130,657 research outputs found

    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

    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

    Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund

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    At the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far

    Tree indexed Markov processes and long range dependency

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    Langford B. White and Sylvie L. Perrea

    High postprandial triglyceridemia in patients with type 2 diabetes and microalbuminuria

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    Microalbuminuria ( MA) is an independent risk factor for atherosclerosis in patients with type 2 diabetes mellitus (T2DM). Postprandial lipemia is also associated with excess cardiovascular risk. However, the association between MA and postprandial lipemia in diabetes has not been investigated. A total of 64 patients with T2DM, 30 with and 34 without MA, were examined. Plasma total triglycerides (TGs), triglycerides contained in chylomicrons (CM-TG), and TGs in CM-deficient plasma were measured at baseline and every 2 h for 6 h after a mixed meal. Postheparin LPL and HL activities were also determined. Plasma levels of apolipoprotein A-V (apoA-V), apoC-II, and apoC-III were measured in the fasting state and 2 h postprandially. Patients with MA had higher postprandial total TG levels than those without MA (P < 0.001); this increase been attributed mainly to CM-TG. LPL activity and fasting concentrations of the measured apolipoproteins were not different between the studied groups, whereas HL activity was higher in the patients with MA. ApoC-II and apoC-III levels did not change postprandially in either study group, whereas apoA-V increased more in the patients with MA. These data demonstrate for the first time that MA is characterized by increased postprandial lipemia in patients with T2DM and may explain in part the excess cardiovascular risk in these patients. -Tentolouris, N., A. Stylianou, E. Lourida, D. Perrea, D. Kyriaki, E. C. Papavasiliou, A. D. Tselepis, and N. Katsilambros. High postprandial triglyceridemia in patients with type 2 diabetes and microalbuminuria.Journal of Lipid Researc

    The R&D Tax Incentives

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    This article sets out some background information and reflections of the author on the R&amp;D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&amp;D through ad hoc tax incentives included in the CCTB Proposal and dives into the actual provisions included in the Proposal highlighting the most relevant issues connected with their design and interpretation. Moreover, the author explores the interaction between the CCTB Proposal and the granting by Member States of domestic R&amp;D tax incentives
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