Análise histoquímica e molecular comparada do fluido espermatecal e da secreção das glândulas espermatecais das fêmeas e das glândulas de muco dos machos em três espécies de abelhas com diferentes níveis de sociabilidade

Pós-graduação em Ciências Biológicas (Biologia Celular e Molecular) - IBRC

Análise Bayesiana para a distribuição Exponencial-Logarítmica

Pós-graduação em Matematica Aplicada e Computacional - FCT

Predicados matrizes adjetivais de orações subjetivas no Português brasileiro: gramaticalização e dessentencialização

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimação Bayesiana dos parâmetros da distribuição Exponencial Generalizada Bivariada

Pós-graduação em Matematica Aplicada e Computacional - FCT

Bayesian inference for two-parameter gamma distribution assuming different noninformative priors

In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.

Differential calculus and integration of generalized functions over membranes

In this paper we continue the development of the differential calculus started in Aragona et al. (Monatsh. Math. 144: 13-29, 2005). Guided by the so-called sharp topology and the interpretation of Colombeau generalized functions as point functions on generalized point sets, we introduce the notion of membranes and extend the definition of integrals, given in Aragona et al. (Monatsh. Math. 144: 13-29, 2005), to integrals defined on membranes. We use this to prove a generalized version of the Cauchy formula and to obtain the Goursat Theorem for generalized holomorphic functions. A number of results from classical differential and integral calculus, like the inverse and implicit function theorems and Green's theorem, are transferred to the generalized setting. Further, we indicate that solution formulas for transport and wave equations with generalized initial data can be obtained as well.

Bestimmung der spektralen Empfindlichkeit eines Bewegungsdetektors auf der Basis von Zapfenerregungen beim Menschen

Die Detektion von Bewegung stellt eine der fundamentalsten Fähigkeiten der visuellen Wahrnehmung dar. Um zu klären, ob das System zur Bewegungswahrnehmung Eingang nur durch einen Zapfentyp erhält, oder ob eine Kombination von verschiedenen Zapfentypen vorliegt, wurde eine rotierende zwei-armige archimedische Spiralscheibe verwendet (reale Bewegung), bei der sich Spirale und Hintergrund farblich unterschieden. Durch Veränderung der Intensität farbiger Leuchtstoffröhren konnte eine Beleuchtungssituation geschaffen werden, bei der die (radiale) Bewegung der Spirale nicht mehr wahrgenommen werden konnte, obwohl Spirale und Hintergrund farblich verschieden waren. Die Bestimmung der Zapfenerregungen im 3-D Rezeptorraum ließ einen Beitrag sowohl des L– als auch des M-Zapfens bei normalsichtigen Trichromaten (dominiert durch L), jedoch einen alleinigen Beitrag des M-Zapfens bei Protanopen erkennen. Die Ermittlung der spektralen Empfindlichkeit basierend auf einer Vektor Analyse im 3D-Rezeptorraum zeigte schließlich, dass dem neuronalen Bewegungsdetektor ein additiver Beitrag des L- und M-Zapfens, in Übereinstimmung mit der Hellempfindlichkeitsfunktion (Vλ), zugrunde liegt. Als Ergebnis schreiben wir die Detektion von Objektbewegung einem farbenblinden Mechanismus zu. Es ist sehr wahrscheinlich, dass der Magnozelluläre-Kanal das neuronale Substrat dieses Bewegungsdetektors repräsentiert.

Semiparametric Methods for Semi-competing Risks Problem with Censoring and Truncation

Studies of chronic life-threatening diseases often involve both mortality and morbidity. In observational studies, the data may also be subject to administrative left truncation and right censoring. Since mortality and morbidity may be correlated and mortality may censor morbidity, the Lynden-Bell estimator for left truncated and right censored data may be biased for estimating the marginal survival function of the non-terminal event. We propose a semiparametric estimator for this survival function based on a joint model for the two time-to-event variables, which utilizes the gamma frailty specification in the region of the observable data. Firstly, we develop a novel estimator for the gamma frailty parameter under left truncation. Using this estimator, we then derive a closed form estimator for the marginal distribution of the non-terminal event. The large sample properties of the estimators are established via asymptotic theory. The methodology performs well with moderate sample sizes, both in simulations and in an analysis of data from a diabetes registry.

MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Analyzing Bivariate Survival Data with Interval Sampling and Application to Cancer Epidemiology

In medical follow-up studies, ordered bivariate survival data are frequently encountered when bivariate failure events are used as the outcomes to identify the progression of a disease. In cancer studies interest could be focused on bivariate failure times, for example, time from birth to cancer onset and time from cancer onset to death. This paper considers a sampling scheme where the first failure event (cancer onset) is identified within a calendar time interval, the time of the initiating event (birth) can be retrospectively confirmed, and the occurrence of the second event (death) is observed sub ject to right censoring. To analyze this type of bivariate failure time data, it is important to recognize the presence of bias arising due to interval sampling. In this paper, nonparametric and semiparametric methods are developed to analyze the bivariate survival data with interval sampling under stationary and semi-stationary conditions. Numerical studies demonstrate the proposed estimating approaches perform well with practical sample sizes in different simulated models. We apply the proposed methods to SEER ovarian cancer registry data for illustration of the methods and theory.

Empirical Analysis of Credit Risk Regime Switching and Temporal Conditional Default Correlation in Credit Default Swap Valuation: The Market liquidity effect

In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.

Diatom biostratigraphy of sediments from the Kerguelen Plateau, Southern Ocean

The biostratigraphic distribution and abundance of lower Oligocene to Pleistocene diatoms is documented from Holes 747A, 747B, 748B, 749B, and 751A drilled during Ocean Drilling Program Leg 120 on the Kerguelen Plateau in the southeast Indian Ocean. The occurrence of middle and upper Eocene diatoms is also documented, but these are rare and occur in discrete intervals. The recovery of several Oligocene to Pleistocene sections with minimal coring gaps, relatively good magnetostratigraphic signatures, and mixed assemblages of both calcareous and siliceous microfossils makes the above four Leg 120 sites important biostratigraphic reference sections for the Southern Ocean and Antarctic continent. A high-resolution diatom zonation divides the last 36 m.y. into 45 zones and subzones. This zonation is built upon an existing biostratigraphic framework developed over the past 20 yr of Southern Ocean/Antarctic deep-sea coring and drilling. After the recent advances from diatom biostratigraphic studies on sediments from Legs 113, 114, 119, and 120, a zonal framework for the Southern Ocean is beginning to stabilize. The potential age resolution afforded by the high-diversity diatom assemblages in this region ranks among the highest of all fossil groups. In addition to the 46 datum levels that define the diatom zones and subzones, the approximate stratigraphic level, age, and magnetic anomaly correlative of more than 150 other diatom datums are determined or estimated. These total 73 datum levels for the Pliocene-Pleistocene, 67 for the Miocene, and 45 for the Oligocene. Greater stratigraphic resolution is possible as the less common and poorly documented species become better known. This high-resolution diatom stratigraphy, combined with good to moderately good magnetostratigraphic control, led to the recognition of more than 10 intervals where hiatuses dissect the Oligocene-Pleistocene section on the Kerguelen Plateau. We propose 12 new diatom taxa and 6 new combination

Contribución al estudio de dos conceptos básicos de la lógica fuzzy

La tesis doctoral CONTRIBUCIÓN AL ESTUDIO DE DOS CONCEPTOS BÁSICOS DE LA LÓGICA FUZZY constituye un conjunto de nuevas aportaciones al análisis de dos elementos básicos de la lógica fuzzy: los mecanismos de inferencia y la representación de predicados vagos. La memoria se encuentra dividida en dos partes que corresponden a los dos aspectos señalados. En la Parte I se estudia el concepto básico de «estado lógico borroso». Un estado lógico borroso es un punto fijo de la aplicación generada a partir de la regla de inferencia conocida como modus ponens generalizado. Además, un preorden borroso puede ser representado mediante los preórdenes elementales generados por el conjunto de sus estados lógicos borrosos. El Capítulo 1 está dedicado a caracterizar cuándo dos estados lógicos dan lugar al mismo preorden elemental, obteniéndose también un representante de la clase de todos los estados lógicos que generan el mismo preorden elemental. El Capítulo finaliza con la caracterización del conjunto de estados lógicos borrosos de un preorden elemental. En el Capítulo 2 se obtiene un subconjunto borroso trapezoidal como una clase de una relación de indistinguibilidad. Finalmente, el Capítulo 3 se dedica a estudiar dos tipos de estados lógicos clásicos: los irreducibles y los minimales. En el Capítulo 4, que inicia la Parte II de la memoria, se aborda el problema de obtener la función de compatibilidad de un predicado vago. Se propone un método, basado en el conocimiento del uso del predicado mediante un conjunto de reglas y de ciertos elementos distinguidos, que permite obtener una expresión general de la función de pertenencia generalizada de un subconjunto borroso que realice la función de extensión del predicado borroso. Dicho método permite, en ciertos casos, definir un conjunto de conectivas multivaluadas asociadas al predicado. En el último capítulo se estudia la representación de antónimos y sinónimos en lógica fuzzy a través de auto-morfismos. Se caracterizan los automorfismos sobre el intervalo unidad cuando sobre él se consideran dos operaciones: una t-norma y una t-conorma ambas arquimedianas. The PhD Thesis CONTRIBUCIÓN AL ESTUDIO DE DOS CONCEPTOS BÁSICOS DE LA LÓGICA FUZZY is a contribution to two basic concepts of the Fuzzy Logic. It is divided in two parts, the first is devoted to a mechanism of inference in Fuzzy Logic, and the second to the representation of vague predicates. «Fuzzy Logic State» is the basic concept in Part I. A Fuzzy Logic State is a fixed-point for the mapping giving the Generalized Modus Ponens Rule of inference. Moreover, a fuzzy preordering can be represented by the elementary preorderings generated by its Fuzzy Logic States. Chapter 1 contemplates the identity of elementary preorderings and the selection of representatives for the classes modulo this identity. This chapter finishes with the characterization of the set of Fuzzy Logic States of an elementary preordering. In Chapter 2 a Trapezoidal Fuzzy Set as a class of a relation of Indistinguishability is obtained. Finally, Chapter 3 is devoted to study two types of Classical Logic States: irreducible and minimal. Part II begins with Chapter 4 dealing with the problem of obtaining a Compa¬tibility Function for a vague predicate. When the use of a predicate is known by means of a set of rules and some distinguished elements, a method to obtain the general expression of the Membership Function is presented. This method allows, in some cases, to reach a set of multivalued connectives associated to the predicate. Last Chapter is devoted to the representation of antonyms and synonyms in Fuzzy Logic. When the unit interval [0,1] is endowed with both an archimedean t-norm and a an archi-medean t-conorm, it is showed that the automorphisms' group is just reduced to the identity function.

Geometric diagnostics of complex patterns: Spiral defect chaos

Motivated by the observation of spiral patterns in a wide range of physical, chemical, and biological systems, we present an automated approach that aims at characterizing quantitatively spiral-like elements in complex stripelike patterns. The approach provides the location of the spiral tip and the size of the spiral arms in terms of their arc length and their winding number. In addition, it yields the number of pattern components (Betti number of order 1), as well as their size and certain aspects of their shape. We apply the method to spiral defect chaos in thermally driven Rayleigh- Bénard convection and find that the arc length of spirals decreases monotonically with decreasing Prandtl number of the fluid and increasing heating. By contrast, the winding number of the spirals is nonmonotonic in the heating. The distribution function for the number of spirals is significantly narrower than a Poisson distribution. The distribution function for the winding number shows approximately an exponential decay. It depends only weakly on the heating, but strongly on the Prandtl number. Large spirals arise only for larger Prandtl numbers. In this regime the joint distribution for the spiral length and the winding number exhibits a three-peak structure, indicating the dominance of Archimedean spirals of opposite sign and relatively straight sections. For small Prandtl numbers the distribution function reveals a large number of small compact pattern components.