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3,172 results for “Publications”
goChem publication data v1.0
<p>Trajectories and other data for the goChem publication.</p>
Build better LibGuides: A dataset of Political Science, Public Affairs, and International Studies LibGuides
<p>The dataset that accompanies the "Build Better LibGuides" chapter of <em>Teaching Information Literacy in Political Science, Public Affairs, and International Studies</em>. This dataset was created to compare current practices in Political Science, Public Affairs, and International Studies (PSPAIS) LibGuides with recommended best practices using a sample that represents a variety of academic institutions. Members of the ACRL Politics, Policy, and International Relations Section (PPIRS) were identified as the librarians most likely to be actively engaged with these specific subjects, so the dataset was scoped by identifying the institutions associated with the most active PPIRS members and then locating the LibGuides in these and related disciplines. The resulting dataset includes 101 guides at 46 institutions, for a total of 887 LibGuide tabs.</p>
Raw Data files for publication: " A matter of design and coupling: High indoor charging efficiencies with organic solar modules direct coupled to a sodium ion battery"
<p>Supporting raw data for the publication linked below: </p> <p>Inclusive of</p> <ul> <li>spectral data of light sources </li> <li>LED calibration data </li> <li>PV characterization data under LED and AM1.5 </li> <li>battery characterization data and charge-discharge data</li> </ul>
Spike-in and real-world proteomics data sets used in publication of PRONE
<p>Spike-in and real-world data sets used in the evaluation study by Arend et al. (see reference), and some utilized in the vignettes of PRONE, an R package designed for preprocessing, normalization, and performance evaluation of normalization methods of proteomics data. </p> <h3>Overview of the Data Sets</h3> <p>Due to the unavailability of proteomics quantification data from all original publications, data were extracted from alternative sources, which are also listed in the table below. Please refer to the paper's supplementary material and GitHub repository (https://github.com/lisiarend/PRONE.Evaluation) for more comprehensive information on the data sets. A processed metadata file and the protein quantification data file are provided for all data sets. The original quantification data used to generate these two files for each data set are consistently provided in the `original_data` directory of each data set.</p> <p> </p> <div> <table> <tbody> <tr> <td> <p>Data Set</p> </td> <td> <p>Type</p> </td> <td> <p>Quantification Type</p> </td> <td> <p>Raw Data (ID)</p> </td> <td> <p>Quantification Data</p> </td> </tr> <tr> <td> <p>dS1</p> </td> <td> <p>UPS1 spike-in </p> <p>(4 levels)</p> </td> <td> <p>LFQ</p> </td> <td> <p>Tabb et al. <a href="https://www.zotero.org/google-docs/?gkmf6j">[1]</a></p> </td> <td> <p>Välikangas et al. <a href="https://www.zotero.org/google-docs/?Tt81W8">[10]</a> </p> </td> </tr> <tr> <td> <p>dS2</p> </td> <td> <p>UPS1 spike-in </p> <p>(6 levels)</p> </td> <td> <p>LFQ</p> </td> <td> <p>Ramus et al. <a href="https://www.zotero.org/google-docs/?HP8b9X">[2]</a> (PXD001819)</p> </td> <td> <p>Graw et al. <a href="https://www.zotero.org/google-docs/?aiEVfL">[11]</a></p> </td> </tr> <tr> <td> <p>dS3</p> </td> <td> <p>E.coli spike-in </p> <p>(5 levels)</p> </td> <td> <p>LFQ</p> </td> <td> <p>Shen et al. <a href="https://www.zotero.org/google-docs/?zHIDZy">[3]</a></p> <p>(PXD003881)</p> </td> <td> <p>Sticker et al. <a href="https://www.zotero.org/google-docs/?aZ7oZu">[12]</a></p> </td> </tr> <tr> <td> <p>dS4</p> </td> <td> <p>E.coli spike-in </p> <p>(2 levels)</p> </td> <td> <p>LFQ</p> </td> <td> <p>Cox et al. <a href="https://www.zotero.org/google-docs/?scM19M">[4]</a></p> <p>(PXD00279)</p> </td> <td> </td> </tr> <tr> <td> <p>dS5</p> </td> <td> <p>E.coli spike-in </p> <p>(3 levels)</p> </td> <td> <p>TMT 10-plex (1)</p> </td> <td> <p>Zhu et al. <a href="https://www.zotero.org/google-docs/?qAz08E">[5]</a></p> <p>(PXD013277)</p> </td> <td> <p>Phil Wilmarth <a href="https://www.zotero.org/google-docs/?i7xmgP">[13]</a></p> </td> </tr> <tr> <td> <p>dS6</p> </td> <td> <p>yeast spike-in </p> <p>(3 levels)</p> </td> <td> <p>TMT 11-plex (1)</p> </td> <td> <p>O’Connell et al. <a href="https://www.zotero.org/google-docs/?C2XoaJ">[6]</a></p> <p>(PXD007683)</p> </td> <td> <p>Ammar et al. <a href="https://www.zotero.org/google-docs/?UWcyly">[14]</a></p> </td> </tr> <tr> <td> <p>dR1</p> </td> <td> <p>Osteogenic differentiation of hPCLSCs (4 time points)</p> </td> <td> <p>TMT 6-plex (3)</p> </td> <td> <p>Li et al. <a href="https://www.zotero.org/google-docs/?BouGSs">[8]</a> (PXD020908)</p> </td> <td> <p>MaxQuant executed in-house</p> </td> </tr> <tr> <td> <p>dR2</p> </td> <td> <p>Prospective Ovarian JHU Proteome</p> </td> <td> <p>TMT 10-plex (13)</p> </td> <td> <p>Hu et al. <a href="https://www.zotero.org/google-docs/?kVn4pf">[9]</a></p> <p>(PDC000110)</p> </td> <td> <p>MaxQuant executed in-house</p> </td> </tr> <tr> <td> <p>dR3</p> </td> <td> <p>AROM+ transgenic vs. wild-type mice</p> </td> <td> <p>LFQ</p> </td> <td> <p>Vehmas et al. <a href="https://www.zotero.org/google-docs/?qwYM2A">[7]</a></p> <p>(PXD002025)</p> </td> <td> </td> </tr> <tr> <td> <p>dR4</p> </td> <td> <p>Mycobacterium tuberculosis</p> <p>(healthy, disease vs. treated)</p> </td> <td> <p>TMT 10-plex (2)</p> </td> <td> <p>Schmidt et al. <a href="https://www.zotero.org/google-docs/?m1VHIG">[15]</a></p> <p>(PXD030883)</p> </td> <td> </td> </tr> </tbody> </table> </div> <h3>References</h3> <p>[1] D. L. Tabb et al., ‘Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography−Tandem Mass Spectrometry’, J. Proteome Res., vol. 9, no. 2, pp. 761–776, Feb. 2010, doi: 10.1021/pr9006365.<br>[2] C. Ramus et al., ‘Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods’, Data Brief, vol. 6, pp. 286–294, Mar. 2016, doi: 10.1016/j.dib.2015.11.063.<br>[3] X. Shen et al., ‘IonStar enables high-precision, low-missing-data proteomics quantification in large biological cohorts’, Proc. Natl. Acad. Sci., vol. 115, no. 21, pp. E4767–E4776, May 2018, doi: 10.1073/pnas.1800541115.<br>[4] J. Cox, M. Y. Hein, C. A. Luber, I. Paron, N. Nagaraj, and M. Mann, ‘Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ *’, Mol. Cell. Proteomics, vol. 13, no. 9, pp. 2513–2526, Sep. 2014, doi: 10.1074/mcp.M113.031591.<br>[5] Y. Zhu et al., ‘DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis *’, Mol. Cell. Proteomics, vol. 19, no. 6, pp. 1047–1057, Jun. 2020, doi: 10.1074/mcp.TIR119.001646.<br>[6] J. D. O’Connell, J. A. Paulo, J. J. O’Brien, and S. P. Gygi, ‘Proteome-Wide Evaluation of Two Common Protein Quantification Methods’, J. Proteome Res., vol. 17, no. 5, pp. 1934–1942, May 2018, doi: 10.1021/acs.jproteome.8b00016.<br>[7] A. P. Vehmas et al., ‘Liver lipid metabolism is altered by increased circulating estrogen to androgen ratio in male mouse’, J. Proteomics, vol. 133, pp. 66–75, Feb. 2016, doi: 10.1016/j.jprot.2015.12.009.<br>[8] J. Li et al., ‘Dynamic proteomic profiling of human periodontal ligament stem cells during osteogenic differentiation’, Stem Cell Res. Ther., vol. 12, no. 1, p. 98, Feb. 2021, doi: 10.1186/s13287-020-02123-6.<br>[9] Y. Hu et al., ‘Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma’, Cell Rep., vol. 33, no. 3, p. 108276, Oct. 2020, doi: 10.1016/j.celrep.2020.108276.<br>[10] T. Välikangas, T. Suomi, and L. L. Elo, ‘A systematic evaluation of normalization methods in quantitative label-free proteomics’, Brief. Bioinform., vol. 19, no. 1, pp. 1–11, Jan. 2018, doi: 10.1093/bib/bbw095.<br>[11] S. Graw et al., ‘proteiNorm – A User-Friendly Tool for Normalization and Analysis of TMT and Label-Free Protein Quantification’, ACS Omega, vol. 5, no. 40, pp. 25625–25633, Oct. 2020, doi: 10.1021/acsomega.0c02564.<br>[12] A. Sticker, L. Goeminne, L. Martens, and L. Clement, ‘Robust Summarization and Inference in Proteome-wide Label-free Quantification’, Mol. Cell. Proteomics, vol. 19, no. 7, pp. 1209–1219, Jul. 2020, doi: 10.1074/mcp.RA119.001624.<br>[13] ‘understanding_IRS’. Accessed: Mar. 07, 2024. [Online]. Available: https://pwilmart.github.io/IRS_normalization/understanding_IRS.html<br>[14] C. Ammar, M. Gruber, G. Csaba, and R. Zimmer, ‘MS-EmpiRe Utilizes Peptide-level Noise Distributions for Ultra-sensitive Detection of Differentially Expressed Proteins[S]’, Mol. Cell. Proteomics, vol. 18, no. 9, pp. 1880–1892, Sep. 2019, doi: 10.1074/mcp.RA119.001509.<br>[15] F. Biadglegne et al., ‘Mycobacterium tuberculosis Affects Protein and Lipid Content of Circulating Exosomes in Infected Patients Depending on Tuberculosis Disease State’, Biomedicines, vol. 10, no. 4, p. 783, Mar. 2022, doi: 10.3390/biomedicines10040783.</p>
SUSTAINABILITY CLAUSES IN PRIVATE AND PUBLIC CONTRACTS: THE AFTERMATH OF CSDDD
<div> <p><em>On 12 July 2024, SAPIENS Network Early Stage Researcher Ezgi Uysal held a scientific webinar titled "SUSTAINABILITY CLAUSES IN PRIVATE AND PUBLIC CONTRACTS: THE AFTERMATH OF CSDDD." </em></p> <p><em>The webinar featured prominent speakers:</em></p> <ul> <li><em><strong>Kateřina Mitkidis</strong>, a professor at Aarhus University specializing in environmental law, sustainable development, and international business contracts, discussed sustainability clauses in supply chains and strategies for mitigating plastic pollution.</em></li> <li><em><strong>Daniel Schönfelder</strong>, the European Legal Advisor for the Responsible Contracting Project, focused on drafting and disseminating sustainability clauses tailored to the German and European contexts and implementing the German Supply Chain Due Diligence Act.</em></li> <li><em><strong>Martijn Scheltema</strong>, a professor of private law at Erasmus University Rotterdam and partner at Pels Rijcken, explored the enforcement of sustainability considerations in contracts and the development of European Model Contract Clauses.</em></li> </ul> <p><em>Ezgi Uysal, a PhD Researcher at the University of Turin and an Early Stage Researcher at the SAPIENS Network, discussed monitoring and enforcing sustainability clauses in public procurement contracts, the interplay between contract law and public procurement law, and the Corporate Sustainability Due Diligence Directive (CSDDD).</em></p> <p><em>The focus of the webinar was on the incorporation and enforcement of sustainability considerations in contracts, sustainable public procurement under the EU legal framework, and the need for effective contract management. The discussions highlighted new European contract clauses developed for corporate sustainability and the critical interplay between public procurement law and corporate sustainability due diligence. This webinar is particularly relevant for students, newcomers to public procurement, and professionals interested in understanding the latest legal mechanisms for promoting sustainability in supply chains.</em></p> </div> <div> <div> <div> </div> </div> </div>
Phantom SPECT images aasociated with publication
<p>Those DICOM files represent images of various imaging Scienarios. There are two set; clockwise and anticlockwise</p>
Figure 1 from: Kress WJ, Knapp S, Stoev P, Penev L (2018) PhytoKeys at 100: progress in sustainability, innovation, and speed to enhance publication in plant systematics. PhytoKeys 100: 1-8. https://doi.org/10.3897/phytokeys.100.27591
Figure 1 Growth of submitted manuscripts and published articles in PhytoKeys from 2010 to 2018 (until 1.6.2018).
Data for blog post: Are there publications in Mathematics written only by women?
<p>Data for the blog post: <a href="https://nikoleta-v3.github.io/2019/06/women-publications-in-mathematics.html">Are there publications in Mathematics written only by women?</a></p>
Systematic review blockchain, public and accounting
<p>The keywords used for the analysis are "blockchain", "public" and "accounting". The selection of the articles was conducted with an analysis of the metadata on the TUTTO’s database of the University of Turin. The research gave 1954 results focusing attention in the period between 2016 and 2019. Selecting only publications in peer review the results have been reduced to 167. The research presented as a collection of the various databases the following results divided by type of publishing house or database: Scopus (Elsevier)(115), ScienceDirect Journals (Elsevier)(81), Social Sciences Citation Index (Web of Science)(51), Science Citation Index Expanded (Web of Science)(39), Taylor & Francis Online - Journals(16), MEDLINE/PubMed (NLM)(14), Sociological Abstracts(13), SpringerLink Open Access(10), Oxford Journals (Oxford University Press)(10), Sage Journals (Sage Publications)(9), SpringerLink(8), Directory of Open Access Journals (DOAJ)(8), PMC (PubMed Central)(8), Walter De Gruyter Journals/Yearbooks(6), Informa - Taylor & Francis (CrossRef)(6), ACM Digital Library(5), arXiv(4), Arts & Humanities Citation Index (Web of Science)(4), Academic Law Reviews (LexisNexis)(3), HAL (CCSd)(3). Only the sources in English are considered only by reducing the selection to 160 articles. By eliminating the books and duplications the results have been reduced to 156.</p>
Data From: The Future of OA: A large-scale analysis projecting Open Access publication and readership
<p>This is the raw data behind the publication on bioRxiv at https://doi.org/10.1101/795310: </p> <p><strong>Piwowar, Priem, Orr (2019) The Future of OA: A large-scale analysis projecting Open Access publication and readership. bioRxiv: <a href="https://doi.org/10.1101/795310">https://doi.org/10.1101/795310</a></strong></p> <p>The jupyter notebook that produces the manuscript using the data here is available at: <a href="https://github.com/Impactstory/future-oa">https://github.com/Impactstory/future-oa</a></p> <p> </p> <p>Summary:</p> <p>Understanding the growth of open access (OA) is important for deciding funder policy, subscription allocation, and infrastructure planning.</p> <p>This study analyses the number of papers available as OA over time. The models includes both OA embargo data and the relative growth rates of different OA types over time, based on the OA status of 70 million journal articles published between 1950 and 2019.</p> <p>The study also looks at article usage data, analyzing the proportion of views to OA articles vs views to articles which are closed access. Signal processing techniques are used to model how these viewership patterns change over time. Viewership data is based on 2.8 million uses of the Unpaywall browser extension in July 2019.</p> <p>We found that Green, Gold, and Hybrid papers receive more views than their Closed or Bronze counterparts, particularly Green papers made available within a year of publication. We also found that the proportion of Green, Gold, and Hybrid articles is growing most quickly.</p> <p>In 2019:</p> <ul> <li> <p>31% of all journal articles are available as OA</p> </li> <li> <p>52% of article views are to OA articles</p> </li> </ul> <p>Given existing trends, we estimate that by 2025:</p> <ul> <li> <p>44% of all journal articles will be available as OA</p> </li> <li> <p>70% of article views will be to OA articles</p> </li> </ul> <p>The declining relevance of closed access articles is likely to change the landscape of scholarly communication in the years to come.</p>
Figure 1 from: He L, Liao S, Applequist W, Chen S (2019) The valid publication of Salix suchowensis (Salicaceae). PhytoKeys 131: 27-35. https://doi.org/10.3897/phytokeys.131.37065
Figure 1 Salix suchowensis: C.T. Yang 20640 (NF barcode 04801064!, ♂, isolectotype).
m-sized Training and Evaluation Data for Publication "Using Supervised Learning to Classify Metadata of Research Data by Field of Study"
<p>Automated classification of metadata of research data by their discipline(s) of research can be used<br> in scientometric research, by repository service providers, and in the context of research data aggregation<br> services. Openly available metadata of the DataCite index for research data were used to compile a large<br> training and evaluation set comprised of 609,524 records. This is the cleaned and vectorized version with a feature selection of medium size</p>
Micro-Laue diffraction data used in the publication 'Dislocation density distribution at slip band-grain boundary intersections'
<p>The Ti-Bi.xml file is an indexed data set from a differential aperture X-ray micro-Laue diffraction experiment at beamline 34-ID-E, Advanced Photon Source, USA. To obtain strain and rotation field the data need to be feed into LaueGo as specified in <a href="https://www.aps.anl.gov/Science/Scientific-Software/LaueGo">https://www.aps.anl.gov/Science/Scientific-Software/LaueGo</a></p> <p>The GND_data_Zenodo.mat is a Matlab file containing the rotation fields and GND density results. The data structure is explained below:</p> <p>GND_rho_2D and GND_rho_3D are the density of the 33 types of dislocations for all 31 slices of data. Each slice is a 4462x33 matrix where the columns are 33 types of dislocations specified in 'sliplabels'. Each columns has 4462 points giving rise to the 194x23 pixel size image of each slice of data.</p> <p>GND_total_2D and GND_total_3D are the total dislocation density maps in 2D and 3D. Each cell is a slice of the 3D data with 194x23 pixels.</p> <p>For more information, please contact Dr Ben Britton: b.britton@imperial.ac.uk</p>
Work Engagement in the Public Service: a multicultural model
<p><strong>Database of the following article:</strong></p> <p>Abstract</p> <p>The objective of this study is to propose a model to measure work engagement in Brazilian and Portuguese public service. The research is supported by a review of the literature that seeks to delineate the area of organizational behavior, the cross-cultural studies and the hypothetical theoretical model, which presents the ontological vision of the work. The unit of analysis are public institutions of both countries, the sample, which is of the convenience type, was composed of 609 respondents public servants. Three research instruments were used: the Articulación entre la Persona y la organización (APO) of Ramos, Jordão and Morais (2012); the Escala de Satisfação no Trabalho (EST) by Siqueira (2008); and the Utrecht Work Engagement Scale (UWES) tool by Schaufeli, Bakkerand, Salanova (2006). The results did not reject the hypotheses of the model, both of the Portuguese and Brazilian samples, and the comparison between them shows that in general the Portuguese are more satisfied and more engaged in the work than the Brazilians. The exception was observed only in the hypothetical factors Promotion and Salary.</p>
Figure 6 from: Ryvak T, Denysiuk O (2019) Public opinion study on the role of advertising in choice of non-prescription drugs for self-treatment. Pharmacia 66(3): 135-140. https://doi.org/10.3897/pharmacia.66.e35075
Figure 6 What measures, in your opinion, need a drug advertising situation in Ukraine?
Figure 1 from: Ryvak T, Denysiuk O (2019) Public opinion study on the role of advertising in choice of non-prescription drugs for self-treatment. Pharmacia 66(3): 135-140. https://doi.org/10.3897/pharmacia.66.e35075
Figure 1 Characteristics of the contingent of respondents (n=137).
Fig. 4 in Spatial distribution of Culicidae (Diptera) larvae, and its implications for Public Health, in five areas of the Atlantic Forest biome, State of São Paulo, Brazil
Fig. 4. Spatial distribution of the species found in the Santa Alice rural districts.
Fig. 5 in Spatial distribution of Culicidae (Diptera) larvae, and its implications for Public Health, in five areas of the Atlantic Forest biome, State of São Paulo, Brazil
Fig. 5. Semi-variograms of Shannon and Simpson diversity indices.
SPARCS_WP4_Leipzig_City_Total amount of e-buses in public transport
<p>The number of electronic buses used in the city of Leipzig's public transport with annually captured data covering the period between 2021 and 2024.</p>
SPARCS_WP4_Leipzig_City_Total amount of vehicles in public transport
<p>The number of vehicles used in the city of Leipzig's public transport with annually captured data covering the period between 2016 and 2023.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.