44 resultados para Resources texts
em Université de Lausanne, Switzerland
Resumo:
Seventeen innovative studies are collected in this volume which has been produced under the aegis of the Centre for Biblical Studies, University of Manchester, and L'Institut des sciences bibliques, Université de Lausanne. The majority of the studies engage with narrative through providing insightful working examples. Building on the many contributions of recent narratological research, for the most part the studies in this collection avoid the technical language of narratology as they present fresh insights at many levels. Some essays focus more on the implied author, some on the implied reader or hearer, and some on the way particular messages are constructed; some of the studies consider how author, message and reader are all interconnected. There are several creative proposals for refining genre definition, from law and wisdom to gospel and apocryphal writings. Some studies highlight the way in which narratives can contain ethical, religious, and cultural messages. Sensitivity to narrative is also shown by some contributors to expose in intruing ways the redactional processes behind the final form of texts. Students of narrative in the ancient world will find much to consider in this book, and others engaged with literary studies more generally will discover that scholars of the worlds of the Bible and Late Antiquity have much to offer them.
Resumo:
Although stress has been a longstanding issue in organizations and management studies, it has never been studied in relation to Public Service Motivation. This article therefore aims to integrate PSM into the job demands-job resources model of stress in order to determine whether PSM might contribute to stress in public organizations. Drawing upon original data from a questionnaire in a Swiss municipality, this study unsurprisingly shows that "red tape" is an antecedent of stress perception, whereas satisfaction with organizational support, positive feedback, and recognition significantly decrease the level of perceived stress. Astonishingly, the empirical results show that PSM is positively and significantly related to stress perception. By increasing individuals' expectations towards their jobs, PSM might thus contribute to increased pressure on public agents. Ultimately, this article investigates the "dark side" of PSM, which has been neglected by the literature thus far.
Resumo:
This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.
Resumo:
This contribution, based on a statistical approach, undertakes to link data on resources (personnel and financial means) and the working of the administration of penal justice (prosecution, sentencing) taking into account the nationality of those prosecuted. In order to be able to distinguish prosecution and sentencing practices of judicial authorities and possible processes of discrimination, diverse sources have been used such as data from court administrations, public finances and police forces, collected by the Swiss Federal Statistical Office and the Swiss Federal administration of finances. The authors discuss discrimination in prosecution and sentencing between Swiss residents and foreigners taking into account localization and resources regarding personnel and public finances.
Resumo:
OBJECTIVES: To assess whether patients' characteristics and healthcare resources consumption and costs were different between native and migrant populations in Switzerland. METHODS: All adult patients followed-up in the Swiss HIV-cohort study in our institution during 2000-2003 were considered. Patients' characteristics were retrieved from the cohort database. Hospital and outpatient resource use were extracted from individual charts and valued with 2002 tariffs. RESULTS: The 66 migrants were younger (29 +/- 8 years versus 37 +/- 11, p < 0.001), less often of male gender (38 % versus 70 %, p < 0.001), predominantly infected via heterosexual contact (87 % versus 52 %, p < 0.01), with lower mean CD4 level at enrollment (326 +/- 235 versus 437 +/- 305, p = 0.002) than their 200 native counterparts. Migrants had fewer hospitalizations, more frequent outpatient visits, laboratory tests, and lower total cost of care per year of follow-up (<euro> 2'215 +/- 4'206 versus 4'155 +/- 12'304, p = 0.037). Resource use and costs were significantly higher in people with < 200 CD4 cell counts in both groups. CONCLUSIONS: Migrant population had more advanced disease, more outpatient visits but less hospitalizations, resulting in lower costs of care when compared with native population.
Resumo:
Latin medical texts transmit medical theories and practices that originated mainly in Greece. This interaction took place through juxtaposition, assimilation and transformation of ideas. 'Greek' and 'Roman' in Latin Medical Texts studies the ways in which this cultural interaction influenced the development of the medical profession and the growth of knowledge of human and animal bodies, and especially how it provided the foundations for innovations in the areas of anatomy, pathology and pharmacology, from the earliest Latin medical texts until well into the medieval world.
Resumo:
Access to online repositories for genomic and associated "-omics" datasets is now an essential part of everyday research activity. It is important therefore that the Tuberculosis community is aware of the databases and tools available to them online, as well as for the database hosts to know what the needs of the research community are. One of the goals of the Tuberculosis Annotation Jamboree, held in Washington DC on March 7th-8th 2012, was therefore to provide an overview of the current status of three key Tuberculosis resources, TubercuList (tuberculist.epfl.ch), TB Database (www.tbdb.org), and Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org). Here we summarize some key updates and upcoming features in TubercuList, and provide an overview of the PATRIC site and its online tools for pathogen RNA-Seq analysis.