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--- /arXMLiv/repos/arXMLiv/trunk/sty/0089.cls	2010-04-01 16:55:29.000000000 +0200
+++ /arXMLiv/repos/arXMLiv/trunk/sty/aa1.cls	2010-04-01 19:54:29.000000000 +0200
@@ -1,4 +1,4 @@
-% This is aa.cls
+% This is aa1.cls
% A&A DOCUMENT CLASS -- version 6.1 for LaTeX2e
%
% LaTeX document class for Astronomy and Astrophysics journal
@@ -71,9 +71,6 @@
\DeclareOption{longauth}{\@longauthtrue}
\DeclareOption{rnote}{\@rnotetrue}
\DeclareOption{oldversion}{\@oldversiontrue}
-%% January 2008 - abstract
-\DeclareOption{structabstract}{\@oldversionfalse}
\DeclareOption{letter}{\@lettertrue}
%
@@ -309,10 +306,6 @@
\fi

\def\keywords#1{\gdef\@keywords{#1}}
-%% January 2007
-\def\topics#1{\gdef\@topics{#1}}
-\def\@topics{}
-

\def\institute#1{\gdef\@institute{#1}}

@@ -417,12 +410,24 @@
\ch@ckobl{author}{Name(s) and initial(s) of author(s) should be given}
\ch@ckobl{institute}{Address(es) of author(s) should be given}
\if@oldversion
-\ch@ckobl{abstract}{An abstract should be given}
+\ch@ckobl{abstract}{abstract}
\else
-\ch@ckoblabs{abstract}{An abstract should be given}{An abstract should be given}
-{An abstract should be given}{An abstract should be given}{An abstract should be given}
+\ch@ckoblabs{abstract}{Mathematical optimization can be used as a computational tool to obtain the optimal solution to a given problem in a systematic
+and efficient way. For example, in twice-differentiable functions and problems with no constraints, the optimization consists
+of finding the points where the gradient of the objective function is zero and using the Hessian matrix to classify the type of each
+point. Sometimes, however it is impossible to compute these derivatives and other type of techniques must be employed such as the
+steepest descent/ascent method and more sophisticated methods such as those based on the evolutionary algorithms.}
+{We present a simple algorithm based on the idea of genetic algorithms (GA) for optimization. We refer to this algorithm as
+AGA (Asexual Genetic Algorithm) and apply it to two kinds of problems: the maximization of a function where classical methods fail
+and model fitting in astronomy. For the latter case, we minimize the chi-square function to estimate the parameters in two examples:
+the orbits of exoplanets by taking a set of radial velocity data, and the spectral energy distribution (SED) observed towards a YSO
+(Young Stellar Object).}
+{The algorithm AGA may also be called genetic, although it differs from standard genetic algorithms in two main aspects:
+a) the initial population is not encoded, and b) the new generations are constructed by asexual reproduction.}
+{Applying our algorithm in optimizing some complicated functions, we find the global maxima within a few iterations. For
+model fitting to the orbits of exoplanets and the SED of a YSO, we estimate the parameters and their associated errors.}{}
\fi
-\ch@ckobl{keywords}{Keywords should be given}
+\ch@ckobl{keywords}{Methods:numerical--Stars--55 Cancri--Planets and Satellites:general--ISM:individual(L1448)}
\begingroup
\begin{stopref}
\renewcommand\thefootnote{\@fnsymbol\c@footnote}%
@@ -522,8 +527,6 @@
\global\let\@title\@empty
\global\let\@subtitle\@empty
\global\let\@abstract\@empty
-%%January 2007
- \global\let\@topics\@empty
\global\let\@keywords\@empty
\global\let\keywords\relax
\global\let\title\relax
@@ -567,15 +570,8 @@
\setbox\authrun=\vbox\bgroup
\fi
-%% January 2007
- \if!\@topics!\vskip32pt\else
- \vskip24pt
- {\fontsize{12}{14}\selectfont\sffamily {\itshape \@topics} \hfill \fontsize{17}{20}\selectfont\sffamily Special feature}
- \vskip12pt
- \fi
\begin{center}
-%% Januray 2007
-%% \vskip24pt
+ \vskip24pt
\if@letter{\large \lettername}\fi
{\LARGE \sffamily\bfseries\boldmath
\hrule\@height\logodepth\@width\z@
@@ -1318,7 +1314,6 @@
\def\baselinestretch{1.5}
\let\AALogo\relax
\onecolumn
-  \AtEndDocument{\listofobjects}
\else
\if@onecolumn
\onecolumn
@@ -1641,6 +1636,7 @@
%
\uchyph=0
%
+\AtEndDocument{\listofobjects}
\long\def\Online{\if@online\else\@onlinetrue
\clearpage
@@ -1653,10 +1649,9 @@
}
\setcounter{page}{1}
-%% 2008
-%% \twocolumn[\vspace*{4cm}\noindent{\sffamily\bfseries\Huge\centerline{Online Material}}]
-%% \vfill
-%% \clearpage
+\twocolumn[\vspace*{4cm}\noindent{\sffamily\bfseries\Huge\centerline{Online Material}}]
+\vfill
+\clearpage
\fi}
\renewenvironment{thebibliography}[1]{%
@@ -1691,4 +1686,4 @@
%
\endinput
%%
-%% End of file aa.cls'.
+%% End of file aa1.cls'.

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