7, "featur": [7, 42, 50], "influenc": 7, "lad": [7, 13, 40], "line": [7, 27], "fit": 7, "identifi": 7, "multivari": 7, "how": [7, 46], "do": 7, "perform": [7, 42, 50, 52], "bim": [8, 9, 10, 11, 12, 17, 18, 52, 55], "microchip": [8, 55], "build": [8, 44, 64], "matrix": 8, "reformul": [8, 30, 37, 45, 57], "canon": 8, "form": [8, 42, 62], "lo": [8, 30], "dual": [9, 37, 42, 50], "deriv": 9, "variant": [10, 11, 55, 64], "two": [10, 27, 61, 62, 63, 66], "fraction": 10, "addit": [10, 14, 39], "fix": [10, 69], "cost": [10, 32, 34], "worst": [11, 15, 64], "case": [11, 15, 44, 62, 63, 64, 65], "minmax": 11, "function": [11, 50, 68], "maxim": [11, 15, 59], "lowest": 11, "possibl": 11, "profit": [11, 15, 59, 60], "demand": [12, 60, 62], "forecast": [12, 65], "acquisit": 12, "more": [12, 30], "parsimoni": 12, "least": [13, 40], "gener": [13, 37, 40, 53, 62, 63, 65], "visual": [13, 21, 25, 40, 53, 57, 69], "result": [13, 21, 32, 40, 41, 60], "portfolio": [14, 38, 48, 49, 58], "yfinanc": 14, "download": [14, 29], "histor": 14, "stock": [14, 37, 60], "price": [14, 41], "analysi": [14, 52, 57], "asset": 14, "scale": 14, "statist": 14, "daili": 14, "return": [14, 64], "risk": [14, 46, 47, 49, 64], "versu": [14, 64], "free": [14, 49, 53], "multi": [15, 26, 44, 69], "facil": [15, 20], "scenario": [15, 59, 62, 63, 65], "summari": [15, 59, 64], "mix": [16, 44], "integ": [16, 44, 55], "perturb": 17, "revisit": [18, 48], "implement": [18, 21, 23, 25, 26, 30, 42, 49, 50, 55, 65], "altern": 18, "block": [18, 69], "cryptarithm": 19, "puzzl": 19, "suggest": [19, 39, 41], "exercis": [19, 21, 23, 39, 41, 46], "locat": 20, "milo": [20, 26, 57], "formul": [20, 21, 25, 33, 34, 37, 38, 42, 45, 48, 50, 53, 63], "second": [20, 45, 55], "option": [20, 39], "job": [21, 22], "shop": [21, 59], "schedul": [21, 22, 25, 33, 53], "exampl": [21, 37, 68], "task": 21, "decomposit": 21, "print": 21, "gantt": [21, 22], "chart": [21, 22], "applic": 21, "batch": [21, 68], "process": [21, 22], "singl": [21, 44, 45, 54, 56], "strategi": [21, 24, 27, 64], "multipl": [21, 44, 45], "overlap": 21, "ad": [21, 46, 62], "time": [21, 22, 29], "unit": [21, 66], "clean": 21, "out": [21, 22], "zero": 21, "wait": 21, "polici": [21, 35], "refer": [21, 37, 68], "specif": 21, "cleanout": 21, "comput": 21, "impact": 21, "machin": [22, 42, 50], "empir": 22, "rule": 22, "fifo": 22, "earliest": 22, "due": 22, "date": 22, "edd": 22, "shortest": 22, "spt": 22, "disjunct": [22, 23, 26], "program": [22, 26, 42, 68], "mainten": 23, "ramp": 23, "specifi": 23, "minimum": [23, 34], "number": [23, 30], "oper": [23, 32], "dai": 23, "between": [23, 30, 62], "period": 23, "recharg": 24, "an": [24, 29, 39], "electr": 24, "vehicl": 24, "charg": 24, "station": 24, "inform": [24, 59], "rout": 24, "car": 24, "workforc": 25, "shift": 25, "set": [25, 42, 50, 55, 69], "paramet": [25, 49, 69], "master": 25, "categor": 25, "worker": 25, "store": 25, "manag": 25, "factori": 26, "strip": 27, "pack": 27, "statment": 27, "lower": 27, "upper": 27, "bound": [27, 69], "shelf": 27, "width": 27, "version": [27, 47], "up": [27, 59], "box": [27, 55], "rotat": 27, "place": 27, "dimens": 27, "advanc": 27, "topic": 27, "symmetri": [27, 53], "break": 27, "network": [28, 30, 35, 66], "cryptocurr": 29, "arbitrag": [29, 31], "search": 29, "networkx": 29, "ccxt": 29, "exchang": 29, "repres": 29, "direct": 29, "graph": [29, 31, 33], "order": [29, 45, 55], "book": 29, "trade": 29, "find": 29, "demonstr": [29, 31], "opportun": 29, "brute": 29, "forc": 29, "simpl": 29, "cycl": 29, "capac": 29, "question": 29, "user": 29, "real": 29, "from": [29, 37, 39, 60], "dinner": 30, "seat": [30, 62], "arrang": 30, "minim": [30, 32], "maximum": 30, "group": 30, "size": 30, "tabl": 30, "max": 30, "flow": [30, 34, 35, 65], "systemat": 30, "comparison": [30, 40], "algorithm": [30, 37], "forex": 31, "triangular": 31, "displai": [31, 32, 69], "gasolin": 32, "distribut": [32, 39, 60, 62], "franchis": 32, "total": [32, 53], "deliveri": [32, 39], "entri": 32, "rate": [32, 49], "owner": 32, "share": [32, 45], "compar": [32, 35], "appendix": [32, 45, 67], "method": [32, 45, 60, 62], "manual": 32, "format": 32, "graphviz": 32, "color": 33, "energi": [35, 57, 66], "dispatch": [35, 57, 66], "background": 35, "power": [35, 65], "physic": 35, "setup": 35, "code": [35, 69], "edg": 35, "structur": 35, "instanc": 35, "opf": 35, "strict": 35, "fossil": 35, "fuel": 35, "pt": 35, "three": 35, "convex": [36, 39, 40], "cut": 37, "pattern": 37, "known": [37, 69], "bilinear": [37, 39], "hybrid": 37, "jump": 37, "document": 37, "column": [37, 63], "wikipedia": 37, "woodwork": 37, "googl": 37, "sheet": 37, "markowitz": [38, 48, 58], "milk": 39, "pool": 39, "blend": 39, "wholesal": 39, "busi": 39, "usual": 39, "bui": 39, "truck": 39, "remot": 39, "supplier": 39, "why": [39, 41, 68], "ar": 39, "hard": 39, "approxim": [39, 60], "global": 39, "nonlinear": [39, 42, 50], "gnlo": 39, "couenn": 39, "conclud": 39, "remark": 39, "bibliograph": [39, 44, 45, 46, 47, 49, 63, 64], "note": [39, 44, 45, 46, 47, 49, 63, 64], "ordinari": 40, "squar": 40, "ol": 40, "refineri": 41, "shadow": 41, "cvxpy": 41, "crude": 41, "oil": 41, "feed": 41, "kerosin": 41, "so": 41, "high": 41, "support": [42, 50], "vector": [42, 50], "binari": [42, 47], "classif": 42, "read": [42, 50], "select": [42, 50], "train": [42, 50], "svm": [42, 50], "classifi": 42, "metric": [42, 50], "quadrat": [42, 44, 45], "primal": [42, 50], "kernel": [42, 50], "space": [42, 50], "trick": [42, 50], "polynomi": [42, 50], "conic": [43, 45, 47, 50], "design": [44, 49], "multilay": 44, "insul": 44, "analyt": [44, 60, 62], "n": 44, "layer": 44, "miqco": 44, "econom": [45, 57], "quantiti": 45, "usag": 45, "eoq": 45, "classic": 45, "item": 45, "hyperbol": 45, "cone": [45, 55], "as_domain": 45, "simplifi": 45, "rotated_quadrat": 45, "extend": 45, "resourc": 45, "test": 45, "larger": 45, "soco": 45, "luenberg": 46, "s": [46, 47, 64], "invest": 46, "wheel": 46, "simul": [46, 47, 52], "avers": [46, 49], "doe": 46, "chang": 46, "kelli": 47, "criterion": 47, "log": 47, "growth": [47, 49], "game": 47, "outcom": 47, "constrain": [47, 55, 57], "financi": 49, "effect": 49, "equiti": 49, "multipli": 49, "interest": 49, "extens": [49, 62], "radial": 50, "basi": 50, "account": 51, "uncertainti": [51, 55], "meet": 51, "realiti": 51, "robust": [52, 54, 55, 63], "via": 52, "actual": 52, "fleet": 53, "assign": 53, "flight": 53, "naiv": 53, "unimodular": 53, "aircraft": 53, "reduc": [53, 68], "riski": 53, "stage": [54, 56, 61, 62, 63, 66], "origin": 55, "copper": 55, "consumpt": 55, "counterpart": 55, "cardin": 55, "adversari": 55, "approach": 55, "budget": 55, "ball": 55, "environ": 55, "9": 56, "stochast": [56, 59, 62, 64, 65], "system": 57, "chanc": [57, 58, 62], "ed": 57, "understand": 57, "sensit": 57, "pop": 59, "net": 59, "expect": 59, "evm": 59, "vss": 59, "perfect": [59, 65], "evpi": 59, "seafood": 60, "center": 60, "explicit": 60, "determinist": [60, 62], "averag": [60, 62, 63], "sampl": [60, 63], "converg": 60, "saa": [60, 62, 63, 65], "10": 61, "airlin": 62, "alloc": 62, "attribut": 62, "its": [62, 64], "continu": 62, "uncorrel": 62, "correl": 62, "differ": 62, "type": 62, "tackl": 62, "farmer": 64, "recommend": 64, "plant": 64, "recours": 65, "action": 65, "imbal": 65, "nonzero": 65, "wind": 66, "curtail": 66, "commit": 66, "packag": 66, "assess": 66, "work": 67, "workflow": [68, 69], "monad": 68, "pure": 68, "composit": 68, "map": 68, "filter": 68, "functool": 68, "mayb": 68, "failur": 68, "wrap": 68, "transform": 68, "pyomomonad": 68, "reactor": 68, "builder": 68, "execut": 68, "alternt": 68, "syntax": 68, "style": 69, "guid": 69, "convent": 69, "namespac": 69, "instead": 69, "abstractmodel": 69, "rangeset": 69, "domain": 69, "rather": 69, "than": 69, "within": 69, "when": 69, "prefer": 69, "constraintlist": 69, "decor": 69, "improv": 69, "readabl": 69, "name": 69, "short": 69, "mai": 69, "all": 69, "cap": 69, "capit": 69, "tidi": 69, "dimension": 69, "acknowledg": 69}, "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.ext.intersphinx": 1, "sphinxcontrib.bibtex": 9, "sphinx": 56}}) \ No newline at end of file