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363
datasets available to search
ShareScore release 0.9.0
Dataset results
363 results for “stack”
Effects Of Breath And Stacking-Spirometry Incentive in Patients With Parkinson's Disease
ClinicalTrials.gov study NCT01932684. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Effects of Pursed Lip Breathing Technique Versus Stacked Breathing Technique Among Chronic Bronchitis Patients
ClinicalTrials.gov study NCT06242210. IPD Sharing: NO. Countries: 1. Publications: 3.
Seroquel STACK Study in Schizophrenic or Schizoaffective Subjects
ClinicalTrials.gov study NCT00328978. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Air Stacking Technique For Pulmonary Reexpansion
ClinicalTrials.gov study NCT05702411. IPD Sharing: NO. Countries: 1. Publications: 54.
Data from: Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches
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Data from: Stacking the odds: light pollution may shift the balance in an ancient predator-prey arms race
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Data from: Comparing ant morphology measurements from microscope and online AntWeb.org 2D z-stacked images
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LSFM-image z-stack of an optically cleared porcine adipose tissue sample
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Histological stacks for: Vestigial structures and variation in the evolution of the marsupial mammal dental development: A study of the Woolly Opossum Caluromys philander
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Data from: Testing species assemblage predictions from stacked and joint species distribution models
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Data from: How to best threshold and validate stacked species assemblages? Community optimisation might hold the answer
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fMRI/fPACT 3D image stacks and analysis codes for function
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Original CT image stacks of five fossil petrosal bones from Siberia, 3D PDF files of reconstructed endocasts, blood vessels and innervation patterns, 3D PDF instruction file, STL files of the petrosals
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An Annotated Dataset of Stack Overflow Post Edits
<p>To improve software engineering, software repositories have been mined for code snippets and bug fixes. Typically, this mining takes place at the level of files or commits. To be able to dig deeper and to extract insights at a higher resolution, we hereby present an annotated dataset that contains over 7 million edits of code and text on Stack Overflow. Our preliminary study indicates that these edits might be a treasure trove for mining information about fine-grained patches, e.g., for the optimisation of non-functional properties.</p> <p>EDIT: In the more recent version I fixed <a href="https://zenodo.org/api/files/85e326db-29e3-432f-bf30-cb88deb89deb/GetEditContent.sql">GetEditContent.sql</a>, which had an ambiguous column name in one of the select statements.</p>
Dataset for the paper: Generating Question Titles for Stack Overflow from Mined Code Snippets
<p>This is the dataset for our paper: Generating Question Titles for Stack Overflow from Mined Code Snippets</p> <p>All the data are extracted from the Stack Overflow data dump, please feel free to use! :)</p>
Satellite-derived long-term estimates of full-coverage PM1 concentrations across China based on a stacking decision tree model
<p>The open data uploaded by Rui Li</p>
Are comments on Stack Overflow well organized for easy retrieval by developers?
<p>Many Stack Overflow answers have associated informative comments that can strengthen them and assist developers. A prior study found that comments can provide additional information to point out issues in their associated answer, such as the obsolescence of an answer. By showing more informative comments (e.g., the ones with higher scores) and hiding less informative ones, developers can more effectively retrieve information from the comments that are associated with an answer. Currently, Stack Overflow prioritizes the display of comments and as a result, 4.4 million comments (possibly including informative comments) are hidden by default from developers. In this study, we investigate whether this mechanism effectively organizes informative comments. We find that: 1) The current comment organization mechanism does not work well due to the large amount of tie-scored comments (e.g., 87% of the comments have 0-score). 2) In 97.3% of answers with hidden comments, at least one comment that is possibly informative is hidden while another comment with the same score is shown (i.e., unfairly hidden comments). The longest unfairly hidden comment is more likely to be informative than the shortest one. Our findings highlight that Stack Overflow should consider adjusting the comment organization mechanism to help developers effectively retrieve informative comments. Furthermore, we build a classifier that can effectively distinguish informative comments from uninformative comments. We also evaluate two alternative comment organization mechanisms (i.e., the <em>Length</em> mechanism and the <em>Random</em> mechanism) based on text similarity and the prediction of our classifier.</p>
Training sets of complexes of fluorescent proteins chromophores in pi-stacking with substituted benzenes and imidazoles
<p>each zip archive containes a subset with the corresponding chromophore</p>
X-ray microtomography of Baltelater bipectinatus gen. et sp. nov., holotype, 6685 (MAIG) (stack data).
<p>X-ray microtomography of <em>Baltelater bipectinatus </em>gen. et sp. nov., holotype, 6685 (MAIG) (stack data).</p>
Data from: Automated segmentation of skin strata in reflectance confocal microscopy depth stacks
Reflectance confocal microscopy (RCM) is a powerful tool for in-vivo examination of a variety of skin diseases. However, current use of RCM depends on qualitative examination by a human expert to look for specific features in the different strata of the skin. Developing approaches to quantify features in RCM imagery requires an automated understanding of what anatomical strata is present in a given en-face section. This work presents an automated approach using a bag of features approach to represent en-face sections and a logistic regression classifier to classify sections into one of four classes (stratum corneum, viable epidermis, dermal-epidermal junction and papillary dermis). This approach was developed and tested using a dataset of 308 depth stacks from 54 volunteers in two age groups (20–30 and 50–70 years of age). The classification accuracy on the test set was 85.6%. The mean absolute error in determining the interface depth for each of the stratum corneum/viable epidermis, viable epidermis/dermal-epidermal junction and dermal-epidermal junction/papillary dermis interfaces were 3.1 μm, 6.0 μm and 5.5 μm respectively. The probabilities predicted by the classifier in the test set showed that the classifier learned an effective model of the anatomy of human skin.
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.