Identification des mesures d’inégalité dans les modèles de sélection

Dans ce mémoire, je considère un modèle de sélection standard avec sélection non aléatoire. D’abord, je discute la validité et la ‘‘sharpness ’’ des bornes sur l’intervalle interquantile de la distribution de la variable aléatoire latente non censurée, dérivées par Blundell et al. (2007). Ensuite, je dérive les bornes ‘‘sharp ’’ sur l’intervalle interquantile lorsque la distribution observée domine stochastiquement au premier ordre celle non observée. Enfin, je discute la ‘‘sharpness’’ des bornes sur la variance de la distribution de la variable latente, dérivées par Stoye (2010). Je montre que les bornes sont valides mais pas nécessairement ‘‘sharp’’. Je propose donc des bornes inférieures ‘‘sharp’’ pour la variance et le coefficient de variation de ladite distribution.

Identification et regroupement de QTL influençant la pression artérielle en modules épistatiques et analyse de deux gènes candidats chez la souche Dahl Salt-Sensitive

L’hypertension essentielle étant un facteur majeur de morbidité, la compréhension de son l’étiologie est prépondérante. Ainsi, la découverte de nouvelles composantes ou mécanismes de régulation de la PA par l’identification de QTL et l’étude de leurs interactions s’avère une approche prometteuse. L’utilisation de souches congéniques de rats pour l’étude de l’hypertension est une stratégie payante puisqu’elle permet de masquer les effets de l’environnement, tout en gardant le caractère polygénique de la PA. Longtemps conçu comme un trait issu de l’accumulation des effets minimes des QTL, la PA est régulée par une architecture basée sur l’existence d’interactions épistatiques. L’analyse par paires de QTL individuels a permis d’établir une modularité dans l’organisation des QTL chez le rat Dahl Salt-sensitive en fonction de la présence ou de l’absence d’une interaction épistatique entre eux. Ainsi, deux modules épistatiques ont été établis; EM1 et EM2 où tous les QTL appartenant à EM1 sont épistatiques entre eux et agissent de façon additive avec les membres de EM2. Des hiérarchies dans la régulation peuvent alors être révélées si les QTL d’un même EM ont des effets opposés. L’identification de la nature moléculaire des candidats C18QTL4/Hdhd2 et C18QTL3/Tcof1, membres du EM1, et de l’interaction épistatique entre ces deux QTL, a permis, en plus, d’élucider une régulation séquentielle au sein du module. Hdhd2 pourrait agir en amont de Tcof1 et réguler ce dernier par une modification post-traductionnelle. Cette interaction est la première évidence expérimentale de la prédiction des relations entre QTL, phénomène établi par leur modularisation. Le dévoilement du fonctionnement de l’architecture génétique à la base du contrôle de la PA et la découverte des gènes responsables des QTL permettrait d’élargir les cibles thérapeutiques et donc de développer des traitements antihypertenseurs plus efficaces.

Identification et étude de mécanismes régulant l’expression de MAPK

Les fichiers accompagnant le document sont en format Microsoft Excel 2010.

Développement des marqueurs moléculaires spécifiques pour l'identification et la quantification de deux espèces de champignons mycorhiziens arbusculaires en utilisant la PCR en temps réel

Les champignons mycorhizien à arbuscules (CMA) sont des organismes pouvant établir des symbioses avec 80% des plantes terrestres. Les avantages d'une telle symbiose sont de plus en plus caractérisés et exploités en agriculture. Par contre, jusqu'à maintenant, il n'existe aucun outil permettant à la fois l'identification et la quantification de ces champignons dans le sol de façon fiable et rapide. Un tel outil permettrait, entre autres, de mieux comprendre les dynamiques des populations des endomycorhizes dans le sol. Pour les producteurs d'inoculum mycorhiziens, cela permettrait également d'établir un suivi de leurs produits en champs et d'avoir un contrôle de qualité de plus sur leurs inoculants. C'est ce que nous avons tenté de développer au sein du laboratoire du Dr. Hijri. Depuis environ une trentaine d'années, des outils d'identification et/ou de quantification ont été développés en utilisant les profiles d'acides gras, les isozymes, les anticorps et finalement l'ADN nucléaire. À ce jour, ces méthodes d’identification et de quantification sont soit coûteuses, soit imprécises. Qui plus est, aucune méthode ne permet à la fois la quantification et l’identification de souches particulières de CMA. L’ADN mitochondrial ne présente pas le même polymorphisme de séquence que celui qui rend l’ADN nucléaire impropre à la quantification. C'est pourquoi nous avons analysé les séquences d’ADN mitochondrial et sélectionné les régions caractéristiques de deux espèces de champignons mycorhiziens arbusculaires (CMA). C’est à partir de ces régions que nous avons développé des marqueurs moléculaires sous forme de sondes et d’amorces TaqMan permettant de quantifier le nombre de mitochondries de chacune de ces espèces dans un échantillon d’ADN. Nous avons ensuite tenté de déterminer une unité de quantification des CMA, soit un nombre de mitochondries par spore. C’est alors que nous avons réalisé que la méthode de préparation des échantillons de spores ainsi que la méthode d’extraction d’ADN avaient des effets significatifs sur l’unité de quantification de base. Nous avons donc optimisé ces protocoles, avant d’en e tester l’application sur des échantillons de sol et de racines ayant été inoculés avec chacune des deux espèces cibles. À ce stade, cet outil est toujours semi-quantificatif, mais il permet 9 l’identification précise de deux espèces de CMA compétentes dans des milieux saturés en phosphore inorganique. Ces résultats , en plus d’être prometteurs, ont permis d’augmenter les connaissances méthodologiques reliées à la quantification des CMA dans le sol, et suggèrent qu’à cause de leurs morphologies différentes, l’élaboration d’un protocole de quantification standardisé pour toutes les espèces de CMA demeure un objectif complexe, qui demande de nouvelles études in vivo.

Identification des résidus essentiels à l’interaction du récepteur CXCR7 avec ses ligands SDF-1 et ITAC

Les chimiokines sont des petites protéines secrétées dont la fonction principale est la stimulation de la migration de cellules immunitaires vers différents organes et tissus. Elles sont souvent impliquées lors des maladies inflammatoires, auto-immunes et des cancers. Ainsi, les chimiokines et leurs récepteurs couplés aux protéines G (RCPG) sont la cible pharmacologique de plusieurs molécules, actuellement testées en essais cliniques. Nous avons pris comme modèle, lors de notre étude, le récepteur atypique CXCR7. Ce récepteur est dit atypique, car il ne signalise pas via la voie classique des protéines G, mais plutôt via la voie de la β-arrestine. CXCR7 est impliqué dans de nombreux cancers, favorise la progression métastatique et est un co-récepteur pour le virus de l’immunodéficience humaine (VIH). Cependant, aucune donnée sur son mode de liaison avec ses ligands CXCL11/ITAC et CXCL12/SDF-1 n’existe à date. Nous pensons que cette information est essentielle pour le développement efficace d’agonistes et d’antagonistes, et nous nous sommes intéressés à identifier les résidus essentiels à la liaison des deux ligands de CXCR7 et à son activation par ces derniers. Pour cela, nous avons créé une série de mutants par substitution ou délétion d’acides aminés de la partie N-terminale, des boucles extracellulaires et des domaines transmembranaires du récepteur. Nous avons testé leur marquage en surface cellulaire par cytométrie en flux, leur liaison des deux ligands par expériences de radio-liaison, et leur capacité à recruter la β-arrestine en réponse aux ligands par essais BRET. Les résultats obtenus ont permis d’identifier des résidus importants à l’interaction des systèmes CXCR7/SDF-1 et CXCR7-ITAC et suggèrent des modes de liaison à CXCR7 différents entre ITAC et SDF-1. Tout comme la liaison d’ITAC à son autre récepteur CXCR3, sa liaison à CXCR7 suivrait le mode conventionnel de liaison en deux étapes des récepteurs de chimiokines. Cependant, la liaison de SDF-1 à CXCR7 suivrait un autre mode de liaison, contrairement à sa liaison à son autre récepteur, CXCR4.

A simple model of two-stage choice

I provide choice-theoretic foundations for a simple two-stage model, called transitive shortlist methods, where choices are made by sequentially by applying a pair of transitive preferences (or rationales) to eliminate inferior alternatives. Despite its simplicity, the model accommodates a wide range of choice phenomena including the status quo bias, framing, homophily, compromise, and limited willpower. I establish that the model can be succinctly characterized in terms of some well-documented context effects in choice. I also show that the underlying rationales are straightforward to determine from readily observable reversals in choice. Finally, I highlight the usefulness of these results in a variety of applications.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Finite-size scaling analysis of the avalanches in the three-dimensional Gaussian random-field Ising model with metastable dynamics

A numerical study is presented of the third-dimensional Gaussian random-field Ising model at T=0 driven by an external field. Standard synchronous relaxation dynamics is employed to obtain the magnetization versus field hysteresis loops. The focus is on the analysis of the number and size distribution of the magnetization avalanches. They are classified as being nonspanning, one-dimensional-spanning, two-dimensional-spanning, or three-dimensional-spanning depending on whether or not they span the whole lattice in different space directions. Moreover, finite-size scaling analysis enables identification of two different types of nonspanning avalanches (critical and noncritical) and two different types of three-dimensional-spanning avalanches (critical and subcritical), whose numbers increase with L as a power law with different exponents. We conclude by giving a scenario for avalanche behavior in the thermodynamic limit.

Speaker identification using models for phonemes

Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter.

Model Development and Validation for Studying Consumer Preferences of Car Owners

Globalization and liberalization, with the entry of many prominent foreign manufacturers, changed the automobile scenario in India, since early 1990‟s. Manufacturers such as Ford, General Motors, Honda, Toyota, Suzuki, Hyundai, Renault, Mitsubishi, Benz, BMW, Volkswagen and Nissan set up their manufacturing units in India in joint venture with their Indian counterpart companies, by making use of the Foreign Direct Investment policy of the Government of India, These manufacturers started capturing the hearts of Indian car customers with their choice of technological and innovative product features, with quality and reliability. With the multiplicity of choices available to the Indian passenger car buyers, it drastically changed the way the car purchase scenario in India and particularly in the State of Kerala. This transformed the automobile scene from a sellers‟ market to buyers‟ market. Car customers started developing their own personal preferences and purchasing patterns, which were hitherto unknown in the Indian automobile segment. The main purpose of this paper is to come up with the identification of possible parameters and a framework development, that influence the consumer purchase behaviour patterns of passenger car owners in the State of Kerala, so that further research could be done, based on the framework and the identified parameters

Conceptualisation Of Model For Studying Consumer Purchase Behaviour Of Passenger Cars

Automobile Industry in India is influenced by the presence of national and multi-national manufacturers. The presence of many manufacturers and brands in the state provides many choices to the customer. The current market for car manufacturers has been transformed from a monopoly of one or two manufacturers in the seventies to oligopoly of many manufacturers in the current marketing scenario. The main objective of the research paper is to explore and conceptualize various parameters and develop a model, which influence the purchase patterns of passenger cars in the State of Kerala. Thus, the main purpose of this paper is to come up with a model, which shall facilitate further study on the consumer purchase behaviour patterns of passenger car owners in the State of Kerala, India. The author intends to undertake further quantitative analysis to verify and validate the model so developed. The main methods used for this paper are secondary research on available material, depth interview of car dealers, car financing agencies and car owners in the city of Cochin, in Kerala State in India. The depth interviews were conducted with the use of prepared questionnaire for car dealers, car customers and car financing agencies. The findings resulted in the identification of the parameters that influence the consumer purchase behaviour of passenger cars and the formulation of the model, which will be the basis for the further research of the author. The paper will be of tremendous value to the existing and new car manufacturers both indigenous and foreign, to formalize and strategies their policies towards an effective marketing strategy, so as to market their models in the State, which is known for its high literacy, consumerism and higher educational penetration

Parameter identification of structural dynamic models by inverse statistical analysis

Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.

Identification, characterization and antigenicity of the Plasmodium vivax rhoptry neck protein 1 (PvRON1)

Background: Plasmodium vivax malaria remains a major health problem in tropical and sub-tropical regions worldwide. Several rhoptry proteins which are important for interaction with and/or invasion of red blood cells, such as PfRONs, Pf92, Pf38, Pf12 and Pf34, have been described during the last few years and are being considered as potential anti-malarial vaccine candidates. This study describes the identification and characterization of the P. vivax rhoptry neck protein 1 (PvRON1) and examine its antigenicity in natural P. vivax infections. Methods: The PvRON1 encoding gene, which is homologous to that encoding the P. falciparum apical sushi protein (ASP) according to the plasmoDB database, was selected as our study target. The pvron1 gene transcription was evaluated by RT-PCR using RNA obtained from the P. vivax VCG-1 strain. Two peptides derived from the deduced P. vivax Sal-I PvRON1 sequence were synthesized and inoculated in rabbits for obtaining anti-PvRON1 antibodies which were used to confirm the protein expression in VCG-1 strain schizonts along with its association with detergent-resistant microdomains (DRMs) by Western blot, and its localization by immunofluorescence assays. The antigenicity of the PvRON1 protein was assessed using human sera from individuals previously exposed to P. vivax malaria by ELISA. Results: In the P. vivax VCG-1 strain, RON1 is a 764 amino acid-long protein. In silico analysis has revealed that PvRON1 shares essential characteristics with different antigens involved in invasion, such as the presence of a secretory signal, a GPI-anchor sequence and a putative sushi domain. The PvRON1 protein is expressed in parasite's schizont stage, localized in rhoptry necks and it is associated with DRMs. Recombinant protein recognition by human sera indicates that this antigen can trigger an immune response during a natural infection with P. vivax. Conclusions: This study shows the identification and characterization of the P. vivax rhoptry neck protein 1 in the VCG-1 strain. Taking into account that PvRON1 shares several important characteristics with other Plasmodium antigens that play a functional role during RBC invasion and, as shown here, it is antigenic, it could be considered as a good vaccine candidate. Further studies aimed at assessing its immunogenicity and protection-inducing ability in the Aotus monkey model are thus recommended.

Identification of Putative Wintering Areas and Ecological Determinants of Population Dynamics of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) Breeding in Northern Italy

To identify the causes of population decline in migratory birds, researchers must determine the relative influence of environmental changes on population dynamics while the birds are on breeding grounds, wintering grounds, and en route between the two. This is problematic when the wintering areas of specific populations are unknown. Here, we first identified the putative wintering areas of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) populations breeding in northern Italy as those areas, within the wintering ranges of these species, where the winter Normalized Difference Vegetation Index (NDVI), which may affect winter survival, best predicted annual variation in population indices observed in the breeding grounds in 1992–2009. In these analyses, we controlled for the potentially confounding effects of rainfall in the breeding grounds during the previous year, which may affect reproductive success; the North Atlantic Oscillation Index (NAO), which may account for climatic conditions faced by birds during migration; and the linear and squared term of year, which account for nonlinear population trends. The areas thus identified ranged from Guinea to Nigeria for the Common House-Martin, and were located in southern Ghana for the Common Swift. We then regressed annual population indices on mean NDVI values in the putative wintering areas and on the other variables, and used Bayesian model averaging (BMA) and hierarchical partitioning (HP) of variance to assess their relative contribution to population dynamics. We re-ran all the analyses using NDVI values at different spatial scales, and consistently found that our population of Common House-Martin was primarily affected by spring rainfall (43%–47.7% explained variance) and NDVI (24%–26.9%), while the Common Swift population was primarily affected by the NDVI (22.7%–34.8%). Although these results must be further validated, currently they are the only hypotheses about the wintering grounds of the Italian populations of these species, as no Common House-Martin and Common Swift ringed in Italy have been recovered in their wintering ranges.

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.