Abstract

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Abstract
This work explores an application of the spatial prisoner's dilemma in two situations: when all agents use the same type of behavior and when they use a mix of behaviors. Our aim is to explore the evolutionary dynamics of this game to analyze the dominance of one strategy over the other. We also investigate, in some possible scenarios, which behavior has better performance when they all coexist in the same environment.

Abstract
In this study, we analyze firms' membership in R&D (Research and Development) cooperation networks trough simulation methods. Our main research hypothesis is that the membership in cooperation networks is related to the degree of the knowledge spillover. The approach has two scenarios: cost symmetry and cost asymmetry. We first develop an analytical model with three stages: firstly, firms decide whether to participate in a cooperative research network; secondly they simultaneously choose the level of R&D output, and finally they choose the level of output. Then we proceed with computational simulations to verify our hypothesis. From our results, we were able to conclude that cooperation leads to an improvement on RJV firms' position in the market as they produce more than others with the same production conditions. Additionally, cooperating firms have to spend fewer resources on research, which turns the network a tremendous success on the productive efficiency level.

Abstract
Reaching the United Nations Millennium Development Goals and the necessary statistical literacy for citizens' understanding of what they entail requires that National Statistical Offices (NSOs) become more involved in the promotion of statistical literacy in cooperation with national statistical societies, international organizations like IASE and ISLP and national education institutions. All these stakeholders share an interest in the promotion of statistical literacy in schools yet for rather different reasons. Sharing the different skills that each possesses could have benefits for the long term goals of each stakeholder, could help improve school curricula, contribute to the debate on what constitutes statistical literacy and what is the best way to help citizens achieve it, and make the path to evidence based decision making easier. In this paper we present examples of what National Statistics Offices can and can not do regarding the promotion of statistical literacy in schools. We illustrate the common and singular aspects of their programs for schools and discuss how they follow the current trends in statistics education while helping the National Statistics Office's goal of promoting their statistics products and creating more users of official statistics. The work of the International Statistical Literacy Project (ISLP) is discussed in the context of drawing together stakeholders and resources.

Abstract
Whenever new sequences of DNA or proteins have been decoded it is almost compulsory to look at similar sequences and papers describing those sequences in order to both collect relevant information concerning the function and activity of the new sequences and/or know what is known already about similar sequences that might be useful in the explanation of the function or activity of the newly discovered ones. In current web sites and data bases of sequences there are, usually, a set of paper references linked to each sequence. Those links are very useful because the papers describe useful information concerning the sequences. They are, therefore, a good starting point to look for relevant information related to a set of sequences. One way is to implement such approach is to do a blast with the new decoded sequences, and collect similar sequences. Then one looks at the papers linked with the similar sequences. Most often the number of retrieved papers is small and one has to search large data bases for relevant papers. In this paper we propose a process of generating a classifier based on the initially set of relevant papers that are directly linked to the similar sequences retrieved and use that classifier to automatically enlarge the set of relevant papers by searching the MEDLINE using the automatically constructed classifier. We have empirically evaluated our proposal and report very promising results. © 2011 IEEE.