--- a/scripts/optimization/lsqnonneg.m	Tue Jan 13 11:56:00 2009 -0500
+++ b/scripts/optimization/lsqnonneg.m	Tue Jan 13 14:08:36 2009 -0500
@@ -69,11 +69,11 @@
   endif
 
 
-  MaxIter = optimget (options, "MaxIter", 1e5);
+  max_iter = optimget (options, "MaxIter", 1e5);
 
   ## Initialize the values.
   p = false (1, numel (x));
-  z = ~p;
+  z = !p;
   ## If the problem is significantly over-determined, preprocess it using a
   ## QR factorization first.
   if (rows (c) >= 1.5 * columns (c))
@@ -89,7 +89,7 @@
 
   iter = 0;
   ## LH3: test for completion.
-  while (any (z) && any (w(z) > 0) && iter < MaxIter)
+  while (any (z) && any (w(z) > 0) && iter < max_iter)
     ## LH4: find the maximum gradient.
     idx = find (w == max (w));
     if (numel (idx) > 1)
@@ -102,7 +102,7 @@
     p(idx) = true;
 
     newx = false;
-    while (! newx && iter < MaxIter)
+    while (! newx && iter < max_iter)
       iter++;
 
       ## LH6: compute the positive matrix and find the min norm solution
@@ -122,7 +122,7 @@
         x = x + alpha*(xtmp - x);
         ## LH11: move from P to Z all X == 0.
         z |= (x == 0);
-        p = ~z;
+        p = !z;
       endif
     endwhile
     w = c'*(d - c*x);
@@ -137,7 +137,7 @@
     residual = d - c*x;
   endif
   exitflag = iter;
-  if (nargout > 3 && iter >= MaxIter)
+  if (nargout > 3 && iter >= max_iter)
     exitflag = 0;
   endif
   if (nargout > 4)