Efeito do campo elétrico em nanocones formados por aln e BN: um estudo por primeiros princípios

The development of computers and algorithms capable of making increasingly accurate and rapid calculations as well as the theoretic foundation provided by quantum mechanics has turned computer simulation into a valuable research tool. The importance of such a tool is due to its success in describing the physical and chemical properties of materials. One way of modifying the electronic properties of a given material is by applying an electric field. These effects are interesting in nanocones because their stability and geometric structure make them promising candidates for electron emission devices. In our study we calculated the first principles based on the density functional theory as implemented in the SIESTA code. We investigated aluminum nitride (AlN), boron nitride (BN) and carbon (C), subjected to external parallel electric field, perpendicular to their main axis. We discuss stability in terms of formation energy, using the chemical potential approach. We also analyze the electronic properties of these nanocones and show that in some cases the perpendicular electric field provokes a greater gap reduction when compared to the parallel field

Simulações de Monte Carlo para os modelos Ising e Blume-Capel em redes complexa

We studied the Ising model ferromagnetic as spin-1/2 and the Blume-Capel model as spin-1, > 0 on small world network, using computer simulation through the Metropolis algorithm. We calculated macroscopic quantities of the system, such as internal energy, magnetization, specific heat, magnetic susceptibility and Binder cumulant. We found for the Ising model the same result obtained by Koreans H. Hong, Beom Jun Kim and M. Y. Choi [6] and critical behavior similar Blume-Capel model

Propriedades eletrônicas, estruturais e constantes elásticas do ZnO

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

Relevância de exames de rotina em pacientes de baixo risco submetidos a cirurgias de pequeno e médio porte

JUSTIFICATIVA E OBJETIVOS: A avaliação pré-operatória tem como objetivos diminuir a morbimortalidade do paciente cirúrgico, o custo do atendimento perioperatório e a ansiedade pré-operatória. A partir da avaliação clínica deve-se definir a necessidade de exames complementares e estratégias para reduzir o risco anestésico-cirúrgico. O objetivo deste trabalho foi avaliar o benefício de exames de rotina pré-operatório de pacientes de baixo risco em cirurgias de pequeno e médio porte. MÉTODOS: Trata-se de um estudo descritivo, transversal, com 800 pacientes atendidos no consultório de avaliação pré-anestésica do Hospital Santo Antonio, Salvador, BA. Foram incluídos pacientes de 1 a 45 anos, estado físico ASA I, que seriam submetidos a cirurgias eletivas de pequeno e médio porte. Avaliaram-se alterações no hemograma, coagulograma, eletrocardiograma, RX de tórax, glicemia, função renal e dosagem de sódio e potássio e as eventuais mudanças de conduta que ocorreram decorrentes dessas alterações. RESULTADOS: Dos 800 pacientes avaliados, 97,5% fizeram hemograma, 89% coagulograma, 74,1% eletrocardiograma, 62% RX de tórax, 68% glicemia de jejum, 55,7% dosagens séricas de ureia e creatinina e 10,1% dosagens de sódio e potássio séricos. Desses 700 pacientes, 68 (9,71%) apresentaram alteração nos exames pré-operatórios de rotina e apenas 10 (14,7%) dos considerados alterados tiveram conduta pré-operatória modificada, ou seja, solicitação de novos exames, interconsulta ou adiamento do procedimento. Nenhuma das cirurgias foi suspensa. CONCLUSÃO: Observou-se que excessivos exames complementares são solicitados no pré-operatório, mesmo em pacientes jovens, de baixo risco cirúrgico, com pouca ou nenhuma interferência na conduta perioperatória. Exames aboratoriais padronizados não são bons instrumentos de screening de doenças, além de gerar gastos elevados e desnecessários.

Jogo da Minoria: um modelo baseado em agentes aplicado ao mercado financeiro

Nos últimos anos houve uma contribuição significativa dos físicos para a construção de um tipo de modelo baseado em agentes que busca reproduzir, em simulação computacional, o comportamento do mercado financeiro. Esse modelo, chamado Jogo da Minoria consiste de um grupo de agentes que vão ao mercado comprar ou vender ativos. Eles tomam decisões com base em estratégias e, por meio delas, os agentes estabelecem um intrincado jogo de competição e coordenação pela distribuição da riqueza. O modelo tem demonstrado resultados bastante ricos e surpreendentes, tanto na dinâmica do sistema como na capacidade de reproduzir características estatísticas e comportamentais do mercado financeiro. Neste artigo, são apresentadas a estrutura e a dinâmica do Jogo da Minoria, bem como as contribuições recentes relacionadas ao Jogo da Minoria denominado de Grande Canônico, que é um modelo mais bem ajustado às características do mercado financeiro e reproduz as regularidades estatísticas do preço dos ativos chamadas fatos estilizados.

Hydrolyzed alpha-lactalbumin as a source of protein to the exercising

This work describes the effect of feeding enzymatically hydrolyzed a-lactalbumin on blood sugar, albumin and fatty acids, muscular and hepatic glycogen of rats subjected to physical exercise. Three normoenergetic/normoproteic diets, containing either casein (C), alpha-lactalbumin (L) or alpha-lactalbumin hydrolyzate (H) were fed to thirty male Wistar rats for five weeks. During this period, half of the rats swam for 1 hr daily (T category) while the other half remained sedentary (S category). At the end of training, all rats were required to swim to exhaustion. The results showed that those rats of the T-category consuming diet H reached exhaustion with significantly higher concentrations of serum glucose ([H] 56.0 and [L] 32.3 mg/100ml), serum albumin ([H] 3.8 and [L] 2.1 mg/dl) and muscle glycogen ([H] 2.1 and [L] 0.6 mg/g), while no differences were observed between diets regarding the time of arrival to exhaustion. Results from diets C and L differed minimally. It was concluded that feeding the hydrolyzed protein may result in nutritional advantage to the exercising rat. (C) 1998 Elsevier B.V.

Thermal diffusivity analysis of doped poly(methyl-methacrylate) with electron donor and acceptor molecules

A computer-assisted method for analysing photoacoustic spectra has been developed in the Windows(TM) environment with the use of an easy graphical interface, the computer simulation was carried out with the aim of using the entire expression of the Rosencwaig-Gersho theory, thus permitting multiple applications. The simulation was applied to a system that mimics the electron transfer process in which the concentration of octaethylporphin donor molecules was constant whereas the concentration of duroquinone and 2,3-dichloro-5,6-dicyano-1, l-benzoquinone acceptor molecules varied. The increment of the acceptor concentration influenced the photoacoustic amplitude and phase signals. In the phase signal a significant shift to smaller values was observed, denoting a faster heat generation. The analysis of the photoacoustic signal enabled the determination of the thermal diffusivity, the result obtained through the simulation was about (7 +/- 1) x 10(-7) m(2) s(-1) indicating that changes in the photoacoustic phase signals were due to the electron transfer process rather than changes in the thermal properties of the sample.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Static converter: didactic support software

Teaching a course of special electric loads in a continuing education program to power engineers is a difficult task because they are not familiarized with switching topology circuits. Normally, in a typical program, many hours are dedicated to explain the thyristors switching sequence and to draw the converter currents and terminal voltages waveforms for different operative conditions. This work presents teaching support software in order to optimize the time spent in this task and, mainly to benefit the assimilation of the proposed subjects, studying the static converter under different non-ideal operative conditions.

Modelling of the influence of the layer pollution thickness in high voltage polluted insulators

An experimental model and a mathematical model with the introduction of a ramp in the channel of Obenaus model are presented. The aim is to present a better reproduction of the real layer pollution deposited on the HV insulators. This better reproduction is obtained from two types of thickness variation: the introduction of a ramp (soft variation) and the introduction of a step (sudden variation). The computational simulations and the experimental data suggest that the introduction of the ramp is the better reproduction of the layer pollution. The ramp approximates to the real layer pollution more than the step.

Neural networks training using the constructivism paradigms

The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural network training using the BA inspired on constructivism, an alphabetization method proposed by Emilia Ferreiro based on Piaget philosophy. Simulation results show that the proposed configuration usually obtains a lower final mean square error, when compared with the standard BA and with the BA with momentum factor.

Another prefiltering algorithm for adaptive IIR filtering

An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.

Asymmetrical magnetization in three-phase core type transformers

The performance of the three-phase core type transformers, under AC/DC double excitation is discussed in this work. It is presented a mathematical model that considers the mutual coupling between phases and the magnetic nonlinearity. The validity of the proposed model is verified by means of the experimental and simulated results.

Electric power systems transient stability analysis by neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise do escoamento de HFC-134a em tubos capilares usando o modelo de dois fluidos

This work presents a numerical model to simulate refrigerant flow through capillary tubes, commonly used as expansion devices in refrigeration systems. The capillary tube is considered straight and horizontal. The flow is taken as one-dimensional and adiabatic. Steady state and thermodynamic equilibrium conditions are assumed. The two-fluid model, involving four conservation equations and considering the hidrodynamic nonequilibrium between the liquid and vapor phases is applied to the flow region. The pressure profiles and the mass flow rates given by the model are compared with experimental data.