130,384 research outputs found
MeSH term explosion and author rank improve expert recommendations
No full textInformation 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
No full textThe 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"
No full textBoth 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
No full textWe 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
An energizing role for motivation in information-seeking during the early phase of the COVID-19 pandemic.
No full textThis project contains code and data related to Abir, Y., Marvin, C. B., van Geen, C., Leshkowitz, M., Hassin, R. R., & Shohamy, D. (2022). An energizing role for motivation in information-seeking during the early phase of the COVID-19 pandemic. Nature Communications, 13(1), 1-10.
It collates a github repository with the code used to run the experiment reported in the main text, and shares the code and data used in producing the figures and statistics reported in the main text and supplementary information. Analyses are implemented on an included docker image with all the software packages necessary to reproduce our findings.
Stored on osf are the outputs of the analysis script, except the figure source csvs which are available with the paper. These outputs are reproduced by the docker image.
To reproduce our analyses, download the folder "covid_paper_shared_docker" as a zip, unzip it on your computer, and follow the instructions in the README.file
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt 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
Domains with transcriptional regulatory activity within the ALL-1, AF4 and AF9 proteins involved in acute leukemia
No full textThe ALL1 gene, located at chromosome band 11q23, is involved in acute leukemia through a series of chromosome translocations and fusion to a variety of genes, most frequently to AF4 and AF9. The fused genes encode chimeric proteins. Because the Drosophila homologue of ALL1, trithorax, is a positive regulator of homeotic genes and acts at the level of transcription, it is conceivable that alterations in ALL1 transcriptional activity may underlie its action in malignant transformation. To begin studying this, we examined the ALL1, AF4, AF9, and AF17 proteins for the presence of potential transcriptional regulatory domains. This was done by fusing regions of the proteins to the yeast GAL4 DNA binding domain and assaying their effect on transcription of a reporter gene. A domain of 55 residues positioned at amino acids 2829-2883 of ALL1 was identified as a very strong activator. Further analysis of this domain by in vitro mutagenesis pointed to a core of hydrophobic and acidic residues as critical for the activity. An ALL1 domain that repressed transcription of the reporter gene coincided with the sequence homologous to a segment of DNA methyltransferase. An AF4 polypeptide containing residues 480-560 showed strong activation potential. The C-terminal segment of AF9 spanning amino acids 478-568 transactivated transcription of the reporter gene in HeLa but not in NIH 31'3 cells. These results suggest that ALL1, AF4, and probably AF9 interact with the transcriptional machinery of the cell
The R&D Tax Incentives
No full textThis 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
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