Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Aplicação da metodologia ROC na avaliação de desempenho de índices de gravidade clínica em unidades de neonatologia de Portugal

Tese de Doutoramento em Engenharia Industrial e de Sistemas

Pure elastic contact force models

"Series: Solid mechanics and its applications, vol. 226"

Contact force models for multibody dynamics

"Series: Solid mechanics and its applications, vol. 226"

Caracteritació de models funcionals d'àmfores romanes mitjançant Finite Element Analysis

Projecte de recerca elaborat a partir d’una estada al Laboratory of Archaeometry del National Centre of Scientific Research “Demokritos” d’Atenes, Grècia, entre juny i setembre 2006. Aquest estudi s’emmarca dins d’un context més ampli d’estudi del canvi tecnològic que es documenta en la producció d’àmfores de tipologia romana durant els segles I aC i I dC en els territoris costaners de Catalunya. Una part d’aquest estudi contempla el càlcul de les propietats mecàniques d’aquestes àmfores i la seva avaluació en funció de la tipologia amforal, a partir de l’Anàlisi d’Elements Finits (AEF). L’AEF és una aproximació numèrica que té el seu origen en les ciències d’enginyeria i que ha estat emprada per estimar el comportament mecànic d’un model en termes, per exemple, de deformació i estrès. Així, un objecte, o millor dit el seu model, es dividit en sub-dominis anomenats elements finits, als quals se’ls atribueixen les propietats mecàniques del material en estudi. Aquests elements finits estan connectats formant una xarxa amb constriccions que pot ser definida. En el cas d’aplicar una força determinada a un model, el comportament de l’objecte pot ser estimat mitjançant el conjunt d’equacions lineals que defineixen el rendiment dels elements finits, proporcionant una bona aproximació per a la descripció de la deformació estructural. Així, aquesta simulació per ordinador suposa una important eina per entendre la funcionalitat de ceràmiques arqueològiques. Aquest procediment representa un model quantitatiu per predir el trencament de l’objecte ceràmic quan aquest és sotmès a diferents condicions de pressió. Aquest model ha estat aplicat a diferents tipologies amforals. Els resultats preliminars mostren diferències significatives entre la tipologia pre-romana i les tipologies romanes, així com entre els mateixos dissenys amforals romans, d’importants implicacions arqueològiques.

Predicting trabecular bone microdamage initiation and accumulation using a non-linear perfect damage model

Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Evaluation of cumulative PCB exposure estimated by a job exposure matrix versus PCB serum concentrations.

Although polychlorinated biphenyls (PCBs) have been banned in many countries for more than three decades, exposures to PCBs continue to be of concern due to their long half-lives and carcinogenic effects. In National Institute for Occupational Safety and Health studies, we are using semiquantitative plant-specific job exposure matrices (JEMs) to estimate historical PCB exposures for workers (n = 24,865) exposed to PCBs from 1938 to 1978 at three capacitor manufacturing plants. A subcohort of these workers (n = 410) employed in two of these plants had serum PCB concentrations measured at up to four times between 1976 and 1989. Our objectives were to evaluate the strength of association between an individual worker's measured serum PCB levels and the same worker's cumulative exposure estimated through 1977 with the (1) JEM and (2) duration of employment, and to calculate the explained variance the JEM provides for serum PCB levels using (3) simple linear regression. Consistent strong and statistically significant associations were observed between the cumulative exposures estimated with the JEM and serum PCB concentrations for all years. The strength of association between duration of employment and serum PCBs was good for highly chlorinated (Aroclor 1254/HPCB) but not less chlorinated (Aroclor 1242/LPCB) PCBs. In the simple regression models, cumulative occupational exposure estimated using the JEMs explained 14-24% of the variance of the Aroclor 1242/LPCB and 22-39% for Aroclor 1254/HPCB serum concentrations. We regard the cumulative exposure estimated with the JEM as a better estimate of PCB body burdens than serum concentrations quantified as Aroclor 1242/LPCB and Aroclor 1254/HPCB.

Towards the validation of "in silico" models and physicochemical filters to identify and characterize new chemical entities

Summary: Lipophilicity plays an important role in the determination and the comprehension of the pharmacokinetic behavior of drugs. It is usually expressed by the partition coefficient (log P) in the n-octanol/water system. The use of an additional solvent system (1,2-dichlorethane/water) is necessary to obtain complementary information, as the log Poct values alone are not sufficient to explain ail biological properties. The aim of this thesis is to develop tools allowing to predict lipophilicity of new drugs and to analyze the information yielded by those log P values. Part I presents the development of theoretical models used to predict lipophilicity. Chapter 2 shows the necessity to extend the existing solvatochromic analyses in order to predict correctly the lipophilicity of new and complex neutral compounds. In Chapter 3, solvatochromic analyses are used to develop a model for the prediction of the lipophilicity of ions. A global model was obtained allowing to estimate the lipophilicity of neutral, anionic and cationic solutes. Part II presents the detailed study of two physicochemical filters. Chapter 4 shows that the Discovery RP Amide C16 stationary phase allows to estimate lipophilicity of the neutral form of basic and acidic solutes, except of lipophilic acidic solutes. Those solutes present additional interactions with this particular stationary phase. In Chapter 5, 4 different IANI stationary phases are investigated. For neutral solutes, linear data are obtained whatever the IANI column used. For the ionized solutes, their retention is due to a balance of electrostatic and hydrophobie interactions. Thus no discrimination is observed between different series of solutes bearing the same charge, from one column to an other. Part III presents two examples illustrating the information obtained thanks to Structure-Properties Relationships (SPR). Comparing graphically lipophilicity values obtained in two different solvent systems allows to reveal the presence of intramolecular effects .such as internai H-bond (Chapter 6). SPR is used to study the partitioning of ionizable groups encountered in Medicinal Chemistry (Chapter7). Résumé La lipophilie joue un .rôle important dans la détermination et la compréhension du comportement pharmacocinétique des médicaments. Elle est généralement exprimée par le coefficient de partage (log P) d'un composé dans le système de solvants n-octanol/eau. L'utilisation d'un deuxième système de solvants (1,2-dichloroéthane/eau) s'est avérée nécessaire afin d'obtenir des informations complémentaires, les valeurs de log Poct seules n'étant pas suffisantes pour expliquer toutes les propriétés biologiques. Le but de cette thèse est de développer des outils permettant de prédire la lipophilie de nouveaux candidats médicaments et d'analyser l'information fournie par les valeurs de log P. La Partie I présente le développement de modèles théoriques utilisés pour prédire la lipophilie. Le chapitre 2 montre la nécessité de mettre à jour les analyses solvatochromiques existantes mais inadaptées à la prédiction de la lipophilie de nouveaux composés neutres. Dans le chapitre 3, la même méthodologie des analyses solvatochromiques est utilisée pour développer un modèle permettant de prédire la lipophilie des ions. Le modèle global obtenu permet la prédiction de la lipophilie de composés neutres, anioniques et cationiques. La Partie II présente l'étude approfondie de deux filtres physicochimiques. Le Chapitre 4 montre que la phase stationnaire Discovery RP Amide C16 permet la détermination de la lipophilie de la forme neutre de composés basiques et acides, à l'exception des acides très lipophiles. Ces derniers présentent des interactions supplémentaires avec cette phase stationnaire. Dans le Chapitre 5, 4 phases stationnaires IAM sont étudiées. Pour les composés neutres étudiés, des valeurs de rétention linéaires sont obtenues, quelque que soit la colonne IAM utilisée. Pour les composés ionisables, leur rétention est due à une balance entre des interactions électrostatiques et hydrophobes. Donc aucune discrimination n'est observée entre les différentes séries de composés portant la même charge d'une colonne à l'autre. La Partie III présente deux exemples illustrant les informations obtenues par l'utilisation des relations structures-propriétés. Comparer graphiquement la lipophilie mesurée dans deux différents systèmes de solvants permet de mettre en évidence la présence d'effets intramoléculaires tels que les liaisons hydrogène intramoléculaires (Chapitre 6). Cette approche des relations structures-propriétés est aussi appliquée à l'étude du partage de fonctions ionisables rencontrées en Chimie Thérapeutique (Chapitre 7) Résumé large public Pour exercer son effet thérapeutique, un médicament doit atteindre son site d'action en quantité suffisante. La quantité effective de médicament atteignant le site d'action dépend du nombre d'interactions entre le médicament et de nombreux constituants de l'organisme comme, par exemple, les enzymes du métabolisme ou les membranes biologiques. Le passage du médicament à travers ces membranes, appelé perméation, est un paramètre important à optimiser pour développer des médicaments plus puissants. La lipophilie joue un rôle clé dans la compréhension de la perméation passive des médicaments. La lipophilie est généralement exprimée par le coefficient de partage (log P) dans le système de solvants (non miscibles) n-octanol/eau. Les valeurs de log Poct seules se sont avérées insuffisantes pour expliquer la perméation à travers toutes les différentes membranes biologiques du corps humain. L'utilisation d'un système de solvants additionnel (le système 1,2-dichloroéthane/eau) a permis d'obtenir les informations complémentaires indispensables à une bonne compréhension du processus de perméation. Un grand nombre d'outils expérimentaux et théoriques sont à disposition pour étudier la lipophilie. Ce travail de thèse se focalise principalement sur le développement ou l'amélioration de certains de ces outils pour permettre leur application à un champ plus large de composés. Voici une brève description de deux de ces outils: 1)La factorisation de la lipophilie en fonction de certaines propriétés structurelles (telle que le volume) propres aux composés permet de développer des modèles théoriques utilisables pour la prédiction de la lipophilie de nouveaux composés ou médicaments. Cette approche est appliquée à l'analyse de la lipophilie de composés neutres ainsi qu'à la lipophilie de composés chargés. 2)La chromatographie liquide à haute pression sur phase inverse (RP-HPLC) est une méthode couramment utilisée pour la détermination expérimentale des valeurs de log Poct.

L'aprenentatge basat en problemes en models híbrids de docència-aprenentatge

La Facultat de Ciències de la Salut i de la Vida ha utilitzat des de 2004 la metodologia d'aprenentatge basat en problemes (en endavant ABP) com a mètode docent en els seus estudis de Biologia. En aquest període hem après algunes de les claus de l'aplicació del mètode en els nostres estudis. En primer lloc, cal disposar d'elements formatius que afavoreixin la formació dels tutors que participin en el projecte. Per assolir aquest objectiu hem dissenyat un portal on els nostres professors poden disposar de materials útils per a la seva activitat, així com de documents que permetin entendre millor el que suposa l'ABP. En segon lloc, el projecte tenia l'objectiu de dissenyar i avaluar activitats que permetessin integrar les pràctiques de laboratori en la lògica de la resolució de problemes pròpia de l'ABP. En aquest sentit vam dissenyar dues activitats en el tercer curs de la llicenciatura que anomenaren aprenentatge basat en el laboratori (ABL). Per aquest motiu es van dissenyar problemes que tinguessin una primera part de resolució a l'aula en grup de tutoria i una segona que obligués els estudiants a realitzar experiments de laboratori dirigits a entendre i resoldre les qüestions plantejades al grup de tutoria. L'ABL-1 fou un projecte de biologia cel·lular i destinat a aprofundir en els mecanismes implicats en els fenòmens de diferenciació dels miòcits. L'ABL-2 era un projecte conjunt dels professors de Fisiologia vegetal, Bioestadística i Microbiologia. En aquest cas es desitjava que els estudiants plantegessin la resolució a un problema que suposava la manipulació genètica de cèl·lules vegetals per fer possible que produïssin una substància específica, l'escopolamina. Finalment els estudiants havien d'escriure un article original com a projecte final de cada ABL. Els resultats dels dos anys d'experimentació han esta altament satisfactoris, d'acord amb les enquestes completades per alumnes i professors.

Analysis of nonlinear noisy integrate & fire neuron models: blow-up and steady states

Nonlinear Noisy Leaky Integrate and Fire (NNLIF) models for neurons networks can be written as Fokker-Planck-Kolmogorov equations on the probability density of neurons, the main parameters in the model being the connectivity of the network and the noise. We analyse several aspects of the NNLIF model: the number of steady states, a priori estimates, blow-up issues and convergence toward equilibrium in the linear case. In particular, for excitatory networks, blow-up always occurs for initial data concentrated close to the firing potential. These results show how critical is the balance between noise and excitatory/inhibitory interactions to the connectivity parameter.

Linear Aggregation In The Social Accounting Matrix Framework

In economic literature, information deficiencies and computational complexities have traditionally been solved through the aggregation of agents and institutions. In inputoutput modelling, researchers have been interested in the aggregation problem since the beginning of 1950s. Extending the conventional input-output aggregation approach to the social accounting matrix (SAM) models may help to identify the effects caused by the information problems and data deficiencies that usually appear in the SAM framework. This paper develops the theory of aggregation and applies it to the social accounting matrix model of multipliers. First, we define the concept of linear aggregation in a SAM database context. Second, we define the aggregated partitioned matrices of multipliers which are characteristic of the SAM approach. Third, we extend the analysis to other related concepts, such as aggregation bias and consistency in aggregation. Finally, we provide an illustrative example that shows the effects of aggregating a social accounting matrix model.

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Hierarchical conditional random fields for parts based models matching

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

Symmetry-breaking in cumulative measures of shapes of polymer models.

Using numerical simulations we investigate shapes of random equilateral open and closed chains, one of the simplest models of freely fluctuating polymers in a solution. We are interested in the 3D density distribution of the modeled polymers where the polymers have been aligned with respect to their three principal axes of inertia. This type of approach was pioneered by Theodorou and Suter in 1985. While individual configurations of the modeled polymers are almost always nonsymmetric, the approach of Theodorou and Suter results in cumulative shapes that are highly symmetric. By taking advantage of asymmetries within the individual configurations, we modify the procedure of aligning independent configurations in a way that shows their asymmetry. This approach reveals, for example, that the 3D density distribution for linear polymers has a bean shape predicted theoretically by Kuhn. The symmetry-breaking approach reveals complementary information to the traditional, symmetrical, 3D density distributions originally introduced by Theodorou and Suter.