# conflict of elsart, lineno and amsmath

*From*: "Diego Torquemada" <diegotorquemada@xxxxxxxxx>*Date*: 14 Jul 2006 02:10:49 -0700

Hi people!

I would like to use lineno with elsevier class elsart. However, amsmath

makes some conflicts, namely the line number does not appear in all

lines. Please compile the code below with and without the line

\usepackage{amsmath}

Thans for some help,

Diego

RESULT OF \listfiles

*File List*

elsart.cls 2006/05/01, 2.19: Elsevier

latexsym.sty 1998/08/17 v2.2e Standard LaTeX package (lasy symbols)

ulasy.fd 1998/08/17 v2.2e LaTeX symbol font definitions

amsmath.sty 2000/07/18 v2.13 AMS math features

amstext.sty 2000/06/29 v2.01

amsgen.sty 1999/11/30 v2.0

amsbsy.sty 1999/11/29 v1.2d

amsopn.sty 1999/12/14 v2.01 operator names

lineno.sty 2005/01/10 line numbers on paragraphs v4.1c

***********

\listfiles

\documentclass{elsart}

\usepackage{amsmath}

\usepackage{lineno}

\linenumbers

\begin{document}

In the following we will briefly discuss nonspecificity for finite

sets and for convex subsets of $R^d$. For details the

reader is referred to XXX.

\subsection{Nonspecificity for finite sets}

Consider the following problem: given a finite set $E$ of balls,

which contains a black ball, while the rest are white, we would like

to measure the amount of information $H$ required to find the

black ball. Suppose that the set of balls $E$ has $m \times n$

elements. If this set is partitioned into $n$ sets of $m$ balls or

into $m$ sets of $n$ balls, the measure of nonspecificity $H$

characterizing all those sets will be

\begin{equation}

H(m \times n) = H(m) + H(n) \label{eq:ax1ns}

\end{equation}

Also, note that the larger the set of balls $E$, the less specific

the predictions are, and in consequence

\begin{equation}

H(n) \leq H(n+1) \label{eq:ax2ns}

\end{equation}

where $n := \|E\|$.

xxx proposed the formula

\begin{equation}

H(n) := \log_2 n

\end{equation}

where $n := \|E\|$, and XXX showed that this is

the unique expression that satisfies equations \ref{eq:ax1ns}

and \ref{eq:ax2ns} up to the normalization $H(2)=1$.

This function is known in the literature as the \emph{Hartley

measure} of uncertainty, and it measures the lack of specificity

of a finite set.

\end{document}

.

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