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Data set from Mazzaccaro D, Modafferi A, Malacrida G, Nano G. Assessment of long-term survival and stroke after carotid endarterectomy and carotid stenting in patients older than 80 years. J Vasc Surg. 2019 Aug;70(2):522-529. doi: 10.1016/j.jvs.2018.10.121. Epub 2019 Mar 2. PMID: 30837178.
<p>Data set from Mazzaccaro D, Modafferi A, Malacrida G, Nano G. Assessment of long-term survival and stroke after carotid endarterectomy and carotid stenting in patients older than 80 years. J Vasc Surg. 2019 Aug;70(2):522-529. doi: 10.1016/j.jvs.2018.10.121. Epub 2019 Mar 2. PMID: 30837178.</p> <p> </p> <p>This is the abstract:</p> <p><strong>Objective: </strong> The objective of this study was to analyze preoperative risk factors affecting long-term survival and the occurrence of stroke in patients older than 80 years undergoing either carotid endarterectomy (CEA) or carotid artery stenting (CAS) for carotid stenosis.</p> <p><strong>Methods: </strong> Data of all consecutive patients treated from January 1999 to December 2017 were retrospectively reviewed and outcomes analyzed. Kaplan-Meier analysis was used to estimate long-term survival and the risk of stroke for both groups. Cox proportional hazards analysis was used to assess the relative risk of all-cause mortality and long-term stroke for patients in the presence of selected comorbidities, including preoperative symptoms, coronary artery disease, chronic renal failure, atrial fibrillation (AF), hypertension, diabetes mellitus, and dyslipidemia. A P value <.05 was considered statistically significant.</p> <p><strong>Results: </strong> A total of 473 patients older than 80 years (298 men [63%]) underwent either CEA (n = 178) or CAS. At 30 days, one patient died in the CEA group of unrelated causes; no deaths were recorded after CAS (0.6% vs 0%; P = .18). At 5 years, survival was 67.6% ± 4.9% after CEA and 90.2% ± 2.3% after CAS (P < .0001). The main cause of death after CEA and CAS was a neoplasm. Estimated freedom from any stroke at 5 years was 97.3% ± 0.5% after CEA and 93.2% ± 1.2% after CAS (P = .07). The presence of preoperative AF significantly affected long-term mortality after CAS (hazard ratio [HR], 1.56; 95% confidence interval [CI], 1.34-1.98; P = .04) as well as being classified as American Society of Anesthesiologists class 3 at evaluation of the preoperative anesthesiology risk. The presence of preoperative AF was the only factor that significantly affected the occurrence of long-term stroke after both CAS (HR, 2.28; 95% CI, 1.86-5.63; P = .001) and CEA (HR, 3.45; 95% CI, 2.29-8.19; P = .005).</p> <p><strong>Conclusions: </strong> Both CEA and CAS showed low 30-day mortality and any-stroke rates in patients older than 80 years. In the long term, survival was significantly better after CAS; however, deaths after CEA and CAS were mainly unrelated to the procedure. No significant differences were recorded in the occurrence of any stroke in the long term. The presence of preoperative AF significantly affected long-term survival after CAS as well as being classified as American Society of Anesthesiologists class 3 at evaluation of the preoperative anesthesiology risk. The presence of preoperative AF also significantly affected long-term risk of stroke after both CAS and CEA.</p> <p> </p>
Data set and 3d model from Emendi M, Sturla F, Ghosh RP, Bianchi M, Piatti F, Pluchinotta FR, Giese D, Lombardi M, Redaelli A, Bluestein D. Patient-Specific Bicuspid Aortic Valve Biomechanics: A Magnetic Resonance Imaging Integrated Fluid-Structure Interaction Approach. Ann Biomed Eng. 2020 Aug 17. doi: 10.1007/s10439-020-02571-4. Epub ahead of print. PMID: 32804291.
<p>Data set and 3d model from Emendi M, Sturla F, Ghosh RP, Bianchi M, Piatti F, Pluchinotta FR, Giese D, Lombardi M, Redaelli A, Bluestein D. Patient-Specific Bicuspid Aortic Valve Biomechanics: A Magnetic Resonance Imaging Integrated Fluid-Structure Interaction Approach. Ann Biomed Eng. 2020 Aug 17. doi: 10.1007/s10439-020-02571-4. Epub ahead of print. PMID: 32804291.</p> <p> </p> <p>This is the abstract:</p> <p>Congenital bicuspid aortic valve (BAV) consists of two fused cusps and represents a major risk factor for calcific valvular stenosis. Herein, a fully coupled fluid-structure interaction (FSI) BAV model was developed from patient-specific magnetic resonance imaging (MRI) and compared against in vivo 4-dimensional flow MRI (4D Flow). FSI simulation compared well with 4D Flow, confirming direction and magnitude of the flow jet impinging onto the aortic wall as well as location and extension of secondary flows and vortices developing at systole: the systolic flow jet originating from an elliptical 1.6 cm<sup>2</sup> orifice reached a peak velocity of 252.2 cm/s, 0.6% lower than 4D Flow, progressively impinging on the ascending aorta convexity. The FSI model predicted a peak flow rate of 22.4 L/min, 6.7% higher than 4D Flow, and provided BAV leaflets mechanical and flow-induced shear stresses, not directly attainable from MRI. At systole, the ventricular side of the non-fused leaflet revealed the highest wall shear stress (WSS) average magnitude, up to 14.6 Pa along the free margin, with WSS progressively decreasing towards the belly. During diastole, the aortic side of the fused leaflet exhibited the highest diastolic maximum principal stress, up to 322 kPa within the attachment region. Systematic comparison with ground-truth non-invasive MRI can improve the computational model ability to reproduce native BAV hemodynamics and biomechanical response more realistically, and shed light on their role in BAV patients' risk for developing complications; this approach may further contribute to the validation of advanced FSI simulations designed to assess BAV biomechanics.</p> <p> </p>
unarXive: A Large Scholarly Data Set with Publications' Full-Text, Annotated In-Text Citations, and Links to Metadata
<h2><strong>Description</strong></h2> <p><strong>unarXive</strong> is a scholarly data set containing <strong>publications' full-text</strong>, annotated <strong>in-text citations</strong>, and a <strong>citation network</strong>.</p> <p>The data is <strong>generated from all LaTeX sources on </strong><a href="https://arxiv.org/"><strong>arXiv</strong></a> and therefore of higher quality than data generated from PDF files.</p> <p>Typical <strong>use cases</strong> are</p> <ul> <li>Citation recommendation</li> <li>Citation context analysis</li> <li>Bibliographic analyses</li> <li>Reference string parsing</li> </ul> <p>This version (v3) of our data set is based on all arXiv publications until 2020-07-31 and on the Microsoft Academic Graph as of 2020-08-18. As additional contribution, we included a table with the publication date and the scientific discipline for each paper for easier filtering.</p> <p><strong>Note:</strong> This Zenodo record is an old version of unarXive. You can find the <strong>most recent version</strong> at <a href="../record/7752754">https://zenodo.org/record/7752754</a> and <a href="../record/7752615">https://zenodo.org/record/7752615</a></p> <h2><strong>Access</strong></h2> <p>┏━━━━━━━━━━━━━━━━━━━━━━━━━━┓<br>┃ <a href="https://github.com/IllDepence/unarXive/blob/legacy_2020/doc/unarXive_sample.tar.bz2"><strong>D O W N L O A D S A M P L E</strong></a>  ┃<br>┗━━━━━━━━━━━━━━━━━━━━━━━━━━┛</p> <p>To download the whole data set send an access request and note the following:</p> <blockquote> <p><strong>Note</strong>: this Zenodo record is a "full" version of unarXive, which was generated from all of arXiv.org <em>including non-permissively licensed papers</em>. Make sure that your use of the data is compliant with the paper's licensing terms.¹</p> <p>¹ For information on papers' licenses use <a href="https://info.arxiv.org/help/bulk_data/index.html">arXiv's bulk metadata access</a>.</p> </blockquote> <p>The <strong>code</strong> used for generating the data set is <a href="https://github.com/IllDepence/unarXive/tree/legacy_2020/">publicly available</a>.</p> <p><strong>Usage examples</strong> for our data set are provided at <a href="https://github.com/IllDepence/unarXive/tree/legacy_2020/#usage-examples">here on GitHub</a>.</p> <h2><strong>Citing</strong></h2> <p>This initial version of unarXive is described in the following journal article.</p> <p><em>Tarek Saier, Michael Färber: "</em><a href="http://dx.doi.org/10.1007/s11192-020-03382-z"><em>unarXive: A Large Scholarly Data Set with Publications' Full-Text, Annotated In-Text Citations, and Links to Metadata</em></a><em>", Scientometrics, 2020,</em><br>[<a href="https://www.aifb.kit.edu/images/f/f9/UnarXive_Scientometrics2020.pdf">link to an author copy]</a></p> <p>The <strong>updated version</strong> is described in the following conference paper.</p> <p><em>Tarek Saier, Michael Färber. "</em><a href="10.1109/JCDL57899.2023.00020"><em>unarXive 2022: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Network</em></a><em>", JCDL 2023.</em><br>[<a href="https://doi.org/10.48550/arXiv.2303.14957">link to an author copy</a>]</p>
Numerical data sets pertaining to phase-field simulations of faceted crystal dissolution processes
<p>The numerical data in this repository (Archive.zip + Animation.zip) pertains to the simulation results of faceted crystal dissolution processes in different crystal-liquid systems. The simulations were performed using the software package named "Pace3D version 2.5.1". The software license can be purchased at Steinbeis Network (www.steinbeis.de) in the management of Britta Nestler and Michael Selzer under the subject area ‘Material Simulation and Process Optimization’. </p> <p><br> The data is organized, the way it appears in the figures in the manuscript. Thus, the folders (compressed) are named according to the figure number in the manuscript.</p> <ul> <li>For the sake of convenience, the simulation data at intermediate dissolution stages was converted from Pace3D output format (*.phiindex.p3s and *.phi_crystal.p3s) to VTK data format, that can be visualized using open source software packages like Paraview. The VTK data files in each subfolder are also compressed (*.gz). For visualization, a decompression of the data is necessary (e.g. with gzip, 7zip).</li> <li>The animation videos of the simulations are also attached as a separate compressed file named Animation.zip.</li> </ul>
SCAD-zbMATH-01 Open Access Data Set for Author Name Disambiguation (AND)
<p> </p> <p><strong>Note: This data set is <em>deprecated</em>. Please use the enhanced, open access version available at https://doi.org/10.5281/zenodo.161333</strong><strong> !</strong></p> <p> </p> <p>This data set contains disambiguated publication data from zbMATH (www.zbmath.org) for use in author name disambiguation (AND). </p> <p>It covers 28321 publications with 33810 authorship records, authored by 2946 distinct authors. Authorship records have been manually annotated with author identifiers. </p> <p>For details, see "Data Sets for Author Name Disambiguation: An Empirical Analysis and a New Resource", Mark-Christoph Müller, Florian Reitz, and Nicolas Roy, 2016, submitted to Scientometrics.</p>
SOTorrent Data Set 2017-07-25
<p><strong>Moved to this Zenodo record: <a href="https://zenodo.org/record/1135262">https://zenodo.org/record/1135262</a></strong></p> <p>Stack Overflow (SO) is the largest Q&A website for software developers, providing a huge amount of copyable code snippets. Recent studies have shown that developers regularly copy those snippets into their software projects, often without the required attribution. Beside possible licensing issues, maintenance issues may arise, because the snippets evolve on SO, but the developers who copied the code are not aware of these changes. To help researchers investigate the evolution of code snippets on SO and their relation to other platforms like GitHub, we build <em>SOTorrent</em>, an open data set based on data from the official SO data dump and the Google BigQuery GitHub data set. <em>SOTorrent</em> provides access to the version history of SO content on the level of whole posts and individual text or code blocks. Moreover, it links SO content to external resources in two ways: (1) by extracting linked URLs from text blocks of SO posts and (2) by providing a table with links to SO posts found in the source code of all projects in the BigQuery GitHub data set.</p>
Eddy Covariance and Agronomical Meta Data Set from a Three Year Agroecosystem Site (RNG1)
<p>Dataset of soil, plant, forage, agronomical and eddy flux data from three years of commercial bioenergy feedstock production in California funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users only. Data sets include three years of all 30 minute interval data. Full data sets will be published through Ameriflux. Some data, such as methane and nitrous oxide are embargoed.</p> <p>This work was partially funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).</p>
Eddy Covariance and Agronomical Meta Data Set from a Three Year Agroecosystem Site (RNG3)
<p>Dataset of soil, plant, forage, agronomical and eddy flux data from three years of commercial bioenergy feedstock production in California funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users only. Data sets include three years of all 30 minute interval data. Full data sets will be published through Ameriflux. Some data, such as methane and nitrous oxide are embargoed.</p> <p>This work was partially funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).</p>
Eddy Covariance and Agronomical Meta Data Set from a Three Year Agroecosystem Site (RNG4)
<p>Dataset of soil, plant, forage, agronomical and eddy flux data from three years of commercial bioenergy feedstock production in California funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users only. Data sets include thre years of all 30 minute interval data. Full data sets will be published through Ameriflux. Some data, such as methane and nitrous oxide are embargoed.</p> <p>This work was partially funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).</p>
Eddy Covariance and Agronomical Meta Data Set from a Three Year Agroecosystem Site (RNG5)
<p>Dataset of soil, plant, forage, agronomical and eddy flux data from three years of commercial bioenergy feedstock production in Arkansas funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users only. Data sets include three years of all 30 minute interval data. Full data sets will be published through Ameriflux. Some data, such as methane and nitrous oxide are embargoed.</p> <p>This work was partially funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).</p>
Eddy Covariance and Agronomical Meta Data Set from a Two Year Agroecosystem Site (RNG6)
<p>Dataset of soil, plant, forage, agronomical, and eddy flux data from two years of commercial bioenergy feedstock production in California funded under the DOE ARPA-E SMARTFARM program in Phase I. Data set is provided to restricted users only. Data sets include two years of 30-minute interval flux data. Full data sets will be published through Ameriflux. Some data, such as methane and nitrous oxide are embargoed.</p> <p>This work was partially funded through the U.S. Department of Energy, ARPA-E, under Cooperative Agreement DE-AR0001228 led by ARVA Intelligence Corp. (https://www.arvaintelligence.com) in collaboration with Lawrence Berkeley National Laboratory (LBNL).</p>
The raw data set for people entering plateau.
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Data Set - Analysis of Mandarin–Indonesian Translation Accuracy using Google Translate, Baidu Translate, and DeepL
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Data Set_Urinary Albumin-to-Creatinine Ratio as an Independent Predictor of Long-term Mortality in Atherosclerotic Cardiovascular Disease Patients: A Propensity Score-Matched Study
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[OUTDATED] Data set [ref. paper "An innovative automated method for SHM of road pavements based on Hilbert transform"]
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[OUTDATED] Data set [ref. paper "Predictive modeling of drivers' brake reaction time through machine learning methods"]
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Data set [ref. paper "An innovative automated method for SHM of road pavements based on Hilbert transform"]
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Data sets of the article Validation of the Health Protective Sexual Communication Scale (HPSC) in British and Spanish young adults.
<p>Data sets of the article <em>Validation of the Health Protective Sexual Communication Scale (HPSC) in British and Spanish young adults. </em></p> <p>SPSS data sets used to perform Exploratory Factor Anlaysis (EFA) and Confirmatory Factor Analysis (CFA) in Spain and the United Kingdom.</p> <p>SPSS AMOS data sets to perform CFA in Spain and the United Kingdom.</p>
Data set related to the article: "BPIFB4 Circulating Levels and Its Prognostic Relevance in COVID-19 "
<p>This record contains raw data related to the article: "BPIFB4 Circulating Levels and Its Prognostic Relevance in COVID-19".</p> <p> </p> <p>Abstract</p> <p>Aging and comorbidities make individuals at greatest risk of COVID-19 serious illness and mortality due to senescence-related events and deleterious inflammation. Long-living individuals (LLIs) are less susceptible to inflammation and develop more resiliency to COVID-19. As demonstrated, LLIs are characterized by high circulating levels of BPIFB4, a protein involved in homeostatic response to inflammatory stimuli. Also, LLIs show enrichment of homozygous genotype for the minor alleles of a 4 missense single-nucleotide polymorphism haplotype (longevity-associated variant [LAV]) in BPIFB4, able to counteract progression of diseases in animal models. Thus, the present study was designed to assess the presence and significance of BPIFB4 level in COVID-19 patients and the potential therapeutic use of LAV-BPIFB4 in fighting COVID-19. BPIFB4 plasma concentration was found significantly higher in LLIs compared to old healthy controls while it significantly decreased in 64 COVID-19 patients. Further, the drop in BPIFB4 values correlated with disease severity. Accordingly to the LAV-BPIFB4 immunomodulatory role, while lysates of SARS-CoV-2-infected cells induced an inflammatory response in healthy peripheral blood mononuclear cells in vitro, the co-treatment with recombinant protein (rh) LAV-BPIFB4 resulted in a protective and self-limiting reaction, culminating in the downregulation of CD69 activating-marker for T cells (both TCD4+ and TCD8+) and in MCP-1 reduction. On the contrary, rhLAV-BPIFB4 induced a rapid increase in IL-18 and IL-1b levels, shown largely protective during the early stages of the virus infection. This evidence, along with the ability of rhLAV-BPIFB4 to counteract the cytotoxicity induced by SARS-CoV-2 lysate in selected target cell lines, corroborates BPIFB4 prognostic value and open new therapeutic possibilities in more vulnerable people.</p>
Data set from the article Malavazos AE, Capitanio G, Milani V, Ambrogi F, Matelloni IA, Basilico S, Dubini C, Sironi FM, Stella E, Castaldi S, Secchi F, Menicanti L, Iacobellis G, Corsi Romanelli MM, Carruba MO, Morricone LF. Tri-Ponderal Mass Index vs body Mass Index in discriminating central obesity and hypertension in adolescents with overweight. Nutr Metab Cardiovasc Dis. 2021 May 6;31(5):1613-1621. doi: 10.1016/j.numecd.2021.02.013. Epub 2021 Feb 23. Erratum in: Nutr Metab Cardiovasc Dis. 2021 Oct 28;31(11):3247-3248. PMID: 33741212.
<p>Data set from the article Malavazos AE, Capitanio G, Milani V, Ambrogi F, Matelloni IA, Basilico S, Dubini C, Sironi FM, Stella E, Castaldi S, Secchi F, Menicanti L, Iacobellis G, Corsi Romanelli MM, Carruba MO, Morricone LF. Tri-Ponderal Mass Index vs body Mass Index in discriminating central obesity and hypertension in adolescents with overweight. Nutr Metab Cardiovasc Dis. 2021 May 6;31(5):1613-1621. doi: 10.1016/j.numecd.2021.02.013. Epub 2021 Feb 23. Erratum in: Nutr Metab Cardiovasc Dis. 2021 Oct 28;31(11):3247-3248. PMID: 33741212.</p> <p> </p> <p>Astract</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.