Chronic stress disrupts neural coherence between cortico-limbic structures

Chronic stress impairs cognitive function, namely on tasks that rely on the integrity of cortico-limbic networks. To unravel the functional impact of progressive stress in cortico-limbic networks we measured neural activity and spectral coherences between the ventral hippocampus (vHIP) and the medial prefrontal cortex (mPFC) in rats subjected to short term stress (STS) and chronic unpredictable stress (CUS). CUS exposure consistently disrupted the spectral coherence between both areas for a wide range of frequencies, whereas STS exposure failed to trigger such effect. The chronic stress-induced coherence decrease correlated inversely with the vHIP power spectrum, but not with the mPFC power spectrum, which supports the view that hippocampal dysfunction is the primary event after stress exposure. Importantly, we additionally show that the variations in vHIP-to-mPFC coherence and power spectrum in the vHIP correlated with stress-induced behavioral deficits in a spatial reference memory task. Altogether, these findings result in an innovative readout to measure, and follow, the functional events that underlie the stress-induced reference memory impairments.

A Importância da Música na Motivação do Aluno

A presente pesquisa faz uma análise sobre o reconhecimento da necessidade da Música na Escola, levando em consideração o caráter interdisciplinar, lúdico e as restantes propriedades da música, capazes de promover cada vez mais sinapses, fato este comprovado pela Neurociência, em que o aluno passa a estar mais motivado, através da constante e percetível ativação de diversas áreas cerebrais distintas das áreas específicas do tratamento da informação musical. O ponto de partida para esta pesquisa foi a Lei 11.769/08 do Governo Federal Brasileiro que trata da obrigatoriedade do ensino da música na educação básica, a partir deste momento, houve grandes perspetivas e projetos direcionados ao retorno da música à sala de aula, focalizando a atenção para a melhor organização dos espaços, nomeadamente, estruturas, materiais e pessoal, de forma a garantir o sucesso do ensino através da música. Tendo em conta a implementação desta lei, houve a necessidade de analisar na prática, os benefícios da música na aprendizagem, bem como a formação do docente para esta atividade. Deste modo, fez-se o enquadramento teórico com base nos conhecimentos já existentes sobre políticas educativas públicas e o ensino artístico, especificamente a presença da Música no currículo escolar. Este enquadramento serviu de base para a realização de um estudo no município de Coelho Neto no Maranhão – Brasil, com base na temática: ―A Importância da Música na Motivação do Aluno‖, que demonstrou a falta de preparação dos docentes no que concerne à música. Assim, esta investigação-ação levou-nos à elaboração do Projeto ―Formar para melhor ensinar‖, no sentido de ajudar os professores a superar esta lacuna. Este projeto será implementado no próximo ano letivo.

Optimal design of piezolaminated structures using B-spline strip finite element models

A package of B-spline finite strip models is developed for the linear analysis of piezolaminated plates and shells. This package is associated to a global optimization technique in order to enhance the performance of these types of structures, subjected to various types of objective functions and/or constraints, with discrete and continuous design variables. The models considered are based on a higher-order displacement field and one can apply them to the static, free vibration and buckling analyses of laminated adaptive structures with arbitrary lay-ups, loading and boundary conditions. Genetic algorithms, with either binary or floating point encoding of design variables, were considered to find optimal locations of piezoelectric actuators as well as to determine the best voltages applied to them in order to obtain a desired structure shape. These models provide an overall economy of computing effort for static and vibration problems.

Large area image sensing structures based on a-SiC : H: a dynamic characterization

In recent works large area hydrogenated amorphous silicon p-i-n structures with low conductivity doped layers were proposed as single element image sensors. The working principle of this type of sensor is based on the modulation, by the local illumination conditions, of the photocurrent generated by a light beam scanning the active area of the device. In order to evaluate the sensor capabilities is necessary to perform a response time characterization. This work focuses on the transient response of such sensor and on the influence of the carbon contents of the doped layers. In order to evaluate the response time a set of devices with different percentage of carbon incorporation in the doped layers is analyzed by measuring the scanner-induced photocurrent under different bias conditions.

GA topology optimization using random keys for tree encoding of structures

Topology optimization consists in finding the spatial distribution of a given total volume of material for the resulting structure to have some optimal property, for instance, maximization of structural stiffness or maximization of the fundamental eigenfrequency. In this paper a Genetic Algorithm (GA) employing a representation method based on trees is developed to generate initial feasible individuals that remain feasible upon crossover and mutation and as such do not require any repairing operator to ensure feasibility. Several application examples are studied involving the topology optimization of structures where the objective functions is the maximization of the stiffness and the maximization of the first and the second eigenfrequencies of a plate, all cases having a prescribed material volume constraint.

Avaliação de dados funcionais em repouso do cérebro normal: causalidade de Granger

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Ressonância Magnética

Photonics Active Filters Based on SiC Multi layer Structures: A Two Stage Active Circuit

Characteristics of tunable wavelength filters based on a-SiC:H multi-layered stacked cells are studied both theoretically and experimentally. Results show that the light-activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal. The sensor is a bias wavelength current-controlled device that make use of changes in the wavelength of the background to control the power delivered to the load, acting a photonic active filter. Its gain depends on the background wavelength that controls the electrical field profile across the device.

: SiC Multilayer Photonic Structures with Self Optical Bias Amplification

Characteristics of tunable wavelength pi'n/pin filters based on a-SiC:H multilayered stacked cells are studied both experimental and theoretically. Results show that the device combines the demultiplexing operation with the simultaneous photodetection and self amplification of the signal. An algorithm to decode the multiplex signal is established. A capacitive active band-pass filter model is presented and supported by an electrical simulation of the state variable filter circuit. Experimental and simulated results show that the device acts as a state variable filter. It combines the properties of active high-pass and low-pass filter sections into a capacitive active band-pass filter using a changing photo capacitance to control the power delivered to the load.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Syntheses, Molecular Structures, Electrochemical Behavior, Theoretical Study, and Antitumor Activities of Organotin(IV) Complexes Containing 1-(4-Chlorophenyl)-1-cyclopentanecarboxylato Ligands

The organotin(IV) compounds [Me2Sn(L)(2)] (1), [Et(2)sn(L)(2)] (2), [(Bu2Sn)-Bu-n(L)(2)] (3), [(n)Oct(2)Sn(L)(2)] (4), [Ph2Sn(L)(2)] (5), and [PhOSnL](6) (6) have been synthesized from the reactions of 1-(4-chlorophenyl)-1-cyclopentanecarboxylic acid (HL) with the corresponding diorganotin(IV) oxide or dichloride. They were characterized by IR and multinuclear NMR spectroscopies, elemental analysis, cyclic voltammetry, and, for 2, 3, 4 and 6, single crystal X-ray diffraction analysis. While 1-5 are mononuclear diorganotin (IV) compounds, the X-ray diffraction of 6 discloses a hexameric drumlike structure with a prismatic Sn6O6 core. All these complexes undergo irreversible reductions and were screened for their in vitro antitumor activities toward HL-60, BGC-823, Bel-7402, and KB human cancer cell lines. Within the mononuclear compounds, the most active ones (3, 5) are easiest to reduce (least cathodic reduction potentials), while the least active ones (1, 4) are the most difficult to reduce. Structural rearrangements (i.e., Sn-O bond cleavages and trans-to-cis isomerization) induced by reduction, which eventually can favor the bioactivity, are disclosed by theoretical/electrochemical studies.

A model updating technique based on FRFs for damped structures

Model updating methods often neglect that in fact all physical structures are damped. Such simplification relies on the structural modelling approach, although it compromises the accuracy of the predictions of the structural dynamic behaviour. In the present work, the authors address the problem of finite element (FE) model updating based on measured frequency response functions (FRFs), considering damping. The proposed procedure is based upon the complex experimental data, which contains information related to the damped FE model parameters and presents the advantage of requiring no prior knowledge about the damping matrix structure or its content, only demanding the definition of the damping type. Numerical simulations are performed in order to establish the applicability of the proposed damped FE model updating technique and its results are discussed in terms of the correlation between the simulated experimental complex FRFs and the ones obtained from the updated FE model.

The effects of air pollution on cardiovascular diseases: lag structures

OBJECTIVE: To assess the lag structure between air pollution exposure and elderly cardiovascular diseases hospital admissions, by gender. METHODS: Health data of people aged 64 years or older was stratified by gender in São Paulo city, Southeastern Brazil, from 1996 to 2001. Daily levels of air pollutants (CO, PM10, O3, NO2, and SO2) , minimum temperature, and relative humidity were also analyzed. It were fitted generalized additive Poisson regressions and used constrained distributed lag models adjusted for long time trend, weekdays, weather and holidays to assess the lagged effects of air pollutants on hospital admissions up to 20 days after exposure. RESULTS: Interquartile range increases in PM10 (26.21 mug/m³) and SO2 (10.73 mug/m³) were associated with 3.17% (95% CI: 2.09-4.25) increase in congestive heart failure and 0.89% (95% CI: 0.18-1.61) increase in total cardiovascular diseases at lag 0, respectively. Effects were higher among female group for most of the analyzed outcomes. Effects of air pollutants for different outcomes and gender groups were predominately acute and some "harvesting" were found. CONLUSIONS: The results show that cardiovascular diseases in São Paulo are strongly affected by air pollution.

Analysis of functionally graded sandwich plate structures with piezoelectric skins, using B-spline finite strip method

Functionally graded materials are composite materials wherein the composition of the constituent phases can vary in a smooth continuous way with a gradation which is function of its spatial coordinates. This characteristic proves to be an important issue as it can minimize abrupt variations of the material properties which are usually responsible for localized high values of stresses, and simultaneously providing an effective thermal barrier in specific applications. In the present work, it is studied the static and free vibration behaviour of functionally graded sandwich plate type structures, using B-spline finite strip element models based on different shear deformation theories. The effective properties of functionally graded materials are estimated according to Mori-Tanaka homogenization scheme. These sandwich structures can also consider the existence of outer skins of piezoelectric materials, thus achieving them adaptive characteristics. The performance of the models, are illustrated through a set of test cases. (C) 2012 Elsevier Ltd. All rights reserved.