131,473 research outputs found

    Sexualités et mondialisation. Ouverture

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    Gilbert Elbaz annonce le programme de cette journée d\u27étude, il présente un extrait du curriculum vitae de Louis-Georges Tin (invité d\u27honneur)et termine en exposant son idée sur la sexualité, l\u27homophobie et la mondialisation

    Using actigraphy versus polysomnography in the clinical assessment of chronic insomnia (retrospective analysis of 27 patients)

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    The current study was conducted in order to investigate whether several different methods of characterizing sleep and insomnia symptoms produce different diagnoses. To this aim, we performed a retrospective study in order to compare the outcome of the assessment obtained using polysomnography (PSG) in 27 outpatients complaining of chronic insomnia. Subjects were recruited from a database consisting of patients referred to the sleep centre of the Hotel-Dieu Hospital (Paris) complaining of chronic insomnia. Patients were divided into different groups with regard to type of insomnia. As far as the type of insomnia was concerned, the comparison between actigraphy and PSG showed quite a good contingency coefficient value (C= 0.64). Although this was a preliminary and retrospective study, our results seemed to indicate that actigraphy and PSG were able to lead to a similar output particularly with regard to type of insomnia. Beyond PSG, actigraphy might have a clinical utility in assessing sleep disorders in adults complaining of chronic insomnia

    MeSH term explosion and author rank improve expert recommendations

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    Information overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    "Closing the R&D Gap, Evaluating the Sources of R&D Spending"

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    Both spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.

    A. D. Fricke, author

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    Black and white photograph of author, A. D. Fricke

    Traffic-related air pollution in relation to cognitive function in older adults.

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    BACKGROUND: Few epidemiologic studies have investigated associations of air pollution with cognition in older adults, and none has specifically compared associations across particle sources. We investigated whether exposure to particulate air pollution, characterized by size and source, was associated with cognitive function and decline in cognitive function. METHODS: We included participants of the Whitehall II cohort who were residents of greater London and who attended the medical examination in study wave 2007-2009 (n = 2867). Annual average concentrations of particulate matter (PM) (PM10 and PM2.5 from all sources and from traffic exhaust) were modeled at resolution of 20 × 20 m for 2003-2009. We investigated the relationship between exposure to particles and a cognitive battery composed of tests of reasoning, memory, and phonemic and semantic fluency. We also investigated exposure in relation to decline in these tests over 5 years. RESULTS: Mean age of participants was 66 (standard deviation = 6) years. All particle metrics were associated with lower scores in reasoning and memory measured in the 2007-2009 wave but not with lower verbal fluency. Higher PM2.5 of 1.1 μg/m (lag 4) was associated with a 0.03 (95% confidence interval = -0.06 to 0.002) 5-year decline in standardized memory score and a 0.04 (-0.07 to -0.01) decline when restricted to participants remaining in London between study waves. CONCLUSIONS: This study provides support for an association between particulate air pollution and some measures of cognitive function, as well as decline over time in cognition; however, it does not support the hypothesis that traffic-related particles are more strongly associated with cognitive function than particles from all sources

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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