Effect of age and gender on citalopram and desmethylcitalopram steady-state plasma concentrations in adults and elderly depressed patients.

The effect of aging on steady-state plasma concentrations of citalopram (CIT) and desmethylcitalopram (DCIT) was investigated in 128 depressive patients treated with 10-80 mg/day CIT. They were separated into three groups, with age up to 64 years (mean age+/-S.D.: 47+/-12 years; n=48), between 65 and 79 years (72+/-1 years; n=57), and from 80 years or older (84+/-1 years; n=23). Body mass index (BMI), renal and hepatic functions were similar in the three groups. A large interindividual variability of plasma levels of CIT (16-fold) and DCIT (12-fold) was measured for a given dose. The mean plasma levels of CIT corrected for a 20 mg daily dose were 55% higher in the very elderly (>=80 years) patients (65+/-30 ng/ml; p<0.001) and 38% higher in the elderly (65-79 years) patients (58+/-24 ng/ml; p<0.001) when compared to the adult patients (42+/-17 ng/ml). DCIT mean plasma level was 38% higher (p<0.05) in the group of very elderly patients (22+/-10 ng/ml) when compared to the adult patients (16+/-9 ng/ml). As a consequence, the mean plasma concentration of CIT+DCIT was 48% higher in the very elderly patients (86+/-36 ng/ml; p<0.001) and 33% higher in the elderly patients (77+/-28 ng/ml; p<0.001) when compared to the adult patients (58+/-21 ng/ml). Age correlated significantly with CIT (r=0.43, p<0.001), DCIT (r=0.28, p<0.01), and CIT+DCIT plasma levels (r=0.44, p<0.001), and thus accounts for 18% of the variability of CIT plasma levels, with no influence of gender. The recommended dose reduction of CIT in elderly patients seems therefore justified.

Instrumental leadership: An extension of the Full-Range Leadership Theory

From a theoretical perspective, an extension to the Full Range leadership Theory (FRLT) seems needed. In this paper, we explain why instrumental leadership--a class of leadership includes leader behaviors focusing on task and strategic aspects that are neither values nor exchange oriented--can fulfill this extension. Instrument leadership is composed of four factors: environmental monitoring, strategy formulation and implementation, path-goal facilitation and outcome monitoring; these aspects of leadership are currently not included in any of the FRLT's nine leadership scales (as measured by the MLQ--Multifactor Leadership Questionnaire). We present results from two empirical studies using very large samples from a wide array of countries (N > 3,000) to examine the factorial, discriminant and criterion-related validity of the instrumental leadership scales. We find support for a four-factor instrumental leadership model, which explains incremental variance in leader outcomes in over and above transactional and transformational leadership.

Properties of a risk measure derived from ruin theory

This paper studies a risk measure inherited from ruin theory and investigates some of its properties. Specifically, we consider a value-at-risk (VaR)-type risk measure defined as the smallest initial capital needed to ensure that the ultimate ruin probability is less than a given level. This VaR-type risk measure turns out to be equivalent to the VaR of the maximal deficit of the ruin process in infinite time. A related Tail-VaR-type risk measure is also discussed.

The Uncertain generalized probabilistic weighted average and its application in the theory of expertons

A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

The evolution of unicoloniality in ant societies : recognition, dispersal and population genetic structure

Introduction Societies of ants, bees, wasps and termites dominate many terrestrial ecosystems (Wilson 1971). Their evolutionary and ecological success is based upon the regulation of internal conflicts (e.g. Ratnieks et al. 2006), control of diseases (e.g. Schmid-Hempel 1998) and individual skills and collective intelligence in resource acquisition, nest building and defence (e.g. Camazine 2001). Individuals in social species can pass on their genes not only directly trough their own offspring, but also indirectly by favouring the reproduction of relatives. The inclusive fitness theory of Hamilton (1963; 1964) provides a powerful explanation for the evolution of reproductive altruism and cooperation in groups with related individuals. The same theory also led to the realization that insect societies are subject to internal conflicts over reproduction. Relatedness of less-than-one is not sufficient to eliminate all incentive for individual selfishness. This would indeed require a relatedness of one, as found among cells of an organism (Hardin 1968; Keller 1999). The challenge for evolutionary biology is to understand how groups can prevent or reduce the selfish exploitation of resources by group members, and how societies with low relatedness are maintained. In social insects the evolutionary shift from single- to multiple queens colonies modified the relatedness structure, the dispersal, and the mode of colony founding (e.g. (Crozier & Pamilo 1996). In ants, the most common, and presumably ancestral mode of reproduction is the emission of winged males and females, which found a new colony independently after mating and dispersal flights (Hölldobler & Wilson 1990). The alternative reproductive tactic for ant queens in multiple-queen colonies (polygyne) is to seek to be re-accepted in their natal colonies, where they may remain as additional reproductives or subsequently disperse on foot with part of the colony (budding) (Bourke & Franks 1995; Crozier & Pamilo 1996; Hölldobler & Wilson 1990). Such ant colonies can contain up to several hundred reproductive queens with an even more numerous workforce (Cherix 1980; Cherix 1983). As a consequence in polygynous ants the relatedness among nestmates is very low, and workers raise brood of queens to which they are only distantly related (Crozier & Pamilo 1996; Queller & Strassmann 1998). Therefore workers could increase their inclusive fitness by preferentially caring for their closest relatives and discriminate against less related or foreign individuals (Keller 1997; Queller & Strassmann 2002; Tarpy et al. 2004). However, the bulk of the evidence suggests that social insects do not behave nepotistically, probably because of the costs entailed by decreased colony efficiency or discrimination errors (Keller 1997). Recently, the consensus that nepotistic behaviour does not occur in insect colonies was challenged by a study in the ant Formica fusca (Hannonen & Sundström 2003b) showing that the reproductive share of queens more closely related to workers increases during brood development. However, this pattern can be explained either by nepotism with workers preferentially rearing the brood of more closely related queens or intrinsic differences in the viability of eggs laid by queens. In the first chapter, we designed an experiment to disentangle nepotism and differences in brood viability. We tested if workers prefer to rear their kin when given the choice between highly related and unrelated brood in the ant F. exsecta. We also looked for differences in egg viability among queens and simulated if such differences in egg viability may mistakenly lead to the conclusion that workers behave nepotistically. The acceptance of queens in polygnous ants raises the question whether the varying degree of relatedness affects their share in reproduction. In such colonies workers should favour nestmate queens over foreign queens. Numerous studies have investigated reproductive skew and partitioning of reproduction among queens (Bourke et al. 1997; Fournier et al. 2004; Fournier & Keller 2001; Hammond et al. 2006; Hannonen & Sundström 2003a; Heinze et al. 2001; Kümmerli & Keller 2007; Langer et al. 2004; Pamilo & Seppä 1994; Ross 1988; Ross 1993; Rüppell et al. 2002), yet almost no information is available on whether differences among queens in their relatedness to other colony members affects their share in reproduction. Such data are necessary to compare the relative reproductive success of dispersing and non-dispersing individuals. Moreover, information on whether there is a difference in reproductive success between resident and dispersing queens is also important for our understanding of the genetic structure of ant colonies and the dynamics of within group conflicts. In chapter two, we created single-queen colonies and then introduced a foreign queens originating from another colony kept under similar conditions in order to estimate the rate of queen acceptance into foreign established colonies, and to quantify the reproductive share of resident and introduced queens. An increasing number of studies have investigated the discrimination ability between ant workers (e.g. Holzer et al. 2006; Pedersen et al. 2006), but few have addressed the recognition and discrimination behaviour of workers towards reproductive individuals entering colonies (Bennett 1988; Brown et al. 2003; Evans 1996; Fortelius et al. 1993; Kikuchi et al. 2007; Rosengren & Pamilo 1986; Stuart et al. 1993; Sundström 1997; Vásquez & Silverman in press). These studies are important, because accepting new queens will generally have a large impact on colony kin structure and inclusive fitness of workers (Heinze & Keller 2000). In chapter three, we examined whether resident workers reject young foreign queens that enter into their nest. We introduced mated queens into their natal nest, a foreign-female producing nest, or a foreign male-producing nest and measured their survival. In addition, we also introduced young virgin and mated queens into their natal nest to examine whether the mating status of the queens influences their survival and acceptance by workers. On top of polgyny, some ant species have evolved an extraordinary social organization called 'unicoloniality' (Hölldobler & Wilson 1977; Pedersen et al. 2006). In unicolonial ants, intercolony borders are absent and workers and queens mix among the physically separated nests, such that nests form one large supercolony. Super-colonies can become very large, so that direct cooperative interactions are impossible between individuals of distant nests. Unicoloniality is an evolutionary paradox and a potential problem for kin selection theory because the mixing of queens and workers between nests leads to extremely low relatedness among nestmates (Bourke & Franks 1995; Crozier & Pamilo 1996; Keller 1995). A better understanding of the evolution and maintenance of unicoloniality requests detailed information on the discrimination behavior, dispersal, population structure, and the scale of competition. Cryptic genetic population structure may provide important information on the relevant scale to be considered when measuring relatedness and the role of kin selection. Theoretical studies have shown that relatedness should be measured at the level of the `economic neighborhood', which is the scale at which intraspecific competition generally takes place (Griffin & West 2002; Kelly 1994; Queller 1994; Taylor 1992). In chapter four, we conducted alarge-scale study to determine whether the unicolonial ant Formica paralugubris forms populations that are organised in discrete supercolonies or whether there is a continuous gradation in the level of aggression that may correlate with genetic isolation by distance and/or spatial distance between nests. In chapter five, we investigated the fine-scale population structure in three populations of F. paralugubris. We have developed mitochondria) markers, which together with the nuclear markers allowed us to detect cryptic genetic clusters of nests, to obtain more precise information on the genetic differentiation within populations, and to separate male and female gene flow. These new data provide important information on the scale to be considered when measuring relatedness in native unicolonial populations.

Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review

Gender inequalities exist in work life, but little is known about their presence in relation to factors examined in occupation health settings. The aim of this study was to identify and summarize the working and employment conditions described as determinants of gender inequalities in occupational health in studies related to occupational health published between 1999 and 2010. A systematic literature review was undertaken of studies available in MEDLINE, EMBASE, Sociological Abstracts, LILACS, EconLit and CINAHL between 1999 and 2010. Epidemiologic studies were selected by applying a set of inclusion criteria to the title, abstract, and complete text. The quality of the studies was also assessed. Selected studies were qualitatively analysed, resulting in a compilation of all differences between women and men in the prevalence of exposure to working and employment conditions and work-related health problems as outcomes. Most of the 30 studies included were conducted in Europe (n=19) and had a cross-sectional design (n=24). The most common topic analysed was related to the exposure to work-related psychosocial hazards (n=8). Employed women had more job insecurity, lower control, worse contractual working conditions and poorer self-perceived physical and mental health than men did. Conversely, employed men had a higher degree of physically demanding work, lower support, higher levels of effort-reward imbalance, higher job status, were more exposed to noise and worked longer hours than women did. This systematic review has identified a set of working and employment conditions as determinants of gender inequalities in occupational health from the occupational health literature. These results may be useful to policy makers seeking to reduce gender inequalities in occupational health, and to researchers wishing to analyse these determinants in greater depth.

Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies.

ABSTRACT: BACKGROUND: Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory. METHODS: We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies. RESULTS: We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure. CONCLUSIONS: We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

The effect of obesity, age, puberty and gender on resting metabolic rate in children and adolescents.

During puberty fat-free mass (FFM) and fat mass (FM) change quickly and these changes are influenced by sex and obesity. Since it is not completely known how these changes affect resting metabolic rate (RMR), the aim of the present study was to investigate the effect of body composition, age, sex and pubertal development of postabsorptive RMR in 9.5- to 16.5- year-old obese and non-obese children. Postabsorptive RMR was measured in a sample of 371 pre- and postpubertal children comprising 193 males (116 non-obese and 77 obese) and 178 females (119 non-obese and 59 obese). RMR was assessed by indirect calorimetry using a ventilated hood system for 45 min after an overnight fast. Body composition (FFM and FM) was estimated from skinfold measurements. The mean (+/- SD) RMR was significantly (P < 0.001) lower in non-obese (males: 5600 +/- 972 kJ/24 h; females: 5112 +/- 632 kJ/24 h) than in obese (males: 7223 +/- 1220 kJ/24 h; females: 6665 +/- 1106 kJ/24 h) children. This difference became non-significant when RMR was adjusted for body composition (FFM+FM). However, the difference between the genders still remained significant (control male: 6118 +/- 507, control female: 5652 +/- 507, P < 0.001; obese male: 6256 +/- 507, obese female: 5818 +/- 507 kJ/24 h, P < 0.001). The main determinant of RMR was FFM. In the whole cohort. FFM explained 79.8% of the variation in RMR, followed by age, gender and FM adding further 3.8%, 1.1% and 0.8% to the predictability of RMR, respectively. No significant contribution for study group (obese, non-obese), pubertal stage, or fat distribution was found in the regression for RMR. The adjusted value of RMR (for FFM and FM) slightly, but significantly (P < 0.01) decreased between the age of 10-16 years, demonstrating the important effect of age on RMR. CONCLUSIONS: The resting metabolic rate of obese and control children is not different when adjusted for body composition. The main determinant of RMR is the fat-free mass, however, age, gender and fat mass are also significant factors. Pubertal development and fat distribution do not influence RMR independently from the changes in body composition.

When several queens reign: how polygyny affects social life in ants

Astract: The aim of this thesis was to investigate how the presence of multiple queens (polygyny) affects social organization in colonies of the ant Formica exsecta. This is important because polygyny results in reduced relatedness among colony members and therefore reflects a potential paradox for altruistic cooperation being explained by inclusive fitness theory. The reason for this is that workers in polygynous colonies rear no longer only their siblings (high inclusive fitness gain) but also more distantly ox even unrelated brood (low or no inclusive fitness gain). All research projects conducted in this thesis are novel and significant contributions to the understanding of the social evolution of insect societies. We used a mixture of experimental and observational methodologies in laboratory and field colonies of F. exsecta to examine four important aspects of social life that are impacted by polygyny. First, we investigated the influence of queen number on colony sex allocation and found that the number of queens present in a colony significantly affects colony sex ratio investment. The data were consistent with the queen-replenishment hypothesis, which is based on the observation that newly mated queens are often recruited back to their parental nest. According to this theory, colonies containing many queens should only produce males due to local resource competition (i.e. related queens compete for common resources), whereas colonies hosting few queens benefit most from producing new queens to ensure colony survival. Second, we examined how reproduction is partitioned among nestmate queens. We detected a novel pattern of reproductive partitioning whereby a high proportion of queens were completely specialized in the production of only a subset of offspring classes produced within a colony, which might translate into great differences in reproductive success between queens. Third, we could demonstrate that F. exsecta workers indiscriminately reared highly related and unrelated brood although such nepotistic behaviour (preferential rearing of relatives) would be predicted by inclusive fitness theory. The absence of nepotism is probably best explained by its negative effects on overall colony efficiency. Finally, we conducted a detailed population genetic analysis, which revealed that the genetic population structure is different for queens and workers. Our data were best explained with queens forming family-based groups (multicolonial population structure), whereas workers from several nests seemed to be grouped into larger unites (unicolonial population structure) with workers moving freely between neighbouring nests. Altogether, the presented work significantly increased our understanding of the complex organization of polygynous social insect colonies and shows how an important life history trait such as queen number affects social organization at various levels. Résumé: Le but de cette thèse était d'étudier comment la présence de plusieurs reines par colonie (polygynie) influence la vie sociale chez la fourmi Formica exsecta. Ce sujet est important parce que la polygynie chez les insectes sociaux présente un passible paradoxe au niveau de la théorie du "fitness inclusive". Ce paradoxe est basé sur le fait que les ouvrières n'élèvent plus uniquement leurs frères et soeurs (gain de "fitness inclusive" maximale), mais également des individus moins ou pas du tout apparentés (gain de "fitness inclusive" réduit ou absent). Tous les projets de recherche présentés au cours de cette thèse apportent une meilleure compréhension et connaissance au niveau de l'organisation des colonies chez les insectes sociaux. Nous avons employé des méthodes d'observation et de laboratoire afin de mettre en évidence des aspects importants de la vie sociale chez les fourmis influencés par la polygynie. Quatre aspects ont été caractérisés : (1) l'influence du nombre de reines sur le sexe ratio produit par la colonie. Nous avons démontré que les colonies contenant beaucoup de reines produisaient rarement des reines tandis que les colonies contenant peu de reines souvent investissaient beaucoup de ressources dans la production des reines. Ces résultats sont en accord avec la "queen-replenishment hypothesis" qui est basé sur l'observation que les nouvelles reines sont recrutées dans la colonie où elles étaient nées. Cette hypothèse postule que la production des reines est défavorable dans les colonies contenant beaucoup de reines, parce que ces reines apparentées, rentrent en compétition pour des ressources communes. Au contraire, la production des reines est favorable dans des colonies contenant peu de reines afin d'assurer la survie de la colonie ; (2) comment les reines dans une colonie répartissent leur reproduction. Nous avons mis en évidence un nouveau pattern de cette répartition où une grande proportion de reines est complètement spécialisée dans la production d'un seul type de couvain ce qui probablement aboutit à des différences significatives entre reines dans le succès reproducteur ; (3) la capacité des ouvrières à discriminer un couvain de soeur d'un couvain non apparenté. Les résultats ont montré que les ouvrières ne font pas de discrimination entre le couvain de soeur et le couvain non apparenté ce qui n'est pas en accord avec la théorie de la "fitness inclusive". Cette absence de discrimination est probablement due à des effets négatifs comme par exemple la diminution de la production du couvain; (4) la structure génétique d'une population de F. exsecta. Nous avons mis en évidence que la structure génétique entre des groupes de reines est significativement différente de la structure génétique entre des groupes d'ouvrières. Les données suggèrent que les reines forment des groupes basés sur une structure familiale tandis que les ouvrières sont groupées dans des unités plus grandes.

Aproximaciones a la lectura crítica: teoría, ejemplos y reflexiones

Dentro de las ciencias del lenguaje, el Análisis Crítico del Discurso (ACD) aprovecha las aportaciones de los recientes estudios sobre el texto (análisis del discurso, pragmática, sociolingüística, etnografía de la comunicación, teoría de la enunciación, etc.) para definir los propósitos y la metodología del análisis crítico. Ante el mundo multicultural y globalizado en el que vivimos, la única respuesta educativa posible es la necesidad de formar a una ciudadanía, que tenga habilidades críticas de lectura, escritura y pensamiento y participe de modo constructivo en el desarrollo de una comunidad plural, respetuosa y progresista. El artículo explora en la teoría y en la práctica la lectura crítica, para reflexionar sobre la necesidad de fomentar este tipo de práctica lectora en el aula. Para ejemplificar el funcionamiento de la lectura crítica, se trabajan lingüísticamente desde el ACD algunos fragmentos breves de discurso. Se analiza el grado y el tipo de comprensión lectora crítica que muestran 25 exámenes de universitarios españoles de 20 años, estudiantes de Traducción e Interpretación en la Universidad Pompeu Fabra de Barcelona, que habían tenido 80 horas de instrucción sobre lengua escrita y análisis deldiscurso en castellano y catalán (con varias sesiones sobre Análisis Crítico del Discurso), en las que se habían analizado cooperativamente textos parecidos al propuesto en el examen.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Gender stereotypes of personality : universal and accurate ?

Numerous studies have documented subtle but consistent sex differences in self-reports and observer-ratings of five-factor personality traits, and such effects were found to show well- defined developmental trajectories and remarkable similarity across nations. In contrast, very little is known about perceived gender differences in five-factor traits in spite of their potential implications for gender biases at the interpersonal and societal level. In particular, it is not clear how perceived gender differences in five-factor personality vary across age groups and national contexts and to what extent they accurately reflect assessed sex differences in personality. To address these questions, we analyzed responses from 3,323 individuals across 26 nations (mean age = 22.3 years, 31% male) who were asked to rate the five-factor personality traits of typical men or women in three age groups (adolescent, adult, and older adult) in their respective nations. Raters perceived women as slightly higher in openness, agreeableness, and conscientiousness as well as some aspects of extraversion and neuroticism. Perceived gender differences were fairly consistent across nations and target age groups and mapped closely onto assessed sex differences in self- and observer-rated personality. Associations between the average size of perceived gender differences and national variations in sociodemographic characteristics, value systems, or gender equality did not reach statistical significance. Findings contribute to our understanding of the underlying mechanisms of gender stereotypes of personality and suggest that perceptions of actual sex differences may play a more important role than culturally based gender roles and socialization processes.