131,067 research outputs found
MeSH term explosion and author rank improve expert recommendations
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
Asymmetric synthesis of aliphatic 2-hydroxy ketones by enzymatic carboligation of aldehydes
Dominguez de Maria P, Pohl M, Gocke D, et al. Asymmetric synthesis of aliphatic 2-hydroxy ketones by enzymatic carboligation of aldehydes. EUROPEAN JOURNAL OF ORGANIC CHEMISTRY. 2007;2007(18):2940-2944.Benzaldehyde lyase (BAL) and benzoylformate decarboxylase (BFD) catalyse the asymmetric ligation of aliphatic aldehydes to afford enantiomerically enriched 2-hydroxy ketones. Carboligation of linear aldehydes with both enzymes results in high levels of conversion and in enantioselectivities of up to 80 % ee. In cases involving branched aliphatic aldehydes, BAL enables the carboligation of 3-methylbutanal with a high level of conversion and an enantioselectivity of 89 % ee. ((c) Wiley-VCH Verlag GmbH & Co
Going Beyond Counting First Authors in Author Co-citation Analysis
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"
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.
Dispelling the Myths Behind First-author Citation Counts
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
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
Cascading appearance-based features for visual speaker verification
The cascading appearance-based (CAB) feature extraction technique has established itself as the state of the art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the speech recognition application also provide similar improvements for speaker recognition. These results suggest that visual speaker recognition can improve considerable when conducted solely through a consideration of the dynamic speech information rather than the static appearance of the speaker's mouth region
The R&D Tax Incentives
This article sets out some background information and reflections of the author on the R&D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&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&D tax incentives
Silicon uptake by wheat: Effects of Si pools and pH
Silicon (Si), although not considered essential, has beneficial effects on plant growth which are mostly associated with the ability to accumulate amorphous (phytogenic) Si, e.g., as phytoliths. Phytogenic Si is the most active Si pool in the soil–plant system because of its great surface-tovolume ratio, amorphous structure, and high water solubility. Despite the high abundance of Si in terrestrial biogeosystems and its importance, e.g., for the global C cycle, little is known about Si fluxes between soil and plants and Si pools used by plants. This study aims at elucidating the contribution of various soil Si pools to Si uptake by wheat. As pH affects dissolution of Si pools and Si uptake by plants, the effect of pH (4.5 and 7) was evaluated. Wheat was grown on Si-free pellets mixed with one of the following Si pools: quartz sand (crystalline), anorthite powder (crystalline), or silica gel (amorphous). Silicon content was measured in aboveground biomass, roots, and soil solution 4 times in intervals of 7 d. At pH 4.5, plants grew best on anorthite, but pH did not significantly affect Si-uptake rates. Total Si contents in plant biomass were significantly higher in the silica-gel treatment compared to all other treatments, with up to 26 mg g⁻¹ in aboveground biomass and up to 17 mg g⁻¹ in roots. Thus, Si uptake depends on the conversion of Si into plant-available silicic acid. This conversion occurs too slowly for crystalline Si phases, therefore Si uptake from treatments with quartz sand and anorthite did not differ from the control. For plants grown on silica gel, real Si-uptake rates were higher than the theoretical value calculated based on water transpiration. This implies that Si uptake by wheat is driven not only by passive water flux but also by active transporters, depending on Si concentration in the aqueous phase, thus on type of Si pool. These results show that Si uptake by plants as well as plant growth are significantly affected by the type of Si pool and factors controlling its solubility
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