130,917 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
Inhibition of EGFR-AKT axis results in the suppression of ovarian tumors in vitro and in preclinical mouse model
Ovarian cancer is the leading cause of cancer related deaths in women. Genetic alterations including overexpression of EGFR play a crucial role in ovarian carcinogenesis. Here we evaluated the effect of phenethyl isothiocyanate (PEITC) in ovarian tumor cells in vitro and in vivo. Oral administration of 12 μmol PEITC resulted in drastically suppressing ovarian tumor growth in a preclinical mouse model. Our in vitro studies demonstrated that PEITC suppress the growth of SKOV-3, OVCAR-3 and TOV-21G human ovarian cancer cells by inducing apoptosis in a concentration-dependent manner. Growth inhibitory effects of PEITC were mediated by inhibition of EGFR and AKT, which are known to be overexpressed in ovarian tumors. PEITC treatment caused significant down regulation of constitutive protein levels as well as phosphorylation of EGFR at Tyr1068 in various ovarian cancer cells. In addition, PEITC treatment drastically reduced the phosphorylation of AKT which is downstream to EGFR and disrupted mTOR signaling. PEITC treatment also inhibited the kinase activity of AKT as observed by the down regulation of p-GSK in OVCAR-3 and TOV-21G cells. AKT overexpression or TGF treatment blocked PEITC induced apoptosis in ovarian cancer cells. These results suggest that PEITC targets EGFR/AKT pathway in our model. In conclusion, our study suggests that PEITC could be used alone or in combination with other therapeutic agents to treat ovarian cancer. © 2012 Loganathan et al
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
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
A study on the propagation of aero and wind uncertainties and their effect on the dynamic loads of a wind turbine
This work is concerned with the quantification of uncertainties associated with wind turbines. A part form the understanding of the Effects of uncertainties per se, the efficient propagation of uncertainties is necessary for the implementation of robust design optimization methods, which is one of our future goals. Among all possible sources of uncertainties, here uncertainties related to the incoming wind and to the aerodynamic characteristics of the blades are propagated throughout a high-fidelity multibody aeroservoelastic tool. Different techniques, which could all be used for propagating uncertainties other than the ones considered here, are tested and compared. These include different formulations from the family of Non-Intrusive Polynomial Chaos Expansion, as well as Ordinary and Universal Kriging. By running a reduced subset of standard design load cases, a comparison among the various methods is drawn in terms of accuracy and computational efficiency with respect to a standard Monte Carlo approach. It is concluded that, for the uncertain- ties considered here, all approaches lead to a significantly higher performance compared to Monte Carlo, with Universal Kriging slightly standing out. It is also observed that the output parameters exhibit significant variations, and this highlights the importance of a comprehensive framework for the quantification and propagation of uncertainties in wind energy systems
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