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256 results for “submissions”

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zenodo36/100

Dataset for the submission entitled: Journal article publishing in the social sciences and humanities: a comparison of Web of Science coverage for five European countries

<p>Dataset for the manuscript submission entitled: Journal article publishing in the social sciences and humanities: a comparison of Web of Science coverage for five European countries.</p>

opencc-by-4.0Sep 2020View details →
dryad36/100

The influence of the global COVID-19 pandemic on manuscript submissions and editor and reviewer performance at six ecology journals

Government policies attempting to slow the spread of COVID-19 have reduced access to research laboratories and shifted many scholars to working from home. These disruptions will likely influence submissions to scholarly journals, and affect the time available for editors and reviewers to participate in peer review. In this editorial we examine how journal submissions, and editorial and peer review processes, have been influenced by the pandemic at six journals published by the British Ecological Society (BES). We find no evidence of a change in the geographic pattern of submissions from across the globe. We also find no evidence that submission of manuscripts by women has been more affected by pandemic disruptions than have submissions by men – the proportion of papers authored by women during the COVID period of 2020 has not changed relative to the same period in 2019. Editors handled papers just as quickly, and reviewers have agreed to review just as often, during the pandemic compared to pre-pandemic. The one notable change in peer review during the pandemic is that reviewers replied more quickly to emails inviting them to review (albeit only 4% sooner), and those that agreed to review returned their reviews more quickly (17% sooner), during the pandemic. We thus find no evidence at these six ecology journals that submissions and peer review processes have been negatively impacted by the pandemic. Also, contrary to analyses in other disciplines, we do not find evidence that there have been disproportionate impacts of the pandemic on female authors and reviewers.

opencc-zeroDec 2020View details →
zenodo36/100

Dataset accompanying paper submission for "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"

<p>This data set accompanies code archived at DOI:&nbsp;<a href="https://doi.org/10.5281/zenodo.3833186">10.5281/zenodo.3833186</a>, which was used in the experiments for the paper submission &quot;Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems&quot;</p>

opencc-by-4.0Dec 2020View details →
zenodo36/100

Artifacts of the ISSTA2021 Submission JUnitTestGen

<p>This repository contains the artifacts of JUnitTestGen, a paper&nbsp;under review by ISSTA&#39;21.</p> <p>The file&nbsp;<strong>RQ1&amp;RQ2_result</strong>&nbsp;illustrates the detailed results of&nbsp;JUnitTestGen&nbsp;on the three datasets(E1, E2, and E3).</p> <p>The file&nbsp;<strong>RQ3_result</strong>&nbsp;illustrates the detailed results of&nbsp;JUnitTestGen in detecting compatibility issues,&nbsp;in which the column&nbsp;<em>TargetAPI</em>&nbsp;shows the target API to be tested,&nbsp;the column&nbsp;<em>Type</em>&nbsp;refers to the two different&nbsp;compatibility issue types, and the last&nbsp;column&nbsp;<em>TestCase_name------runtime result</em> indicating the specific runtime results from SDK version 21 to 29.</p> <p>The file<strong> E1+E2+E3_TestCaseName_TargetAPI_Map.csv </strong>is a map recording all the generated test case&nbsp;names and their corresponding target API. We then run all these test cases on Android SDK version 27 and the logs are detailed in file&nbsp;<strong>E1+E2+E3_runtime_log.txt.</strong></p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Dataset for submission of "Correction of river bathymetry parameters using the stage–discharge rating curve"

<p>Dataset for submission of &quot;Correction of river bathymetry parameters using the &nbsp;stage&ndash;discharge rating curve&quot;.&nbsp;</p>

opencc-by-4.0Jun 2021View details →
zenodo36/100

Tractography Challenge ISMRM 2015 Submissions

<p>Submissions to the open international ISMRM 2015 tractography challenge. 20 research groups with extensive expertise in diffusion imaging from 12 countries participated in the competition and submitted a total of 96 tractograms generated using a large variety of tractography pipelines with different pre-processing, local reconstruction, tractography and post-processing algorithms.</p> <p>Each file represents an individual submission. The mapping from file name to team can be inferred from the listing in the paper, as seen in the references.</p>

opencc-by-4.0Aug 2017View details →
zenodo36/100

Data and scripts for the submission "A locally smoothed terrain-following vertical coordinate to improve the simulation of fog and low stratus in numerical weather prediction models"

<p>Dataset and scripts used to generate Figures for &quot;A locally smoothed terrain-following vertical coordinate to improve the simulation of fog and low stratus in numerical weather prediction models&quot;, submitted to the <strong><em>Journal of Advances in Modeling Earth Systems</em></strong> (JAMES).</p> <p>Scripts: Python and NCL</p> <p>Data: Netcdf, PNG, Python pickled objects</p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Artifacts of the ISSTA-2024 Submission——DroidTEC

<div> <p>This release includes the experimental results that are used for the ISSTA artifact analysis. All the results are described in our paper. All required artifacts are attached to this release.</p> <p><br>The source code is made publicly available on the github: page:&nbsp;<a href="https://anonymous.4open.science/r/TypeStateMisuseDetector">https://anonymous.4open.science/r/TypeStateMisuseDetector</a><br>Users can easily access and execute our tool following the steps in the Setup part.</p> <p>In addition, all of our experimental results are publicly available on this page. For simplicity, we provide the following instructions for our artifacts:</p> <ol> <li><strong>Experimental_Setup.txt&nbsp;</strong>: Experimental Setup, including 10,000 Android apps</li> <li><strong>RQ1_Rules.zip:&nbsp;</strong>TypeState API rules.</li> <li><strong>RQ2_typestate_API_usage.zip</strong>&nbsp;: The prevalence of typestate APIs in Android applications.</li> <li><strong>RQ4_Typestate_Misuses.zip</strong>&nbsp;: Identified&nbsp;typestate misuses in real-world applications.</li> <li><strong>RQ5_CrySL_Results.zip</strong>&nbsp;: Execution results of CrySL on&nbsp;10,000 Android apps.</li> <li><strong>RQ5_AsyncChecker_Results.zip</strong>&nbsp;: Execution results of AsyncChecker on&nbsp;10,000 Android apps.</li> <li><strong>RQ5_VALA_Results.zip</strong>&nbsp;:&nbsp;Execution results of VALA on&nbsp;10,000 Android apps.</li> <li><strong>RQ5_CiD_Results.zip</strong>&nbsp;:&nbsp;Execution results of CiD on&nbsp;10,000 Android apps.</li> <li><strong>RQ5_BenchMark_Apps.zip</strong>&nbsp;:&nbsp;Execution results of VALA on&nbsp;10,000 Android apps.</li> </ol> <p>&nbsp;</p> </div>

opencc-by-4.0Dec 2023View details →
zenodo36/100

A multi-omics systems vaccinology resource to develop and test computational models of immunity: 1st challenge dataset and submissions

<p>The goal of the CMI-PB prediction contest is to foster a collaborative research community that can collectively tackle challenges and accelerates scientific progress beyond the capabilities of individual researchers or groups. The CMI-PB consortium has curated multi-source data from multiple individuals, encompassing Ab titers (around four antibodies/features), cell frequency (approximately 20 cell types/features), gene expression (roughly 50,000 RNA transcripts/features), and plasma proteomics (around 50 proteins/features). The challenge requires integrating these diverse data sources to predict different immune responses or tasks. Specifically, you will utilize multi-source data from several individuals on day 0 (baseline) to predict specific immune responses at later time points (1, 3, 7, and&nbsp; 14 days post-booster vaccination).</p> <p>The first CMI-PB challenge, which is an internal challenge, was conducted using datasets from 2020 (train) and 2021 (test). In the following sections, we provide detailed information on the datasets, challenge tasks, submission format, descriptions, and access to the necessary data files for participants to develop their models and make predictions.</p> <p><br><strong>A) Multiomics CMI-PB dataset:</strong></p> <p>We propose a study design that enables a systems-level understanding of the immune responses through computational modeling. Our cohort comprises aP vs. wP infancy-primed subjects boosted with Tdap. We recruit individuals born before 1995 (wP) and after 1996 (aP), collect baseline plasma and blood samples, and then at 1, 3, 7 and&nbsp; 14 days post booster vaccination.</p> <p>With the obtained samples processed, we generated omics data by:</p> <ul> <li> <p>Bulk PBMCs transcriptomics,</p> </li> <li> <p>Plasma proteomics using Olink, which provides a quantitative readout of cytokines, chemokines, and other immune factors,</p> </li> <li> <p>Cell frequency in PBMCs using flow cytometry,</p> </li> <li> <p>Tdap-specific antibodies levels</p> </li> </ul> <p><strong>B) List of tasks can be accessed using the &ldquo;List of tasks for challenge 1.docx&rdquo; file, and submissions need to submit in provided format here: &ldquo;submission template challenge 1.tsv&rdquo;</strong></p> <p><strong>C) Datasets for model building and making predictions:</strong></p> <p>&nbsp; &nbsp;&nbsp;Data files are divided into two categories: 1) raw dataset and 2) computable matrices.</p> <ol> <li> <p><strong>Raw dataset: </strong>This raw-most dataset is divided into training and test datasets.&nbsp;</p> </li> <li> <p><strong>Computable matrices: </strong>There are three different types of computable matrices. a) Full: These files are generated by dividing raw files into sub-files specific to planned days specific to vaccination. b) harmonized: These are generated by preserving only overlapping features between train and test datasets. b) imputed: MICE imputation is performed to impute missing values in the dataset.</p> </li> </ol> <p><strong>D) Submission evaluation</strong></p> <p>This folder contains all submitted models with ranking files and code for evaluating these models.</p> <p><strong>To learn more about the CMI-PB prediction challenge, visit our website at www.cmi-pb.org.</strong></p>

openmit-licenseMar 2024View details →
zenodo36/100

Data and Code for "A Novel Emergent Constraint Approach for Refining Regional Climate Model Projections of Flood Timing" Paper Submission to AGU GRL

<p>This contains the emergent constraint code, the offline CMIP6 hydrology data, and the shapefiles for each region used in the paper "A Novel Emergent Constraint Approach for Refining Regional Climate Model Projections of Flood Timing" submitted to AGU GRL.</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

3D-Printed Pulsator to Enhance Mass Transfer in Electrochemical Reactors HardwareX submission

<p>This repository contains CAD drawing, data, Python codes, and Arduino sketch files for submission to HardwareX journal titled "3D-Printed Pulsator to Enhance Mass Transfer in Electrochemical Reactors". The CAD file can be open with FreeCAD 1.1.0dev or newer. Python codes were used to analyzed and generate figures from electrochemical data for the publication. Arduino sketch files were use for controlling the electrical motor used in the experimental setup for the publication.<br><br>The abstract of the publication is provided below.<br><br>This study presents a cost-effective diaphragm pulsator, constructed for approximately &euro;500, designed to enhance mass transport in laboratory electrochemical reactors. The pulsator allows accurate control of pulsation frequency between 1 Hz and 6 Hz and displacement volume, with simple programmability using an Arduino microcontroller. The design features multiple chambers that effectively isolate corrosive liquids from the mechanical components, ensuring durability and extended operational life. The pulsator's 3D-printed components can be customized with different materials to suit various applications. Engineered to generate a pulsating flow profile that closely resembles a sinusoidal wave, video tracking analysis confirmed the sinusoidal nature of the flow, demonstrating consistent flow profile generation with adjustable frequency and amplitude. The maximum volume displacement achieved was 11.9 mL, which was reduced to 2.0 mL when the electrochemical cell was connected. Limiting current experiments with a ferri/ferrocyanide electrolyte showed that the mass transport coefficient of a typical cell increased from 2.3 &times; 10⁻&sup3; cm/s under constant flow to 4.5 &times; 10⁻&sup3; cm/s under pulsating conditions. These findings validate that the adjustable, Arduino-programmable sinusoidal pulsation generated by the diaphragm pulsator offers a practical and customizable method for enhancing mass transport in small-scale electrochemical reactors.&nbsp;</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

VaMoS 2022 Submission 12 - Continuous T-Wise Sampling: Increasing Coverage over Time

<p>Evaluation results for the VaMoS 2022 submission 12. For more details regarding the dataset please refer to the included readme.md file.</p>

opencc-by-4.0Nov 2021View details →
zenodo36/100

Submission and acceptance data for journals involved in the Taylor & Francis FAIR data pilot

<p>Submission, acceptance&nbsp;and peer review data for journals involved in the Taylor &amp; Francis FAIR data pilot. Data is anonymised. Includes journal article submissions, acceptances and peer review for the years 2018, 2019 and 2020.</p>

opencc-by-4.0Aug 2021View details →
zenodo36/100

Supplementary files of the GRL submission 2022GL098289

<p>List of the stations used, dates of the flood events and basin area&nbsp;</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Data and Analysis Script for Cluster2022 Submission pap254: "Painless Transposition of Reproducible Distributed Environments with NixOS Compose"

<p>Data and Analysis Script for Cluster2022 Submission pap254: &quot;Painless Transposition of Reproducible Distributed Environments with NixOS Compose&quot;</p> <p>The experiments repository is available at: <a href="https://gitlab.inria.fr/nixos-compose/articles/cluster2022">https://gitlab.inria.fr/nixos-compose/articles/cluster2022</a></p>

opencc-by-4.0May 2022View details →
zenodo36/100

Datatset associated to Journal of Marine Systems submission : Ms. No. MARSYS-D-21-00246R1

<p>Individual growth increment measurements (&micro;m)&nbsp;of the 21 live collected <em>A. islandica</em> used in the publication entitled : &quot;The 18.6-year lunar nodal cycle may affect ecosystems on the Northwest Atlantic continental shelves&quot;.&nbsp;All information regarding data acquisition are presented in the section &quot;2. Construction of <em>Arctica islandica </em>master chronology&quot; of the article submitted to Journal of Marine Systems.</p> <p>Data are presented as a &quot;Tucson File&quot; which is a standard format for tree-ring dataset (see :&nbsp;<a href="http://www.cybis.se/wiki/index.php?title=Tucson_format">http://www.cybis.se/wiki/index.php?title=Tucson_format</a>&nbsp;for a precise description).</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2022View details →
zenodo36/100

Replication Package for ICSE 2023 submission "How Deep Learning Packages Form Supply Chain in PyPI: Types, Clusters, and Detachment"

<p>This is the replication package for our&nbsp;ICSE 2023 submission <em><strong>How Deep Learning Packages Form Supply Chain in PyPI: Types, Clusters, and Detachment</strong></em>.&nbsp;</p>

opencc-by-4.0Aug 2022View details →
dryad36/100

Higher ultraviolet skin reflectance signals submissiveness in the anemonefish, Amphiprion akindynos

<p>Ultraviolet (UV) vision is widespread among teleost fishes, of which many exhibit UV skin colours for communication. However, aside from its role in mate selection, few studies have examined the information UV-signalling conveys in other socio-behavioural contexts. Anemonefishes (subfamily, Amphiprioninae) live in a fascinating dominance hierarchy, in which a large female and male dominate over non-breeding subordinates, and body size is the primary cue for dominance. The iconic orange and white bars of anemonefishes are highly UV-reflective, and their colour vision is well-tuned to perceive the chromatic contrast of skin, which we show here decreases in the amount of UV-reflectance with increasing social rank. To test the function of their UV-skin signals, we compared the outcomes of staged contests over dominance between size-matched Barrier Reef anemonefish (<em>Amphiprion akindynos</em>) in aquarium chambers viewed under different UV-absorbing filters. Fish under UV-blocking filters were more likely to win contests, whereas fish under no-filter or neutral-density filter were more likely to submit. For contests between fish in no-filter and neutral density filter treatments, light treatment had no effect on contest outcome (win/lose). We also show that sub-adults were more aggressive towards smaller juveniles placed under a UV filter than a neutral density filter. Taken together, our results show that UV-reflectance or -contrast in anemonefish can modulate aggression and encode dominant and submissive cues when changes in overall intensity are controlled for.</p>

opencc-zeroSep 2022View details →
zenodo36/100

Why are we linguistically submissive…

<p>A brief explanation about what linguistic submissiveness is, and why minoritized language speakers are linguistically submissive.</p> <p>Credits -&nbsp;Concept art:&nbsp;R&eacute;ka Kassay. Animation:&nbsp;Judith Vicsi,&nbsp;Bence Orosz. Graphics:&nbsp;&Eacute;va&nbsp;P&aacute;nc&eacute;l. Narration text:&nbsp;Erika&nbsp;Keszeg,&nbsp;Tibor&nbsp;Tor&oacute;.</p>

opencc-by-4.0Oct 2022View details →
zenodo36/100

Why are we linguistically submissive… and how to overcome it?

<p>The animation presents several resources that can be used in face-to-face situations to help minoritized language speakers overcome linguistic submissiveness.</p> <p>Credits -&nbsp;concept art:&nbsp;R&eacute;ka Kassay. Animation:&nbsp;Judith Vicsi,&nbsp;Bence Orosz. Graphics:&nbsp;&Eacute;va&nbsp;P&aacute;nc&eacute;l. Narration text:&nbsp;Erika&nbsp;Keszeg,&nbsp;Tibor&nbsp;Tor&oacute;.</p>

opencc-by-4.0Oct 2022View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record