Trends in properties of para-substituted 3-(phenylhydrazo)pentane-2,4-diones

Trends between the Hammett's sigma(p) and related normal sigma(n)(p), inductive sigma(I), resonance sigma(R), negative sigma(-)(p) and positive sigma(+)(p) polar conjugation and Taft's sigma(o)(p) substituent constants and the N-H center dot center dot center dot O distance, delta(N-H) NMR chemical shift, oxidation potential (E-p/2(ox), measured in this study by cyclic voltammetry (CV)) and thermodynamic parameters (pK, Delta G(0), Delta H-0 and Delta S-0) of the dissociation process of unsubstituted 3-(phenylhydrazo)pentane-2,4-dione (HL1) and its para-substituted chloro (HL2), carboxy (HL3), fluoro (HL4) and nitro (HL5) derivatives were recognized. The best fits were found for sigma(p) and/or sigma(-)(p) in the cases of d(N center dot center dot center dot O), delta(N-H) and E-p/2(ox), showing the importance of resonance and conjugation effects in such properties, whereas for the above thermodynamic properties the inductive effects (sigma(I)) are dominant. HL2 exists in the hydrazo form in DMSO solution and in the solid state and contains an intramolecular H-bond with the N center dot center dot center dot O distance of 2.588(3)angstrom. It was also established that the dissociation process of HL1-5 is non-spontaneous, endothermic and entropically unfavourable, and that the increase in the inductive effect (sigma(I)) of para-substitutents (-H < -Cl < -COOH < -F < -NO2) leads to the corresponding growth of the N center dot center dot center dot O distance and decrease of the pK and of the changes of Gibbs free energy, of enthalpy and of entropy for the HL1-5 acid dissociation process. The electrochemical behaviour of HL1-5 was interpreted using theoretical calculations at the DFT/HF hybrid level, namely in terms of HOMO and LUMO compositions, and of reactivities induced by anodic and cathodic electron-transfers. Copyright (C) 2010 John Wiley & Sons, Ltd.

Dynamical analysis in growth models: Blumberg’s equation

We present a new dynamical approach to the Blumberg's equation, a family of unimodal maps. These maps are proportional to Beta(p, q) probability densities functions. Using the symmetry of the Beta(p, q) distribution and symbolic dynamics techniques, a new concept of mirror symmetry is defined for this family of maps. The kneading theory is used to analyze the effect of such symmetry in the presented models. The main result proves that two mirror symmetric unimodal maps have the same topological entropy. Different population dynamics regimes are identified, when the intrinsic growth rate is modified: extinctions, stabilities, bifurcations, chaos and Allee effect. To illustrate our results, we present a numerical analysis, where are demonstrated: monotonicity of the topological entropy with the variation of the intrinsic growth rate, existence of isentropic sets in the parameters space and mirror symmetry.

An Extension of Gompertzian Growth Dynamics Weibull and Frechet Models

In this work a new probabilistic and dynamical approach to an extension of the Gompertz law is proposed. A generalized family of probability density functions, designated by Beta* (p, q), which is proportional to the right hand side of the Tsoularis-Wallace model, is studied. In particular, for p = 2, the investigation is extended to the extreme value models of Weibull and Frechet type. These models, described by differential equations, are proportional to the hyper-Gompertz growth model. It is proved that the Beta* (2, q) densities are a power of betas mixture, and that its dynamics are determined by a non-linear coupling of probabilities. The dynamical analysis is performed using techniques of symbolic dynamics and the system complexity is measured using topological entropy. Generally, the natural history of a malignant tumour is reflected through bifurcation diagrams, in which are identified regions of regression, stability, bifurcation, chaos and terminus.

Copper(II) aza-bis(oxazoline) complex immobilized onto ITQ-2 and MCM-22 based materials as heterogeneous catalysts for the cyclopropanation of styrene

A copper(II) chiral aza-bis(oxazoline) homogeneous catalyst (CuazaBox) was anchored onto the external surface of MCM-22 and ITQ-2 structures, as well as encapsulated into hierarchical MCM-22. The transition metal complex loading onto the porous solids was determined by ICP-AES and the materials were also characterized by elemental analysis (C, N, H, S), FTIR, XPS, TG and low temperature N-2 adsorption isotherms. The materials were tested as heterogeneous catalysts in the benchmark reaction of cyclopropanation of styrene to check the effect of the immobilization procedure on the catalytic parameters, as well as on their reutilization in several catalytic cycles. Catalyst CuazaBox anchored onto the external surface of MCM-22 and ITQ-2 materials were more active and enantioselective in the cyclopropanation of styrene than the corresponding homogeneous phase reaction run under similar experimental conditions. This is due to the propylation of the acidic aza-Box nitrogen. HMCM-22 was nevertheless the best heterogeneous catalyst. Encapsulation of CuazaBox on post-synthesis modified MCM-22 materials led to low activities and enantioselectivities. But reversal on the stereochemical course of the reaction was observed, probably due to confinement effect. (C) 2013 Elsevier Inc. All rights reserved.

Topological Complexity and Predictability in the Dynamics of a Tumor Growth Model with Shilnikov's Chaos

Dynamical systems modeling tumor growth have been investigated to determine the dynamics between tumor and healthy cells. Recent theoretical investigations indicate that these interactions may lead to different dynamical outcomes, in particular to homoclinic chaos. In the present study, we analyze both topological and dynamical properties of a recently characterized chaotic attractor governing the dynamics of tumor cells interacting with healthy tissue cells and effector cells of the immune system. By using the theory of symbolic dynamics, we first characterize the topological entropy and the parameter space ordering of kneading sequences from one-dimensional iterated maps identified in the dynamics, focusing on the effects of inactivation interactions between both effector and tumor cells. The previous analyses are complemented with the computation of the spectrum of Lyapunov exponents, the fractal dimension and the predictability of the chaotic attractors. Our results show that the inactivation rate of effector cells by the tumor cells has an important effect on the dynamics of the system. The increase of effector cells inactivation involves an inverse Feigenbaum (i.e. period-halving bifurcation) scenario, which results in the stabilization of the dynamics and in an increase of dynamics predictability. Our analyses also reveal that, at low inactivation rates of effector cells, tumor cells undergo strong, chaotic fluctuations, with the dynamics being highly unpredictable. Our findings are discussed in the context of tumor cells potential viability.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Towards a complex model of cooperative learning

Este artigo é uma introdução à teoria do paradigma desconstrutivo de aprendizagem cooperativa. Centenas de estudos provam com evidências o facto de que as estruturas e os processos de aprendizagem cooperativa aumentam o desempenho académico, reforçam as competências de aprendizagem ao longo da vida e desenvolvem competências sociais, pessoais de cada aluno de uma forma mais eficaz e usta, comparativamente às estruturas tradicionais de aprendizagem nas escolas. Enfrentando os desafios dos nossos sistemas educativos, seria interessante elaborar o quadro teórico do discurso da aprendizagem cooperativa, dos últimos 40 anos, a partir de um aspeto prático dentro do contexto teórico e metodológico. Nas últimas décadas, o discurso cooperativo elaborou os elementos práticos e teóricos de estruturas e processos de aprendizagem cooperativa. Gostaríamos de fazer um resumo desses elementos com o objetivo de compreender que tipo de mudanças estruturais podem fazer diferenças reais na prática de ensino e aprendizagem. Os princípios básicos de estruturas cooperativas, os papéis de cooperação e as atitudes cooperativas são os principais elementos que podemos brevemente descrever aqui, de modo a criar um quadro para a compreensão teórica e prática de como podemos sugerir os elementos de aprendizagem cooperativa na nossa prática em sala de aula. Na minha perspetiva, esta complexa teoria da aprendizagem cooperativa pode ser entendida como um paradigma desconstrutivo que fornece algumas respostas pragmáticas para as questões da nossa prática educativa quotidiana, a partir do nível da sala de aula para o nível de sistema educativo, com foco na destruição de estruturas hierárquicas e antidemocráticas de aprendizagem e, criando, ao mesmo tempo, as estruturas cooperativas.

A new bridge between leptonic CP violation and leptogenesis

Flavour effects due to lepton interactions in the early Universe may have played an important role in the generation of the cosmological baryon asymmetry through leptogenesis. If the only source of high-energy CP violation comes from the left-handed leptonic sector, then it is possible to establish a bridge between flavoured leptogenesis and low-energy leptonic CP violation. We explore this connection taking into account our present knowledge about low-energy neutrino parameters and the matter-antimatter asymmetry observed in the Universe. In this framework, we find that leptogenesis favours a hierarchical light neutrino mass spectrum, while for quasi-degenerate and inverted hierarchical neutrino masses there is a very narrow allowed window. The absolute neutrino mass scale turns out to be m less than or similar to 0.1 eV. (c) 2007 Elsevier B.V. All rights reserved.

Tuneable micro- and nano-periodic structures in urethane/urea networks

Micro- and nano-patterned materials are of great importance for the design of new nanoscale electronic, optical and mechanical devices, ranging from sensors to displays. A prospective system that can support a designed functionality is elastomeric polyurethane thin films with nano- or micromodulated surface structures ("wrinkles"). These wrinkles can be induced on different lengthscales by mechanically stretching the films, without the need for any sophisticated lithographic techniques. In the present article we focus on the experimental control of the wrinkling process. A simple model for wrinkle formation is also discussed, and some preliminary results reported. Hierarchical assembly of these tunable structures paves the way for the development of a new class of materials with a wide range of applications, from electronics to biomedicine.

Self-assembly in chains, rings, and branches: a single component system with two critical points

Agências financiadoras: FCT - PEstOE/FIS/UI0618/2011; PTDC/FIS/098254/2008 ERC-PATCHYCOLLOIDS e MIUR-PRIN

Avaliação da qualidade em creche: implicações e resultados da aplicação do modelo de avaliação da qualidade das respostas sociais - creche, numa instituição particular de solidariedade social

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção do Grau de Mestre em Ciências da Educação, especialização em Administração Escolar

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Integração de reacção e deliberação em agentes inteligentes

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

O terceiro corpo na escrita cénica contemporânea : uma proposta de intervenção para a formação do intérprete

Doutoramento em Motricidade Humana na especialidade de Dança