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15,733 results for “article”
Fine-grained classification of journal articles by relying on multiple layers of information through similarity network fusion: the case of the Cambridge Journal of Economics
<p>prova</p>
Marathi News Article Text Dataset
<p>The Marathi News Article Text Dataset (MNATD) consists of meticulously curated news articles in the Marathi language, sourced from various online platforms. With a substantial collection exceeding over 6.5 Lakh articles, this dataset provides a thorough exploration of the Marathi news landscape. Encompassing diverse subjects such as Politics, Astrology , sports, and more, MNATD offers a comprehensive representation of the Marathi news domain. Researchers and enthusiasts will find this dataset valuable for delving into the linguistic and thematic richness of Marathi journalism. MNATD aims to contribute to a nuanced understanding of the Marathi news landscape and serve as a valuable resource for linguistic analysis and research.</p>
Alexander von Humboldts unpublished essays and articles
<p>This table is a collection of unpublished essays and articles by Alexander von Humboldt from his estate in the Berlin State Library and the Jagiellonian Library in Krakow. The table contains information on the titles, the authors, the language in which they were written and, where available, links to digital copies. </p> <p>The works listed here are articles and essays which Humboldt clearly intended for publication but which were not published, as well as works for which the intention of publication is unclear. The degree of maturity of the works varies, ranging from manuscripts ready for publication to fragmentary drafts. Most of the works listed here have not yet been published. </p>
Dataset for the article titled ""An Updated Parameterization of the Unstable Atmospheric Surface Layer in WRF Modeling System"".
<p>The dataset is organized in to five ZIP folders as described below:</p> <p>1. Offline_Exp_Data: This contains data for stability parameter (z/L), transfer coefficient for momentum (CD), and heat (CH) simulated from different experiments using the bulk flux algorithm (offline mode) corresponding to different similarity functions over smooth (z0 = 0.01 m), transition (z0 = 0.1 m), and rough (z0 = 1 m) surfaces. This dataset corresponds to Figure 4.</p> <p>2. Similarity_Functions: This contains data for the similarity functions for momentum and heat in gradient (Phi_m and Phi_h) as well as integrated (Psi_m and Psi_h) forms with stability parameter (z/L) for considered functional forms of similarity functions (e.g., Businger et al., 1971 (BD71); Carl et al., 1973 (CL73); Kader and Yaglom, 1990 (KY90); and Fairall et al., 1996 (F96)) under unstable conditions. The dataset corresponds to Figures 2 and S1 (supporting information).</p> <p>3. WRF_Data1: This contains hourly averaged data for considered variables from WRF model simulations during the MAM (March–April–May) season. This dataset can be used to reproduce Figures 9, 10, and 11.</p> <p>4. WRF_Data2: This contains model output for considered variables extracted during highly convective hours (z/L<-10 over most of the domain) in the daytime. This dataset can be used to reproduce Figures 12, S3, S4, S5, and S6.</p> <p>5. WRF_Data3: This consists of data from different simulations (CTRL, Exp1-4) with the WRF model extracted at the location of the flux tower (23.412 N, 85.44 E (Ranchi), India). The dataset contains stability parameter (z/L), bulk Richardson number (RiB), transfer coefficients for momentum (CD) and heat (CH), sensible heat flux (HFX), 10-m wind speed (WS), u*2 (representative of momentum flux), and 2-m temperature (T2m). This dataset corresponds to Figures 5, 6, 7, 8, S2, S7, and S8.</p>
Additional material for the article "Widespread fracture movements during a volcano-tectonic unrest: the Reykjanes Peninsula, Iceland, from 2019–2021 TerraSAR-X interferometry"
<p><span>Additional Material for the article "Widespread fracture movements during a volcano-tectonic unrest: the Reykjanes Peninsula, Iceland, from 2019–2021 TerraSAR-X interferometry" published in Bulletin of Volcanology (<a href="https://doi.org/10.1007/s00445-023-01699-0" target="_blank" rel="noopener">https://doi.org/10.1007/s00445-023-01699-0</a>).<br></span></p> <p> </p> <p><span>Description of the content in the zip folder:</span></p> <p><span>The georeferenced mapped discontinuities are listed in text files that are classed </span><span>by interferogram date and track. Each file contains a list of longitude and lati</span><span>tude values of the mapped fractures, with the beginning of each fracture trace</span><span> </span><span>annotated by a line starting with ">" and the fracture ID (i.e., the number of </span><span>the fracture starting at 1 in each file), the QI (1, 2 or 3), the estimated sense of</span><span> </span><span>motion (N for normal or SL for strike-slip), and the indicative LOS amplitude</span><span> </span><span>of motion.</span></p>
Data of top 50 most cited articles about COVID-19 and the complications of COVID-19
<p><strong>Background</strong></p> <p>This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems.</p> <p><strong>Methods</strong></p> <p>Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact factor, authors, study details, and patient demographics.</p> <p><strong>Results</strong></p> <p>The focus is primarily on 2020 publications (96%), with all articles being open-access. Leading journals include The Lancet, NEJM, and JAMA, with prominent contributions from Internal Medicine (46.9%) and Pulmonary Medicine (14.5%). China played a major role (34.9%), followed by France and Belgium. Clinical features were the primary study topic (68%), often utilizing retrospective designs (24%). Among 22,477 patients analyzed, 54.8% were male, with the most common age group being 26–65 years (63.2%). Complications affected 13.9% of patients, with a recovery rate of 57.8%.</p> <p><strong>Conclusion</strong></p> <p>Analyzing these top-cited articles offers clinicians and researchers a comprehensive, timely understanding of influential COVID-19 literature. This approach uncovers attributes contributing to high citations and provides authors with valuable insights for crafting impactful research. As a strategic tool, this analysis facilitates staying updated and making meaningful contributions to the dynamic field of COVID-19 research.</p>
Data supporting the article "Replication of extinction retrieval prediction by prefrontal reactivations and non-replication of L-DOPA effects on retrieval and reactivations in males"
<p>These datasets contain sAA, sCORT, US expectancy, questionnaire and rating raw data generated in this replication study. Furthermore, the processed MRI data (vmPFC reactivations) and derived SCR data are available. The custom-made analysis script for scoring SCR can be run on Matlab 2015b.</p>
Dataset for the article entitled: "Revealing the strengthening contribution of stacking faults, dislocations and grain boundaries in severely deformed LPBF AlSi10Mg alloy"
<p>Dataset includes:</p> <p>EBSD data:</p> <p>AlSi10Mg_HT320.ang - Heat treated sample</p> <p>HT320E100.ang - Heat treated ECAP processed sample</p> <p>TKD data:</p> <p>HT320E100.ang - Heat treated ECAP processed sample</p> <p>XRD data:</p> <p>AlSi10Mg_HT320.ASC - Heat treated sample</p> <p>AlSi10Mg_HT320_ECAP100.ASC - Heat treated ECAP processed sample</p>
Supplementary Materials of the article:The relationship between circulating inflammatory proteins mediating gut microbiota and postherpetic neuralgia: A Mendelian Randomization study
Open the record for dataset details and reuse information.
Reduced Gun Violence Frame Corpus data set for the Text2Story 2024 article: "Evaluating the Ability of Computationally Extracted Narrative Maps to Encode Media Framing"
<p><strong>Title: </strong>Simplified Gun Violence Frame Corpus (GVFC) Subset</p> <p><strong>Description:</strong><br>This data set is a simplified subset of the Gun Violence Frame Corpus (GVFC) from Liu et al. (2019). The original GVFC consists of 1300 news articles in English from multiple U.S. based sources extracted during the year 2018, focusing on media frames commonly used when reporting the issue of Gun Violence. The original data set has 9 types of frames, including both issue-specific and generic frames. Due to high computational costs in our analysis methods, we decreased the data set size from 1300 articles to 131 articles using stratified sampling, maintaining the original distribution of the frame labels. We also manually searched for the original sources of each article based on its headline and added the missing temporal information and news source to the data set, as it was required by our algorithms.</p> <p>To further reduce the complexity of the framing model and account for the smaller data set size, we grouped the original nine frames into three higher-level frames:</p> <p>1. Frame 1: Political Issues - Combining the first, second, and third frames, which focus on political issues mostly related to gun control.<br>2. Frame 2: Public Services - Combining the fourth and fifth frames, which focus on mental healthcare issues, as well as school and public safety.<br>3. Frame 3: Cultural and Societal Issues - Combining the last four frames, which are oriented towards cultural or societal issues, including discussions around race and ethnicity, public opinion, and economic consequences.</p> <p>The resulting simplified data set contains 131 news articles, each labeled with one of the three higher-level frames, along with the necessary temporal information and news source for the narrative extraction process.</p> <p>If you use this data set, please make sure to cite the original GVFC paper and our workshop paper please. </p> <p><strong>References:</strong></p> <ol> <li>Liu et al. (2019) "Detecting Frames in News Headlines and Its Application to Analyzing News Framing Trends Surrounding US Gun Violence", 23rd Conference on Computational Natural Language Learning (CoNLL 2019).</li> <li>Concha Macías, Sebastián and Keith Norambuena, Brian (2024). "Evaluating the Ability of Computationally Extracted Narrative Maps to Encode Media Framing", Text2Story 2024 Workshop, ECIR 2024.</li> </ol>
Supplementary Tables S1-S5 for an article "Square Antiprismatic Chelation Is a Key Determinant for Potassium Ion Selectivity"
<p>This file contain tables S1-S5 for the supporting information from the original paper. These tables describe potassium binding sites indentifieid in potassium channels, other membrane proteins and randomly chosen non-membrane proteins. (See the article text for details)</p> <p> </p>
Supplementary material of article "Stem-loop-induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control"
Open the record for dataset details and reuse information.
Data and R scripts supporting the article: "Evolution of genetic (co)variances during the worldwide invasion of Drosophila suzukii"
<p>This repository contains raw data, processed data (.RData files) and R scripts necessary to replicate the analyses, figures and tables from the manuscript "Evolution of genetic (co)variances during the worldwide invasion of Drosophila suzukii" (Fraimout, A., Chantepie, S., Navarro, N., Teplitsky, C. & Debat, V.).</p> <p>Each R script contains detailed information about the location of each analysis in the manuscript (i.e., line numbering and paragraph title as in Fraimout et al. 2024: https://www.biorxiv.org/content/10.1101/2024.01.02.573869v1)</p>
Data for article: Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists
<p><strong>### Update 03/02/2025: the most up to date version of the processing pipeline presented here, also working on Linux, is available on github: https://github.com/fischer-fjd/GCA/tree/main, and a worked example with open data from the Dutch AHN surveys is available on Zenodo: https://zenodo.org/records/14722001 ###<br></strong></p> <p>This is a collection of scripts and research data to assess the robustness of forest structure characterization from airborne laser scanning (ALS). It accompanies the article "Robust characterization of forest structure from airborne laser scanning – a systematic assessment and sample workflow for ecologists" (accepted in Methods in Ecology and Evolution on 25/08/2024). </p> <p>In the article, we assess the derivation of canopy height models (CHMs) from point cloud data, how sensitive CHM algorithms are to point cloud degradation (pulse density thinning, large scan angles, loss of higher-order returns) and how uncertainties and biases propagate to commonly used forest structure metrics. In addition, we provide a standardized processing pipeline in R to convert point clouds into CHMs. </p> <p>The main data source for this study are ALS point clouds from nine Australian research sites belonging to the Terrestrial Ecosystem Research Network (TERN, 5 km x 5 km extent each). The underlying data can be found here: https://portal.tern.org.au/metadata/TERN/4ff0b4c9-cfa0-4d09-9520-b5402adc583f. For one site (Robson Creek), we also used field data to assess the sensitivity of aboveground biomass estimates to ALS point cloud characteristics. Data are available here: https://portal.tern.org.au/metadata/supersite.174. </p> <p>To characterize climatic/environmental differences between sites, we used climatic data from the CHELSA/BIOCLIM+ climatology 1981-2010 (Brun et al. 2022: Global climate-related predictors at kilometer resolution for the past and future. Earth System Science Data, 14(12), 5573–5603. https://doi.org/10.5194/essd-14-5573-2022; Karger et al. 2017: Climatologies at high resolution for the earth's land surface areas. Scientific Data, 4(1), 170122. https://doi.org/10.1038/sdata.2017.122). </p> <p>We note that the enormous size of the full set of manipulated point clouds (original + thinned + individual flightlines: ~400 GB) and the derived raster products (~200 GB) by far exceeds limits on data storage in Zenodo. However, all analyses can be recreated from scratch from the openly available data and the R code in this repository. In addition, we include derived products for the nine study sites that allow to replicate results in the main text without any point cloud processing (CHMs and other rasters across thinned point clouds + summary statistics). </p> <p>The different data layers are:</p> <p><strong>01_rscripts.zip:</strong></p> <ul> <li>contains a sample script to test the processing pipeline (<em>test.processing.R</em>) as well as a collection of helper functions (<em>ALS_processing_helperfunctions_v40.R</em>); the script can be run directly after unzipping the folder, but an installation of LAStools (https://rapidlasso.de) is necessary (path_lastools = "PATH/TO/LASTOOLS/BIN"); we note that the script was developed on Windows PCs, its application with the recent Linux distribution of LAStools has not yet been tested</li> <li>contains the full set of scripts necessary to reproduce the analyses, including point cloud manipulations and derivation of CHMs from the raw data (<em>create.CHMs.R)</em> as well as the overall robustness analysis (<em>analyze.CHMs.R</em>); to replicate the processing of the raw point clouds step by step, .laz files should be downloaded from the TERN repository (cf. citation above) and placed in a "data" folder, with subfolders for each site and with the same naming conventions as in this repository (e.g., "/data/Alice Mulga")</li> </ul> <p><strong>02_reference.zip</strong></p> <ul> <li>contains reference digital surface models (DSMs), canopy height models (CHMs) and digital terrain models (DTMs) for all nine TERN sites, based on the original ALS point clouds</li> <li>note that these reference layers are produced with the "CHMhighest" algorithm, which provides an easily interpretable canopy description as long as pulse densities are high (>= 20 shots per squaremetre)</li> </ul> <p><strong>03_climate.zip</strong></p> <ul> <li>contains site coordinates</li> <li>contains the climate layers from the CHELSA climatology (cf. citation above, only used to evaluate climatic ranges of sites)</li> </ul> <p><strong>04_robson_additional.zip</strong></p> <ul> <li>contains biomass estimates for Robson Creek</li> <li>contains shapefiles for large trees at Robson Creek (only used for visualization purposes)</li> </ul> <p><strong>05_downsampling_pulse_[Site name].zip</strong></p> <ul> <li>[Site name] is a stand-in for the nine TERN sites (e.g., "Alice Mulga.zip", "Credo.zip", etc.)</li> <li>contains the data necessary to reproduce results in the main text of the study, i.e. DSMs, CHMs, and DTMs for all nine TERN sites, and at different pulse density levels (from 16 down to 0.5 laser shots per squaremetre)</li> <li>also contains calculated summary statistics for each site</li> </ul> <p>All zip files should be extracted into the same folder, except for 05_downsampling_pulse_[Site name].zip which should all be moved to a subfolder called "downsampling_pulse".</p>
Database - List of articles
<pre><span>This database contains a list of articles, hosted in Scopus, Scielo and Web Of Science.<br><br></span></pre> <p><a href="https://revmedmilitar.sld.cu/index.php/mil/article/view/2821/2060">https://revmedmilitar.sld.cu/index.php/mil/article/view/2821/2060</a></p> <p>https://revmedmilitar.sld.cu/index.php/mil/article/view/2340</p> <p>https://revmedmilitar.sld.cu/index.php/mil/article/view/2852/1988</p> <p>https://revistas.unal.edu.co/index.php/rccquifa/article/view/108840</p> <p>http://www.scielo.org.pe/scielo.php?script=sci_arttext&pid=S1727-558X2018000400009</p> <p>https://scielo.isciii.es/scielo.php?pid=S2340-98942019000200119&script=sci_abstract&tlng=es</p> <p>http://www.scielo.org.pe/scielo.php?script=sci_arttext&pid=S2413-32992019000100018</p> <p>https://revmedmilitar.sld.cu/index.php/mil/article/view/1336</p> <p>https://scielo.isciii.es/pdf/ars/v62n3/2340-9894-ars-62-03-280.pdf</p> <p>https://revmedmilitar.sld.cu/index.php/mil/article/view/489/0</p> <p>http://www.scielo.org.pe/pdf/arnal/v25n2/a13v25n2.pdf</p> <p> </p>
Supporting datasets for the article Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia
<h3>Supporting datasets for the article<em><strong> Using rare event algorithms to understand the statistics and dynamics of extreme heatwave seasons in South Asia, </strong></em>submitted to <em>Environmental Research: Climate</em></h3> <p> </p> <p>The dataset contains all intermediate data used for the article. The raw outputs of the model may be available upon reasonable request to clement.lpr@gmail.com</p> <p>The climate model Plasim can be downloaded, together with its documentation, from the webpage of the « Theoretische Meteorologie » group at the University of Hamburg: <a href="https://www.mi.uni-hamburg.de/en/arbeitsgruppen/theoretische-meteorologie/modelle/plasim.html">https://www.mi.uni-hamburg.de/en/arbeitsgruppen/theoretische-meteorologie/modelle/plasim.html</a></p> <p>The three jupyter notebooks <a href="../api/records/10888194/draft/files/Figures_article_archive.ipynb/content" target="_blank" rel="noopener noreferrer">Figures_article_archive.ipynb</a>, <a href="../api/records/10888194/draft/files/Zg500_maps_article_archive.ipynb/content" target="_blank" rel="noopener noreferrer">Zg500_maps_article_archive.ipynb</a>, <a href="../api/records/10888194/draft/files/Correlation_maps_3days_ERA5_Plasim_archive.ipynb/content" target="_blank" rel="noopener noreferrer">Correlation_maps_3days_ERA5_Plasim_archive.ipynb</a> contain the analysis and code used to produce the figures in the article.</p> <p><strong><a href="../api/records/10888194/draft/files/pyscripts.tar/content" target="_blank" rel="noopener noreferrer">pyscripts.tar</a> </strong>contains 4 python utilities, <em>data_proceeding_module.py, plot_routines.py, subseasonal_stats_utilities.py, utilities_REA_analysis.py </em>that are imported by the notebooks.</p>
Reproduction Package for Article `Fault Localization on Witnesses'
<h2>Fault Localization on Witnesses</h2> <h2>Article Abstract</h2> <p>When verifiers report an alarm, they export a violation witness (exchangeable counterexample)<br>that helps validate the reachability of that alarm.<br>Conventional wisdom says that this violation witness should be very precise:<br>the ideal witness describes a single error path for the validator to check.<br>But we claim that verifiers overshoot and produce large witnesses<br>with information that makes validation unnecessarily difficult.<br>To check our hypothesis, we reduce violation witnesses to that information<br>that automated fault-localization approaches deem relevant for triggering the reported alarm in the program.<br>We perform a large experimental evaluation on the witnesses<br>produced in the International Competition on Software Verification (SV-COMP 2023).<br>It shows that our reduction shrinks the witnesses considerably<br>and enables the confirmation of verification results that were not confirmable before.</p> <h2>VM</h2> <p>The username for the VM is `vagrant`.<br>The password for the VM is `vagrant`.</p> <h2>System Requirements</h2> <p>The artifact requires 4 CPU cores and 8 GB of RAM.</p> <p>To inspect the data, we require at least 150GB of empty disk space to run the VM.<br>To reproduce the results, we require 155GB.<br>To run the full reproduction, we require 300GB.</p> <p>The VM was tested on Ubuntu with Virtual Box Version 7.0.10 r158379 (Qt5.15.3).</p> <h2>Reproduction</h2> <p>Import the VM to VirtualBox and start it.<br>We provide symbolic links to the reproduction directory on the Desktop.<br>Please follow the instructions in the `ReadMe.md` inside the VM (located at `~/fault-localization-witnesses/ReadMe.md`).<br>The upcoming three subsections serve as a quick-start guide for our artifact.</p> <h3>Reproduce the Example</h3> <p>To reproduce the example in our paper, navigate to `~/fault-localization-witnesses` and execute `./example.sh`.</p> <h3>Reproduce the Plots</h3> <p>Execute `./reproduce.sh` from `~/fault-localization-witnesses/` to reproduce our experiments.</p>
Dataset and mesh convergence study for the article: Implementing moving object capability in a two-phase Eulerian model for sediment transport applications
<p>This dataset includes the results for the article Implementing moving object capability in a two-phase Eulerian model for sediment transport applications (2024). OpenFOAM Journal.<br>The dataset consists of the results obtained to produce the figures of the manuscript and the mesh convergence test.</p>
Data archive for the peer-reviewed journal article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements"
<p>This data archive accompanying the article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements", which was accepted in April 2024 in the peer-reviewed journal <strong><em>Science of the Total Environment</em></strong>. This data archive contains the processed OPvDTT measurements, chemical speciation of PM2.5, and source contribution used in the manuscript.</p>
Dataset for the article 'Beyond Human Perception: Challenges in AI Interpretability of Orangutan Artwork'
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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.