A main thrust of this thesis is to develop and explore linearization-based numeric-analytic integration techniques in the context of stochastically driven nonlinear oscillators of relevance in structural dynamics. Unfortunately, unlike the case of deterministic oscillators, available numerical or numeric-analytic integration schemes for stochastically driven oscillators, often modelled through stochastic differential equations (SDE-s), have significantly poorer numerical accuracy. These schemes are generally derived through stochastic Taylor expansions and the limited accuracy results from difficulties in evaluating the multiple stochastic integrals. We propose a few higher-order methods based on the stochastic version of transversal linearization and another method of linearizing the nonlinear drift field based on a Girsanov change of measures. When these schemes are implemented within a Monte Carlo framework for computing the response statistics, one typically needs repeated simulations over a large ensemble. The statistical error due to the finiteness of the ensemble (of size N, say)is of order 1/√N, which implies a rather slow convergence as N→∞. Given the prohibitively large computational cost as N increases, a variance reduction strategy that enables computing accurate response statistics for small N is considered useful. This leads us to propose a weak variance reduction strategy. Finally, we use the explicit derivative-free linearization techniques for state and parameter estimations for structural systems using the extended Kalman filter (EKF). A two-stage version of the EKF (2-EKF) is also proposed so as to account for errors due to linearization and unmodelled dynamics. In Chapter 2, we develop higher order locally transversal linearization (LTL) techniques for strong and weak solutions of stochastically driven nonlinear oscillators. For developing the higher-order methods, we expand the non-linear drift and multiplicative diffusion fields based on backward Euler and Newmark expansions while simultaneously satisfying the original vector field at the forward time instant where we intend to find the discretized solution. Since the non-linear vector fields are conditioned on the solution we wish to determine, the methods are implicit. We also report explicit versions of such linearization schemes via simple modifications. Local error estimates are provided for weak solutions. Weak linearized solutions enable faster computation vis-à-vis their strong counterparts. In Chapter 3, we propose another weak linearization method for non-linear oscillators under stochastic excitations based on Girsanov transformation of measures. Here, the non-linear drift vector is appropriately linearized such that the resulting SDE is analytically solvable. In order to account for the error in replacing of non-linear drift terms, the linearized solutions are multiplied by scalar weighting function. The weighting function is the solution of a scalar SDE(i.e.,Radon-Nikodym derivative). Apart from numerically illustrating the method through applications to non-linear oscillators, we also use the Girsanov transformation of measures to correct the truncation errors in lower order discretizations. In order to achieve efficiency in the computation of response statistics via Monte Carlo simulation, we propose in Chapter 4 a weak variance reduction strategy such that the ensemble size is significantly reduced without seriously affecting the accuracy of the predicted expectations of any smooth function of the response vector. The basis of the variance reduction strategy is to appropriately augment the governing system equations and then weakly replace the associated stochastic forcing functions through variance-reduced functions. In the process, the additional computational cost due to system augmentation is generally far less besides the accrued advantages due to a drastically reduced ensemble size. The variance reduction scheme is illustrated through applications to several non-linear oscillators, including a 3-DOF system. Finally, in Chapter 5, we exploit the explicit forms of the LTL techniques for state and parameters estimations of non-linear oscillators of engineering interest using a novel derivative-free EKF and a 2-EKF. In the derivative-free EKF, we use one-term, Euler and Newmark replacements for linearizations of the non-linear drift terms. In the 2-EKF, we use bias terms to account for errors due to lower order linearization and unmodelled dynamics in the mathematical model. Numerical studies establish the relative advantages of EKF-DLL as well as 2-EKF over the conventional forms of EKF. The thesis is concluded in Chapter 6 with an overall summary of the contributions made and suggestions for future research.

No description available.

Les propriétés des matériaux moléculaires proviennent à la fois de la structure des composantes individuelles et de la façon dont elles s’associent. Ce dernier aspect reste difficile à contrôler, malgré de grandes avancées en science des matériaux. Pour mieux comprendre la relation structure-propriétés, nous avons entrepris une étude systématique de l'hexaphénylbenzène et de ses dérivés, qui offrent une charpente symétrique et rigide. En premier lieu, nous avons attaché six groupements diaminotriazinyles sur l’hexaphénylbenzène afin de produire des réseaux tridimensionnels hautement poreux maintenus par des ponts hydrogène. En modifiant systématiquement le coeur moléculaire, nous avons excisé près du tiers de la molécule-mère, générant des réseaux supramoléculaires dont la porosité s’est élevée graduellement jusqu’à 75%, équivalant ainsi le record pour ce type de matériaux. Ensuite, nous avons étudié le comportement de l’hexakis(4-nitrophényl)benzène. Dans les structures cristallines obtenues, des interactions non-covalentes entre groupements nitro démontrent leur potentiel en chimie supramoléculaire. Le coeur moléculaire ne joue qu’un rôle secondaire dans l’empilement des molécules : seules quelques interactions C-H•••π impliquant le cycle aromatique central de l’hexaphénylbenzène sont évidentes. Cette dernière observation nous a poussés à étudier le comportement à l’état cristallin de l’hexaphénylbenzène et ses dérivés. En scrutant attentivement neuf structures cristallines de ces composés, nous avons décerné la présence récurrente d’interactions C-H•••π impliquant le cycle aromatique central. Cette association caractéristique a été exploitée pour créer des réseaux supramoléculaires maintenus par des interactions C-H•••π sélectives entre un groupement éthynyle et le cycle aromatique central de l’hexaphénylbenzène. Finalement, nous avons joint le côté sombre de l’ingénierie cristalline en utilisant nos connaissances dans le but d’empêcher la formation d’interactions directionnelles. En protégeant le cycle aromatique central de l’hexaphénylbenzène à l’aide de groupements alkyles, les interactions C-H•••π ont été pratiquement éliminées. Ces résultats offrent la possibilité de créer de nouveaux matériaux amorphes. Dans ces études, focalisées sur le système hexaphénylbenzène, nous avons mis en relief des phénomènes qui sont obscurcis dans d'autres familles de molécules. De plus, ce système a grandement facilité l’utilisation d’une approche méthodique pour explorer la relation structure-propriétés. Nos travaux nous ont amenés à des conclusions de valeur universelle en science des matériaux moléculaires. / The properties of molecular materials depend on the identity of individual components and on their organization. Unfortunately, it remains difficult to control molecular organization, despite advances in materials science. To better understand the relationship between molecular structure and collective properties, we undertook a systematic study of hexaphenylbenzene and its derivatives, which possess a rigid symmetric framework. Our first study focused on using hydrogen bonds to control self-assembly in the solid state. By installing six diaminotriazinyl groups on a hexaphenylbenzene core, we predictably obtained highly porous three-dimensional hydrogen-bonded networks. Through systematic structural modifications of the molecular core, we excised nearly a third of the parent molecule, and the porosity of the networks gradually increased, matching the record of 75% previously obtained for this type of material. We then turned to weaker interactions to control organization, as revealed by the packing of hexakis(4-nitrophenyl)benzene. In the crystal structures analyzed, non-covalent interactions between nitro groups were observed, demonstrating their potential in supramolecular chemistry. Careful examination of the structures showed that the hexaphenylbenzene moieties play only a secondary role in determining the overall packing; however, C-H•••π interactions involving the central aromatic ring of hexaphenylbenzene were also observed. To further document this unexpected behavior, we analyzed nine crystal structures of hexaphenylbenzene and derivatives, which showed that a C-H•••π recognition pattern involving the central aromatic ring occurs consistently throughout the series. This motif was used to prepare supramolecular networks based exclusively on selective and directional C-H•••π interactions involving ethynyl groups and the central aromatic ring of hexaphenylbenzene. Finally, we joined the dark side of crystal engineering by using our knowledge of supramolecular chemistry to prevent the formation of directional interactions. By installing alkyl groups near the central aromatic ring of hexaphenylbenzene, C-H•••π interactions were practically eliminated. These results were then used to devise new amorphous materials. The hexaphenylbenzene system permitted a methodical analysis of structure-property relationships in molecular materials. This particular system exposed phenomena normally obscured in other families of molecules, and our analysis of its behavior has yielded conclusions of universal value in materials science.

La dernière décennie a connu un intérêt croissant pour les problèmes posés par les variables instrumentales faibles dans la littérature économétrique, c’est-à-dire les situations où les variables instrumentales sont faiblement corrélées avec la variable à instrumenter. En effet, il est bien connu que lorsque les instruments sont faibles, les distributions des statistiques de Student, de Wald, du ratio de vraisemblance et du multiplicateur de Lagrange ne sont plus standard et dépendent souvent de paramètres de nuisance. Plusieurs études empiriques portant notamment sur les modèles de rendements à l’éducation [Angrist et Krueger (1991, 1995), Angrist et al. (1999), Bound et al. (1995), Dufour et Taamouti (2007)] et d’évaluation des actifs financiers (C-CAPM) [Hansen et Singleton (1982,1983), Stock et Wright (2000)], où les variables instrumentales sont faiblement corrélées avec la variable à instrumenter, ont montré que l’utilisation de ces statistiques conduit souvent à des résultats peu fiables. Un remède à ce problème est l’utilisation de tests robustes à l’identification [Anderson et Rubin (1949), Moreira (2002), Kleibergen (2003), Dufour et Taamouti (2007)]. Cependant, il n’existe aucune littérature économétrique sur la qualité des procédures robustes à l’identification lorsque les instruments disponibles sont endogènes ou à la fois endogènes et faibles. Cela soulève la question de savoir ce qui arrive aux procédures d’inférence robustes à l’identification lorsque certaines variables instrumentales supposées exogènes ne le sont pas effectivement. Plus précisément, qu’arrive-t-il si une variable instrumentale invalide est ajoutée à un ensemble d’instruments valides? Ces procédures se comportent-elles différemment? Et si l’endogénéité des variables instrumentales pose des difficultés majeures à l’inférence statistique, peut-on proposer des procédures de tests qui sélectionnent les instruments lorsqu’ils sont à la fois forts et valides? Est-il possible de proposer les proédures de sélection d’instruments qui demeurent valides même en présence d’identification faible? Cette thèse se focalise sur les modèles structurels (modèles à équations simultanées) et apporte des réponses à ces questions à travers quatre essais. Le premier essai est publié dans Journal of Statistical Planning and Inference 138 (2008) 2649 – 2661. Dans cet essai, nous analysons les effets de l’endogénéité des instruments sur deux statistiques de test robustes à l’identification: la statistique d’Anderson et Rubin (AR, 1949) et la statistique de Kleibergen (K, 2003), avec ou sans instruments faibles. D’abord, lorsque le paramètre qui contrôle l’endogénéité des instruments est fixe (ne dépend pas de la taille de l’échantillon), nous montrons que toutes ces procédures sont en général convergentes contre la présence d’instruments invalides (c’est-à-dire détectent la présence d’instruments invalides) indépendamment de leur qualité (forts ou faibles). Nous décrivons aussi des cas où cette convergence peut ne pas tenir, mais la distribution asymptotique est modifiée d’une manière qui pourrait conduire à des distorsions de niveau même pour de grands échantillons. Ceci inclut, en particulier, les cas où l’estimateur des double moindres carrés demeure convergent, mais les tests sont asymptotiquement invalides. Ensuite, lorsque les instruments sont localement exogènes (c’est-à-dire le paramètre d’endogénéité converge vers zéro lorsque la taille de l’échantillon augmente), nous montrons que ces tests convergent vers des distributions chi-carré non centrées, que les instruments soient forts ou faibles. Nous caractérisons aussi les situations où le paramètre de non centralité est nul et la distribution asymptotique des statistiques demeure la même que dans le cas des instruments valides (malgré la présence des instruments invalides). Le deuxième essai étudie l’impact des instruments faibles sur les tests de spécification du type Durbin-Wu-Hausman (DWH) ainsi que le test de Revankar et Hartley (1973). Nous proposons une analyse en petit et grand échantillon de la distribution de ces tests sous l’hypothèse nulle (niveau) et l’alternative (puissance), incluant les cas où l’identification est déficiente ou faible (instruments faibles). Notre analyse en petit échantillon founit plusieurs perspectives ainsi que des extensions des précédentes procédures. En effet, la caractérisation de la distribution de ces statistiques en petit échantillon permet la construction des tests de Monte Carlo exacts pour l’exogénéité même avec les erreurs non Gaussiens. Nous montrons que ces tests sont typiquement robustes aux intruments faibles (le niveau est contrôlé). De plus, nous fournissons une caractérisation de la puissance des tests, qui exhibe clairement les facteurs qui déterminent la puissance. Nous montrons que les tests n’ont pas de puissance lorsque tous les instruments sont faibles [similaire à Guggenberger(2008)]. Cependant, la puissance existe tant qu’au moins un seul instruments est fort. La conclusion de Guggenberger (2008) concerne le cas où tous les instruments sont faibles (un cas d’intérêt mineur en pratique). Notre théorie asymptotique sous les hypothèses affaiblies confirme la théorie en échantillon fini. Par ailleurs, nous présentons une analyse de Monte Carlo indiquant que: (1) l’estimateur des moindres carrés ordinaires est plus efficace que celui des doubles moindres carrés lorsque les instruments sont faibles et l’endogenéité modérée [conclusion similaire à celle de Kiviet and Niemczyk (2007)]; (2) les estimateurs pré-test basés sur les tests d’exogenété ont une excellente performance par rapport aux doubles moindres carrés. Ceci suggère que la méthode des variables instrumentales ne devrait être appliquée que si l’on a la certitude d’avoir des instruments forts. Donc, les conclusions de Guggenberger (2008) sont mitigées et pourraient être trompeuses. Nous illustrons nos résultats théoriques à travers des expériences de simulation et deux applications empiriques: la relation entre le taux d’ouverture et la croissance économique et le problème bien connu du rendement à l’éducation. Le troisième essai étend le test d’exogénéité du type Wald proposé par Dufour (1987) aux cas où les erreurs de la régression ont une distribution non-normale. Nous proposons une nouvelle version du précédent test qui est valide même en présence d’erreurs non-Gaussiens. Contrairement aux procédures de test d’exogénéité usuelles (tests de Durbin-Wu-Hausman et de Rvankar- Hartley), le test de Wald permet de résoudre un problème courant dans les travaux empiriques qui consiste à tester l’exogénéité partielle d’un sous ensemble de variables. Nous proposons deux nouveaux estimateurs pré-test basés sur le test de Wald qui performent mieux (en terme d’erreur quadratique moyenne) que l’estimateur IV usuel lorsque les variables instrumentales sont faibles et l’endogénéité modérée. Nous montrons également que ce test peut servir de procédure de sélection de variables instrumentales. Nous illustrons les résultats théoriques par deux applications empiriques: le modèle bien connu d’équation du salaire [Angist et Krueger (1991, 1999)] et les rendements d’échelle [Nerlove (1963)]. Nos résultats suggèrent que l’éducation de la mère expliquerait le décrochage de son fils, que l’output est une variable endogène dans l’estimation du coût de la firme et que le prix du fuel en est un instrument valide pour l’output. Le quatrième essai résout deux problèmes très importants dans la littérature économétrique. D’abord, bien que le test de Wald initial ou étendu permette de construire les régions de confiance et de tester les restrictions linéaires sur les covariances, il suppose que les paramètres du modèle sont identifiés. Lorsque l’identification est faible (instruments faiblement corrélés avec la variable à instrumenter), ce test n’est en général plus valide. Cet essai développe une procédure d’inférence robuste à l’identification (instruments faibles) qui permet de construire des régions de confiance pour la matrices de covariances entre les erreurs de la régression et les variables explicatives (possiblement endogènes). Nous fournissons les expressions analytiques des régions de confiance et caractérisons les conditions nécessaires et suffisantes sous lesquelles ils sont bornés. La procédure proposée demeure valide même pour de petits échantillons et elle est aussi asymptotiquement robuste à l’hétéroscédasticité et l’autocorrélation des erreurs. Ensuite, les résultats sont utilisés pour développer les tests d’exogénéité partielle robustes à l’identification. Les simulations Monte Carlo indiquent que ces tests contrôlent le niveau et ont de la puissance même si les instruments sont faibles. Ceci nous permet de proposer une procédure valide de sélection de variables instrumentales même s’il y a un problème d’identification. La procédure de sélection des instruments est basée sur deux nouveaux estimateurs pré-test qui combinent l’estimateur IV usuel et les estimateurs IV partiels. Nos simulations montrent que: (1) tout comme l’estimateur des moindres carrés ordinaires, les estimateurs IV partiels sont plus efficaces que l’estimateur IV usuel lorsque les instruments sont faibles et l’endogénéité modérée; (2) les estimateurs pré-test ont globalement une excellente performance comparés à l’estimateur IV usuel. Nous illustrons nos résultats théoriques par deux applications empiriques: la relation entre le taux d’ouverture et la croissance économique et le modèle de rendements à l’éducation. Dans la première application, les études antérieures ont conclu que les instruments n’étaient pas trop faibles [Dufour et Taamouti (2007)] alors qu’ils le sont fortement dans la seconde [Bound (1995), Doko et Dufour (2009)]. Conformément à nos résultats théoriques, nous trouvons les régions de confiance non bornées pour la covariance dans le cas où les instruments sont assez faibles. / The last decade shows growing interest for the so-called weak instruments problems in the econometric literature, i.e. situations where instruments are poorly correlated with endogenous explanatory variables. More generally, these can be viewed as situations where model parameters are not identified or nearly so (see Dufour and Hsiao, 2008). It is well known that when instruments are weak, the limiting distributions of standard test statistics - like Student, Wald, likelihood ratio and Lagrange multiplier criteria in structural models - have non-standard distributions and often depend heavily on nuisance parameters. Several empirical studies including the estimation of returns to education [Angrist and Krueger (1991, 1995), Angrist et al. (1999), Bound et al. (1995), Dufour and Taamouti (2007)] and asset pricing model (C-CAPM) [Hansen and Singleton (1982, 1983), Stock and Wright (2000)], have showed that the above procedures are unreliable in presence of weak identification. As a result, identification-robust tests [Anderson and Rubin (1949), Moreira (2003), Kleibergen (2002), Dufour and Taamouti (2007)] are often used to make reliable inference. However, little is known about the quality of these procedures when the instruments are invalid or both weak and invalid. This raises the following question: what happens to inference procedures when some instruments are endogenous or both weak and endogenous? In particular, what happens if an invalid instrument is added to a set of valid instruments? How robust are these inference procedures to instrument endogeneity? Do alternative inference procedures behave differently? If instrument endogeneity makes statistical inference unreliable, can we propose the procedures for selecting "good instruments" (i.e. strong and valid instruments)? Can we propose instrument selection procedure which will be valid even in presence of weak identification? This thesis focuses on structural models and answers these questions through four chapiters. The first chapter is published in Journal of Statistical Planning and Inference 138 (2008) 2649 – 2661. In this chapter, we analyze the effects of instrument endogeneity on two identificationrobust procedures: Anderson and Rubin (1949, AR) and Kleibergen (2002, K) test statistics, with or without weak instruments. First, when the level of instrument endogeneity is fixed (does not depend on the sample size), we show that all these procedures are in general consistent against the presence of invalid instruments (hence asymptotically invalid for the hypothesis of interest), whether the instruments are "strong" or "weak". We also describe situations where this consistency may not hold, but the asymptotic distribution is modified in a way that would lead to size distortions in large samples. These include, in particular, cases where 2SLS estimator remains consistent, but the tests are asymptotically invalid. Second, when the instruments are locally exogenous (the level of instrument endogeneity approaches zero as the sample size increases), we find asymptotic noncentral chi-square distributions with or without weak instruments, and describe situations where the non-centrality parameter is zero and the asymptotic distribution remains the same as in the case of valid instruments (despite the presence of invalid instruments). The second chapter analyzes the effects of weak identification on Durbin-Wu-Hausman (DWH) specification tests an Revankar-Harttley exogeneity test. We propose a finite-and large-sample analysis of the distribution of DWH tests under the null hypothesis (level) and the alternative hypothesis (power), including when identification is deficient or weak (weak instruments). Our finite-sample analysis provides several new insights and extensions of earlier procedures. The characterization of the finite-sample distribution of the test-statistics allows the construction of exact identificationrobust exogeneity tests even with non-Gaussian errors (Monte Carlos tests) and shows that such tests are typically robust to weak instruments (level is controlled). Furthermore, we provide a characterization of the power of the tests, which clearly exhibits factors which determine power. We show that DWH-tests have no power when all instruments are weak [similar to Guggenberger(2008)]. However, power does exist as soon as we have one strong instruments. The conclusions of Guggenberger (2008) focus on the case where all instruments are weak (a case of little practical interest). Our asymptotic distributional theory under weaker assumptions confirms the finite-sample theory. Moreover, we present simulation evidence indicating: (1) over a wide range cases, including weak IV and moderate endogeneity, OLS performs better than 2SLS [finding similar to Kiviet and Niemczyk (2007)]; (2) pretest-estimators based on exogeneity tests have an excellent overall performance compared with usual IV estimator. We illustrate our theoretical results through simulation experiment and two empirical applications: the relation between trade and economic growth and the widely studied problem of returns to education. In the third chapter, we extend the generalized Wald partial exogeneity test [Dufour (1987)] to non-gaussian errors. Testing whether a subset of explanatory variables is exogenous is an important challenge in econometrics. This problem occurs in many applied works. For example, in the well know wage model, one should like to assess if mother’s education is exogenous without imposing additional assumptions on ability and schooling. In the growth model, the exogeneity of the constructed instrument on the basis of geographical characteristics for the trade share is often questioned and needs to be tested without constraining trade share and the other variables. Standard exogeneity tests of the type proposed by Durbin-Wu-Hausman and Revankar-Hartley cannot solve such problems. A potential cure for dealing with partial exogeneity is the use of the generalized linear Wald (GW) method (Dufour, 1987). The GW-procedure however assumes the normality of model errors and it is not clear how robust is this test to non-gaussian errors. We develop in this chapter, a modified version of earlier procedure which is valid even when model errors are not normally distributed. We present simulation evidence indicating that when identification is strong, the standard GW-test is size distorted in presence of non-gaussian errors. Furthermore, our analysis of the performance of different pretest-estimators based on GW-tests allow us to propose two new pretest-estimators of the structural parameter. The Monte Carlo simulations indicate that these pretest-estimators have a better performance over a wide range cases compared with 2SLS. Therefore, this can be viewed as a procedure for selecting variable where a GW-test is used in the first stage to decide which variables should be instruments and which ones are valid instruments. We illustrate our theoretical results through two empirical applications: the well known wage equation and the returns to scale in electricity supply. The results show that the GW-tests cannot reject the exogeneity of mother’s education, i.e. mother’s education may constitute a valid IV for schooling. However, the output in cost equation is endogenous and the price of fuel is a valid IV for estimating the returns to scale. The fourth chapter develops identification-robust inference for the covariances between errors and regressors of an IV regression. The results are then applied to develop partial exogeneity tests and partial IV pretest-estimators which are more efficient than usual IV estimator. When more than one stochastic explanatory variables are involved in the model, it is often necessary to determine which ones are independent of the disturbances. This problem arises in many empirical applications. For example, in the New Keynesian Phillips Curve, one should like to assess whether the interest rate is exogenous without imposing additional assumptions on inflation rate and the other variables. Standard Wu-Durbin-Hausman (DWH) tests which are commonly used in applied work are inappropriate to deal with such a problem. The generalized Wald (GW) procedure (Dufour, 1987) which typically allows the construction of confidence sets as well as testing linear restrictions on covariances assumes that the available instruments are strong. When the instruments are weak, the GW-test is in general size distorted. As a result, its application in models where instruments are possibly weak–returns to education, trade and economic growth, life cycle labor supply, New Keynesian Phillips Curve, pregnancy and the demand for cigarettes–may be misleading. To answer this problem, we develop a finite-and large-sample valid procedure for building confidence sets for covariances allowing for the presence of weak instruments. We provide analytic forms of the confidence sets and characterize necessary and sufficient conditions under which they are bounded. Moreover, we propose two new pretest-estimators of structural parameters based on our above procedure. Both estimators combine 2SLS and partial IV-estimators. The Monte Carlo experiment shows that: (1) partial IV-estimators outperform 2SLS when the instruments are weak; (2) pretestestimators have an excellent overall performance–bias and MSE– compared with 2SLS. Therefore, this can be viewed as a variable selection method where the projection-based techniques is used to decide which variables should be instrumented and which ones are valid instruments. We illustrate our results through two empirical applications: the relation between trade and economic growth and the widely studied problem of returns to education. The results show unbounded confidence sets, suggesting that the IV are relatively poor in these models, as questioned in the literature [Bound (1995)].

La dialectique pluralisme religieux/incertitude religieuse, sur laquelle porte cette thèse, se révèle être un thème majeur dans la pensée de Peter L. Berger, en sociologie des religions et en théologie protestante. Une analyse systématique et détaillée des concepts-clés qui la constituent débouche sur la question des rapports entre sociologie et théologie à laquelle Berger lui-même s’est confronté. Abordée sous l’angle de l’idée du principe protestant, cette question s’est résolue, dès la fin des années 1960, en un certain « mariage » entre son approche de la sociologie de la connaissance et son approche théologique libérale. Les concepts de foi et théologie « inductives », de « voie médiane entre le fondamentalisme et le relativisme », semblent jaillir de cette dialectique et de ce « mariage ». Si néanmoins cette dialectique se retrace dans la pensée de Berger dès ses premières œuvres, la défense d’une via media théologique appliquée à toutes les religions se révèle être la conséquence de l’abandon (dès 1967), de sa posture théologique néo-orthodoxe. Dans cette posture, la dialectique bergérienne s’appliquait à toutes les religions mais laissait la foi chrétienne intouchée et pensée en termes de certitude. Or, une analyse critique de sa pensée permet de situer au moins à trois niveaux un certain nombre de problèmes : le niveau de sa conception de la religion manifestant une ambiguïté; le niveau des rapports entre sociologie et théologie révélant un biais libéral et une absence de contenu religieux concret pour le principe protestant; enfin le niveau de sa critique des quêtes contemporaines de certitudes religieuses, critique dont le fondement sur sa dialectique peut être questionné par des exemples de conception différente de la religion et de la certitude religieuse. Pour ces trois niveaux, l’exemple de la conception de la certitude religieuse par les protestants évangéliques permet au moins une ébauche d’un tel questionnement. Cette conception, surtout dans son idée de l’« assurance du salut», se fonde, dans son approche surnaturelle de la certitude religieuse, sur une adhésion et une confiance fortes quant aux contenus traditionnels de la foi chrétienne. Si les arguments avancés dans cette perspective demeurent discutables, ils semblent assez pertinents puisque la vitalité contemporaine de la religion à l’ère du pluralisme religieux (voir notamment le protestantisme évangélique aux États-Unis) constitue une indication que la validité empirique de la dialectique bergérienne, et la critique qu’elle fonde, sont largement problématiques si l’on tient compte de l’auto-compréhension des groupes religieux eux-mêmes. / The dialectic religious pluralism/religious uncertainty, with which deals this dissertation, reveals itself as a major theme in Peter L. Berger’s thought, in sociology of religion and in protestant theology. A systematic and detailed analysis of the key concepts which constitute that dialectic leads to the question of the relationship between sociology and theology, which has been confronted by Berger himself. It is at the time Berger studied that question from the point of view of the idea of the protestant principle, during the late sixties, that he solved it by a kind of ‘wedding’ between his approach in the sociology of knowledge and his liberal theological approach. Concepts as ‘inductive faith and theology’, ‘middle position between fundamentalism and relativism’, seem to emerge both from that dialectic and from that ‘wedding’. Nevertheless, while that dialectic can be retraced in Berger’s thought since his earlier works, the defence of a theological via media applied to all religions, appears to be the consequence of his rejection (since 1967), of his earlier theological stance deployed from the neo-orthodox approach. In that stance, the bergerian dialectic was applied to all religions but not to the Christian faith, thought in terms of certainty. But, a critical analysis of Berger’s thought allows one to identify some problems at least at three levels: the level of his concept of religion which evidentiates an ambiguity ; the level of the relationship between sociology and theology which reveals a liberal bias and a lack of specific religious content for the protestant principle; and finally, the level of his critique of the contemporary religious certainty impulses; a critique whose base on his dialectic can be questioned by some examples of different conceptions of religion and of religious certainty. About those three levels, the example of the conception of religious certainty by the Evangelical Protestants allows at least a draft of that questioning. It deploys a supernatural conception of the religious certainty, especially by the notion of « assurance of salvation », based on strong adherence and confidence in the traditional contents of the Christian faith. While the arguments of that conception can be subjected to questions, they seem enough relevant since the contemporary vitality of religion at the pluralistic era (cf. Evangelical Protestantism in U.S.A for example) constitutes an indication that the empirical validity of the bergerian dialectic, and of the critique based on it, is largely problematic if one takes into account the self-understanding of the religious groups themselves.

In Canada’s recent history, the cases of Kanao Inouye, Omar Khadr, and Maher Arar shed light on the relationship between citizen-rights and sovereign power, a problem which this thesis studies through its three-pronged strategy of analysis. First, it takes a postmetaphysical approach to the problem of exceptionality as it has been explored in the works of Jacques Derrida, Gianni Vattimo, and Reiner Schürmann. Their responses to the problem of exceptionality provide a framework that enables this thesis to capture the relationship between citizen-rights and sovereign power in relative detail. Second, it applies Schürmann’s epochal theory in order to offer a historical periodization of citizen-rights in Canada that highlights the effect of sovereign power on citizen-rights. Lastly, in light of its philosophical and theoretical framework, it interprets the Inouye, Khadr, Arar cases in order to account for the effect of Charter rights on sovereign power. / Graduate / 0626 / tsujikt@gmail.com

The objective of this research is to develop and design front-end analog circuits for Capacitive Micromachined Ultrasound Transducers (CMUTs) and optical grating MEMS microphone. This work is motivated by the fact that with micro-scaling, MEMS sense capacitance gets smaller in a CMUT array element for intravascular ultrasound imaging, which has dimensions of 70um x 70um and sub pico-farad capacitance. Smaller sensors lead to a lower active-to-parasitic ratio and thus, degrads sensitivity. Area and power requirements are also very stringent, such as the case of intravascular catheter implementations with CMOS-First CMUT fabrication approach. In this implementation, capacitive feedback charge amplifier is an alternative approach to resistive feedback amplifiers. Capacitive feedback charge amplifier provides high sensitivity, small area, low distortion and saving power. This approach of charge amplifiers is also suitable in capacitive microphones where it provides low power and high sensitivity. Another approach to overcome capacitive detection challenges is to implement optical detection. In the case of biomimetic microphone structure, optical detection overcomes capacitive detection's thermal noise issues. Also with micro-scaling, optical detection overcomes the increased parasitics without any sensitivity degradation, unlike capacitive detection. For hearing aids, along with sensitivity, battery life is another challenge. We propose the use of 1-bit front-end sigma-delta ADC for overall improved hearing aid power efficiency. Front-end interface based on envelope detection and synchronous detection schemes have also been designed. These interface circuits consume currents in microampere range from a 1.5V battery. Circuit techniques are used for maximizing linear range and signal handling with low supplies. The entire front end signal processing with Vertical Cavity Surface Emitting Laser (VCSEL) drivers, photodiodes, filters and detectors is implemented on a single chip in 0.35um CMOS process.

This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.

Title: Incompressible fluids with temperature dependent visco- sity, numerical analysis and computational simulations Author: RNDr. Oldřich Ulrych Department: Mathematical Institute of Charles University Supervisor: prof. RNDr. Josef Málek, CSc., DSc. Abstract: Flows of incompressible fluids connected with significant exchange of ther- mal and mechanical energy and with material moduli varying with the temperature and the shear rate, are described by the balance equations for linear momentum and energy, complemented by suitable constitution equations for the Cauchy stress and the heat flux. Assuming sufficient smoothness of quantities involved, the energy balance equation exhibits several equivalent formulations. However, within the context of weak solution, these formulations are, in general, not equivalent. This thesis is based on the existence theory for the generalized Navier-Stokes-Fourier system describing planar flow of fluids with a shear and temperature dependent vis- cosity. We specify parameters of a generalized power-law model under which weak formulations of balance equations are meaningful and both considered formulations of the energy balance equation are equivalent. Supported by the existence theory, we propose and numerically solve several problems pursuing the aim to systematically compare the...

Testing Structural Changes Using Ratio Type Statistics Barbora Peštová Charles University in Prague, Faculty of Mathematics and Physics, Department of Probability and Mathematical Statistics, Czech Republic Abstract of the doctoral thesis We deal with sequences of observations that are naturally ordered in time and assume various underlying stochastic models. These models are parametric and some of the parameters are possibly subject to change at some unknown time point. The main goal of this thesis is to test whether such an unknown change has occurred or not. The core of the change point methods presented here is in ratio type statistics based on maxima of cumulative sums. Firstly, an overview of thesis' starting points is given. Then we focus on methods for detecting a gradual change in mean. Consequently, procedures for detection of an abrupt change in mean are generalized by considering a score function. We explore the possibility of applying the bootstrap methods for obtaining critical values, while disturbances of the change point model are considered as weakly dependent. Procedures for detection of changes in parameters of linear regression models are shown as well and a permutation version of the test is derived. Then, a related problem of testing a change in autoregression parameter is studied....