Avian erythrocytes have functional mitochondria, opening novel perspectives for birds as animal models in the study of ageing.

BACKGROUND: In contrast to mammalian erythrocytes, which have lost their nucleus and mitochondria during maturation, the erythrocytes of almost all other vertebrate species are nucleated throughout their lifespan. Little research has been done however to test for the presence and functionality of mitochondria in these cells, especially for birds. Here, we investigated those two points in erythrocytes of one common avian model: the zebra finch (Taeniopygia guttata). RESULTS: Transmission electron microscopy showed the presence of mitochondria in erythrocytes of this small passerine bird, especially after removal of haemoglobin interferences. High-resolution respirometry revealed increased or decreased rates of oxygen consumption by erythrocytes in response to the addition of respiratory chain substrates or inhibitors, respectively. Fluorometric assays confirmed the production of mitochondrial superoxide by avian erythrocytes. Interestingly, measurements of plasmatic oxidative markers indicated lower oxidative stress in blood of the zebra finch compared to a size-matched mammalian model, the mouse. CONCLUSIONS: Altogether, those findings demonstrate that avian erythrocytes possess functional mitochondria in terms of respiratory activities and reactive oxygen species (ROS) production. Interestingly, since blood oxidative stress was lower for our avian model compared to a size-matched mammalian, our results also challenge the idea that mitochondrial ROS production could have been one actor leading to this loss during the course of evolution. Opportunities to assess mitochondrial functioning in avian erythrocytes open new perspectives in the use of birds as models for longitudinal studies of ageing via lifelong blood sampling of the same subjects.

Local Distance-Based Generalized Linear Models using the dbstats package for R

This paper introduces local distance-based generalized linear models. These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing. Distances between individuals are the only predictor information needed to fit these models. Therefore they are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type. Models can be fitted and analysed with the R package dbstats, which implements several distancebased prediction methods.

The MIGCLIM R package - seamless integration of dispersal constraints into projections of species distribution models

The MIGCLIM R package is a function library for the open source R software that enables the implementation of species-specific dispersal constraints into projections of species distribution models under environmental change and/or landscape fragmentation scenarios. The model is based on a cellular automaton and the basic modeling unit is a cell that is inhabited or not. Model parameters include dispersal distance and kernel, long distance dispersal, barriers to dispersal, propagule production potential and habitat invasibility. The MIGCLIM R package has been designed to be highly flexible in the parameter values it accepts, and to offer good compatibility with existing species distribution modeling software. Possible applications include the projection of future species distributions under environmental change conditions and modeling the spread of invasive species.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Influence of Individual Characteristics on Work Engagement and Job Stress in a Sample of National and Foreign Workers in Switzerland

In most Western postindustrial societies today, the population is aging, businesses are faced with global integration, and important migration flows are taking place. Increasingly work organizations are hiring crossnational and multicultural workteams. In this situation it is important to understand the influence of certain individual and cultural characteristics on the process of professional integration. The present study explores the links between personality traits, demographic characteristics (age, sex, education, income, and nationality), work engagement, and job stress. The sample consisted of 618 participants, including 394 Swiss workers (200 women, 194 men) and 224 foreigners living and working in Switzerland (117 women, 107 men). Each participant completed the NEO-FFI, the UWES, and the GWSS questionnaires. Our results show an interaction between age and nationality with respect to work engagement and general job stress. The levels of work engagement and job stress appear to increase with age among national wotkers, whereas they decrease among foreign workers. In addition, work engagement was negatively associated with Neuroticism and positively with the other four personality dimensions. Finally, job stress was positively associated with Neuroticism and Conscientiousness, and negatively associated with Extraversion. However, the strength of these relationships appeared to vary according to the worker's nationality, age, sex, education, and income.

Experimental models of Schistosoma mansoni infection

Experimental models of Schistosoma mansoni infections in mammals have contributed greatly to our understanding of the pathology and pathogenesis of infection. We consider here hepatic and extrahepatic disease in models of acute and chronic infection. Experimental schistosome infections have also contributed more broadly to our understanding of granulomatous inflammation and our understanding of Th1 versus Th2 related inflammation and particularly to Th2-mediated fibrosis of the liver.

Conceptual models for designing information systems supporting the strategic analysis of technology environments

1 6 STRUCTURE OF THIS THESIS -Chapter I presents the motivations of this dissertation by illustrating two gaps in the current body of knowledge that are worth filling, describes the research problem addressed by this thesis and presents the research methodology used to achieve this goal. -Chapter 2 shows a review of the existing literature showing that environment analysis is a vital strategic task, that it shall be supported by adapted information systems, and that there is thus a need for developing a conceptual model of the environment that provides a reference framework for better integrating the various existing methods and a more formal definition of the various aspect to support the development of suitable tools. -Chapter 3 proposes a conceptual model that specifies the various enviromnental aspects that are relevant for strategic decision making, how they relate to each other, and ,defines them in a more formal way that is more suited for information systems development. -Chapter 4 is dedicated to the evaluation of the proposed model on the basis of its application to a concrete environment to evaluate its suitability to describe the current conditions and potential evolution of a real environment and get an idea of its usefulness. -Chapter 5 goes a step further by assembling a toolbox describing a set of methods that can be used to analyze the various environmental aspects put forward by the model and by providing more detailed specifications for a number of them to show how our model can be used to facilitate their implementation as software tools. -Chapter 6 describes a prototype of a strategic decision support tool that allow the analysis of some of the aspects of the environment that are not well supported by existing tools and namely to analyze the relationship between multiple actors and issues. The usefulness of this prototype is evaluated on the basis of its application to a concrete environment. -Chapter 7 finally concludes this thesis by making a summary of its various contributions and by proposing further interesting research directions.

Foreign ant queens are accepted but produce fewer offspring.

Understanding social evolution requires us to understand the processes regulating the number of breeders within social groups and how they partition reproduction. Queens in polygynous (multiple queens per colony) ants often seek adoption in established colonies instead of founding a new colony independently. This mode of dispersal leads to potential conflicts, as kin selection theory predicts that resident workers should favour nestmate queens over foreign queens. Here we compared the survival of foreign and resident queens as well as their relative reproductive share. We used the ant Formica exsecta to construct colonies consisting of one queen with workers related to this resident queen and introduced a foreign queen. We found that the survival of foreign queens did not differ from that of resident queens over a period of 136 days. However, the genetic analyses revealed that resident queens produced a 1.5-fold higher number of offspring than introduced queens, and had an equal or higher share in 80% of the colonies. These data indicate that some discrimination can occur against dispersing individuals and that dispersal can thus have costs in terms of direct reproduction for dispersing queens.

Three essays in international finance

Executive Summary The first essay of this dissertation investigates whether greater exchange rate uncertainty (i.e., variation over time in the exchange rate) fosters or depresses the foreign investment of multinational firms. In addition to the direct capital financing it supplies, foreign investment can be a source of valuable technology and know-how, which can have substantial positive effects on a host country's economic growth. Thus, it is critically important for policy makers and central bankers, among others, to understand how multinationals base their investment decisions on the characteristics of foreign exchange markets. In this essay, I first develop a theoretical framework to improve our knowledge regarding how the aggregate level of foreign investment responds to exchange rate uncertainty when an economy consists of many firms, each of which is making decisions. The analysis predicts a U-shaped effect of exchange rate uncertainty on the total level of foreign investment of the economy. That is, the effect is negative for low levels of uncertainty and positive for higher levels of uncertainty. This pattern emerges because the relationship between exchange rate volatility and 'the probability of investment is negative for firms with low productivity at home (i.e., firms that find it profitable to invest abroad) and the relationship is positive for firms with high productivity at home (i.e., firms that prefer exporting their product). This finding stands in sharp contrast to predictions in the existing literature that consider a single firm's decision to invest in a unique project. The main contribution of this research is to show that the aggregation over many firms produces a U-shaped pattern between exchange rate uncertainty and the probability of investment. Using data from industrialized countries for the period of 1982-2002, this essay offers a comprehensive empirical analysis that provides evidence in support of the theoretical prediction. In the second essay, I aim to explain the time variation in sovereign credit risk, which captures the risk that a government may be unable to repay its debt. The importance of correctly evaluating such a risk is illustrated by the central role of sovereign debt in previous international lending crises. In addition, sovereign debt is the largest asset class in emerging markets. In this essay, I provide a pricing formula for the evaluation of sovereign credit risk in which the decision to default on sovereign debt is made by the government. The pricing formula explains the variation across time in daily credit spreads - a widely used measure of credit risk - to a degree not offered by existing theoretical and empirical models. I use information on a country's stock market to compute the prevailing sovereign credit spread in that country. The pricing formula explains a substantial fraction of the time variation in daily credit spread changes for Brazil, Mexico, Peru, and Russia for the 1998-2008 period, particularly during the recent subprime crisis. I also show that when a government incentive to default is allowed to depend on current economic conditions, one can best explain the level of credit spreads, especially during the recent period of financial distress. In the third essay, I show that the risk of sovereign default abroad can produce adverse consequences for the U.S. equity market through a decrease in returns and an increase in volatility. The risk of sovereign default, which is no longer limited to emerging economies, has recently become a major concern for financial markets. While sovereign debt plays an increasing role in today's financial environment, the effects of sovereign credit risk on the U.S. financial markets have been largely ignored in the literature. In this essay, I develop a theoretical framework that explores how the risk of sovereign default abroad helps explain the level and the volatility of U.S. equity returns. The intuition for this effect is that negative economic shocks deteriorate the fiscal situation of foreign governments, thereby increasing the risk of a sovereign default that would trigger a local contraction in economic growth. The increased risk of an economic slowdown abroad amplifies the direct effect of these shocks on the level and the volatility of equity returns in the U.S. through two channels. The first channel involves a decrease in the future earnings of U.S. exporters resulting from unfavorable adjustments to the exchange rate. The second channel involves investors' incentives to rebalance their portfolios toward safer assets, which depresses U.S. equity prices. An empirical estimation of the model with monthly data for the 1994-2008 period provides evidence that the risk of sovereign default abroad generates a strong leverage effect during economic downturns, which helps to substantially explain the level and the volatility of U.S. equity returns.

Metodologies de Desenvolupament Dirigides per Models

En aquest treball, s'introduiran dos de les metodologies de desenvolupament dirigides per models més significatives: Model Driven Architecture (MDA) i Domain Specific Modeling (DSM). Així mateix, es presentarà un estudi comparatiu d'algunes de les diferents eines existents actualment al mercat que els hi donen suport.

Models i mètriques d'estimació d'esforç per la gestió de projectes informàtics.

L'objectiu principal d'aquest treball ha estat buscar i valorar les diferents opcions que hi ha en la gestió de projectes per a estimar-ne els costos relacionats. La primera de les tasques que s'ha fet és definir el terme 'projecte' per esbrinar quins tipus de projectes són susceptibles de ser valorats; aquesta tipificació ha portat a dividir els projectes en dues branques molt diferenciades, tot i que relacionades, durant el seu desenvolupament.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.