998 resultados para 319.272053
Resumo:
Future changes in population exposures to ambient air pollution are inherently linked with long-term trends in outdoor air quality, but also with changes in the building stock. Moreover, the burden of disease is further driven by the ageing of the European populations. This study aims to assess the impact of changes in climate, emissions, building stocks and population on air pollution related human health impacts across Europe in the future. Therefore an integrated assessment model combining atmospheric models and health impacts has been setup for projections of the future developments in air pollution related premature mortality. The focus is here on the regional scale impacts of exposure to surface ozone (O3), Secondary Inorganic Aerosols (SIA) and primary particulate matter (PPM).
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The rapid growth of the Chinese tourism has stimulated competition within tourism-related industries, such as the hospitality industry. The purpose of this study is to examine the Chinese consumer reaction to different promotional tools used by hotels in China and, thus, to provide a deeper understanding for marketers of how to use sales promotion effectively to generate appropriate consumer responses. An experimental survey was administered yielding a total sample of 319 Chinese customers, who were probed using different types of sales promotion tools. Data analysis indicates that bonus packs (e.g. a 3-night stay at a hotel for the price of 2) induced the highest consumer perceived value, brand switching, and purchase acceleration intention, whereas price discounts resulted in the highest intention to spend more. Although this study has its limitations given its reliance on a convenience sample, it offers insightful practical implications for hotel business owners in Asia regarding targeting the right customers with the right promotional tools, where it is proposed that bonus packs successfully attract new Chinese customers and price discounts support in generating more sales.
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Politicians, industry and the public generally accept the need for energy consumption to be cut to deliver climate change mitigation measures essential for us to avoid climate disaster. For non-domestic fuel users current energy policy has attempted to drive this through rational economic responses to energy cost pressures. This reliance on voluntary action has created an “Energy Inconsistency”, that is a marked difference between energy opportunities that have been proven technically viable, financially rational and retrofit feasible and those actually adopted. Other factors must therefore be involved to influence what appear to be simple carbon and cost saving opportunities. This paper presents a new approach to energy efficiency and consumption in non-domestic buildings, viewing attitudes and behaviours of building owners and users as the key driver of energy consumption. A new framework is proposed as a method to examine the impact of building ownership on the users’ and owners’ abilities to improve energy efficiency and consumption and identify opportunities to overcome the barriers inherent in these ownership structures.
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In August 2006, Portugal approved a new quota law, called the parity law. According to this, all candidate lists presented for local, parliamentary, and European elections must guarantee a minimum representation of 33 per cent for each sex. This article analyses the proximate causes that led to the adoption of gender quotas by the Portuguese Parliament. The simple answer is that the law’s passage was a direct consequence of a draft piece of legislation presented by the Socialist Party (PS), which enjoyed a majority. However, the reasons that led the PS to push through a quota law remain unclear. Using open-ended interviews with key women deputies from all the main Portuguese political parties, and national public opinion data, among other sources, the role of four actors/factors that were involved in the law’s adoption are critically examined: notably, civil society actors, state actors, international and transnational actors, and the Portuguese political context.
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In 1968, Herbert Marcuse believed that a Great Refusal was possible, one that would deny the exploitative power of corporate capitalism. Marcuse's vision was never realised. This essay argues that society today is in an advanced state of that which the Frankfurt School termed repressive desublimation and questions whether a liberationary praxis is still possible. It claims that Bret Easton Ellis's fiction choreographs an internalising of the forms of critique that marked 1968 and about which Marcuse writes. It is Ellis's act of double voicing that allows him to develop a duplicitous recalcitrant voice within the state of assimilation and it is double voicing which emerges as the key technique in Ellis's work that effects an ongoing critique in commodity society. Looking at Slavoj iek's recent revisionism of the notion of repressive desublimation, which connects Marxism and psychoanalysis, the essay considers how Ellis's novels, American Psycho, Glamorama and Lunar Park, function to address and reconfigure the relationship between the status of the Marxist fetishised object and the psychoanalytic phobic object in the present-day era of late capitalism. This essay seeks to illuminate how Ellis's fiction, through an involution of Marcuse's political theories, enacts a contemporary refusal from within the state of reification.
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Although originally an academic and research product, the WS-PGRADE/gUSE framework is increasingly applied by commercial institutions too. Within the SCI-BUS project, several commercial gateways have been developed by various companies. WS-PGRADE/gUSE is also intensively used within another European research project, CloudSME (Cloud-based Simulation Platform for Manufacturing and Engineering). This chapter provides an overview and de-scribes in detail some commercial WS-PGRADE/gUSE based gateway implemen-tations. Two representative case studies from the SCI-BUS project, the Build and Test portal and the eDOX Archiver Gateway are introduced. An overview of WS-PGRADE/gUSE based gateways for running simulation applications in the cloud within the CloudSME project is also provided.
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Besides core project partners, the SCI-BUS project also supported several external user communities in developing and setting up customized science gateways. The focus was on large communities typically represented by other European research projects. However, smaller local efforts with the potential of generalizing the solution to wider communities were also supported. This chapter gives an overview of support activities related to user communities external to the SCI-BUS project. A generic overview of such activities is provided followed by the detailed description of three gateways developed in collaboration with European projects: the agINFRA Science Gateway for Workflows for agricultural research, the VERCE Science Gateway for seismology, and the DRIHM Science Gateway for weather research and forecasting.
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Science gateways can provide access to distributed computing resources and applications at very different levels of granularity. Some gateways do not even hide the details of the underlying infrastructure, while on the other end some provide completely customized high-level interfaces to end-users. In this chapter the different granularity levels at which science gateways can be developed with WS-PGRADE/gUSE are analysed. The differences between these various granu-larity levels are also illustrated via the example of a molecular docking gateway and its four different implementations.
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Researchers want to run scientific experiments focusing on their disciplines. They do not want to know how and where the experiments are executed. Science gateways hide details by coordinating the execution of experiments using different infrastructures and workflow systems. ER-flow/SHIWA and SCI-BUS project developed repositories to share artefacts such as applications, portlets, workflows, etc. inside and among research communities. Sharing artefacts in re-positories enable gateway developers to reuse them when building a new gateway and/or creating a new application.
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Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.
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Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology
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In recent years, Deep Learning (DL) techniques have gained much at-tention from Artificial Intelligence (AI) and Natural Language Processing (NLP) research communities because these approaches can often learn features from data without the need for human design or engineering interventions. In addition, DL approaches have achieved some remarkable results. In this paper, we have surveyed major recent contributions that use DL techniques for NLP tasks. All these reviewed topics have been limited to show contributions to text understand-ing, such as sentence modelling, sentiment classification, semantic role labelling, question answering, etc. We provide an overview of deep learning architectures based on Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Recursive Neural Networks (RNNs).