131,220 research outputs found
Handbook on advanced methods and processes in Oxidation Catalysis, From Laboratory to Industry
No full textThis book offers a comprehensive overview of the most recent developments in both total oxidation and combustion and also in selective oxidation. For each topic, fundamental aspects are paralleled with industrial applications. The book covers oxidation catalysis, one of the major areas of industrial chemistry, outlining recent achievements, current challenges and future opportunities. One distinguishing feature of the book is the selection of arguments which are emblematic of current trends in the chemical industry, such as miniaturization, use of alternative, greener oxidants, and innovative systems for pollutant abatement. Topics outlined are described in terms of both catalyst and reaction chemistry, and also reactor and process technolog
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
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
Experimental vaccination for onchocerciasis and the identification of early markers of protective immunity
No full textOnchocerciasis, caused by Onchocerca volvulus remains a major public health and
socio-economic problem across the tropics, despite years of mass drug administration
(MDA) with Ivermectin to reduce disease burden. Through modelling, it has been
shown that elimination cannot be achieved with MDA alone and additional tools are
needed, such as vaccination, which remains the most cost-effective tool for long-term
disease control. The feasibility behind vaccination against O. volvulus can be
demonstrated in the Litomosoides sigmodontis mouse model, which shows that
vaccine induced protection can be achieved with immunisation using irradiated L3, the
infective stage of L. sigmodontis and with microfilariae (Mf), the transmission stage
of the parasite. There is further evidence of protective immunity in humans, with
individuals living in endemic areas that show no signs of infection despite being
exposed to the parasite (endemic normal).
The protective efficacy of promising vaccine candidates were evaluated using an
immunisation time course in the L. sigmodontis model, using either DNA plasmid or
peptide vaccines. In immunisation experiments in L. sigmodontis, Mf numbers are
used as a measure of protection and marks the end of an immunisation time course.
However, when changes in gene expression were measured at the end of an
immunisation time course, in attempts to identify gene signatures that could be used
as markers of protection (correlates of protection) in the blood, no gene signatures were
found to be associated with protection. This suggest that at the end of an immunisation
time course, when protection is measured (change in Mf numbers), it is too late in
infection to measure changes in immune pathways being triggered. Changes in gene expression were therefore measured in blood samples collected
throughout an immunisation time course in the L. sigmodontis model, in order to
identify the time point in an immunisation experiment which are the most indicative
of protection. Two independent immunisation time courses were used, either using
irradiated L3 or Mf as vaccine against L. sigmodontis, as these elicit the greatest
protection. This generated a large high dimensional dataset, that was too large and
complex for a differential fold-change analysis. Therefore, an analysis pipeline was
created using machine learning algorithms, to detect changes in gene expression
throughout the time courses to detect markers of protection.
The 6 hour time point following immunisation showed the greatest change in gene
expression, with the analysis pipeline identifying known pathways associated with
vaccine-induced immunity. The pipeline was applied to gene expression data from
human samples obtained from individuals living in endemic areas who were either
infected with O. volvulus or endemic normal (naturally protected), this was to identify
pathways associated with protective immunity in humans. When comparing vaccine
induced immunity seen in mice and natural protective immunity in humans there was
some overlap in pathways being triggered, suggesting that similar pathways are needed
for protection and that if a vaccine can trigger the right pathways in mice, it is likely
to be effective in humans.
Overall the machine learning analysis of the gene expression data, not only shows that
it is feasible to measure change in gene expression in blood during filarial infections,
but that during an immunisation time course it is the early time points following
immunisation that are the most predictive of vaccine efficacy (protection outcome). One of the vaccine candidates, cysteine protease inhibitor-2 (CPI), is a known
immuno-modulator that inhibits MHC-II antigen presentation on antigen presenting
cells such as dendritic cells (DC). This candidate has consistently been shown to
induce protection if its immuno-modulatory active site was modified. In in vitro
studies, it was shown that modification of the active site of CPI rescues antigen
presentation in DC. This shows the importance of DC activation before the onset of
infection, demonstrating the importance of triggering protective responses early in
infection, and provides insight on how one of the vaccine candidates achieves
protection
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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