305,390 research outputs found
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
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
Multiresolution spectral–element representations of electronic wave functions
No full textOne of the grand challenges of quantum chemistry is computing observables (energies, scattering cross–sections, response properties) and their confidence intervals with high precision. This requires fast methods, characterized by a low–order scaling of the computational cost with the system size and error. Despite significant advances in the area, we are still very far from this goal. This talk will address some of our recent work on fast methods, with the word fast referring to the scaling with precision (i.e. the discretization error) and with the system size. Specifically, I will discuss our efforts to compute two–particle wave functions in hierarchical (multiresolution) discontinuous spectral–element representations. [1, 2] Each volume element of the six–dimensional wave function is supported by an orthonormal basis set of tensor products of polynomials. To alleviate the severe (exponential) cost of finite–element representation in many dimensions, which makes precise representation and computation of correlated wave functions intractable, we use low–rank tensor approximations, namely the singular value decomposition SVD, and reformulate all operations necessary to solve the Schr ̈odinger equation in low–rank form. [3] The low-rank approximations alone are not sufficient; hence we use explicitly–correlated terms in the wave function to regularize the electron–electron Coulomb singularities of the Hamiltonian. Our approach does not assume any geometric symmetry, hence the method is tractable for molecules. [2] The method was used to compute the first–order Møller-Plesset wave function and the second-order energy of the helium atom with precision guaranteed by construction (our most precise value for the MP2 energy is −37.379 mEh). We will further highlight the strengths and weaknesses of the adaptive discretization strategy.
[1] F. A. Bischoff, R. J. Harrison, and E. F. Valeev, J. Chem. Phys. 137, 104103 (2012). [2] F.A.BischoffandE.F.Valeev,inpreparation.
[3] F. A. Bischoff and E. F. Valeev, J. Chem. Phys. 134, 104104 (2011).Non UBCUnreviewedAuthor affiliation: Virginia TechFacult
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
Comb-e-Chem: an e-science research project
No full textThe background to the Comb-e-Chem e-Science pilot project funded under the UK-Science Programme is presented and the areas being addresses within chemistry and more specifically combinatorial chemistry are discussed. The ways in which the ideas underlying the application of computer technology can improve the production, analysis and dissemination of chemical information and knowledge in a collaborative environment are discussed
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
Multi-omics “upstream analysis” of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer
No full textAbstractWe present an “upstream analysis” strategy for causal analysis of multiple “-omics” data. It analyzes promoters using the TRANSFAC database, combines it with an analysis of the upstream signal transduction pathways and identifies master regulators as potential drug targets for a pathological process. We applied this approach to a complex multi-omics data set that contains transcriptomics, proteomics and epigenomics data. We identified the following potential drug targets against induced resistance of cancer cells towards chemotherapy by methotrexate (MTX): TGFalpha, IGFBP7, alpha9-integrin, and the following chemical compounds: zardaverine and divalproex as well as human metabolites such as nicotinamide N-oxide
Mining e-mail content for author identification forensics
No full textWe describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different email topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation
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