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        <rdf:li rdf:resource="http://hdl.handle.net/10071/16343" />
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    <dc:date>2018-10-13T12:45:14Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10071/16343">
    <title>Planning health workforce training in the detection and prevention of excessive alcohol consumption: an optimization-based approach</title>
    <link>http://hdl.handle.net/10071/16343</link>
    <description>Title: Planning health workforce training in the detection and prevention of excessive alcohol consumption: an optimization-based approach
Authors: Faria, J.; Cardoso-Grilo, T.; Gomes, C.
Abstract: The adequate training of health workforce in the field of excessive alcohol consumption is essential to provide health professionals with the necessary tools for an adequate provision of care, thus leading to a decrease in alcohol consumption. Proper planning of such training is thus essential, but literature in this area is still scarce. This paper proposes an optimization model based on mathematical programming for supporting the planning of health workforce training in the field of excessive alcohol consumption in National Health Service-based countries – the WFTMalcohol. The model aims at informing on (i) how many health professionals (physicians and nurses) should be trained per year and health unit, and (ii) which training packages should be available per year. The model allows exploring the impact of considering different objectives relevant in this sector, including the minimization of costs and the maximization of multiple performance indicators. Acknowledging that several sources of uncertainty may affect planning decisions, a sensitivity analysis on key parameters of the model is performed. To illustrate the applicability of the model, a case study based on the Oeste Sul ACES in Lisbon is analyzed. Results confirm that there is a shortage of trained professionals in this field in Portugal.</description>
    <dc:date>2018-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10071/16293">
    <title>Towards artistic education with textiles: a sustainable challenge with K-10 children</title>
    <link>http://hdl.handle.net/10071/16293</link>
    <description>Title: Towards artistic education with textiles: a sustainable challenge with K-10 children
Authors: Delgado, M. J.; Almeida, I. D.
Abstract: Making art with textiles has become part of the development process of creative potential that has led to the acquisition of different types of skills strongly correlated to the success of the textile and clothing industry. There are objectives defined in the curricula of basic education and pre-school education (K10 children) that tackle the artisanal process of transforming raw textile materials: these include acquiring knowledge of textile materials, highlighting the importance of handicrafts in culture and heritage, textile arts and the development of fine motor skills. The objective of this study is to learn about the practices of K10 children using textiles in schools, and to understand how these practices contribute to the development of their creative potential with regard to the area of textiles and clothing. Integrating the activities with textiles makes sensitization to the ma-terials and techniques of the textile arts possible, and paves the way for greater sustainability of this sector in Portuguese society.</description>
    <dc:date>2018-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/10071/14582">
    <title>Designing integrated biorefineries supply chain: combining stochastic programming models with scenario reduction methods</title>
    <link>http://hdl.handle.net/10071/14582</link>
    <description>Title: Designing integrated biorefineries supply chain: combining stochastic programming models with scenario reduction methods
Authors: Paulo, H.; Cardoso-Grilo, T.; Relvas, S.; Barbosa-Póvoa, A. P.
Abstract: This paper addresses the design and planning of integrated biorefineries supply chain under uncertainty. A two-stage stochastic mixed integer linear programming (MILP) model is proposed considering the presence of uncertainty in the residual lignocellulosic biomass availability and technology conversion factors. Nevertheless, when the scenario tree approach is applied to a large real world case study, it generates a computationally complex problem to solve. To address this challenge the present paper proposes the improvement of the scenario tree approach through the use of two scenario reduction methods. The results illustrate the impact of the uncertain parameters over the network configuration of a real case when compared with the deterministic solution. Both scenario reduction methods appear promising and should be further explored when solving large scenario trees problems.</description>
    <dc:date>2017-01-01T00:00:00Z</dc:date>
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