Evidências de validade da versão brasileira do Exercise Motivation Inventory-2 em contexto de academia e personal training

Este estudo teve como objetivos verificar a validade fatorial e a validade interna da versão brasileira do Exercise Motivation Inventory-2 (EMI-2) e comparar os principais motivos para prática de exercício tendo em conta os contextos de academia e personal training. Um total de 588 praticantes de exercício da cidade de Pelotas/RS/Brasil (405 de academia e 183 de personal training) preencheram o EMI-2, o qual é constituído por 51 itens, agrupados em 14 motivos (fatores) para prática de exercício físico. A validade fatorial do EMI-2 foi testada através da realização de análises fatoriais confirmatórias e a validade interna através do alfa de Cronbach. Para a verificar o efeito do contexto nos motivos foi utilizada a MANOVA e calculado o tamanho do efeito. Os resultados obtidos dão suporte à estrutura original do EMI-2 com 14 fatores, nesta amostra. Verificou-se um efeito multivariado significativo do contexto sobre os motivos de prática [Wilks’ λ = 0.912, F (14, 573.000) = 3.9, p < 0.001, η² = 0.088]. Os motivos de “Prazer”, “Força e resistência”, “Desafio”, “Socialização”, “Competição” e “Reconhecimento Social” foram significativamente superiores no contexto de academia e os motivos de “Agilidade” e “Prevenção de Doenças” foram significativamente superiores no contexto de personal training.

OC/EC ratio observations in Europe: Re-thinking the approach for apportionment between primary and secondary organic carbon

This study explores a large set of OC and EC measurements in PM(10) and PM(2.5) aerosol samples, undertaken with a long term constant analytical methodology, to evaluate the capability of the OC/EC minimum ratio to represent the ratio between the OC and EC aerosol components resulting from fossil fuel combustion (OC(ff)/EC(ff)). The data set covers a wide geographical area in Europe, but with a particular focus upon Portugal, Spain and the United Kingdom, and includes a great variety of sites: urban (background, kerbside and tunnel), industrial, rural and remote. The highest minimum ratios were found in samples from remote and rural sites. Urban background sites have shown spatially and temporally consistent minimum ratios, of around 1.0 for PM(10) and 0.7 for PM(2.5).The consistency of results has suggested that the method could be used as a tool to derive the ratio between OC and EC from fossil fuel combustion and consequently to differentiate OC from primary and secondary sources. To explore this capability, OC and EC measurements were performed in a busy roadway tunnel in central Lisbon. The OC/EC ratio, which reflected the composition of vehicle combustion emissions, was in the range of 03-0.4. Ratios of OC/EC in roadside increment air (roadside minus urban background) in Birmingham, UK also lie within the range 03-0.4. Additional measurements were performed under heavy traffic conditions at two double kerbside sites located in the centre of Lisbon and Madrid. The OC/EC minimum ratios observed at both sites were found to be between those of the tunnel and those of urban background air, suggesting that minimum values commonly obtained for this parameter in open urban atmospheres over-predict the direct emissions of OC(ff) from road transport. Possible reasons for this discrepancy are explored. (C) 2011 Elsevier Ltd. All rights reserved.

Otimização de dose em mamografia

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Imagem Digital com Radiação X.

Intelligent behavior in a Cyber-Ambient training system for control center operators

This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

Using an ambient intelligent architecture for developing an intelligent tutoring system for training operators of power system control centres

This paper describes an architecture conceived to integrate Power Sys-tems tools in a Power System Control Centre, based on an Ambient Intelligent (AmI) paradigm. This architecture is an instantiation of the generic architecture proposed in [1] for developing systems that interact with AmI environments. This architecture has been proposed as a consequence of a methodology for the inclu-sion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Sys-tems Research for Ambient Intelligence). The architecture presented in the paper will be able to integrate two applications in the control room of a power system transmission network. The first is SPARSE expert system, used to get diagnosis of incidents and to support power restoration. The second application is an Intelligent Tutoring System (ITS) incorporating two training tools. The first tutoring tool is used to train operators to get the diagnosis of incidents. The second one is another tutoring tool used to train operators to perform restoration procedures.