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7,195 results for “SET”
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>
Immoscraper full final set
<p>From 2012 to 2014 our webscraper collected the information for houses, apartments and building land from Belgian online real estate listings. This dataset contains all the unique records with full address, that were successfully geocoded. Since multiple real estate agents can add the same premises, there are still duplicates present.</p>
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>
Dataset related to article "Impact of the Extremities Positioning on the Set-Up Reproducibility for the Total Marrow Irradiation Treatment"
<p>Abstract</p><p>Total marrow (lymph node) irradiation (TMI/TMLI) delivery requires more time than standard radiotherapy treatments. The patient's extremities, through the joints, can experience large movements. The reproducibility of TMI/TMLI patients' extremities was evaluated to find the best positioning and reduce unwanted movements. Eighty TMI/TMLI patients were selected (2013-2022). During treatment, a cone-beam computed tomography (CBCT) was performed for each isocenter to reposition the patient. CBCT-CT pairs were evaluated considering: (i) online vector shift (OVS) that matched the two series; (ii) residual vector shift (RVS) to reposition the patient's extremities; (iii) qualitative agreement (range 1-5). Patients were subdivided into (i) arms either leaning on the frame or above the body; (ii) with or without a personal cushion for foot positioning. The Mann-Whitney test was considered (p < 0.05 significant). Six-hundred-twenty-nine CBCTs were analyzed. The median OVS was 4.0 mm, with only 1.6% of cases ranked < 3, and 24% of RVS > 10 mm. Arms leaning on the frame had significantly smaller RVS than above the body (median: 8.0 mm/6.0 mm, p < 0.05). Using a personal cushion for the feet significantly improved the RVS than without cushions (median: 8.5 mm/1.8 mm, p < 0.01). The role and experience of the radiotherapy team are fundamental to optimizing the TMI/TMLI patient setup.</p><p> </p>
Video 1: Working steps and features of setting virtual occlusion in mixed reality environment
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The rough set
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Supplementary Material for "Assessing the Impact of Groundwater Saturation Excess Runoff on Hydrologic Features and Processes in a Watershed Modeling Setting"
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Zebrafish (Danio rerio) Social Preference | Set 1 | PRE INTERVENTION | Processed, Acclam
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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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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.