Discordances between phylogenetic and morphological patterns in alpine leaf beetles attest to an intricate biogeographic history of lineages in postglacial Europe.

Pleistocene glacial and interglacial periods have moulded the evolutionary history of European cold-adapted organisms. The role of the different mountain massifs has, however, not been accurately investigated in the case of high-altitude insect species. Here, we focus on three closely related species of non-flying leaf beetles of the genus Oreina (Coleoptera, Chrysomelidae), which are often found in sympatry within the mountain ranges of Europe. After showing that the species concept as currently applied does not match barcoding results, we show, based on more than 700 sequences from one nuclear and three mitochondrial genes, the role of biogeography in shaping the phylogenetic hypothesis. Dating the phylogeny using an insect molecular clock, we show that the earliest lineages diverged more than 1 Mya and that the main shift in diversification rate occurred between 0.36 and 0.18 Mya. By using a probabilistic approach on the parsimony-based dispersal/vicariance framework (MP-DIVA) as well as a direct likelihood method of state change optimization, we show that the Alps acted as a cross-roads with multiple events of dispersal to and reinvasion from neighbouring mountains. However, the relative importance of vicariance vs. dispersal events on the process of rapid diversification remains difficult to evaluate because of a bias towards overestimation of vicariance in the DIVA algorithm. Parallels are drawn with recent studies of cold-adapted species, although our study reveals novel patterns in diversity and genetic links between European mountains, and highlights the importance of neglected regions, such as the Jura and the Balkanic range.

"MIATA"-minimal information about T cell assays.

Immunotherapy, especially therapeutic vaccination, has a great deal of potential in the treatment of cancer and certain infectious diseases such as HIV (Allison et al., 2006; Fauci et al., 2008; Feldmann and Steinman, 2005). Numerous vaccine candidates have been tested in patients with a variety of tumor types and chronic viral diseases. Often, the best way to assess the clinical potential of these vaccines is to monitor the induced T cell response, and yet there are currently no standards for reporting these results. This letter is an effort to address this problem.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Bargaining and Conflict with Incomplete Information

This paper studies bargaining and conflict under incomplete information, provides an overview and a critical account of the literature on the topic and contributes with original research. We first revise models of mechanism design and sequential bargaining that take confrontation as final. Conflict and inefficiencies are to be expected in these models whenever parties have optimistic prospects on the outcome of the all-out conflict. After examining the causes and reasons for this optimism, we move to the analysis of the recent literature that considers the existence of limited confrontations that allow bargaining to resume. In the presence of private information, these limited conflicts convey information and thus become a bargaining instrument. The paper closes with a discussion on the related empirical literature, the challenges that it faces and some potential avenues for further research.

Optimal contracting with private information on cost expectation and variability

We study the screening problem that arises in a framework where, initially, the agent is privately informed about both the expected production cost and the cost variability and, at a later stage, he learns privately the cost realization. The speci c set of relevant incentive constraints, and so the characteristics of the optimal mechanism, depend nely upon the curvature of the principal s marginal surplus function as well as the relative importance of the two initial information problems. Pooling of production levels is optimally induced with respect to the cost variability when the principal's knowledge imperfection about the latter is sufficiently less important than that about the expected cost.

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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.

Regiones salientes complejas para aplicaciones de seguimiento facial

Este trabajo presenta una metodología para detectar y realizar el seguimiento de características faciales. En el primer paso del procedimiento se detectan caras mediante Adaboost con cascadas de clasificadores débiles. El segundo paso busca las características internas de la cara mediante el CSR, detectando zonas de interés. Una vez que estas características se capturan, un proceso de tracking basado en el descriptor SIFT, que hemos llamado pseudo-SIFT, es capaz de guardar información sobre la evolución de movimiento en las regiones detectadas. Además, un conjunto de datos públicos ha sido desarrollado con el propósito de compartirlo con otras investigaciones sobre detección, clasificación y tracking. Experimentos reales muestran la robustez de este trabajo y su adaptabilidad para trabajos futuros.

Expert Information and Majority Decisions

This paper studies dichotomous majority voting in common interest committees where each member receives not only a private signal but also a public signal observed by all of them. The public signal represents, e.g. expert information presented to an entire committee and its quality is higher than that of each individual private signal. We identify two informative symmetric strategy equilibria, namely i) the mixed strategy equilibrium where each member randomizes between following the private and public signals should they disagree; and ii) the pure strategy equilibrium where they follow the public signal for certain. The former outperforms the latter. The presence of the public signal precludes the equilibrium where every member follows their own signal, which is an equilibrium in the absence of the public signal. The mixed strategy equilibrium in the presence of the public signal outperforms the sincere voting equilibrium without the public signal, but the latter may be more efficient than the pure strategy equilibrium in the presence of the public signal. We suggest that whether expert information improves committee decision making depends on equilibrium selection.

The Market for "Rough Diamonds": Information, Finance and Wage Inequality

During the past four decades both between and within group wage inequality increased significantly in the US. I provide a microfounded justification for this pattern, by introducing private employer learning in a model of signaling with credit constraints. In particular, I show that when financial constraints relax, talented individuals can acquire education and leave the uneducated pool, this decreases unskilled inexperienced wages and boosts wage inequality. This explanation is consistent with US data from 1970 to 1997, indicating that the rise of the skill and the experience premium coincides with a fall in unskilled-inexperienced wages, while at the same time skilled or experienced wages do not change much. The model accounts for: (i) the increase in the skill premium despite the growing supply of skills; (ii) the understudied aspect of rising inequality related to the increase in the experience premium; (iii) the sharp growth of the skill premium for inexperienced workers and its moderate expansion for the experienced ones; (iv) the puzzling coexistence of increasing experience premium within the group of unskilled workers and its stable pattern among the skilled ones. The results hold under various robustness checks and provide some interesting policy implications about the potential conflict between inequality of opportunity and substantial economic inequality, as well as the role of minimum wage policy in determining the equilibrium wage inequality.

How private is private information? The ability to spot deception in an economic game

We provide experimental evidence on the ability to detect deceit in a buyer-seller game with asymmetric information. Sellers have private information about the buyer's valuation of a good and sometimes have incentives to mislead buyers. We examine if buyers can spot deception in face-to-face encounters. We vary (1) whether or not the buyer can interrogate the seller, and (2) the contextual richness of the situation. We find that the buyers' prediction accuracy is above chance levels, and that interrogation and contextual richness are important factors determining the accuracy. These results show that there are circumstances in which part of the information asymmetry is eliminated by people's ability to spot deception.

What is the Causal Effect of Information and Learning about a Public Good on Willingness to Pay?

In this study we elicit agents’ prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis.

The Impact of Information Provision on Agglomeration Bonus Performance: An Experimental Study on Local Networks

The Agglomeration Bonus (AB) is a mechanism to induce adjacent landowners to spatially coordinate their land use for the delivery of ecosystem services from farmland. This paper uses laboratory experiments to explore the performance of the AB in achieving the socially optimal land management configuration in a local network environment where the information available to subjects varies. The AB poses a coordination problem between two Nash equilibria: a Pareto dominant and a risk dominant equilibrium. The experiments indicate that if subjects are informed about both their direct and indirect neighbors’ actions, they are more likely to coordinate on the Pareto dominant equilibrium relative to the case where subjects have information about their direct neighbors’ action only. However, the extra information can only delay – and not prevent – the transition to the socially inferior risk dominant Nash equilibrium. In the long run, the AB mechanism may only be partially effective in enhancing delivery of ecosystem services on farming landscapes featuring local networks.

Contribution à l'élaboration de mécanismes de détection, de contrôle et de lutte contre le blanchiment d'argent au regard de l'usage des technologies de l'information et de la communication "cas de l'Algérie"

Résumé : Désormais, la lutte contre le blanchiment d'argent constitue une priorité pour les Etats et les gouvernements dans le but, d'une part, de préserver l'économie et l'intégrité des places financières et, d'autre part, de priver les organisations criminelles des ressources financières. Dans ce contexte, la préoccupation majeure des autorités algériennes en charge de la lutte contre ce phénomène est de mettre en place un dispositif capable de détecter les mécanismes de blanchiment, d'en évaluer la menace et sur la base de cette connaissance, de définir et de déployer les moyens de riposte les plus efficaces et efficients. Mais nous constatons que mener des enquêtes de blanchiment en conséquence à un crime sous-jacent a montré ses limites en matière d'établissement de preuves, d'élucidation d'affaires et de recouvrement des avoirs. Par ailleurs, nous pensons qu'il serait plus judicieux de mettre en place en amont un contrôle «systématique» des flux financiers et des opérations inhabituelles et/ou suspectes et de là, identifier d'éventuelles opérations de blanchiment, sans forcément connaître le crime initial, en veillant au maintien de l'équilibre entre le «tout sécuritaire» orienté vers la surveillance accrue des flux et la préservation de la vie privée et des libertés individuelles. Notre thèse apporte un regard critique sur le dispositif actuel de lutte contre le blanchiment existant en Algérie que nous évaluons et sur lequel nous relevons plusieurs lacunes. Pour répondre aux problèmes identifiés nous proposons des solutions stratégiques, organisationnelles, méthodologiques et technologiques intégrées dans un cadre opérationnel cohérent au niveau national et international.