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.

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.

Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

Cyber-ambient intelligent training of operators in power systems control centres

Cyber-Physical Systems and Ambient Intelligence are two of the most important and emerging paradigms of our days. The introduction of renewable sources gave origin to a completely different dimension of the distribution generation problem. On the other hand, Electricity Markets introduced a different dimension in the complexity, the economic dimension. Our goal is to study how to proceed with the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

An intelligent tutoring system for operators’ training in power system control centres

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, taking into account context awareness and the unobtrusive integration in the working environment.

Intelligent training in control centres based on an ambient intelligence paradigm

This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

The impact of exercise training on liver transplanted familial amyloidotic polyneuropathy (FAP) patients

Liver transplantation is nowadays the only effective answer to adjourn the outcome of functional limitations associated with familial amyloidotic polyneuropathy (FAP), a neurodegenerative disease characterized by sensory and motor polyneuropathies. Nevertheless, there is a detrimental impact associated with the after-surgery period on the fragile physical condition of these patients. Exercise training has been proven to be effective on reconditioning patients after transplantation. However, the effects of exercise training in liver transplanted FAP patients have not been scrutinized yet.

A doença oncológica no fórum da História: breve síntese sobre a evolução da luta anticancerosa em Portugal

Introdução – A doença oncológica tem sido assunto de abordagem historiográfica particularmente abundante no contexto internacional. No caso português só recentemente começaram a surgir os primeiros trabalhos em redor desta ampla temática. Objetivos – Revolvendo em torno da emergência e estruturação da luta anticancerosa no âmbito internacional, pretende-se apresentar uma breve síntese sobre a evolução deste fenómeno em Portugal na primeira metade do século XX. Metodologia – Análise documental. Qualitativa e heurística. Resultados/Discussão/Considerações finais – A luta contra a doença oncológica em Portugal não destoou do contexto médico-científico e do movimento internacional anticanceroso da primeira metade do século XX. No entanto, a emergência e a institucionalização do projeto anticanceroso nacional apresentou algumas particularidades. Inserido entre uma especialidade médica em processo de afirmação e as necessidades assistenciais dos cancerosos, resultou da conjugação de uma série de fatores que ultrapassam a mera assimilação de novas tecnologias médicas ou da criação de um espaço próprio para a prática da oncologia. Tornou-se também num meio para realizar um trabalho intenso de educação para a saúde, num instrumento de ponta na formação médica especializada e numa referência de modernidade científica no contexto do Estado Novo.

Neonatal mortality in intensive care units of Central Brazil

OBJECTIVE: To identify potential prognostic factors for neonatal mortality among newborns referred to intensive care units. METHODS: A live-birth cohort study was carried out in Goiânia, Central Brazil, from November 1999 to October 2000. Linked birth and infant death certificates were used to ascertain the cohort of live born infants. An additional active surveillance system of neonatal-based mortality was implemented. Exposure variables were collected from birth and death certificates. The outcome was survivors (n=713) and deaths (n=162) in all intensive care units in the study period. Cox's proportional hazards model was applied and a Receiver Operating Characteristic curve was used to compare the performance of statistically significant variables in the multivariable model. Adjusted mortality rates by birth weight and 5-min Apgar score were calculated for each intensive care unit. RESULTS: Low birth weight and 5-min Apgar score remained independently associated to death. Birth weight equal to 2,500g had 0.71 accuracy (95% CI: 0.65-0.77) for predicting neonatal death (sensitivity =72.2%). A wide variation in the mortality rates was found among intensive care units (9.5-48.1%) and two of them remained with significant high mortality rates even after adjusting for birth weight and 5-min Apgar score. CONCLUSIONS: This study corroborates birth weight as a sensitive screening variable in surveillance programs for neonatal death and also to target intensive care units with high mortality rates for implementing preventive actions and interventions during the delivery period.

Radiographers and radiation protection: education, training and CPD

The increasing use of ionizing radiation for medical purposes emphasizes the concern about safety and justification of using ionizing radiation. This is linked with the use of new and high-dose X-ray technology (particularly CT). According to the UNSCEAR 2010 Report the total number of diagnostic medical examinations (both medical and dental) is estimated to have risen from 2.4 billion (period 1991–1996) to 3.6 billion (period 1997– 2008) - a marked increase in collective doses. An appropriate use of technology aiming diagnostic or therapy and respecting the ALARA principle is a mandatory requisite to safely perform any radiological procedure. Radiation protection is thus, a concern of all specialists in the radiology field ( radiologists, radiographers, medical physicists, among other professional groups). The importance of education and training of these professionals in reducing patients’ doses while maintaining the desired level of quality in medical exposures, as well as precise therapeutic treatments is well recognized. Education, training and continuing professional development (CPD) constitute a triad pointing towards the radiographers’ development of competences in the radiation protection field. This presentation excludes the radiographer role and competences in the fields of ultrasonography and MRI.

Literary translation and quality assessment analysis – its significance in translation training

This paper aims to highlight the role of translation quality assessment in translation training so as to develop students’ translation competence and skills to face translation problems. An analysis to assess literary translation quality is proposed before proceeding to discuss its pedagogical implementation.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.