1,721,196 research outputs found
An updated cloud-overlap photolysis module for atmospheric chemistry models, UCI Cloud-J v8.0, with near-UV H2O absorption
No full textThis new data set (Cloud-J v8.0) includes near-UV cross sections for water vapor absoprtion that can be used to calculate photolysis rates in atmospheric chemistry models using the new photolysis code UCI Cloud-J version 8.0. This data set and the code that uses it are updated and improved versions of the last published version 7.6c (Prather, Michael; Hsu, Juno, 2019, Solar-J and Cloud-J models version 7.6c, Dryad, Dataset, https://doi.org/10.7280/D1096P). It cleans up some minor bugs (see notes) and now includes the option for water vapor absorption in the ultraviolet region 290-340 nm. The new H2O cross sections are derived from Pei et al. (2019, Water vapor near‐UV absorption: Laboratory spectrum, field evidence, and atmospheric impacts. JGR-Atmos, 124, 14,310–14,324. doi: 10.1029/2019JD030724). With these new H2O cross sections, more solar UV is absorbed in the lower atmomsphere and many major photolysis rates are reduced by 10% near the surface. We estimate that the lifetime of methane will increase by 7%.
Note (30 May 2023). An error in the calculation of Ice Water Path [IWP(L)] in the standalone driver code for Cloud-J versions 7.6 through 8.0 has been discovered. This does not affect any of the results or example output archived here because the calculations of with and without UV H2O absorption were done with clear skies. A corrected version 8.0c is posted. The corrected code line goes from "IWP(L) = 1000.d0*WIC(L)*PDEL*G100 / CLF(L)" to "IWP(L) = 1000.d0*WIC(L)*PDEL*G100"The primary dataset (FJX_spec.dat) can be opened and read with any editor. The use of this data to calculate photolysis rates (J-values) requires the Cloud-J v8.0 FORTRAN F90 source code and a FORTRAN compiler. No special libraries are needed. A standalone version of the code and necessary data tables are provided in the Zenodo software archive linked to this Dryad data DOI.Funding provided by: NASA HeadquartersCrossref Funder Registry ID: http://dx.doi.org/10.13039/100017437Award Number: 80NSSC21K1454Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: AGS-2135749The dataset was taken directly from the Pei et al. 2019 published tables and then re-mapped onto the Cloud-J wavelength bins
An updated cloud-overlap photolysis module for atmospheric chemistry models, UCI Cloud-J v8.0, with near-UV H2O absorption
No full text<p>This new data set (Cloud-J v8.0) includes near-UV cross sections for water vapor absoprtion that can be used to calculate photolysis rates in atmospheric chemistry models using the new photolysis code UCI Cloud-J version 8.0. This data set and the code that uses it are updated and improved versions of the last published version 7.6c (Prather, Michael; Hsu, Juno, 2019, Solar-J and Cloud-J models version 7.6c, Dryad, Dataset, <a href="https://doi.org/10.7280/D1096P">https://doi.org/10.7280/D1096P</a>). It cleans up some minor bugs (see notes) and now includes the option for water vapor absorption in the ultraviolet region 290-340 nm. The new H<sub>2</sub>O cross sections are derived from Pei et al. (2019, Water vapor near‐UV absorption: Laboratory spectrum, field evidence, and atmospheric impacts. JGR-Atmos, 124, 14,310–14,324. doi: 10.1029/2019JD030724). With these new H2O cross sections, more solar UV is absorbed in the lower atmomsphere and many major photolysis rates are reduced by 10% near the surface. We estimate that the lifetime of methane will increase by 7%. </p>
<p>Note (30 May 2023). An error in the calculation of Ice Water Path [IWP(L)] in the standalone driver code for Cloud-J versions 7.6 through 8.0 has been discovered. This does not affect any of the results or example output archived here because the calculations of with and without UV H2O absorption were done with clear skies. A corrected version 8.0c is posted. The corrected code line goes from "IWP(L) = 1000.d0*WIC(L)*PDEL*G100 / CLF(L)" to "IWP(L) = 1000.d0*WIC(L)*PDEL*G100"</p><p>The primary dataset (FJX_spec.dat) can be opened and read with any editor. The use of this data to calculate photolysis rates (J-values) requires the Cloud-J v8.0 FORTRAN F90 source code and a FORTRAN compiler. No special libraries are needed. A standalone version of the code and necessary data tables are provided in the Zenodo software archive linked to this Dryad data DOI.</p><p>Funding provided by: NASA Headquarters<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100017437<br>Award Number: 80NSSC21K1454</p><p>Funding provided by: National Science Foundation<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001<br>Award Number: AGS-2135749</p>
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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