Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

Avaliação clínico-neuro-psicológica de trabalhadores expostos a mercúrio metálico em indústria de lâmpadas elétricas

Objetivou-se estudar a intoxicação por mercúrio metálico em trabalhadores de uma indústria de lâmpadas elétricas no Estado de São Paulo, Brasil. Foram investigados 71 trabalhadores, dos quais 61 (85,92%) apresentaram quadro de intoxicação crônica por mercúrio. O tempo de exposição dos trabalhadores estudados variou de 4 meses a 30 anos. Dentre os intoxicados foram detectadas alterações de coordenação motora em 57 (80,30%), neurológicas, em 56 (78,88%), de memória, em 51 (71,83%), no exame clínico, em 47 (66,20%), psiquiátricas, em 45 (63,38%) e da atenção concentrada, em 37 (52,10%).

Developmental and evolutionary assumptions in a study about the impact of premature birth and low income on mother–infant interaction

In order to study the impact of premature birth and low income on mother–infant interaction, four Portuguese samples were gathered: full-term, middle-class (n=99); premature, middle-class (n=63); full-term, low income (n=22); and premature, low income (n=21). Infants were filmed in a free play situation with their mothers, and the results were scored using the CARE Index. By means of multinomial regression analysis, social economic status (SES) was found to be the best predictor of maternal sensitivity and infant cooperative behavior within a set of medical and social factors. Contrary to the expectations of the cumulative risk perspective, two factors of risk (premature birth together with low SES) were as negative for mother–infant interaction as low SES solely. In this study, as previous studies have shown, maternal sensitivity and infant cooperative behavior were highly correlated, as was maternal control with infant compliance. Our results further indicate that, when maternal lack of responsiveness is high, the infant displays passive behavior, whereas when the maternal lack of responsiveness is medium, the infant displays difficult behavior. Indeed, our findings suggest that, in these cases, the link between types of maternal and infant interactive behavior is more dependent on the degree of maternal lack of responsiveness than it is on birth status or SES. The results will be discussed under a developmental and evolutionary reasoning

Lanczos algorithm on the grassmann manifold

5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

Prevalência de sintomas neuro-músculo-esqueléticos nos agricultores

Objectivos: O presente estudo teve como objectivos avaliar a prevalência da sintomatologia neuro-músculo-esquelética nos agricultores, identificar os seus factores de risco e avaliar a implementação de um projecto comunitário na sintomatologia neuro-músculo-esquelética dos agricultores. Metodologia: O estudo foi dividido em Estudo A e B. A amostra do Estudo A foi constituída por 250 agricultores seleccionados por amostragem consecutiva em 5 Cooperativas Agrícolas da Região Agrária entre Douro e Minho. A amostra do Estudo B foi constituída por 10 agricultores da Freguesia de Britelo - Concelho de Ponte da Barca, que aceitaram participar nas actividades do projecto (acção de educação e programa de exercícios específicos). Os dados foram recolhidos, por entrevista, através do Questionário de Avaliação dos Agricultores e o Questionário Nórdico Músculo-Esquelético. A análise estatística foi realizada recorrendo ao programa Statistical Package for Social Sciences, versão 17.0, considerando um nível de significância de 0,05. Resultados: No Estudo A observou-se que 74,4% dos agricultores referiram sintomatologia neuro-músculo-esquelético durante as actividades agrícolas e as regiões mais afectadas, foram a lombar, o pescoço e os ombros. Encontrou-se também uma associação significativa (p<0.05) entre a presença de sintomas nos agricultores e alguns factores de risco. Relativamente ao Estudo B, verificou-se uma diminuição significativa (p<0.05) na intensidade média de dor referida na lombar em algumas actividades e um aumento significativo (p<0.05) na pontuação final dos conhecimentos sobre os factores de risco. Conclusão: A população agrícola apresenta factores de risco que levam ao surgimento de sintomas neuro-músculo-esqueléticos, os quais podem ser prevenidos com a implementação de projectos comunitários.

Reorganização dos componentes neuro-motores com influência na marcha em indivíduos com lesão do sistema nervoso central - impacto funcional

Objectivo: Avaliar o impacto qualitativo de um programa de intervenção em fisioterapia, segundo o Conceito de Bobath, nas actividades e participação de dois indivíduos com lesão do Sistema Nervoso Central. Avaliar as modificações no comportamento da actividade muscular ao longo da fase de apoio do ciclo da marcha, na força de reacção ao solo e respectiva contribuição muscular. Metodologia: A avaliação realizou-se antes e após um programa de intervenção, segundo a abordagem do Conceito de Bobath, através da Classificação Internacional de Funcionalidade, Incapacidade e Saúde, electromiografia, plataforma de forças e máquina fotográfica. Resultados: Obteve-se melhorias na restrição da participação e na limitação da actividade. Verifica-se uma tendência de modificação do comportamento muscular ao longo da fase de apoio e na componente antero-posterior (Fy), mais evidente no mecanismo de aceleração. A mudança na contribuição muscular para a este mecanismo é mais evidente. Conclusão: O programa de intervenção, segundo o Conceito de Bobath, induziu mudanças positivas quanto à funcionalidade dos indivíduos, reflectindo-se na possibilidade de reorganização dos componentes neuro-motores em indivíduos com lesão do Sistema Nervoso Central.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Prevalência de sintomas neuro-músculo-esqueléticos nos agricultores

Introdução: A agricultura é considerada uma actividade fisicamente árdua, acarretando riscos para a saúde dos seus trabalhadores. Objectivo: Avaliar a prevalência de sintomatologia neuro-músculo-esquelética em agricultores e identificar os seus factores de risco. Métodos: Os Questionários Avaliação dos Agricultores e o Nórdico Músculo-Esquelético foram aplicados a 250 agricultores da Região Agrária entre Douro e Minho. Resultados: 74,4% dos agricultores referiram sintomatologia, principalmente, na lombar, pescoço e ombros. A presença de sintomas estava significativamente associada a alguns factores de risco (p<0.05). Conclusão: Os agricultores constituem uma população de risco para o surgimento de sintomas neuro-músculo-esqueléticos.

Prevalência e análise de factores de risco de problemas neuro-músculo-esqueléticos em músicos

Introdução: A prevalência de problemas neuro-músculo-esqueléticos nos músicos é elevada, pois estão sujeitos a grande exigência física e psicológica. Objectivos: Analisar a prevalência de factores de risco em marimbistas e caracterizar a postura da coluna vertebral na situação de tocar. Métodos: A recolha das situações de risco foi realizada através de um questionário e a postura da coluna, numa amostra de 10 marimbistas, analisada pelo SAPO. Resultados: As posturas entre as situações sem tocar e a tocar um excerto difícil são significativamente diferentes. Conclusão: Os marimbistas têm uma grande prevalência de sintomas sendo necessários programas de educação e promoção de saúde.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Comparison between deterministic and meta-heuristic methods applied to ancillary services dispatch

This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.