简单的焊缝编号递增复制
本帖最后由 fangmin723 于 2025-4-23 15:32 编辑焊缝编号递增复制 快捷键《 DZFZ 》
多关键字[增(W)/减(S)/步减(Q)/步增(E)/括号(B) or 常规(R)/子级(D) or 父级(A)]
适用范围：A-Z单个字母开头，后面只有数字或者数字后面跟着-，-后面只有数字的字符串
如：B1；A10；D101；B1-1；A10-5；D101-50等等
;;说明:(DZFZ)焊缝编号递增复制
(defun C:DZFZ(/ dxf dxflst endstr ent fnum index iskh iskhchange issub keywords matchstr prfix promptstr pt pt0 refpt setp snum startstr str tempstr txthig vet)
(defun dxf(ent code)
(if ent
(progn
(cond
((equal (type ent) 'ENAME) (setq ent (entget ent)))
((equal (type ent) 'VLA-OBJECT) (setq ent (entget (vlax-vla-object->ename ent))))
)
(cdr (assoc code ent))
)
(progn
(princ "\n对象传入错误，传入图原名、组码表或VLA-OBJECT对象！")
nil
)
)
)
(setq matchstr "#,##,###,#-#,#-##,#-###,##-#,##-##,##-###,###-#,###-##,###-###,(#),(##),(###),(#-#),(#-##),(#-###),(##-#),(##-##),(##-###),(###-#),(###-##),(###-###)")
(if (and
(progn
(initget "E")
(setq ent (entsel "\n拾取文字[输入内容(E)]:"))
(if ent (if (= (type ent) 'STR) (setq ent (getstring "\n输入内容:")) (setq ent (car ent))))
)
(wcmatch
(setq str
(if (= (type ent) 'ENAME)
(progn
(setq pt0 (dxf ent 11) refpt (getpoint "\n拾取参考点:"))
(setq vet (mapcar '- pt0 refpt))
(setq dxflst (entget ent))
(setq dxflst (vl-remove (assoc 5 dxflst) dxflst))
(dxf ent 1)
)
(progn
(setq
refpt (getpoint "\n拾取参考点:")
pt0 (getpoint refpt "\n拾取相对放置点:")
vet (mapcar '- pt0 refpt)
txthig (if (setq txthig (getreal "\n输入文字高度<3.5>:")) txthig 3.5)
dxflst (list '(0 . "TEXT") (cons 1 ent) (cons 10 pt0) (cons 11 pt0) (cons 40 txthig) '(41 . 0.7) '(71 . 0) '(72 . 4))
)
ent
)
)
)
matchstr
)
)
(progn
(setq
iskh (wcmatch str "(*)")
issub (wcmatch str "*-*")
prfix (substr str (if iskh 2 1) 1)
setp 1
startstr (if iskh "(" "")
endstr (if iskh ")" "")
)
(setq tempstr (vl-string-trim (strcat startstr prfix endstr) str))
(if issub
(setq
index (vl-string-search "-" tempstr)
fnum (atoi (substr tempstr 1 index))
snum (atoi (substr tempstr (+ index 2)))
)
(setq fnum (atoi tempstr) snum 1)
)
(setq str
(strcat startstr prfix
(if issub
(strcat (itoa fnum) "-" (itoa (setq snum (+ snum setp))))
(itoa (setq fnum (+ fnum setp)))
)
endstr
)
)
(cond
((and iskh issub) (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/常规(R)/父级(A)]" keywords "W S Q E R A"))
((and iskh (not issub)) (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/常规(R)/子级(D)]" keywords "W S Q E R D"))
((and issub (not iskh)) (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/括号(B)/父级(A)]" keywords "W S Q E B A"))
(t (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/括号(B)/子级(D)]" keywords "W S Q E B D"))
)
(setq iskhchange nil)
(while (progn (initget keywords) (setq pt (getpoint refpt (strcat "\n拾取放置点" promptstr "步长<" (itoa setp) ">,当前<" str ">:"))))
(if (= (type pt) 'STR)
(progn
(setq pt (strcase pt))
(cond
((equal pt "W") (if issub (setq snum (+ snum setp)) (setq fnum (+ fnum setp))))
((equal pt "S") (if issub (setq snum (if (< (- snum setp) 1) 1 (- snum setp))) (setq fnum (if (< (- fnum setp) 1) 1 (- fnum setp)))))
((equal pt "Q")
(setq setp (1- setp))
(if issub
(setq snum (if (< (1- snum) 1) 1 (1- snum)))
(setq fnum (if (< (1- fnum) 1) 1 (1- fnum)))
)
)
((equal pt "E")
(setq setp (1+ setp))
(if issub (setq snum (1+ snum)) (setq fnum (1+ fnum)))
)
((equal pt "R") (setq iskh nil)
(if iskhchange
(progn
(if issub
(setq snum (+ snum setp))
(setq fnum (+ fnum setp))
)
(setq iskhchange nil)
)
)
)
((equal pt "B") (setq iskh T)
(if (not iskhchange)
(progn
(if issub
(setq snum (if (< (- snum setp) 1) 1 (- snum setp)))
(setq fnum (if (< (- fnum setp) 1) 1 (- fnum setp)))
)
(setq iskhchange t)
)
)
)
((equal pt "A") (setq issub nil fnum (+ fnum setp)))
((equal pt "D") (setq issub T))
)
(setq
startstr (if iskh "(" "") endstr (if iskh ")" "")
str
(strcat startstr prfix
(if issub
(strcat (itoa fnum) "-" (itoa snum))
(itoa fnum)
)
endstr
)
)
)
(progn
(setq iskhchange nil)
(if (not issub) (setq snum 1))
(setq dxflst (subst (cons 1 str) (assoc 1 dxflst) dxflst))
(setq pt (mapcar '+ pt vet))
(setq dxflst (subst (cons 10 pt) (assoc 10 dxflst) dxflst))
(setq dxflst (subst (cons 11 pt) (assoc 11 dxflst) dxflst))
(entmake dxflst)
(setq str
(strcat startstr prfix
(if issub
(strcat (itoa fnum) "-" (itoa (setq snum (+ snum setp))))
(itoa (setq fnum (+ fnum setp)))
)
endstr
)
)
)
)
(cond
((and iskh issub) (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/常规(R)/父级(A)]" keywords "W S Q E R A"))
((and iskh (not issub)) (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/常规(R)/子级(D)]" keywords "W S Q E R D"))
((and issub (not iskh)) (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/括号(B)/父级(A)]" keywords "W S Q E B A"))
(t (setq promptstr "[增(W)/减(S)/步减(Q)/步增(E)/括号(B)/子级(D)]" keywords "W S Q E B D"))
)
)
)
)
(prin1)
)
(princ "\n焊缝编号递增复制 快捷键《 DZFZ 》\n适用范围：A-Z单个字母开头，后面只有数字或者数字后面跟着-，-后面只有数字的字符串\n如：B1；A10；D101；B1-1；A10-5；D101-50；等等")
(prin1)
阴线标注的会自动递增么? 收藏了，谢谢 jy06614998 发表于 2025-4-24 08:21
阴线标注的会自动递增么?
没有考虑引线，你可以试试，看看能否增加 fangmin723 发表于 2025-4-24 11:23
没有考虑引线，你可以试试，看看能否增加
引线标注肯定行不通，已试过多次，多次请教大神无果 305341043 发表于 2025-4-26 00:27
引线标注肯定行不通，已试过多次，多次请教大神无果
什么样的引线，截图或者上传个测试图看看 fangmin723 发表于 2025-4-26 07:44
什么样的引线，截图或者上传个测试图看看
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B1cNnwSkgFAMA1me9HVDlHb81AawaAMylrp9YV33fn4eGhJk2aaN++fYqMjCwV2qviCsZ1jfnDi3M5Omx+3RcuXKikpCQ1bty4xHpN+eCDD0o8jomJqfAPOuqq8PDwUn/nzdMWQE2o9fBKSAUAoG4xr/5b3m5oWYHWPG58OnXlmKLdbpevr6+OHj0qlXNrFTMAuQPzhxdne3T41B36hIQErVq1Svv27VODBg1KzFWn0NBQRUdHy7KsUt93Pv/88yUen+/Cw8PLPP5ufn2BmlBj4ZWQCgDA+cHcQT3dbqgZbM/l6KH5PkP9taPnamw2m2w2mzIzM6W/Pkbz+HBwcPA5BffzgXm09my/9qf++ToRkFJSUip9waaJEyfKsqyzqtjY2FJ/ziUpLCysQn8Gg4ODS/0aFa2aEBoaqvDwcMXHx5cZXFXOD6eA6lbl4ZWQCgDA+cs80qkzXEDJDLYVvXCTyrmfqiuw2WwqKipSbm7uybWyjg9PnDjxrI/Ong8qcnTY/LNxIgAfP35c3t7eJXo1KSEhocLB1RWYAfhMFRsbq7lz55b7PXpYWJi5BNSISoXXwMDAOhdSLcuSl5cXRVEURZ23dejQIfN/f6VmKlq9evUq8bpz5swpNXNqvf/++yXmJalXr16l5soqc5dpx44dpWZqo8zPb3x8vLZu3aqioqIS6xwfLn209ExHh80jwyfCYk5Ojjw9PU+ZrFnBwcFn/NjdRV0O8aj7PCRV+PxBenp6pY9w1LTt27eroKDAXAYA4LzRuHFjNWvWrMRaVbxX1MfHp9QPohMSEkrsOJaloh9P27ZtS3yfkZGRoaSkpBIzZ9KiRQs1bNjQXD6j1NRUJScnm8tSGb+fY8eOyW63Kzg4WCkpKSVmZ8yYoYkTJ5ZYmzlzZplHLs33FiYkJCgkJOTkY6fTqXHjxmnevHl6/vnnS72uh4dHiccVER0dXeK4rPkxmMx58/cWGhqq2NjYk4/P9Hqn/sDi1NcaOnSoHn74YQ0aNOiU6dMHKfOHH1UhISFBY8aMKffXPMH8vFSlM32dy/ozVxViYmI0dOhQcxmoUZUKr3fddZfq16+vdu3aqXXr1urTp4/atm1rjrmUESNG6PDhw+YyAADnjdtvv1333XdfibUzHdc8G+brxsbG6rHHHisxU5aQkJBSO46zZ8/WggULSqyZHn30Ud14440nH5/tr3cq8zXO1uLFi/XKK6+Yy1IZn4dly5apYcOGuummm8r8HiM+Pr5U6C8rdJ2P4VVl/P7L+r2rjN//qXPDhg1TZGSkrrzyylOeUf5rqYzwWtbHVp7Q0FD16NFDjz32WKmvnc7w66qMz8uZPo9VqSrDa0JCgqZNm3batwYANc2qbNlsNsvb29tq2LCh1blzZ2vo0KHW448/bi1atMj6888/rd27d1uuokOHDqU+foqiKIo6n2rGjBnm//5KzVSk4uPjS7zmjBkzSs2UV+Zz4+PjS82YFR0dXeI5VgV+H2W9xtmIjo4u9Vonyvz8/vTTT1ZCQoLVrFmzUrOSrNDQ0BLzVjm///Dw8NPOOJ1OKzIy0nI6naU+BqsCn5uyyvx8mR+DWeZ8WX8mzI+1rBnztcxf98Ybb7SWL19e4nUsy7JCQ0NLvc6JMpX3656pyvr6WWf4fJufF/P3U51lfr6tM3ysoaGhpT5e66+/A6f7/FJUbVSl3vN6QnFxsfLy8pSamqrt27crOjpaL774om699VZdfPHF6t27t7p06aJhw4bpiSee0H//+19t3LjxnI/+AACA2lHWfR7P5eqt5nPP5sJNO3bsMJeqZAe5qhUXF8tut8vLy8tsSVx9+KyvOlzWVYZPcDqdysvLK7FWU+Li4hQREWEunzdfv7i4OA0dOrTURZiGDBmi2NjYM/49BWpSlYTX8hBqAQA4P5x6IZ2qcqbX3LJli7mkHj16mEunNXToUHl4eJyxzHB5LoqLi+Xh4SE/Pz+zdVJZx1Xd5erDZV112GQGJDPwNmzYUNnZ2SXWalJUVFSpq0eXF8Lrqri4uFIBVpLmzp173gR11H3VGl7LQ6gFAKBuqY6Lz5zpNcu6qFO3bt3MpVpXVFSk/Px81a9f32yVUNbunfle4PNVfHx8icdmWC3vKsOSZLfb1bx5cx0/fvzkWm0wd4PP5tY/dU15u8wTJ04s9TUDakOthNfyEGoBAHA91flN6+l2dMwdO7nobldxcbHS0tJKXVHZFBUVpZiYmBJrFT0+XNaudFUEKfOiQmborCjzfr/mrvupP8gwf0273a62bdvq6NGjJdZrWlmf8/NRVFRUmScR5s6dWyV/xoDKcKnwWh5CLQAAtce8wm9CQkKpY7dnW+caRsva7arOMF0RlmVpz5496tChg9kqpaxbjVTk+HBZu9JVwTzSW9b7jivCvFrtqWHV/HqaQdfb21tt27Yt80rOqB6RkZGl/q7KjU4KwHXVifBanoqE2l27dpkvAwAAyhEaGloq0EybNq3E43NxrmHUfO+jygjTtc2yLG3dulXdunWTp6en2S6lrGOZ5xoKyrpNy8iRI82lc1JWgK7K3UZz1/nE193chTWDbmBgoIKCgnTkyJES6zXNFY+sVydzF16VOCkAVJU6HV7Lc7pQCwAAzl5ZgcgMF+eirDBqhpdTxcXFlQo9rvYNtGVZ2rhxo7p37y5fX1+zXUp5x4fPNZSbO2OdOnUq8fhclfW1rsodXnNH9cTX/dRdWPPzIkktW7aUJKWlpZmtGlXWKYGyfohwPinrBy0VOSkAVJXzMryWp7i42FwCAACnMXHixBKPywoX56Ks97Ge6cJNzz//vLlU5ReQqWzw27Ztm5o1a6ZGjRqZrTKVdXzY3OE+E3MXe8iQIZUKFWY4My+cVFnmDz3K+njNgKu/rjC9Z8+eWr3acFm3iqrs34W6oKyrLKsCJwWAquJW4RUAAJy9ssJhWeHiXJmhS2dx4abyLiBzuuedjdDQUMXHx58xQJ/J/v37lZGRoS5dupitcpW1q3UuytrFrmiomDFjRqlwVtbXqbLMwGd+vGbA9fLy0qWXXqo1a9aooKCgRK+mhIaGau7cueZylfxdqAvGjBljLrnc6Qe4D8IrAAAoU1nHec1wURFl3fPU3PUzRUZGlgo++msHNj4+vtQO3pmcCK2xsbGlQltFZGRk6LffftOAAQNkt9vNdpnKOj58LsraxQ4ODj7nz8eMGTNK7bCrnK9TZZmB79TPfVmfi8DAQF188cVavXp1jZ+gCw8PP/lnxJSQkFAlfxfqgvJ+eMTxYdQGwisAACiTuRtZVrioKPO1znThJv111NZ8nv56bmxsrCzL0owZM8r8hjo0NFShoaGaMWOGLMs6bWiNiYkp81jv6eTn5+t///ufrrjiCgUEBJjtcp3rr2Mqb1csNjZW8fHxCg8PL/fzER0dLcuyygyuld0VLs/pAp8ZbPXXcW5fX98qee/txIkTZVnWWdfcuXPL/TNS1uf9dIKDg0u9fmWrrK9rdeHqw3AVhFcAAFBKWUcCy3rvaUWVFVTK2uk1DR06tMxdoBMmTpx4MsieWrGxsYqNjS0zqJ2QkJCgsLCwCgfKtWvXqmnTpurYsaPZOq3KBMW4uLhynx8cHKy5c+eW+/kwfzhxwsyZM08bMiurrB9AqIxga7fbNXjwYK1bt86lbpMTFhZWpe8FrivKCuwcH0ZNI7wCAIBSzGO81X3xHpWx01ueyMhIhYWFlbkTVFEREREKCQmp1O9x//79Wr9+va655pqzPjqsKjg+HBUVpbCwMHO5QiIiIqrluPCpyvrBRVm//3r16unaa6/VkiVLlJuba7ZrXExMjDw8PCr1Z6QuO93xYaCmEF4BAEAJoWXc27U6Lt5T1jfCZ7uLExcXp5CQkEqF2ISEBEVERMjDw6PMMH2ucnJytGjRIt1www2qX7++2T6tiu72nhAXFycPD48yQ+DZiImJUVhYWJV8Hs6krF+jrEDbs2dP1a9fX6tXrzZbNSIhIUExMTEn/4xU9mt0Pijv+HB0dLS5BFQbi6IoiqIoqq5XeHi4FR0dbcXHx1tliY+Pt6Kjo63w8PBSz62qatWqlbVt2zZryJAhpXqVLafTaUVGRlpOp7NUzyxX+FxUpry9va2oqChr9uzZlpeXV6k+RVHuWR5//QcAAAAqydPTU//+97/VsWNH3XXXXVV6b1Kn06lx48Zp3rx5yszMNNvnlc6dOysmJkZ33nlnmVf7BeCeODYMAABQRQoKCvTJJ5+ob9++6tGjh9nGWXA4HBo1apS2bNmiDRs2mG0AbozwCgAAUIV27Nihb7/9VhEREfL19TXbOIM2bdro9ttv11tvvXXe7zADODeEVwAAgCqUm5urOXPmaNCgQerVq5fZxml4enpqzJgx2rlzp1atWmW2Abg5wisAAEAV27x5s5YsWaJHHnlEAQEBZhvl6NKli+688069+uqrSk9PN9sA3BzhFQAAoIrl5eXpzTff1AUXXKCrr77abKMM/v7+evTRR/Xjjz+67b1UAZwe4RUAAKAa7Ny5U6+99pomT56stm3bmm0Yrr76aoWFhemVV16p0qs0Azh/EF4BAACqQVFRkT777DPt379fjzzyiPz8/MwR/KVDhw565plnNH36dG3fvt1sA4BEeAUAAKg+qampevrppzVs2DBde+21stvt5ojbCwgI0OTJk5WQkKCPP/5YhYWF5ggASIRXAACA6rVhwwa98MILeu6557j3q8HT01N33nmnLrnkEj311FNKS0szRwDgJMIrAABANSosLNSnn36qb7/9Vq+99ppatmxpjrglm82mK664QpMmTdL//d//adu2beYIAJRAeAUAAKhmWVlZmjp1qvLy8vTCCy+oYcOG5ojb6dmzp2bMmKHXX39dy5cvV3FxsTkCACUQXgEAAGrAwYMHNXHiRHXr1k1PPPGEW9//tXPnzpozZ46WL1+uqKgo5efnmyMAUArhFQAAoIbs2LFDERERuuaaazRp0iS3DLDBwcGKiorSli1b9PzzzyszM9McAYAyEV4BAABq0Lp16zRu3DjdeOONevzxx1WvXj1z5LzVpUsXvfPOO9q7d6/+9a9/KTU11RwBgHIRXgEAAGrYmjVrNHbsWA0bNkxTp05VUFCQOXJesdls6tOnj+bPn6+dO3fq4Ycf1uHDh80xADgtwisAAEAt+PXXX3XHHXeoZ8+emjNnjjp27GiOnBe8vLx09dVX66OPPtJPP/2kRx99lOAKoEIIrwAAALVk48aNuvPOO1VQUKDPPvtMAwYMkKenpzlWZwUGBmrChAl66623NGfOHE2ZMoWjwgAqzC5pirkIAACAmpGWlqaVK1eqXr16evbZZ1VUVKQdO3YoNze3xJyXl5d69+6tdevWufzVeW02m4KDgzVt2jQNGzZMkZGRWrhwoXJycsxRADhr7LwCAADUstTUVL388st64IEHdPfdd+u9995T79696+QubEBAgG699VYtWbJEdrtdN910k6Kjo10+cANwfYRXAAAAF5CXl6evvvpKI0aM0L59+/T5559r0qRJatmypWw21/+WzcvLS3369NG8efM0ZcoUTZ8+XREREdq+fbs5CgAV4vr/EgIAALiRxMREPfbYY5owYYIGDx6sr7/+WnfddZcaN24sDw8Pc7zWeXl5qUuXLnrhhRf0+eef6+jRo7ruuuv0/vvvKz093RwHgArzkGSZiwAAAKh9jRo10nXXXacHHnhA2dnZ+uabb/Tpp58qMTFRhYWF5niN8vX1VadOnXTnnXfqxhtv1Pr16/Xaa6/pt99+K/V+XQCoCoRXAAAAF2az2dSkSRNdd9116tixo6666irFxMRo8eLF2rFjhzIzM1VcXGw+rVp4enqqYcOG6tu3r26//XZdcsklWrNmjebOnau1a9cqMzPTfAoAVBnCKwAAQB3gdDoVERGhnTt3atSoUerXr5+SkpL01Vdf6YcfftCuXbuUkZGhgoIC86kVZrPZ5OXlpUaNGqlHjx4aMmSIrrzySknSsmXLtGjRIm3bto2rCAOoEYRXAACAOsDpdGrcuHGaN2+eCgsL1aZNG11++eUaPny4unfvrvT0dK1du1Y///yztmzZov379ys9PV15eXkqLCxUcXFxuTu0drtdNptNnp6e8vX1VcOGDdWuXTv16tVLoaGh6t69u/Lz87V69WotW7ZMv//+u44cOVLrR5cBuBfCKwAAQB1wang99Xiun5+fmjZtqh49eigsLEwXX3yx2rRpI7vdrmPHjmn//v1KTk7WoUOHlJaWpqysLBUWFsrDw0NeXl4KCAhQw4YN1bx5c7Vs2VLNmzeXv7+/MjMztW3bNsXFxemXX35RfHy80tLSuOUNgFpDeAUAAKgDyguvp7Lb7fLx8VFgYKCaNm2qVq1aqU2bNmrVqpWaNGmievXqyc/PTw6HQ5ZlKT8/X5mZmTp27JgOHjyovXv3as+ePdq/f7+OHDmizMxM5eXlmb8MANQKwisAAEAdcDbhtTwnjgXbbDZ5eHicvOWOZVknjxOf7lgxALgC7vMKAABwnisqKlJBQYHy8vKUm5urnJwc5eTkKDc3V/n5+SffEwsArozwCgAAAABweYRXAAAAAIDLI7wCAAAAAFwe4RUAAAAA4PIIrwAAAAAAl0d4BQAAAAC4PMIrAAAAAMDlEV4BAAAAAC6P8AoAAAAAcHmEVwAAAACAyyO8AgAAAABcHuEVAAAAAODyCK8AAAAAAJdHeAUAAAAAuDzCKwAAAADA5RFeAQAAAAAuj/AKAAAAAHB5hFcAAAAAgMsjvAIAAAAAXB7hFQAAAADg8givAAAAAACXR3gFAAAAALg8wisAAAAAwOURXgEAAM5jDodDXl5e8vPzU0BAgOrXr68GDRqoQYMGqlevnpxOp3x9feXp6Sm73W4+HQBchocky1wEAACAa3E6nRo3bpzmzZunzMxMsy1J8vb2VmBgoJo0aaJ27dqpY8eOat++vVq2bKnGjRvL6XTKy8tLdrtdlmWpqKhIOTk5Sk9P1+HDh7Vnzx7t2rVLO3fu1N69e3X06FFlZ2eroKDA/KUAoMYRXgEAAOqAssKrw+FQYGCggoODdckll6h///7q1q2b/Pz8lJaWpqSkJCUmJmrfvn06fPiwjh8/rtzcXBUWFsrDw0Oenp7y9/dXgwYN1KxZM7Vp00bt27dXq1at5OPjo5SUFP3+++/68ccftW7dOu3fv19ZWVnmhwYANYLwCgAAUAecCK/vvPOO7Ha7evTooeHDh2vw4MGqX7++tm7dqp9++km//fabEhMTlZqaejKoFhYWmi9Xis1mk91uPxlomzZtqs6dOys0NFRhYWFq1qyZduzYoWXLlmnFihVKSkpSTk6O+TIAUG0IrwAAAHVA/fr1NW7cOOXl5WnUqFFq1qyZVq9eraVLl2rdunU6fPiwcnNzVVxcbD61UhwOh/z9/dW2bVsNGDBAI0aMUMeOHfXrr79q/vz5+vnnn5Wammo+DQCqHOEVAADAhXl6eqpDhw6688475e3trV69eunTTz/VihUrdODAAeXl5ZlPqVYBAQHq1KmTbrrpJt144406evSo5s6dq5iYGKWkpJjjAFBlCK8AAAAuyG63q3Xr1ho7dqzuuOMOrV+/Xr///rs++OADJScnm+M1zuFwqHnz5ho+fLjGjx+vvLw8vfbaa1q+fLmOHz9ujgNApdklTTEXAQAAUHvq16+v0aNH64033lBAQICefPJJvfvuu+ratat+/vln5efnm0+pccXFxUpPT9fvv/+upUuXqqCgQI899pgGDRqkpKQkHTp0SEVFRebTAKDCCK8AAAAuwuFw6KKLLtLMmTM1ZMgQvfTSS3rhhRe0ZcsWeXh4qHfv3lq3bp1LhNcTLMtSZmam1q1bp6+//lpt27bV008/rXr16mnr1q3l3tYHAM6VzVwAAABAzQsICNA999yjRYsWKSkpSdddd50+/vhjpaWlmaMuqaioSImJiXrqqac0ZswYXXbZZVq4cKFCQ0PlcDjMcQA4Z4RXAACAWtaqVSu99tprmjhxoh577DFNmjRJiYmJVX7l4JqQl5enH3/8USNHjtSqVau0YMEC3XXXXfL39zdHAeCccGwYAACgFvXs2VPz5s2Tt7e3xo8fr9WrV6ugoMAck5eXl0seGy5PVlaW4uLitHv3bj3zzDNq0aKF1q1bp+zsbHMUAM4KO68AAAC1wG636/LLL9fHH3+sDRs2aOzYsdqyZUud3G0tT25urpYsWaLRo0crLCxMb7zxhlq1amWOAcBZIbwCAADUMIfDoWuuuUbvvPOOPvzwQz355JM6fPiwOXZeKCoq0u+//67bb79dTqdTb7/9ttq3b2+OAcAZEV4BAABqkN1u1zXXXKNZs2Zp+vTpmjlzpjIyMsyx886uXbsUHh6ujIwMAiyACiG8AgAA1BCbzaYrrrhCr7/+uqZNm6Z33nlHOTk55th5Kzk5WQ8++KBSU1P15ptvcoQYwDkhvAIAANSQPn366I033tDs2bP13nvvKTc31xw57x08eFAPPfSQiouLNW3aNDVq1MgcAYAyEV4BAABqQIcOHfTGG29oyZIlmjNnjlsG1xP279+vBx98UO3bt9e//vUv+fn5mSMAUArhFQAAoJo1aNBAL730knbv3q3//Oc/ysrKMkfczs6dO3X//ffrhhtu0KhRo+RwOMwRACiB8AoAAFCNvLy8FBERoY4dO+rxxx9XamqqOeK21q9fryeeeEKTJ0/W3/72N7MNACUQXgEAAKrRpZdeqgkTJmjSpEnatWuX2XZrRUVF+vLLL7Vw4UK99NJLatq0qTkCACcRXgEAAKpJs2bN9Pzzz2vevHlatWqV2Yak3NxczZw5Uw6HQxEREfLy8jJHAEAivAIAAFQPT09PjR8/XoWFhYqKilJ+fr45gr8cOHBATz31lO6++2717t3bbAOARHgFAACoHj169NDdd9+tf//73zp8+LDZhiEuLk6LFy/W448/rsDAQLMNAIRXAACAqubn56eHHnpIK1asUGxsrNlGGfLy8jR79mx17txZgwcPNtsAQHgFAACoan/729/Uv39/zZo1Szk5OWYb5di9e7fmzJmjhx9+WI0aNTLbANwc4RUAAKAK+fn56f7779fixYu1bds2s43TKCoq0qJFixQQEKCrrrrKbANwc4RXAACAKnThhRfq4osv1nvvvcdFmirg4MGDeueddzRhwgTVr1/fbANwY4RXAACAKuLl5aV//OMfWrFiheLj4802zkJRUZGWLl2q5s2bq2/fvmYbgBsjvAIAAFSRVq1a6eqrr9aHH36ovLw8s+2y4uPjZVmWLMtSaGio2a5x+/fv17Jly3TnnXfKx8fHbANwU4RXAACAKjJo0CAlJydrw4YNZstlzZgxQ8HBweZyrSooKNCiRYt06aWXqnXr1mYbgJsivAIAAFQBp9Opm2++Wf/973+VkZFhtl1SeHi4Jk6caC67hK1bt2rv3r26/PLLzRYAN0V4BQAAqAJt2rRR586d9d1336m4uNhsu5zQ0FDNnTvXXHYZmZmZWrp0qa6//nr5+fmZbQBuiPAKAABQBf7+979r9+7dSkpKMlsuJzQ0VLGxseaySykuLtb333+v7t27q1mzZmYbgBsivAIAAFSSt7e3Bg8erO+++07Z2dlm26WEh4e7fHA9ITExUampqbrooovMFgA3RHgFAACopHr16qlnz56KjY1VUVGR2XYZ0dHRLn1U2JSZmak1a9aof//+cjgcZhuAmyG8AgAAVFLr1q3l5eXlsvd2DQ8Pl2VZGjJkiNlyaQUFBYqLi9PFF18sX19fsw3AzRBeAbgdLy8vcwkAKqVr167at2+fjh07ZrZqVWhoqOLj48vcbU1ISFBYWJi57HK2bNmiFi1aqEGDBmYLgJshvAI4b3l5ealevXrq2LGjBg0apMjISE2bNk1Hjx5Vly5dzHEAqBC73a4LL7xQmzdvVm5urtmudWXdwzUiIkIhISHmsks6cOCACgsL1bJlS7MFwM0QXgHUeWWF1A8//FA///yzNmzYoISEBK1YsUKvvfaaHn30UTmdTvMlAKDCPD091aVLF23ZskWFhYVm26XExMQoLCxMUVFRZstlZWZm6uDBg2rXrp3ZAuBmCK8A6oxzCal33HGHevfurbZt25ovAwBVytvbWy1bttTu3bvNlss4cUR46NChiouLM9suLT8/X0lJSerQoYNsNr51BdwZ/wIAcDmEVAB1iZ+fnwIDA3Xo0CGzVevi4uIUFhamkJCQOhdaTygqKtKePXvUunVrwivg5vgXAECtIaQCOB/4+fnJ09NTx48fN1suoa6G1hOKiop08OBBNW3aVHa73WwDcCOEVwDVjpAK4Hzm5+en4uJi5eTkmC1UkdTUVNWvX5/wCrg5wiuAKkNIBeCOvL29VVRUpIKCArOFKpKVlSVfX1/CK+DmPCRZ5iIAnIvZs2erZcuWsixL/v7+Gjx4sDnich599FGlpKSYy8B5qVevXlq/fr25jCrSunVr3XTTTbr66qur9d8Vp9OpcePGad68ecrMzDTbFRIaGqrY2NgSa2FhYS531HjYsGF69tlnNXDgQKWnp5ttAG6C8Aqg0hISEpSfn6+uXbuaLZe1YsUKZWdnm8vAealHjx7atGmTuYwqEhgYqC5duujCCy8kvFaToUOH6rnnntPAgQNd9r3FAKof4RVApTkcDnl7e6t+/fpq1aqVunbtqt69e6tnz55q1aqVOnToYD6l1nXs2NGlb2sBVCWbzabi4mJzGVWkR48emjp1qsaNG1etVxx25/B63XXXafLkyRo0aJAyMjLMNgA3QXgFUG1cOdR27dpV27ZtM5cB4Jz17NlTX3zxhfr376/9+/eb7SrjzuF11KhRuvfeezVkyBBlZWWZbQBuggs2Aag2hYWFysrK0v79+/XLL7/o/fff14MPPqhBgwbpwgsvVKtWrXTJJZdo7NixmjVrln766Sft2rXLfBkAcGk5OTmy2Wzy8fExW6gi9erVU3p6uoqKiswWADdCeAVQ4wi1AM4nWVlZKi4uVkBAgNlCFbDZbGratKlSUlIIr4CbI7wCcBmEWgB1UU5OjjIzM9W4cWOzhSpgt9vVqlUr7d+/n/duA26O8ArA5RFqAbiy3NxcHTp0SG3atDFbqAKenp5q166dEhMT2XkF3BzhFUCdVZFQm5iYaL4MAFRKfn6+4uPj1aVLF9ntdrONSvLz81PLli35oSQAwiuA88/pQu0FF1ygVq1acaVhAFWmsLBQGzduVI8ePeTl5WW2UUmNGzeWv7+/9u3bZ7YAuBnCKwC3cWqoBYCqtHnzZnXo0EGBgYFmC5UUEhKi1NRUHTlyxGwBcDOEVwAAgEpKTEyUp6cn73utYna7Xf369dOGDRu4vysAwisAAEBlHT16VPHx8erbt6/ZQiX4+voqLCxMq1atUn5+vtkG4GYIrwAAAJWUm5urlStX6sorr5Svr6/ZRgW1aNFC7du319q1a80WADdEeAUAAKik4uJi/fjjj7rwwgvVtGlTs40KuuSSS7R//37t2bPHbAFwQ4RXAACAKrBjxw6lpqbq73//u9lCBfj6+mrEiBGKjo5WZmam2QbghgivAAAAVSA9PV3Lli3TLbfcwtHhKtCmTRv16tVLy5cvV1FRkdkG4IYIrwAAAFWgqKhIX375pXr37q2OHTuabZwDu92uoUOHKj4+Xjt27DDbANwU4RUAAKCKxMfH648//tBNN90kh8Nhtl1OXFycPDw8SlRcXJw5VuMaNGig22+/XR999JEyMjLMNgA3RXgFAACoIllZWXr33Xc1atQoNW/e3GzjLF122WXy8fHRihUrzBYAN0Z4BQAAqEKrV6/W0aNHNWLECNntdrNditPpPKvy8/OTzWaTn59fqV55VRfVr19f9957r+bPn69Dhw6ZbQBuzEOSZS4CAACg4kaPHq0nnnhCQ4YM0b59+8z2SU6nUw8//LAyMzNVXFxstkvw8PBQQECAMjIyZFmn//btxOz06dPr3JV6b7jhBr344ou65pprtHv3brMNwI0RXgEAAKpYw4YNtXjxYi1fvlyvvPKKCgsLzRHpr/A6fvx4LViwQNnZ2Wa7wvz8/HTHHXcoKiqqToXXxo0ba8mSJfriiy80c+bMcj9vANwTx4YBAACqWGpqqqZNm6bx48erc+fOZrsEy7KUnZ2tzMzMKqvs7Owz7uS6GrvdfvI2Q5988gnBFUAphFcAAIBq8MMPPyg2NlaTJk2Sv7+/2YYhJCREDz30kF566SUlJyebbQAgvAIAAFSHrKwsvfzyywoNDdWwYcNks/FtV3mcTqcef/xxrV27VsuXLzfbACARXgEAAKrPtm3b9PLLL2vKlCnq1KmT2cZfx4VvuukmXXLJJZo6dSr3dQVQLsIrAABANSkqKtLChQv122+/6bnnnlODBg3MEbd30UUX6amnntKUKVO0fft2sw0AJxFeAQAAqlF6erqmTJmiDh066P7775ePj4854rZatWql6dOna+nSpVq6dKmKiorMEQA4ifAKAABQzXbt2qWHHnpIY8eO1c033yyHw2GOuJ0GDRro+eefV1ZWlv7zn/9U6a2CAJyfCK8AAAA1IC4uTpMnT9Zzzz2nQYMGyW63myNuw+l0atKkSbrgggv00EMP6dChQ+YIAJTi4XQ6LXMRAAAAVc/Ly0tjxozR3XffrYceekgbN27UbbfdprfffluZmZnmeIU5nU6NHz9eCxYscLkdTV9fX40fP1633HKLHnzwQa1fv94cAYAyeURGRhJeAQAAaojNZlNAQICcTqdSU1Pl6emp6dOnV3l4ffjhh5WZmani4mKzXWtO/b0fPXpUeXl5siy+FQVwdth5BQAAqGF+fn4aP368brjhBi1evFizZ8/W8ePHzbEKc8Wd14CAAE2YMEEjRozQpEmT9PPPP7tUsAbg+jwkEV4BAABqmJ+fn8LDw9WqVStt3LhRn332mXJzc82xCnE6nRo3bpzmzZtXpTu6FdW0aVNNmTJFYWFhmjBhgtasWUNwBXDOuGATAABALcjOztb8+fN17Ngx/etf/9K//vUvNWzY0Byr02w2m7p166b33ntPXbp00W233aa4uDiCK4AKIbwCAADUkvz8fGVnZ+uBBx7Q8OHD9fbbb6tr167nxZWIfXx8NHz4cC1atEjJycm68847tWnTJnMMAM4a4RUAAKAWWZalX375RbfccosyMjK0ePFijRw5Uk6n0xytM1q1aqV///vfmjFjht5880099NBD2rdvnzkGAOeE8AoAAOACEhMT9cADD2jatGl69tln9dZbb+mCCy6Qp6enOeqynE6nRowYoSVLlqhXr14aNWqU5s6dq4yMDHMUAM4Z4RUAAMBFZGRk6IMPPtD111+vwsJCLV26VP/617/Upk0blz5K7OPjo379+mnevHmaNm2aPvzwQ40ePVq//PKLCgsLzXEAqBDCKwAAgAspKirS1q1bdd999+nee+/VFVdcoeXLl2vixIlq27atHA6H+ZRa4+fnp4svvlivv/66PvvsMx05ckTDhw/X7NmzdeTIEXMcACqF8AoAAOCCsrOztXz5ct1888165plndN111+nbb7/VlClTdNFFF8nf3998So2w2+1q1KiRhgwZovfee0+LFi2SzWbTLbfcokceeUTbtm1jtxVAteA+rwAAALXE6XRq/PjxWrBggbKzs812CYGBgbr44os1atQoXXTRRdq6dau++uor/fLLLzp8+LBycnJOzvr5+en222/X22+/XSX3eXU4HHI6nQoODtY111yjESNGyOl0asmSJfrkk0+0ffv2KrtHLQCUh/AKAABQS5xOpx5++GFlZmae8d6nHh4eCggIUFZWlux2u3x9feXn5ye73a78/Hzl5uYqPz9fhYWFsixL/v7+mj59eoXCq5eXl3x9fdW4cWN17dpVAwYM0OWXX66goCCtX79eixYt0qpVq3To0CEVFBSYTweAakF4BQAAqEVne0scPz8/3XHHHfroo4+UnZ0tm80mp9Opdu3aqV+/frr00kvVqVMnSdK+ffu0fft27dixQ3v27NHhw4eVnp6u3NxcFRQUnAzKdrtdXl5e8vPzU4MGDdSsWTN17NhR3bp1U5cuXdSkSROlpaVp7dq1WrFihX777TclJyeX2OUFgJpCeAUAAKgDnE6nxo0bp3nz5pW5m+rr66sGDRqoTZs26tq1q3r06KFOnTqpRYsWCgwMlKenpyzLUnFxsSzr/337Z7PZZLPZZFmWcnNzlZqaqj179mjr1q3atGmTduzYoeTkZGVkZLDDCqDWEV4BAADqgDOFV5PD4ZDD4ZC3t7d8fX3l6+srHx8feXt7y263y7IsFRYWKi8vTzk5OcrOzi5x9PhMx5gBoKYRXgEAAOqAcw2vAHC+4VY5AAAAAACXR3gFAAAAALg8wisAAAAAwOURXgEAAAAALo/wCgAAAABweYRXAAAAAIDLI7wCAAAAAFwe4RUAAAAA4PIIrwAAAAAAl0d4BQAAAAC4PMIrAAAAAMDlEV4BAAAAAC6P8AoAAAAAcHmEVwAAAACAyyO8AgAAAABcHuEVAAAAAODyCK8AAAAAAJdHeAUAAAAAuDzCKwAAAADA5RFeAQAAAAAuj/AKAAAAAHB5hFcAAAAAgMsjvAIAAAAAXB7hFQAAAADg8givAAAAAACXR3gFAAAAALg8wisAAAAAwOURXgEAAAAALo/wCgAAAABweYRXAAAAAIDLI7wCAAAAAFwe4RUAAAAA4PIIrwAAAAAAl0d4BQAAAAC4PMIrAAAAAMDlEV4BAAAAAC6P8AoAAAAAcHmEVwAAgPOUw+GQj4+PAgIC1KhRIzVr1kytWrVS27Zt1aZNG7Vs2VJNmjRRgwYN5O/vLy8vL9ntdvNlAMAleEiyzEUAAAC4FqfTqXHjxmnevHnKzMw023I4HPLz81NQUJDatWunzp07q3PnzmrXrp2aNGmiwMBAeXt7y2azycPDQ5JkWZYKCwuVk5OjY8eOKTk5WTt37tS2bdsUHx+vffv2KS0tTbm5uSouLjZ/SQCoUYRXAACAOqCs8Orj46OmTZuqV69euvzyy3XJJZeoWbNmysrKUmJionbs2KFdu3YpOTlZqampyszMVF5enoqKiuTh4SGHwyFfX18FBgYqKChIrVu3VnBwsEJCQtSyZUtZlqX4+Hj99NNPWrVqlbZv3660tDQVFhaaHx4AVDvCKwAAQB1wIry+//77cjqdCgsL00033aQ+ffooPT1dsbGxWrVqlTZv3qyDBw8qKytLBQUF5xw0PT095e3trXr16qlNmzbq3bu3rrjiCvXs2VM5OTn69ttvtXTpUm3cuFFpaWnm0wGg2hBeAQAA6oDGjRvrnnvuUaNGjXTdddcpKytLX375pZYvX64dO3YoIyNDBQUF5tOqhI+Pjxo3bqzevXtrxIgRGjBggA4ePKgPP/xQ0dHROnDgwDmHZAA4V4RXAAAAF+br66vevXsrPDxcKSkpatKkiRYsWKDffvtNaWlpKioqMp9Srby9vdWiRQsNHjxYY8aMUaNGjfTRRx/p448/1p49ewixAKoN4RUAAMAFeXp6qkePHpo4caIuu+wyLV26VMnJyXr33Xd15MgRc7xWNGjQQP3799d9992ndu3a6e2339aCBQt04MABcxQAKo1b5QAAALiYFi1a6Mknn9TixYtVWFioESNG6N///rfy8/OVm5trjteaY8eOadmyZRo5cqQmTZqkESNG6Msvv9SNN94of39/cxwAKsUuaYq5CAAAgJrn7e2twYMHa+7cuWrRooUeeeQRRUVFad++fbLb7erdu7fWrVun/Px886m1Ki8vT9u3b9eXX36pwsJCTZ48WT169NCWLVuUlpYmy+KgH4DKY+cVAADABQQFBWny5Ml66623tGjRIo0cOVIrV65UTk6OOeqyUlJSNGfOHI0YMUK+vr764osvdN1118nHx8ccBYBzxs4rAABALevWrZveeustde3aVffee68+//xzZWRklJjx8vJy2Z3XUxUXFyslJUXffvut8vLy9O9//1tOp1N//vmnSx15BlD3sPMKAABQSxwOhwYOHKjPPvtM+/fv16233qrVq1dX2y1valJ6erqioqL0j3/8Q8OHD9fs2bPVpk0bcwwAzhrhFQAAoBZ4eXnphhtu0Lx58/TRRx/pkUce0b59+8yxOq2wsFCrVq3SqFGj5O/vr/fff19dunQxxwDgrBBeAQAAapi3t7duv/12TZs2Tc8++6xmzpyp9PR0c+y8kZCQoPDwcO3atUvz589Xz549zREAOCPCKwAAQA3y8vLS7bffrqefflqPPvqoPv74Y7d4L+ihQ4c0adIkrVmzRu+++64uvPBCcwQATovwCgAAUEMcDoduvPHGk8F1yZIl58X7W89Wamqqnn76acXFxentt99W586dzREAKBfhFQAAoAbYbDYNHDhQL774op566iktW7ZMhYWF5th5Ly0tTc8884y2bNmiN954Qy1btjRHAKBMhFcAAIAa0KNHD82YMUOzZs3SwoUL3WrH1ZSamqonnnhCBQUFmjp1qurVq2eOAEAphFcAAIBq1qxZM02fPl0rV67U22+/rby8PHPE7Rw4cEAPPfSQevXqpQkTJsjLy8scAYASCK8AAADVyNfXV4899phsNpumTp2qjIwMc8Rtbd++XQ8//LD++c9/6oorrjDbAFAC4RUAAKAaDRkyRCNGjNCkSZN04MABs+32Vq1apTfeeEMvvvii2rZta7YB4CTCKwAAQDVp3769pkyZoldeeUV//PGH2Yak/Px8vfvuu0pOTtbDDz8sX19fcwQAJMIrAABA9fDx8dGDDz6o3bt365NPPnHLKwufrdTUVE2ZMkXXXXed+vfvb7YBQCK8AgAAVI+LL75YN9xwg6ZOnaq0tDSzDcOGDRv0zjvv6IknnlCjRo3MNgAQXgEAAKpaQECAHn30US1cuFDr16832yhDQUGB3nvvPdWvX1/XX3+9bDa+TQVQEv8qAAAAVLEBAwaoW7duioqKUn5+vtlGOQ4cOKAZM2bogQceUNOmTc02ADdHeAUAAKhCgYGBuv/++zV//nzt3r3bbOM0iouL9fXXXys/P1/XXXcdu68ASuBfBAAAgCp08cUXKyQkhIs0VVBKSormzJmjcePGqWHDhmYbgBsjvAIAAFQRHx8f3XXXXVq6dKmSkpLMNs7S8uXL5evry5WHAZRAeAUAAKgi7du316WXXqpPP/1UBQUFZrtWhIaGasaMGYqPj5dlWaUqPj5e4eHh5tNqVUpKihYtWqR//OMf8vPzM9sA3BThFQAAoArYbDZdc8012rFjh7Zu3Wq2a1xoaKji4+MVGxuriRMnKjg42ByRJAUHB2vu3LmyLEszZsww27WisLBQS5YsUa9evdS+fXuzDcBNEV4BAACqgNPp1A033KBFixYpMzPTbNeo8PBwxcbGlhtYyzNx4kTFx8eby7UiISFB27Zt0+DBg7lwEwCJ8AoAAFA1OnTooNatW+unn34yWzUqPDxcc+fONZfPWnBwsEsE2KysLC1dulTDhw/n6DAAifAKAABQNfr376/t27dr//79ZqtGlRdcZ86cqbCwMHl4eJyssLAwxcTEmKMKDg52iSPEq1atUseOHdWqVSuzBcANEV4BAAAqydfXV4MGDdKKFSuUk5NjtmtMWYEzJiZGHh4eioyMVFxcXIleXFychg4dqrCwsBLr+usIcWhoqLlco/bs2aMDBw6oV69eZguAGyK8AgAAVFL9+vXVrVs3/fzzzyouLjbbNWbixIklHickJGjo0KEl1soSFxeniIgIc1kjR440l2pUdna2YmNjNWDAAHl6epptAG6G8AoAAFBJbdu2lYeHhxITE81WjSlrl3TMmDHmUrmioqJKHSHu1KlTicc1rbCwUGvWrFHv3r153ysAwisA1DUOh0NOp9NcBlCLunfvrqSkJKWlpZmtGtOjRw9zqdQx4TNZsmRJicchISElHteG7du3q0mTJmrYsKHZAuBmCK8A4KJOhNTWrVsrNDRU48aN05tvvqn33ntPBw4cUN++fc2nAKgFDodDF1xwgTZt2qT8/HyzXWOioqIUFhammTNnKiEhQQkJCebIOTvXW+1Uh0OHDikvL4+LNgEgvAJAbSsvpP7www/6888/tWfPHsXGxurtt9/WP//5T91xxx3svAIuxNPTU506ddLWrVtVWFhotmtUXFycIiMjFRISUiW7plURgCsrKytLycnJat++vdkC4GYIrwBQQ841pIaFhfHNGlAHeHt7q0WLFkpKSjJbdU63bt1KPHaF+73m5+crKSlJ7du3l83Gt66AO+NfAACoYoRUwL34+fkpICBAhw8fNlt1jnm14h07dpR4XBuKioq0Z88etW7dWna73WwDcCOEVwCoIEIqAP0VXu12uzIyMsxWnVLWPWIXLlxoLtW44uJiHTp0SE2aNCG8Am6O8AoAZ0BIBXA6fn5+Ki4uVk5OjtmqM0JDQ0vtusbExJzz1YqrS1pamgIDAwmvgJsjvALAXwipACrC29tbRUVFKigoMFt1RmxsrLmk559/3lyqNVlZWfL19eU9r4Cb85BkmYsA4G5++OEHFRUVyeFwaMCAAWbbJc2bN08pKSnmMlDK3/72N/3222/mMqpIkyZNNGDAAIWFhVXr30mn06lx48Zp3rx5yszMNNsVFh8fX+qWOBEREYqKiiqxVpuGDh2q5557TldccYXS09PNNgA3wY+vAEBSYWGhmjRpUqd2Um02m+x2O0VRLlAeHh7mX9E6oazgGhMT41LBFQBOYOcVAP7icDjk6+ur+vXrq02bNurWrZv69OmjCy64QM2bN3e5YNuvXz/9+uuv5jKAGnbxxRfr448/1qWXXqpDhw6Z7SpT1Tuv5QXXoUOHllhzBddff72eeOIJXXnllXX+wlgAKo6dVwD4S2FhoTIyMrR3796T722dMGGCLrvsMvXs2VNt2rTRpZdeqvDwcM2dO1dxcXFKTEw0XwaAm8nLy5Pdbpenp6fZckmhoaGyLKvOBFdJ8vf3V05OjoqLi80WADdCeAWAMyDUAjid7Oxs2Ww2+fr6mi2XExoaWubFmVw5uEpS/fr1lZ6erqKiIrMFwI0QXgGgggi1APRXeC0qKlJAQIDZcikzZsyok8HVZrOpadOmOnz4MOEVcHOEVwCoYoRawL1kZ2crIyNDTZo0MVsuIzo6utR9XCVp5syZLh1cJclut6t169bau3cv4RVwc4RXAKghhFrg/JSXl6fk5GS1bdvWbLmE+Ph4DRkyxFxWRESEIiMjzWWX4+XlpXbt2ikxMZH3vAJujvAKALXsXEPtggULquRKowCqRkFBgXbs2KGuXbvK4XCY7VpV1hWFJSksLKzO3A7H399fLVq04Id5AAivAOCqygu1d911l1q0aMFtcgAXUVhYqI0bN6pHjx7y8vIy27WmrOCakJAgDw8PxcXFlVh3ZU2aNJG3t7f27dtntgC4GcIrANQxJ0ItANexZcsWtW3bVvXr1zdbtSI6OrrM4BoSElJirS7o3LmzUlJSlJqaarYAuBnCKwAAQCUlJSXJsiy1b9/ebNW4GTNmlHqPa0xMTJ0Mrg6HQ3//+9/1+++/Kzs722wDcDOEVwAAgEo6duyYtmzZoksuuUQ2W+19exUaGlrqqsKufiuc0/Hz81NoaKhWrVqlgoICsw3AzdTev64AAADniZycHH333Xe68sor5evra7ZrzAcffFDicUJCQp0NrpLUpk0btWjRQuvWrTNbANwQ4RUAAKAKrFq1Sl26dFHLli3NVo0IDQ0t9T7X4OBgWZZVqapNl156qXbu3MnFmgBIhFcAAICqsWvXLu3bt0/9+/c3WzVi8uTJ5lKd5u/vrxEjRujLL7/k/a4AJMIrAABA1cjMzNQXX3yhW265RU6n02xXu7p4QabTCQ4OVpcuXbRixQoVFxebbQBuiPAKAABQBYqLixUTE6POnTurS5cuZrvamUeG6zKHw6Hrr79e69ev165du8w2ADdFeAUAAKgiiYmJio2N1ejRo+Xp6Wm2q5WHh0e1VG0ICgrSyJEjNX/+fI4MAziJ8AoAAFBFcnNz9d577+n6669X27ZtzTbO0jXXXKOcnBytXr3abAFwY4RXAACAKrR27VolJCRo1KhRcjgcZhtnEBQUpIiICM2bN09Hjx412wDcGOEVAACgCqWnp2vWrFkaM2aM2rVrZ7ZxGjabTcOGDZOPj4+WLVvGhZoAlEB4BQAAqGKrVq3S1q1bNX78eHl5eZltlKN58+aaOHGiZs2apUOHDpltAG6O8AoAAFDF0tPTNW3aNN1666266KKLzDbK4Onpqbvuukvp6elasmQJu64ASiG8AgAAVIO1a9dqyZIlmjx5surXr2+2Ybjwwgs1btw4TZ06lfe6AigT4RUAAKAa5ObmaubMmWrXrh0XbzqDBg0aaMqUKfryyy+1atUqsw0AEuEVAACg+iQlJWnKlCl67LHHOD5cDk9PT919991q2bKlXn31VeXk5JgjACARXgEAAKpPcXGxYmJitHTpUr388stq3ry5OeL2BgwYoAceeEBPPPGEkpKSzDYAnER4BQAAqEY5OTmaNm2aJOmJJ56Q0+k0R9xW586d9eqrr2rOnDn6/vvvzTYAlEB4BQAAqGYHDhzQww8/rCuvvFLjx4+Xt7e3OeJ2mjVrpunTp2vDhg2aM2eO8vLyzBEAKIHwCgAAUAM2btyoiRMn6sEHH9TNN98sT09Pc8RtNGzYUC+88IK8vb315JNPKi0tzRwBgFIIrwAAADWguLhYK1eu1BNPPKGpU6dq+PDhbnkF4vr16+uZZ55Rjx49dN9992nfvn3mCACUyS5pirkIAACAqldcXKwdO3YoLS1NU6dO1Z49e5SQkKDi4mJztBQvLy/17t1b69atU35+vtmuE07cEmfAgAG65557tHnzZnMEAMpFeAUAAKhBRUVF2rJli44dO6YXXnhBR44c0fbt21VYWGiOllDXw2vTpk314osvqm/fvrrnnnu0YcMGcwQATovwCgAAUMOKioq0efNm7d27V1OnTpXdbtfGjRtPe9GiuhxeO3bsqFmzZqlFixYaN26cNm3aZI4AwBnxnlcAAIBakJ+fr8WLF2vcuHH6xz/+oVdeeUWtWrUyx+o0h8OhSy+9VJ9++qlycnI0ZswYbd261RwDgLNCeAUAAKglhYWF+u6773TrrbeqdevW+vTTTxUWFnZeXIk4MDBQ48aN04cffqivv/5a9913n/bs2WOOAcBZ49gwAABALUtJSdG3336rZs2aacqUKbLZbNqxY4eys7NPztSVY8N2u11du3bVtGnTdN111+lf//qX3n//fWVkZJijAHBO2HkFAABwASkpKXr++ed177336tZbb9XChQt1xRVXyNfX1xx1WY0bN9aECRO0dOlS5eXl6YYbbtDSpUuVm5trjgLAOWPnFQAAwEUUFhYqISFB0dHRCgoK0tNPP61OnTopKSlJmZmZuuiii1xy5zUwMFBXX321Zs6cqX79+umZZ57RrFmzdODAAVmWZY4DQIV4SOJfFAAAABfj5eWlHj16aOLEiRowYICWLFmiAwcO6N1339WRI0fM8VrRoEEDhYWF6b777lPHjh319ttva8GCBUpOTjZHAaDSCK8AAAAuzM/PT71791Z4eLgOHz6soKAgLViwQL///rvS0tJUVFRkPqVaeXl5qUWLFho8eLDGjBmjxo0ba8GCBfr444+VlJR0xvvVAkBFEV4BAADqgMaNG+uee+5R48aNdd111ykjI0PLli3TN998o/j4eGVkZKigoMB8WpXw8fFR48aN1atXL40YMUKXXXaZDh06pI8++khff/21kpOTCa0Aqh3hFQDqiDlz5mj27Nnas2ePMjMza3y3BUDtcjqdGjdunN5//305nU5deumluummm9SnTx+lpaUpNjZWP/30k7Zs2aKDBw8qKytLBQUF5/xvhaenp7y8vFSvXj21adNGvXv31hVXXKGLLrpIOTk5WrFihZYsWaI///xT6enpKi4uNl8CAKoF4RUA6oiUlBQ1btxYq1evVnp6ur755hutWrVKiYmJyszMZNcDOM+dCK/z5s1TZmam9NeOaLNmzdSrVy9dfvnluuSSS9S0aVNlZmYqMTFRO3bs0K5du5ScnKzU1FRlZmYqLy9PRUVF8vDwkMPhkK+vrwIDA9W4cWO1bt1awcHB6tSpk1q1aiVJSkhI0E8//aSffvpJ27dvV1paWrXt8ALA6RBeAaCOaNCggR5++GFNnjy5xHpSUpLi4+P17bff6scff1RCQoLS09MJs8B5pqzweiqHwyF/f38FBQWpXbt26ty5szp37qx27dqpadOmCggIkJeXl+x2+8nnWJalwsJC5ebm6tixYzpw4IB27typbdu2aceOHdq3b5+OHTum3NxcdlgB1DrCKwDUMT179tQbb7yhSy+91GxJf4XZpKQkffvtt/rhhx+0Y8cOdkqA88CZwmtZHA6HHA7HyaPAXl5ecjgcstlskqSioiIVFBQoPz9f+fn5J48Zn+tRYwCoCYRXAKiD/P39NWbMGE2aNElt27Y12yUkJSUpOTlZK1as0MqVK7V161YdO3bM5e4TCeD0KhJeAeB8QngFgDosODhY06dP1/Dhw81WuZKSknT48GF9//33WrFihTZt2qTU1FTl5eWZowBcCOEVgLsjvAJAHeft7a0RI0boxRdfVPv27c32Wfnjjz/0448/6ttvv9Wff/6pI0eOKDc31xwDUIsIrwDcHeEVAM4TLVq00NSpU3XXXXeZrXO2adMmrVq1St9++63Wr1+vw4cPKycnxxwDUIMIrwDcHeEVAM4jnp6eGjhwoGbMmKEuXbqY7QrbunWrfv75Z33zzTf6/fffdeDAAWVnZ5tjAKoR4RWAuyO8AsB5qFGjRvq///s/Pfroo2arSuzYsUO//vqrvvnmG/3666/av3+/cnJyuJUGUI0IrwDcHeEVAM5TdrtdF198sd544w316dPHbFephIQErV+/XsuXL9eaNWu0d+9eZWdnc7sNoAoRXgG4O8IrAJznAgICdO+99+qf//znGW+rU1W2bNmi7t27m8sAKoHwCsDd/b87VAMAzlsZGRl6+eWXNWzYMK1cudJsV4tu3bpp8ODB5jIAAECFEV4BwE1s3rxZ1157rcaNG6ekpCSzXaU2b96suLg4cxkAAKDCCK8A4EZycnL0zjvv6PLLL9d///tfs11l3njjDWVlZZnLAAAAFUZ4BQA3tHv3bt1+++268cYbtXPnTrNdKUlJSfriiy/MZQAAgEohvAKAm8rPz9cXX3yhSy+9VHPnzjXbFbZ06VIdOnTIXAbgAux2uxwOx8my2+2y2+3mGAC4JK42DACQw+FQ//79NWvWrEpfJbhbt27aunWruQygks72asOenp7y9fVVvXr1FBQUpObNm6tZs2YKCgpS/fr15e/vL4fDIcuylJ+fr4yMDKWmpurQoUM6ePCgDh48qKNHjyojI0N5eXnc8gqAyyC8AgBOatCggR555BE9+eSTZuusHD16VE8++aQWL16slJQUsw2gEsoLr56engoMDFS7du3Up08f9evXTz169FBQUJAsy9Lx48eVkpKilJQUpaWlKTs7WwUFBfLw8JC3t7ecTqcaNmyooKAgNW7cWP7+/srPz9fevXu1bt06rVmzRps2bVJycrKys7NVXFxc4uMCgJpCeAUAlGCz2dSrVy+98cYbuuSSS8z2aU2aNEnDhg1T27ZttXjxYkVFRWnnzp0qLCw0RwGco1PDa25urho1aqRevXpp2LBhGjBggAICArRz5079+uuvWrdunXbu3KmUlBRlZmYqPz9fRUVFKi4ulmWV/NbPw8Pj5HFiHx8fBQYGqkWLFurSpYv69u2rPn36qHHjxkpMTNTy5cv1v//9T/Hx8crIyCjxOgBQ3QivAIAynfhGOTIyUm3btjXbpWzevFn9+vVTQUGBunXrpvvuu0+DBw/Wpk2bNH36dK1Zs0bZ2dnm0wCcJafTqfDwcK1Zs0bDhw/X8OHDZbPZ9P3332v58uXauHGjUlJSlJubW2VHfT09PeXv76/WrVvrkksu0bXXXqsLL7xQiYmJ+uSTT/Ttt98qOTlZBQUF5lMBoMoRXgEAp9W5c2fNmDFD11xzjdkq4Z///KfmzJlz8rHNZlPz5s01atQohYeHKy8vT7NmzdKSJUs4Ugyco8DAQA0YMEB///vfdeONN+qPP/7Qxx9/rLVr1+ro0aM1Fh59fX3VunVrDR48WLfddpuCgoK0ePFiffjhh4qPj1d+fr75FACoUhZFURRFna58fHysO++800pMTLTKsnv3bqtJkyalnneiAgMDreHDh1s//PCDlZiYaL366qtW586dLYfDUWqWoqj/v/z9/a2rrrrKio6OtjZu3Gg9++yz1t/+9jfL19e31GxNls1msxo0aGBdddVV1n//+18rMTHRmj59utWlSxf+XlMUVZ1VaoGiKIqiyqzWrVtbCxYsMLOrNXPmzFKzZZWXl5d10UUXWW+//ba1e/du66uvvrIGDhxo+fn5lZqlKHcuT09Pq1evXtaCBQusnTt3Ws8++6zVvXt366GHHrKcTmep+dosf39/q3///taiRYushIQE61//+pfVrFmzUnMURVFVUKUWKIqiKKrc8vT0tIYNG2Zt3779ZHjt2rVrqbnTlc1ms1q2bGk98sgj1vbt260///zTGj9+vBUUFFRqlqLcrYKCgqxJkyZZu3btsubOnWt169bN8vT0tJxOpxUZGely4fVEOZ1Oa+jQodbq1autNWvWWEOGDLF8fHxKzVEURVWiSi1QFEVR1BkrKCjImjlzppWSkmJ5enqW6p9tBQQEcKSYoiTL4XBYffv2tVasWGH98ssv1jXXXFPieLCrh9cT1aRJE+uxxx6zEhMTrf/85z9W8+bNS81QFEVVsEotUBRFUdRZld1uL7VW0eJIMeXO5e/vb919993Wrl27rFdeecVq2bJlqZm6El711wmNfv36WStXrrR+/PFH6+KLL67Sfy8oinLbKrVAURRFUbVWHCmm3K2CgoKsV1991dqxY4d1yy23lHsxproUXk9U06ZNrWnTplkJCQnWLbfcYnl7e5eaoSiKOtuyS5pS8uLDAADUHsuylJGRoZ9//lkffPCBdu3apYiICE2aNEmtW7dWUlKSjh8/ruLiYvOpQJ3Ttm1bvf766+ratavGjRun77//vtzbzXh5eal3795at25duTOuJisrS7GxsUpNTdXzzz+v4uJibdy4scZu7QPg/GIzFwAAcBUZGRn68ssvddVVV+n6669XYGCgvvnmGy1ZskQDBw6Un5+f+RSgzujUqZPee+892Ww23X777fr9999VVFRkjtV52dnZ+vDDDxUREaEJEybo//7v/xQYGGiOAcAZsfMKAHB5RUVFOnTokL7++mstXLhQ/v7+euaZZzR27FgVFhZq7969ys7ONp8GuKwuXbro3XffVWJioiIjI7V//35zpJS6uPN6QnFxsRITE7V27Vo99thjatmypX755Rfl5eWZowBwWqXOElMURVGUq9epVynevXs3Vymm6kwFBwdbq1evtubNm2c1bty4VL+8qovveS2r+vTpY/3555/WCy+8UOd/LxRF1WxxbBgAUCdxpBh1UcuWLfXGG29o9+7devzxx3XkyBFz5Lz3+++/a9y4cbrhhht07733ysfHxxwBgDJxbBgAUKedeqT4s88+40gxXFb9+vX1yiuvyM/PTw888IAOHTpkjpxWXT42bDpw4IC2bNmif//73zp06JC2bNnCRdgAnJVS27EURVEUVZeLI8WUq5W3t7f11FNPWevWrbM6depUqn82db4cGz5RDofDGj16tLVr1y6rf//+pfoURVFmcWwYAHDe4UgxXInNZtOQIUN09913KzIyUjt27DBH3FJhYaG++OILzZ8/X6+++qratm1rjgBACYRXAMB5Kz8/Xxs2bFBERIRCQ0O1cuVKvfXWW1qzZo3Gjx+voKAg8ylAlQsODtbUqVP1n//8Rz///LPZdmu5ubmaNWuWDh48qCeeeEL+/v7mCACUUGo7lqIoiqLO1zpxpPj777+3du/ebU2fPt3q0qWL5enpWWqWoipbTqfT+vDDD60FCxZYgYGBpfrnUufbseFT64ILLrDi4+OtUaNGWTabrVSfoihKHBsGALibE0eKr776al1//fUKCAjQ8uXL9cUXX3CkGFXKZrPp2muvVd++ffX8888rPT3dHMFftmzZopdeekmTJ0/m+DCAchFeAQBuqawjxW+++SZHilFlWrZsqccff1yvvPIK73M9g6KiIn3++efatWuX7r//fnl7e5sjAEB4BQC4t+LiYiUnJ2v69Om6+OKL9eSTT+q2227T2rVrNX36dHXp0kWenp7m04DT8vT01NixY5WSkqLPP/9cRUVF5ggMaWlpevHFF3XTTTepV69eZhsACK8AAJxgHil2Op1avnw5VynGOevYsaPGjBmj//znP0pNTTXbKMe6deu0bNkyRUZGcvEmAKUQXgEAMJw4UjxhwgSFhobqu+++O3mkODw8nCPFOC1PT0/dfffd+uOPPxQXF2e2cRp5eXmaO3eu+vXrpz59+phtAG6O8AoAQDnKOlI8evRojhTjtNq1a6ebbrpJs2fPVmZmptnGGcTHx2vJkiWaMGGCfH19zTYAN0Z4BQDgLJzuSPGgQYM44ghJkt1u180336wdO3Zo7dq1ZhtnIT8/Xx988IFCQ0PVpUsXsw3AjRFeAQA4B2UdKZ49e7Z+/vlnhYeHq0mTJuZT4EYaNWqkUaNG6d1331VGRobZrjXh4eGKj4+XZVklKj4+XjNmzDDHa9327dv1888/69Zbb5XD4TDbANxYqZu/UhRFURR19hUQEGBde+211vfff2/t3r3bmj59utWlSxfL09Oz1Cx1ftd1111nbdq0yWrWrFmpXmXL6XRakZGRltPpLNUrr8LDw62zFR0dXer5tVnDhg2ztmzZYjVv3rxUj6Io9yx2XgEAqKSMjAx99dVXHCl2c97e3rrlllv01Vdf6ciRI2a7xkVHR2vu3LnmcrmGDBmi+Ph4hYaGmq1asXbtWhUWFqpv375mC4CbIrwCAFBFOFLs3po2baq///3v+vLLL1VYWGi2a1R0dLSGDBliLp9RcHCwYmNjzeVakZqaquXLl2vEiBHy8vIy2wDcEOEVAIAqZl6l+IknntDo0aP166+/cpXi81ifPn2UkZGhbdu2ma0aFR4eXmZwjYmJUVhYmDw8PE5WRESEEhISzFFFR0ebSzWusLBQMTExCg0NVaNGjcw2ADdEeAUAoBpxpNg9eHp66sorr9RPP/2k48ePm+0a9dhjj5lLioiI0NChQ0vddzYqKkohISGlAuyQIUNc4vjw1q1bVVxcrK5du5otAG6I8AoAQA0wjxSvWLGCI8XnEafTqUsuuUTff/99rR4ZDg8PV3BwcIm1mTNnKioqqsSaKSQkxFzSyJEjzaUad+zYMa1fv15hYWGy2+1mG4CbIbwCAFCDThwpfu211zhSfB5p3ry5GjVqpM2bN5utGjVixAhzSZGRkeZSmWbOnFnicadOnUo8rg15eXlavXq1QkND5e3tbbYBuBnCKwAAtYQjxeePTp066ciRIzp8+LDZqlHmDmpMTEyJx6ezZcuWEo/N16otGzZsUMeOHRUYGGi2ALgZwisAALWsvCPFa9as4UhxHWCz2XTBBRdo69atysnJMds1KiQkRBEREYqJiVFCQoKWLFlijtQ5e/fulcPhULNmzcwWADdDeAUAwEWYR4off/xxjhTXAQ6HQ926ddOmTZuUn59vtmtcVFSUhg4dqpCQkDO+1/VU5pHj+Pj4Eo9rS1pamo4cOaJ27dqZLQBuhvAKAIAL4khx3eHt7a127dpp586dZqvOCA0NLXV7HVfZtc3Ly9OePXvUoUMHswXAzRBeAQBwYRwpdn2+vr5q2LChkpOTzVadEBoaqg8++KDEWkxMzDnt2lanwsJCJSUlqW3btnI4HGYbgBshvAIAUAec7kjxa6+9xpHiWuTn5ycvLy+lpaWZLZcWGhqq6OhoxcbGlri9TkJCgoYOHVpitjYVFRUpOTlZzZo1k83Gt66AO+NfAAAA6hjzSLG/vz9HimuRn5+fJCkrK8tsuZzo6GhZliXLshQbG1vqqHBMTIzLXGX4VEePHlXDhg251yvg5givAADUURwpdg2+vr4qKipyiYs1ncnpgmlMTIxL7bieKiMjQ/7+/oRXwM15SLLMRQAAUDcFBATosssu0yOPPKL27dvriy++0OLFi7V3715zFFWkS5cueuSRR3T77bdX631enU6nxo0bp3nz5ikzM9Nsn5X4+PgSR4TLEhMTo+eff15xcXFmq9Zce+21mjJligYOHKj09HSzDcBNEF4BADgPeXl5qUuXLrrvvvt05513VmuocndeXl6qV6+e2rVrp5SUFLNdZaoivFqWpZiYmJOPQ0JCyg2zYWFhLhNghw4dqueee04DBw7U8ePHzTYAN0F4BQDgPGaz2RQQEGAuowp169ZNTz/9tMaMGVOtPySoivBanhkzZmjixInmsjw8PMylWjF8+HA9/fTTGjRoEDuvgJuzKIqiKIqiqIpVr169rJ07d1otWrQo1avKcjqdVmRkpOV0Okv1qqJCQ0MtU3R0dKm52qhbbrnFio2NrbbfO0VRdaO4YBMAAEAl5Obmym63y8vLy2zVKXFxcZo5c2aJNfNqxLUlICBAmZmZKioqMlsA3AjhFQAAoBKysrJkWZacTqfZqnMiIyPNJYWHh5tLNS4oKEhHjx4lvAJujvAKAABQCdnZ2crNzVXDhg3NVp106gWd9Nd7emuTw+FQy5YtlZycTHgF3BzhFQAAoBJyc3N15MgRtWzZ0myhCjgcDrVt21a7d+8mvAJujvAKAABQCfn5+dq1a5dCQkJks9Xut1ahoaEKDw9XdHS0LMsy23WSj4+P2rRpo8TERLMFwM3U7r+wAAAAdVx+fr42b96sHj16yNPT02zXmNDQUMXGxmru3LknL7RUkfermhdp2rJlS4nHNa1BgwaqX7++kpKSzBYAN0N4BQAAqKSNGzeqc+fO8vf3N1s1Ji4uzlzSY489Zi6dVllhd9OmTeZSjWrXrp1yc3N16NAhswXAzRBeAQAAKikhIUH16tVTs2bNzFaNMi+2FBwcXGYgLc/cuXNLPE5ISCgzFNek3r17a9u2bcrIyDBbANwM4RUAAKCSDh06pAMHDqhnz55mq0YtWbLEXNLcuXPPGGBDQ0PLfI/stGnTzKUa5ePjo/79+ys2Nla5ublmG4CbIbwCAABUUnZ2tlatWqWBAwfKy8vLbNeYqKioUruv+ivARkdHKzQ0tMR6aGiooqOjFRsbW2Jdf+3iRkVFmcs1qnHjxurRo0et7/4CcA2EVwAAgEoqLCzUd999p9DQUDVo0MBs16ihQ4cqISHBXNaQIUMUGxsry7JOVmxsbKkLNOmv48JDhw41l2tcz549lZOTo/j4eLMFwA0RXgEAAKrAn3/+KbvdrgsvvNBs1biQkJAyA+zZSEhIUEhIiLlc47y8vHTttdfqhx9+UFpamtkG4IYIrwAAAFXg6NGjWrlypUaMGFGrR4dPCAkJ0cyZM83l04qIiHCJ4CpJQUFBuuKKK7Rs2TIVFBSYbQBuiPAKAABQBfLz8/X5559r8ODBtX7V4RMiIyPl4eGhiIiIMndiExISFBMTo4iICHl4eNT6e1xP1b9/f2VnZ2v9+vVmC4CbIrwCAABUkfXr1+vo0aMaPHiw2apVUVFRCgkJkYeHR4kKCQnR0KFDXSq0SpLT6dSdd96phQsX6tixY2YbgJsivAIAAFSRtLQ0zZ8/X2PHjq31CzfVZT179lS3bt20ZMkSFRUVmW0AborwCgAAUEWKi4v11VdfqVGjRrrsssvMNs6Cr6+vxo8fr+joaCUmJpptAG6M8AoAAFCFDhw4oA8++ED333+/6tevb7ZxBhdeeKEuv/xyvfPOO8rLyzPbANwY4RUAAKAKFRYW6pNPPlGLFi101VVXmW2chr+/vx588EFFR0dr8+bNZhuAmyO8AgAAVLF9+/Zp9uzZeuyxx9S8eXOzjXL0799fl1xyiWbPns2uK4BSCK8AAABVrKioSAsXLlRubq7Gjh0rT09PcwSGJk2a6Mknn9S8efO0Y8cOsw0AhFcAAIDqkJKSoueee07jx49Xr169zDZO4enpqXvuuUcOh0PvvfeeCgoKzBEAILwCAABUl59++kmLFy/W888/r6CgILONv/Tr108RERF6+umndfDgQbMNABLhFQAAoPrk5ubqtddeU0BAgO677z75+PiYI26vVatWevnllzV//nz99NNPZhsATiK8AgAAVKN9+/Zp0qRJGjNmjIYOHSq73W6OuK2AgABNnjxZ6enpmjVrFhdpAnBahFcAAIBq9vPPP+uFF17Qyy+/rD59+phtt+Tt7a1x48ZpwIABeuyxx5SSkmKOAEAJhFcAAIBqVlhYqAULFujzzz/X7Nmz1alTJ3PErTgcDt1www168MEHFRkZqS1btpgjAFAK4RUAAKAGZGdn6z//+Y82b96sN998U+3atTNH3ILdbtfVV1+tF198UU8//bS+//57FRcXm2MAUArhFQAAoIakpqbq//7v/5SWlqY333xTbdu2NUfOaw6HQ4MHD9brr7+uV155RQsXLuS2OADOGuEVAACgBh08eFATJ05Ubm6u3n77bQUHB5sj5yVPT08NGzZMb775pmbOnKl33nmHCzQBOCeEVwAAgBq2f/9+3XfffTp8+LA+/PBD9erVSzbb+fttma+vr26//XbNnDlTL730kqKiopSbm2uOAcBpnb//SgIAALiwAwcOaOLEiVqzZo0+/vhjXX311fLy8jLH6rwGDRpo0qRJeuqpp/TYY4/p/fffJ7gCqBC7pCnmIgAAAKpfTk6OYmNjVVRUpKlTp0qStm7dWma48/LyUu/evbVu3Trl5+ebbZdjs9kUEhKi1157TZdccokmTJigFStW8B5XABXGzisAAEAtyszM1Jw5cxQREaE777xTb7/9trp37y673W6O1hl+fn66/vrrtXjxYhUUFGjkyJFavXq1CgsLzVEAOGuEVwAAgFqWn5+vb775RjfddJMyMjL0xRdf6J577lGDBg3MUZdmt9sVEhKiV199Va+88orefPNN3Xvvvdq1a5c5CgDnjGPDAAAALuLYsWP67rvvtG/fPj3yyCO65pprlJycrEOHDsnDw8Oljw03adJE//jHPzRz5kxlZWXp/vvvV0xMjHJycsxRAKgQD0mWuQgAAIDaY7PZ1KpVK40fP1533HGHYmNj9fbbb6tPnz6KiopSZmam+ZRaYbPZ1LBhQ1111VV68MEHZbfbNW3aNC1fvlzp6enmOABUCuEVAADARXl6eqpLly6KiIjQwIED9cUXXyguLk5xcXE6fvy4iouLzafUCE9PTzVv3lzXXHON7rnnHvn6+mrOnDlavHixDh48aI4DQJUgvAIAALg4b29vXXDBBRo+fLhuuOEGZWZmauHChfr222+VlJSkrKws8ylVzuFwqF69eurevbtuvPFGDR06VEeOHNG7776r6OhoHTp0SEVFRebTAKDKEF4BAADqAKfTqfHjxysmJkahoaEaNWqUOnXqpO3bt2v58uWKjY1VYmKi0tPTVVBQUOldWbvdLh8fHzVq1EjdunXToEGDNGjQIAUEBOjHH3/UZ599pt9++03Hjh0znwoA1YLwCgAAUAc4nU6NGzdO8+bNU2ZmppxOp9q3b6/LL79cV199tbp27arc3Fxt2bJFv//+uzZv3qy9e/fq6NGjys7OVl5enoqKikqEWg8PD9lsNjkcDvn4+CggIEBNmjRRhw4d1LNnT/Xp00ft2rVTTk6O1qxZo5iYGK1du1YHDx50yYtGATi/EV4BAADqADO8nsrPz0+NGzdWp06d1Lt3b/Xu3VshISEnb7WTnZ2tjIwMZWRkKCcnRwUFBfLw8JCXl5f8/f0VGBiogIAAeXt7Kz8/XwcPHtTmzZv122+/acOGDUpKStLx48cJrABqFeEVAACgDjhdeDV5e3vLx8dHgYGBatCggRo1aqQGDRqoXr168vPzk8PhkGVZys/PV2ZmptLS0pSamqqjR48qLS1NWVlZysvLU0FBgfnSAFBrCK8AAAB1wLmEVwA4H9nMBQAAAAAAXA3hFQAAAADg8givAAAAAACXR3gFAAAAALg8wisAAAAAwOURXgEAAAAALo/wCgAAAABweYRXAAAAAIDLI7wCAAAAAFwe4RUAAAAA4PIIrwAAAAAAl0d4BQAAAAC4PMIrAAAAAMDlEV4BAAAAAC6P8AoAAAAAcHmEVwAAAACAyyO8AgAAAABcHuEVAAAAAODyPCRZ5iIAAABci9Pp1Lhx4zRv3jxlZmaa7RIcDoe8vLzk6+urgIAA1atXT/Xq1VNAQIB8fX3lcDhkWZby8/OVnZ2t9PR0HT9+XMePH1dmZqZyc3NVUFCg4uJi86UBoNYQXgEAAOqA04VXLy8vBQYGqk2bNurRo4d69+6tbt26qWXLlvLz85NlWcrNzVVOTo5yc3NVVFR08nk+Pj7y9fWVl5eXiouLlZaWpsTERP35559av369tm/froMHDyorK+vk8wCgNhBeAQAA6gAzvPr4+KhZs2bq27evrr76avXr109+fn7as2ePNmzYoI0bN2rnzp06dOiQ0tPTlZOTc3I31bL+37d/NptNdrtdXl5e8vPzU4MGDdSyZUt17txZF110kbp3766GDRtq3759+uGHH/S///1PmzdvVlpamgoLC80PEQCqFeEVAACgDnA6nRo/frwWL16sCy+8ULfeeqv+/ve/KzU1VStXrtT333+vrVu36ujRo8rNza10uPTy8pK/v79atGih3r1766qrrlK/fv2UnZ2tr776SkuWLNHWrVuVlZVlPhUAqgXhFQAAwMU5HA516tRJN998s4YMGaLAwEAtW7ZMy5Yt07Zt25SRkVHpsHom3t7eCgoKUt++fTVy5Ej169dPmzZt0rx587Rq1SqlpqaaTwGAKkV4BQAAcFF2u11t2rTRnXfeqZtvvllff/21tmzZohUrViglJaXaA2t5fH191b59e91000267bbbdOTIEc2aNUvffvut0tLSzHEAqBJ2SVPMRQAAANSuoKAgjR07VjNnzlRAQID+85//yNvbWwsWLFBqamqtXgm4sLBQKSkpiouL05IlSyRJjzzyiK655hodOHBABw4cqLVgDeD8RXgFAABwIT4+Prr88sv11ltvqXfv3nruuef08ssva+fOnerVq5fWrVun/Px882m1ori4WOnp6Vq7dq2+/PJLNWzYUE8//bQ6duyo7du3Ky0t7eTFoQCgsmzmAgAAAGpH8+bNNWXKFL399ttavny5rr/+ev33v//V8ePHzVGXUlRUpKSkJL3wwgu68cYbFRQUpKVLl+rmm2+Wn5+fOQ4AFcLOKwAAQC1zOBy6+OKLFRUVpebNm+u+++7TokWLSoRWLy8v9e7d26V2Xk3FxcU6ePCgli9froyMDD3zzDNq06aNNmzYUOretABwrth5BQAAqEU+Pj669dZb9fHHHysuLk6jR4/Wzz//rIKCAnO0zkhPT9f777+vkSNHqnv37lqwYIF69uwpm41vPQFUHP+CAAAA1JLAwEA98sgjeu655/T000/r2Wef1aFDh8yxOqmwsFDr1q3THXfcoc2bN+uTTz7RoEGD5HA4zFEAOCscGwYAAKgFDRs21LPPPqvhw4crPDxcy5cvP+1x4LpwbLgsmZmZWrVqlWw2m5577jnt379f8fHxKioqMkcB4LQIrwAAADWscePGevnll9WnTx+NHTtWv/766xlvfVNXw6sk5efna926dTpy5IheeOEFHT58WNu2bSPAAjgnhFcAAIAa1LBhQ7300kvq1q2bxo4dq82bN5sjZarL4VV/XZF4y5Yt2r9/v1544QUdPHhQ27ZtO2NoB4ATeM8rAABADQkICNBTTz2lnj17aty4cdq2bZs5cl4rKCjQ4sWL9cQTT2jq1KkaMmSI7Ha7OQYAZSK8AgAA1AAfHx/de++9uuqqqxQeHq6tW7eaI26hoKBA//3vf/XSSy9p+vTp6tevnzkCAGUivAIAAFQzu92u6667ThMmTNADDzygP/74wxxxK/n5+frggw/08ccf6/XXX1dwcLA5AgClEF4BAACqWc+ePTV16lQ9++yz+umnn8y2W8rJydFrr72m+Ph4TZ06VQ0aNDBHAKAEwisAAEA1atKkiV5++WV99dVXWrhwoQoLC80Rt3Xs2DFNnjxZnTp10j333CNPT09zBABOIrwCAABUEy8vL02YMEF+fn6aNm2asrOzzRG3t3PnTj3++OO6//771bdvX7MNACcRXgEAAKpJ3759dffdd2vy5MlKTk422/jL999/r08++UTPPvusGjVqZLYBQCK8AgAAVI8GDRpo8uTJ+uSTTxQXF2e2cYq8vDzNnj1bDRo00OjRo7l9DoAyEV4BAACqmM1m03XXXaeWLVvqrbfeUl5enjkCw759+/TCCy/ogQceUPv27c02ABBeAQAAqlqzZs300EMP6bXXXtO+ffvMNsrxv//9T1u3btX48ePl5eVltgG4OcIrAABAFbLb7brpppuUnZ2tZcuWqbi42BxBOdLT0/Xaa69p5MiRCgkJMdsA3BzhFQAAoAo1adJE48eP16xZs3TkyBGzjTP47bfftHbtWo0ZM4Zb5wAogfAKAABQha666irl5eVpxYoVZgtnISsrS3PnztWNN96oNm3amG0AbozwCgAAUEXq1aunsWPHav78+Tp69KjZdlnR0dGyLOtk1bbffvtNe/bs0bXXXiubjW9XAfw//GsAAABQRS644AK1bt1aX3/9dZ15r2t4eLiGDBliLteq48ePa/78+Ro9erTq1atntgG4KcIrAABAFfD09NSNN96oH3/8Ufv37zfbLmvu3Lnmkkv4/vvv1bhxY11wwQVmC4CbIrwCAABUgQYNGuiqq67S559/Xmfu6xodHW0uuYyDBw9q1apVGj58uBwOh9kG4IYIrwAAAFWge/fu8vT01Pr1682WS3LF48KnysvL07Jly3TllVdydBiARHgFAACoPLvdroEDB+qXX36pExdqCg0Nddnjwqdat26d6tWrp44dO5otAG6I8AoAAFBJfn5+uuyyy/Tdd9/ViSPDH3zwgbnkklJSUrR161b169fPbAFwQ4RXAACASgoKClLr1q3rxJHhGTNmKDg4+OTjmTNnlui7ktzcXK1evVr9+/eXt7e32QbgZgivAAAAldSxY0dlZWUpOTnZbLmU0NBQTZw48eTjmJgYLVy4sMSMKykuLtZvv/2mbt26KSAgwGwDcDOEVwAAgEq64IILtGPHDmVmZpotlxIbG1vi8dChQ0s8dkWJiYlyOp0KCgoyWwDcDOEVAACgEjw9PdW9e3dt2rRJBQUFZttlmLfFiYiIKPHYVR09elTHjx9XmzZtzBYAN0N4BQAAqAQvLy917NhRO3bsUFFRkdl2CeZtcWJiYhQVFVVixlXl5ORo79696tChg9kC4GYIrwAAAJXg4+OjoKAg7du3z2y5jFNvi5OQkFAnjgufUFhYqKSkJLVr1052u91sA3AjhFcAAIBK8PPzk6+vr8ve3zU+Pr7E4zFjxpR47OoKCwu1b98+tWzZkvAKuDnCKwAAQCX4+/vLZrO55MWayrotTlxcXImZuiAlJUWNGjUivAJujvAKAABQCb6+vioqKlJeXp7ZqlXmbXESEhIUGRlZYqauSE9PV0BAgGw2vnUF3Bn/AgAAgCpht9vl4+PjdmW327Vt2zYVFhaan5Ja9cEHH5R4XNeOC58qJydH3t7e7LwCbs5DkmUuAgAAnIvmzZvrySef1ODBg83Wec/b21uNGjVShw4dlJKSYrarjNPp1Lhx4zRv3rwzHlGOjo4ucXXhmTNnlrvrGhoaWur+rx4eHiUe17ahQ4fqueee08CBA3X8+HGzDcBNEF4BAECF+fn5aeTIkXr66af1yy+/6P3339fhw4fNsfNaSEiI7r33Xo0cObJaf+9nG17Dw8NLXF04JibmtFcXrgvhddiwYXr22Wc1cOBApaenm20AbsSiKIqiKIo6l7Lb7Vbfvn2t2NhY648//rAGDRpkeXp6lppzh+rTp4+VkJBgNW/evFSvKsvpdFqRkZGW0+ks1Tu1TGbfrNDQUPMppWZqu2688Ubr559/PuPvnaKo87t4zysAADgnLVq00KxZs7Rw4UL997//1YABA/Tdd9+poKDAHHULubm5stvt8vT0NFs1Ljo6usTjiIiIEo/rKqfTqaysLBUXF5stAG6E8AoAAM6Kn5+f7r77bsXGxqpevXq64oor9Nprr7n9Mc7s7Gx5eHjIz8/PbNWoGTNmlHifa0xMjKKiokrM1FWNGjVSWlqaioqKzBYAN0J4BQAAp2W329WvXz+tWLFCDzzwgO6++27dddddSkxMNEfdUnZ2tvLz81W/fn2zVaOGDRtW4vGQIUNkWdYZy3y/q6RSMzNmzDBHaozdblfz5s114MABwivg5givAACgXC1bttTs2bP12Wef6bPPPtNll12m77//3m2PCJclJydHx44dU/Pmzc0WqoDdblfbtm21Z88el7sdEYCaRXgFAACl+Pv7a9y4cVq9erX8/f11+eWXa+bMmW5/RLgseXl52rNnjzp06GC2UAW8vb3Vtm1b7dq1y2wBcDOEVwAAcJLD4dDf//53rVixQvfee6/Gjh2ru+++W7t37zZH8ZfCwkJt3bpV3bt3d4mLNp1v6tWrp6CgIP4MAiC8AgCA/6dVq1Z688039cknn+jjjz/WZZddph9++IEjwmdQVFSkP//8U926dZOvr6/ZrjEhISHy8PA45woLCzNfqtRMZGSkOVJjWrZsKcuydODAAbMFwM0QXgEAcHP+/v4KDw/XqlWr5O3trcsuu0yzZs1SRkaGOYpybN++XU2bNlXjxo3NFirpggsu0O7du3X8+HGzBcDNEF4BAHBTDodDoaGhWrlypSIiIjRmzBjdc889SkpKMkdxBsnJyUpPT1fXrl3NFirBy8tLl156qX7++Wfl5uaabQBuhvAKAIAbatWqlebMmaOPP/5Y8+fP1+WXX66ffvqJq7lWUEZGhtauXavLLrtMDofDbKOC6tWrp7/97W9avXo1t8kBQHgFAMCdOJ1OTZgwQatWrZLdbteAAQM0e/ZsjghXUn5+vv73v//p8ssvl9PpNNuooM6dO8vb21ubN282WwDcEOEVAAA34HA4dOmll2rlypW655579I9//EPjx4/Xnj17zFFU0Nq1a9W4cWOFhISYLVSA3W7XVVddpd9++01Hjhwx2wDcEOEVAIDzXOvWrRUVFaWPPvpI77//vq644gqtWrWKI8JV7MCBA/r99981dOhQ2e12s41zVL9+fQ0bNkxLlizh/a4AJMIrAADnL6fTqXvvvVerVq2SZVnq37+/3nzzTWVmZpqjqAI5OTlatGiRRowYoQYNGphtnKNevXopICBAcXFxZguAmyK8AgBwnnE4HOrfv79++OEH3XXXXbr99tsVERGhvXv3mqOoYqtXr5a3t7cuueQSs+Wy4uLiSt3XtbZ5e3vrtttuU0xMjA4ePGi2AbgpwisAAOeRNm3aaN68eZo/f77mzZungQMHKjY2liPCNeTw4cP6/PPPdffdd8vf399s4yx17NhRV1xxhT755BMVFBSYbQBuivAKAMB5ICAgQPfff79++uknFRQUqH///pozZw5HhGtYYWGhPv30U/Xq1Us9e/Y02zgLnp6eGj16tDZs2KCNGzeabQBujPAKAEAd5nA4dNlll+mHH37QnXfeqdtuu03//Oc/tW/fPnMUNSQhIUHR0dGaMGGCfH19zTbOoF27dho9erTeeustZWVlmW0AbozwCgBAHdW2bVu9++67ev/99zV37lwNHDhQcXFxHBGuZXl5eYqKilL//v31t7/9zWzjNLy8vDR27Fht3bqVCzUBKIXwCgBAHRMQEKAH/7/27j6oyjp/4/jlOZ5zIImHAMecDJMKxUxXrOCgyeQjsBSlWaY5TVo2ZknqoKXuWddxjYdctyl2SyYy3d1awIQk14yUatHWbXxAtMYYYdJSU9AwERDu3z+/dfJGS3y8D+f9mrlmmO/nc5Q/+INr7i/nPP+8ysrK1NDQoMGDB+vNN9/kKZWF7NmzRwUFBZo9e7YCAwPNY5xHdHS0xo8fr6VLl6q+vt48BuDjKK8AAHgJh8OhhIQElZWVafz48Xr00Uf17LPP6sCBA+ZVXGNNTU3661//qqioKCUnJ8tm41euXxMQEKD09HRt2LBBW7ZsMY8BgPIKAIA36Nmzp/Ly8pSXl6ecnBwNHz5cW7Zs4YqwhVVXVys7O1svvfSSIiIizGP8jM1mU3JysgYNGqSlS5eqoaHBvAIAlFcAAKwsMDBQaWlp2rRpk+rr6zV48GDl5uZyRdgLtLS0qKCgQFVVVUpPT+ejc35BZGSkFixYoKysLO3du9c8BgCJ8goAgDU5HA7dd999Kisr07hx4/TII49o+vTpXBH2MseOHZPH49Hw4cOVmpoqu91uXvF5gYGB8ng82rVrl/75z3+qpaXFvAIAZxiEEEIIsU5uueUW4+9//7uxb98+48knnzSuu+66NjvEe2K3243HH3/c2Lt3rxETE9NmfqEJCAgw0tLSjICAgDYzb43T6TTS0tKMiooKIyoqqs2cEEJ+Hp68AgBgEYGBgZo5c6Y2btyouro6xcfH66233tLJkyfNq/AiLS0tKiwsVHFxsZYtW6abb77ZvOKT7Ha7RowYobS0NKWnp+vrr782rwDAWSivAABcYw6HQ8OGDdNnn32mhx56SOPGjdPzzz+v7777zrwKL3Xy5EllZGSotrZWGRkZCgsLM6/4nJiYGC1dulTZ2dkqLS01jwGgDcorAADXUK9evfTOO+9o+fLl+tOf/qSRI0fqP//5D3/31wEdPnxYM2fOVEREhDwej4KCgswrPqNv3776y1/+otWrVysvL09NTU3mFQBog/IKAMA1EBQUpNmzZ+uTTz7RkSNHFB8fr7fffpsrwh1cVVWVnnnmGQ0ZMkTz5s1TYGCgeaXD6927t5YvX66tW7cqIyODd84GcMEorwAAXEUOh0MjRozQZ599pgceeEBjx45VWlqavv/+e/MqOqidO3dq8uTJGjVqlDwej0JCQswrHdYdd9yhvLw87d69W/PmzdOxY8fMKwBwXpRXAACuksjISK1atUpvvPGGsrOzNWrUKP33v//lirAP+vLLL/XEE09o6NChysrKUrdu3cwrHYrdbldsbKxWrlypbdu2ac6cOTp69Kh5DQB+EeUVAIArLCgoSOnp6SotLdXBgwfldrv1zjvvcEXYx23btk2PP/64brnlFuXm5ioqKsq80iG4XC6lpKRo5cqVKikp0UsvvURxBXDR2nx+DiGEEEIuPQ6Hwxg5cqRRUVFhlJWVGTExMYbdbm+zR3w7N910k7FixQpjx44dxvDhww2n09lmR176Oa8hISHGnDlzjOrqamPq1Kl8ZjEh5FLT5oAQQgghl5hbb73VyM/PN6qqqoyJEyca/v7+bXYI+V+CgoKM9PR0o7q62pgzZ44RGhraZsebyqvdbjeio6ONgoICY9u2bcawYcMMh8PRZo8QQtoTrg0DAHAZBQcHa+7cufr444+1f/9+ud1urVq1Sg0NDeZV4Izjx49r2bJleuqppzR27Fj97W9/U2xsrJxOp3nV8oKCgjRp0iS9//77qq+v15gxY1RaWqrm5mbzKgC0W5tGSwghhJD2xel0GqNHjzZ27dplbNq0yRg4cCBXhMlFpUePHkZ2drZRXV1tLFq0yIiIiDDsdrvln7z6+fkZbrfbKC4uNiorK40JEyZY9nslhHht2hwQQgghpB257bbbjMLCQqOqqsp47LHHuCJMLjl+fn5GQkKCsX79eqOystKYNm2a0atXL+OFF16wXCF0uVzGnXfeaeTk5BjV1dXGK6+8YvTq1cuw2Wxtdgkh5FLS6f+/AAAA7RQcHKxp06bp6aefVmFhoTIzM3Xo0CHzGnDRgoODlZiYqBkzZshms2nt2rXKz8/XN998c82v4Xbp0kXR0dF64oknlJSUpH//+9969dVXtWPHDjU2NprXAeCSUV4BAGgnp9OpYcOGKTs7W4cOHdLMmTNVUVHB57XiigkPD1diYqKio6OVnJys0tJS5efnq7KyUvX19VftZ8/pdCo8PFxut1sTJ05U//79tXHjRi1fvlzbt2/n458AXFGUVwAA2uH2229XRkaG+vXrpwULFmjNmjW8GROuioCAAD399NPas2ePHn74YQ0dOlQ//PCDSkpKVFpaqm+++UbHjx+/rE897Xa7XC6Xunbtqv79+yspKUkJCQk6efKkVq9erdWrV6uqqkqnTp0yvxQALjvKKwAAFyAkJETTpk3TU089pfz8fGVlZenw4cPmNeCKCQgI0JQpU5Sbm6vm5mZ1795dgwcPVkpKigYOHKjGxkZt375dmzdvVkVFhb799lsdO3ZMp06dUnNzs1pbW8/5hNZms8lms8lut8vhcKhLly4KCwtTr169FBMTo7i4ON1222368ccftXHjRpWUlGj79u2qq6s7578HAFcK5RUAgF/gdDo1YsQIZWVl6bvvvtOsWbO0a9cufmnHVffz8nrixIkz535+fgoLC1OfPn0UFxenu+++W5GRkfL391d9fb0OHjyo77//XocPH1ZdXZ1++uknnT59Wp06dZLL5VJAQIBCQ0PVrVs33XjjjQoPD5fT6VRdXZ127dqlzZs3a+vWrdq3b5+OHz+u06dPn/V9AcDVQnkFAOA8oqKilJmZqejoaM2fP19FRUVcj8Q1c77y+nN2u11Op1PXX3+9wsLC1L17d/Xo0UPdu3dX165dFRwcrOuuu06dO3eWJDU2NurEiROqra3VwYMHtX//fu3fv18HDx5UbW2tTp48qaamJvN/AwDXBOUVAACTkJAQTZ8+XZMnT9Z7772n7Oxs/fDDD+Y14Kq6kPJ6Pv+7GtypU6czkSTDMGQYxnmvFAOAldjMBwAA+Cqn06mUlBSVl5fr3nvv1f33368XX3yR4gqv19raqtOnT6u5uVlNTU1qbGxUY2Ojmpqa1NzcTHEF4BUorwAASOrdu7cKCgq0dOlS/e53v1NKSop27typ1tZW8yoAALgGKK8AAJ92ww03yOPx6F//+pcqKysVFxen/Px8/rYVAACLobwCAHySy+XS/fffr/LycrndbqWkpGjevHk6cuSIeRUAAFgA5RUA4HP69OmjwsJCZWdna968eXrggQdUUVHBFWEAACyM8goA8BmhoaFauHCh1q1bpx07dsjtdquwsJArwgAAeAHKKwCgw3O5XEpNTVV5ebnuvvtuJScna8GCBVwRBgDAi1BeAQAdWnR0tN5//31lZGToxRdfVGpqqiorK7kiDACAl6G8AgA6pNDQUC1atEgffvihvvzyS7ndbq1evVqNjY3mVQAA4AUorwCADsXlcumhhx5SeXm5YmJilJSUpAULFujo0aPmVQAA4EUorwCADsFms+mOO+5QUVGR/vjHP2rOnDl68MEHtXv3bvMqAADwQpRXAIDXCwsL06JFi7R27Vp98cUXio+P15o1a7giDABAB0J5BQB4LT8/P40ZM0bl5eXq37+/EhMT5fF4uCIMAEAHRHkFAHgdm82mfv36qaioSIsXL9bs2bM1ZswY7dmzx7wKAAA6CMorAMCrhIeHa/Hixfrggw9UXl4ut9ut4uJirggDANDBUV4BAF7Bz89PDz/8sMrLy9W3b1+NHj1aCxcuVG1trXkVAAB0QJRXAMBV0blzZ02aNEmpqanm0S+y2Wy688479cEHH+gPf/iDXnjhBY0dO1ZfffWVeRUAAHRglFcAwBXn7++v+fPna8WKFVq2bJlCQ0PNK+cUHh6uJUuWqLi4WJ9++qncbrfWrl2rpqYm8yoAAOjgKK8AgCsqODhYb775pjwejyQpIiJCM2bMMK+dxc/PT4888og2b96sqKgojRo1SosWLVJdXZ15FQAA+AjKKwDgiunRo4eKi4s1ceLEs84nTZqk6Ojos84kyW63q3///iopKZHH49GMGTM0btw4ff311+ZVAADgYyivAIArYsCAAdqwYYOGDBliHikiIkKZmZlyuVxnzrp27aqXX35ZRUVF+uSTTxQfH6+SkhKuCAMAAInyCgC43Gw2mxITE7VmzRpFRUWZx2ckJydr9OjR8vf31/jx41VeXq5bb71VI0eO1OLFi7kiDAAAztJJkmE+BADgYjgcDk2ZMkU5OTnm0Tlt2rRJdrtdoaGhmj17tkpLS3nSCpxHQECApkyZotzcXJ04ccI8BoAOjyevAIDLokuXLlqyZMkFF1dJSkhIUG1treLj47Vu3TqKKwAAOC/KKwDgkoWFhWnlypWaNWuWefSrBgwYoBtvvNF8DAAAcBbKKwDgkkRGRmrdunV68MEHzaMLcq43bwIAADCjvAIALlpsbKzWr1+vQYMGmUft8tvf/lYjR440HwMAAJxBeQUAtJvdbtfYsWP17rvvKjIy0jy+KJmZmbrhhhvMxwAAABLlFQDQXi6XSzNnzlR+fr4iIiLM44vWu3dvTZ8+3XwMAAAgUV4BAO1x/fXX689//rMyMzPNo8ti7ty55iMAAACJ8goAuFDdunVTQUGBpk6dah5dspqaGmVnZysxMdE8AgAAkCivAIAL0adPH3300UeX/U2Vdu7cqeeee07x8fGaO3euysrKzCsAAAAS5RUA8GsSEhL04Ycfql+/fubRRampqdHbb7+tuLg4xcbG6rXXXtOBAwfU0tJiXgUAADiD8goAOKfOnTtr0qRJ2rhxo3r27Gket9vWrVs1efJk3XPPPZo8ebK2bNmihoYG8xoAAMA5UV4BAG34+/tr/vz5WrFihXnULtXV1crJydHAgQN177336q233tKhQ4fU2tpqXgUAAPhFlFcAwFlCQkK0fPlyeTwe8+iCff755xo/frzuuusuPfvss9q2bZtOnTplXgMAALhglFcAwBk9evRQcXGxJkyYYB79qn379ikrK0t9+/bVsGHD9O677+rIkSPmNQAAgItCeQUASJIGDBigDRs2aPDgwebRL/r444+VmpqqgQMHKj09Xbt371ZTU5N5DQAA4JJQXgHAx9lsNiUlJWnNmjWKiooyj89p7969+v3vf6/bb79dSUlJKioq0rFjx8xrAAAAlw3lFQB8mMPh0NSpU1VSUqKIiAjzuI3i4mKNGjVKgwYN0sKFC7V37141Nzeb1wAAAC47yisA+KguXbpoyZIlysnJMY/OsmfPHqWnp6tnz54aM2aMPvroI/3444/mNQAAgCuK8goAPigsLEyrVq3SrFmzzCNJUk1Njd577z0NHTpUd911l7KyslRTU6PTp0+bVwEAAK4KyisA+JjIyEitW7dOqamp5pF27Nih6dOnKz4+XhMmTNCnn36qn376ybwGAABw1VFeAcCHxMbGav369Ro0aNCZs5qaGuXl5Sk2NlZxcXF6/fXXdeDAAbW0tJz1WgAAgGuJ8goAPsBut+vRRx9VYWGhIiMjJUlbt27Vk08+qXvuuUdTpkzRF198oYaGBvNLAQAALIHyCgA+IDc3V//4xz904MABvfbaa/rNb36jIUOGKC8vT4cOHVJra6v5JQAAAJZCeQUAH5CamqpnnnlGiYmJeu6557R9+3Y1Njaa1wAAACyL8goAPiAkJERvvPGGjh49ah4BAAB4BcorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDyKK8AAAAAAMujvAIAAAAALI/yCgAAAACwPMorAAAAAMDy/g+6v7MbLj8XpAAAAABJRU5ErkJggg==
305341043 发表于 2025-4-26 10:44
引线内容的组码是302，你稍微修改修改就可以用了，使用vla-copy函数复制后，改下组码内容，然后使用vla-move移动就行
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