ELF          >            @       Pr         @ 8  @                                  X      X                    `       `       `                                               8;     8;                  M     ]     ]     "       -                   \     l     l                                                $       $                    J     J     J                                  J     J     J     p       p              Std   J     J     J                            Ptd   ,     ,     ,                        Qtd                                                  Rtd   M     ]     ]     p      p                      GNU kPHb"pb!M                              )*l                                                                                                                b                     e                                          
                     x                     A                                          j                                          	                     t                                           [                                          Y                                                                                                                                                                        -                     	                     +                     e                      j
                                          9                                          A                     	                     F   "                                                                                   
                     
                                          $	                                           	                                                                                                          %                                                                                    O                                          M                                          R                     \
                     L                     +                     t	                                                                                    	                                          C
                     d                                          Q                                          P                     T                                           /
                                                               
                                                                                     l                     	                                                               :                                                               H                     v                     ~                                                               
                                                                                    .                     J                     
                     B                                          w                                                                                    R                                                                                                                               4                                          U                      :                     @                     &                                          	                     
                     j                                           o                                                                                                                                                                                                                  ?	                                          A                     c	                                           R                     _                                          3                                          E                     }                                                                                                                                                    $                     P	                                                                                    :                     4                     $                     {
                                                               	                     o                     b                     =                                                                                    m                                          g                     	                     5                                          
                                                                                                                                F                                          e                                                                                    #                                                                                                           ,                                            
                     V                                                                                        ق              __gmon_start__ _ITM_deregisterTMCloneTable _ITM_registerTMCloneTable __cxa_finalize PyExc_Exception PyObject_VectorcallMethod _Py_NoneStruct PyExc_TypeError PyErr_Format _Py_Dealloc __stack_chk_fail _Py_FalseStruct PyTuple_New _Py_TrueStruct _PyDict_GetItem_KnownHash PyList_New PyMethod_Type PyObject_Vectorcall PyObject_IsTrue PyErr_Clear PyObject_GetOptionalAttr PyErr_Occurred PyExc_NameError PyObject_GetAttr PyLong_AsSsize_t PyObject_RichCompare PyFloat_FromDouble PyLong_Type PyUnicode_Type PyUnicode_Format PyNumber_Remainder PyFloat_Type PyLong_FromLong PySlice_New PyObject_SetItem PyBuffer_Release PyThreadState_GetUnchecked PyNumber_Invert PyException_SetTraceback PyNumber_Long PyExc_SystemError PyErr_SetString PyBaseObject_Type PyFloat_AsDouble PyTuple_Type PyList_Type PyNumber_Add PyNumber_InPlaceAdd PyObject_Size PyLong_FromSsize_t PyObject_GetIter PyExc_ValueError PyImport_ImportModule PyExc_ModuleNotFoundError PyErr_ExceptionMatches PyObject_GetAttrString PyCapsule_Type PyExc_RuntimeError PyCapsule_GetPointer __cxa_rethrow __cxa_begin_catch PyExc_MemoryError __cxa_end_catch PyExc_IOError PyExc_IndexError PyExc_OverflowError PyExc_ArithmeticError _Unwind_Resume _ZTINSt8ios_base7failureB5cxx11E _ZTISt10bad_typeid _ZTISt11range_error _ZTISt12domain_error _ZTISt12out_of_range _ZTISt14overflow_error _ZTISt15underflow_error _ZTISt16invalid_argument _ZTISt8bad_cast _ZTISt9bad_alloc _ZTISt9exception __gxx_personality_v0 _ZdlPvm PyGILState_Ensure PyGILState_Release PyObject_Format Py_BuildValue __memcpy_chk PyUnicode_FromOrdinal PyNumber_InPlaceSubtract __gcc_personality_v0 _Znwm memcpy _ZSt20__throw_length_errorPKc PyArg_ValidateKeywordArguments PyDict_Next PyNumber_Subtract PyExc_UnboundLocalError PyObject_CallFinalizerFromDealloc PyObject_GC_IsFinalized PyObject_GC_UnTrack PyDict_SetItemString PyExc_AttributeError PyThreadState_Get PyInterpreterState_GetID PyExc_ImportError PyModule_NewObject PyModule_GetDict PyDict_New memcmp PyObject_Hash PyObject_RichCompareBool PyInit__shortest_path PyModuleDef_Init PyCFunction_Type PyObject_VectorcallDict Py_EnterRecursiveCall Py_LeaveRecursiveCall PyObject_IsSubclass PyErr_SetObject PyObject_Call PyTuple_Pack PyImport_AddModuleRef PyObject_SetAttrString Py_Version PyOS_snprintf PyErr_WarnEx PyBytes_FromStringAndSize PyUnicode_FromStringAndSize PyDict_Type PyUnicode_InternFromString PyUnicode_Decode PyEval_GetBuiltins PyObject_GetItem PyType_Type PyImport_GetModuleDict PyDict_GetItemString PyCapsule_New PyDict_SetItem PyMem_Malloc PyMem_Free PyObject_SetAttr _PyType_Lookup PyDict_DelItem PyType_Modified PyList_AsTuple PyObject_CallObject PyException_GetTraceback PyList_Append PyType_IsSubtype PyList_SetSlice PyDict_GetItemRef PyDict_Size PyErr_GetRaisedException PyErr_SetRaisedException PyNumber_Index PyErr_GivenExceptionMatches PyUnicode_FromString PyExc_DeprecationWarning PyErr_WarnFormat PyMethod_New PyExc_RuntimeWarning PyImport_ImportModuleLevelObject PyObject_ClearWeakRefs PyObject_GC_Del PyUnicode_FromFormat PyTuple_GetSlice PyTuple_GetItem PyErr_NoMemory PyObject_GetBuffer PyErr_PrintEx PyErr_WriteUnraisable PyUnicode_New PyUnicode_CopyCharacters memset PyObject_HasAttr PyObject_CallMethodObjArgs PyType_Ready PyGC_Disable PyGC_Enable PyModule_GetName PyUnicode_Concat PyImport_GetModule strrchr PyType_FromMetaclass PyDict_SetDefaultRef _PyObject_GC_New PyObject_GC_Track PyFrame_New PyTraceBack_Here PyCode_NewEmpty memmove PyMem_Realloc PyLong_AsLong __vsnprintf_chk _Py_FatalErrorFunc PyLong_AsUnsignedLong PyDict_GetItemStringRef PyCapsule_IsValid PyCapsule_GetName PyDict_SetDefault PyBytes_AsString PyUnstable_Code_NewWithPosOnlyArgs PyExc_StopIteration libstdc++.so.6 libgcc_s.so.1 libc.so.6 GLIBC_2.4 GLIBC_2.14 GLIBC_2.3.4 GLIBC_2.2.5 GCC_3.0 GCC_3.3.1 CXXABI_1.3.9 GLIBCXX_3.4 CXXABI_1.3 GLIBCXX_3.4.21                                                                                                                                                                                                   	            
                                                                                                                                                                                r     P   ii  
 |             ti	        ui	           d     0   P&y        a_&	           U         yѯ  	      t)        ӯk        q         ]                  ]            @      ]                  ^                 ^                  ^                 ^            H     ^                 ^                 ^                 ^                 @_                 _                 _                 _                 @`            {     `                 `            @     `            H     `            g     `            X     `            N     `            L      a                  a                  a                 0a                 @a                 Pa            `     `a            T     pa            H     a                  a                 a                 a                 a                 a            е     a                 a                  b            `     b            W      b            @     0b            0     @b                  Pb                 `b                 pb                 b                 b                 b                 b                 b            p     b            @     b                  b                  c                 c                  c                 0c            Բ     @c            в     Pc            ɲ     `c            ò     pc                 c                 c                 c                 c            @     c                  c                  c                 c            Ф      d                 d                  d                 0d                 @d                 Pd            t     `d            p     pd            h     d            X     d            O     d            J     d            @     d            0     d                  d                 d                   e                 e                  e            У     0e            ţ     @e                 Pe                 `e                 pe                 e                 e                 e                 e            x     e            h     e            `     e            S     e            @      f            0     f                  f            	     0f                 @f                 Pf                 `f                 pf                 f            ؎     f            Ȏ     f                 f            p     f            f     f            a     f            X     f            U      g            H     g            0      g                  0g                  @g                 Pg                 `g                 pg            ؁     g            ΁     g                 g                 g                 g                 g                 g            y     g            p      h            h     h            s      h            s     0h            s     @h            s     Ph            ps     `h            ds     ph            as     h            Xs     h            Ps     h            @s     h            9s     h            0s     h             s     h            s     h            	s      i             s     i            r      i            r     0i            r     @i            r     Pi            r     `i            r     pi            `r     i             r     i            r     i            r     i            r     i            r     i            q     i            q     i            q      j            q     j            q      j            q     0j            q     @j            q     Pj            pq     `j            hq     pj            dq     j            Pq     j            @q     j             q     j            q     j            p     j            p     j            p     j            @p      k            5p     k            (p      k            p     0k             p     @k            o     Pk            o     `k            S     pk            pS     k            bS     k            ]S     k            VS     k            HS     k            8S     k            (S     k            !S     k            S      l            S     l            	S      l            R     0l            R     @l            R     Pl            R     `l            R     pl            R     l            R     l             C     l            C     l            C     l            z     l            t     t            t     u                 u                  v                  v                 v            p     (v            )     0v                 8v            p     Pv            1     Xv                 `v            @     xv            ;     v                 v            @     v            D     v                  v                 v            Q     v                  v            @     v            [     v                   w            @     w            d      w                  @w            q     Hw                  hw            }     pw            @     w                 w            @     w                 w            `     w                 w            `     x                 x            P     x            p     0x                 8x            P     @x            p     Xx                 `x                 hx            0     x                 x                 x                 x                 x                  y                 (y                 Py                  xy                 y            (     y                 (z            u     Hz                 Xz                  hz            0     xz                 z            P     z            y     z             y     z             v     z                 z            R     z                  {                 {            `u     H{            z      X{                  {            H0     {             z     {            p0     {            @z     {            0     {            @     x|            =     |            >     |            >     x}            0     }             @     H~            z     ~                                               `u                  R     (                 @            w     H            8     X                 `            
     h            n     x                                               З                                  V                                                    3                                                    4                 P                  @                                         H            3     P                 `                 h            @{     n                   n                   n                   n                   n                   n                   n        %           n        2            o        3           o        9           o        >           o        ?            o        R           (o        S           0o        T           8o        ]           @o        _           Ho        a           Po        k           Xo        m           `o        u           ho        y           po                   xo                   o                   o                   o                   o                   o                   o                   o                   o                   o                   o                   o                   o                   o                    u                   (u        c           0u                   8u        1           @u                   Hu        A           Pu        d           Xu                   `u                   hu        ~           pu                   xu                   u                    p                   p                   p                   p                    p                   (p                   0p        	           8p        
           @p                   Hp                   Pp                   Xp                   `p                   hp                   pp                   xp                   p                   p                   p                   p                   p                   p                   p                   p                    p        !           p        "           p        #           p        $           p        &           p        '           p        (           p        )            q        *           q        +           q        ,           q        -            q        .           (q        /           0q        0           8q        4           @q        5           Hq        6           Pq        7           Xq        8           `q        :           hq        ;           pq        <           xq        =           q        @           q        B           q        C           q        D           q        E           q        F           q        G           q        H           q        I           q        J           q        K           q        L           q        M           q        N           q        O           q        P            r        Q           r        U           r        V           r        W            r        X           (r        Y           0r        Z           8r        [           @r        \           Hr        ^           Pr        `           Xr        b           `r        e           hr        f           pr        g           xr        h           r        i           r        j           r        l           r        n           r        o           r        p           r        q           r        r           r        s           r        t           r        v           r        w           r        x           r        z           r        {           r        |            s        }           s                   s                   s                    s                   (s                   0s                   8s                   @s                   Hs                   Ps                   Xs                   `s                   hs                   ps                   xs                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                   s                    t                   t                   t                   t                    t                   (t                   0t                   8t                   @t                   Ht                   Pt                   Xt                   `t                   ht                   pt                   xt                   t                   t                   t                   t                   t                   t                   t                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           HH HtH     5 % @ h    fh   fh   fh   fh   fh   fh   fh   rfh   bfh	   Rfh
   Bfh   2fh   "fh   fh   fh   fh   fh   fh   fh   fh   fh   fh   fh   rfh   bfh   Rfh   Bfh   2fh   "fh   fh   fh   fh    fh!   fh"   fh#   fh$   fh%   fh&   fh'   rfh(   bfh)   Rfh*   Bfh+   2fh,   "fh-   fh.   fh/   fh0   fh1   fh2   fh3   fh4   fh5   fh6   fh7   rfh8   bfh9   Rfh:   Bfh;   2fh<   "fh=   fh>   fh?   fh@   fhA   fhB   fhC   fhD   fhE   fhF   fhG   rfhH   bfhI   RfhJ   BfhK   2fhL   "fhM   fhN   fhO   fhP   fhQ   fhR   fhS   fhT   fhU   fhV   fhW   rfhX   bfhY   RfhZ   Bfh[   2fh\   "fh]   fh^   fh_   fh`   fha   fhb   fhc   fhd   fhe   fhf   fhg   rfhh   bfhi   Rfhj   Bfhk   2fhl   "fhm   fhn   fho   fhp   fhq   fhr   fhs   fht   fhu   fhv   fhw   rfhx   bfhy   Rfhz   Bfh{   2fh|   "fh}   fh~   fh   fh   fh   fh   fh   fh   fh   fh   fh   rfh   bfh   Rfh   Bfh   2fh   "fh   fh   fh   fh   fh   fh   fh   fh   fh   fh   f%F fD  %F fD  %> fD  %6 fD  %. fD  %& fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  %~ fD  %v fD  %n fD  %f fD  %^ fD  %V fD  %N fD  %F fD  %> fD  %6 fD  %. fD  %& fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  %~ fD  %v fD  %n fD  %f fD  %^ fD  %V fD  %N fD  %F fD  %> fD  %6 fD  %. fD  %& fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  %~ fD  %v fD  %n fD  %f fD  %^ fD  %V fD  %N fD  %F fD  %> fD  %6 fD  %. fD  %& fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  %~ fD  %v fD  %n fD  %f fD  %^ fD  %V fD  %N fD  %F fD  %> fD  %6 fD  %. fD  %& fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD  % fD                                  UH= HATSHHu4H H8r  H= HH   H5  H.IċxȉuHM   H I9D$t8H H5
 H8:A$   A$   L~1LH A$xA$uLH HuH, H5Z H81=   H v(   H5 H H81v  !H    H5 H81HX   uH H5ا H8@ȸ    tH~ H5 H8[A\]UHSQH?  {HHH
  H HcH>HHRHH H8Z[]NHHRHH H8HHRHH H8leHHRHH H8JCHHRHH H8(mHHRHH H8HHHRHH H8#HHRHH H8HHRHH H8HHRHH H8oeHHRHH H8J@H H5ҙ H8*o:4.("
H}HHiHX[]HpHtHuH)%HEdH+%(   uHYHuH}H  HEdH+%(   uH0LLHM0T  ~ HHXHHH  H0H H  HEdH+%(      HHHEdH+%(   uH= HxHu+H  HAR  
 Hr%L  
 H8H'$HL/I  }
 HHUHHATSHUHdL$%(   LeIH= H]Hu%_HuH LH5Ö H81HEdH+%(   t{ZHY[A\]UHAWEAVIAUIHATSAQ1Ht>H;M Iu1AtLLLzA$x1A$u)LH H8tq1Z[A\A]A^A_]UHAVAUIATS*HxqHt^HL Hu	H? H9tHy H5J H8+L%	 Mu&H5 LMIHu(L  1   A$=wA$L   HHAxAuLHtH_IHt#A   H HLH wyIwA   H LLH LxA   H LLH )xE1H LLH 	xH[A\A]A^]UHATSH   dH%(   HE1hH  Hx
 IH. L H0HH`   ~ 
 )0A  H H  H H IL H H0H  H0H
 H8H H@H^ HHH( HPH
 HXH	 H`H	 HhH HpH HxH HE@  H H  H
 H IL+ H
 H0H@$   ~
 ~;
 t ~ -  H`)0)@)PP@  HF H5  HF IL$ H0H`<f  H0H H8Hg H@H	
 HHH
 HPH HXH H`Hq HhH	 HpH HxHG HEHD	 HEH)
 HEH HEH HEH HEH H H	 HEH HEHQ HEHV HEHS HEH8 HE?  H  H  H H IL H	 H0HEl  H0HQ H8H H@H HHHw	 HPH1 HXH H`H HhH HpH HxH HEH HEH- HE>  H H  H ILk H0H  H0Ht H8H. H@H HHH HPHT HXH H`H8 HhH2 HpH HxH HEH HEH HEHE HEH
 HEH HEH H HN HEH HE<  H H  H ILi H0H   H0HZ H8H< H@HF HHH( HPH HXH\ H`H HhH HpH HxH HEHy HEH HEH# HEH  HEH- HEHr H H, HEH HE;  H  H   H H IL  Ha H0HA  	   H0;  H  HtpH H IL؝ H H0H` 	   H0H
 H81;  HW  Hty1)ȉuHxȉuHHUdH+%(   t#H   [A\]H=< UHAWAVAUATSH  Hp dH%(   HE1Ht)H9/  HD H5 H8/  =wH= H H  wH= H H  H=v H H  H H= H5[   Hs H 0HH  u1HV Huk  HHW   HH    A   L RH PH P1H 1   H   1H= 0H H   1H=ȍ bH H   H L% ~ fHnLL= flV M,$MtuAD$
 t:@t
L?At$Hc$t1LILAt$LHcoHtGIHoHt7II1Hr Ht   sHd H   1E1E1A   HH' E1HHu  Lm  Ha  LY  H=  tMH=W  tEHtDH= 
` H=k Ht<1H[ x-ȉu' mHuH H5z H8H=" ,  HH HHkHl HfIHu   i	   H= AHHtLHnIċxȉuHMtLJA$xA$uLt1 uzHHu0kHt1E11A   HH{ A   LH5    1IHtHH5 11  Hm A$xA$uLH=N Ht1H5 t1  H HeIHTH5C HkHtH= H H   HY H5
 LH= Hu H  H=5 H  H=P H  H  H= tH  Hp  H=( XH  HT  H=t <H HaH5      1HHr H  L5 LLLHE H  HL   1JH3 H  H5    1'H H  AWH.    1HH L AVL H5 H ZYHc  L H 1   H H5 H H+  L H L1H5    vH H gHr H=+ ~ H<  H5 fHnH	 H= flfHnH )+ ~[ H< fl)! i)  u  H= 11L-z IHt?I  H5 Hx%A$W  A$K  L>  L.  
  HcHIcA   IH IGHID HL9R  KD H  )  IH  I   LH;  H9uAH  LHHP)  HLHHHAHI9   H   IcH5Ě ID HHI   HPH H81WL1E1E1A   HH A   tL5 E1I   MP  HA|$H HAH   HIH   HL7Hx H5) H= -FL-V H5' LL5 HIuH5 LIH?  :H5 LI9tE1E1E1E1LLLq  H5Z Lz HH  I9/  H5" LIHtH5 L; HHuE1E1E1LL  L;u5HH5 LHHHHHu1yH5 H['  AąuE1E1E1L  HH5` L3%  "  I  H5J %Aąu
L6&   L;   H   E1HH5p L8LMtH5] L&  utHH5< LLMt>H5 LLq$  xjI  H5 gAąu
LxxDMt7hHu3E1LXnE1E1E1LLLE1E1+HuH IUH5\ H81AE1E1E1E1LLHl  H`  HT  LL  LD  AH= H=- #  H= IH  A     HH H5Ȃ %  H( H  AE xAE uL?H=҂ IH  A       HH H5 ;%  H Hw  A   H
  LH H5t 
%  H HF  A   0  LHY H5C $  H} H  A      LH2 H5 $  HT H  A      LH	 H5 w$  H+ H  A      LH H5 F$  H H  A      LH H5 $  H HQ  A      LH H5N #  H H   A      LHT H5 #  H H  A      LH3 H5 #  H^ H  A      LH H5 Q#  H5 H  A      LHـ H5  #  H H\  A      LH H5Y "  H H+  A      LH H5( "  H H   A      LHi H5 "  H H   AE xAE uL0H=4 IH   A   p   HHP H5 ,"  HH HtlH  $!  Ht[A      LH H5 !  H Ht.H     HtAE x"AE uLE1L  H=v HH  H H HH5i '    H H HH5U '    H H HH5? '  ~  H H HH5. ~'  Y  H' H HH5 Y'  4  H H; HH5 4'    H  H HH5
 '    Hx H HH5~ &    H H HH5~ &    Hޓ H HH5~ &  {  H Hb HH5~ {&  V  H H5 HH5~ V&  1  H H HH5~ 1&    H" H HH5~ &    H% H HH5u~ %    H@ H HH5j~ %    H[ HT HH5W~ %  x  H^ H' HH5?~ x%  S  H4~ H HH5@~ S%  .  H1~ H HH5+~ .%  	  H H  HH5~ 	%     H2 H{ HH5	~ $     H5 HN HH5} $     H@ H! HH5} $  tyHW H HH5} y$  tXHn H HH5} X$  t7H H HH5} 7$  tx ȉuHoHE1  /  H=V '  HH|  H5> H= H    H= &  HH  H5n H= H  
  H H5    18  HH  H= H  IH  
  H5 L  HHj  H5 H= Hq  
  H5 L  HH'  H5 H= H.  W
  AE b
  H5    1b  IH  H=" H  HH   AE 5
  H5 H5  IH  H5 H=! H9   AE 	
  
  H H5-    1  HH  H=n HX  IH  	  H5 L  HH  H5 H= H  	  H5 LX  HH  H5 H=D H\  	  AE 	  HXxIL+M	  H[Hu1E1H	  H̯  Lį  H踯  H= | IH=  H5) H1 HHH  AE   H5R H={ HB    H=:  HH>  H5B Hʮ IHJ    H5 H= L.F  AE   H    H01$IH5  LxE11I9|  M  LHA  H!  HCE1E1HL9  MuL5L A=wAH H5 LHL=n HHH  fHnfIn1H      flHHH o HIċ  M  HH5l L  H5 LL  I9tLH5Ex L  AE   L La 1H= H Hz   IH  Hj H   =wH5 Hx LLI9D$:    AE +  ~ fHn1LHH H      flL% 1I苬  M  H5 H= L  AE   A$  A    L L9 1H= H H
   HH  HJ H   =wH5 H= H     L/ L 1H=7 HX H1 A  HH  H H   =wH5 H=o H{  +  L LG 1H= H H    HHY  H= 1AHCxIHb  H= 赪 IHo  H5 Hj IHy  AE   HCxH5 HH= L`HR%  H   [    L Lv 1H= H Ho   HH9  H H   =wH5< H=% H=(  (  L L 1H= H H& ~  HH  H H   =wH5 H= H    ]HH  H H5{ H  H H5 Hm  H H5 HO  L L 1H= H H   IH  H   =(  H5V H= L|  A$   L< L    H=y H: H3 #  IHT  H5 H=l H@  A$
  L LB    H= H H   IH  H5 H=	 H!  A$
  IH  H H5 Hv
  E11HBu A   A   ȉHȉHȉGH:ȉsHfȉHAE LAE LqAE LXȉHAȉH*ȉ>H1ȉjH]AE ]LPL;- [AE =wAE I]=wLH:ID$pHu1E1E1  H  H! LxL2M9tuIF   tUIN1H9~M;| tVH1H9~It I9t@LHH
] HHuHLL\ _H   H=p 8@ Mt$p1IT$pMtHM~A=wALHH   =  H  1E1HID$xLHL0H٤  Hͤ  H  H= =w1HH      HH H H	 HxʉuHHHt$H1H车 Hxʉt  
HID$xE1H8L(E1  H1  H  LA"   ٣  LA   ˣ  H迣  HJ H=bn > H?q AE Lȉ&HȉLH?AE ]LPMd ID$   udH5 LHHHq	  lHuP2AE =N	  AE C	  A9LH,M	  LL	  LE11A*   蔢  A   H'p JD LxMtLLIuELL:tM1H H5S E1A*   A   H8Ho IE1E1Ho A   A   v1E1E1A   HH~o A   OE1E1Hfo A   A   1E1E1E1A   LH8o A   	E1E1H o A   LA   E1Hn A   A   E1E11A   LHn A   E1E1Hn A   LA   }E1Hn A   A   bE1E1E1A   LHin A   :E1HTn A   A   E1E1H6n A   LA   E1Hn A   A   1E11A   HHz A   1E1Hz A   HA   E1E1Hz A   A   w1E1E1A   HHWz A   P1E1A   A   HH-z ,E11Hz A   A   1E11A*   HHm A   1E1Hm A*   HA   1E1E1A   HHl A   ȉMCyHF  I(A$-  A$!  LS  AE cL:VAE LAE .L!A$!LALȉHȉiH\ȉHAE ELo8ȉlHX_ȉHAȉ0H*#yHA$LA$LֿA$hL轿[H H5 LRlH H5 L4NH H5 L0H/ H58 LHQ H5R LڼH5 H= L輼A$A$L}LHi A+   A   1E1E1A/   HHi A   E1E1Hi A/   A   w1E1E1A"  HHi A   PE1E1Hgi A"  A   21E1E1A  HH:i A   E1E1H"i A   LA  E1E1Hh A  LA   LHh E1A  A   E1E1Hh A  A   E1E1Hh Af  LA   E1YE1E1Hph Af  A   ;E1E1E1AW  LHBh A   E1E1H*h AW  A   E1E1E1Aq  LHg A   E1E1Hg Aq  A   E11Hg Aq  A   E1LE11H_ A   A   kE1LE11H_ A   A   D1HE1LHIg A*   A   L1HHH H      L HIċxȉuȻMID$   t8MtnIvLLHZkA$   H?E1HR H5z H8ӼA$0A$$LCH薻IH1H9sIt IVH4wHA$mL`A=vA=[AQAHUdH+%(   tHe[A\A]A^A_]UHGH   uHb HH5} H81(1Ht&H;W t H8 HH5} H81]UHAVIAUIATISH  ɷÅuULH5\ Lܶt:H5I LE1LL1λHHt xȉuŹ[A\A]A^]HHP   uH   HuAUHAUATSHQHP  HtwH   Hq   H9~bHD    uHPH* H5+ H81kHu,H    t"HHHSH5) H H81踸:HHH      A薻H   AEt޹AZD[A\A]]UH5 HATS4HHtM1HºIHu uHuH9 H52 H8ڹxȉtL
HQH[A\]UHATSHUHdH%(   H]HH5m HLeMu	ʸ1H޺   LfÅxLh  HEdH+%(   tZY[A\]UHAWIHAVEAUIATISAQĴHH   H@   u Hd LLH5_ H81qLK(HC Mt   I9LLIM9s#HS MLLH5C H81ٶ-Au2I9s-RL1MPMH 11蠺Y^y
H1p  HeH[A\A]A^A_]UHAVIAUIATS1"IHtH5C E1LHLHL  H[A\A]A^]UHSHH   HHHPHXL`Lht#)p)M)U)])e)m)u)}dH<%(   H8Hvǅ    ǅ$0   HHEH(H@H0HtGLVI   H}1/w
уLHHLAwAMHH9uH8dH+%(   töH   H[]UHAWIAVAUATSHHv IH   H H8k   HFHu1E1E11RH蝵IHtH5F HIHt'HL1HHtHEPH}H11>  L6  L.  HuH¶ LH5_ H81>IHL[A\A]A^A_]UHAWAVIAUATSH8H}L&.   HU1LdH%(   HE1HUbHtL`L豴HH  H=^ 蹲IH   H腱IH   HUHHzuIcVH}L+         HMH}LL議HEH   LHMHH莲L}H}I9t/Mtbxȉu[IcVLLL}u8AxAuL,L褐  xȉuHH]H}聐  1HEHEdH+%(   t%H8H[A\A]A^A_]UHAWMAVIAUIATMSHH=k uHUH2  uHU1LhH@HÉ   1fHnHp(HxpMtA=wAWLs K@=wA1L{`HK8CP=wAMtA$=wA$1W1LchHCxAEH   %        tVtXH tW=   tGHY
 =  t@Hó H5[ H8x2ȉu,H舱"H 1H	 HS0H61HH[A\A]A^A_]U1HAWIAVIAUIH5[ ATSHdL$%(   LeIHE0HH   HHULմH}Hu+LLH5| HH H81v   L	H}u6茵LIMMLHHn H5| H81-=L裲IHt-xȉuHWH}xȉuB1H趍  H}譍  HUdH+%(   tTH[A\A]A^A_]UHAWIAVAUATISH8HUHHHMЃLELMIՈEHHH AfAHHF  LM1L9}I<ǋwH| HHHLܳHEHuE1E1E1   H}AHIHtCD61E1ƉE &IH   HRIH   M1LMLLIE1H HA  DAMHd 5f AUATuuuPPuPPAW諬H`IHt	1A   L  L  xȉtL
H]HeH[A\A]A^A_]UHAVAUATSHdL,%(   LmI衭H   H5 HUHI2H]Hu贮HEdH+%(         H5] HUHLuMuyL> tȉuH蜭1L  HtxȉuHyA$x!A$uLaJHtHEdH+%(   uAXLAY1[A\A]A^]MfZLY[A\A]A^]HtH)H=W 蚫H=W 莫f.     @ H= H H9tH֮ Ht	        H= H5z H)HH?HHHtH HtfD      =U  u+UH=  HtH=^ 9d- ]     wf.     f.     f.     f.     f.     D  UfH fHnHATSH@dL%(   LUI)E~ HE    fl)EHd  LIHMT  IX  I8  M  HH]LeMLM J4HLASLU _AX  H} LU  M"J|   IItJ|   HEHUH fHnLA fInfl=wA H=K HU1LH      LE)ELEHA xA   H  xo  H =wH;Htx)  HL9u    I  Iu@HV=wHHUȋwHEH]Le    M  H(L A   L|N H HH]HL H5T LeH8AR1NXZH;HtxS  HI9uHT +   H=T ! 1HEdH+%(   z  HeH[A\]ÐHV=wHUH=wHUHwH' HE
w
HUH]Le H"K A   LjR     LHM褨HM
 H =wHUQf.     HI HHJ H57S LM A   HJ H8AR1Y^+fD  HMHMfD  H  HS ,   H=-S HM<  HMq ff.     UHAVAUIATL% SA$=wA$   軥HA$H   H wL5 HK AwALs(=wnPLc0   DA$IExLc8HP=wHS@   LcH+Ht6AHX wALp([A\A]A^]@ Lc0f.     xtCHQ   H=(R  [1A\A]A^]ÅxكA$uL{f     HhfD  UfHx fHnHAWAVAUATSH8  dH%(   H]H)@H   )PfHnH   H-   )`fHn~͖ Hǅp    fl)E~ fl)E~ fl)EfHn)EHt,LIHM~ H  Hr HcH>D  H  Hr HcH>D  HV0=wHpHV(=wHhHV =wH`HV=wHXHV=wHPHV=wHHH=wH@HHUH4IH@L%N H AT _AX   HH ]  HP   HX   H`   Hh u  Hp ?  H H~  fD  HH  H< uHԥ HH9F H5N LH A   LH8S1wY^H LxD  HL9t'H;Htxu荣HL9u@ HN /   H=UO E1 HEdH+%(   <  HeL[A\A]A^A_]Hǅ    HV(H=wHHhHN H=wHH`HNH=wHHXHNH=wHHPHNH(=!  L>AHH=wAL@H   H 	  H 8	  H ]	  H@H H g
  A=wAH(=wL% H=d IT$LǣHH   =wL% H=/ IT$L蒣IH   =wA I@LLH5ڹ H   HR  LIM  A xA 
  L- H= IULIH   =wA I@LLH58 H   H+  LIM  A xA `     LLHI  H fInfHnfl=wIEA   E1LH H. H9C     L]LHE    L}KLHI  HY HP =w   LLHH?L)L H	HELmJ4HxL HMtAxA  AE xAE U
  A$xA$P
  xO
  H 4  AxA>
  H H= HSHIH_   =wAHZ H= L HSHL HI   =wA Hϟ HL H9HL9  H;=ϟ   LL LL L  L  AM=wAHLLL L虡L LL  L  H =wHLH A   1I9A  Hf   LLHEHLEL LH]HE)E臛L LHLI  H LHP =wH L]IV(=w   LLLH?L)LH	HLLJ4LLeqHLLH LLtx8  A xA   AxA  A$xA$'  AxA=  AxA  H H  xU  H5 H(L L L     Hǅ     H5% E1H( 1     HH;Ҝ !  H H= HSHjIHG$   =wAH0 A   E1I9A$  Hf   LHE    HEHLeHEE*LHH   H HP =wHH HEHS(=wHHD HEHS0=wH   LHL)LHELH?H	HJ4MLItA$xA$  x  AxA  M  E1E1LE1E11۾
  e  @ L>A=wAH5V L@H(=  HHHǅ    Hǅ    Hǅ    Hǅ    H5| H=wHHPHH L A=wALXLH L A=wAL`LH L A=wALhLy@ Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    @ Hǅ    Hǅ    Hǅ    Hǅ    g    Hǅ    Hǅ    Hǅ    f.     Hǅ    Hǅ    D  HN0H=wHHpo@ H =wH@HpHH cf.     H(L>HHA=@ HHL@H(HPHHXHH`HHhHHpHHG  H!9 A   Li@ H HH-@ H5A H8S1GH@_AXH HH9  I=|fLH H5Q H=wHHPH =wHH    H) =wHp    L A=wALhhD  L A=wAL`2D  LY A=wALXD  LL9LD  L  L H  L 裕H=t H8LH8H記H$  E1E1E1E1Hǅ     E1      H6 A   L%9     #H= H8L}L8ML!LHC&  1E1E1E1H E1      f軔H= H8LL8ML蹗LHu-H> LH56 H81RLff.     E1E1E1   Hǅ     LHtx  MtA xA   MtA$xA$  MtAxA  MtAxA  H> H=> E1B MtAE xAE    H Htx   Hx   H(xt_H Lx,f     ff.     ff.     HL9H;Htxu)    HfD  L; HH HP Lґ    HLL褑LL1 LLsLLLKLf     Lω"    Lq 蛍LI@ AM=wA=wAMI=HnA      At'Hǅ     E1E1   E11    LLE1E1L>LHǅ     Lf.     Hǅ     E1        HL H5K HGH   H  L IM     11LL  IH  AE L xAE   LLL lL LHI  AxA  H H= L HSHL HI   =wAE Hː I9E  HHuLMH      L HE    HEl L IAxA  MI  Hx  L5) H= LIVLGLHH   =wH H9C  HuHL}IH      LHE    k LIAE xAE U  M  L;M9@
  L; 3
  LL LLL 
  AxA  2
  H H=Ԡ LHSH1LHI   =wAIFLLH5 H   H]  LH H    AxA[  H =wH H1L}H=! LH      H]迉LIŋx!X  xH   M!  L;M9  L;-^   LL葏L  AE xAE   i  A=wAH1L}H      H= LHE    LIAxA  M  A=wAH1L}H      H= LHE    yLH AxA  H    H; H9&  HO H=h HLHSH辌LHHI   =wA$ID$HLLH5 H   H  LHIM`  A$xA$  H5_ H 1LHL輎LHH  Hڋ I9ALH  HuLH      HLHE    H]Lg LLHIƋx  A$xA$  M:!  L;M9D  I9;  LÌÅ  AxA  <  H_ =wH( xH(  H(H5< LE1E1   Hǅ     .@LILL肈L_LLLLYLLLLLL)LLLLL LLLLLׇLLAE1E1   Hǅ     *HL蒇LL[LcA=wAA$=wA$x	  LE1M_	  AT	  LE1M   LE1E1E1Hǅ        H(Hǅ    Hǅ    HHHǅ    Hǅ    FlH== H8HƋL8ML jL HB  E1E1E1Hǅ     L1E1   HLL*LLLLL 轆H= H8HL8L MLL 證L LH>  E1E1: H5 H(   E  L% H= IT$L\HH   =wH# A   E1H9C2  Hf   LMLHEHHE    HEELHIw  H HP =wHH HEIT$(=wHH HEIT$0=wH   LHL)LHELH?H	HJ4LIMtAxA*  A$xA$S  xO    MfAxA\E1   E1E1Hǅ     UIYMi=wAE =wAE AxA  ME1LLH  AL xAuLL'LIGLLH5k H   H  LIM  IGLLH5 H   H   LIM  H5 LLL  L`  L '  H5l LLL ƽ L'  L   H5 LL L荽 LL   AxA    A=wAH1L}H      H= LHE    ~LIAxA  M]  IALLLH5Θ H   H  LLH H    A,A LLL    E1E1E1   L   E1E1E1E11E1Hǅ     ALLL 袀LL LL 耀L FLL eL LE1E11Hǅ        E1H5k H(菻   +  H H= HSHIH   =wA$H A   1I9D$6  HfH]   HE    HEHEHE}IH  H HP =wHHB HEIW(=wHH HEIW0=wH   LLL)HELH?H	HJ4譀IHtx  AxA4  A$xA$,    Mf     HL ~L LL L_~L LAxAZ  IGH5 H   H  LLLH H  E1E1E1E11۾   gfD  MLE1E1Hǅ     E1   EHL}LJHL}LcLr}iL  E1E1E1E11LL?}L;HyL IULE1E1E1Hǅ     E11۾   oHǅ        LE1ME1f.     xtE1i HL|LL||LHLL ML LHL   E1_L |H= H8H@L8L MHI  1LE1E1H E1E11۾   L LfHILH*YH e{HH3  1HL,IH  LHxd  L;M9  I9  LHL~LH}  AxA  HP =wH(xw  H(HLLLLL zL LLH֍ =wH HuHH      HE    HE?X Iċx`	  Mt1LZ A$xA$G  L	  H5 H(C     L% H=G IT$L{HH   =wHq{ A   E1H9C2  HfLe   HE    HEHEHErwIH   H? HP =wHH HEIW(=wHHK HEIW0=wH   LHL)HELH?H	HJ4bzIMtA$xA$  AxA  x  Mv1E1ILE1E1  1LE1E1E1E11E1   Hǅ     I]MufHn=wA=wAAE xAE N  H   LL )EU L IǋH}wL L%xH= H8L|H8LH#{IH     E1E1DwH= H8H,|L8MLzLH  LE1E1E11۾
  =@ MaIYA$=wA$=wAxA  IE15Hӏ H= LHSHIxLHI   =wAIAL LLH5Î H   H  LL IM  AxAN  Hw I9EK  1LHuLHULH      L}S LIŋx  E1E1Mp  IGHPpH  HRH  LLLLIMO  AE xAE Q  H5; L9  IAH;v P  LAAMEHPpH  HRH  LLLLLLH H  N  AxAz  AxA  H LH5 HGH   H  LIM0E1E1E1E11۾   fLsfInLkAfInfl=wAAE =wAE x  H   LL)EQ LIAALL LqsL LLLOsLH(7sXHL#sLLLsL!H HrLLLrLL  RLrHrLEsH= H8HwL8LMICvH  1E1E1E1H 1E1   f        E1E1E1Hǅ     1nLIE1E1E1E1Hǅ     1۾   J\nLIE1E1E11Hǅ        (nLH LL) _qLfo E1E1E11E1   L   E1Hǅ     >E1E1E1E1Hǅ     1۾   zLpLL LpL L0HpLpL&LpLpLxpLkpH^p1E1E1E1H E11۾   L0pLLHLLpHLLHoHLHk =H:q LH5 H81NoHLoLLLooL  E1E1E11۾   kLLH 1E1E1E1H 1۾   L  LKLcA=wAA$=wA$xx  LE1koH=< H8LsH8HCprH  LE1E1E1E1  LHLDnHLLHLnHLHL )mL foH_o LH57 LH81lmLLmHHLmHL LrmWMLIݾ   E1E1E1E1   mH=̀ H8HUrL8M: qHt  LE1E1E11۾  tE1E11۾   bMAfHnMaA fInfl=wA A$=wA$AxA  H   LHLL)EqJ LLIHA A LHLlHL~E1E1E1   E1E1E1E11۾   gyhHLIoHLplH=A H8HpL8LHMgoHA
  E1E1E11۾      E1E1E11LcLsA$=wA$A=wAx  LE1Hg~ =wH= H;=#l S  H(H@   tH;Jl 2  H(mIM  E1HuHLeH      LMH IA$xA$  x  Mt1LCJ AxAp  L  L  jH=} H8L#oH8HSmH  LE1E1E1E1  ALi&   g  E1HI\$Mt$=wA=wAA$xA$  ME1HL4iLmHj HH5 L H81hL E11E1E11H    eweL LILL LhL LLLiH=| H8HmL8LM8LClLHS  1E1E1E1H 1E1   E1E1E11۾   MIA LLLgLL]1LH    HPhH  Hz   LLL褮 LIU   E1E1E11MufInI]AfInfl=wA=wAE xAE \  H   HL)EE LIAlA`LfLLHPhH  Hz   LLLL貭 LLH LLyfLgHg HH5 H81eLL H2fYLLbLH LLeLHqg HH5I LH81~eLHCg LH5 H81WeH#g HH5 H817eH(hIHfeXHf HH5 H81dL9eH aLI     H5{ H8LLjH8H   E1HuHLmH      LuB LIzoHL LdLL FHe LH5 E1E1H81d1E1E1H    He HH5 LH81cL>dIGHPHe H5 H81cE1۾   E1LL LL )cL fozH;e 6  LϺ   L L)hLL HIUL E1E11E1E1   L E1E11E1E1ɾ         H5y LH8LL  hH8LL H   LHuE1HH      LLULu@ LLH HqbLLffA.Az	MhL\bLIAHPHd E11H5 LE1H81aL   E1L E1m  >LajHanLaH4c LH5 H81HaHc HH5 H81(alLHLL)OaHLfoLHb HH5 H81`fff.     UH(t fHnflHAWAVAUATSHH  HZH;=b dL$%(   LeIHǅ    Hǅ    HǅX    HǅP    w
  HHMH)HP  foH0f  L;%a HZ
  HP HMLHX HU/  H5s H@ L0{  HHH5w HHGH   Ho  IM  AFHHbIH|  H5` HHaHH  AxA
  Hz HLH aHAE   xAE 	  x	  Hvz d  E  A   HA   LK   I)H    I8HA(f     ff.     AHHE9s"
f/rA	HHE9rރLA9uAt$I|$   H  LAF+ E1MTL     L1E1fD  AHHE9tXf.ztI ff.     HH)BXf/v HH9uAHHE9uHIL9yMt#E1Hd H98
  H\HX   Hd H9E	  HX\M  fff.     HEdH+%(     HH  [A\A]A^A_]AE xAE 
  Mt!AxAuL\f.     E1YHHXpIH@p    H  LsA=wALc(MtA$=wA$H  Hc H98  H[HX tHc H9E  HX[Ht
L9c(  I}pI]pHtx  MtAxA  MtA$xA$  H=  MA{AoL[bAt$I|$   H  n t  A$=wA$Hv 1LeH      H=Ks HEHEHHXIA$xA$"  M3AE xAE ,  L-gt H=n IUL\IH   =wAIGH5u LH   H0  IHAxA  Hs H=n HQHHi\IH0   =wAIGH5s LH   H  HHAxAuLHZHH[ H9A  HuHfH      H)E7 LIA xA uLYM  Ln\IAMM  xAM  HP[ I9ET  HuLLEH      LHE    E7 LLIA xA   x  M111L HHLLHZH  x'  ID$H5p LH   Hj  HHHH[HHI  H5Y HHYHHIW  AE xAE   Hcs HLHYH  x|  A$xA$t  HE   LXA~H1H% HDLLMfff.     LE1E1AIME9tzAf.ztH1O,"f     ff.     AHXFA@f/vAA@AT H9uAHIME9HHMH9THLHHX <f.     Hǅ8    #D  AE   E1E1E1HUVMtAE xAE $  MUA$IA$<LV/H5] L;%FW Hǅ     H8H(fH] EHh HEXE1E1H&HX H\ H9E  HXE1E1TFHE    LHUUHLAUH
H#UULULTLTLHTHWLTLT.HX W  H[ H9E  HXSSLHRMDH9HxH=tg 1]4 xHPIE1UxAuLTAE 2AE %LSEH =HX HZ H9E  HX&SqAE AE LSHǅ8    HE    HeSwLXSI]p=HBS9LH.SHLLSLID$ DH9H;Pq|SH=sf HLWLMVHH/T LH5 H81CRfD  HROIHdAt$I|$   HXNHL2R'RHH=e H>WLHMHUH  AE LILAA=wAA =wA x  HHLLM   LLHEw/ LLIAAL7QLuL#QHLQMMfInIMAfInfl=wA=wAE xAE >  HHϺ   LLH)E. LHILAIA=LLVPLH\QE1LH4)E1E1E1{iHE     HLLOLLHE    LLHL)_OLfoHL|1HEpHP HH5 H81N,IPf     UfHf fHnHAWAVAUATSH  dH%(   H]H)`HP  H  )pfHn~? HE    fl)E~? fl)EfHn)EHt*LIHM~HA  H HcH> H#  H HcH>D  HV =wHUHV=wHxHV=wHpHV=wHhH=wH`HHUH4IH`L% H@AT A[A]   Hh   Hp   Hx 5  H}   H@H~  HH  H< uHN HLL A   HI H5 H8S1LAYAZH@LeH;HtxtSHI9uH "  H= E1 HEdH+%(   W'  HeL[A\A]A^A_]f.     kLf     Hǅ    1Hǅ     HNH=
  L6AHh=wAL`H 	  H  /	  H`H@H'
  L%f H=Y_ IT$LMIHp   =wAL%` H=#_ IT$LMIH   =wAH|L L-MM H9H0L9	  H;L   HLHNLH    H0=wL0HL    1I9G  Hf   LMLHH H]LuHE)EHLHHH  Ha H HP =wHRa LmHQ(=wH   LLeH)H?LH	HEHH4H KHHLHHtxn  AxA  A$xA$  x  AxA  HH 4  L%Ub H=] IT$LyKHH=   =wH@K H9C  HuHLuH      HE    I9' IAxAC	  MJ  L;0M92  L;%3J %  LmLÅ  A$xA$n      yHIH7  H5c HHH9  HAH;{J   H0AIDHHLHJ  xY  A$xA$Q  H H;0L9  H;5HI   H ~K4  >  HGa H=`[ HSHIIHq   =wAIGH5^` LH   HS  IMR  AxA  HKI I9AA  HHHuLH      HE    HEL 9% H IċxF  M   LIIHQ  A$xA$uLFH	b HHLrH  AxAuLF HH;0@L9@ 	H;=G ʈuI  L5_ H=Y IVLy  4HHH:   =wHCH5] HH   H  IM6  xuHEHHH5;` HGH   H5  HH  L5"[ H=+Y IVLGIHZ   =wAHUG I9D$r  f   H]LHE    )EmCLHIm!     E1H      H\ IH wH^ LMH=4Z IH(wH H}LHLHLLLhFLLLIMtAxAh  x  AxA{  A xA   A$xA$  M  1A  E1     Htx  MtA xA   H DH=I , HHHtx  M  HǅH      fD  Hǅ     1HNH=wHHp    L6A=wAH5ND L`H0=  HhH01Hǅ     HL-D AE =wAE LpLH  L-D AE =wAE LxL  1HNH =wH HxfH^ =wH]     &AE =wAE M(H"  Hd A   L HC HH5 Hh H8S1AH`Y^H@D       L-C AE =wAE H`LmLH@D  HL6HhA=BC@ HhL`H]HHpHHxH ?fD  "     LH@H
D  LH@HD  H@ L@ L-B AE =wAE Lp  H5A H0=wH0Hhf     L-)B AE =wAE LmfD  L-B AE =wAE Lx H9 A   L     L? AIHX   =wAIGH5}W LH   H  IM  AxAuLLV?LL%T H=R LIT$L-ALHH   =wH@ A   E1I9AR     LfInS HE    )E<LHI^  HoV HP =wL   LLL)H?LH	H H]J4*@MLItAxA  x7
  A$xA$=
  AxAE
  MW  HHH;@? r  L;H[  HH? H9F}  H!=HHN  H Ãh  H xH  HHHXL\ǅX   UL=V H=P IWL;?HH   =wHCH5S HH   H+  IM  xq  HH=wHHH 1H      H=&T HE    H]9Ix	  M_  H5W 1LLALHI4  AxA  H#> I9G  HuLLELH      LHE     LIA xA   x  M*  L;0M9  L;%<   L1?Å'  A$xA$=	  '   uH> (  D E     m9IH.  HH=wHHID$ A=wAHHMt$( xHH0  LH AxA  LHH@LeH;Htx  HI9u@ HHLj:HLi    LH: :H=M HXLU?LXMt >H  E11E1A~  HǅH     ff.     E1MA$A$LL09L0[:H=,M HXL>LXM
LHY=LHH  E1E11A~  HǅH    E1fff.     AxA  M7A,A LL08L0H8L8H8LL 8L 6MyMaA=wAA$=wA$AxAm  ME1fA  fx   M   1E1E18H=K HXL>=LXML0;L0H  E1E1MA  fD  7,fD  L7 HL07ML0S1E1E1h@ LL L0b7L0L 2    HL097L03D  L 79 H7\ E1A  E11HǅH    f.     H+  HǅH    A~  qI_IW=w=wAxA  I1    H0HhVD  A~  E1pf=f     6H=I HXLE;HXH9HtE1E1A  
Hk7 LH5C H815@ ff.     E1A  1E1D  L{fInLsAfInfl=wAA=wAx  H    L)EY IAA	L'5E1A  E11E1E1A$x	A$tE1MM LL L04L0L E1A  1E1H0-H4E1A  1E1Hk4E11A  vHN4rLL:4LL&49A  AxA  LHL3LLL3LL3HH=PILL HH~3HHL E1A  E1E1E1FLL34H=F HXH\8LXMs7H	  E11E1A   HHL2LPLL2LjL2pHLL2LL!H;4   HH   7IHHE1E11E1A  7L=2.IE1E11A  MqIYAfInH=wA=wAxA  H    H)E IAAL1uL1L8L%aE M  HHHpI9tDHX  H	  HJH
  1@ ff.     HH9	  L;d uL;5]2 *IvL9HX  H  HJH~1    L9d HH9uH2 IL$A  1HVH5 E1H81P0 H)0fo71H=D HPL5HPH0<4IH  E1A  R4HLA  10LL0LLv0H=zC HXL5HXH3IH  E1E1A  E1E11E1A  |L%kC MkH1 H5 1A  H80w0H=B HXLl4LXM3IH\  E11E1A  (     +IE1A  +I[s+IME1A  1E1A  HH.E1E1E1MA  BHH+HL"/H=A HXL|3HXLH)L02L0H5
  AxAr  E1A       MT$fHnM|$AfInfl=wAA=wAA$xA$  fɿ   )ELL)M+LLHII	  E1MA  FIwfInI_fHnHfl=w=wAxAW  H    HL)E
 HLIċH,LA  J1A  HHff.@zH0L
A  11E1A  sHB H=? HSH9.IH   =wAHE H=? HSH.IH   =wA$ID$H5F LH   H  IM  A$xA$  HH=wHHH 1H      H=B L0HE    H](L0Iċxe  1E1A  MH5RF 1LL0/L0HH  A$xA$z  H, I9@  1HuLH]H      HEL0 L0Ix  A$xA$  E11A  M-11LϹ   L0eo L0HI%  AxA  H=? H;=i+   I@   tH;+   LL0R,L0IM  A xA |  H+ I9G  1HuLLMHUMH      L0 L0HAxA  A$xA$  Ht1HP	 x  A  1E1OA  1E1?L) )fo 01A  L(LLL)(foLLLL)(LfoH* H5 1A  H8)H) LH5 H81'=H) LH5 H81'LHHH   L9%HuL;%) 'LL0'L02HH'L0LL0'L0$LL0'L0[HL0{'L0Lg'L0rHH   I9,HuL;%) H) IL$A  1HVH5o E1H81&%H( HH5^ H81&E1A  1E1MhfHnM`AE fInfl=wAE A$=wA$A xA )  H    L)E IAE AE LL0G&L0LL0\)L0I51A  E1A  "I11E1A  &H=q9 HPH*LPM)Hg  E11E1A  YT&H=%9 HPH*LPMMMV)H   1A  pLL0A%L0ip&H(%MofInMgAE fInfl=wAE A$=wA$AxA   H    LL0)E L0HAE AE L$L0Lx$Lk$H% HH5 H81#LL0) 0$fo L0FM1   H% LE1H5c A  H81#He% LH5= H81y#L0E1MA  lA1E1E1HHA~  csH% LH5 A  H81#L)0R#fo0H$ HH5 H81"yLL0#H0E1H0LME1Hx$ H5S L A  H81"L0L H@$ LH5 E11A  H81I"E1E1E1A  Htxt
f     ["ff.     UHAWAVAUATSH   H$ H  HH   HH0HPLL dH%(   HE1HxHHP   HpHH    HhHH   H`HH   HXHH   HPHH`   HHHH0   H@HH    HHH   HHH   H8HHp   H0HH@   H(HH   H HH   HHH   HHH   HHHP   HHH    HHH   HH=wHP=wL%	; H=3 IT$L"IH   =wAL-C5 H=l3 IUL!IH   =wA$H!    E1I9Fs  H0   H`Hǅp    LPHXH`LhIH9  H6 H`HP =wH!    LH)HpHH?H	HPH4LH H@MtAxA|  A$xA$7  AE xAE   AxA  H@ i  x   H7 H=1 HSH^ IHR/   =wAE IEH54 LH   H0  IM&0  AE xAE   H@H5[5 HGH   H  IM0  H58 1Lp"HHH:  AE xAE S  H| I9D$A<  HHHXLLH      HǅP    HXd IHHx  x  M;  L;0 HY L;   I9  LL`t L`A*<  AxA  E  L%7 H=80 IT$LIHD   =wAIGH5m7 LH   HJG  HHHH F  AxA`<  HHH5 H9pG  LHH1 HXH      HǅP    LHX H`A$xA$;  H` -H  H`x;  H@H56 HGH   H;  IM;  11L׹   L`m` L`HHH<  AxA3-  L-4 H=. IULH9Pq  IH(D   =wAIFH5f1 LH   HF  IME  AxA:  L-+0 H=4. IULIHG   =wAH^    E1I9D$H  HPf   H`Hǅp    LPHX)`WIH4<  H3 H5U/ H`HP =wH1 H`IU(=wH0 LhIU0=wH    LH)HpHH?H	HH4L>HMtAxA4  AxA:  AE xAE o:  A$xA$J:  H $;  HPx4  u,     H`HX5  HH=wH`HHHH ,   L L L Hp L`Z LPw Dm    H@IJ@ E1E1E1ǅ`  E1E1E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    H@H ff.     MtAxA(  MtAxA@  MtA$xA$V  MtAE xAE l  MtA xA   MtAxA  HHt#H9tP8Hǅ      Hǅ    HPHt#H9tP8HǅX      HǅP    H Ht#H9tP8Hǅ(      Hǅ     HHt#H9tP8Hǅ      Hǅ    HHt#H9tP8Hǅ      Hǅ    HHt#H9tP8Hǅ      Hǅ    H`Ht#H9tP8Hǅh      Hǅ`    H0Ht#H9tP8Hǅ8      Hǅ0    H Ht#H9tP8Hǅ      Hǅ     HHt#H9tP8Hǅ      Hǅ    HHt#H9tP8Hǅ      Hǅ    HpHt#H9tP8Hǅx      Hǅp    H@Ht#H9tP8HǅH      Hǅ@    HHt#H9tP8Hǅ    "  Hǅ    HHt#H9tP8Hǅ    "  Hǅ    HHt#H9tP8Hǅ    "  Hǅ    HHt#H9tP8Hǅ    "  Hǅ    HPHt#H9tP8HǅX    "  HǅP    H Ht#H9tP8Hǅ(    "  Hǅ     HH9t#HtP8Hǅ    "  Hǅ    HG H=( { HHHtx  H` t"E1H`x  L`H8 tH8x  HHtx{  HHtxn  HHtxa  HHtxT  HHtxG  HHtx:  H Htx-  HHtx   H0Htx  H Htxn  HHtxa  H@xY  HPxQ  HEdH+%(   Rz  H`He[A\A]A^A_]     LLLLL    LLLLL    LLLLL    LLLjLLk    LLALaD  L(g H H H H H=wH8L8H`1H      H=( HLPHXLIM˶  HH  H`p  e  @ H`4V    H k Hx H  H H H H H H H HL`yL`4D  HL`YL`%D  L@ H=  HHLMLHM#Hd  H@E1E1E1Hǅ    E1H" Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅ`  @ H= HHLMLHMYHd  H@E1E1E1Hǅ    H% Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅ`      L0l M~MnA=wAAE =wAE AxA&  M1F';  HHHHǅ    3(
;  HPHBHǅP    -"e
:  H H<Hǅ     '%
:  HH6Hǅ    !	:  HH0Hǅ    	:  HH*Hǅ    
e	 :  H`H$Hǅ`    %	:  H0HHǅ0    	o:  H HHǅ     :  HHHǅ    e:  HHHǅ    %*:  HpHHǅp    :  H@H Hǅ@    	IH:   =wA$ID$H5 LH   H\>  IM=  A$xA$uL9L- H= IUL	IHR>   =wA$H A   E1I9G"#  HH   LPL`Hǅ`    HXL`HI!  H^ HP =w   LLLH?L)L`H	HL`J4L`HMtAxAp6  A$xA$4  AE xAE 4  AxA4  H "!  x4  D]E(     H`HBV  HH=wH`HHHH HHPH H5r H9p(  H 4f. zC  ff/C  L% EH= IT$L(  IHX   =wAE IEH5 LH   H[  IM*[  AE xAE E  L% H=! L8IT$L}L8HI]   =wAE IEL8LH5 H   H_  L8IM(_  AE xAE pG  L%d H= L8IT$LL8HIV`   =wAE H    E1I9@Wb  HH   L8H Hǅh    LPHXL`L8HIT  H H HP =wHȺ   LL H)H?LhH	HH4LML H8tA$xA$Z  AxAPR  AE xAE VR  AxA R  A xA R  H8HS  H HPHe  HH;k H;9 >:  H95:  Hb  L% H= IT$L:  M$L  IHu   =wAIAL LH5 H   HQ|  L IM{  AxA|h  L% H= IT$LpHHH}   =wH0 A   E1I9ED}  HH   LPL Hǅ`    HX4L HIj  H HP =wH   LLL)L H`LH?H	HJ4[L HMtAxAv  Hxi  A$xA$i  AE xAE i  HHi  =wLH1H      H= fIn0 )P,IAxAv  M(  AxAv  L- H=, IULIH   =wA$ID$H5P LH   Ho  IMȄ  A$xA$ku  H= L o L HH/  H  E1A   I9A%  1   L H`HHLPHXL HI  He HP =wL   LLL)H?LL H	HL`J4 LIAL xA~  AxA~  AxA}  M  A$=wA$H= 1HH      fIn )PLI3Ms  AE xAE c}  LHH; H;f |[  H9s[  H n  _  H=  IHk  H@L LH5 H   H2  L IM  AxAy  H5B H@ IH?  H5+ HH  L HH~  AxA{  H5c    E1I9t$G  H   LLH)H?LPH	HLXH4> LIAxA ~  A$xA$~  LM0  L% H=m IT$LIH2}   =wAL%. H=7 L IT$LL HHH:|   =wHL A   E1I9Bƍ  H@   L Hǅh    HXHLPH`BL HIq  H@ H HP =w   LHhLH?L)LL H	HJ4iML ItA$xA$v  Hxhq  AE xAE vp  AxA[q  Mp  IGL%Y L9tH;U ތ  IH˃  L9  Iw H=wIO(H=wAxAwz  H0Ǌ у  c  H=  IH4  H5r H IHҨ  AxA  H= L0 E1L0HI  H A   I9B  1   fInL L02 H`)PL0L HIĊ  H HP =w   LLLH?L)L0H	HL L`J4?H HAL0xA  A$xA$  AxA  H   H= ` IH  H5 H IH  A$xA$  H=M  IH  H A   E1I9Fp  1   fInL0 H`)PL0HI  H HP =w   LLLH?L)L`H	HL0J4LH L0AxA  A$xA$  AxA  H  O  }   HPHpy Hx4   HpH ƛ  HHpQz Hp4   HpHP V  HHp{y Hh4   HpH  j  HHpEy H`4   HpH   HHpy HX4   HpH đ  L HpLx HP4   HpH R  LHpx HH4   HpH` Y  H8Hpy H@4   HpH0   HHpz H4   HpH  q  HHpy H4   HpH D  H   H4   HH   H4   H@8h@p0L(L`HXHHHX# H   *  Hx+*   Hpf-*  )ۂ Hhf/*  )P迂 H`f1*  ) 裂 HXf3*  )臂 HPf5*  )k HHf7*  )O H@f9*  )`3 Hf;*  )0 Hf=*  )  f)1HH H0HH膃 T  H8} ;  =wL8H`1H      H=( HLPHX^LIMŘ  H=wLH`1H      HH= LPHXLHLM8  H=wLH`1H      HH=N LLPHXLIML     L8LHI  HHLx LP(Lp0xH#  HHHǅ    $  HHHǅ    E:$  HHHǅ    u$  HHHǅ    $  HPHHǅP    $  H HHǅ     E"$  HHHǅ    H= HHHLHMHHHaP  Hǅ    E1H E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅb      L Hǅ    E1H# E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅb  f.     I Hǅ    E1HS E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅb  Jf.     HH5 HGH   Hl	  IM(     VIH<)  HH=wHHLLID$ nH`H+  AE xAE   A$xA$  L% H=6 IT$LIH
   =wAIGH5 LH   H>  H8H8   AxAN  H8H5 H9p   L8HHXH      HǅP    LHX IAE xAE   M  A$=wA$H1H= H      fIn )PHPA$xA$D  xA$  HP ]  Hx=  LPH5O 1LIH"  IWLHBpH  H@H  L8LL8IM<(  HHLL8L8HIt'  AE xAE |  HPLLL8"L8)  A$xA$  AxA  L% H= IT$L IHO*   =wAE IEH5i LH   H+  IM*  AE xAE   H5 HP1L WL HH8*,  Hq I9@,  H8HXLH      HǅP    HXL V L IH8x-  A$xA$3  M,  L; L; Z  I9Q  LL8bL8A)  AxAT   E  L% H=& IT$LIHA   =wAE IEH5 LH   H8E  IMD  AE xAE *  HHHP   H8HE  H I9D$E  H8HXLMH      HǅP    HX IH8x5  AxA5  MF  L; L;e #  I9z#  LL8L8A=(  AxA8  EL% A$=wA$Hl HXLH      HǅP    HX IA$xA$=  M~(  1L AE h(  AE S(  ǅz  E1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    fD  H L LdE1E1E1ǅl  E1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    D  MAALLLLLwMWMoA=wAAE =wAE AxAA  ME1HE1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HPǅt  HfIfD  Hǅ    E1H E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅb  D  Hǅ    E1H; E1Hǅ     E1E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅb  ,@ Ml$I\$AE fInH=wAE =wA$xA$  H   H)P IAE AE uLL`L`Z ǅb  E1E1E1Hǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    D  L L L	 H H@<I@ Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅg   L L L_ Hǅ    E1E1E1Hǅ     E1E1E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅg       E1E1E1ǅr  E1E1E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HH5 HGH   H-  IM,     6IH/  HH=wHHLLIG OH`H2  AxA  Ax"HAHPLHHPXfD  SIH/   =wAIGH5e LH   H3  IM(3  AxA  HPH4  HKIH7     IH
8  HHLx =wHHL% H= IF(IT$LzIH:   =wAIGH5 LH   H9>  IM8>  AxA*  Hy H= HQHH8IH>   =wAH E1   I9E?     LPL8H Hǅh    LXL`L8HH2  H9 H HP =wH   LL H)H?H H	HLhH4L H H8MtA xA X6  AxA.  A$xA$.  AxA.  x.  AE xAE .  H8 1  L% H= IT$LoIH=   =wAIAL LH5 H   H>  L IMI>  AxAz5  HPH<  HYHHW?  H I9G?  HHXLMH      HǅP    HX裶 IHx9  A$xA$9  M|@     L yL HI?  HPLP =wHPH? LH8IG(;  AA|LoH=\ HHLLHM%HHHL  Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HǅH    ǅc  黿 H=d HHLLHMH`HG  Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅr  ξfD  L L Hǅ    E1E1E1Hǅ     E1E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅc  ˽ HH鮸    Hǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅr  !f     Iu L8 LhL`AE =wAE A$=wA$HHx  H   LfInI )Pձ H`AE ҷAE ŷL鸷     Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HǅH    ǅc  ƻfD  H=l HHLLHM8H`HQ  Hǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅr  ٺf     H M|$Ml$A=wAAE =wAE A$xA$  M12D  D    Lxm Lhp LX8 HHo L)`1fo`'@ LA$LL8pHBhH	&  Hx %  HPLL8 L8ILLLL8BLH>H= HHLLHMCH8HT  HE1E1E1LE1E1L L0LL LLLLLLL8HPǅw  飸 LHEdH+%(   9  rH=v| ,  1] HEdH+%(   9  rH=M| ,  1q] HEdH+%(   r9  rH=$| ,  1H] HEdH+%(   I9  rH={ ,  1] HEdH+%(    9  rH={ ,  1\ HEdH+%(   8  rH={ ,  1\ HEdH+%(   8  rH={ ,  1\ HEdH+%(   8  rH=W{ ,  1{\ HEdH+%(   |8  rH=.{ ,  1R\ HEdH+%(   S8  rH={ ,  1)\ HEdH+%(   *8  rH=z ,  1 \ HEdH+%(   8  rH=z ,  1[ HE1E1E1Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    HPǅw  ҵH8HEdH+%(   "7  rH=y ,  1Z HEdH+%(   6  rH=y ,  1Z zH=K HHLLHMH`HS  1E1E1E1HH H0HH HHHHHHH8H`ǅl  f.     HEdH+%(   6  rH=x ,  1Y HEdH+%(   5  rH=x ,  1Y HEdH+%(   5  rH=qx ,  1Y HEdH+%(   5  rH=Hx ,  1lY HEdH+%(   m5  rH=x ,  1CY LL8$L8UHEdH+%(   )5  rH=w ,  1X     HE1E1E1ǅw  E1HPHǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    LpLhAfIn=wAAE =wAE H8x%$  H   L)P IAALHǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅl  IHL L LL8L8|H=M HHLLHMH`HP  1E1E1E1HE1H H0HH HHHHHHH8H`ǅl  鹰f     Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅx  9LQM  <IH99   =wAIAL LH5 H   HH  L IME  AxA-  L%M H=V IT$LHHH1D   =wHy A   E1I9FC     fInL  Hǅ`    )PL HI.  H HP =wH   LLL)L H`LH?H	HJ4L HMtAxA7  Hx.  A$xA$.  AxA.  H -  L% H= IT$LWIHfE   =wAE IEH5 LH   H`  IMY  AE xAE 7  L%s H=| L IT$LL HHHX   =wH A   E1I9AX     L fIn Hǅ`    )PL HInH  H HP =wL   LLL)H?LL H	HL`J4LIsAL xA{B  A$xA$~B  AxAB  M'H  LHE1E1E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HPǅv  ǫDHE1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HPǅv  E1E1Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅx  }E1E1E1YjH#+  L% A$=wA$HI HXLH      HǅP    HX6 IA$xA$$  M  1L AE   AE   ǅ~  E1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    #HE1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HPǅv  |ǅx  E1E1E1Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    LL4LL8ѾL8&耿H=Q HHLLHMH8H{J  E1E1E1E1LL L0LL LLLLLLL8ǅy  fD  HE1E1E1E1ǅy  _Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅy  /IaL:ǅz  E1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    {LL8茼L8uLxLk:Hǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    ǅy  鵤MhM`AE fIn8=wAE A$=wA$A xA 4!  H   L)P IAE $AE LL DL Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅy  y蔼IH0   =wAIBL LH5L H   H7  L IM)6  AxA7!  HPH5  H~H!5     H $L HI4  H
 LP =wL%A IV(H=F IT$L詻HHH2   =wHi E1A   I9EJ     LPL Hǅ`    LXtL HI,  H HP =wH   LLL)L H`LH?H	HJ4蛺L HMtAxA1  AxA+  Hx+  A$xA$+  AE xAE +  H $+  H= 薕 IHM  H5 HK IHsM  A$xA$)2  HPL 跺L H~N  HNL HIRN     L HI'N  H L` =wIV(H=
 L Δ L HIM  HL E1   I9B:  E1   L H L`LPLXRL HI:  H H HP =wHȺ   LL H)H?L`H	HH4LyLH*AL xA{:  AxA|:  A$xA$H  AxAH  H E1E1E1LME1E1ǅ  1E1HH H0HH HHHHHϷIH)   =wAIBL LH5 H   H,  L IM..  AxAe  HPH-  H蹱H.     H _L HI,  HHLP =wHHL5u H=~ IE(IVL޶HHH,   =wH E1A   I9D$	F     LPL Hǅ`    LX訲L HI)  H HP =wH   LLL)L H`LH?H	HJ4ϵL HMtAxA +  AE xAE (  Hx(  AxA(  A$xA$(  HH(  =wLH1H      H=U fIn )P荰IAxA'-  MXN  AxA,  H=t O IHC  H5 H IHG  AxA,  HPL rL HtG  H	L HI>     謰L HI=  H Lp =wIU(H= L 艏 L HID=  H    E1I9B<  1   L H H`LPLXL HIk=  H H HP =wHȺ   LL H)H?L`H	HH4L5LHAE L xAE <  AxA<  AxA<  AxA48  H uE1E1E1ǅ  LE1E1fD  LL8ɰL8.HL 记L  LL 蓰L LLL kL 镭LL PL 鏭L<HE1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HPǅp  _HIRHE1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HPǅn  鞗E1E1E1E1ǅ  E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    LLǅ~  E1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HHE1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    HPǅp  xkH=< HHLűLHMMpH[  E1E1E1E1LE1L L0LL LLLLLLL8ǅ  D  軬H= HHLLHMH8HT  1E1E1E1HH H0HH HHHHHHH8ǅ  2fLH AH OLH &H ILH H AHELM     H5 HPHHL8LHL8Mf  HXLH      LXL8HǅP    ~ L8IA$A$yLCL8eHE1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HPǅp  :Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅ  ё茥I'E1E1E1E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅ  I#H LH5J H81ͧLJLL E1E1E1E1E1ǅ  E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    HӨ LH5I H813ǅ  E1E1E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    vL8JH= HHL褫LHL8ML0AL0HH8T  1E1E1ǅ  HH H0HH HHHHHHH8鯎    H)P蹥foPgH=8 HHLLHMlH8HE  E1E1E1E1LL L0LL LLLLLLL8ǅy  ݍD  Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅ  ?L8I"Hǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅ  鏌E1E1E1L虣H L腣yL84H= HHL莨LHL8ML0+L0HH8N  1E1E1ǅ  HH H0HH HHHHHHH8運f     Hǅ    E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅy  貞ILL`L`e除Hǅ    E1E1E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    ǅy  6M`MxA$=wA$A=wAA xA   M1bMl$Mt$AE fIn8=wAE A=wAA$xA$  H   L)P~ IAE ޹AE ѹLL |L 鶹+H= HHL腥LHM0HI  E1E1E1ǅ  E1LL L0LL LLLLLLL8鐈Hǅ    E1E1E1Hǅ     E1Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    ǅy  	ǅ  E1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    uLL 膞L HL kL H HH5@ E1H81H E1E1Hǅ    Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ8    Hǅ`    ǅb  vH@H5 HGH   H)  HH r1E1E1E1HE1H H0HH HHHǅ  裙IE1E1L螝H8H=h HHLHM蟠HK  E1E1m1E1E1E1ǅ  E1HH H0HH HHHHHH1E1E1E1ǅ  E1E1HH H0HH HHHHHHtMEIUA =wA =wAE xAE   I1:H= HHL蔠LHM L08L0H;H  1E1E1E1HH H0HH HHHHHHǅ  鱃1E1E1E1HH H0HH HHHHHHǅ  JL I3L) Gfo HPL8HPH E1E1E1HRH5E LE1H81褙1E1E1HLǅx  H H0HH HHHHHHH8r1E1E1E1HE1E1H H0HH HHHHHǅ  ́L;LwLLMoMgAE fIn=wAE A$=wA$AxAV!  H   L)Pv IAE AE ֿLL WL 黿1E1E1E1HE1E1H H0HH HHHHHHǅ  γ1E1E1E1HE1H H0HH HHHHHHǅ  T1E1E1Hǅ  LE1E1E1Hǅ    E1Hǅ     Hǅ0    Hǅ    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    麲HL赖L訖#L蛖cH莖,L聖41E1E1HLE1E1E1ǅ  E1E1E1E1ǅ|  E1LL L0LL LLLLLLL8~H5 H@r IHD   =wAE HH=r 11H      HXLPɒLHrAE xAE   H qB  H=` r IH\?  H= sr E1IH?  H A   I9FgB  1   LPHhHL L`L0HXL0L HI&  H H HP =wL   LHhL)H?LL0H	HL J4	H IqL0AxA  AE xAE   AxA*  Mf  IGL9tH; K1  IH2  L9p3  Iw H0=wIO(H =wAxAy3  H$ 0  
*  H=wHHHPHp}   s Hx4   HpH |>  HHp Hp4   HpHP >  HHp Hh4   HpH  <>  HHp H`4   HpH 2>  HHp; HX4   HpH >  H0Hpe HP4   HpH I>  H Hp/ HH4   HpH` ?>  H8Hp9 H@4   HpH0 =  HHp H4   HpH P=  HHpm H4   HpH  E=  H   H4   HH   H4   H@8h@p0L(L`HXHHH  H   :  Hx+   Hpf+  )f Hhf+  )PJ H`f+  ) . HXf+  ) HPf+  ) HHf+  ) H@f+  )` Hf+  )0 Hf+  ) f) 1H H锜H LH5o1 E1E1H81襎E1E1E1LL L0LL LLLLLLL8ǅr  iw1E1E1E1ǅ  E1HH H0HH HHHHwL%`L) fo BL貎H= HHLLHML0谑L0H2  1E1E1E1HH H0HH HHHHHHǅ  )vLL :L 4E1E1E1E1Lǅ  LE1LSH^LfLӌn艍H=Z HHLLHMˊL0臐L0H<  1E1E1E1HH H0HH HHHHHHǅ   uیH= HHL5LHMAH;  E1E1E1E1LE1L L0LL LLLLLLǅ  \tH LH5- E1E1H811E1E1HH H0HH HHHHHHH8H`ǅc  sLHԊLǊL躊!E1E1E1E1Lǅ  LE1E1;AH= HHL蛏LHMFH+  E1E1E1E1LE1L L0LL LLLLLLǅ  rLL ӉL oLL 踉L zHL 虉L ǉL腉։Lx1E1E1HMLE1E1ǅ  E11E1HH H0HH HHHHL L }L阎xL IFLwH=H HHLэHHHHuH/3  E1E1E1ǅ  LL L0LL LLLLLpE1E11E1E1ǅ  HH H0HH HHHHHH餣E1E1E1E1ǅ  LL L0LL LLLLLL,pE1E1E1&E1E1E1E1LL L0LL LLLLLLǅ  oLΆ脇H=U HHLދHHHH肊H*  E1E1E1E1LL L0LL LLLLLǅ  nL LL L ;HL L LL ҅L 1E1E1ǅ  HH H0HH HHHHHHBnL I駃E1E1E1ǅ  1E1HH H0HH HHHHHHԠ1E1E1E1HH H0HH HHHHHHǅ  ]m1E1E1E1ǅ  HH H0HH HHHHHHlE1E1E1E1LL lMUMeA=wAA$=wA$AE xAE 72  ME1rbH=3 HHL輈HHHH&`H(  1E1E1E1HH H0HH HHHHHǅ  kLLL H8H8L HlL IuMVMfA=wAA$=wA$AxAj2  ME10H= HHL芇HHHH.H+  1E1E1E1HE1H H0HH HHHHHǅ  j1E1E1E1HH H0HH HHHHHHǅ  KjLc܄HRL mLL 7L gL#mH LH5w# E1H81谀1E1E1HH H0HH HHHHHHH8ǅr  ui1E1E1E1HE1H H0HH HHHHHǅ  iL*鐂LHL ρLL L ǁ蠀H=q HHLLHM襃HW%  1E1E1E1HH H0HH HHHHHǅ  ,hLD|L H=Ē HHLMHHL HHL0L0H+  1E1E1E1HE1MH H0HH HHǅ  ZgMH= HHL觃LHMRH'  1E1E1E1HE1H H0HH HHHǅ  fzL I H}ρL}ׁ1E1E1ǅ  HH H0HH HHHcf1E1E1ǅ  HH H0HH HHHHf1E1E1ǅ  HH H0HH HHHHeryL I1E1E1E1HH H0HH HHHHǅ  JeL MjMbAE =wAE A$=wA$AxA$,  M1L|L qLL {L iLE1E1E1ǅ  LL L0LL LLLLLIdE1E1H| LH5 E1E1H81{1E1E1HHH H0HH HHHHHHHPǅw  cwI{E1E1E1E1LL L0LL LLLLǅ  _cE1E1E1ǅ  LL L0LL LLLLLcMt$Ml$A=wAAE =wAE A$xA$&  M1n}LL0yL0X1E1E1E1HE1H H0HH HHHǅ  FbHz LH5 E1H81x1E1E1HH H0HH HHHHHHH8ǅl  aLxyH=\ HHL}LHM1y|Hz%  1E1E1E1HH H0HH HHHHHǅ  aE1LE1E1LE1E1L L0LL LLLLǅ  `HTy LH5, E1E1H81bw1E1E1HH H0HH HHHHHHH8ǅl  _L) 8wfo Lǅ  E1E1LL L0LL LLLLL_MiMaAE =wAE A$=wA$AxAm   ME1wIWH2H=wHJH=p|p|3%  HxF 1E1E1E1ǅ  E1E1HH H0HH HHH^E1E1E1E1ǅ  E1LL L0LL Lv^Lu4E1E1E1ǅ  ME1E11HH H0H H^L;uL.uMbMrA$=wA$A=wAAxA  M1E1E1E1E1ǅ  1HH H0HH HHHHHoE1E1E1E1E1E1E1E1E1LZLLtL LL 1tL LL tL Hu LH5c E1H81s1E1E1HH H0HH HHHHHHǅy  h\H@pH H84   HpH 1  HHp% H04   HpHp   HHpO H(4   HpH@ o  HHp H 4   HpH d  HHp H4   HpH   H0Hp H4   HpH   H Hpw H4   HpH l  H8Hp H4   HpHP   HHp+ H4   HpH   HHp H4   HpH Hu  Rxp80(PH@ h`XP 0`PLHLHxHHHc  H   M  H8+   H0f+  ) H(f+  )pj H f+  )@N Hf+  )2 Hf+  ) Hf+  ) Hf+  ) Hf+  )P Hf+  ) f) 1E1E1E1HE1H H0HH HHHHHǅ  WMMMeA=wAA$=wA$AE xAE <  ME1+ML$Mt$A=wAA=wAA$xA$-  ME1魹LGnnvLL03nL0uLnuE1E1E11ME1E1ǅ  E1E1HH H0HH H鷉LmL0auLL mL 0Lm6MbMjA$=wA$AE =wAE AxA  ME1qLlIHAxA  IBL LL   AL HI  LAL H  LH AH L L c  AxA  LLrMqMaA=wAA$=wA$AxA  ME1驧L lH= HHLMqHHL HHOL0oL0He  1E1E1E1HH H0HH HHHHǅ  jT1E1E1ǅ  HH H0HH HHHHHTǅ  E1E1E1E1E11E1E1E1HE1H H0HH HHHHHǅ  tSE1E1E1E1LL L0LL LLLLLǅ  +SE1E1E1E1LL L0LL LLLLLǅ  RE1E1E1E1ǅ  1HH H0HH HHHHHwE1E1E1E1E1E1E1E1E1ǅ  6H5 HfF HHE1E1E1E1L E1Lǅ  QLiHPHp: H84   HpH   HHp H04   HpHp   HHp H(4   HpH@   HHp H 4   HpH   HHp H4   HpH q
  L HpL) H4   HpH 	  LHp H4   HpH 
  H8HpA H4   HpHP ^	  HHp H4   HpH    HHpu H4   HpHH  RH@ Pxp80( h`XP 0`PLHLHxHHH  H     H8*  " H0f*  ) H(f*  )p H f*  )@ Hf*  ) Hf*  ) Hf*  )z Hf*  )^ Hf*  )PB Hf*  ) & f)&r1E1E1E1HE1H H0HH HHHHHǅ  CME1E14`I3E1E1E1E1ǅ  E1LL L0LL1E1E1E1HE1H H0Hǅ  LE1E1E1E1ǅ  E1LL L0L~L1E1E1E1HE1H H0Hǅ  ELE1E1E11ME1MHE1E1E1ǅ  H H0HH 1E1E1E1ǅ  E1H HK1E1E1E1ǅ  E1H HK1E1E1E1ǅ  E1HH HnKL&bIHN  AxA~  ID$LL   AIH   LAH   LH0AHu L0t(A$xA$   L0L t1E1E1E1ǅ  E1HH H0H H}A   A$x	A$t$U t%E1E1E1E1ǅ  	LnaLt E1LUaL0EHRb    H5 H81`1E1E1E1ǅ  E1E1HH H0H HIL`uHx A   AxA   p    E1E1E1E1ǅ  E1LL L0LL LLLIIWH2H0=wHJH =E1IL	`OL_zL BHka LH5C E1H81|_1E1E1HH H0HH HHHHHHǅy  HHMJMbA=wAA$=wA$AxAtRME1f1E1E1E1HE1H H0HH Hǅ  zLL0^L0L^lH9` LH5 H81M^KLL ^L cLL n^L 1E1E1E1ǅ  E1HH H0H	G1E1E1E1HE1H H0Hǅ  F1E1E1E1ǅ  E1HH H0HF1E1E1E1HE1H H0Hǅ  ^F1E1E1E1ǅ  E1HH H0H%FE1E1E1E1LE1L L0Lǅ  E1E1E1E1ǅ  E1HH H0HEE1E1E1E1LE1L L0Lǅ  xE1E1E1E1ǅ  E1H HME1E1E1E1H E1Hǅ  "E1E1E1E1ǅ  E1H HD1E1E1E1H E1Hǅ  DHm] LH5E H81[CL[dL[dL[dH&] LH5 H81:[L0H\ LH5 H81[L0tLO[ ǅ  E1E1E1MnMfAE =wAE A$=wA$AxAx  ME1FcE1E1E1E1ǅ  E1LL L0LC1E1E1E1HE1H H0Hǅ  UCH[ LH5 H81
ZH[ LH5 H81Y1E1E1E1HH H0HH ǅ  B1E1E1E1HH H0HH ǅ  B1E1E1E1HE1H H0HH ǅ  CBLL0lYL0mLXYgE1E1E1E1ǅ  E1AE1E1E1E1ǅ  A=wH8L8H`1H      H=r HLPHXVLIA6M   H=wLH`1H      H=r HLPHXULI5M      zVIHtoL` Lp(HH x/HH*FIgǅ  E1E1E1@H` xH`IL`Fǅ  E1E1@ǅ  E1E1E1@ǅ  E1E1E1n@E1E1E1E1ǅ  E1LL L0L4@E1E1E1E1LE1L L0Lǅ  ?E1E1E1E1ǅ  ?HX LH5X E1H81V1E1E1HH H0HH HHHHHHǅ  ]?HW LH5 H81V(HW LH5 H81UHW LH5 H81ULV1E1E1E1HH H0H Hǅ  >1E1E1E1HE1H H0H Hǅ  s>1E1E1E1ǅ  E1H HH>LL YUL HV LH5 H81TLL UL HV E1LH5h LE1H81TLE1LL L0LL LLLLLLǅ  L=E1E1E1E1L E1Lǅ  8=E1E1E1E1L E1Lǅ  =E1E1E1E1ǅ  E1L L<1E1E1E1H E1Hǅ  <E1E1E1E1ǅ  E1L L<E1E1E1E1L E1Lǅ  ]<E1E1E1E1ǅ  E1L L1<HT LH5 H81RL0GL"S=HT LH5v H81RfH~T LH5V H81RL0鞷1E1E1E1HE1H H0H Hǅ  v;MNMnA=wAAE =wAE AxAtME1ULL L0<RL0L HS LH5 LE1H81Q1LE1HH H0HH HHHHHHǅ  :H S H8H5 H810QմLL lQL HR LH5 H81Pɤǅ  E1E1E1mE1E1E1E1ǅ  lHR    H5 H81P1E1E1E1HE1H H0HH Hǅ  91E1E1E1HE1H H0HH Hǅ  %91E1E1E1HE1H H0HH Hǅ  8LL PL {LOHoQ LH5G H81OHOQ LH5' H81cOL0     UfH(g fHnHAUATSH   LoxdL%(   LEI)PHx  )`fHnHX  H  )pfHn~@ HE    fl)E~@ fl)E~? fl)EfHn)EHt/LIHM~#I  H JcH>     I  H JcH>D  HV0=wHUHV(=wHxHV =wHpHV=wHhHV=wH`HV=wHXH=wHPHL% HPATHUJ4HLH* AYAZ   HX LHP  H`   Hh   Hp   Hx @  M~)  ff.     ff.     II  J< uHO HLL Ho H5 H8AP1A   L_AXA  Le    HL9t'H;HtxuLHL9u@ DH E1H=  HUdH+%(     HeL[A\A]]fD  LA=wAL~M LPA=  LXAE1E111H{M wH`IHH  Mh  HPM  H  H;= M H;=M c  H;=M V  L(L0L8H@LH.OLHH@L8AL0L(  HLLLAULe)Y^IHL9H;Htxu)K    1E11E1E1 LVA=wALLXA=wALPMHHL wHhHMHL wHpIHPMxMMA=wALxHPHVE1D  11E1E1LfA$=wA$L`@ 1E1E1HN=wHhD  1E1LF A =wA LpfD  1LN(A=wALxf     H~0=wH}     D    H}LPLXL`HhLpLx5M  Hv    L HJ HH5 A  HPH8AP1IH HXZD  HJ wHp0fD  HJ wHhfD  HI wH`fD  LiI A=wALXD  IU=wHxfHY    L      KLHH@HL8L0L(PA  LXdHf.     f     UHAWMAVMAUATSH   HH  oEhHuH5 H   HUH HM1HE$oExD$o   D$ o   D$0o   D$@o   D$Po   D$`o   D$po   $   o   $   o  $   o  $   o(  $    b H   H  IH@H5
a LH   H?  IM  A$xA$\  H5ea    LJIAE M  xAE 7  L E  A$xA$  EH3  UHLEMHLePE1E1HUM9  DD  E  UD1MHuL;MHn  ]HU@x1LML}(H]L}8LLpLWL9U0o  H;}0e  HE8Hu(EHHcA9"  LMHuMHHMHhML`H]LH  L9  H9   H]HL)HHU H]HcH  L9  HHU`XLHU@
f/veH  H9   H  L9U  Ut6HUH;Ux  H9]  H   HUH   HUp< HLA9"HhL`MH;}  L}8HU`M9c  L@ HD 1H5P H81nC ff.     H=a d 1He[A\A]A^A_] x܃AE uL{Cf     [GHofA$xA$uLGCD  HL\HHP^    HLmH%D    H5 H81B:f.     LB LB LB IMxUyHUH;UxK  H]C   lf.     IIHIMCDUEHUH;UxrHUHH?    >I 1H'C H5 H81AAxLMLp;ELMHuAEu5IHuLmXL;}@ ff.     fD  L;}HvHU@HE    L}H](HuLH]8LmILEEHELhL;m0oH9E0eHEHE8HM(DHcA9   I<HMMAIHxm LLpH49HMHH   L9H9II)CD= H] LmIc\ H   L9H]`XXf/   HLA9HxLpEȃD9suH]8LU`M9Lm@ 1H9]H f     LH<HH0@LWDGL}HuLmLE@ UHAWMAVMAUATSH   Hx  HEpoEhHuHUH56 HO HEHExHM1HEH   HEH   HEH   HE$oExD$o   D$ o   D$0o   D$@o   D$Po   D$`o   D$po   $   o   $   o  $   o  $   o(  $   Z H   H  IH@H5$Y LH   HQ  IM  A$xA$  H5Y    LBIAE M  xAE   L) E}  A$xA$x  EH]  UHH}PMMHE1E1E1L;}  D<    1L;}H  H](H]8ME1H]H]LU@PLHHHhMHpH`L@D<ICHXH9E0I  L;]0?  HEHM(DHE8IHcA9   LIt HMH0HAIHxHHH  L9   H;E   HxII)AHU H]IH9S  HU`f(XHLHU@f/>  
Ug  Xf/vAf(Аff.     HLA9SH0L;`S  HM8LU`HMHMHpH;X(  LX@ H= 1H5p H81; ff.     H= 脬 1He[A\A]A^A_] x܃AE uL;f     {?HufA$xA$uLg;D  LH\HURXf/UA   L;}rK1L;]   fD  L;}  H;]  H]XHhf/DAL;]   HpHf(LDA9d@ L:= L:b Lx:{ f(H   ff.     Hi;    H5 H819^fD  6I 1H/; H5 H819)f     1H;]D     ËMPHHL@D<9u,IHuLuXLEI9 fD  L;}H^LU@HE(L1HE8LpMHEMLxHhH`HSH;U09H;]0/HEHu(DHE8HHcA9   HxMD MHXMHPN LHuLHH   L9H;EHL)B;HU H]HcH'H95HU`XA\fT* f/wkHLA9HXHP9sRHu8HuHu`HxH9GH    LHHU
UD/MLpIHhH`%UHAWAVIHAUIATSH(
  H   H8L dH%(   HE1HHHp   HHH@   HHH   HHH   HHH   HHH   HHHP   H HH    HHH   HHA=wAAE =wAE L%}Q H=J IT$Ly8HH%   =wL%K H=I IT$LD8IH%   =wAH
8    E1H9C&  H8   HHǅ    LpLxHL4HH  H.M HHP =wH7    HHH)HHH?H	HpH4H0$7MHHtA$xA$L  AxA  x  x  H A  AxA  HH5HO HGH   H(  IM'  11L׹   Ly LHHh'  AxAt  HM L;-5 H=G HSHB  M6IH)   =wA$ID$H5J LH   H*  IM*  A$xA$  HhI H=qG LHSH5LHI+   =wA$H5 A   E1I9A,  f   LLpLx)1LHHe'  HL HH HP =wHJ HHS(=wL   LHL)H?LH	H0LJ44MLItAxA,'  A$xA$uLL2LxuHLy2LAxAuL[2MZ&  AE xAE uL92H5bM 1L6HH&  IVHBpHs'  H@Hf'  HLIM*(  HhLL47LHI(  AxA&  LHLLI3L,  AxA/(  x(  HJ H=D HSHL3IH8-   =wAIALLH5G H   H.  LIMG+  AxA)  H5L 1L5HH/  H2 I9D$1  HHxLMH      Hǅp    Hx HHx)  AE xAE )  H,  L-T1 L9H;2 $  H;e1 $  H3Aą$-  x3*  E(  HSI H=lC HSH1IH7   =wAIALLH5F H   H7  LIM)  AxAX.  Hh   LLp3LpHHk7  H1 I9B7  HHxLH      Hǅp    HxLp LpHHx.  A$xA$.  H*  L9H;0 L)  H;/ ?)  H2Aą+  x0  Er&  M1  fLHA.HD  H(. H. 0IH)   =wAIALLH5SD H   H{*  LIM)  AxA$  HC H=%A HSH/IH+   =wAHO/ A   E1I9G,  Hh   LpLpLHǅ    HxL+LLpHH&  HD HP =wL   HLL)H?LpH	H0LLJ4l.LpLIMtAxA!  AxA&  x%  AxA%  M&  H-  xH5w-    MIEH5F LH   H*  HHM*     *IH+  Hh=wHhLHLpIA -*LpHHv,  x-%  AxA2%  HD H=> HSHX-IH,   =wAIGH5A LH   H?-  HpHp ,  AxA%  HpH5, H9p.  HpHxH      Hǅp    LxH HPxk%  HP .  HP=wHPH01H      H=OD fHnE )p'H`x!)  xHP$  H` /  AE xAE %  HOC H=h= HSH+IHA0   =wAIALpLH5A H   H0  LpIM?&  AxA4(  H`Lp,LpH1  H%LpHI%     LPHp='LpLPHI%  HhLH =wHhH,> LpH=N< ID$(HSH*LpHIv4   =wAHl* A   1I9C5     LPLpHǅ    HpLxq&LpLPHIQ.  H? HP =w   LLLH?L)LH	H0L@LPJ4)HLPL@HptxX/  A$xA$-  AxA-  AE xAE ,  AxA,  HpHe-  =wH@ H=: HSH)IHX4   =wAIGH5p? LH   HK5  HPHP E5  AxA`.  HpHP1H      H0H=> HpHx#H@x2  HPx-  H@ 5  H@x.  H? H=9 HSH(IH5   =wAICLPLH5X< H   H5  LPIM5  AxAw1  H`\(Hv3  H!HPH6  H[' I9GE6  HPHxLLH      Hǅp    HxD IHPx 2  x
2  Mt6     LP#LPHIX6  H`LP =wH`H? LHpIG(Q&}2  AxAE3  HL-% L9H;[&  -  H;% ,  H'6  L%= H=7 IT$LT-  &IH5   =wAICLPLH5; H   H;  LPIM5  AxAB6  H`LPa&LPHk>  HLPHI5     H@!LPL@HI5  HhLX =wHhH8 L@H=6 ID$(HSH%L@HHP?  HË =wH$    E1I9A@     LLpL@Hǅ    Lx L@LHI@  H1: HP =wHP   LLH)LHHH?L@H	H0H4#LL@HMtAxA<  A$xA$B8  HPxR8  AxAZ8  AxA8  H?  =wH01H=x9 H      fHn< )pIx<  M?  AxA7  HPH L9H;" 0  H;A" 0  H w$7  0  H@: H=Y4 HSH"IH<   =wAIBL@LH5%: H   Hb=  L@IM=  AxAW9  HH57 HGH   HA  IMUA  IBL LH5: H   HA  L H@H@ @  AxA8  H! I9D$TC  1HxLLHpH@H      Hx H H@x9  x8  H IH?  H`9 H=2 L@HSH&!L@HI/8   =wA$H|4 H=2 L HSH L HH@:  HË =wH  A   E1I9D$9  H   L Hǅ    HxH@LpHL HH6  H7 H5G5 HP =wL   HLL)H?HH	H0L J4ML ItAxA6  H@x5  x5  A$xA$5  MN5  IGH H9tH; A  IH9  H9=  I_ H@=wIw(H =wAxA5  H8L9H; 2  H;7 2  H8Lf LJ<  L8H`H/   H4   HL8H ?  LH\ H4   HL8Hp C  H@HL8x H4   HL8H@ ??  H H; H4   HL8H B  HpH~ H4   HL8H >  HPH H4   HL8H \>  H   H4   H80` PLHLHxHHH.H0  HcL8HI>  H5  L ԩ HfҾ5  )踩 HfҾ5  )p蜩 HfҾ5  )@耩 HfҾ5  )d HfҾ5  )H L8L H55 f   LL)tLHI<  H蹪 Lo<  AxA:  :  HLz LA  Hp7  =wHpH1H      H0H=3 LHpHxNHIsML=  HP=wLPH1H      H0H=2 LLpHxLHHLeB     L0L0HI"B  HhLx HX(Q  A  L`L`  fD  L L LH@ LLLD  E11E1Hǅ8    E1E1Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    Hǅh    LA  D  MtA$xA$6  HtxP  MtAxAh  MtAxA  MtAxA  HHt'H; tP8Hǅ      Hǅ    HpHt'H; tP8Hǅx      Hǅp    H@Ht'H; tP8HǅH      Hǅ@    HHt'H;C tP8Hǅ      Hǅ    HHt'H; tP8Hǅ      Hǅ    HHt'H; tP8Hǅ      Hǅ    HHt'H; tP8Hǅ      Hǅ    HPHt'H;K tP8HǅX      HǅP    H Ht'H; tP8Hǅ(      Hǅ     HHt'H; tP8Hǅ      Hǅ    Hu DH= 覌 HhHtx  E1H tHxT  LHp tHpxC  HPHtx  H`Htx  H@Htx  H Htxw  H8Htx  Hx  AE xAE    HEdH+%(   )  HHe[A\A]A^A_]@ LLL0LL0    HLL0LL0    LLL0zLL0o    LL0QL0eD  L8k L( HU Hb Ho H|H7  7  L`L`f     H    H H1 Hp9 H`2 H=$ HhLmHhHHw!  LE1E1E1Hǅ8    A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    Hǅh    @ cH=4$ HhLLhMThH   LE1E1A  Hǅ8    Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    Hǅh        LcHSA$=wA$=wx  H1D    HHHǅ    u  HpHHǅp    5  H@HHǅ@      HH
Hǅ      HHHǅ    uh  HHHǅ    5Q  HHHǅ    :  HPHHǅP    #  H H Hǅ     u  HHHǅ    5Hǅ8    E1E1E1Hǅ     A  Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    Hǅh    @ HT	I@ Hǅ8    E1E1E1Hǅ     1E1A  Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    MAALLL0LL0fD  E1E1E1Hǅ8    E11A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    RfLL@ Dk    H`7 ME1E1E1Hǅ8    A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    @ HH
HD  L
L9@ LL
LD  HBhH7  Hx ,  HLQ IzD  #H= HhH}LhM(E1E1HH,   Hǅ8    E1A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ        ME1Hǅ8    E1Hǅ     A  Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    9    HP	 L@	 I Hǅ8    E1E11Hǅ     A  Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ         L Ld	H=5 HhHLhLMLp[E1LpHH/H	 HE1H5 L0A  H811L0E1H8H H@H`HPHp HQ =wH4  HxHH      Hǅp    Hx Iċx  Mt1L~ A$xA${  ME1A  E1Hǅ8    E1Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    D  L MyIYA=wA=wAxA  IE1@ H: L? L/ Hp L` HPLp@ L8 E1E1E1A  E11Hǅ8    E1Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ        H E1ME1Hǅ8    A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    ?    D    L06 H  H ME1A  E1E1H=| HhH
LhMLpE1E1LpHH/  ff.     Hǅ8    A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    (     E1 E1E1pD  L% H= HhH	LhMLpLpHH
H; HME1H5 L0A  H81<1L0E1H8H H@H`HPHpALI}@ L`E1Hǅ8    A  Hǅ     Hǅ@    HǅP    Hǅp    Hǅ`    MA  Hǅ8    E1E1E1Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    V@ LId@ H= HhHuLhMLpLpHHH HH5k L0H81E11L0A  H8H H@H`HPHp    Hǅ8    E1E1E1Hǅ     A  Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    7    H5 LLp!LpD  LLLD  ME1E1E1Hǅ8    1A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    UD  MWI_A=wA=wAxAt  IE1@ HPH9 fHǅ8    E1E1A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    Hǅ    fH L M|$Ml$AfIn=wAAE =wAE A$xA$+  H0   L)pX HAAL&Hǅ8    E1E1A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    H=Y HhHLhMeHpHtN1E1E1A  H8H H@H`HPHpD@ HHH HH5 H81Hǅ8    E1E1A  Hǅ     Hǅ@    Hǅ`    HǅP    {HpHEdH+%(     rH= 6  1趋 HEdH+%(   c  rH=i 6  1荋 HEdH+%(   :  rH=@ 6  1d HEdH+%(     rH= 6  1; HEdH+%(     rH= 6  1 HEdH+%(     rH=ũ 6  1 HEdH+%(     rH= 6  1 HEdH+%(   m  rH=s 6  1藊 HEdH+%(   D  rH=J 6  1n HEdH+%(     rH=! 6  1E L`HXfInA$fInfl=wA$=wHpx  H0   H)p HPA$A$LHǅ8    E1E1E1Hǅ     A  Hǅ@    Hǅ`    Hǅp    D   	  H5 HhLa LhMT	  HxLH      Hǅp    Hx IA$A$LLLH%LLPLP.L4LL@LPtL@LPLLPRLPHǅ8    E1E1E1Hǅ     A  Hǅ@    HǅP    Hǅp    L7LxE1E11E1L`E1Hǅ8    A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    ?:H= HhHLhMLP8E1LPHHpH HE1H5 L0A  H811L`E1H8L0H H@HP1H`fD  {H=L HhHLhM+LpILIH`LSHL@LP8L@LPL`E1Hǅ8    A  Hǅ     E1Hǅ@    Hǅ`    HǅP    Hǅp    ME1E1E1Hǅ8    1E1A  Hǅ     Hǅ@    Hǅ`    HǅP    Hǅp    &He6MzMbAfIn=wAA$=wA$AxA  H0   L)p HAALHH    =wHCH5 HH   H  IM  x	     LPLPHH  Hv =wHhHS =wHhL% LPH=	 HC(IT$LLPHH@H   =wH E1A   I9Cn     LLpLPHǅ    HxLPLHI	  H ID$ wH@   LLL)LHLH?LH	H0J4LLHPMtAxA  xt
  H@xw
  A$xA$}
  AxA
  HP [E1E111LPL`E1H8A  H H@H`HPL)|LpH= HhH2LhLpM`LPLpLpLPH  E1E1E11L8L L@LPLpL`L`A  :f.     HpdI[Mk=wAE =wAE AxA  ME1HL@
L@HLPLPLLpLLLpcuH=F HhHLhMzH~  E1E1L`E1L8LpA  L L@LPL`,@ L)p)fopL`A  E1E1Hǅ8    Hǅ     Hǅ@    Hǅ`    HǅP    IVH HRH5r MA  H81O5HPL`E1Hǅ8    A  Hǅ     LpHǅ@    Hǅ`    1L9L`E1E1E1Hǅ8    A  Hǅ     HǅP    Hǅ`    H=y HhHLhMLPLPH5  E1E1L`Hǅ8    A  Hǅ     Hǅ@    HǅP    Hǅ`    GpH)P@foPLE1LPIVHH5t HGH   H  IM1L`E1E1H8E1A  H H@1H`    H) LH5 H81=iH	 LH5 H81L`E1Hǅ8    E1Hǅ     A  Hǅ@    Hǅ`    MgI_A$fInP=wA$=wAxA  H0   H)p IA$A$uLL@L@ZE1L`E1E11Hǅ8    E1A  Hǅ     Hǅ@    HǅP    Hǅ`    L)p fopH= HhL(LhMLPLPH{  E11L`E1A  H8H H@HP1H`}L`A  E1E1E1iLLPcLPHLPHLPLLp-Lplp H4   HL8H   LHp H 4   HL8HP   H@HL8o H4   HL8H  O  H Ho H4   HL8H U  HpHq H4   HL8H   HPHXr H4   HL8H m  H   H4   H80@ p0L(L`HXHHHeH0  HcfL8HI  H5  LKz H f۾5  )/z Hf۾5  )Pz Hf۾5  ) y Hf۾5  )y Hf۾5  )y L8LrHLELqHL*LnLL@L@hLnHw HH5O E1A  H811E1E1H8H H@H`HPHpLL@L@LxHL@dL@LLPILPL5
kE1L`E1E1L8A  E1L L@L`LLxIEkLPIwH=H HhLHhH|H  E11E1L`E1H8E1A  H H@HPL`01E1E1H@1L@LE1L`ML`A  H8E1H H@HL L HL@L@LL@L@E1E1E1E1L8L L@LPL`L`A  6H@HPLAL `LL&LL)@fo@!LLL@H=i HhHLhL@ML@H  E1L`E1E1L8E1A  L L@L`LHTHGMKMcA=wAA$=wA$AxA?  ME1JLPH= HhLHhLPHH@LPH{  1L`E1E1H8A  H HP1H`GH HE1H5Ç L0H81E1SHLP1LPL`A  E1LL@
Mt$I\$A=wA=wA$xA$S  IE1L hH=9 HhHHhL HH@L8XL8H  1L`E1E1H8E1LA  H L`H= HhH8LhMVH2  E1E1L`E1L`E1E1A  L8L L@  HxL@X L@1L`E1E1L`A  H8H H@I1E1L`E1H8E1E11H A  H@L`L@IL@H= HhHHhL@HHPL@H  11L`E1H8E11A  H H@H`81E1E1HP1LPIE1L`H81A  H H@H`HP1L`E1E1H8E1A  H H@1HPH`LpMQIYA=wA=wAxA  I1Ӿ=wHpHpH1H      H0H=[ LHpHxHI趾MLm  Hh #  HhHL0L0L`L`HnILLPLPH, HH5 H81@LPLpE1L`E1E1L`A  E1L8A1L`E1E1H8E1A  L`1L`E1E1H8E1A  L`1L`E1E1H8E1A  L`H    H5m L@H81\L@IWHH@=wHrH =??L_LE11L`E1L8E1E1A  L@H`11L`E1H8E1E11H A  H`L H@11L`E1H8E1E11H A  H@H`SH'IQH=0 L輻 LHH  H= H;=   ID$   tH; ~  LL{LIM  H5    E1H9sF  H0H   HH?H)LH	H4LpLxŻ LI*A$LxA$  x^  Mt-1LL0g AE L0xAE   L`E1E1E1L`A  L`A  E1E1L`L`E1E1L`A  E1L`E1E1L8E1A  L`1L`E1E1H8E1A  L`1L`E1E1H8E1A  L`YMt$I\$AfIn@=wA=wA$xA$  H0   H)p H ApAdLWLL@kL@HI)AxA  ICL LL@L   AL@L HHW  LLAL@LHH    LAHr L@LtYAxA   H@LL@L@FL`E1E1L`A  1L`E1E1L`A  E1L H8H H@@A   AxAtPL@&q L@tQL`1L`E1E1H8A  E1H H@LL@L@LO L`L@H xHL`LL`L`E1E1E1L`A  H HH5{ H81,L@L) afo 4LLL01L`E1E1L`A  E1H8E1LL@L@Hs LH5K{ H81OLL L@L L@LsLkA=wAAE =wAE xtnL1yH HH5z H81L8L`E1E1E1L`A  HL0L0HLLwL`E1E1E1L`A  LL0L0LLLI}L`E1E1E1L`A  \LL ]L H LH5y H81LP^H LH5y H81LP^H HH5\y H81b1L`E1E1L`A  E1H8騿H9 HH5y H81MH HH5x H81-L@H HH5x H81LPHhL07L0L`E1E1L`A  L`E1E1L`A  ݾfff.     UfHh fHnHSH   dL%(   LEI)EHx  HP  )EfHn~ HE    fl)E~v fl)EfHn)EHt0LIHM~$I  H JcH>f     I  H JcH>D  HV =wHUHV=wHUHV=wHUHV=wHUH=wHUHLw H]ARJ4HUHLx _AX   H} Lx]  H} *  H}   H} \  M~  fII  J< uH HHYv H5~ Lx H&w H8AP1A   Y^HH]H8HtxtDHH9uH~ f  H= L 1HUdH+%(     H]     HxtHx 11E1LNA=wAH>LM=wH}H   H   H]M
  L=HH]H:Htx-  HH9u>    1E1HV=wHUW     E1HN=wHMD  H>=wL H}A=  LMA1E1H =wHUHH wHEHH]MH 0w0HEIH]D  LF A =wA LE HpHxHpHxM   Hs    L/v HW HH5L| H]H8AP1IHt XZk H}LMHUHMLE    Hi =wHUf.     L A=wALMH wHEH wHEZHr    L;z 
     LMfUf(fHAWAVAUATSHH  HEHHH] HHE(HHLuxHHE@LH HEPL@HHEhHdH%(   HE1H   )pfHE    H)PH~D   L9	  Hp  H0H~   H8H90	  	  HPHE1E1Hǅ8    H   H	 DXIHPfoPAELxLpLAUH AED(L)LHH@c H0 D(H ~L  Hh  B"AHD9   D!H   ILI    L;8HHHpH D DXHPD(a HELxHH8D (H}8   LpLL)  A7E_IH[  H   Ef(fWe LxIfA/wH   Hǅl    HH   HHh  HH  HACHHE0HE0ILc$D91MLMHLMLN<LfAH@HH\f/rH   HA6f/w6IID9LMyLL)BHL     A6fWB L98  hI`fo`AELxHpLAULAELH)HHHL D(8R` H 8D(L HLL~HHHDH0 ~HHHHIЋHEH8LAE AUAu L)E]IIH   MH1f(I fD  yHA|AI9~YHLPKtLHHHLLf/wf/ȋwI9s    f(K4fD  f(Au6III9u*HL6HHHL@A7AD7HfLD (^ D (zD  HHEpǅl    HHEpILc$D9LM`HMN<HEXLHE`IO    AHEHH \f/rH   HA6f/w1IL}`D9LMyLL)BHE8LD  A6fW L;8  hI`fo`AELxHpLAULAEHH)HLHL D(8*] H 8D(L LHL~HHHDH0 ~HHHHIЋHEH8     1MtH8LL)HEdH+%(     HH  [A\A]A^A_]H`HpLLHL D(h8`[ LxLLHL D(8H`HpLHLL D(h8`gZ LxLHLL D(81VH @HH=w   IH	  H   HHb  E1L   =wIGJ0II@	  K<4HH  x   HӋ=vHǅ8    E1E1 HJ H=w   IH	  Hp  IH  AE E1Lp  =wAE ID$N,8II@  K<>HHl  AE x	AE t+IAE =vHH8H8
LH@H@Hh w   H=Au ,= H[  x  AxA  @OHH 	  E1E11HH  H
  A  x  LMtA$xA$|  Htx   H(o DH=t HS< HHELpH8Hg w   H=)t < MtAE xAE   A$xA$  H5A  CA@rHH   E1E1    H߉HH A  JA-    AxA"  H[ IGH0H93  A=|  MAxA  LHHg     IH  HX H@H;0  A=&  LAxA?  H Le   H]HEHs HEHH HEAD$ @u    t   EC @       EIT$HCH}   HT-6 IH  A$xA$  x  ffInHHHuH      fl)E= HAxA{  HHxp  Ht1H x  @A  H׉@@GL牍HHkA$q  rA4$AE   AE o  A$xA${  H ID$H0H9  A$=  MA$xA$  H89IH     IH  L` H@H;0  A=  MAxA  H, Lm   LeHEH HEH HEAE @u    t   EAD$ @!       EIUID$H}   HT(J4 IH  AE xAE d  A$xA$\  ffInHuHH      fl)E譜 IAxA,  x(  Mt1Lg A$xA$  HgA  &M(MwLLpM]LLLֽh@HH :PH衽DL蔽xH臽LzLmL`LSHFH9UL,H<A$xA$i  AE x	AE tA  LHּHHƼL蹼L謼A$A$L苼H_ u   H=l 4 H_ u   H=l 4 RkH;6   LPXIH  A$@*HHE1 {A  6HAE AE ILA  H߉H藻HJnH;} h  LPXIH,  AH;V   LPXHH[  AH;/   LPXIH  AdAE HLA$LȺxAL診A  H譼HA$A$~L牍H_H;[ H5 L޾@NHH x,E1LH; H5 L蓾}LE1@蓾HH LLH; [H5\ L<ML牍H艹H~H蓻.AE x5IMLA  H;Q H5 LԽMA  \HUIHAWAVAUIHPATSHX  HEHHL      HHE(LH   HHE@LLExHHEPL   HHEhHH   dH%(   HE1L   D HH    HDH;     H;     H;   
  Ek  MLIHL;? ǅ(    L 	HLH; 	HH;5 	H8HHHAE H= 8 IH%  H=Z    1jHH  HIW LHwZ     HHIo  x  AxA  H1   L; ǅ<   HK  H   LH ASH<   L@L4 ZLY  LHH H@Ml  AxA   uH   O8   u   AL$8  H   LXHǅH`H   H u   K8  HH   H H  HǅH(H   fo H0HpHLP$   fo0$   fo@$   foP$   fo`$  fop$   fo$0  fo$@  fo$P  fo$`  fo$p  fo$  fo$  foP$fo`L$fopL$ foL$0foL$@foL$PfoL$`foL$pfo$   fo$   fo$   fo $   fo$          upu`uXuHu8u0Lu LuHH     L;= tAG8.   uHF8   uAD$8   uC8  H   (H(H   LH L   9 &1      IċLA`  x  A`  x$  Mt?A$1ۅx5A$h  Ht#xuH. ff.     11E1MtL;U tA@8  HtH;3 tB8f  HtH;5 tF8  H\ DH=tb ) HUdH+%(   9  He[A\A]A^A_]     M11@ LLQLbD  L4L2     LHHHHHHf     1E1   11MtAxA   A`  C8  peHHH L(aL(H H.    H8 LHA`  H L(L(H H kfD  Lد L;= HLLLL-1 AE =wAE L
E1H   L(LLIףp=
ףL-t} HIHH?HHH)HkdH)ø   AAAII9ICAHHC4?L)HcHH9HBI)HLMd   L&HHuA	LML(H4I)H    yF-IHI|
  1MDII1	& HH  HL1LD  MiQLI%H%kd)ø   H94HCHcHH)HH9HBH)HLHL   H(C cH(Hw
  	HH4I)I	  1MDII18% IMu
  H HSfInfHn~       ~} HID$HflflHT5)) " IH
  x  A$xA$  HHLH      Hǅ@    LH HAxA  AE xAE b  Ht1HÌ x  11E1AR  H! =wH(L
E1L   LL%yz Hףp=
ףILH?LHH)HkdI)Ƹ   EDIAAII9ICō4HHcL)HH9HBI)HLMl   L%HMu	H(H4I)H    yF-IHI  1MDII1# IM  HL1LD  MiQLI%H%kd)ø   H94HCHcHH)HH9HBH)HLHL   H(M cH(H  	HH4I)I  1MDII1B" IM  H IVfInfIn~       ~ HID$HflflHT8))  IAM	  xAuLAA$xA$uL(HHHH      Hǅ@    LH IAE xAE uLxuH̩Mt1L轉 A$xA$  11E1AV  }fD  AW  =D    HND v  A$HA$<fD    kafH =wH(L
E1L   LL%v Hףp=
ףILH?LHH)HkdI)Ƹ   EDIAAII9ICō4HHcL)HH9HBI)HLMl   L蕬HMu	H(H4I)H      I>  1MDII1 IM  HL1LD  MiQLI%H%kd)ø   H9HCHH)HV4H9HcHBH)HLHL   H(ū cH(H=  	HH4I)I  1MDII1 IM  H IUfInfIn~       ~ HID$HflflHT3)) , IAE Ma  xAE   A$xA$  HHHH      Hǅ@    LH苄 IAxA  x  Mt1LE A$xA$  11E1AZ  fD  *  AALfD  #  A A LH H(赥H(H f  Hf[HvNx  HH(FH(df.       A$A$L	@   ;0Hݤ#       H譤     F-IHW    >I1     Lh LXl LH H8 >hH>XIK>HI`>8I!>(IHأ!LˣL辣L豣L褣:H藣>L芣UD AE xAE   AS   ff.     11PAE    AS  AE      LHMtA$xA$LD XHEdH+%(   {  q1  H=O 10 HEdH+%(   R  q0  H=qO 10 HEdH+%(   )  q1  H=HO 1q0 AE xAE   AS  D 9E1A[  AALMoA$cAW  HUdH+%(     p41  H=N 1/ HUdH+%(   ^  pR1  H=}N 1/ HUdH+%(   5  pQ1  H=TN 1}/ HUdH+%(     p81  H=+N 1T/ HUdH+%(      pT1  H=N 1+/ HUdH+%(      p61  H=M 1/ HUdH+%(      pS1  H=M 1. HUdH+%(   ulp:1  H=M 1. A{AE xA[  AE XKyA[  E1AS  .艡LA`  E1H1E11ҹ   j@ UHAWAVAUATSH   H$ Hx  H(IILHHH   LdH%(   HE1HHHP   HxHH    HpH   LHH   HhH   HHH`   H@HH0   HHH    HHH   HHH   HHHp   HHH@   HHH   HHH   HHH   HHH   HHHP   HHH    HHH   HHA$=wA$A=wAH; H; w  H;0 j  Hj]  Hǅ0    E1E1E1HǅH    E1Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    Hǅh    L`A  D  MtA xA 4  MtAxA4  H0Htx4  HHt'H; tP8Hǅ    5  Hǅ    HPHt'H;ڝ tP8HǅX    5  HǅP    H Ht'H; tP8Hǅ(    5  Hǅ     HHt'H;^ tP8Hǅ    5  Hǅ    HHt'H;  tP8Hǅ    8  Hǅ    HHt'H; tP8Hǅ    8  Hǅ    H`Ht'H; tP8Hǅh    8  Hǅ`    H0Ht'H;f tP8Hǅ8    8  Hǅ0    H Ht'H;( tP8Hǅ    8  Hǅ     HHt'H; tP8Hǅ    8  Hǅ    HHt'H; tP8Hǅ    8  Hǅ    HpHt'H;n tP8Hǅx    8  Hǅp    H@Ht'H;0 tP8HǅH    8  Hǅ@    HHt'H; tP8Hǅ    8  Hǅ    HHt'H; tP8Hǅ    8  Hǅ    HHt'H;v tP8Hǅ    8  Hǅ    HHt'H;8 tP8Hǅ    8  Hǅ    HPHt'H; tP8HǅX    z:  HǅP    H Ht'H; tP8Hǅ(    :  Hǅ     HHt'H;~ tP8Hǅ    :  Hǅ    H$C DH=
I U HhHtxX.  1HP tHPxd.  HX tHXxZ.  H Htx}.  H Htxp.  HHtxc.  HHtxV.  HHtxI.  HHtx<.  H@Htx/.  HHHtx".  Ml)  Aa)  AU)  L肖H)  D  H= ^(  HO HQHHhLHH07   =wH H= HQHHhIH8   =wA Hח    E1H9C:  HH   LPL`LhLhHXHǅp    LXH`LhL`HHF-  H߬ HXHP =wH?    HLPH)LXHpHH?HhH	HPH4H`ǖLXHhH`LPMt6Ax/Au'LHXLhHXLh A xA (  x'  x'  H` 5,  A$xA$'  H`H5 HGH   H8  IM8  11L߹   LX  LXHHh9  AxAuLL%K L;= H=] IT$LW'  躕HH:   =wHCH5 HH   H;  IM$;  x7  L%ܨ H= LXIT$LALXHH~;   =wH E1A   I9A><  f   LPLPLXLX)`LXLPHH9  HT H5 HP =wHT H`HQ(=wL   LL0L)H?HPH	H`LXHhJ4L0LXHPIMtA xA *,  xI7  xx7  AxAU7  M8  AxA+  ID$H5 LH   H*<  IM;     LX諏LXHI!<  Hh=wHhLLL0LXIA 诏LXL0HHP=  AxAN+  AxA++  HT H=m HSHђIH=   =wA I@L0LH51 H   H?  L0HXHX Y?  A xA uL\HXH6 H9XA  LXHXH      HǅP    LXL"n LHËxuHH^*  =wH`1H=Щ H      fHn )PIǋxD:  xuH臏M)  A$xA$8  H5 1LIHB  IWHBpH:  H@H:  LXLLLXIMG  HhLL0LXOLXL0HIUF  AxAB:  LLLL0LXVLXL0G  AxA';  AxA;  Hӧ H= HSHPIH+I   =wAIBLXLH5 H   HvJ  LXH0H0 pJ  AxAc>  H5 1L~HXHK  H0H H9XO  H0HXHXH      HǅP    HHX}k IHXxp?  xD?  MN  L;I L; 6  L;] 6  LLX萐LXH  AxAA  L<  H= H=V HSH躎IHS   =wAIBLXLH5 H   HS  LXIMS  AxA~M  Hh   LL0L0HHXU  H I9AU  HXHXLH      HǅP    HXL0i L0IHXxL  A$xA$M  MU  L; L;u A  L; 
A  LLXLXG  AxA1O  :  H H= HSHIHA   =wAIALXLH5Т H   HD  LXH0H0 D  AxAr7  L_HD  HIHyG     HX蠈LXHHG  HhLH =wHhL% H= HC(IT$LIHL   =wAH0H5݋    E1H9pTM     LLPLXH Hǅ`    HXۇLXLHIA  HJ H HP =wHȺ   H0L H)H?L`H	H`LH4LL LHXMtAxAC  xM>  AxAU>  A$xA$M>  H0xB>  HXH@  =wH H= HSHzIHrL   =wA I@L0LH5  H   HYM  L0H H  L  A xA HB  HXH 1H      H`H= HPHXH xK  H xA  H  N  H x#C  H H= HSH^H0HN  HË =wH0H5 HGH   HCO  IMIO  H0xI  LL0覉L0H}O  H=L0HH P  H I9@Q  H HXLH      HǅP    HXL0|d H0IH xJ  xJ  MR     L0OL0HIR  LX A=wAMx(H LHXL0臇L0S  A xA K  H(H; H; cA  H;ӆ VA  H(	R  Hڞ H= HSHޅC  OH0H0V  HË =wH0H5 HGH   HY  IMaY  H0xS  LL0藇L0HX  HL'LHH0I[     ÂLHHp[  HhL` =wHhL%ٙ L0H=ۗ HC(IT$L:L0HH HaZ   =wH A   E1I9A`     L LPLHǅ`    HXLL HH0`  Hb HP =wH    LH0L)L H`LH?LH	H`J4L LIMtAxALY  x$U  H xV  H0xR  AxAR  M]  A$=wA$H`1H= H      fInҝ )PIA$xA$\  Ma^  AxA\  L H H=ŕ HSH)IH\   =wAICL0LH5! H   Hj\  L0IM3[  AxA9Q  H H=C L0HSH蠃L0HH@Z  HË =wHY A   Hǅ0    I9BY  H0   LHǅ`    HPHhHXNLHHYQ  HĘ HP =wH   LHL)LH`LH?H	H`J4uH0LH Htx*X  HxQ  xQ  AxA2Q  H  yP  H`H5 HGH   H_  IMO_  A=wAH`1H=Ж H      LPL0HǅX    }L0HAxA3W  AxAkP  H ~^  H= \ H$^  H= H0\ L0HI[  H,    1I9B[  1H`LHh   L`L0HHPHX}L0LHIV  H H5ϕ HHP =wHȺ   LHhH)H?LH	H`LH4L1HH0[LL0LAxAV  A$xA$U  AxAU  MV  I@H& H9tH;" Fc  IxH_  H9^  IX H=wIX(H=wA xA 	_  HH ]  LpHLO  P H4   LH ]  HL  Hx4   LHP ^  HLT  Hp4   LH  ]  H Lf 4   LLH r]  @ p0L(L`HXHHH8  H0HcHH]  HE?   HxfG?  )o HpfI?  )PS fK?  L) ; H5 Hf   )xIHWx  HH0 L0
x  A xA ]  _r  HL  4   LLH r  HL H4   LH0 q  HLj H4   LH  q  H L H4   LH {q   PLL@H8H@H H:  H0?  L	 Hf侽?  )	 Hf便?  )0	 Hf?  ) e	 H=~ f)NW H@p  H5֑ HH@V L@HH0o  AxAv  Lm|Hs  HvHr     H@wL@HHr  H LX =wHS(H=ʎ V IH9r  H0H5{    E1H9pr  1ҿ   LxLPL@HH`HXwL@LxHI`r  H HHP =wHȺ   H0L`H)H?LH	H`LxH4L(zHxH@ULxqr  AxArr  AE xAE r  H0xzr  H@ uq  HH r  Nc  H=> U IHc  H5 HHHT LHHIb  AxAq  H=ڌ LHT LHHǅ0    HHNb  H1y A   I9Ca  1   LH~0H`E )P9uLHHIo`  H HP =w   LLLH?L)LH	H`H`J4gxH0HHTLx]`  AE xAE `  AxA`  HH _  H= S HHa  H5 H?S IH`  x_  H={ L0?S L0HI`  Hw A   E1I9A_  1LfInݐ H`   L0)PsL0LHHb^  H- HP =wL   LHL)H?L`H	H`LL0J4vLIRLL0AxA!^  x$^  AxA,^  M]  LL
 H4   LH b]  HL| H4   LHp ]  HL H4   LH@ \  HL H4   LH \  HHL H4   LH S\  LL( H4   LH \  LL H4   LH [  HXLP H4   LHP [  H L H4   LH  L[  H@L H4   LH ;[  H=n IP H&[  H5a HH0O L0HIZ  A xA [  Ht I9ATZ  LL0trL0f.? z9Z  AxAY  PH@ xp80( h`XP 0`PLHLHxHHHpH   X  H@  E1  Hfɾ@  )  Hfɾ@  )pt  Hfɾ@  )@X  Hfɾ@  )<  Hfɾ@  )   Hfɾ@  )  Hfɾ@  ) Hfɾ@  )P Hfɾ@  )  f)LXH LuHH~W  A$xA$W  H5ׄ H  HT  LHHX LXHIU  AxAT  LHL0lL0HHXdT  AxAT  x^T  H(  S  HXjS  =wHXHP1H      H`H=& HPHXclHH0LL0MR  H =wH HP1H      H`H= L(HPHXkHH0LL0L(MkR     L(L0lL0L(HHR  LX LH(Hh Q  HhNHnAD  L- IULoHhHH   =wHhH5o H9p4  HHLhHXH      HxH`H(LHǅP    LXLhHppK HAE xAE    L`E1H8  MtAE xAE   H`x  AxA  HEdH+%(   ;  HeH[A\A]A^A_] Lls Hl0 Hl LHhlHhD  Lpl cnIH   =wAIALXLH5 H   H  LXIMV  AxAuLLXkLXHb H=k LXHSHmLXHIF   =wAHm A   E1I9@s  Hh   L0LPLPLXHǅ`    HX}iLXLPHL0H-  H HP =wL   LHL)H?L0H	H`L`LPJ4LXlL0LXLPIMtAxAz  AxA  x+  A xA 8  MW  Hk  xHk 0  ID$H5 LH   H  HH     9hIHB   Hh=wHhLHLXI@ KhLXHHPU"  x,  A xA N  MV     HxiHP    HPDi    H0i L i+ Hi L i Hhv Hh Hh Hh Hh Hh Hh Hh LL(ihL(ED  LPhK H@hX E1E11Hǅ0    E1E1E1HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    Hǅh    L`A  fD  HtxtNMEA:A.LLL(HgLL(D  HLLL(gLLL({f     g  HH5Hǅ     f  HPH3HǅP    uf	  H H1Hǅ     5f  HH/Hǅ    eLe* LeHPLXD  Le LLXeLXD  ME1A  E1Hǅ0    E1E1HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    E1E1E1Hǅ0    E11A  HǅH    E1E1Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    D  MAALLLL(3dLLL(MXIXA=wA=wA xA *  IE1IHEdH+%(   2  rH= +B  1 HEdH+%(   2  rH=o ,B  1 HEdH+%(   2  rH=F *B  1j HEdH+%(   i2  rH= -B  1A c  HHmHǅ    XMbCL  HHkHǅ    VKbA5  H`HiHǅ`    TIub?  H0HgHǅ0    RG5b=  H HeHǅ     PEa;  HHcHǅ    NCa9  HHaHǅ    LAua7  HpH_Hǅp    J?5a5  H@H]Hǅ@    H=`3  HH[Hǅ    F;`1  HHYHǅ    D9u`/  HHWHǅ    B75`-  HHUHǅ    @5_+`H=|s HHLeHHHhHcHm*  L`E1E1E1Hǅ0    E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    f     _HhH=r HH!dHHHhHH`bHhH*  L`E1E1E1Hǅ0    E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    Hǅh    @   HPH{HǅP    f[]Q       H HqHǅ     \Q]G  HHoHǅ    ZOU]E^HhH=p HHabLHM+L`aL`H1*  1L`E1E1H01E1E1HHA  H@HHHHH H HXHPHh    LpLhA=wAAE =wAE Hhx  HHHP   LHxH`H(LPLXLhHp
: HAAL[v LSHSA=wA=wx  H1    HLXy[LX
D  H`WI#@ Hǅ0    E1E1E1HǅH    E1A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    Hǅh    酽D  HHPLXZHPLX    LxZ HLXaZLXmD  Hǅ0    E1E1E1HǅH    1E1E1Hǅ@    A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    K E1E11Hǅ0    E1A  E1HǅH    E1Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP     YH=l HHL5^HHHU\HPHs(  Hǅ0    E1E1E1HǅH    E1A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP     Hǅ0    E1E1E1HǅH    E1A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    0[TI6 LXdXH=5k HHL\HHLXHWb[LXHHP1  Hǅ0    E1E1E1HǅH    A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    鞹fD  MAMaA =wA A$=wA$AxA  ME1zLxV
 LLXaVLXD  HLXAVLXD  L(V )     HVME1E1E1Hǅ0    E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    @RIH[UHNUME1E1E1Hǅ0    A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    9HLXL`HhTHhL`LXLLXqTL0LXHBhH  Hx   LLLXD LXILLPLXTLPLX]ME1E1E1Hǅ0    A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HoSLXL[SLNSLXL:SL-SSH=f HHH=XLHMGLHVLHHHX2  E1E1ME1L0E1E1A  LHL@LLLLL L LXG    +SH=e HHLWLHMLX)VLXHHP[/  1E1E1E1L0E1A  HHH@HHHHH H HXHP錴@ Hǅ0    E1E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    MLXIME1E1E1Hǅ0    A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     p;ML0HXHc =wHh HXHH      HǅP    HXQ. Iċxd  M  1L0 A$  A$  Hǅ0    E1A  E1HǅH    E1E1Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    LLtOLX#PH=b HHH}TLHLXMLHLXSLXLHHHP,  1E1E1E1L0A  HHH@HHHHH H HXHPrfLxHHfInAfInfl=wA=wHXx`  H`HϺ   HX)PB, HXHAAL	NHXHLXMLXHL0ML0uHEdH+%(     rH= .B  1 HEdH+%(     rH=a /B  1 HEdH+%(     rH=8 0B  1\ HEdH+%(   [  rH= 1B  13 HEdH+%(   2  rH= 2B  1
 HEdH+%(   	  rH= 3B  1 HEdH+%(     rH= 4B  1 HEdH+%(     rH=k 5B  1 HEdH+%(     rH=B 6B  1f Hǅ0    E1E1E1HǅH    E1A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    顮HEdH+%(     rH= 7B  1 HEdH+%(     rH=k 8B  1 HEdH+%(     rH=B 9B  1f LNKmHEdH+%(   X  rH= :B  10 HEdH+%(   /  rH= ;B  1 HEdH+%(     rH= <B  1 HEdH+%(     rH= =B  1 HLJLLJLuJHhJFH2ME1E1E1Hǅ0    E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    鋬ME1E1E1Hǅ0    E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅP    IH=\ HHH=NLHM LXLLXHm'  E11E1E1LHE1L@LLLLL L LXA  H0RfHǅ0    HǅH    E11E1Hǅ@    E1A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    Hǅ0    E1E11HǅH    E1A  E1Hǅ@    E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    Hǅ0    E1ME1E1E1Hǅ0    E1A  HǅH    Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    GHǅ0    A  HǅH    E11E1Hǅ@    E1E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    BLXH0pHǅH    E1E1E1Hǅ@    A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    鑨LE髽HE	HǅH    E1A  E1Hǅ@    E1E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    L%ELEH=X HHH.JLHMHHXHh   11E1E1H0E1E1A  HHH@HHHHH H HXH     LLXaDLXHMDмHǅ0    A  E1i鶾LDHǅ0    E1A  E1HǅH    E1E1Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    j5@LXH0邵E1HǅH    E1E1E1Hǅ@    A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅH    E1E1E1Hǅ@    A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    aHǅH    E1E1E1Hǅ@    A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    HǅH    E1E1E1Hǅ@    E1A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     {CIH   =wAIBLLH5^Y H   H6  LH0H0 o  AxA/  LCH  H=He     H1?LHH  H\ LP =wL%NV HS(H=ST IT$LBH HHh   =wH0H5oB E1ɹ   H9p!      LPLHHǅ`    HXt>LHI  HW HHP =wH    H0LH)H`HH?H	H`H4LALH MtAxA  x~  H xs  A$xA$  H0x  H  1E1E1H0L 1L E1E1HHA  E1H H@HHHHH H DLLX>LXgHL0>L0LLX>LXHǅ0    E1E1E1HǅH    E1A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     HǅX    ΠL`HXA$fInX=wA$=wH0x  H`   H)P IA$A$LL0l=L0HLQ=LP >H=P HHLZBLHMLX@LXHK  E1E1E1E1LHE1A  L@LLLLL L LXD  HX<ٴLPL`A=wAA$=wA$H0x^
  L01\HL00<L0ڵHL0<L0еL<°<H=O HHHALHMrLH?LHH)  HXE1E1E1LHE1A  H0L@LLLLL L (     HXE1E1E1HǅH    A  H0Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     鱝|7L0H 韲H:   	  H5`Q HHLLX?HHLXH  HXHH      LXLXHǅP    Y LXI HL0LX:LXL0L9?HH0)9foH0vLLPLX9LXLP\:H=-M HHH>LHM׬a=HXH  11E1E1H0E1E1A  HHH@HHHHH H HXЛHǅ0    E1E1E1HǅH    E1A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     aHǅ0    5LXI(9H=K HHH=HHH0H&<H  1E1E1E1HHE1A  H@HHHHH H 鬚@ H0l4I鮰HǅH    E1E1E1Hǅ@    A  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     (1A  E1E1H01E1HHH@HHHHH H љHǅ0    E1E1E1HǅH    A  Hǅ@    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ     ZIYMafHnX=wA$=wA$AxA8  H`   L)P8 IËODHL06L0)1E1E1E1H01A  HHH@HHHHH u1E1E1E1L0E1E1A  HHH@HHHHH H HXH6 LH5 H8141L`E1E1H01A  E1HHE1H@HHHHH H HXHPHh邗M`IXA$fIn =wA$=wA xA |
  H`   H)P` IA$߭A$ҭLL0%4L0鷭H5 H`E1E1H5h H8131E1E1H01L`A  HHH@HHHHH H HXHP[11E1E1H0E1E1A  HHH@HHHHH H 1E1E1E1L01E1E1HHA  H@HHHHH H dHU4 HhH5) LhH81^2LhE11A  E1H0E1E1E1LHL@LLLLL L 1E1A  E1L0E1E1HHH@HHHHH H 鿔H0LLX1LXLuH)1foa2IWLXHo3 HR1E1H5? L(A  E1H81111L(H0E1E1E1HHH@HHHHH H HXL0HL0L21E1E1E1HHE1A  H@HHHHH H 
LL0y0L0鬮H1 LE1E1H5 A  H81/E1E1E1L0E1LHL@LLLLL L LX鿒HL/LL/1E1H01H1LE1E1HH1E1E1H@A  HHHHH HL0P/L0ҮHL05/L0ȮL!/鈯L//H=B HHH$4HHH0H2H*  1E1E1E1HHE1A  H@HHHHH H N9/H=
B HHH3LHM>2H;*  E11E1E1LHE1E1L@LLLLL L A  H0麐HL-L躱 Hh4   LH   HL 4   HLH (  HL辰 H@4   LH`   H Lб 4   LLH y  @ pLhLHHHHRJ  H0Hc0HH
  Hhh?   fj?  H)ٻ H@fl?  )轻 fn?  L)`襻 eLH,H;,HL',L%H,uH,L+J11A  E1H0E1E1HHH@HHHHH H m1E1E1E1HHA  H@HHHHH H H0'I4+H=> HHLP0HHH Ht.H&  E1E1E1E1LHE1E1A  L@LLLLL 1E1E1E1HHE1A  H@HHHHH H ,1A  E1E1HHE1E1H@HHHHH H یL)0)fo0L)0)fo0hL)L頦L0s*H=D= HHL.HHL0HH mLHc-LHH$  1E1E1E1H01E1A  HHH@HHHHH 1E1E1E1HHA  H@HHHHH H 钋1E1E1E1HHA  H@HHHHH H DLl(L0鹨HX(L§LLL06(LL0LL0(L0E11E11A  E1E1H01E1E1HHH@HHHKLLL0'LL0XIrIZH0=w=wAxAq
  IE1L0'H=: HHHW,HHL0HHLH*LHH	  1E1E1E1H01E1A  HHH@HHHH #E11E1E1H0E11E1LHL@LLLLL A  LL0<&L0ʣ"LH0&H=9 HHH-+LHMߣ)H  11E1E1H0E1E1A  HHH@HHHHH \L%5"L0I鎣H& LE1E1H5 L(A  H81$E1E1L0E1LHL@LLLLL L LXL(鲇1E1E1H H LE1E1A  E1E1H01HHH@HHHHH H H% HE1E1H5 A  H81#1E1E1H01HHH@HHHHH H ̆1E1L E1L0E1E1E1HHA  H@HHHHH qIZMb=wA$=wA$AxAH  M1)11E1E1H0E1E1A  HHH@HHH陻MYMaA=wAA$=wA$AxAv  ME1מIHH$ LE1E1H5 L(A  H81I"1L0E1HHL(E1H@HHHHH H HXH# E1H1H5 LE1E1H81L(!LHL(L@LLLLLL L LXA  H0|1E1A  E1L0E1E1E1HHH@HDH" HH5 H81	!LXl11E1E1H0E1E1A  HHH@HHH؃E1E1E1E1L0E1E1A  LHL@LLL鑃E11E1E1H0E1E1A  LHL@LLLLDH`IGH $LHL`A=wAA$=wA$H0x  L01H! HME1H5W L(E1A  H8111L(H0E1HHH@HHHHH H Q1E1A  E1L0E1E1E1HHH@H1E1A  E1L0E1E1E1HHH@HIPHH=wHZH=55   H   1A  E1E1H01E1HHH@HHHWLLr1E1E1E1L0E1E1A  HHH@HLH9 LH11A  E1H0E1E1HHH@HHH鰀H    H5} LHH81lLHH4 LH5 H81HLXH HH5 H81!LHH HH5 H81H HH5 H81LH1LL0L0H HH5\ H81L1E1E1A  H0H= HE1E1H5 A  H81E1E1E1H01HHH@HHHHH H HPֲ1E1E1A  H0霷1E1E11H0A  逷=wHXLXHP1H      H=5 H`LPHXLHHt;HhW1A  E1E1H0'~1E1E1A  H0~1HXE1A  H0}H镫1HXE1E1H0A  }LLXLX1HXE1E1H01A  CLLL07L0HIA xA   ICL0LH   L0HIp  LLHLLHH0t`LH] LLt-AxA  H0LH=A  E1E11   AxAt\LHZ LHt]1A  E1E1H01E1E1HHH@HHH̱LLH;LHHL(E1E1- 1A  E1H01L(E1HHH@HHHY1LLLE1E1A  L0E1j{1A  E1E1H0E1M{L0m0HXT1AA鷥L0 L0H1A  E1E1H0z1E1A  H0z1E1E1E1H0A  z1A  E1E1H0E1}z1E1E1E1H0A  `z1A  E1E1H0E1Cz1E1E1E1H0A  &z1A  E1E1H0E1	zE1E1E1A  L0E1yE1E1E11LA  MH0E1E1E1E1|LL0L0LL0ˡHL0L0Lǡ11E1H01IA  E1HHE11E1E1LL0SL0L?HL0+L0HL0L0鈟MiIYAE =wAE =wAxAt)IE1 E1E1E1E1L0A  txLL0L0IsMkH0=wAE =wAE AxAtpME1
E1E1E1E1L0E1A  钭1E1E1E1H0E1A  wE1E1E1E1LHE1E1A  nLE11E1E1L0A  E1HH}w1E1E1E1H01A  HHWwH=+   H     HHLHHI*  H=wHHIB =wHHIB(=wHH5[. L0H`LHIB0  LHL0HHe  H    E1I9KU  H   LLXH)H?LH	H`LHLPH4H`b  LH0LLHAxA*  x  AxA  H0   H0H5( H  IH+  x  A=wAH`H=w- 11H      LPLHHXHHILHAxA  M  H5) LV  IH  HLHH訖 4   LLLHH 9  AxA  H5<* L  IH  HLHH HL4   LHH0 }  AxA]  H5) L  IH  HLHH蠔 HL4   LHH  <  AxA(  H L H4   LH    PLL@H8H@H HV(  H0/A  L՟ Hf1A  )蹟 Hf3A  )0蝟 Hf5A  ) 聟 fLL)k H4   LH   HLݓ H4   LHp `  HL H4   LH@   HL H4   LH   H5& L  IH  HLHH5 HL4   LHH   AxA  H5e' L  IHq  HLHH/ HL4   LHH   AxAn  H5' L  IH`  HLHHɑ HL4   LHH X  AxA8  HXL H4   LHP   H Ls H4   LH b  H@LE H4   LH  4  H='   IH  H5& HHH  LHHI  AxA  Hc I9C\  LLH"LHf. z  AxA.  Vxp80( H@ h`XP 0`PLHLHxHHHSH   Q  HA  E1Z HfҾA  )> HfҾA  )p" HfҾA  )@ HfҾA  ) HfҾA  )Κ HfҾA  )貚 HfҾA  )薚 HfҾA  )Pz HfҾA  )^ f1HH) 頚ACLH
HE1E1A  E1L0E1E1LHum1E1E1A	  H01HHRm1E1A  E1H0E1E1LH+m1E1E1A	  H01HHmL0HHL0H11A	  E1H0E1E11HHE1qE1E1E111E1E1A  HHH@EE1E1E1E1L0E1E1A  LHL@Sl1E1E1E1L0E1E1A  HHH@"l11A  E1H0E1E1E1HHH@kH= f  IH;  H= H;=D
   HH@   tH;k
   HLH"LHIM  H
 E1   I9Z  H`H   LH?H)LXH	H4L0LHLPe  LHL0LHAxA  AxAtMHtZ1H  xJt;E11A  E1L0E1E1E1HHH@jLHE11A  E1H0E1E1E1LHL@ZjMbIZA$=wA$=wAxA}  I1MkISAE =wAE =wAxA  I1f1E1E1E1HHE1E1A  H@FE1E1E11E1E1E1HHE1A  H@qi1A  E1E1HHE1E1H@Ji1E11E1H01A  E1E1HHE1E1H@ҡLPLhA=wAAE =wAE H0xtL01݌H0LL@L@LHL{L遍LLHLHLnH{y1E1E1E1H01E1A   HHh1A  E1E1H01E1E1HHgE11E1E1L01E1E1HHA   鈠LLHHe LH5= H81yE1E1E1E1L0E1E1A  LHL@L[gH LH5 H81 LHLL0UL0oH HH5 H81ZH0LLH HH5c H81LL0L0^1E1E1E1H01E1A  HHH@ofL݉11A  E1H0E1E1HHH@5f11E1E1H0E1A  HHH@fHLHULHI^LLH1E1E1E1H01E1A  HHH@TLLHLHh1E1E1A  H01HHde1E1E1E1H01A  HH>eE11A  E1L0E1E1HHe11E1E1H0E1A  HHd11E1E1H0E1A  HHdLE1E1E1A  L0E1LHdE11E1E1L0A  HHudE1E1E1A  L0E1LHPdE11E1E1L0A  HH,dE11E1E1L0A  HHdL011E1E1H0A  HHcL 11E1E1H0A  HHcLLH LH[1E1E1A  H01HHjc11E1E1H0A  HHGcE11E1E1L0E1A  HH cLH `1E1E1A  H01HHbL E11E1E1L0A  HHbL1E1E1E1HHE1A   bH0LHLH1E1E1E1HHE1A  SbL{(HLHgLHJLSPE11E1E1LHE1E1A  H0鴚LH0LHLHH0ff.     UfHx fHnHSH   dL%(   LEI)EHx  HP  )EfHn~ HE    fl)E~ fl)EfHn)EHt0LIHM~$I  H3 JcH>f     I  H' JcH>D  HV =wHUHV=wHUHV=wHUHV=wHUH=wHUHL H]ARJ4HUHLx: _AX   H} Lxm  H} :  H}   H} l  M~%      ff.     II  J< uH HHY H5 L HN H8AP1A   Y^HH]H8HtxtDHH9uHԧ W  H= u 1HUdH+%(     H]     HxtHx 11E1LNA=wAH>LM=wH}H   H   H]M
  L[HH]H:Htx-  HH9u>    1E1HV=wHUW     E1HN=wHMD  H>=wL H}A=  LMA1E1H =wHUHH wHEHH]MH 0w0HEIH]D  LF A =wA LE HpHxHpHxM   Hڜ    L/ HW HH5L H]H8AP1IH XZk H}LMHUHMLE    Hi =wHUf.     L A=wALMsH wHEuH wHEJH    L; 
     LMf1f/ ff.     HGH9G fff.     UHATSHGHP AHu&EuHC[A\] @ [O A\] H [  H= 0q [fA\]    UHATSHGHP AHu&EuHC [A\]@ [ A\] H `  H= p [fA\]    UHH0dH%(   HE1H HE    fHn)EH   LIHM   HS  H   H HH8RH5 L 1A   HE H* i^_H}Htx=  H՚    H=Z o HEdH+%(     1fD  HmH=wHUH5 H= 6  H=    Hb ~o H}HtxuyfD  H=wHHUHMHUH< A   HP 4 AXAYefD  HHMHUE1L AR3 ZYH} ,HN HH8j ~[UfHAWAVAUATSHXdH%(   H]HHE    )EHCHP AH  E  HCH}Hp6 HEL{ fHE    LeLm)EHEHCH Lp(MM9thfoff.     AIVIF    I~IvAFAoFIVAFANHtH)PfAV I(AVM9uLs I~IVHS HtIvH)M)ItSLM LELKt,H}`    ff.     ff.     HcHJHHJHHA H9uH}Hk0HtHuH)MtHuLL)HEdH+%(      EHX[A\A]A^A_] n  H H= l H}HtHuH);E    fH =wH
 HuHH      HE    HE  Iċxt*Mt1L  A$x	A$to  UHLH UHAWfI~fAVAUATISHcHH(  dH%(   HE1HG H+GHǅ0    HHǅX    H) HH;G0   HGPH  fInf/rbHHHtHXH)H HtH0H)HEdH+%(     H(  [A\A]A^A_]    L ;uNw    HH(H   HHHH0  HHHH   Hc;t+H(H;0uHL輄 f.     =u@_    HH(HcHHE HIHE`HUt!H(H;0uHLB HHLL@ʂ IL$`ID$ HHH)H  HHHH@HH HHIHPHH)HHpHMM  HpH9  HHHfHnHHHUflHxMH IKHL{HCEL)X  HHHLHHHH}HHAHxHtHuH)EM)HC(IH MI\$(H9  @H H9  LHHPL)  HIHLHIL<HL HAAHYHA    HAAoAA HA(AfAID$ I9tSfoCHCH(HC    H{0Hs@C(oCHC@C0KHtH)fɋC CHI9uH HxHpLpLxLx8HtH)mH M|$ H ID$HHLH+HH'fD  IwH)M|$ LI+D$HHI9D$0"IIGID$ HuID  HH}pA     Hǅx    HE    A     E1E1QD  HPfH+H6HF    F  HPHH fHnHfl@HHHXHPH)H~HHHH HHLx(H M|$  HL H3333333L+H9mH   HEHH3333333H9HGL,IL@IIHHHPIG    AfAGH)B  HHH?HfHnHHflHAGIOHHH IOAG HH9  Lfff.      HHH(H(Bo@HJHBJH9uH H+HH(HHHH!HDM<HH I(H9   L@ ff.     ff.     ff.     ff.     ff.      HHH(H(Bo@HJHBJH9uHHH(H+ HHHH!HDM<HHtHH)MMt$M|$ Ml$(L8@ 1f     HI\$(H9H E11vfD  B  Hd H= b IIG    1IG    MOH5>HHt    UHH0dH%(   HE1HPHH   H5 H=   H    H=V a HEdH+%(     1fH) HE1L H H5 H8R1H XZ    Hy xoHAHE       t[H@h1PHEHHlH Hi H5x H81fH}?4*HE    HMH}1HUHuHM=w{ff.     UHAWAVAUATSHhHELU0Le(HEHE HEHE8HEE  HEHMIMLeLMHHEABIE1HEMiL9mL  L;MB  HEHUHc8M9   M9   I?HHLEILMHLxHLpHEIHLLH   I9   XII9   Mc M   M9   LeLmHHHMC\D% A9ELMLxLpHUH]HUL;M   Mf     MIx=XIIMx&N$ML+mMOcd% M[M[H 1H5 H81HhH= [A\A]A^A_]W     Hh[A\A]A^A_]ÐUHAWAVAUATSHXL}0E_  IHHHM HUH}M1LMH<
AWHUHM(HU(EE1H}HMHHHIBHEH9E3  L;U)  HE L]D!IIcA9   IMLMH}LL]M\ LLELELUMH  L9   L9   LULL)BHH}Lc;M   M9   LH}8XH}(f/v H   L9}iM   M9}[HIIA9iLUH}L;U   HEH}8HM I9t I     LLv@ H 1H5 H81H=ח U 1HX[A\A]A^A_]f     LHxLMxAfD  MxM2M.뇋EH׃A9L]Le1S HML]LeLeLRI9FH9=HEH}DHE HHcA9   H}MD ILULHULH}LHH   L9L9IM)CIHcH   L9HU8XLU(XAf/w~HHA9LUHUH;UtLHU HUHU8HUM9bLf.     LHDLH8cMLjE7@ ff.     UHAWAVAUATSHXL}0E  H]IHM HMHMHHA_H1H]H](HME1IHMH]H]ȉEHMIAHEH9E1  L;M'  HEH]DHE IHcA9   H]L8LMLL]HHKL](HH   H9   L9   IIM)AAT L9   HU8f(XAf/vAXf/vHUf(HHA9LML]L;M   HEH]8H]H] H]I9t8IHx+LHx#I	AT L9ifff.     H 1H5H H81fH=_ jQ 1HX[A\A]A^A_]ËEHMLڃA9OH]L]E1 HMZL;]}L;UtHE H]D
IHcA9   H]LL]LHUH]JHHHH   H95L9,IM)AIIcT H   L9HU8L](XA\fTv f/wyHHA9L]HUL;UtGH]8HU H]M9Mf     HHLH	_LggD@ ff.     UHAWAVAUATIHSH  HEH   HHXLLHHdH%(   HE1HPHH   HHH   HHH   HHA$=wA$L-K H= IULHHH%   =wL5 H= IVLIH'   =wAE H    E1H9C(  H   HHǅ    LLH LIHd  H HHP =wH]    HH)HHH?H	HH4LH`HMtAxA  AE xAE #  AxA   x  H   A$xA$  HH5 HGH   HZ-  IML,  11L׹   L ! L HH=  AxA  HVc Aă  x  H H= HSHIH   =wAIFH5! LH   H?  IM$  AxA%#   xIH\$  H H= HSHIHF?   =wAHH    E1I9E@  H   LL HHǅ    HL ?L HH+  H HHP =wHȺ   LL H)H?LH	H`H4HfL HMt#AxAuL|ff.     AxA-  AxA
  x  AE xAE   H *  H H= HSHIH@   =wAIAL LH5 H   HA  L IM@  AxAuLIcHH@IHzA     H L HI;  H=wHH MN(H= IF HSHIHA   =wAH A   E1I9GB  H    LHǅ    LLH LHH$>  HI HP =w   LHLH?L)LH	H`L J4ML HtAE xAE ?  AxA&=  AxA=  x<  AxA<  H I=  HH;= AL% H;= E	L9Dʈu5J  fIn)0)  H H= HSHGIH=P   =wAIBL LH5 H   H:  L IMQ  AxAK  HL H52 HGH   HfS  L IMR  IBLLL H5 H   H)V  L LHH $U  AxAJ  H I9AW  HHLH      Hǅ    HL  HH Hx_J  xAJ  Hǅ    E1Hǅ    H  pV  HH;5 H;5m ;  L9;  HcO  ]?  H=wH H= HSHIHZY   =wAIBLLH5 H   H[  LIMZ  AxA~M  H H=8 HSHIH\   =wAHb    E1I9F\     fInL HHǅ     )bLHHR  H HHP =wHȺ   LL H)H?LH	H`H4HMLHtAE xAE V  AxAOO  xKO  AxAEO  H IQ  HHHRZ AŃZ  HX:Z AƃZ  H`   1ǅP   HL9 VF  H L`HPL       HV Q A[[Ed  foH)Pfo H)`fo)pfo )fo0)fo@)foP)fo`)fop)foE)foE)foE) foE)HR  HH59 HGH   HY  HHQ  H`   1ǅ    HL9E  HL`H L S      Hx O AYAZe  HHHH HHH@HHQg  xM  HH5f HGH   H_  HH^  H`   1ǅ    HL9E  HL`H L S      H N _AXh  HHHH HHhH@H(Hj  xO  H`1   ǅ    HHL9%F  H   L`Hj H    L N ZYi  foH) fo H)0fo)@fo )Pfo0)`fo@)pfoP)fo`)fop)foE)foE)foE)foE)HW  HH5; HGH   HC`  HHmW  H`   1ǅ   HL9jG  HL`HL S      Hz L _AXi  HHHH HxH H@HHk  xT  HH5i HGH   Hd  HHc  H`   1ǅ   HL9I  H   L`H SH   L K ZYyj  HHHH HpHH@H H+p  xU  H`1   ǅ   HHL9tLHL`HL P      H K AYAZd  fo)0fo fo0) fofH~))0fo ))@fo0f֝)Pfo@)`foP)pfo`)fop)foE)foE)foE)foE)Hd  H`1   HHG HHL9K  HL`HL       H I _AXac  HHH HHH@HHHFd  LHL HPWDVDQRP`  fo H   $fo0D$fo@D$ foPD$0fo`D$@fopD$PfoD$`foD$pfo$   fo$   fo$   fo$   fo$   (hfoPH   $fo`D$fopD$ foD$0foD$@foD$PfoD$`foD$pfo$   fo$   fo$   fo $   fo$   LLHH  H   H&d  L9tC8]f  HL9tH¸B8f  HL9tH¸B8g  HL9tH¸B8Jh  HxL9tH¸B8g  HpL9tH¸B8g  HHt#L9tP8Hǅ    h  Hf)L9tH¸B8h  E#  H f  HHGHPpHd  HRHd  HXHHkf  HHGHPpHTj  HRHGj  HIMYx  LHLLHIw  xAk  AxAi  HLyHHr  AxAi  Hxi  HHHa =w ~HIH$j  H1H:IHyi  AxAM]  HHH      Hǅ    LP  HAxA]  x]  H j  H@;IH/j     HLHHj  H=wHHHHH; HP LH(H;t 0V  L9'V  HHbk  HHRHZpW  HVm  H{ Km  HLLIHIm  HHSIAxAj  M֎  AE =wAE    IH  H=wHH`1H      H= IG LLHAE j  AE *m  AxAj  AE xAE j  H[l  HH@LppMon  I~ dn  HLLpIHbn  HHAVIAE xAE l  M3n  A$=wA$HH`1H      H= LHIA$x"A$Xn  A$xA$6n  Mm     _IH  HHX Lh(d  Y  HLL>  @ L L H L LHI AăJbfHxJ LhK LX/ HH
 L8 L( HHǅp    1A   E1Hǅx    E1E1E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ       H= HH%LMHH2Y  Hǅp    1E1E1Hǅx    E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    	  @ E11E1Hǅp    1E1E1Hǅx    E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    LA   fMtAxA  Htx  MtAE xAE   MtAxA   MtAxAH  EuHhC8	  L%ڿ MtM9tAC8
  HHtL9tHƸF8
  HHt#L9tH8Hǅ    .
  Hǅ    HHtL9tHƸF8L
  HHtL9tHƸF8e
  HL9tHtHƸF8~
  HHt#L9tH8Hǅ    
  Hǅ    HHt#L9tH8Hǅ    
  Hǅ    HHt#L9tH8Hǅ    
  Hǅ    HHtL9tHøC8
  HHtL9tHƸF8
  HHtL9tHøC8  HL9tHtHƸF8$  HxL9tHtHA8=  HpL9tHtHøC8V  L9tHtB8y  `Hf H=p 04 HHtx  H t"E1Hx~  LH  tH xu  HHtxh  HHtx[  HHtxN  HHtxA  HHtx  HHtx  Hx  HEdH+%(   ^  HHe[A\A]A^A_]fD  LHHLPLXSHHLPLX!f     HHHLPLXHHLPLXf     LHHLPLXӹHHLPLXf     LHHLPLX蓹HHLPLXf     LHPLXZHPLX    H8_ H(l Ht HLLcH~ Hظ Hȸ H踸 H訸 H蘸 L舸 ;H= HL蕽HH'@HF  L1E1E1Hǅp    E1E1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    ǅ`  ?Hǅp    1E1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    ǅ`  E    H= HLULM HF  L1E1E1Hǅp    E1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    ǅ`  @ L{LsA=wAA=wAxw  L1D  )  HhHHPLX耴LXHPD  )  AALHh<Hh)  HHHhHh )  HHHǅ    H讳Hfv)  HHHoHw _)  HyHH/H^ *  Hk`HHHE )  HHfHǅ    QFH螲H.f)  HHPHǅ    ;0HNHf)  HH:Hǅ    %HHf)  HHH迱H o)  HHHH X)  HHH?H A)  HHHH *)  HxHH述H )  HpHHHm (  wlHM_     Hǅp    1E1E1Hǅx    E1E1A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    ǅ`  ?HԫI@ E1E1E1E1Hǅp    1E1A   Hǅx    E11Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    MAALHHLPLXHHLPLX    HH5" HGH   H'  HHX  =wH`1H=Z H      Hǅ    H詪H x"  xuH.H    H H= HSHIH)   =wAIALLH5F H   H+  LIM)  AxA=!  H5 H 19HH.  HZ I9G/  HHLMH      Hǅ    HC  HHx!  AxA!  H/  H; H;ۭ   L9  H_Aǅ0  xn$  Hǅ    Hǅ    EH H= HSHzIHE   =wAIALLH5r H   HwE  LIM:  AxAY9  H@FIH9  HS H=| HHSH٬LHI:9   =wAH    E1I9FG     LLLHHǅ     L薨LLHH?  H HHP =wHȺ   LLH)H?L H	H`LH4H诫MLLHtAxA)A  AxA<=  AxAD=  x@=  AxA<  H >  HH;5t H;5B 1  L91  HƬ]J  H`       ǅP   HH ;2  L92@  H L`HPL       HX ' A[[h  HHH(H HHxH@HpH~Z  HhHH5 HGH   H_X  HHS  H`   1ǅP   HL99B  AVL`   HPSL    H -& A_ZXc  HLHH HH@HMb  x?M  HLH5 HGH   H"Q  LHH(Q  H`   1ǅP   HL9C  L   HPL AVL`H    S?% A_LZ`  HH@LL HHH`  xaO  H`1   ǅP   HHL9AC  LH    HPRL`L    P$ YL^b  fofo fH~))) fo)0fo )@fo0)Pfo@)`foP)pfo`)fop)foM)foM)foM)foM)Ha  L L`LH HpHxH(Hd$f<$AWAVH0HcFL HHa  HhL9tP8Ѓ`  M9tAC8b  HL9tP8Ѓb  HHt"L9tP8E1Lb  H5 Hf   )HH(S  H;H AH; D;  L9;  H蘧AƅP  xI  ERQ  H`1   ǅP   HH L9?  AQL`HPL P      H ! AZA[V  fofo fH~))) fofօ)0fo )@fo0)Pfo@)`foP)pfo`)fop)foM)foM)foM)foM)Hh  HH5 HGH   Hg  HHS  H`   1ǅP   HL9A  VL`HPL S      H= h  _AXSg  fofo fH~)))fofօ) fo )fo0) fo@)0foP)@fo`)Pfop)`foM)pfoM)foM)foM)He  xG  HH5 HGH   HU  HH}R  H`   1ǅP   HL9A  PL`H    SHP   L  ZY^  fofH~HH`)fօ4   He  xQ  HH =$ H4   H HHHvc  A    L0LHH`H H舷HPH0I  / HfI  ). HfI  ). HfI  ). f)    Hǅp    1E1E1Hǅx    E1E1E1Hǅ    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    Hǅ    ǅ`   fD  Hǅp    1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    E11A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    ǅ`   HH| Hǅp    1E1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    E1E1E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     UL IH ۘIb H= HHELMHHHq HH5I> H81腛111HpE1E1HxHHHHHHHHHhHHǅ    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    ǅ`   L4 H L LL њL D  MUI]A=wA=wAE xAE   I1- E1E1E1E1Hǅp    1E1A   Hǅx    1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    O    +H= HH腞LMdL )L HH:  fHǅp    1E1E1Hǅx    E1A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     Hǅ    ǅ`  -    L L @ 諔L IL@ Hǅp    1E1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ        H= HHuLM@L L HHH HE11H5f9 LXA   H81蕖1LX1HpE1HxHHHHHHHH1HhH1HHHHHH ǅ`  fD  MoI_AE =wAE =wAxA  IE1f.     HH5 HGH   HM&  HHHw%  =wHH`1H      H=^ Hǅ    H迒Hx!  xH  H %   uH讘AŅ(  E  E  HH5[ HGH   H8  HH0  H`   1ǅP   HL9e$  HL`HPL S      H  AZA[y=  fofo fH~))) fofօ)0fo )@fo0)Pfo@)`foP)pfo`)fop)foM)foM)foM)foM)H:  x.  HH5ݫ HGH   H>:  HHn/  H`   1ǅP   HL9'  HL`L HPS      H G AXAY C  fofo fH~)))fofօ) fo )fo0) fo@)0foP)@fo`)Pfop)`foM)pfoM)foM)foM)H9  x0  HH5w HGH   H8  HHN2  H`   1ǅP   HL9(  H   L`HPSL    H  ^_R  fofo fH~)))fofօ)fo )fo0)fo@) foP)fo`) fop)0foM)@foM)PfoM)`foM)pHP  x1  H 0  H`1   ǅP   HHL9Y*  H   L`H PHP   L x ZYqD  fofo fH~)))fofօ)fo )fo0)fo@)foP)fo`)fop) foM)foM) foM)0foM)@HF  Hd$f<$ L0LHH`H H迦HH0Ht#L9tP8Hǅ    B  Hf)Ht#L9tP8Hǅ    F  Hf)Ht#L9tP8Hǅ    F  Hf)Ht#L9tP8Hǅ    F  f)HH5m HGH   Hm,  HH 1E1E11HpE1E1E1HxE1A   HHHHHHHHLhLLǅ`
  R@ D    Hǅp    1E1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  fH HfoH)Pfo )`fo)pfo )fo0)fo@)foP)fo`)fop)foE)foE)foE) foE)    LL 蹋L δD  HHǅ    Hǅ    Hǅ    fHs鲵Hf锵LYLL EL H1HHǅ    Hǅ(    Hǅh    ʺHLLL ԊL CHUdH+%(   .  p&K  H=7 1 HUdH+%(   .  p(K  H=]7 1 HUdH+%(   .  p'K  H=47 1] HEdH+%(   u.  q)K  H=7 14 HUdH+%(   L.  p*K  H=6 1 HUdH+%(   #.  p+K  H=6 1 HfoH) fo )0fo)@fo )Pfo0)`fo@)pfoP)fo`)fop)foE)foE)foE)foE)HUdH+%(   0-  p,K  H=5 1 HEdH+%(   -  q-K  H=5 1 HEdH+%(   ,  q.K  H=t5 1 HEdH+%(   ,  q/K  H=K5 1t HUdH+%(   ,  p0K  H="5 1K HUdH+%(   c,  p1K  H=4 1" HUdH+%(   :,  p2K  H=4 1 HUdH+%(   ,  p3K  H=4 1 HUdH+%(   +  p4K  H=~4 1 HUdH+%(   +  p5K  H=U4 1~ HUdH+%(   +  p6K  H=,4 1U H=L0uHxHǅ     Hǅ    Hǅ    蹇H= HHLM辊H?  E1E11E1LpE1LxLLLLLLLLLhLHǅ    E1E1A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     ǅ`  H蚂HQHǅp    1E1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  E1E1E1Hǅ    Hǅ    Hǅ    (Hǅp    11E1Hǅx    E1E1E1Hǅ    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     ǅ`  L7餰H*騰L鮰HpHǅ     Hǅ    Hǅ    鴶HڲHǅp    1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    HL I鋬H= HHJLMLLHB  Hǅp    1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    E1E1A   Hǅ    Hǅ    Hǅ    Hǅ    ǅ`  E1E1E1H1E1E1Hǅp    1E1A   HHǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    }LIrHǅp    11E1Hǅx    E1E1E1Hǅ    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ     ǅ`  &|LL HϩH%H H=魬H1111鲴LLLHǅp    1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    E1E1E1Hǅ    E1A   Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    ǅ`  #Hǅp    1E1E1Hǅx    E1E1A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    ǅ`  [MqIYAfIn=wA=wAxA  H`   H)\  H AAL}Hǅp    11E1Hǅx    E1E1E1Hǅ    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    ǅ`  ͽL|LHIOMwfHn=wA=wAAxA  H`   LH)Z  HHË>3H[|&HN|Hǅp    1E1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Ss|H=D HH̀LMxH5  E1E11E1LhE1LLpLxLLLLLLLLE1H1E1A   HHHǅ`  Hǅp    1A   E1Hǅx    E1E1E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    H1E1E1Hǅp    E11E1Hǅx    A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    Hǅ`  H1y%uLIF}H111A   Hp1E1E1HxE1E1HHHHHHHHHhHǅ`  H鄹q|HBi.yH= HH}LMǣ3|H~>  E1E11E1LpE1LxLLLLLLLLLhL HdtHHHwGMnI^AE =wAE =wAxAf  I1HQw&Hǅp    1Hǅx    Hǅ    E1E1E1Hǅ    E1A   Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    ǅ`  ķL9  H L`HPL       Hi   AYAZh5  HHHxH HH H@H(H(  HHH5 HGH   Hg&  HHK"  H`   1ǅP   HL9  PL`Hf    SHP   L   ZY+  HHHH HHhH@HH<*  x  HH5 HGH   Hu%  HH$  H`   1ǅP   HL9  AQL`HPL S      He   AZA[a6  HH@LL HHpH5  x`  H`1   ǅP   HHL9  RL`HXf    PHP   L j  Y^*  fofo fH~))) fofօ)0fo )@fo0)Pfo@)`foP)pfo`)fop)foM)foM)foM)foM)H?)  `LLh HH(H Hd$Hxf<$pAWAVyH0Hc-vHH)  HL9tP8Ѓ.  HL9tP8Ѓ)  HL9tP8Ѓ&  HHL9P8E1L9  HH1HrfD  Hǅp    1Hǅx    Hǅ    Hǅ    :HanHܠLqH-s LH5 H81AqEL@rH= HHvLLM>uLHu"Hr HH5 H81pLHǅp    1E1Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    E1A   Hǅ    Hǅ    Hǅ    Hǅ    ǅ`  FfInHǅp    1E1E1Hǅx    E1E1A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    ǅ`  HlHHp LH5 H81nBHǅp    1E1E1Hǅx    E1E1A   Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    Hǅ    ǅ`  邯HkH鮟Hǅp    1A   E1Hǅx    E1E1E1Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    鼮H"  H{   HLLoIH  HHSHA$xA$  H  =w   vkIH'  H=wHH`1H      H= IG HL=jI    AxA  x  M1  H   H߰適LxlLLdlLLPlHClHǅp    1E1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  E1E1E1Hǅ    Hǅ    fInHǅp    1A   Hǅx    Hǅ    Hǅ    Hǅ    Hǅ    E1E1E1Hǅ    E1Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    鸫E1E1E1E1Hǅp    1E1A   Hǅx    E11Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    Hǅ    Hǅ    Hǅ    Hǅ    ĻHǅp    1HlfHHǅp    1Hǅx    Hǅ    Hǅ    Hǅ    E1E1E1Hǅ    E1A   Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    ǅ`  fInHi颢LiڢHhޢHHǅx    Hǅ     Hǅ(    HhHǅx    Hǅp    Hǅ(    *LhLL鼾ExL) fhfo A1A   1HpHxHHfHP4   H`)Hǅ    1A   E1Hǅ    E1E1E1Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    霨Hi HH5	 E1H810gE1E11LhE1LE1LpLxLLLLLLLLLH)gfoHK11E1E1HE1E1A   HHH1HhHǅ`  霧E1E11A   Lp1E1E1LxE1LLLLLE1LhLǅ`  H+11HpHxHyfIn1HHHHh|1IHHH^bLI遺jfH=;y HHjLM%LhiLH+  E1E11E1LpE1LxLLLLLLLLLhLjHdiE11E1HLE1E1E1LA   LLE1HhHǅ`  L鑥1A   1HpHxHǅ    E1E1E1Hǅ    E1Hǅ    Hǅ    Hǅh    Hǅ    ǅ`  Hǅ    E1HE1LpE1dfInx11E11HpE1E1E1HxE1A   HHHHHHHHHhHLLǅ`  _1HE1E1H鍼fIn%fInHPhH%  Hz %  HXH  HKE1A   1LpmM~I^A=wA=wAxA6  I1  HH{bt11HpHǅ    E1E1E1Hǅ    E1A   Hǅ    Hǅ    Hǅh    Hǅ    Hǅ    ǅ`  LLaLO$  HHaӘ$  HޘӘHaƘH^HHdaJH c H H52 H81`1E1E11HpE1E1E1HxE1A   HHHHHHHHLhLLǅ`  鸡p  Hx)H`w&  HpHa`fIn>  HH(`釗  HH1HїƗ_鼗#  HҗǗH_麗Hwa H\ H5 H81G_11E1E1HpE1E1A   HxHHHHHHHH1HhH1HHǅ`	  
H_^fInRHxͥLT1E1A   1HhHǅ`  LpLxLLLLLLLLE11E1E1E1HHHH5H_ HE1E1H5  LXA   H81]11LXHp1E1HxHHHHHHHH1HhHHHHHHH ǅ`  hLb]5LU]ZHD]aHPhH=!  Hz 2!  HH$  I钕1E1E1E11LpE1E1E1LxLLLLLLLLE1LhLLǅ`  LA   QE1E11E1LpE1A   LxLLLLLLLLE1LhLE1ǅ`  H[L體HzXHH[p ]11E11HpE1E1E1HxA   HHHHHHHHHhLǅ`  C11E1E1HpE1E1A   HxHHHHHHHH1Hh1Hǅ`  ƛ111E1HpE1E1A   HxHHHHHHHHHhǅ`  UHLHZL馲H4ZCL'Z2HZHLZLI11E1E1HpE1E1A   HxHHHHHHHH1Hhǅ`  鄚H~YBLqY)A.LTY!HUHMAbzHUH111E1HpE1E1E1HxA   HHHHHHHH1HhHHǅ`  {HlZ HRH5 H81'XE1E11E1LhE1E1E1LpA   LxLLLLLLLLǅ`  LLWL$HY HRH5 H81zWE1E11E1LpE1E1A   LxLLLLLLLLE1Lhǅ`  RLLWHL8WL鄰L$WɒLWTHLWL"fHP4   )1H`1E1HpA   HxHHHHHHHH1HhHǅ`  E1E1E1E1LL3HRLHϮL9hǅ`  A111HpE1E1E1HxHHHHHHHHHHHHH霖HPHsW H5	 H812UE1E11E1LpE1E1LxLLLLLLLLA   LhE1ǅ`  LU齑LT雑E111E1LpE1E1A   LxLLLLLLLLHhHǅ`  wLLLcTLLL9hǅ`  A1E11Hp1E1E1HxE1E1HHHHHHHHHLLLL鶔111E1HpE1E1E1HxA   HHHHHHH1HhHHHHHǅ`  $E1E1A   1LpE1LxLLLLLLLLLhLǅ`  E1E1E1E1LLLyH=Bh /  IH  H=:h L9  HH@   tH;S g  HTHH   HT E1   I9U(  H`H   LLH?H)LH	H4L/  LHI/AxA  AE xAE   Ht1H1  x=  11A   1HpE1HxHHHHHHHHHhHǅ`  1E11E1HhE1E1E1H1A   LpLxLLLLLLLLHHHǅ`  zE1E1E11LpE1E1A   LxLLLLLLE1LhLE1LLLLǅ`  HLH钧fH4   )HRLH|H>LH11E1E1HpA   HxHHHHHHHH1HhH1Hǅ`   111E1HpHxHHHHHHHHHhH1E1E1A   Hǅ`  HN*11E1E1HpE1E1A   HxHHHHHHHH1HhH1HHHǅ`  1E1E11HpE1E1E1HxE1A   HHHHHHHHLhLLLLǅ`  b11HpHxHHHHHHH1E1E1E1H1E1A   HhH1HHHǅ`  ΍fH`E11HP4   )A   1E1LhHpHxHHHHHHHHLǅ`  R  HH[1HH=L3HHH۪  HZOHKBf1H1H`4   )A   1HpE1HxHHHHHHHHHhHǅ`	  11E1E1HpE1E1A   HxHHHHHH1HhH1HHHHǅ`  釋1A   1E1HpHxHHHHHHH1HhHǅ`  E1E1E1E1LLLL1E111HpE1E1E1HxE1A   HHHHHHhHLLLǅ`  錊fH`1E1HP4   )A   11ǅ`  HpHxHHHHHHhH11HpHxHHHH  H,!HHHUdH+%(   p<J  H=m  1  E11E11LpE1E1E1LxLLLLLLLLE1LA   HhHǅ`	  Z  HHX1HE:G0E  HHTE1L@5G+C  HHOE1L;0IG&HUdH+%(   lp>J  H=  1+  HEdH+%(   CrH=  BJ  1  HUdH+%(   p6J  H=  1  HJH HH5"  H81^FL9hǅ`  A1E11HpE1E1E1HxHHHHHHHHLLLLL9hǅ`  AE11LpLxLLLLLLLLLxH2G HH5
  H81FE111E1HpE1E1IHxA   HHHHHHHHHhǅ`  L9hǅ`  AE1E11LpE1E1E1LxLLLLLLLLLLLLLqL9hǅ`  AE1E11LpLxLLLLLLLLE1L  HD9HC,  HhHLCLݞfHP4   H`)L9hǅ`  A11HpHxHHHHHHHHL9hǅ`  A1E11HpE1E1E1HxHHHHHHHHLLL頃d  AܝAНL}BÝc  H͝HNB鵝HEdH+%(   krH=  bH  1*  fH4   )E1E1H`1A   LpLxLLLLLLLLE1LhLǅ`  E1E11E1LhE1E1A   LpLxLLLLLLLLǅ`  1E1A   1HpE1HxHHHHHHHHLhLǅ`  =E1E1A   1LpE1LxLLLLLLLLLhLǅ`  HA HH5  H81?LE1E1E11LpE1E1A   LxLLLLLLLLE1LhLE1Lǅ`	  f1Hf1Hp4   A   E1HxH`HHHHHHHH1)HhHǅ`	  E1E1E11LpE1E1E1LxLLLLLE1LLLLA   LhLǅ`  M1E1A   1HpE1HxHHHHHHLhLǅ`  E1E11E1LpMA   LxLLLLLLLLE1Lhǅ`  ~HUdH+%(   p8J  H=K  1t       H5T HHmBLM  HX1LHH      HH  HAE :uAE -uL< uHUdH+%(   p:J  H=  1  E1E111LpE1E1E1LxA   LLLLLLLLE1LhLHHǅ`  }HUdH+%(   FpDJ  H=  1       H5R HH@LM  H1HLHH      H  IAE tAE sLLc;LsE1E1E11LpE1E1E1LxLLLLLLLLA   LhLE1LLǅ`  {fH4   )HA7H111E1HpE1E1E1HxA   HHHHHHHH1HhHHHǅ`  {HUdH+%(   6p@J  H=  1  HEdH+%(   rH=  I  1  H=; HH5  H81Q9bH; HH5  H8119L0:HH@HPH:; H5  H818H<9HEdH+%(   _rH=  H  1  9HH@HPH: H5  H81811E1HpE1HxHHHHHHHH1HhHE1E1E11LhE1E1A   LE1LpLxLLLLLLLLLLǅ`  xH7+H;HE1E111LpE1E1LxLLLLLLLLE1LLLA   HhHǅ`  6xHUdH+%(   `p^H  H=  1  HUdH+%(   7p`H  H=  1  MeI]A$=wA$=wAE x	AE tI1L6L6HUdH+%(   pH  H=J  1s  HUdH+%(   p\H  H=!  1J  HEdH+%(   brH=  I  1!  11E1E1HpE1A   HxHHHHHHHH1Hhǅ`  vHEdH+%(   rH=c  I  1  HEdH+%(   rH=:  I  1^  HUdH+%(   vpH  H=  15  HUdH+%(   MpH  H=  1  ff.     UfHO fHnHATSH   dL%(   LEI)`H)pfHnHpHH)EfHn~' HE    fl)E~p' fl)E~h' fl)EfHn)EHt*LIHM~I  H JcH> I  H>=wLVH`A=wAL^LhA=wAHNLp=wH4 Hx=wH5 HU0HEwDFvAE0HEIIH`HLLeLP/TY^$D  ff.     ff.     HL9t7H;HtxuHHX3HXL9ufD  HUdH+%(   {  He[A\]@ HV=wHxHV=wHpHV=wHhH=wH`HL%)  H`ATHUJ4HLXo  AYAZ   H} LX  H} x  H} M  I~%      ff.     II   J< uH3 HLLt  H?  H5  H8AP1A   V1_AXLefff.     HI9t'H;Htxum1HI9u@ Hy  q  H=  訩  1QH3 HH  L  H  H5  H8AP1A   H`0XZVf     H`LhLpHxLELMHE` H2 wHEH2 wHEiH1 =wHU?1f.     f.     f.     f.     D  HHHtH 1D  @swH  @HcH>D  H       H  H  H  H  H  Hq  ÅH  H  HEÅH  H  HEHs  HQ  H  H>  H(  H  Hr  HS  HC  ÅH  H  HEH  H  f     H0  1H=0 HHHP=wHtxt
1    UH.1] G<4wH  HcH>D  UH/ @H5  H81H .1]@    f   f.        f.        f.        f.     UHw@LGDHH/ H:MtZIH2H6H9t,IHLJHH5  ]H	LH1y-f     Hi  IHI1H5?  ]Q-HJ  H5l  UHAUIATSHHGH   u^Me I]I9t#H{HtHsH);.H(I9uI]HtIu(HH).IELH@  H[A\A]]   @u$HpH9P0uL(tH[A\A]]*hIEUHSHHHGH   uRH/H{HtHC    xtHCHH]H@      k,f     +*uHSH|H9B0uH>(tH]@ wD@  UHAWAVAUATSHH(HGL8IHxH   HcPX@sJ  @p@  {G t  A   E       CG {@HC0   @Q   N      EIH u4  EH    IFIL-  HECF<@c  f<^Y  F<4  H  HcH>f     {@A   @Qf@>~2N   EUH	& uEP@PsEO@OeH+ @H5+  H81i*HC{@E sDL82fHK0CGH9
  @  HЃA   t$LpHH9     ff.     LpHLpH9ux     H9+ @HME1H5  H81)CFHM<@  A\L9atC<C  HH([A\A]A^A_]    A\A   L9au     8Et<C  <Ht}HuHCHS IOHHH9  LLeH{0IMIEHS HWHS0L9U  IOIH8H  y\Su&HqH> %  IO(HxHHH{HpHHH  HC{@sDL8CFI<@V4IcT L>D  A   D  A   D  A   H) H5  HME1H8)CFHM<@{     {DHMHHtH{ 1HMHHHtH7H)HC H{8 /{DHMoHMHC8MIIMII@ A   D  A   D  A   D  A   D  MII D  MIIxD  MII`D  HQHhHCIOHpHHHsHPHS0HHfD  LxHHHKL9tHCfD  IL9uHC    HCD 1C@    H([A\A]A^A_] HQHpfD  H' H5Z  H81P& 1ÃCEH' HH5  H81&1Hi' H5  H81%`   ܐff.     UHAWAVIAUIATSHHLHMLEI  IE H  M0     ff.     ff.     ID$IH   H L9xuL@M;FuDH AN Dʉ@@8uA    Hx(H8A@HD    IF(Iv8@HEI,#tHEI)IL H   [A\A]A^A_]fHpI;vu&D@ AN D@@8t]D  HI9tHH L9xuf     1H[A\A]A^A_]    Iv8W    Hx8/    A ubHx8 tnMF(IF8@IEHHK"sH<& HULH5  H81#lf.     Hx(H8A@HD uIF8  IH뽐UHAWAVAUATSHHGLE      HHIIIIHuEIFIHt7H8   H'tnuٸH[A\A]A^A_]D  IM9   I$   HH8&tۃuH/% HUHH5  H81"D  M)IM7H[A\A]A^A_]    H$ HUH5  H81"V    1MHGH   Htf.     [ff.     UHHSH(HWdH%(   H]HH=6 $Ht+H =wHEdH+%(   u_H]Hf#H=5 HUHh'HMHuHM&HMHuH# HH5v  H81!HM7#    UIII?HAVISHH5 HwI   H9   L# L9   LX  M   IZH~,1f.     IT H9"  L9  HH9u   t5HF8HHt(HL1L[A^]     H9uHG0HuHL1L[A^]"D  HWBtI61Lr uH_H=  Hu$   HuHAHE!HEHt|H[A^]    Hf.     ff.     H   H9t4HuHH" H9t#HH   L9tHuI9fD  HWBD'$Hu"HC" H5  H8!ff.     1Qf     UIHH HH;5.! H      H   @         A   @   H   H~H      @t<I9^  HuLH}LM
H}HM  HALMH         =wxHt"H! H55  H8 @    @t)L`H  H5B  H8i f        tA   @t1LMLMHHte1HLHMLMsHMLMIxt{Mt3IH   @   LLLELEA xA tÐLW    Hο   1LMLMHdLw    HLELELMl    H LH5o  LEH81LEf     dH ff.     UHAWAVAUATSH	  H  HHH  H1HH  HHH   LHHH  LH`dH%(   HE1H]HM`HXHu o   HH@  HH   Hp   HH   HH   HxHHHP   HhH@H50  HH    HPH$o      D$o  D$ o   D$0o0  D$@o@  D$PoP  D$`o`  D$pop  $   o  $   o  $   o  $   o  $   7 H   H-  IH@H5'6 LH   H-  HH6-  AE xAE *  H56 H9tHCH;B \'  Cr'  ǅ   L-9 A   x?+  L;- L;-A uEuLu/  AE xAE *  H*4 H=C. HSHIH/   =wAE IEH5 1 LH   H0  IM0  AE xAE +  HcHH(tIH@0     ~IH0  H@LL(H}/ H=- HSHLHI72   =wAE H    E1I9F3     LLHǅ     LLHI%  H*1 HP =w   HLLH?H)L H	HLH4L HMLL Ht*Ax#AuLL LD  A xA (  AE xAE `(  AxA=(  AxAZ(  HHb2  ~ H1   H; ǅ   H)0'  H   LH	 SH   LK  ZY5  fofo fH~)))fofօ) fo )fo0) fo@)0foP)@fo`)Pfop)`foM)pfoM)foM)foM)H5  HxD+  HHv0 fH=* )HHSHHH H0HIH)1   =wAIGH5. LH   H1  IM>1  AxAs,  Hc  HH IH1  H+ H=) HSH/IH33   =wA H    E1I9E3  H<1    LHǅ    LLH LHI\/  Hi- HP =wHغ   LLH)H?LH	HLH4!MLHtAxA/  AxAd.  A xA A.  A$xA$.  AE xAE -  H.  H1   H; ǅ   H~(  HLHLS      H# Β  A\A]16  fofo fH~)))fofօ) fo )fo0) fo@)0foP)@fo`)Pfop)`foM)pfoM)foM)foM)H6  x-  foH)@foHH)Pfo H H0)`foH)pfo )fo0)fo@)foP)fo`)fop)fo)fo)fo) f)L-, H=&& IULHH1   =wHCH5* HH   H
2  IM1  x;-  H L`LHI1  Hv+ H=% L HSHL HIA2   =wA$ID$L LH5+* H   H2  L IM2  A$xA$(  L%& H=$ L IT$LWL HH2   =wH A   E1I9@k5     L Hǅ    LLL L HHD'  H( HP =wL   LHL)H?L H	HHJ4EML HIt/AE x'AE uLVHL      AxA'  AxA'  x9(  x(  A xA '  M6  H1   L;% ǅ   H$'  HLHLAT      H Í  A[[=9  fofo fH~)))fofօ)fo )fo0)fo@) foP)fo`) fop)0foM)@foM)PfoM)`foM)pH#9  A$xA$.  HH' fH=" )HHSHHHH H?IH4   =wAIBL LH5% H   H4  L IM4  AxA.  HP# H=Y! HSHIHB5   =wAH A   E1I9G5     fInL( L Hǅ     )L LHH41  H$ HP =w   LHLH?L)LH	HL L J4LL IMtA xA 3  AxA-  x-  AxA-  Ml0  H1   L;- ǅ   HI+  HLHLAU      H `  _AX%8  fofo fH~)))fofօ) fo )fo0) fo@)0foP)@fo`)Pfop)`foM)pfoM)foM)foM)H8  AE xAE 51  foL5 )fo) fo )0fo)@fo )Pfo0)`fo@)pfoP)fo`)fop)fo)fo)fo)f)A=wAHc  zIH5  HLH      Hǅ    HHA$xA$0  AxA0  H4  H(LLLHJ6foHIH  ILHxH     $   fo $   fo0$   fo@$   foP$  fo`$   fop$0  fo$@  fo$P  fo$`  fo$p  fo$  fo$  fo@$foPD$fo`D$ fopD$0foD$@foD$PfoD$`foD$pfo$   fo$   fo$   fo$   fo $   AWAVAT      pxh     LLHHH H
7H   K3  Hc  HJ0HHIL HpHf. zG'  HuH  HH H4  HHHH(HHHH-  L%#  H=< IT$LIHz7   =wAE IEH5` LH   H8  IMy8  AE xAE l3  L% H= IT$L'IH7   =wAE H    E1I9Gz7     HfIn
! Hǅ     )IH'7  Hp HHP =wHȺ   LL H)H?H	HH4L(M  ItAxA6  AE xAE 3  A$xA$3  AxA3  M8  H1   L;2 ǅ,   HtaH   LH ARH,   L0L0  ZL0Y8  fo  )0fo fo0)fofI~))fo ))fo0)fo@) foP)fo`) fop)0foE)@foE)PfoE)`foE)pM8  AxAf4  Hf)HHHH HH@HP=   HLL L`L  fD  ff.     ff.     ff.     ff.     HcJJ4HIHHHH(  AAuσ    Hǅ   ~L~ HHH`HHXH))DD9'9  HHL  D8HXIH`H I)H0ML(IcH;-  H(  H`HcAHhIHc@H`*  H`H   H4 A*  IcH   DD916  HHIc&@ ff.     ff.     H9)  HHHIID9uH(HHHIHH)  f.z/  DE1LL 1f     D6f.     ff.     ff.     ff.     A9  HcHJ<"HHH(  Hڋ<B;<:tAH   D9uHhHJ&HIH(  H`=  HL`L@HH8H; L  D0E1	DAh    E}IcMcHLEyH   H   EIDfoH H;  )tHι   N8B*  ǅ E1E1HH(Hjj jjj H   HcPH   HcHHP0 H@)  H$  H~/HH 1@ ff.     H
HH9uHHt#H; tP8L)  L   LH  HEHHH(  H`D,AtDhL`L@H8L  D0HH1H H  ~#fD  ff.     HHH9uHH1HH ~fff.     H
HH9uHxHH  foDhH     H D/HPH)@HHHfo$   fo $   fo0$   fo@$   foP$  fo`$   fop$0  fo$@  fo$P  fo$`  fo$p  fo$  fo$  fo@$foPD$fo`D$ fopD$0foD$@foD$PfoD$`foD$pfo$   fo$   fo$   fo$   fo $   f(      L   L(HASLHH s*H   4  L Dh0  (\Hp(X(f.-  ,  A%  DLLhH`L  D@E}IcMcHLEyH   1H   EHDHEfHn)PHtH;H t   p8/  ǅ E1E1HjL H@j jjj H   HcHPH   HcHPH   AV^ H@?-  HLEyH   1H   EHDfoH H;5 )t   N8-  ǅ E1E1HHHjj jjj H   HcPH   HcHH(PAV H@8.  foH  1Ҿ      $   fo$   fo$   fo$   fo$  fo $   fo$0  fo $@  fo0$P  fo@$`  foP$p  fo`$  fop$  foP$fo`D$fopD$ foD$0foD$@foD$PfoD$`foD$pfo$   fo$   fo$   fo $   fo$    HĠ  ,  H^  Ht'H;: tP8Hǅ    n,  HPf)Ht'H; tP8HǅX    +  f)P'  HLEyH  1H  LEHDH   fHnx) HtH;x t   H8.  ǅ HE1E1jHPj jjj H  HcHpPH  Hc1HhPH  AV H@Z.  HEyL  1H  ELDHHHHHtH; t   p88+  ǅ HE1E1jHPj jjj L  Jc&PH  HcHHPAVLL H@+  H   4   L1HLH   H4   HP      [ HĠ  *  H;U  Ӄ  HPf=U  )跃  f  ) H  HEHHH(  H`D,ADLLhH`L  D@D9*  E@ H; 
  ff.CzfL- L;- AD  M,  AxAd  Hǅ    E1E11Hǅ    Hǅ     Hǅ    Hǅ    ǅ  AE xAE   MtAxAn  MtA xA 6  MtAxA  HHt'H; tP8Hǅ      Hǅ    MtAxAH  HHt'H; tP8Hǅ      Hǅ    HPHt'H;w tP8HǅX      HǅP    H Ht'H;9 tP8Hǅ(    !  Hǅ     Hٜ  H=z  j  HHtH; tHƸF8  HHtH; tHƸF8  HHtH; tHA8  HHtH;a tHƸF8  Htx  H HtH;  tHA8  MtL;% tAD$8  HEdH+%(   "  He[A\A]A^A_] Lp fo0c LP LL9LD  L  LL	L@D  H L LLLD  LLLD  LLLLLi    LLLRLL!    L0 H 0 Hǅ    1ǅ  LL LLL E1E1LILE11E1L LMtfLI Hǅ     E11E1Hǅ    E1Hǅ    Hǅ    Hǅ    ǅ  Q    Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    ǅ  AE x	AE tE1E1E1     LfD  [H<   HHHǅ    LnLf  HHHǅ    %  HPHHǅP      HG<H/  H HHǅ     u  HHFfo0   HH  HHHHHD  b  H H[  A$A$LY@ ;HlHǅ     1Hǅ    Hǅ    Hǅ    Hǅ    ǅ  f.     H=| H HL M:H  Hǅ     E11E1Hǅ    E1Hǅ    Hǅ    Hǅ    ǅ  xfD  I Hǅ     E11E1Hǅ    E1E1Hǅ    Hǅ    Hǅ    ǅ  L@ L Hǅ     E11E1Hǅ    E1E1Hǅ    Hǅ    Hǅ    ǅ  vAxAI	  ǅ  L Hǅ     E11E1Hǅ    E1Hǅ    Hǅ    Hǅ    ǅ  g       HIH$  ǅ  E1E1Hǅ    Hǅ    x	  Hǅ    E11E1Hǅ     Hǅ    tffo0 LL qL D  LHL JHL     LHL HL     L HL L D  HHL HL     LTH=% H HL LMRLHI;  Hǅ     E11E1Hǅ    E1Hǅ    Hǅ    Hǅ    ǅ  fD  L L L LLLD  M~I^A=wA=wAxAG  I1D  E1E1E1E1Hǅ     E11E1Hǅ    Hǅ    Hǅ    ǅ  aHǅ    ǅ  Hǅ    E11E1Hǅ     Hǅ    D  HHHD  LLU@ KH= H HL MPHuH HH5  H81Hǅ     E11E1Hǅ    Hǅ    Hǅ    ǅ  D  HLLD  sID Hǅ     E11E1ǅ  E1E1Hǅ    Hǅ    Hǅ        HcH<9~jDfHI	HIIIcHN4"IHH(  D;,u&H(LHHHIHAH9D@H`I  H  H<HhHH<  H  HHc9VH0H<DL8     H  HHHIH  IcHJ HHH(  D;,u%HHHHHIHH9D8H0@ H=| H HL MLLHI  Hǅ     E11E1Hǅ    E1Hǅ    Hǅ    ǅ  MuI]A=wA=wAE xAE 3	  I1  f))fo )fo) fo )fo0) fo@)0foP)@fo`)Pfop)`foE)pfoE)foE)foE)L1Hǅ     Hǅ    Hǅ    Hǅ    Hǅ    ǅ      fo0 H= H LH H]Hd  ǅ  E1E1E1Hǅ     Hǅ    Hǅ    fD  LxHHD  ǅ  E1E1z I ǅ  L!fHǅ     E11E1Hǅ    Hǅ    ǅ       Hǅ     E1 D  L HL L D  L LH= H HL L MLCLH-  ǅ  LE1E1Z LLLǅ  LM'L IML1H5L;L qH=B H LH L HNLhLH  ǅ  LE1 f))fo )fo) fo )fo0) fo@)0foP)@fo`)Pfop)`foE)pfoE)foE)foE)Hǅ     I1Hǅ    Hǅ    Hǅ    ǅ  _HEyL  1H  MEIEIHHHH u   p8  ǅ E1E1HHHjj jjj L  MJcPH  HcHPHP0l H@W
  H٩  H~$HH 1@ H
HH9uHHt'H; tP8Hǅ      f)E1E1E1Hǅ     E11Hǅ    ǅ  HEdH+%(     rH=  U  1i  MhM`AE =wAE A$=wA$A xA v  ME1KHEdH+%(   q  rH=*  U  1Ni  HUdH+%(   H  pU  H=  1%i  HEdH+%(     rH=؇  U  1h  HEdH+%(     rH=  U  1h  HUdH+%(     pU  H=  1h  HUdH+%(     pU  H=X  1h  HUdH+%(   {  pU  H=/  1Xh  HUdH+%(   R  pU  H=  1/h  HUdH+%(   )  pU  H=݆  1h  LHHǅ  LLLL YH=* H HL MOLWLH  1E11E1H Hǅ  BHǅ     E11Hǅ    ǅ  L ILLLH   Hc  LM	  H  HHHHHHHP*H= H HL ML(LHH HE11H5|z  LH81E1Lǅ  L Lf.     MGI_A =wA =wAxA  IE1H   HH   H4 IcH   HH   DD9  f(D@E  H`H  H<Hh HH  H  HHc9L  HDLLD8HJ1H  HH  I+D9uIf/  HH  9  HHyHL)F9	uHHf))fo )fo)fo )fo0)fo@) foP)fo`) fop)0foE)@foE)PfoE)`foE)pHǅ     M1Hǅ    Hǅ    ǅ  TLHǅ	  E1U E11E1E1Hǅ     E1ǅ    H ǅ  E1E1E1Hǅ     H  ALH  H  H<HhH  w  HHHǅ    ,  ǅ  E1E1E1Hǅ     L}f))fo )fo) fo )fo0) fo@)0foP)@fo`)Pfop)`foE)pfoE)foE)foE)Hǅ     1Hǅ    ǅ  H HH5gu  H817ǅ  E1E1E1LLLL L L	DD8Df(D8H`H  H  H< HhH  BLHǅ  H HE11H5ht  LH811LE1H HHHHǅ  LL  L\LL}՞  LNLLZ  L>-
  H=2(DEL LHA =wA Li  LHIv  DLHh  LLHIF  IRfHn~ fInH@      ~\ HflflHT) )E  LLHI  AxA  AxA  E1LH8H      LL0L8LIAE xAE M  A xA N  Mt1L裯AxAp  ǅ  E1E1  HHH1H5*B  L-L~  ~H= H L.L MkH
  ǅ  E1E1E1ǅ  E1E1LL  LKMǅ  E1E1ZMwMgA=wAA$=wA$AxA^  M1?H= H LFL MHj  ǅ  E1E1ǅ  E1MdI\HHqT  DhLHHH\  HXLH   LHH@4   HH(  H   HǅpH0ICH4   HXDLߋHĠ  H  HXT  /\  fDhL%  )3H: HE11H5o  LH81B1LE1H HHHǅ  H LH5n  H81|LHǅ2  E1E1HEdH+%(   qS  H=x  1Y  HEdH+%(   rH=x  S  1Y  fH4   H)ǅ  MH LLE1H5m  L H81L ǅ  k  H  f(H HH5om  LH81L  00F  HPH 1HP  ǅ1  LE1HF  HH|1Hi^+  La  H=LHǅ  LLHǅ5  H4 HE11H5l  LE1H819E1ǅ  L LLtǅ  E1JLLALǅ  E1LLLHHGP`H  `4  f.z  H  LHU  HAHHHHW  H   4   HXHXHH   HǅpHXHHH  HH(  H0HBHPH    H  HXU  JW   fL  :  )9  LHqLHHEdH+%(   rH=dt  S  1U  LpLL\LHǅ6  uNLHUdH+%(   vS  H=s  1T  HEdH+%(   qU  H=s  1T  AE xd11E11HHH HHǅ  SHEdH+%(   rH=As  T  1eT  111E1HHH HHǅ  LHǅC  LHǅ=  HEdH+%(   qT  H=r  1S  HUdH+%(   v'U  H=ur  1S  H LH5g  E1H81 E1ǅ  pLHǅ%  HEdH+%(   KT  H=q  1(S  HEdH+%(   "rH=q  T  1R  L;5  M@A@麩HE LH5g  E1E1H81SE1ǅ  H9s  UHHH H9GH9F      HO1H;N   HWLFL9AHAt
I   DW DN 1DEAAD8uiA    H8A   LF(H8A@IE      DD1E9u   HtH{ÐL L9u1uL9u1u   HH   H;n H;=< uEH;= t<H}H}xuEED     f.      LG(H8A@IE Hv8    DD
 DDɸÐff.     UHAWMAVIAUIATISHXHEHEHGdH%(   H]J   ]  HEIIHHEMII1f     I$I| LHumfff.     HPHHtSH;:uIH)LȋwHHI9u1HUdH+%(     HX[A\A]A^A_]D  H9 H9GHE    LMuyLEHMLHuH}OH}HuLMt.tHB HHUH5t  H81iHEII=wH<LEHMLHuH}LMHuH}tHHuHHuHtfH]1LmID  I9H0HULPt\HUHMLHL)HIEIHuI9H]HE    HE    1HUHuL脿HH}HHtfff.     H;8tHBHHuLEHMHLH H9Gu<ΙtHMH H5r  HUH81聿UHAWAVAUATISHHdH%(   H]H     10  IM   H@ IF    IF     Ml$IFH fHnIF(    )EH   HH   M  I2  IL$ wHHMHUHMH5@g  IA   HV13AZLeA[   MtA$xA$  Hi  /  H=~  6  AxA[  E1f.     HEdH+%(   g  HeL[A\A]A^A_] I^  Md$ A$=wA$IL$H H9  IF(MnfIF(    M~ AFHEM9t*Lf     H{HtHsH)軾H(I9uMtHuLL)螾LvM  HH  A$I^0A$Lt    HL-e  I1HMHUE1HHE    AUZLeYjMH HLLa  A   H`  H5g  H8j 1螼AXAY=D  H HH5g  Lxa  A   H:`  He  H8AU1W^_Hi H5: 18  IfHX  HH   H~H  1ff.     HH9   H9D uH LAH5|  HHH' 1H:Hvd  辻YfHn1HufHnH=R    fl)E0Htx   H}衽A$%A$L蠻 胿HHf  1  H={  3  H   H9$HuH;$ H' LAH5{  HH1H:Hc  ׺aLD  L[H,1UIHH HGH;    H; tWHHpHt~Hy twH}HHMHMHb  H}HHEQHU
x
   D  Ht	HyHGt
I;@   ID vcHHhH   HAHtzHy	   LfD  t;Hy6HGHtI;@sEIPHh     H HHE輹HEfD  HLEHtgH}HHEHU
    HHPHuLLEHMLEHuHHMxHHA"fD  1H LEHuH8HMItйHMLEHuHAff.     UHHSHHHֺ H9F  HF   HH)H@  BHHw  HCH;Ĺ    H;    HPpHt`Hz tYHHUմH  HUHEHHRHM      HHE&HE   D  HPhH   HBH   Hm  HH] HxcHCHH9sgHCHЋv,/ H   HCHHH9s8HD wH]fD  HHCH0fD  HسH  HHHEHU
x
uHHE3HED  HUHUH  HCH;7 yH;" Hlfff.     HCH0H#HHuĴHUHHtHUHE軹H}HUHƋHu肶HUHuD  HHH   Hu@BRHH	HGH;p H   H;X HGHqfD  HHUHUHWHy HHUH1
HUt2HBHX蕶H H5v  HH81jf.     1f     rBHH	H H
HHuHHUHuHUHxHHBaHGqHƶ HUHuH8ftHUHuHB'ff.     UHH@HWdH%(   HMHHBpHt'H@HtHUdH+%(      HD  HBhHt'Hx t HEdH+%(      H@    t|H58 HUHMH}蟹LEHMMtJLHuLEH      HE    HMLLEAxAt>HUdH+%(   uAӴH}HWH HRH5_  H81蟳1LHE߳HE@ UHAWAVIAUATISH  HA<T<>      HcH> <s      <xJ  <}   LI\$8-   AD$D IHtIt$ 1HHHtHH)It$ HL[A\A]A^A_]fD  HA   IA	&   <T@  <@  @ H H5rt  H81xE1 HwѺ   H      AF<dtP  IA   A8D$D  L9tID$(IID$0AD$EAD$FAFEl$@AD$DID$(   fD  LOAD$EAD$D IID$0    AoD$ AD$FID$(   fofsffAD$ "D98  AD$GID$(   IID$8Ml$(ID$(   HEA~{  LUfIFAD$D HEAD$0M  HuLIH{IM9uHEHID$8uH, H5r  H8}@A|$D tI|$ tLI|$ L賂I|$(  L芄ID$I1H LEAXff.     A  )~    B<	rJAVIFr@	w2fff.     0HҍJr@	v+A9~ITHcH9  ,te)  HIHAD$EIAD$E=IIFA~:t    H8:uLp@ HfE1     PЀ	}AFIN0p@	wAfD  ff.     ff.     0HPp@	v$HcIIT$(ME1A8D$D|E9l$@qAD$EA8D$F`A|$G TAoD$(IID$(   fofsffAD$0D9   H DH5p  H81$Hx Z   H5b  H81Lu
HM H5Fp  H81ܭ_H0 H5o  H81迭BH H5<o  H8d'H H5Qo  H8IHݮ H5.p  H8.f     HWP=wHfD  HW`=wHfD  H =wH HGhHtw Hq     HWP=wHfD  UHAUIATISHHHpHtHAԅ   H{ HtLAԅ   H{@HtLAԅ   H{XHtLAԅ   H{`Ht
LAԅuwH{8Ht
LAԅudH   Ht
LAԅuNH   Ht
LAԅu8H   Ht
LAԅu"H{x1HtHLL[A\A]]D  H[A\A]]D  IAЃxSHc׉HE9D|>t?1 }1H9})HcHATD9~މ9|A9@ AQ1A9 ff.     1Ht)H9   HOHVDG\H9t&AHt1~\Ht    1H9    D8F\uF]8G]uHcGX;FXu~BH    1D  ff.     HH9tHLH9Lt1        ø   AS{V`19W`mLGHNM   HSI81H   H41H   HDI9DuUHH HDI9DuQLEHUHMt'HULEHMHI<HtH4Hu11HH< 1H<  U   H?IIHwHt/u+H   H   I9LBMuMHF]1@ HuHD  Hy tHb HH(S  H5S  H81'D  H9 HHS  H5&S  H811]f.     H	 HHR  H5R  H81辨@ Hy Do     U   H?LOIHt2u.H   H   H>LBHIuKH6IA]HuHD  Hy tHb IH(R  H5R  H81'D  H9 IHER  H5&R  H811]f.     H	 IHQ  H5Q  H81辧@ Hy Ao        H?IHOIЃtHAHLL    HtIH>HAHLL@ UHp H5-Q  HHQ  H81H"1] ff.        H?ILOHуtLWH8HIAHL     HtLHHfD  UH HP  H5P  IH81H蒦1] ff.     H=P  PHGXHt+w H vfD  HGH@HtUHHH}HHUHBXHtwf     HHt4=wHzXHrXHtxt1f     H5A     UH1] UHSHH   HtYHH H   wHH(H   wxtH]1HxfD  H]D  H   Ht=wHfD  H    t>UHHHUH}9HUtH}H   =wHfH1     H   Ht=wHfD  H    t>UHHHUH}HUtH}H   =wHfH     UHSHHHpHtHCp    x  H{ HtHC     x  H{@HtHC@    x  H{HHtHCH    x  H{PHtHCP    x  H{XHtHCX    x  H{`HtHC`    x  H{hHtHCh    xp  H{8HC8    Htx^  H   HtHǃ       xF  H   HtHǃ       x.  H   HtHǃ       x  H   HtHǃ       x   H{xHtHCx    xtH]1     KH]1 ;fD  +fD  ,fD  >fD  PfD  bfD  ۡtfD  ˡfD  軡fD  諡fD  蛡fD  苡fD  {fD  UHHtSHF   tFH=wHzHHrHHtxt1]    1    H H5d  H8j] UHHtSHF   tFH=wHzPHrPHtxt1]    蛠1    Hi H5rd  H8] UHHtSHF    tfH=wHz@Hr@Htxt1]    1    H H5"d  H8j] Hɡ H52d  H8J     UH;5 HHtLHtGHV    tRwH   H   Htxt1]    1@ c1    H1 H5c  H8負]ff.     UHSHHHGHH   t3HĠ Hc     H81薢u-HH]f     H HH5'd  H81uxt1HH]D  H1螞ff.     HG@Htw	     UHHH}跟H}HG@Htwf     H   Htw    UHSHHWHtH   wH]fD  Ht钠f=wH ff.     HGHHtw	     UHHHGH}H8耛HUHBHHtwfUHATISHtmH;5n HuqH    H5b  H8ƚ=wI$   I$   Htxt1[A\]    ÜH     HF   uH| H5b  H8fD  UHATISHtmH;5 HuqH    H5b  H8=wI$   I$   Htxt1[A\]    HA     HF    uH H5a  H8=fD  H   Ht=wHfD  UHAVISH   u1Hj =w=wI      @    H 蟛HH   =wHA1E11HMHH= GHMHx   H   HBHUHHH   H   HUHx   HtII    -x   I   =wHH[A^]f     Hl =w#@ HHU4HU< I    uf     HHMHMM Ha膖HUHf.     UHSHHۜH{( tH謜HDHH]    HwPH1H=C  7    UIIHHH HGLP@tl   u<HLAfu+H   LFI,  Hv LAf     H H5'C  H8Z1fD  H   LFM  1LAHtH}HL]LUHU#LULMHL]Huz9     H}HL]LUHULULMHL]Hu-IAHA  H5A  HH H81ٗ:@ H}HL]LUHU舜LULMHL]HuD  IAHA  H5A  HH H81rD  IAHxA  H5A  HH| H81Bfff.     UIIHAWAVAUATSHhLO0dH%(   HMHMt<HVHusHEdH+%(     HhIr 1L[A\A]A^A_]AfD     .  HEdH+%(   w  HwHhL[A\A]A^A_]aHAHEHtHEH}HMH<HuHLMHU讖IH  HU1LMLELUHHMt    It I4HH9uH}L]HMLELMHUqHULMHLEHMIL]y  IHU   E1HEHE    LMLxHMLpPD  HEHHPH   H!HwHMwKD HEJIH}HMHULUHu贔LUuHULMLpH  L]LHxLAL]ALxAV  HMH  Hu1HMff.     HH9   H<֋xuHUHuHMHUHuHM HVH}   LHMLU3H   H}1HE苙HULEHHMtzHLHUHU
x
t*HUdH+%(      Hh[A\A]A^A_]     HHE4HEfD  HMLHEFHE릋xt=Hܕ IPPH5Z  H81藓1vL]HEӓL]HEHLE躓LE1>LА1/Hr H5=  L]H8L]1(诔@ ff.     Hc?锖@  H: f  Hz [  AHOxLOpHAHtUH1HrPA   HIHJXH   I1HrH   H1H   IqHrHIH       NHXHcI4fH|PHH~HuH   I1HrH   H1H   Au2H   I1HrH   H	H   @ ff.     HH@HHJ   P8D	t>1 Hǂ   IIHJH2Hǂ   AufD  w1fD  UH5X  HHHʒ HUH8HUfHǂ   Lff.     UHAUIATIԺ=   SHXdH%(   H]HH    HLba  AM$  H;  H}H]fInfHnHE    H     @@ flH;)Efo`  HC    )EfHE)EA|$\SuMLD  ff.     ff.     HBHHHC    HHz\StH]HAHA    Iu(HtpIUML$L9   I}@ t*1HUdH+%(      He[A\A]]f.     HY IE@ H)    H5W  H81賏I}  tH% I9E@   LS@ fH AE fHnH flIE@AE0D  H5O9  IHG4  HCH<4  HHMH5 HH>PH5V  1M$XZXIE@    c艐f     UHAWAVAUIATSHSL`pIH@p    M  M|$I\$(A=#  HAH    JA=  AA$=  A$=  AMfpxA  x-  1LII9\$(  I~pMfpHtxz  AxA  Htx  M   LXAE xAE   H[A\A]A^A_]@ H  A$x=7  A<$=AMfpfH= H[A\A]A^A_]ƐfD  1	LI~pIFp    IH0&f.     KAA$=A=wAMfpTAf  H?1IfD  A$P  A$AMfp   1 Lx AMfpy HL[A\A]A^A_]Jf.     H8 H     L       AA$=   A$AMfpAL1ËQfD  賋|fD  A4$~      AMfpHLՉLX Mfpr1A$fff.     AMfp?1Mfp,{f     HH/  HH4  H5`R  HDHՋ H81kff.     UHAWI AVIAUATIHSH(9F辇H0  H Iŉ   *    ~  HE   HuE   :  IE(IU8@HDHEL9u   O<E1=@ Hz(Hr8@HE9EtX1ILL\Hx}IIM9   I$HZHtHEH)L9|>J  uHr89EuMLHHMH}HD  H H5Q  H8ʊAE xAE    E1H(L[A\A]A^A_]ÄtL@IE(uIE8HEHE   E    HEf.     IE8HE IE8f.     H?E   HuE   }    L蠈Vff.     UHAVAAUIATASH   H觅IHt@ IcMI)Ψ u~Mj8M~HE   AE -   It/L       LUH)I9HMHNLՆHMLU1Kt5 H~HH9uHL[A\A]A^]IR(MJ8@IDIpf.     1}f     UHAVIAUATASHH 诃Lآ IM   5 DLk9   HHIE;butI=wH L1HIH  D`(H规x  AE xAE   H [A\A]A^]@ MEpIEp    M  MHA=wAIH(H  =  HDLLMLEHMHMLEHLMH  I;H(  I}pMEpHtx  AxA  Htx  L^ M  G DL׉ΉMHc9b  LcIME;`   9N  HcLE)HwHM؍PHHHHHHHHLLpLEЋM؃E`I =    UH߉G	fD  LH [A\A]A^]@ H  HDLHMLMLE~LELMHHMHpA  A  A xA @  HHωYfD  Ɵ 9  H@L׉UHcMHڀIHMLcEH  | LII9bD  HDL蚆HHI}pIEp    H迃f.     HDLHMLMLE6LELMHHMH(AA A LHMPHM    Ht     LHM$HM  HMLMHMLMfD     HHnP  H7 H( D`H=    HM: AA A LHMrHMf     HLLMHMLE蹀LMHMLE     I8I=wLHMLEHMLE1A A h@ UAHAWAVIAUAATISLHhLxH dL<%(   L}L}IGH9t4HX  H4  HqH~21    HH9tH;T uI   L  LL1DȜ IHr  HdD9  He+  H}H]fInfHnHE    H     @@ flH;)EfoP  HC    )EfHE)EA~\SuBLD  ff.     HBHHHC    HHz\StH]HAHA    IwhLH  IXMNL9i  IP    MGpMc1AAH4    I<~EIOxHr  tL   I   tL1LHIHH9     tI   H   H<2    HL9o1HxHDL:       HUdH+%(     He[A\A]A^A_]@ ff.     ff.     H   H9HuH; f     L9   DD  I   H   &H DH5I  H81\~Htxtz$2  Z  I    Hy H5"I  H8     AOd1A9HJ DH50E  H81}@ H~y H<1 !  5V    H~ H5G  H8J)D  Hw'  IHo"  HCHd"  HHMH~ HH5!G  LPH1ML5}XZfD  H~ DH5gD  H81}L1A9HM~ DH5G  H81|xH-~ DH5G  H81|XH~ DH5F  H81|8H} DH5G  H81y|}@ ff.     U   IHH@dH%(   HE1H;5} E   HtJHHm    VH}LE   LMZLMȃYt HEdH+%(   uL@ I1 fAY}f     U   IHH@dH%(   HE1H;5.} E   HtJHH_n    VH}LE   LMZLMȃYt HEdH+%(   uL@ I1 fA|f     U   IHH@dH%(   HE1H;5| E   HtJHH?m    VH}LE   LMSZLMȃYt HEdH+%(   uL@ I1 fA|f     U   IHH@dH%(   HE1H;5{ E   HtJHHl    VH}LE   LMZLMȃYt HEdH+%(   uL@ I1 fAy{f     U   IHH@dH%(   HE1H;5N{ HH|G  HEtFHHk    VH}LE   LMZLMȃYtHEdH+%(   uLI1 fAzf     U   IHH@dH%(   HE1H;5z HHF  HEtFHHj    VH}LE   LMoZLMȃYtHEdH+%(   uLI1 fA9zf     UHHHG      HGHHv3   HH)HHt}HtWuHcH9   @ W   H)HHcʉH9tHy H5C  H8yɸf.     WGHH	HcʉH9u    WGHH	HHcʉH9u@ Hu{HtfD  H@`HtwH   HtkHHtaHy H9Gu;ff.     H}H}EwE\HHu    c{H	HCy H5!  H8x@ ff.     UHHHHF     HF   HǃH)Hw(FHHcH9ug|      D  HHH   HtxHHMsHMHcH9tHuzHMHu*ff.     H	x H5A  HMH8wHMHMYzH   HMdfVFHH	HcH9G VFHH	HHcH9H@`H   H   H   H}HHMHHtjHw H9Gu?HMH}H}HMEuEHM]HMHHu
@ 1HM[yHMHH7w H5  H8vHM@ ff.     U   1HAVAUATSHHH    f     L6I&sIH:  I|$PqH  IVhIE E1   H  L/ IHe  I$1Ҿ<   LH   @ H     Hھ   H2A  o1Ҿ      H  $   oC$   oC $   oC0$   oC@$  oCP$   oC`$0  oCp$@  o   $P  o   $`  o   $p  o   $  o   $  Ao$$AoD$D$AoD$ D$ AoD$0D$0AoD$@D$@AoD$PD$PAoD$`D$`AoD$pD$pAo$   $   Ao$   $   Ao$   $   Ao$   $   Ao$   $    HĠ     fAE x	AE toAxAt@HeH[A\A]A^]Hs 1H5 >  H816rHeH[A\A]A^]fD  LhrHeH[A\A]A^]     LHrAE xAE uL-rxH;Htxurf2HC    %D  UHSH  HHHPHXL`Lht#)p)M)U)])e)m)u)}dH%(   H81HE   LPHX   H@L:     HpǅP   ǅT0   H`~qH8dH+%(   uHpH=  YoDr@ HtH;=8r t   G8~    u=wUH=  p1HHH;q tHtH8HG    ~H    @ u'HHtH    xu
HRpfUH=%  q1HH     UHHHG      HGu[Hv5HHt3H5q 1H}YsH}xGt,sfD  G GWHH	f     H)q H5r;  H8
qHÐH@`HtcH   HtWHHtMHjq H9Gu1@ H}'H}xuHE9oHEHHusHuHp H5  H8tpe@ ff.     H;=o H;=p uH;=p tVrfD  Ðff.     H9   UIHATSHH HFLH6HOII)L)L9r>HHL)L9   I   LLNrHLHCH [A\] LLMHuHMoHuLHnLMIMtHuLHEnLEK LHCHCH [A\]D      H~bLLEqLEH{I@I0HH+HH)HH~nHLHCH [A\] K!.A$@ uA	붐 ff.     HUHAWAVAUATSHL?LoM)LHH9HҸ   IHuHEHHH9HGH    HmHuIċC,MtLLL0mOl,MtIvLL)mM&IMnMfH[A\A]A^A_]f.     HUHAWAVAUATSHLL7MM)LHH9JH   IHuHEHHH9HGHHlHuIoB M9t!J LD  oHH@H9uL`MtIuLLEL)lLEME IMeMEH[A\A]A^A_]fff.     AHVf(HH~OHHH f/v-HHL>HJ>H?HHt#HT
H f/wHD9rHH7D@f     HGI         @   HFH            @   H9t7HX  HtGHJH   1fD  HH9   L;T u   ff.     ff.     H   I9tHu1L;&l fH    ff.     ff.     H   H9tHuH;k tfD  IM9uW1@ Lo        tMJM~1ff.     HI9tI;| u/ E1D  KT HB   t   @tH9 HX  H,HqH_1ff.     HH9CH;T u   fD  UHH_eHxpHtHHGHu
1fD  Hj H1H9uHBp    xكuh1HHUtHUHzpHBp    Hu1ɸ UHHHuOdHxpHHt	HGHu1ÐHQj H1H9u`HBp    xރuWh1 xt+HLi    H5  H81gɸ    hHHUtHUHzpHBp    Hu1bD  UHAWAVLuAUE1ATSH(dL<%(   L}ALDHcÉHiQH%)kd)AAAIA܉ø   I9C4$ICHcHL)HH9HBI)Hg5  HHMl   LnkHǅu1A	H4I)EyF-IHIt81MDII1mHUdH+%(   u;H([A\A]A^A_]    HEdH+%(   u>H([A\A]A^A_]bg  HH                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               at least at most __init__ name '%U' is not defined floyd_warshall Missing type object dijkstra numpy._core._multiarray_umath numpy.core._multiarray_umath _ARRAY_API _ARRAY_API is NULL pointer Unknown exception ITYPE_t DTYPE_t bellman_ford <stringsource> (n) fortran johnson const int __setstate_cython__ exactly vector::_M_realloc_insert __reduce_cython__ johnson_dist_array yen const double 'bool' 'char' 'signed char' 'unsigned char' 'short' 'unsigned short' 'int' 'unsigned int' 'long' 'unsigned long' 'long long' 'unsigned long long' 'complex float' 'float' 'complex double' 'double' 'complex long double' 'long double' a struct Python object a pointer a string unparsable format string __loader__ loader __file__ origin __package__ parent __path__ submodule_search_locations builtins cython_runtime __builtins__ does not match __debug__ numpy flatiter broadcast ndarray generic number unsignedinteger inexact complexfloating flexible character ufunc scipy._cyutility memoryview _allocate_buffer array_cwrapper memoryview_cwrapper memview_slice slice_memviewslice pybuffer_index int (__Pyx_memviewslice *) transpose_memslice memoryview_fromslice get_slice_from_memview slice_copy memoryview_copy memoryview_copy_from_slice get_best_order slice_get_size fill_contig_strides_array copy_data_to_temp _err_extents _err_dim int (PyObject *, PyObject *) _err int (void) _err_no_memory memoryview_copy_contents broadcast_leading refcount_copying refcount_objects_in_slice _slice_assign_scalar format_from_typeinfo numpy.import_array __orig_bases__ __cinit__ K __module__ func_doc __doc__ func_name __name__ __qualname__ func_dict __dict__ func_globals __globals__ func_closure __closure__ func_code __code__ func_defaults __defaults__ __kwdefaults__ __annotations__ _is_coroutine __dictoffset__ __vectorcalloffset__ __weaklistoffset__ __reduce__ _shortest_path needs an argument %.200s() %s takes no keyword arguments takes no arguments %.200s() %s (%zd given) takes exactly one argument _cython_3_1_6 <cyfunction %U at %p> Bad call flags for CyFunction keywords must be strings buffer dtype cannot import name %S an integer is required __pyx_fatalerror __pyx_capi__ vector::_M_realloc_append   %.200s() takes %.8s %zd positional argument%.1s (%zd given)     scipy/sparse/csgraph/_shortest_path.pyx scipy.sparse.csgraph._shortest_path.NegativeCycleError.__init__ scipy.sparse.csgraph._shortest_path.__defaults__        '%.200s' object is not subscriptable    scipy.sparse.csgraph._shortest_path.shortest_path       scipy.sparse.csgraph._shortest_path._floyd_warshall     Cannot convert %.200s to %.200s scipy.sparse.csgraph._shortest_path.floyd_warshall      too many values to unpack (expected %zd)        Acquisition count is %d (line %d)       scipy.sparse.csgraph._shortest_path.dijkstra    _ARRAY_API is not PyCapsule object      module compiled against ABI version 0x%x but this version of numpy is 0x%x      module was compiled against NumPy C-API version 0x%x (NumPy 1.23) but the running NumPy has C-API version 0x%x. Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem.       FATAL: module compiled as unknown endian        FATAL: module compiled as little endian, but detected different endianness at runtime   Out of bounds on buffer access (axis %d)        scipy.sparse.csgraph._shortest_path._bellman_ford_directed      scipy.sparse.csgraph._shortest_path._bellman_ford_undirected    scipy.sparse.csgraph._shortest_path.bellman_ford        carray.to_py.__Pyx_carray_to_py_Py_ssize_t      scipy.sparse.csgraph._shortest_path._dijkstra   scipy.sparse.csgraph._shortest_path._dijkstra_multi_separate    scipy.sparse.csgraph._shortest_path.johnson     scipy.sparse.csgraph._shortest_path._YenCandidatePaths.min_distance     scipy.sparse.csgraph._shortest_path._YenCandidatePaths.max_distance     scipy.sparse.csgraph._shortest_path._YenCandidatePaths.__setstate_cython__      scipy.sparse.csgraph._shortest_path._YenCandidatePaths.pop_path_to_memory_view  scipy.sparse.csgraph._shortest_path._YenCandidatePaths.insert_path      %s() got an unexpected keyword argument '%U'    scipy.sparse.csgraph._shortest_path._YenCandidatePaths.__reduce_cython__        scipy.sparse.csgraph._shortest_path._johnson_add_weights        scipy.sparse.csgraph._shortest_path._johnson_directed   scipy.sparse.csgraph._shortest_path._johnson_undirected local variable '%s' referenced before assignment        '%.200s' object is unsliceable  scipy.sparse.csgraph._shortest_path.yen Unexpected format string character: '%c'        Buffer dtype mismatch, expected %s%s%s but got %s       Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'      Expected a dimension of size %zu, got %zu       Expected %d dimensions, got %d  Python does not define a standard format string size for long double ('g')..    Buffer dtype mismatch; next field is at offset %zd but %zd expected     Interpreter change detected - this module can only be loaded into one interpreter per process.  %s() got multiple values for keyword argument '%U'      %.200s() keywords must be strings        while calling a Python object  NULL result without error in PyObject_Call      instance exception may not have a separate value        raise: exception class must be a subclass of BaseException      calling %R should have returned an instance of BaseException, not %R    scipy.sparse.csgraph._shortest_path._yen        ../../../scipy/sparse/csgraph/parameters.pxi    Module '_shortest_path' has already been imported. Re-initialisation is not supported.  scipy.sparse.csgraph._shortest_path     compile time Python version %d.%d of module '%.100s' %s runtime version %d.%d   multiple bases have vtable conflict: '%.200s' and '%.200s'      Unable to initialize pickling for %.200s        int (struct __pyx_array_obj *)  struct __pyx_array_obj *(PyObject *, Py_ssize_t, char *, char const *, char *)  PyObject *(PyObject *, int, int, __Pyx_TypeInfo const *)        struct __pyx_memoryview_obj *(struct __pyx_memoryview_obj *, PyObject *)        int (__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int) char *(Py_buffer *, char *, Py_ssize_t, Py_ssize_t)     PyObject *(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int)    __Pyx_memviewslice *(struct __pyx_memoryview_obj *, __Pyx_memviewslice *)       void (struct __pyx_memoryview_obj *, __Pyx_memviewslice *)      PyObject *(struct __pyx_memoryview_obj *)       PyObject *(struct __pyx_memoryview_obj *, __Pyx_memviewslice *) char (__Pyx_memviewslice *, int)        Py_ssize_t (__Pyx_memviewslice *, int)  Py_ssize_t (Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char)  void *(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int)   int (int, Py_ssize_t, Py_ssize_t)       int (PyObject *, PyObject *, int)       int (__Pyx_memviewslice, __Pyx_memviewslice, int, int, int)     void (__Pyx_memviewslice *, int, int)   void (__Pyx_memviewslice *, int, int, int)      void (char *, Py_ssize_t *, Py_ssize_t *, int, int)     void (__Pyx_memviewslice *, int, size_t, void *, int)   void (char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *)  PyObject *(__Pyx_TypeInfo const *)      ../../../../../../usr/lib/python3/dist-packages/numpy/__init__.cython-30.pxd    __mro_entries__ must return a tuple     metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases        init scipy.sparse.csgraph._shortest_path        scipy.sparse.csgraph._shortest_path._YenCandidatePaths.__cinit__        Argument '%.200s' has incorrect type (expected %.200s, got %.200s)      cannot fit '%.200s' into an index-sized integer Big-endian buffer not supported on little-endian compiler       Buffer acquisition: Expected '{' after 'T'      Cannot handle repeated arrays in format string  Does not understand character buffer dtype format string ('%c') Expected a dimension of size %zu, got %d        Expected a comma in format string, got '%c'     Expected %d dimension(s), got %d        Unexpected end of format string, expected ')'   _cython_3_1_6._common_types_metatype    _cython_3_1_6.cython_function_or_method scipy.sparse.csgraph._shortest_path.__pyx_defaults      scipy.sparse.csgraph._shortest_path._YenCandidatePaths  Shared Cython type %.200s is not a type object  Shared Cython type %.200s has the wrong size, try recompiling   __name__ must be set to a string object __qualname__ must be set to a string object     function's dictionary may not be deleted        setting function's dictionary to a non-dict     __annotations__ must be set to a dict object    __int__ returned non-int (type %.200s).  The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python. __int__ returned non-int (type %.200s)  __defaults__ must be set to a tuple object      changes to cyfunction.__defaults__ will not currently affect the values used in function calls  __kwdefaults__ must be set to a dict object     changes to cyfunction.__kwdefaults__ will not currently affect the values used in function calls        unbound method %.200S() needs an argument       memviewslice is already initialized!    Buffer has wrong number of dimensions (expected %d, got %d)     Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)       need more than %zd value%.1s to unpack  join() result is too long for a Python string   base class '%.200s' is not a heap type  extension type '%.200s' has no __dict__ slot, but base type '%.200s' has: either add 'cdef dict __dict__' to the extension type or add '__slots__ = [...]' to the base type     invalid vtable found for imported type  %.200s.%.200s is not a type object      %.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject      Item size of buffer (%zu byte%s) does not match size of '%s' (%zu byte%s)       Buffer is not indirectly contiguous in dimension %d.    Buffer and memoryview are not contiguous in the same dimension. C-contiguous buffer is not contiguous in dimension %d   C-contiguous buffer is not indirect in dimension %d     Buffer exposes suboffsets but no strides        Buffer not compatible with direct access in dimension %d.       Buffer is not indirectly accessible in dimension %d.    value too large to convert to int       Cannot copy memoryview slice with indirect dimensions (axis %d) can't convert negative value to size_t  %.200s does not export expected C function %.200s       C function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)  ҎoV=$̚Dt$}dK2tt<dn:::::!;F;k;;;;      ?            V瞯<               @                           ]]]l]V]@]`_^`__X`m4X4B4,44 4n7x6506X6(700010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899                        00010203040506071011121314151617202122232425262730313233343536374041424344454647505152535455565760616263646566677071727374757677                                0123456789abcdef0123456789ABCDEF                                                      rY@            r                                                                                                                                  j                        z     8                           0  U   @   (                  |||M:|HHHHHHHHHHHHHHHHHHHHHHHHHHH HHHHHHHz4|4|4|4|4|4|4|4|4|y4|4|y4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|yz4|4|4|4|4|4|z4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|4|{4|{{zzeros   yen (line 1393) 
    yen(csgraph, source, sink, K, *, directed=True, return_predecessors=False,
        unweighted=False)

    Yen's K-Shortest Paths algorithm on a directed or undirected graph.

    .. versionadded:: 1.14.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    source : int
        The index of the starting node for the paths.
    sink : int
        The index of the ending node for the paths.
    K : int
        The number of shortest paths to find.
    directed : bool, optional
        If ``True`` (default), then find the shortest path on a directed graph:
        only move from point ``i`` to point ``j`` along paths ``csgraph[i, j]``.
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along ``csgraph[i, j]`` or
        ``csgraph[j, i]``.
    return_predecessors : bool, optional
        If ``True``, return the size ``(M, N)`` predecessor matrix. Default: ``False``.
    unweighted : bool, optional
        If ``True``, then find unweighted distances. That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized. Default: ``False``.

    Returns
    -------
    dist_array : ndarray
        Array of size ``M`` of shortest distances between the source and sink nodes.
        ``dist_array[i]`` gives the i-th shortest distance from the source to the sink
        along the graph. ``M`` is the number of shortest paths found, which is less than or
        equal to `K`.
    predecessors : ndarray
        Returned only if ``return_predecessors == True``.
        The M x N matrix of predecessors, which can be used to reconstruct
        the shortest paths.
        ``M`` is the number of shortest paths found, which is less than or equal to `K`.
        Row ``i`` of the predecessor matrix contains
        information on the ``i``-th shortest path from the source to the sink: each
        entry ``predecessors[i, j]`` gives the index of the previous node in the
        path from the source to node ``j``.  If the path does not pass via node ``j``,
        then ``predecessors[i, j] = -9999``.

    Raises
    ------
    NegativeCycleError:
        If there are negative cycles in the graph

    Notes
    -----
    Yen's algorithm is a graph search algorithm that finds single-source `K`-shortest
    loopless paths for a graph with nonnegative edge cost. The algorithm was published
    by Jin Y. Yen in 1971 and employs any shortest path algorithm to find the best path,
    then proceeds to find ``K - 1`` deviations of the best path.

    The algorithm is based on Dijsktra's algorithm for finding each shortest path.
    In case there are negative edges in the graph, Johnson's algorithm is applied.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    References
    ----------
    .. [1] https://en.wikipedia.org/wiki/Yen%27s_algorithm
    .. [2] https://www.ams.org/journals/qam/1970-27-04/S0033-569X-1970-0253822-7/

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import yen

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_array, predecessors = yen(csgraph=graph, source=0, sink=3, K=2,
    ...                                directed=False, return_predecessors=True)
    >>> dist_array
    array([2., 5.])
    >>> predecessors
    array([[-9999,     0, -9999,     1],
        [-9999, -9999,     0,     2]], dtype=int32)

     yen where      warnings warn   validate_graph  unweighted      unrecognized method '%s' tocsr tocoo    __test__ sum    <stringsource>  __spec__        source_matrix source size sink          shortest_path (line 47)                         
    shortest_path(csgraph, method='auto', directed=True, return_predecessors=False,
                  unweighted=False, overwrite=False, indices=None)

    Perform a shortest-path graph search on a positive directed or
    undirected graph.

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    method : string ['auto'|'FW'|'D'], optional
        Algorithm to use for shortest paths.  Options are:

           'auto' -- (default) select the best among 'FW', 'D', 'BF', or 'J'
                     based on the input data.

           'FW'   -- Floyd-Warshall algorithm.
                     Computational cost is approximately ``O[N^3]``.
                     The input csgraph will be converted to a dense representation.

           'D'    -- Dijkstra's algorithm with priority queue.
                     Computational cost is approximately ``O[I * (E + N) * log(N)]``,
                     where ``E`` is the number of edges in the graph,
                     and ``I = len(indices)`` if ``indices`` is passed. Otherwise,
                     ``I = N``.
                     The input csgraph will be converted to a csr representation.

           'BF'   -- Bellman-Ford algorithm.
                     This algorithm can be used when weights are negative.
                     If a negative cycle is encountered, an error will be raised.
                     Computational cost is approximately ``O[N(N^2 k)]``, where
                     ``k`` is the average number of connected edges per node.
                     The input csgraph will be converted to a csr representation.

           'J'    -- Johnson's algorithm.
                     Like the Bellman-Ford algorithm, Johnson's algorithm is
                     designed for use when the weights are negative. It combines
                     the Bellman-Ford algorithm with Dijkstra's algorithm for
                     faster computation.

    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.
    overwrite : bool, optional
        If True, overwrite csgraph with the result.  This applies only if
        method == 'FW' and csgraph is a dense, c-ordered array with
        dtype=float64.
    indices : array_like or int, optional
        If specified, only compute the paths from the points at the given
        indices. Incompatible with method == 'FW'.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.
    predecessors : ndarray, shape (n_indices, n_nodes,)
        Returned only if return_predecessors == True.
        If `indices` is None then ``n_indices = n_nodes`` and the shape of
        the matrix becomes ``(n_nodes, n_nodes)``.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    See Also
    --------
    :ref:`word-ladders-example` : An illustratation of the ``shortest_path`` API with a meaninful example.
                                  It also reconstructs the shortest path by using predecessors matrix returned
                                  by this function.

    Notes
    -----
    As currently implemented, Dijkstra's algorithm and Johnson's algorithm
    do not work for graphs with direction-dependent distances when
    directed == False.  i.e., if csgraph[i,j] and csgraph[j,i] are non-equal
    edges, method='D' may yield an incorrect result.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import shortest_path

    >>> graph = [
    ... [0, 0, 7, 0],
    ... [0, 0, 8, 5],
    ... [7, 8, 0, 0],
    ... [0, 5, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 6 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 2)	7
    	(1, 2)	8
    	(1, 3)	5
    	(2, 0)	7
    	(2, 1)	8
    	(3, 1)	5

    >>> sources = [0, 2]
    >>> dist_matrix, predecessors = shortest_path(csgraph=graph, directed=False, indices=sources, return_predecessors=True)
    >>> dist_matrix
    array([[ 0., 15.,  7., 20.],
           [ 7.,  8.,  0., 13.]])
    >>> predecessors
    array([[-9999,     2,     0,     1],
           [    2,     2, -9999,     1]], dtype=int32)

    Reconstructing shortest paths from sources to all the nodes of the graph.

    >>> shortest_paths = {}
    >>> for idx in range(len(sources)):
    ...     for node in range(4):
    ...         curr_node = node # start from the destination node
    ...         path = []
    ...         while curr_node != -9999: # no previous node available, exit the loop
    ...             path = [curr_node] + path # prefix the previous node obtained from the last iteration
    ...             curr_node = int(predecessors[idx][curr_node]) # set current node to previous node
    ...         shortest_paths[(sources[idx], node)] = path
    ...

    Computing the length of the shortest path from node 0 to node 3
    of the graph. It can be observed that computed length and the
    ``dist_matrix`` value are exactly same.

    >>> shortest_paths[(0, 3)]
    [0, 2, 1, 3]
    >>> path03 = shortest_paths[(0, 3)]
    >>> sum([graph[path03[0], path03[1]], graph[path03[1], path03[2]], graph[path03[2], path03[3]]])
    np.int64(20)
    >>> dist_matrix[0][3]
    np.float64(20.0)

    Another example of computing shortest path length from node 2 to node 3.
    Here, ``dist_matrix[1][3]`` is used to get the length of the path returned by
    ``shortest_path``. This is because node 2 is the second source, so the
    lengths of the path from it to other nodes in the graph will be at index 1
    in ``dist_matrix``.

    >>> shortest_paths[(2, 3)]
    [2, 1, 3]
    >>> path23 = shortest_paths[(2, 3)]
    >>> sum([graph[path23[0], path23[1]], graph[path23[1], path23[2]]])
    np.int64(13)
    >>> dist_matrix[1][3]
    np.float64(13.0)

            shortest_path shape             __setstate_cython__     __setstate__    __set_name__ self       scipy.sparse.csgraph._validation                                scipy/sparse/csgraph/_shortest_path.pyx                         scipy.sparse.csgraph._shortest_path             scipy.sparse._sputils   scipy.sparse            safely_cast_index_arrays        return_shape    return_predecessors ret reshape __reduce_ex__   __reduce_cython__       __reduce__ range        __qualname__    __pyx_vtable__  __pyx_state     __prepare__     predecessor_matrix pop  overwrite order ones    numpy._core.umath failed to import                              numpy._core.multiarray failed to import numpy   num_paths_found np                              no default __reduce__ due to non-trivial __cinit__ nnz nan      __name__ msg    __mro_entries__ __module__      min_only method __metaclass__   message __main__ ma limitf      limit must be >= 0 limit        johnson (line 1111)             johnson_dist_array                              
    johnson(csgraph, directed=True, indices=None, return_predecessors=False,
            unweighted=False)

    Compute the shortest path lengths using Johnson's algorithm.

    Johnson's algorithm combines the Bellman-Ford algorithm and Dijkstra's
    algorithm to quickly find shortest paths in a way that is robust to
    the presence of negative cycles.  If a negative cycle is detected,
    an error is raised.  For graphs without negative edge weights,
    dijkstra may be faster.

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    indices : array_like or int, optional
        if specified, only compute the paths from the points at the given
        indices.
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.

    predecessors : ndarray, shape (n_indices, n_nodes,)
        Returned only if return_predecessors == True.
        If `indices` is None then ``n_indices = n_nodes`` and the shape of
        the matrix becomes ``(n_nodes, n_nodes)``.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    Notes
    -----
    This routine is specially designed for graphs with negative edge weights.
    If all edge weights are positive, then Dijkstra's algorithm is a better
    choice.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import johnson

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_matrix, predecessors = johnson(csgraph=graph, directed=False, indices=0, return_predecessors=True)
    >>> dist_matrix
    array([0., 1., 2., 2.])
    >>> predecessors
    array([-9999,     0,     0,     1], dtype=int32)

            johnson issparse isinf  isfinite        isenabled       is_sparse       _is_coroutine   isMaskedArray int32     _initializing   __init__ inf indptr     indices out of range 0...N      indices         has_negative_weights    __getstate__ gc __func__ full format    floyd_warshall (line 290)                       
    floyd_warshall(csgraph, directed=True, return_predecessors=False,
                   unweighted=False, overwrite=False)

    Compute the shortest path lengths using the Floyd-Warshall algorithm

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.
    overwrite : bool, optional
        If True, overwrite csgraph with the result.  This applies only if
        csgraph is a dense, c-ordered array with dtype=float64.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.

    predecessors : ndarray
        Returned only if return_predecessors == True.
        The N x N matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    Notes
    -----
    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import floyd_warshall

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_matrix, predecessors = floyd_warshall(csgraph=graph, directed=False, return_predecessors=True)
    >>> dist_matrix
    array([[0., 1., 2., 2.],
           [1., 0., 3., 1.],
           [2., 3., 0., 3.],
           [2., 1., 3., 0.]])
    >>> predecessors
    array([[-9999,     0,     0,     1],
           [    1, -9999,     0,     1],
           [    2,     0, -9999,     2],
           [    1,     3,     3, -9999]], dtype=int32)

            floyd_warshall  float64 flat fill       , expected  enable empty edges  dummy_source_matrix             dummy_int_array dummy_double_array dtype        __doc__ dist_matrix     dist_array      disable directed        dijkstra (line 483)             
    dijkstra(csgraph, directed=True, indices=None, return_predecessors=False,
             unweighted=False, limit=np.inf, min_only=False)

    Dijkstra algorithm using priority queue

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of non-negative distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j] and from
        point j to i along paths csgraph[j, i].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j or j to i along either
        csgraph[i, j] or csgraph[j, i].

        .. warning:: Refer the notes below while using with ``directed=False``.
    indices : array_like or int, optional
        if specified, only compute the paths from the points at the given
        indices.
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.
    limit : float, optional
        The maximum distance to calculate, must be >= 0. Using a smaller limit
        will decrease computation time by aborting calculations between pairs
        that are separated by a distance > limit. For such pairs, the distance
        will be equal to np.inf (i.e., not connected).

        .. versionadded:: 0.14.0
    min_only : bool, optional
        If False (default), for every node in the graph, find the shortest path
        from every node in indices.
        If True, for every node in the graph, find the shortest path from any
        of the nodes in indices (which can be substantially faster).

        .. versionadded:: 1.3.0

    Returns
    -------
    dist_matrix : ndarray, shape ([n_indices, ]n_nodes,)
        The matrix of distances between graph nodes. If min_only=False,
        dist_matrix has shape (n_indices, n_nodes) and dist_matrix[i, j]
        gives the shortest distance from point i to point j along the graph.
        If min_only=True, dist_matrix has shape (n_nodes,) and contains for
        a given node the shortest path to that node from any of the nodes
        in indices.
    predecessors : ndarray, shape ([n_indices, ]n_nodes,)
        If ``min_only=False``, this has shape ``(n_indices, n_nodes)``,
        otherwise it has shape ``(n_nodes,)``.
        If `indices` is None and ``min_only=False`` then ``n_indices = n_nodes``
        and the shape of the matrix becomes ``(n_nodes, n_nodes)``.
        Returned only if return_predecessors == True.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    sources : ndarray, shape (n_nodes,)
        Returned only if min_only=True and return_predecessors=True.
        Contains the index of the source which had the shortest path
        to each target.  If no path exists within the limit,
        this will contain -9999.  The value at the indices passed
        will be equal to that index (i.e. the fastest way to reach
        node i, is to start on node i).

    Notes
    -----
    As currently implemented, Dijkstra's algorithm does not work for
    graphs with direction-dependent distances when directed == False.
    i.e., if csgraph[i,j] and csgraph[j,i] are not equal and
    both are nonzero, setting directed=False will not yield the correct
    result.

    Also, this routine does not work for graphs with negative
    distances.  Negative distances can lead to infinite cycles that must
    be handled by specialized algorithms such as Bellman-Ford's algorithm
    or Johnson's algorithm.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import dijkstra

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [0, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 4 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 3)	3

    >>> dist_matrix, predecessors = dijkstra(csgraph=graph, directed=False, indices=0, return_predecessors=True)
    >>> dist_matrix
    array([0., 1., 2., 2.])
    >>> predecessors
    array([-9999,     0,     0,     1], dtype=int32)

           dijkstra        diagonal        dense_output data       csr_output      csr_indptr      csr_indices     csr_data        csr_array       csrT_indptr     csrT_indices    csrT_data csrT csr      csgraphT        csgraph csc count       copy_if_sparse  copy_if_dense copy coo          convert_pydata_sparse_to_scipy  compressed      cline_in_traceback              __class_getitem__               bellman_ford (line 870)         
    bellman_ford(csgraph, directed=True, indices=None, return_predecessors=False,
                 unweighted=False)

    Compute the shortest path lengths using the Bellman-Ford algorithm.

    The Bellman-Ford algorithm can robustly deal with graphs with negative
    weights.  If a negative cycle is detected, an error is raised.  For
    graphs without negative edge weights, Dijkstra's algorithm may be faster.

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    indices : array_like or int, optional
        if specified, only compute the paths from the points at the given
        indices.
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.

    predecessors : ndarray, shape (n_indices, n_nodes,)
        Returned only if ``return_predecessors=True``.
        If `indices` is None then ``n_indices = n_nodes`` and the shape of
        the matrix becomes ``(n_nodes, n_nodes)``.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    Notes
    -----
    This routine is specially designed for graphs with negative edge weights.
    If all edge weights are positive, then Dijkstra's algorithm is a better
    choice.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import bellman_ford

    >>> graph = [
    ... [0, 1 ,2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_matrix, predecessors = bellman_ford(csgraph=graph, directed=False, indices=0, return_predecessors=True)
    >>> dist_matrix
    array([0., 1., 2., 2.])
    >>> predecessors
    array([-9999,     0,     0,     1], dtype=int32)

        bellman_ford auto       atleast_1d      asyncio.coroutines array arange any  and        add_note        accept_fv ? .   _YenCandidatePaths.__setstate_cython__                          _YenCandidatePaths.__reduce_cython__            _YenCandidatePaths      ValueError      TypeError T     RuntimeError            Note that Cython is deliberately stricter than PEP-484 and rejects subclasses of builtin types. If you need to pass subclasses then set the 'annotation_typing' directive to False.             Not enough rows in sources matrix. Got                          Not enough rows in predecessors matrix. Got                     Not enough rows in distances matrix. Got        No paths to pop No edge between nodes  Nk       Negative cycle in nodes %s      Negative cycle detected on node %i              NegativeCycleError.__init__     NegativeCycleError N K J        Invalid sources array shape                     Invalid predecessors array shape        ImportError ITYPE       Graph has negative weights: dijkstra will give inaccurate results if the graph contains negative cycles. Consider johnson or bellman_ford. FW   . Expected  DTYPE D                             Cannot specify indices with method == 'FW'. C BF        AssertionError                          
    yen(csgraph, source, sink, K, *, directed=True, return_predecessors=False,
        unweighted=False)

    Yen's K-Shortest Paths algorithm on a directed or undirected graph.

    .. versionadded:: 1.14.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    source : int
        The index of the starting node for the paths.
    sink : int
        The index of the ending node for the paths.
    K : int
        The number of shortest paths to find.
    directed : bool, optional
        If ``True`` (default), then find the shortest path on a directed graph:
        only move from point ``i`` to point ``j`` along paths ``csgraph[i, j]``.
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along ``csgraph[i, j]`` or
        ``csgraph[j, i]``.
    return_predecessors : bool, optional
        If ``True``, return the size ``(M, N)`` predecessor matrix. Default: ``False``.
    unweighted : bool, optional
        If ``True``, then find unweighted distances. That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized. Default: ``False``.

    Returns
    -------
    dist_array : ndarray
        Array of size ``M`` of shortest distances between the source and sink nodes.
        ``dist_array[i]`` gives the i-th shortest distance from the source to the sink
        along the graph. ``M`` is the number of shortest paths found, which is less than or
        equal to `K`.
    predecessors : ndarray
        Returned only if ``return_predecessors == True``.
        The M x N matrix of predecessors, which can be used to reconstruct
        the shortest paths.
        ``M`` is the number of shortest paths found, which is less than or equal to `K`.
        Row ``i`` of the predecessor matrix contains
        information on the ``i``-th shortest path from the source to the sink: each
        entry ``predecessors[i, j]`` gives the index of the previous node in the
        path from the source to node ``j``.  If the path does not pass via node ``j``,
        then ``predecessors[i, j] = -9999``.

    Raises
    ------
    NegativeCycleError:
        If there are negative cycles in the graph

    Notes
    -----
    Yen's algorithm is a graph search algorithm that finds single-source `K`-shortest
    loopless paths for a graph with nonnegative edge cost. The algorithm was published
    by Jin Y. Yen in 1971 and employs any shortest path algorithm to find the best path,
    then proceeds to find ``K - 1`` deviations of the best path.

    The algorithm is based on Dijsktra's algorithm for finding each shortest path.
    In case there are negative edges in the graph, Johnson's algorithm is applied.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    References
    ----------
    .. [1] https://en.wikipedia.org/wiki/Yen%27s_algorithm
    .. [2] https://www.ams.org/journals/qam/1970-27-04/S0033-569X-1970-0253822-7/

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import yen

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_array, predecessors = yen(csgraph=graph, source=0, sink=3, K=2,
    ...                                directed=False, return_predecessors=True)
    >>> dist_array
    array([2., 5.])
    >>> predecessors
    array([[-9999,     0, -9999,     1],
        [-9999, -9999,     0,     2]], dtype=int32)

                    
    johnson(csgraph, directed=True, indices=None, return_predecessors=False,
            unweighted=False)

    Compute the shortest path lengths using Johnson's algorithm.

    Johnson's algorithm combines the Bellman-Ford algorithm and Dijkstra's
    algorithm to quickly find shortest paths in a way that is robust to
    the presence of negative cycles.  If a negative cycle is detected,
    an error is raised.  For graphs without negative edge weights,
    dijkstra may be faster.

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    indices : array_like or int, optional
        if specified, only compute the paths from the points at the given
        indices.
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.

    predecessors : ndarray, shape (n_indices, n_nodes,)
        Returned only if return_predecessors == True.
        If `indices` is None then ``n_indices = n_nodes`` and the shape of
        the matrix becomes ``(n_nodes, n_nodes)``.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    Notes
    -----
    This routine is specially designed for graphs with negative edge weights.
    If all edge weights are positive, then Dijkstra's algorithm is a better
    choice.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import johnson

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_matrix, predecessors = johnson(csgraph=graph, directed=False, indices=0, return_predecessors=True)
    >>> dist_matrix
    array([0., 1., 2., 2.])
    >>> predecessors
    array([-9999,     0,     0,     1], dtype=int32)

                                    
    bellman_ford(csgraph, directed=True, indices=None, return_predecessors=False,
                 unweighted=False)

    Compute the shortest path lengths using the Bellman-Ford algorithm.

    The Bellman-Ford algorithm can robustly deal with graphs with negative
    weights.  If a negative cycle is detected, an error is raised.  For
    graphs without negative edge weights, Dijkstra's algorithm may be faster.

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    indices : array_like or int, optional
        if specified, only compute the paths from the points at the given
        indices.
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.

    predecessors : ndarray, shape (n_indices, n_nodes,)
        Returned only if ``return_predecessors=True``.
        If `indices` is None then ``n_indices = n_nodes`` and the shape of
        the matrix becomes ``(n_nodes, n_nodes)``.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    Notes
    -----
    This routine is specially designed for graphs with negative edge weights.
    If all edge weights are positive, then Dijkstra's algorithm is a better
    choice.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import bellman_ford

    >>> graph = [
    ... [0, 1 ,2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_matrix, predecessors = bellman_ford(csgraph=graph, directed=False, indices=0, return_predecessors=True)
    >>> dist_matrix
    array([0., 1., 2., 2.])
    >>> predecessors
    array([-9999,     0,     0,     1], dtype=int32)

                                
    dijkstra(csgraph, directed=True, indices=None, return_predecessors=False,
             unweighted=False, limit=np.inf, min_only=False)

    Dijkstra algorithm using priority queue

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of non-negative distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j] and from
        point j to i along paths csgraph[j, i].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j or j to i along either
        csgraph[i, j] or csgraph[j, i].

        .. warning:: Refer the notes below while using with ``directed=False``.
    indices : array_like or int, optional
        if specified, only compute the paths from the points at the given
        indices.
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.
    limit : float, optional
        The maximum distance to calculate, must be >= 0. Using a smaller limit
        will decrease computation time by aborting calculations between pairs
        that are separated by a distance > limit. For such pairs, the distance
        will be equal to np.inf (i.e., not connected).

        .. versionadded:: 0.14.0
    min_only : bool, optional
        If False (default), for every node in the graph, find the shortest path
        from every node in indices.
        If True, for every node in the graph, find the shortest path from any
        of the nodes in indices (which can be substantially faster).

        .. versionadded:: 1.3.0

    Returns
    -------
    dist_matrix : ndarray, shape ([n_indices, ]n_nodes,)
        The matrix of distances between graph nodes. If min_only=False,
        dist_matrix has shape (n_indices, n_nodes) and dist_matrix[i, j]
        gives the shortest distance from point i to point j along the graph.
        If min_only=True, dist_matrix has shape (n_nodes,) and contains for
        a given node the shortest path to that node from any of the nodes
        in indices.
    predecessors : ndarray, shape ([n_indices, ]n_nodes,)
        If ``min_only=False``, this has shape ``(n_indices, n_nodes)``,
        otherwise it has shape ``(n_nodes,)``.
        If `indices` is None and ``min_only=False`` then ``n_indices = n_nodes``
        and the shape of the matrix becomes ``(n_nodes, n_nodes)``.
        Returned only if return_predecessors == True.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    sources : ndarray, shape (n_nodes,)
        Returned only if min_only=True and return_predecessors=True.
        Contains the index of the source which had the shortest path
        to each target.  If no path exists within the limit,
        this will contain -9999.  The value at the indices passed
        will be equal to that index (i.e. the fastest way to reach
        node i, is to start on node i).

    Notes
    -----
    As currently implemented, Dijkstra's algorithm does not work for
    graphs with direction-dependent distances when directed == False.
    i.e., if csgraph[i,j] and csgraph[j,i] are not equal and
    both are nonzero, setting directed=False will not yield the correct
    result.

    Also, this routine does not work for graphs with negative
    distances.  Negative distances can lead to infinite cycles that must
    be handled by specialized algorithms such as Bellman-Ford's algorithm
    or Johnson's algorithm.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import dijkstra

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [0, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 4 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 3)	3

    >>> dist_matrix, predecessors = dijkstra(csgraph=graph, directed=False, indices=0, return_predecessors=True)
    >>> dist_matrix
    array([0., 1., 2., 2.])
    >>> predecessors
    array([-9999,     0,     0,     1], dtype=int32)

                   
    floyd_warshall(csgraph, directed=True, return_predecessors=False,
                   unweighted=False, overwrite=False)

    Compute the shortest path lengths using the Floyd-Warshall algorithm

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.
    overwrite : bool, optional
        If True, overwrite csgraph with the result.  This applies only if
        csgraph is a dense, c-ordered array with dtype=float64.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.

    predecessors : ndarray
        Returned only if return_predecessors == True.
        The N x N matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    Notes
    -----
    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import floyd_warshall

    >>> graph = [
    ... [0, 1, 2, 0],
    ... [0, 0, 0, 1],
    ... [2, 0, 0, 3],
    ... [0, 0, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 5 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 1)	1
    	(0, 2)	2
    	(1, 3)	1
    	(2, 0)	2
    	(2, 3)	3

    >>> dist_matrix, predecessors = floyd_warshall(csgraph=graph, directed=False, return_predecessors=True)
    >>> dist_matrix
    array([[0., 1., 2., 2.],
           [1., 0., 3., 1.],
           [2., 3., 0., 3.],
           [2., 1., 3., 0.]])
    >>> predecessors
    array([[-9999,     0,     0,     1],
           [    1, -9999,     0,     1],
           [    2,     0, -9999,     2],
           [    1,     3,     3, -9999]], dtype=int32)

                                    
    shortest_path(csgraph, method='auto', directed=True, return_predecessors=False,
                  unweighted=False, overwrite=False, indices=None)

    Perform a shortest-path graph search on a positive directed or
    undirected graph.

    .. versionadded:: 0.11.0

    Parameters
    ----------
    csgraph : array_like, or sparse array or matrix, 2 dimensions
        The N x N array of distances representing the input graph.
    method : string ['auto'|'FW'|'D'], optional
        Algorithm to use for shortest paths.  Options are:

           'auto' -- (default) select the best among 'FW', 'D', 'BF', or 'J'
                     based on the input data.

           'FW'   -- Floyd-Warshall algorithm.
                     Computational cost is approximately ``O[N^3]``.
                     The input csgraph will be converted to a dense representation.

           'D'    -- Dijkstra's algorithm with priority queue.
                     Computational cost is approximately ``O[I * (E + N) * log(N)]``,
                     where ``E`` is the number of edges in the graph,
                     and ``I = len(indices)`` if ``indices`` is passed. Otherwise,
                     ``I = N``.
                     The input csgraph will be converted to a csr representation.

           'BF'   -- Bellman-Ford algorithm.
                     This algorithm can be used when weights are negative.
                     If a negative cycle is encountered, an error will be raised.
                     Computational cost is approximately ``O[N(N^2 k)]``, where
                     ``k`` is the average number of connected edges per node.
                     The input csgraph will be converted to a csr representation.

           'J'    -- Johnson's algorithm.
                     Like the Bellman-Ford algorithm, Johnson's algorithm is
                     designed for use when the weights are negative. It combines
                     the Bellman-Ford algorithm with Dijkstra's algorithm for
                     faster computation.

    directed : bool, optional
        If True (default), then find the shortest path on a directed graph:
        only move from point i to point j along paths csgraph[i, j].
        If False, then find the shortest path on an undirected graph: the
        algorithm can progress from point i to j along csgraph[i, j] or
        csgraph[j, i]
    return_predecessors : bool, optional
        If True, return the size (N, N) predecessor matrix.
    unweighted : bool, optional
        If True, then find unweighted distances.  That is, rather than finding
        the path between each point such that the sum of weights is minimized,
        find the path such that the number of edges is minimized.
    overwrite : bool, optional
        If True, overwrite csgraph with the result.  This applies only if
        method == 'FW' and csgraph is a dense, c-ordered array with
        dtype=float64.
    indices : array_like or int, optional
        If specified, only compute the paths from the points at the given
        indices. Incompatible with method == 'FW'.

    Returns
    -------
    dist_matrix : ndarray
        The N x N matrix of distances between graph nodes. dist_matrix[i,j]
        gives the shortest distance from point i to point j along the graph.
    predecessors : ndarray, shape (n_indices, n_nodes,)
        Returned only if return_predecessors == True.
        If `indices` is None then ``n_indices = n_nodes`` and the shape of
        the matrix becomes ``(n_nodes, n_nodes)``.
        The matrix of predecessors, which can be used to reconstruct
        the shortest paths.  Row i of the predecessor matrix contains
        information on the shortest paths from point i: each entry
        predecessors[i, j] gives the index of the previous node in the
        path from point i to point j.  If no path exists between point
        i and j, then predecessors[i, j] = -9999

    Raises
    ------
    NegativeCycleError:
        if there are negative cycles in the graph

    See Also
    --------
    :ref:`word-ladders-example` : An illustratation of the ``shortest_path`` API with a meaninful example.
                                  It also reconstructs the shortest path by using predecessors matrix returned
                                  by this function.

    Notes
    -----
    As currently implemented, Dijkstra's algorithm and Johnson's algorithm
    do not work for graphs with direction-dependent distances when
    directed == False.  i.e., if csgraph[i,j] and csgraph[j,i] are non-equal
    edges, method='D' may yield an incorrect result.

    If multiple valid solutions are possible, output may vary with SciPy and
    Python version.

    Examples
    --------
    >>> from scipy.sparse import csr_array
    >>> from scipy.sparse.csgraph import shortest_path

    >>> graph = [
    ... [0, 0, 7, 0],
    ... [0, 0, 8, 5],
    ... [7, 8, 0, 0],
    ... [0, 5, 0, 0]
    ... ]
    >>> graph = csr_array(graph)
    >>> print(graph)
    <Compressed Sparse Row sparse array of dtype 'int64'
    	with 6 stored elements and shape (4, 4)>
    	Coords	Values
    	(0, 2)	7
    	(1, 2)	8
    	(1, 3)	5
    	(2, 0)	7
    	(2, 1)	8
    	(3, 1)	5

    >>> sources = [0, 2]
    >>> dist_matrix, predecessors = shortest_path(csgraph=graph, directed=False, indices=sources, return_predecessors=True)
    >>> dist_matrix
    array([[ 0., 15.,  7., 20.],
           [ 7.,  8.,  0., 13.]])
    >>> predecessors
    array([[-9999,     2,     0,     1],
           [    2,     2, -9999,     1]], dtype=int32)

    Reconstructing shortest paths from sources to all the nodes of the graph.

    >>> shortest_paths = {}
    >>> for idx in range(len(sources)):
    ...     for node in range(4):
    ...         curr_node = node # start from the destination node
    ...         path = []
    ...         while curr_node != -9999: # no previous node available, exit the loop
    ...             path = [curr_node] + path # prefix the previous node obtained from the last iteration
    ...             curr_node = int(predecessors[idx][curr_node]) # set current node to previous node
    ...         shortest_paths[(sources[idx], node)] = path
    ...

    Computing the length of the shortest path from node 0 to node 3
    of the graph. It can be observed that computed length and the
    ``dist_matrix`` value are exactly same.

    >>> shortest_paths[(0, 3)]
    [0, 2, 1, 3]
    >>> path03 = shortest_paths[(0, 3)]
    >>> sum([graph[path03[0], path03[1]], graph[path03[1], path03[2]], graph[path03[2], path03[3]]])
    np.int64(20)
    >>> dist_matrix[0][3]
    np.float64(20.0)

    Another example of computing shortest path length from node 2 to node 3.
    Here, ``dist_matrix[1][3]`` is used to get the length of the path returned by
    ``shortest_path``. This is because node 2 is the second source, so the
    lengths of the path from it to other nodes in the graph will be at index 1
    in ``dist_matrix``.

    >>> shortest_paths[(2, 3)]
    [2, 1, 3]
    >>> path23 = shortest_paths[(2, 3)]
    >>> sum([graph[path23[0], path23[1]], graph[path23[1], path23[2]]])
    np.int64(13)
    >>> dist_matrix[1][3]
    np.float64(13.0)

            
Routines for performing shortest-path graph searches

The main interface is in the function :func:`shortest_path`.  This
calls cython routines that compute the shortest path using
the Floyd-Warshall algorithm, Dijkstra's algorithm with priority queue,
the Bellman-Ford algorithm, or Johnson's Algorithm.

Yen's k-Shortest Path Algorithm is available for
finding the k-shortest paths between two nodes in a graph.
  
+Q                        T nAYj}Aaq$A5JfA5#T6q2U!7%q7%uA2T)2Q#1!6#V1q'q
'(/y)*G1*1!t3a()NbPQqAZwjqq1BfASa7"F!1q$AXWHA%-Ya'7!8:XQAq(r1C1A c+Rq%Qq
",HBa""$4HAQ:R'xr                      _AB qxq	1-Q nAYj*!vQa xs!"G1CvQwgS"F!9F%vQwgS"Kq!q&2T("Cs"DA*AQ "F"Cq
$fAuARqq'#QkA qRvRs!:Tq%qRvRs!:Tq 6#V1we56ayt1
 qq
-|1!*MQt3a !Fb =A"F"Cq
$fAqRvQcq"F!3fA m1  1--B"A9BjQ&gRvQAXWHA%Ya ]!G8:XQ-Qa 1:Taqq81A"(!1{(!1                              /~ nAYj*!vQa xs!"G1CvQ"F!9F%vQq&2T("Cs"DA*AQ7'Ab1HHBa "F"Cq
$fAuARqq'#QkA qRvRs!:Tq%qRvRs$fAq2U!7%q7!6ayt1q$AQ%/}A%2!&aq'1a'4At3a !Fbq81A"(!1{(!1                 oQ%Rqt nAYj}ArQgV2QQa 	vQa xs!"G1CvQ1A7'A"F!9F%vWE1A7'A"Kq!q&2T("Cs"DA*AQ!wbj qbQc6q1KqbRs!:T6q1BgQc+[ q1!64vQe1ABfBd&aq!63azV1e1ABfBc*Da1!6#V1BfASa!63azV1BfBc*Daq2U!7%q7!6ayt1qRvQcq"F!3fA1Qa Q**;1##7q$A Q**;1##7q 	wban$<AV7$a1A1Qam1~Q!!5Q$A!"!+=!,N!!..B!!"q1Kxq&haq!!Kxq&haq{(!1                           Ar .*A!,A!/t1t81A1L5q1ARvQ.aqRvQk&,G6RvRs$fA1AqrQk#Rq !#2V1Ky2Rqq}Aq      1Z ,AYjBfBa !9Ja"$a#4q
 wcG6!0HAQ1whd'qvRqs.aG;aG1BiqE&1a87%s#Rr2RqrQfBaQwc87!*AQ~Qiq2!)(	1xq	,A#<xq	1|1IQ0'|81	1way+1",ha 	j4Ba    q!6                ;     @3  <   <  `F  (H  J  J	  J	  %L  LH  /M  N  U  	V  6    @  h        E  Z,  YX    0  ː`      ʓT  ֓  0  X  p      P  0  0`  @    0   	`  j  `p  0  `  A  `G  G  G  H	  H@	  Jd	  0M	  W
  X8
  Zl
  P^
  a
  
  (  <  P  d       @      t    L             #P  @|  0~    @            @,  `@  T  h  Г|    `    8  `  p           p  <  p\  `    `      (  @T  t     0    P     @  @`  `t  P  p      P4  `       @  0       @  `d       @    4  `                (  Pt  @         8             zR x  $      `.	   FJw ?9*3$"       D   7              \   7p	          $   t   "   ESG
B 0      Z   ECDEH
E
A ,      ܔSE   ESP
A   ,         ASP
A   ,   0  ,   ESP]
K      `  ,%       ,   t  H   AC\
I   (        ESL
G         ?   EJC       zPLR xA    ,   $   PA[    ECB[
E  ,   D  8   ACBEH
D ,   t     ACBEH	
D ,     a   ACDLM$
E $     Xcn   ESH7
I          zPLR x@    0   $   h`  3  EKPo
A       X   oB4   
  ,   t     EFFTr
I  ,     H%   AC\43
D   $     H9~   ESHG
I        >            >       ,   $  >i    ECCd
IL
D`,   T  >i    ECCd
IL
D`      8?   EC
I   0     A    EGM
D         A)     0     lC	  w  ECBOD
H      D  @E        X  Lu   ECc
E   0   |  PN   ECM
LN   ,     ,P   ECM
J   ,     SQ   ECM
A   ,     V$   ACHR$
G  (   @      ESJ
E        l  p            |            h            dM    ACH        @z    AFKg      p    aZHE $         AQu
YZ
F ,   4  H    ECBJj
Bl
A$   d      ECAN
I{(     O@    ACBEEKtL     $   NCIF
H
DxC(     c@w   ECDFd       4  AS   ACJD4   X  /   ACDEF
C`
H  0     |   ACMi
Fh
H     h%                 EFEM
C     9H       4   	     ENBH
J^
JX
H  H   H	  B   EF
IH
HR
N
BA
Oa
OZ  ,   	  Y   ECP-
D   (   	  G-0   ECP0  0   	  m   NC
BzFPN ,   $
  Ho   ECBEEEH
F,   T
  q   ECHH\
D  H   
  v   EFo
Fo
Ae
Kw
IY
Gp
HA
C(   
  Lx   EFA
EY
G,   
   |<   EC~
Jd
Lw
A ,   ,  }   ECDGD
G     \             p                          $)            @       ,     L   ECBED
GJ       ,r       ,     }   COAIKC     4  >u]    AGT  $   T  ȅ    EXk
He
K$   |      EUs
Ce
K     x    Y`H           Y`H       X            Tw    FCm       ]    QCH  $   8  {    ACAZ
AZ   `  Ly    sCtF      y    sCtF (        ECA
IL
D$     Ќ}    EC@
Hl   $     (}    EC@
Hl   $         EC@
Hl
D$   D      EMF
Ht   (   l  p    ACAA
Jr
F      W    iCj        $Z    iCAl     d"            ^    iCq   $         ECBDb
H $   4  X    ECBDb
H $   \     iCBH 
J     9    ECAk     ؒ       4        ALh
Ka
OW
IW
I   8        EIML
Iz
F
I   ,            @  |           T  x   qJhA   (   x  7   ECBEM)
K <     (G   ECFJS
Ee
K
O      85       ,     d   ECBJGG]
A,   (  T    ECBEED
A   (   X  wp    ECBEEDq  $     p    cCE         qt    EJCa       q|    ECKh ,     Mr    ECBHEEF   $   $  
sS    ECBEF}    L  5s   ECA  (   p  &t    ECBJ  (     t   ECDL ,     qv   ECBEEEHa  4     t   ECBGD
E
I   ,   0     EFDEEDX
[    `      EKh
H         x    EKh
H             EKh
H         p    EKh
H             EKl
D         h    EKl
D   <   8     ECS
Ep
PX
H[
E~
A  (   x  T   EFO
Fi
C  8     8;   EJGy
Ai
GW
I        <    ECH     P    zQ        Dx    bQ  <   4  1   ECM
KD
DG
QW
I\
A  ,   t  HuK   EEBEEQ#   (     cv   ECBIH     L4       ,     w1   ECK
ER      x       @   (  4Q   NFC]
DZFHL
D   (   l  P    OCM        nx    (     Ը    OCM        .x         xw                  $   ,      ECa
GW   $   T      ECf
B[
M4   |  2   ECDFJ
H`
E       Y
] e                  }
}	}}}}}}}}}     +  |+  X+  l+  `+  <+  p+  L+  8+  l+  p+  ). *   <     A7          =3o ' j   '  '  '                 GNU                `   ~FDO {"type":"deb","os":"ubuntu","name":"scipy","version":"1.16.3-4build1","architecture":"amd64"}                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 @                                                                                              I                                                                                                                           R                      H                                                                                                                    I                                                                                                                           I                                                                                                                     R                                   {                                                                                        R                @     H     g            X      `     N      `     L      `           ,             `           `                       `     `            T      `     H      `           "                         `           `           `     е      `           `          #       `            W      `     @            0                  *            -            (                         `           `          
 `           `     p      `     @     % `           ' `                                  
 `          	       Բ            в      `     ɲ      `     ò      `           `           `           `           `     @     E                          `           `     Ф      `           `           `           `           `           `     t      `     p      `     h      `     X     	 `     O      `     J      `     @     
 `     0      `            `          
 `           	 `           `           `     У      `     ţ      `           `          	 `          	 `                                 	 `                 x      `     h      `     `      `     S      `     @      `     0      `           `     	      `           `                                   `           `     ؎      `     Ȏ      `          !      p            f      `     a      `     X     	 `     U            H      `     0      `            `                        `           `          	 `     ؁      `     ΁      `           `           `          
 `          
            	 `     y      `     p     	 `     h      `     s           s      `     s            s      `     ps            ds      `     as      `     Xs     	 `     Ps      `     @s      `     9s      `     0s     	 `      s      `     s      `     	s      `      s     	 `     r      `     r      `     r     3       r      `     r      `     r      `     `r     (        r     #       r      `     r      `     r     
 `     r      `     q      `     q      `     q      `     q      `     q      `     q      `     q      `     q      `     pq      `     hq      `     dq      `     Pq      `     @q      `      q      `     q      `     p      `     p     $ `     p     (       @p     ! `     5p      `     (p      `     p      `      p      `     o      `     o      `     S     9      pS            bS      `     ]S      `     VS      `     HS      `     8S     	 `     (S            !S      `     S     	 `     S      `     	S      `     R            R      `     R      `     R      `     R     	 `     R      `     R      `      C           C            C      `                     z     t            U             d             r              `                         ]                          ]                   o                 8             0      
                                  o            (                           J             '             @#      	              o    &      o           o    &%      o    F                                                                                                                                                                                                                                                                                                                                                                                              l                     0`      @`      P`      ``      p`      `      `      `      `      `      `      `      `       a      a       a      0a      @a      Pa      `a      pa      a      a      a      a      a      a      a      a       b      b       b      0b      @b      Pb      `b      pb      b      b      b      b      b      b      b      b       c      c       c      0c      @c      Pc      `c      pc      c      c      c      c      c      c      c      c       d      d       d      0d      @d      Pd      `d      pd      d      d      d      d      d      d      d      d       e      e       e      0e      @e      Pe      `e      pe      e      e      e      e      e      e      e      e       f      f       f      0f      @f      Pf      `f      pf      f      f      f      f      f      f      f      f       g      g       g      0g      @g      Pg      `g      pg      g      g      g      g      g      g      g      g       h      h       h      0h      @h      Ph      `h      ph      h      h      h      h      h      h      h      h       i      i       i      0i      @i      Pi      `i      pi      i      i              t                                                                                                                                                                                                                                                          p                     )          p                     1          @                     ;          @                     D                                Q           @                     [           @                     d                                   q                                   }     @                                  @                                  `                                  `                                  P     p                          P     p                               0                                                                                                                                                                                      @                                   0                                  (                                                                                      (                                                         I       u                     4            B             2       0     G            3       P     @       y     H        y     I        v     6                            R                              `u                                                           z                                                   H0                    z     p0             M     @z                           0                    @                                                                                                                     @             =     >                                                                                                                     >                                                                                                                           0     8                @                                                                                                                                                                                   z                                                                                                                                                                                       `u                    R                         w     8                 
     n                       З                 V                       3                       4     P             @                                                                     3                       @{                             /usr/lib/debug/.dwz/x86_64-linux-gnu/python3-scipy.debug /\G,ճSW6_   b3f7b26bcbffe550a6d44862a7227062f7214d.debug     .shstrtab .note.gnu.build-id .gnu.hash .dynsym .dynstr .gnu.version .gnu.version_r .rela.dyn .rela.plt .init .plt.got .plt.sec .text .fini .rodata .eh_frame_hdr .eh_frame .gcc_except_table .note.gnu.property .note.package .init_array .fini_array .data.rel.ro .dynamic .got.plt .data .bss .gnu_debugaltlink .gnu_debuglink                                                                                            $                                 o                   $                             (             0      0                                0             8      8                                   8   o       &%      &%                                 E   o       &      &                                  T             '      '      @#                           ^      B       J      J      (                          h              `       `                                    c              `       `      	                            n             i      i                                   w             i      i      p	                                         @s      @s                   @                                                                                                                                       ,     ,                                               1     1                                               TI     TI     T                                          J     J                                                 J     J     p                                           ]     M                                               ]     M                                               ]     M     @                                          l     \                                r             n     ^     (                                        o     _                                             t     d                                                    p     	                              !                     p     M                              3                     p     4                                                    q     B                             