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demo.tex
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\documentclass[10pt]{beamer}
\usetheme{yeast}
\usepackage{lipsum}
\usepackage{tabularx}
\renewcommand{\arraystretch}{2}
\renewcommand\tabularxcolumn[1]{m{#1}}
\title{Yeast Theme}
\subtitle{A Beamer Theme Demonstration}
\author[Yist]{Yist Lin}
\date{\today}
\begin{document}
\maketitle
\begin{frame}{Outline}
\tableofcontents
\end{frame}
\begin{frame}{Introduction}
\textbf{Yeast} is a lite and light beamer theme.
Yist created this theme for making a warm and clean slides easier.
\end{frame}
\section{Basic Elements}
\begin{frame}{Emphasized Text}
Text can have different \textbf{weight}.
And not only weight, it could also \textit{be italic}.
But most of the time, simply use \texttt{\textbackslash{}emph\{\}} could be the best choice.
In normal text, text being emphasized looks exactly \emph{like italic text}.\footnote{But it seems that this is not working in italic mode.}
\textit{Sometimes you really need to emphasize something, you might want it not only to be italic, but also \textbf{be bold}.}
Other than italic and bold text, text could \alert{be colored} with \texttt{\textbackslash{}alerted\{\}}.
\end{frame}
\begin{frame}{Ordered and Unordered Lists}
The ordered list looks like this:
\begin{enumerate}
\item The first item
\item second one
\begin{enumerate}
\item the nested first item
\item the second one
\begin{enumerate}
\item the most indented one
\item And the last one
\end{enumerate}
\item No this is the last one
\end{enumerate}
\end{enumerate}
And the unordered one looks like this:
\begin{itemize}
\item The first item
\item and the second one
\begin{itemize}
\item The first nested item
\item the second one
\begin{itemize}
\item Foo
\item bar
\end{itemize}
\end{itemize}
\end{itemize}
\end{frame}
\begin{frame}{Figure}
\begin{figure}
\centering
\includegraphics[width=.7\linewidth]{images/drew-coffman-Azli_kcxRNE-unsplash.jpg}
\caption{Photo by Drew Coffman on Unsplash}
\label{fig:breads-by-drew-coffman}
\end{figure}
\end{frame}
\begin{frame}{Table}
In my opinion, \texttt{tabularx} could work better most of the time than simply using \texttt{tabular}.
\begin{table}
\centering
\begin{tabularx}{\textwidth}{|c|X|X|}
\hline
\textbf{Characteristics} & \textbf{Mold} & \textbf{Yeast} \\ \hline\hline
Appearance
& Fuzzy appearance and can be orange, green, black, brown, pink or purple in color
& White and thready \\ \hline
Uses
& Useful in biodegradation, food production (cheese)
& Makeing of alcoholic beverages, used in baking, and industrial ethanol production \\ \hline
\end{tabularx}
\caption{Molds v.s. Yeasts}
\label{tab:molds-vs-yeasts}
\end{table}
\end{frame}
\subsection{Elements Good for Presentation}
\begin{frame}{Blocks}
Blocks are used to highlight some text.
\begin{block}{Block}
Just a block.
\end{block}
\begin{alertblock}{Alerted Block}
This is an alerted block.
\end{alertblock}
\begin{exampleblock}{Example Block}
And this is an example block.
\end{exampleblock}
\end{frame}
\subsection{Overlay Animation}
\begin{frame}{Animated}
\begin{itemize}
\item <1-> This first item
\item <1-> The second item
\item <2-> The third item is hidden at first
\end{itemize}
\end{frame}
\section{Math Equations}
\begin{frame}{Display and Inline Mode}
Many claim that the most beautiful equation is Euler's equation.
\[ e^{\pi i} = 1 \]
Long ago, Johann Bernoulli noted that
$$ \frac{1}{1+x^2} = \frac{1}{2}\left( \frac{1}{1-ix} + \frac{1}{1+ix} \right) $$
And Roger Cotes in 1714 discovered that $ ix = \ln(\cos x + i \sin x) $
\end{frame}
\subsection{Baum-Welch Algorithm}
\begin{frame}{Forward Procedure}
\textit{Forward algorithm}: define a forward variable $\alpha_t(i)$
\begin{align}
\alpha_t (i)
& = P(o_1, o_2, \dots, o_t,\ q_t = i\ |\ \lambda) \\
& = \text{Prob}\,[\,\text{observing } o_1, o_2, \dots, o_t, \text{ state } i \text{ at time } t\ |\ \lambda\,]
\end{align}
\begin{description}
\item[Initialization]
\begin{equation}
\alpha_1(i) = \pi_i b_i (o_1),\ 1 \leq i \leq N
\end{equation}
\item[Induction]
\begin{multline}
\alpha_{t+1}(j) = \left[\ \sum_{i=1}^{N} \alpha_t(i) a_{i j}\ \right] \cdot b_j(o_{t+1}),\\
1 \leq t \leq T-1,\ 1 \leq j \leq N
\end{multline}
\item[Termination]
\begin{equation}
P\left( \bar{O}\ |\ \lambda \right) = \sum_{i=1}^{N} \alpha_T(i)
\end{equation}
\end{description}
\end{frame}
\begin{frame}{Backward Procedure}
\textit{Backward algorithm}: define a backward variable $\beta_t(i)$
\begin{align}
\beta_t(i)
& = P(o_{t+1}, o_{t+2}, \dots, o_T\ |\ q_t = i, \lambda) \\
& = \text{Prob}\,[\,\text{observing } o_{t+1}, o_{t+2}, \dots, o_T\ | \text{ state } i \text{ at time } t,\ \lambda\,]
\end{align}
\begin{description}
\item[Initialization]
\begin{equation}
\beta_T(i) = 1,\ 1 \leq i \leq N
\end{equation}
\item[Induction]
\begin{multline}
\beta_{t}(i) = \sum_{j=1}^{N} a_{i j}\ b_j (o_{t+1})\ \beta_{t+1}(j),\\
t = \{ T-1, T-2, \dots, 1\},\ 1 \leq i \leq N
\end{multline}
\end{description}
\end{frame}
\section{And This Is Simply a Test to See Whether a Very Long Section Name Looks Good in the Footline}
\begin{frame}{Lipsum}
\begin{quotation}
\lipsum[1]
\end{quotation}
\end{frame}
\end{document}