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15,733 results for “article”
Data Files for Tresoldi/Robinson article on spelling variation in Canterbury Tales manuscripts
<p>This data is at <a href="https://github.com/peterrobinson/CTSpellingArticle2024">https://github.com/peterrobinson/CTSpellingArticle2024</a>. It is contained in three folders, each folder corresponding to one of the three sets of data used in this analysis, as follows:</p> <p><strong> </strong></p> <ol> <li> <p>“sorted by regularization”. This folder contains spelling data and results derived from the regularization process, where (for example) spellings of forms regularized to “goode” are distinguished from spellings of forms regularized to “god”;</p> </li> <li> <p>“sorted by part of speech”. This folder contains spelling data and results derived from a lemmatization and part-of-speech identification process, where (for example) spellings of forms lemmatized to “goode” singular adjective are distinguished from spellings of forms regularized to “goode” plural adjective, and forms lemmatized to “gode” singular noun nominative case are distinguished from “gode” singular noun oblique case (as in “to gode”).</p> </li> <li> <p>“all spellings unsorted”. This folder contains spelling data as undifferentiated counts of “bags of words”: for each witness: so many occurrences of “good”, so many of “goode”, so many of “god”, so many of “gode”.</p> </li> </ol> <p><strong> </strong></p> <p>Each folder contains the following files (under various names):</p> <p><strong> </strong></p> <ol> <li> <p>A . json file holding all the data, structured according to its categorization. The “sorted by part of speech” folder contains two .json files, one with spellings organized by headword lemma, the other organized by part-of-speech;</p> </li> <li> <p>Two .nex Nexus files containing all the data. In the “sorted by regularization” and “sorted by part of speech” folders one Nexus file groups spellings by variant sites within each line, the other Nexus file groups spellings by words within each line. In the “all spellings unsorted” folder one Nexus file contains all the spellings organized by spelling; the second holds a Nexus distance matrix with distances created according to the Manhattan distance algorithm;</p> </li> <li> <p>A .dst distance matrix file, containing a distance matrix constructed with distacnes calculated by the Manhattan distance algorithm;</p> </li> <li> <p>A “features” file, containing a spreadsheet ranking each variant site according to its impact on the analysis </p> </li> <li> <p>Multiple .pdf files visualizing the results of our analysis, with the names reflecting the analysis each contains. Files with names including “Splits” were created using the SplitsTree algorithm and software <a href="https://www.zotero.org/google-docs/?peaEav">(Huson and Bryant 2006; “SplitsTree | Universität Tübingen,” n.d.)</a></p> </li> </ol> <p><strong> </strong></p> <p>The “sorted by regularization” folder also contains a single image file, “tiagoplot1.jpg”, visualizing the results of PCA analysis on the “sorted by regularization” data.</p> <p> </p>
Dataset published in the article: "Electrospun poly(L-lactide-co-DL-lactide) nanofibrous scaffold as substrate for ex vivo limbal epithelial cell cultivation"
Open the record for dataset details and reuse information.
Appendices C, D, and E to the A&A article entitled "Revisiting the BE99 method for the study of outflowing gas in protostellar jets"
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data for article "Theory informed, experiment based, constraint on the rate of autoxidation chemistry – An analytical approach"
<p>The files contain the data from simulations shown in plots for main manuscript figures and SI figures. Further, a preliminary autoCONSTRAINT verion to reproduce the results shown is attached and the PyCHAM model used to create CIMS-like inputs to autoCONSTRAINT referenced (model inputs are attached). For any questions on the data contact: office@pi-numerics.com</p> <p>Detailed information on the file content is provided in file "SI_data_description"</p>
Dataset for article: Dizocilpine derivatives as neuroprotective NMDA receptor antagonists without psychomimetic side effects
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Data for the article 'Love numbers for Io with a magma ocean'
<p>Data sets for the article 'Love numbers of Io with a magma ocean'. The given file has the following structure and can be used to generate figures 2-5 in the manuscript</p> <p>Depth l (km) log10(visocisty (Pa s)) Ocean thickness (km) Dissipation (TW) k20 k22c k22s Delta_t20 (h) Delta_t22c (h) Delta_t22s (h).</p> <p>In case of any inquiries, please send an email to aygun@karel.troja.mff.cuni.cz.</p>
Data and Scripts for the Article: Structural Sensitivity of N1s Excitations in N-methylacetamide Solutions
<p>Data and scripts for the article titled: Structural Sensitivity of N1s Excitations in N-methylacetamide Solutions.</p> <p>For further details on the contents, see the "readme.md"-file.</p>
Data and code for articles on the seasonal variation of the DC global electric circuit
<p>In this repository you can find the measurement and modelling data, the research code, and a comprehensive description of the code developed for two papers on the seasonal variation of the DC global electric circuit.</p> <p>First paper (<strong>Part 1: A new analysis based on long-term measurements in Antarctica</strong>) focuses on the seasonal variation of the global electric circuit (GEC) based on electric field measurements at the Vostok station in Antarctica during 2006–2020.</p> <p>Second paper (<strong>Part 2: Further analysis based on simulations</strong>) further analyses the seasonal variation of the GEC on the basis of simulations with models of atmospheric dynamics.</p> <p>An extended description, including a brief overview of the script code and a description of the data files, is provided in the attached archive in the <code>readme.md</code> file.</p>
Crossref relationships between preprints and journal articles
<p>This dataset contains preprint-journal article relationships deposited by publishers with Crossref and/or discovered by an automated preprint matching strategy. It includes preprints and journal articles deposited until the end of February 2025. The following fields are included:</p> <ul> <li>preprint DOI (string)</li> <li>journal article DOI (string)</li> <li>whether the publisher of the journal article deposited this relationship (boolean)</li> <li>whether the publisher of the preprint deposited this relationship (boolean)</li> <li>the confidence score returned by the strategy (float, empty if the strategy did not discover this relationship)</li> </ul> <p>The code of the preprint matching strategy is available <a href="https://gitlab.com/crossref/labs/marple/-/tree/main/strategies_available/preprint_sbmv">here</a>.</p>
Data for article "Personal approach for cancer treatment: a meta-analysis of Phase II Clinical trials"
<p>We conducted systematic review and meta-analysis to provide a comprehensive overview of outcomes in patients who underwent personalized genomics-based versus non-personalized treatment in oncology. The PubMed searches detected 803 studies based on phase II clinical trials’ results published from 2010 to 2021. We selected 50 studies, having 81 arms and 6536 patients for the analysis. We compared Response Rate (RR), medians and 1-year rates of Overall Survival (OS) and Progression-Free Survival (PFS) between genomics-based personalized and non-personalized arms. This repository contains final dataset (Dataset file) and t<span lang="EN-US">he information on 803 studies identified in the literature search (803 studies description file)</span>. </p> <p>The searches, study selection, data extraction and synthesis were performed in accordance to PRISMA (preferred reporting items for systematic review and meta-analysis) guidelines. The research protocol was registered in PROSPERO (International prospective register of systematic reviews, <a href="https://www.crd.york.ac.uk/PROSPERO" rel="nofollow">https://www.crd.york.ac.uk/PROSPERO</a>), record ID CRD42024504021. </p> <p>We performed proportional meta-analysis using the RStudio program, utilizing the R programming language and packages "meta", "metafor," and "tidyverse", the code is available at github: https://github.com/MikhailPot/PreciseOnco_meta-analysis </p>
Data supporting article: "Data-Driven Discovery of the Origins of UV Absorption in Alpha-3C Protein"
<p>The uploaded folder contains data and a python notebook containing code used to plot the figures presented in the article "Data-Driven Discovery of UV Absorption in Alpha-3C Protein"</p>
Dataset for the article "Can we use seismic reflection data to infer the interconnectivity of fracture networks?"
<p>This package contains the effective stiffness coefficients of the fractured rock samples explored in the paper of Rubino et al. "Can we use seismic reflection data to infer the interconnectivity of fracture networks?".</p>
Dataset of the article 'Redox state kinetics in water-oxidation IrOx electrocatalysts measured by operando spectroelectrochemistry'
<p>Data published in the article 'Redox state kinetics in water-oxidation IrO<sub>x</sub> electrocatalysts measured by <em>operando</em> spectroelectrochemistry', <a href="https://doi.org/10.1021/acscatal.1c03290">https://doi.org/10.1021/acscatal.1c03290</a>.</p> <p>Abstract: hydrous iridium oxides (IrO<sub>x</sub>) are the best oxygen evolution electrocatalysts available for operation in acidic environments. In this study, we employ time-resolved <em>operando</em> spectroelectrochemistry to investigate the redox states kinetics of IrO<sub>x</sub> electrocatalyst films for both water and hydrogen peroxide oxidation. Three different redox species involving Ir<sup>3+</sup>, Ir<sup>3.x+</sup>, Ir<sup>4+</sup> and Ir<sup>4.y+</sup> are identified spectroscopically and their concentrations are quantified as a function of applied potential. The generation of Ir<sup>4.y+</sup> states is found to be the potential determining step for catalytic water oxidation, whilst H<sub>2</sub>O<sub>2</sub> oxidation is observed to be driven by the generation of Ir<sup>4+</sup>states. The reaction kinetics for water oxidation, determined from the optical signal decays at open circuit, accelerate from ~ 20 s to < 0.5 s with increasing applied potential above 1.3V <em>vs.</em> RHE (i.e. TOFs per active Ir state increasing from 0.05 to 2 s<sup>-1</sup>). In contrast, the reaction kinetics for H<sub>2</sub>O<sub>2</sub> are found to be almost independent of the applied potential (increasing from 0.1-0.3 s<sup>-1 </sup>over a wider potential window), indicative of a first order reaction mechanism. These spectroelectrochemical data quantify the increase of both the density of active Ir<sup>4.y+</sup> states and the TOFs of these states with applied positive potential, resulting in the observed sharp turn on of catalytic water oxidation current. We reconcile these data with the broader literature while providing a unique kinetic insight into IrO<sub>x</sub> electrocatalytic reaction mechanisms, indicating a first order reaction mechanism for H<sub>2</sub>O<sub>2</sub> oxidation driven by Ir<sup>4+</sup> states, and a higher order reaction mechanism involving the co-operative interaction of multiple Ir<sup>4.y+</sup> states for water oxidation.</p>
Replication Package (Virtual Machine) for article "starMC: an automata based CTL* model checker"
<p>This package is a virtual machine (VM) to execute the starMC programs and benchmark. The system setup is described in the research article "starMC: an automata based CTL* model checker", being published at PeerJ Computer Science (currently accepted). The virtual machine contains both tools and data to reproduce a CTL* model checking logic benchmark. CTL* is a formal logic for the verification of temporal properties of programs.</p> <p>The benchmark is a collection of 1018 model instances (encoded as Petri nets), derived from the Model Checking Context benchmark (https://mcc.lip6.fr/), and about 60.000 CTL, LTL and CTL* queries. It is currently the only large-scale CTL* benchmark for Petri nets publicly available.</p> <p>The starMC-benchmark.ova VM is configured to use 4 CPU cores and 16 GB of RAM. The VM was created with VirtualBox version 5, and tested on a host machine with an 8-core Xeon CPU and 32 GB of RAM. The VM uses the Ubuntu 20 OS, and username and password are both "user". The home directory contains a README file with instructions on how to run the tools, where the benchmark data (models, queries, variable orders) are found, and the script to reproduce the plots in the paper.<br> The starMC.ova contains the tools presented in the paper, for user evaluation and reproducibility.</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
Data for the article "Magnetic Sensitivity Distribution of Hall Devices in Antiferromagnetic Switching Experiments"
<p>Data for the article "Magnetic Sensitivity Distribution of Hall Devices in Antiferromagnetic Switching Experiments" URL: <a href="https://link.aps.org/doi/10.1103/PhysRevApplied.16.064023">https://link.aps.org/doi/10.1103/PhysRevApplied.16.064023</a><br> DOI: 10.1103/PhysRevApplied.16.064023</p>
Data set used for the article "Atmospheric triggers of the Brunt Ice Shelf calving in February 2021"
<p>Data set used for the manuscript "Atmospheric triggers of the Brunt Ice Shelf calving in February 2021". Which is under review in "Geophysical Research Letters" Journal. </p>
Social media articles dataset - article titles and links
<p>This dataset contains the raw results of topic mapping presented at ngi.https://ngitopics.delabapps.eu. </p> <p>The dataset includes the title and link to the collected article, as well as the location on the map. </p> <p>There is a separate dataset for each analysed map: six umbrella topics + 6 regions</p> <p>For details on data collection and methodology see: https://ngitopics.delabapps.eu/report.pdf and https://ngitopics.delabapps.eu/report_multilanguage.pdf</p> <p> </p> <p> </p>
ScienceDex guides
Understand access before you commit
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.