Abstract
Purpose - The purpose of this paper is to solve the problem of committing electric power generators (unit commitment, UC), considering network constraints. Design/methodology/approach - The UC is first solved with a local search based meta-heuristic, following the assumption that all generators and loads are connected to a single network node. For evaluation purposes, the economical production levels of the units committed are computed by running a pre-dispatch algorithm where network constraints are not included. If a good quality solution is reached, an economic dispatch (ED) with network constraints is performed, where the geographic location of generators and loads are considered. Therefore, the production level of each committed generator is performed that leads to the global lowest solution cost, regarding both the generators' costs and constraints and the power system network constraints. Findings - The algorithm proposed is computationally efficient, given the time available for decision making. In addition, the solution for this algorithm, in terms of minimization of total costs, is generally better than the solution of the two phases approach. Some contractual and legal aspects related with the injection in network connections can also be included in the model. Practical implications - UC with network constraints has a large potential of use, especially for small and medium size power systems. It reflects reality in a closer way and provides a more complete and realistic knowledge about the system in operation. Originality/value - The paper presents an approach where theED with network constraints is integrated with the UC procedure. The model described is currently implemented in an EMS package offered in the market - making it a case of successful transfer from science to industry.

Abstract
Due to its combinatorial nature, the Unit Commitment problem has for long been an important research challenge, with several optimization techniques, from exact to heuristic methods, having been proposed to deal with it. In line with one current trend of research, metaheuristic approaches have been studied and some interesting results have already been achieved and published. However, a successful utilization of these methodologies in practice, when embedded in Energy Management Systems, is still constrained by the reluctance of industrial partners in using techniques whose performance highly depends on a correct parameter tuning. Therefore, the application of metaheuristics to the Unit Commitment problem does still justify further research. In this paper we propose a new search strategy, for Local Search based metaheuristics, that tries to overcome this issue. The approach has been tested in a set of instances, leading to very good results in terms of solution cost, when compared either to the classical Lagrangian Relaxation or to other metaheuristics. It also drastically reduced the computation times. Furthermore, the approach proved to be robust, always leading to good results independently of the metaheuristic parameters used.

Abstract
Asthma patients incur a great cost in terms of loss of quality of life. The purpose of this study is to evaluate the relative contribution and relationship of several patient- and disease-related factors, measured by several variables, to the quality of life in adults with asthma. Two hundred and ten asthmatic outpatients over 18 years old, registered in a Family Health Unit, were randomly selected to complete the Asthma Quality of Life (AQLQ) and Short Form Generic questionnaires (SF-36), respectively. Single and multiple linear regression models were developed to explain the variability of the summary scores of AQLQ and Physical and Mental Health SF-36. As potential predictors, the following independent variables were used: gender, age, number of comorbidities, asthma severity following the Global Initiative for Asthma (GINA) criteria, asthma control (measured by ACQ questionnaire), %FEV1 (forced expiratory volume in the first second) and, for the first time, Graffar Score to assess socioeconomical features. The Graffar Score is an index that divides the population in 5 socioeconomic layers. We report the best Adjusted R Square of these models published in the literature, ranging from 0.40 to 0.76. Women showed poorer quality of life than men. The best predictor of AQLQ was ACQ, followed by Asthma Severity, Gender and %FEV1. The best predictors of Physical and Mental Health SF-36 were, by decreasing importance, ACQ, number of comorbidities, Gender and Graffar Score. We note that the variable Dumber of comorbidities was included in both SF-36 models, but not in AQLQ model. Asthma Severity and %FEV1 did not enter into SF-36 models. We conclude that besides clinical and functional measures, the evaluation process of the overall health status must incorporate quality-of-life measures.

Abstract
Traveler attitudes and preferences as well as demographic variables are important components of travel behavior. By using travel attitudes, factor and cluster analyses were conducted to segment the sample. Six distinct groups were extracted: transit enthusiasts, anxious status seekers, carless riders, green cruisers, frugal travelers, and obstinate drivers. The segments showed unique combinations of attitudes with distinct travel behaviors and various degrees of intention to use public transportation. Gender differences were then investigated, and the results suggest that women and men exhibit differences in attitudes, preferences, and behaviors. The design of strategies to promote alternatives to car use should target the market segments that are most motivated to change, focusing on the attitudes that can induce a change, such as pro transit or sensibility to the environment.

Abstract
According with Axiomatic Design (AD) theory, the world of design is made up of four domains: the customer domain, the functional domain, the physical domain and the process domain. Therefore, to proceed in the design process, firstly, it's necessary to determine the Customer's Attributes (CAs), established in the Customer domain, and translate them into specific requirements, the Functional Requirements (FRs), formalized in the functional domain. This task is considered essential because a major reason for customer dissatisfaction is that the design specifications quite often do not adequately link to customer use of the product, a fact which is being pointed out as the most common cause for product design failures [1-2]. The European Customer Satisfaction Index (ECSI), as a Structural Equation Model (SEM), links customer satisfaction to its main drivers and consequences in terms of causal relationships. We will therefore introduce in this paper a new conceptual framework, aimed at addressing the development and validation of a model based on ECSI that supports the determination of the critical-to-satisfy (CTS) requirements, which are then used to determine the FRs. In order to validate the proposed approach, it was applied to the Portuguese plastic injection moulds sector.

Abstract
The education of professional engineers has been mainly oriented towards the requirements of industry, although many graduates will start and end up working in service organizations. Services always involve interaction, either directly between people or using machines. Most services now require the use of technology, including self service machines, Internet and mobile equipments and may involve complex social and organizational issues. Although engineering programs have evolved in order to accommodate changes in the economy, new proposals must be taken into new graduate and postgraduate education. This paper proposes MESG1, a Master program in Services Engineering and Management compatible with the Bologna European framework. It is still a program to educate professional engineers, in the sense that graduates will be prepared to Conceive, Design, Implement and Operate (CDIO) complex value-added engineering systems. But MESG has a strong emphasis on: (i) understanding the innovative technologies now required for service provision, (ii) understanding the functional and the experience requirements of people using services, and (iii) management of the service CDIO process and understanding its value. Knowledge and experience about people and about business, in social-organizational environments, are important components in the advanced education of service engineers and managers.