En 2007, une étude menée par Hamlin, Wynn et Bloom a montré qu’à 6 mois les jeunes enfants disposent de capacités d’évaluation sociale, qui s’illustrent dans leur préférence pour des personnages prosociaux. Depuis, de nombreuses études ont tenté de retrouver la préférence pour un personnage prosocial. Parmi elles, certaines n’ont pas retrouvé ce résultat, questionnant la solidité de ces capacités.L’objectif de cette thèse est de tester l’existence et la robustesse de la préférence pour un comportement prosocial chez les jeunes enfants en manipulant : 1) l’âge (6, 12, 18, 24, 36 mois), le type de scénario social (aide, jeu, partage), et l’apparence faciale des agents prosociaux et antisociaux (familière ou inhabituelle). Dans cet objectif, quatre études ont été réalisées auprès de 446 enfants âgés de 6 à 36 mois qui ont visionné des dessins animés faisant interagir des agents prosociaux et antisociaux. Leurs préférences ont été identifiées par un geste de pointage/atteinte ou à l’aide d’un oculomètre.Nos résultats montrent que la préférence pour un comportement prosocial est observée quasiment à tous les âges testés, et varie en fonction du scénario social. Enfin, dans les situations sensées être conflictuelles au regard des préférences des jeunes enfants, ces derniers n’expriment majoritairement pas de préférence. L’ensemble des résultats remettent en question la solidité d’une préférence précoce pour un comportement prosocial et questionnent les conditions nécessaires à son observation. Les résultats de cette thèse sont discutés à la lumière de questionnements méthodologiques et d’études récentes qui fragilisent les résultats princeps d’Hamlin et ses collaborateurs. / In 2007, a study carried out by Hamlin, Wynn, and Bloom showed that infants aged 6 months are able to make social evaluation, that could be identified through their preference for prosocial characters. Since, a number of studies have tried to confirm this preference for prosocial characters. Of these, some did not find similar result, raising question on the robustness of this ability.This dissertation aims to test the existence and the strength of the preference for prosocial behaviors in infants by manipulating: 1) age (6, 12, 18, 24 and 36 months), the type of the social scenario (help, play, share), and the facial appearance of the prosocial and antisocial agents (familiar or unusual). To that end, four studies have been carried out with 446 infants aged 6 to 36 months who were shown specially designed animated cartoons in which prosocial and antisocial agents interacted. Infants’ preference was identified through their pointing/reaching gesture or assessed by an eye-tracker. Our results show that the preference for the prosocial behaviors was observed in nearly all the tested age, and varied according to the social scenario. Finally, in the situation assumed to be conflicting infants' preferences, infants mostly did not express any preference. All results challenge the strength of the preference for prosocial behaviors as well as the conditions that must be met to observe it. The results of this dissertation are discussed in the light of methodological issues and recent studies that weaken Hamlin and collaborators’ original results.

Hyaluronic acid (HA) is an unbranched polysaccharide consisting of the repeating disaccharide unit β(1→4)-GlcA-β(1→3)-GlcNAc and is a naturally occurring biopolymer in bacteria and vertebras. HA is predominantly found in the extracellular matrix (ECM) and the in vivo function of HA can vary depending on molecular weight (Mw) for instance high Mw HA is reported to be anti-angiogenic while low Mw HA induces angiogenesis. HA is a popular component for hydrogels such as dermal fillers. HA is commonly used in dermal fillers. However, other materials, such as other polymers, can be used as well. The project goal was to investigate different degradation processes for production of target Mw HA. Alkaline and acidic degradation processes in combination with increased temperatures seemed as the most promising methods. Degradation tests performed both in aqueous solution as well as heterogeneously in ethanol were evaluated. The acidic degradation in aqueous solution was proven to have the largest degradation constant. Both a robustness test as well as a Design of Experiments (DoE) was performed to investigate the influence different factors had on the degradation speed. The investigated factors were HA concentration, HCl concentration and temperature. Temperature and HCl concentrations proved to be the most influencing factors and a model was developed in the DoE software MODDE to describe how the factors influenced the degradation constant. The model was established as a good significant model with a Q2 value of 0.998 and relative standard deviation (RSD) value of 0.022 after a logarithmic transformation was performed as well as a simplification of the model by excluding some of the factor interactions. The acidic degradation method also proved to be a highly robust method which easily could be used to produce target Mw HA.

Les travaux effectués dans le cadre de cette thèse « Analyse de robustesse par contraintes intégrales quadratiques - Application aux lanceurs spatiaux » ont été menés en collaboration entre le Département Automatique de Supélec, EADS Astrium ST, l’Agence Spatiale Européenne (ESA) et l’université de Stuttgart. Le but était d’adapter et d’utiliser des méthodes analytiques de validation de loi de commande d'un lanceur en phase balistique pour améliorer les résultats obtenus par l’approche probabiliste fondée sur des simulations, technique actuellement majoritaire dans l’industrie. Dans ce cadre, l’utilisation des contraintes intégrales quadratiques (IQC) a permis de caractériser la stabilité et la performance robuste de la loi de commande d’un modèle représentatif du lanceur. Nous avons étudié l’influence de la dynamique non-linéaire des lanceurs sur la stabilité et la performance robuste. Dans ce cadre, nous avons factorisé les équations du mouvement en prenant en compte les incertitudes de la matrice d’inertie ainsi que les couplages gyroscopiques. Le second axe traita de l’influence des actionneurs de type modulateur de largeur impulsions (PWM) sur la stabilité du système par deux études IQC. La conclusion de ces travaux de thèse met l’accent sur l’importance de l’utilisation de méthodes analytiques dans le domaine spatial. Ces méthodes permettent l’obtention de garanties rigoureuses de stabilité et de performance des systèmes. De plus, toutes les méthodes d’analyse possèdent leur extension pour la synthèse de correcteurs robustes. Ainsi on imagine aisément l’immense gain que pourrait produire l’utilisation de ces méthodes pour la synthèse de correcteurs robustes. / The introduction of analytical techniques along the steps of the development of a space launcher will allow significant reductions in terms of costs and manpower, and will enable, by a more systematical way of tuning and assessing control laws, to get flyable designs much faster. In this scope, IQC based tools already present promising result and show that they may be the most appropriate ones for the robustness analysis of large complex systems. They account for the system structure and allow dealing specifically with each subsystems, it means that we can improve the representation contained in the multipliers easily and reuse the set up to assess the improvements. The flexibility of the method is a huge advantage. We experienced it during two phases. The first was dedicated to the analysis of the three-degree-of-freedom uncertain nonlinear equation of motion of a rigid body. Secondly, we studied the influence of the pulse-width modulator behavior of the attitude control system on the launcher stability. IQC-based stability analysis allowed defining estimations of the stability domain with respect to uncertainties and system parameters. Moreover, the results obtained with IQC can go way beyond stability analysis with performance analysis with description of the particular performance criteria of the field with appropriate multipliers. Later on controller synthesis and merging of IQC method with worst-case search algorithms could extend greatly the frame of use of this analytical tool and give it the influence it deserves.

Multiples techniques d'optimisation ont été implémentées afin de surmonter le compromis entre la complexité des algorithmes du raisonnement et l'expressivité du langage de formulation des ontologies. Cependant les compagnes d'évaluation des raisonneurs continuent de confirmer l'aspect imprévisible et aléatoire des performances de ces logiciels à l'égard des ontologies issues du monde réel. Partant de ces observations, l'objectif principal de cette thèse est d'assurer une meilleure compréhension du comportement empirique des raisonneurs en fouillant davantage le contenu des ontologies. Nous avons déployé des techniques d'apprentissage supervisé afin d'anticiper des comportements futurs des raisonneurs. Nos propositions sont établies sous forme d'un système d'assistance aux utilisateurs d'ontologies, appelé "ADSOR". Quatre composantes principales ont été proposées. La première est un profileur d'ontologies. La deuxième est un module d'apprentissage capable d'établir des modèles prédictifs de la robustesse des raisonneurs et de la difficulté empirique des ontologies. La troisième composante est un module d'ordonnancement par apprentissage, pour la sélection du raisonneur le plus robuste étant donnée une ontologie. Nous avons proposé deux approches d'ordonnancement; la première fondée sur la prédiction mono-label et la seconde sur la prédiction multi-label. La dernière composante offre la possibilité d'extraire les parties potentiellement les plus complexes d'une ontologie. L'identification de ces parties est guidée par notre modèle de prédiction du niveau de difficulté d'une ontologie. Chacune de nos approches a été validée grâce à une large palette d'expérimentations. / Highly optimized reasoning algorithms have been developed to allow inference tasks on expressive ontology languages such as OWL (DL). Nevertheless, reasoning remains a challenge in practice. In overall, a reasoner could be optimized for some, but not all ontologies. Given these observations, the main purpose of this thesis is to investigate means to cope with the reasoner performances variability phenomena. We opted for the supervised learning as the kernel theory to guide the design of our solution. Our main claim is that the output quality of a reasoner is closely depending on the quality of the ontology. Accordingly, we first introduced a novel collection of features which characterise the design quality of an OWL ontology. Afterwards, we modelled a generic learning framework to help predicting the overall empirical hardness of an ontology; and to anticipate a reasoner robustness under some online usage constraints. Later on, we discussed the issue of reasoner automatic selection for ontology based applications. We introduced a novel reasoner ranking framework. Correctness and efficiency are our main ranking criteria. We proposed two distinct methods: i) ranking based on single label prediction, and ii) a multi-label ranking method. Finally, we suggested to extract the ontology sub-parts that are the most computationally demanding ones. Our method relies on the atomic decomposition and the locality modules extraction techniques and employs our predictive model of the ontology hardness. Excessive experimentations were carried out to prove the worthiness of our approaches. All of our proposals were gathered in a user assistance system called "ADSOR".

Submitted by Aline Batista (alinehb.ufpel@gmail.com) on 2018-04-18T14:21:35Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Rosana_Medina_Zanotelli.pdf: 897398 bytes, checksum: 53b6f15a010386648223058dfc32101b (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2018-04-19T14:42:08Z (GMT) No. of bitstreams: 2 Dissertacao_Rosana_Medina_Zanotelli.pdf: 897398 bytes, checksum: 53b6f15a010386648223058dfc32101b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-04-19T14:42:21Z (GMT). No. of bitstreams: 2 Dissertacao_Rosana_Medina_Zanotelli.pdf: 897398 bytes, checksum: 53b6f15a010386648223058dfc32101b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2015-04-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Esta dissertação contribui com a análise da robustez na Lógica Fuzzy, como uma importante fundamentação para modelagem e desenvolvimento de sistemas robustos, estendendo esta abordagem para a lógica intuicionista de Atanassov. Primeiramente, apresenta-se uma introdução à lógica fuzzy, discutindo as negações, funções de agregações, implicações e coimplicações fuzzy, incluindo também os conectivos Xor e derivações. O trabalho também considera a análise da -sensibilidade destes conectivos fuzzy e suas construções duais, essencialmente focados em propriedades algébricas e projeções. Começando com a avaliação da sensibilidade de conectivos fuzzy, a proposta estende os resultados para classes de conectivos fuzzy intuicionistas. Como principal contribuição, formalmente estabelece-se que a robustez preserva as construções duais e as funções de projeção relacionadas a conectivos fuzzy intuicionistas representáveis. Mostra-se que a extensão, do trabalho científico proposto por Y. Li e colaboradores, 2005 em "An Approach to Measure the Robustness of Fuzzy Reasoning", para a classe de conectivos fuzzy intuicionistas é preservada pelas construções duais. A presente pesquisa mostra que a análise de robustez pode ser diretamente verificada a partir de operadores fuzzy usando duas estratégias: (i) a -sensibilidade de operadores fuzzy baseada na análise da monotonicidade de seus argumentos (negações, agregações, implicações e coimplicações); e ainda (ii) a avaliação do comportamento dos operadores fuzzy nos pontos terminais do intervalo unitário, onde a monotonicidade não pode ser aplicada (conectivos Xor, XNor, bi-implicações e bi-coimplicações). / This dissertation contributes to the robustness analysis in fuzzy logic as an important founding for modeling and developing robust systems, extending such approach to the Atanassov’s intuitionistic fuzzy sets. It begins with the introduction of fuzzy logic, discussing negations, aggregation functions, fuzzy implications and bi-implications, also including Xor connectives and derivations. It also considers the -sensitivity analysis of these fuzzy connectives and their dual constructions from a few essentials such as properties and projections. Starting with an evaluation of the sensitivity in representable fuzzy connectives, the results are applied in the intuitionistic connective classes. The main result formally states that the robustness preserves the projection functions of representable intuitionistic fuzzy connectives. It shows an extension of the work in Y. Li et al, 2005 "An Approach to Measure the Robustness of Fuzzy Reasoning" for the class of intuitionistic fuzzy connectives, showing that the robustness of intuitionistic fuzzy sensitivity is preserved by dual constructions. The present research states that robustness analysis of intuitionistic fuzzy operators can be directly verified from fuzzy operators using two strategies: (i) the -sensitivity analysis of fuzzy connectives based on monotonicity of their arguments (negations, aggregations, implications and coimplications); and, otherwise (ii) the evaluation of the behaviour related to fuzzy connectives in endpoints of the unit interval, when the monotonicity property is not applied (Xor, XNor, bi-implications e bi-coimplications fuzzy operators).

Malgré les améliorations portées à la détection des crues, à leurs prévisions et au perfectionnement des technologies de communication ces vingt dernières années, les systèmes d’alerte aux inondations restent soumis à des vulnérabilités et des incertitudes inhérentes à leur fonctionnement. En s’intéressant plus particulièrement au dispositif de Vigilance crues, ce travail questionne la manière dont les acteurs impliqués dans ce dispositif sociotechnique s’adaptent aux incertitudes et vulnérabilités auxquelles ils sont soumis. Ce travail s’appuie notamment sur le développement d’un modèle centré sur la notion de robustesse. D’une part, celui-ci permet de mieux saisir les processus qui conditionnent l’atteinte de l’objectif d’anticipation et d’amélioration de l’action collective organisée au cours d’une inondation. D’autre part, cette approche, en combinant les capacités à faire face des acteurs et les vulnérabilités du système, questionne les conditions socio-spatiales de la robustesse de la Vigilance crues au quotidien, i.e. en dehors des périodes de crues. Notre méthodologie repose sur plus de cent cinquante entretiens auprès des acteurs du système de vigilance dans le bassin Adour-Garonne. Il est ainsi démontré que la robustesse de ce système dépend (1) de la capacité des acteurs à faire face aux incertitudes et de leurs connaissances territoriales ; (2) de la mise en œuvre d’une approche intégrée qui tient compte des savoirs vernaculaires et des savoirs techniques ; (3) de rencontres régulières entre maires, services de gestion de crise et prévisionnistes, en particulier dans le cadre d’exercices inondation. Ainsi, se développent la confiance entre acteurs, l’apprentissage collectif et le renforcement de l’action collective en situations de crise. / Improving flood forecasting has become a technological race with major advances over the last 20 years. Moreover, communication technologies improvements have significantly increased the speed of warning dissemination. However, flood warning systems present inherent uncertainties and vulnerabilities. The present thesis questions how stakeholders involved in the French Flood Warning System (FFWS) deal with those uncertainties and vulnerabilities to achieve the aim of anticipation. Our approach is based on a conceptual model making use of the concept of robustness. We have applied this model to several flooded territories in the Adour-Garonne basin (France). Taking into account both vulnerability and coping capacities, we analyse the socio-spatial conditions that allows the robustness of the FFWS. A qualitative research methodology (150 semi-directive interviews) was adopted for the case studies. We demonstrate that (1) some vulnerabilities of the institutional warning can be overcome by the coping capacities and territorial knowledge of people at risk ; (2) the improvement of the FFWS can be achieved by the combination of both vernacular and scientific knowledges, and by an adaptation to local context ; (3) the reinforcement of the FFWS robustness depends on the upholding and the development of collective action, integrating people at-risk, crisis management services and forecasters through regular meetings and flood training exercises outside flooding periods. Such actions allow reinforcing collective action during crisis situations through the development of trustfulness.

A review of recent literature and the research effort underlying this dissertation indicates that fractional order differential equations have significant potential to advance dynamical system methods broadly. Particular promise exists in the area of control and estimation, even for systems where fractional order models do not arise “naturally”. This dissertation is aimed at further building of the base methodology with a focus on robust feedback control and state estimation. By setting the mathematical foundation with the fractional derivative Caputo definition, we can expand the concept of the fractional order calculus in a way that enables us to build corresponding controllers and estimators in the state-space form. For the robust eigenstructure assignment, we first examine the conditioning problem of the closed-loop eigenvalues and stability robustnesss criteria for the fractional order system, and we find a unique application of an n-dimensional rotation algorithm developed by Mortari, to solve the robust eigenstructure assignment problem in a novel way. In contradistinction to the existing Fractional Kalman filter developed by using Gru ̈ndwald-Letnikov definition, the new Fractional Kalman filter that we establish by utilizing Caputo definition and our algorithms provide us with powerful means for solving practical state estimation problems for fractional order systems.

Model reliability is important when groundwater models are used for evaluation of environmental impact and water resource management. Model attributes such as geohydrologic units and parameter values need to be quantified in order to obtain reliable results. A primary objective of sampling design for groundwater models is to increase the reliability of modelling results by selecting effective measurement locations and times. It is advantageous to employ simulation models to guide measurement strategies already in early investigation stages. Normally, optimal design is only possible when model attributes are known prior to constructing a design. This is not a meaningful requirement as the model attributes are the final result of the analysis and are not known beforehand. Thus, robust design methods are required that are effective for ranges of parameter values, measurement error types and for alternative conceptual models. Parameter sensitivity is the fundamental model property that is used in this thesis to create effective designs. For conceptual model uncertainty, large-scale sensitivity analysis is used to devise networks that capture sufficient information to determine which model best describes the system with a minimum of measurement points. In fixed conceptual models, effective parameter- and error-robust designs are based on criteria that minimise the size of the parameter covariance matrix (D-optimality). Optimal designs do not necessarily have observations with the highest parameter sensitivities because D-optimality reduces parameter estimation errors by balancing high sensitivity and low correlation between parameters. Ignoring correlation in sparse designs may result in considerably inefficient designs. Different measurement error assumptions may also give widely different optimal designs. Early stage design often involves simple homogenous models for which the design effectiveness may be seriously offset by significant aquifer heterogeneity. Simple automatic and manual methods are possible for design generation. While none of these guarantee globally optimal designs, they do generate designs that are more effective than those normally used for measurement programs. Effective designs are seldom intuitively obvious, indicating that this methodology is quite useful. A general benefit of this type of analysis, in addition to the actual generation of designs, is insight into the relative importance of model attributes and their relation to different measurement strategies.

Unravelling biological processes is dependent on the adequate modelling of regulatory mechanisms that determine the timing and spatial patterns of gene expression. In the last decade, a novel regulatory mechanism has been discovered and its biological importance has been increasingly recognised. This mechanism is mediated by RNA molecules named miRNAs that are the product of the maturation of non-coding gene transcripts and act post- transcriptionally usually to dampen or abolish the expression of protein-coding genes. Despite having eluded detection for such a long time, it is now clear that the elucidation of the expression pattern of many genes cannot be achieved without incorporating the effects of miRNA-mediated regulation. The technical difficulties that the experimental detection of these regulators entailed prompted the development of increasingly sophisticated computational approaches. Gene finding strategies originally developed for coding genes cannot be applied since these non- coding molecules are subject to very different sequence restraints and are too short to exhibit statistical properties that can be easily distinguished from the background. As a result, com- putational tools came to rely heavily on the identification of conserved sequences, distant homologs and machine learning techniques. Recent developments in sequencing technology have overcome some of the limitations of earlier experimental approaches, but pose new computational challenges. At present, the identification of new miRNA genes is therefore the result of the use of several approaches, both computational and experimental. In spite of the advancement that this research field has known in the last several years, we are still not able to formally and rigourously characterise miRNA genes in order to identify whichever sequence, structure or contextual requirements are needed to turn a DNA sequence into a functional miRNA. Efforts using computational algorithms towards the enumeration of the full set of miRNAs of an organism have been limited by strong reliance on arguments of precursor conservation and feature similarity. However, miRNA precursors may arise anew or be lost across the evolutionary history of a species and a newly-sequenced genome may be evolutionarily too distant from other genomes for an adequate comparative analysis. In addition, the learning of intricate classification rules based purely on features shared by miRNA precursors that are currently known may reflect a perpetuating identification bias rather than a sound means to tell true miRNAs from other genomic stem-loops. In this thesis, we present a strategy to sieve through the vast amount of stem-loops found in metazoan genomes in search of pre-miRNAs, significantly reducing the set of candidates while retaining most known miRNA precursors. Our approach relies on precursor properties derived from the current knowledge of miRNA biogenesis, analysis of the precursor structure and incorporation of information about the transcription potential of each candidate. i Our approach has been applied to the genomes of Drosophila melanogaster and Anophe- les gambiae, which has allowed us to show that there is a strong bias amongst annotated pre-miRNAs towards robust stem-loops in these genomes and to propose a scoring scheme for precursor candidates which combines four robustness measures. Additionally, we have identified several known pre-miRNA homologs in the newly-sequenced Anopheles darlingi and shown that most are found amongst the top-scoring precursor candidates for that or- ganism, with respect to the combined score. The structural analysis of our candidates and the identification of the region of the structural space where known precursors are usually found allowed us to eliminate several candidates, but also showed that there is a staggering number of genomic stem-loops which seem to fulfil the stability, robustness and structural requirements indicating that additional evidence is needed to identify functional precursors. To this effect, we have introduced different strategies to evaluate the transcription potential of the remaining candidates which vary according to the information which is available for the dataset under study.

Wireless sensor networks (WSNs) have recently achieved a great deal of attention due to its numerous attractive applications in many different fields. Sensors and WSNs possesses a number of special characteristics that make them very promising in many applications, but also put on them lots of constraints that make issues in sensor network particularly difficult. These issues may include topology control, routing, coverage, security, and data management. In this thesis, we focus our attention on the coverage problem. Firstly, we define the Sensor Energy-efficient Scheduling for k-coverage (SESK) problem. We then solve it by proposing a novel, completely localized and distributed scheduling approach, naming Distributed Energy-efficient Scheduling for k-coverage (DESK) such that the energy consumption among all the sensors is balanced, and the network lifetime is maximized while still satisfying the k-coverage requirement. Finally, in related work section we conduct an extensive survey of the existing work in literature that focuses on with the coverage problem.