Factorization and criticality in the anisotropic XY chain via correlations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

How population loss through habitat boundaries determines the dynamics of a predator-prey system

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

Effects of β-(1→3,1→6)-d-glucan and density of diets on the blood profiles of immunologically challenged weaned piglets

An experiment was conducted to evaluate the effects of two levels of the β-(1→3,1→6)-d-glucan (0 and 500ppm) from yeast Saccharomyces cerevisiae and two levels of energy (3300 and 3450kcalMEkg(-1)) on the hematological, immunological and, biochemical profiles of thirty-six 21-days-old weaned piglets, challenged with 150μgkg(-1) of BW lipopolysaccharide (LPS) from Escherichia coli serotype 055:B5. The experimental design was a randomized complete block design in a 2×2 factorial arrangement with nine replicates per treatment and, one animal per experimental unit. The data were analyzed in accordance with the multivariate analysis procedure of SAS and, the treatment means of parametric and non-parametric data were compared by Bonferroni's test (P<0.05) and, by Dunn's test (P<0.05), respectively. The data of the blood profiles of alanine aminotransferase, alkaline phosphatase and, creatinine showed that LPS did not cause kidney or liver damage in the animals. The addition of beta-glucan in the diets did not prove the robustness of its effect and biological relevance when provided with low nutrient-density. However, its addition combined with the high-nutrient-density diets showed less marked hypoglobulinemia in piglets, which may have contributed to the decreasing of the synthesis of inflammatory mediators.

Effect of avocado/soybean unsaponifiables on ligature-induced bone loss and bone repair after ligature removal in rats

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

Influência da suplementação de tomate e licopeno na remodelação cardíaca após infarto agudo do miocárdio

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Limites dinâmicos para operadores de Schrödinger com potenciais Sturmianos

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

Artificial neural networks applied to bandsawing process control

In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.

Nível de atividade física, estado nutricional e níveis de BACE 1 e BACE 2 em idosos neurologicamente saudáveis e com doença de Alzheimer

Pós-graduação em Ciências da Motricidade - IBRC

Designing Software Product Lines for Testability

Software product line (SPL) engineering offers several advantages in the development of families of software products such as reduced costs, high quality and a short time to market. A software product line is a set of software intensive systems, each of which shares a common core set of functionalities, but also differs from the other products through customization tailored to fit the needs of individual groups of customers. The differences between products within the family are well-understood and organized into a feature model that represents the variability of the SPL. Products can then be built by generating and composing features described in the feature model. Testing of software product lines has become a bottleneck in the SPL development lifecycle, since many of the techniques used in their testing have been borrowed from traditional software testing and do not directly take advantage of the similarities between products. This limits the overall gains that can be achieved in SPL engineering. Recent work proposed by both industry and the research community for improving SPL testing has begun to consider this problem, but there is still a need for better testing techniques that are tailored to SPL development. In this thesis, I make two primary contributions to software product line testing. First I propose a new definition for testability of SPLs that is based on the ability to re-use test cases between products without a loss of fault detection effectiveness. I build on this idea to identify elements of the feature model that contribute positively and/or negatively towards SPL testability. Second, I provide a graph based testing approach called the FIG Basis Path method that selects products and features for testing based on a feature dependency graph. This method should increase our ability to re-use results of test cases across successive products in the family and reduce testing effort. I report the results of a case study involving several non-trivial SPLs and show that for these objects, the FIG Basis Path method is as effective as testing all products, but requires us to test no more than 24% of the products in the SPL.

A comparison of time-motion performance between age groups in judo matches

The aim of this study was to compare time-motion indicators during judo matches performed by athletes from different age groups. The following age groups were analysed: Pre-Juvenile (13-14 years, n=522), Juvenile (15-16 years, n 353); Junior (19 years, n = 349) and Senior (>20 years, n = 587). The time-motion indicators included: Total Combat Time, Standing Combat Time, Displacement Without Contact, Gripping Time, Groundwork Combat Time and Pause Time. Analysis of variance (ANOVA) one-way and the Tukey test, as well as the Kruskal-Wallis test and Mann-Whitney (for non-parametric data), were conducted, using P < 0.05 as significance level. The results showed that all analysed groups obtained a median of 7 (first quantile - 3, third quantile - 12) sequences of combat/pause cycles. In total time of combat, the result was: for Total Combat Time, Standing Combat Time and Gripping Time: Pre-Juvenile and Senior were significantly longer than Juvenile and Junior. Considering Displacement Without Contact, Junior was significantly longer than all other age groups. For Groundwork Combat Time, Senior was significantly longer than all other age groups and Pre-Juvenile was longer than Junior. These results can be used to improve the physiological performance in intermittent practices, as well as technicaltactical training during judo sessions.

Local symmetries in gauge theories in a finite-dimensional setting

It is shown that the correct mathematical implementation of symmetry in the geometric formulation of classical field theory leads naturally beyond the concept of Lie groups and their actions on manifolds, out into the realm of Lie group bundles and, more generally, of Lie groupoids and their actions on fiber bundles. This applies not only to local symmetries, which lie at the heart of gauge theories, but is already true even for global symmetries when one allows for fields that are sections of bundles with (possibly) non-trivial topology or, even when these are topologically trivial, in the absence of a preferred trivialization. (C) 2012 Elsevier B.V. All rights reserved.

How far is C-0(Gamma, X) with Gamma discrete from C-0(K, X) spaces?

For a locally compact Hausdorff space K and a Banach space X we denote by C-0(K, X) the space of X-valued continuous functions on K which vanish at infinity, provided with the supremum norm. Let n be a positive integer, Gamma an infinite set with the discrete topology, and X a Banach space having non-trivial cotype. We first prove that if the nth derived set of K is not empty, then the Banach-Mazur distance between C-0(Gamma, X) and C-0(K, X) is greater than or equal to 2n + 1. We also show that the Banach-Mazur distance between C-0(N, X) and C([1, omega(n)k], X) is exactly 2n + 1, for any positive integers n and k. These results extend and provide a vector-valued version of some 1970 Cambern theorems, concerning the cases where n = 1 and X is the scalar field.

On delta-derivations of n-ary algebras

We give a description of delta-derivations of (n + 1)-dimensional n-ary Filippov algebras and, as a consequence, of simple finite-dimensional Filippov algebras over an algebraically closed field of characteristic zero. We also give new examples of non-trivial delta-derivations of Filippov algebras and show that there are no non-trivial delta-derivations of the simple ternary Mal'tsev algebra M-8.

Dynamical changes from harmonic vibrations of a limited power supply driving a Duffing oscillator

The harmonic oscillations of a Duffing oscillator driven by a limited power supply are investigated as a function of the alternative strength of the rotor. The semi-trivial and non-trivial solutions are derived. We examine the stability of these solutions and then explore the complex behaviors associated with the bifurcations sequences. Interestingly, a 3D diagram provides a global view of the effects of alternate strength on the appearance of chaos and hyperchaos on the system.

Essays on Bayesian Inference for Social Networks

This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time. A social network is conceived as being a structure consisting of actors and their social interaction with each other. A common conceptualisation of social networks is to let the actors be represented by nodes in a graph with edges between pairs of nodes that are relationally tied to each other according to some definition. Statistical analysis of social networks is to a large extent concerned with modelling of these relational ties, which lends itself to empirical evaluation. The first paper deals with a family of statistical models for social networks called exponential random graphs that takes various structural features of the network into account. In general, the likelihood functions of exponential random graphs are only known up to a constant of proportionality. A procedure for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods is presented. The algorithm consists of two basic steps, one in which an ordinary Metropolis-Hastings up-dating step is used, and another in which an importance sampling scheme is used to calculate the acceptance probability of the Metropolis-Hastings step. In paper number two a method for modelling reports given by actors (or other informants) on their social interaction with others is investigated in a Bayesian framework. The model contains two basic ingredients: the unknown network structure and functions that link this unknown network structure to the reports given by the actors. These functions take the form of probit link functions. An intrinsic problem is that the model is not identified, meaning that there are combinations of values on the unknown structure and the parameters in the probit link functions that are observationally equivalent. Instead of using restrictions for achieving identification, it is proposed that the different observationally equivalent combinations of parameters and unknown structure be investigated a posteriori. Estimation of parameters is carried out using Gibbs sampling with a switching devise that enables transitions between posterior modal regions. The main goal of the procedures is to provide tools for comparisons of different model specifications. Papers 3 and 4, propose Bayesian methods for longitudinal social networks. The premise of the models investigated is that overall change in social networks occurs as a consequence of sequences of incremental changes. Models for the evolution of social networks using continuos-time Markov chains are meant to capture these dynamics. Paper 3 presents an MCMC algorithm for exploring the posteriors of parameters for such Markov chains. More specifically, the unobserved evolution of the network in-between observations is explicitly modelled thereby avoiding the need to deal with explicit formulas for the transition probabilities. This enables likelihood based parameter inference in a wider class of network evolution models than has been available before. Paper 4 builds on the proposed inference procedure of Paper 3 and demonstrates how to perform model selection for a class of network evolution models.