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363 results for “stack”
tags-stack-overflow
<h3><strong>Overview</strong></h3><p>This dataset is derived from tags on Stack Overflow posts. Each hyperedge corresponds to all of the tags used in a post, and each node in a hyperedge corresponds to a tag. The timestamps of the posts are in millisecond resolution, are adjusted so that the time of the earliest tag starts at 0, and are in ISO8601 format.</p><h4><strong>Statistics</strong></h4><p>Some basic statistics of this dataset are:</p><ul><li>number of nodes: 49,998</li><li>number of timestamped hyperedges: 14,458,875</li><li>number of unique hyperedges: 5,675,497</li><li>Component sizes:</li></ul><p>Component size, number</p><ul><li>49931, 1</li><li>2, 7</li><li>1, 53</li></ul><h4><strong>Source of original data</strong></h4><ul><li><a href="https://www.cs.cornell.edu/~arb/data/tags-stack-overflow/">tags-stack-overflow dataset</a></li><li><a href="https://archive.org/details/stackexchange">StackExchange</a></li></ul><h4><strong>References</strong></h4><p>If you use this data, please cite the following paper:</p><ul><li><a href="https://doi.org/10.1073/pnas.1800683115">Simplicial closure and higher-order link prediction</a>. Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Proceedings of the National Academy of Sciences (PNAS), 2018.</li></ul>
Unveiling Challenges in Python Library: Insights from Stack Overflow
<p>A dataset of the SANER 2024 ERA track submission "Unveiling Challenges in Python Library: Insights from Stack Overflow" containing all the comments in Stack Overflow that were classified.</p>
Supporting dataset -C for "Crystallization of FAPbI3: polytypes and stacking faults"
<p>XYZ trajectory files of (111)-3R seeded growth of FAPbI3</p>
Dataset for: Unraveling the Optical Signatures of Polymeric Carbon Nitrides: Insights into Stacking-Induced Excitonic Transition
<p>This file contains a set of input and output data for simulations.</p>
Inferred stacking interactions for a dataset of proteins, nucleic acids and ligands
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A GUIDE TOWARDS FULL STACK DEVELOPMENT which was presented by Er.T.Nageswari, Technology Lead, Infosys Ltd, Trivandrum., organized by Department of Computer Applications in association with FX Alumni Association of Francis Xavier Engineering College, Tirunelveli, Tamil Nadu on 06-06-2020.
<p>A GUIDE TOWARDS FULL STACK DEVELOPMENT which was presented<br>by Er.T.Nageswari, Technology Lead, Infosys Ltd, Trivandrum., organized by Department<br>of Computer Applications in association with FX Alumni Association of Francis Xavier<br>Engineering College, Tirunelveli, Tamil Nadu on 06-06-2020.</p>
Replication Package for Automating Technical Debt Management: Insights from Practitioner Discussions in Stack Exchange
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Supplementary material 1 from: Krivak-Tetley FE, Sullivan-Stack J, Garnas JR, Zylstra KE, Höger L-O, Lombardero MJ, Liebhold AM, Ayres MP (2022) Demography of an invading forest insect reunited with hosts and parasitoids from its native range. NeoBiota 72: 81-107. https://doi.org/10.3897/neobiota.72.75392
Tables S1, S2, Figures S1–S4
Technical Debt on Agile Projects: Managers' point of view at Stack Exchange
<p>Technical Debt on Agile Projects: Managers’ point of view at Stack Exchange</p> <p>XXI Simpósio Brasileiro de Qualidade de Software (SBQS '22), Nov 07--10, 2022, 2022, Curitiba, Paraná, Brasil.</p>
Data from: Ellipsoid segmentation model for analyzing light-attenuated 3D confocal image stacks of fluorescent multi-cellular spheroids
In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation. However, several issues hamper accurate analysis. In particular, signal attenuation within the tissue of the spheroids prevents the acquisition of a complete image for spheroids over 100 micrometers in diameter. And quantitative analysis of large 3D image data sets is challenging, creating a need for methods which can be applied to large-scale experiments and account for impeding factors. We present a robust, computationally inexpensive 2.5D method for the segmentation of spheroid cultures and for counting proliferating cells within them. The spheroids are assumed to be approximately ellipsoid in shape. They are identified from information present in the Maximum Intensity Projection (MIP) and the corresponding height view, also known as Z-buffer. It alerts the user when potential bias-introducing factors cannot be compensated for and includes a compensation for signal attenuation.
Retrieving API knowledge from Tutorials and Stack Overflow based on Natural Language Queries
<p>The replication package of PLAN</p>
Supporting dataset -B for "Crystallization of FAPbI3: polytypes and stacking faults"
<p>XYZ trajectories of (100)-seeded MD simulations of crystal growth of FAPbI3</p>
Figure 3 from: Mertens JEJ, Van Roie M, Merckx J, Dekoninck W (2017) The use of low cost compact cameras with focus stacking functionality in entomological digitization projects. ZooKeys 712: 141-154. https://doi.org/10.3897/zookeys.712.20505
Figure 3 - Comparison of image quality between the compact camera (A) and the professional setup (B) with the specimen occupying the same proportion of the frame. A detail is shown below. The compact camera was set up 5 cm from the specimen with the optical zoom at 1×, 29 images (narrow setting) were manually stacked. The professional setup outperforms the compact camera, producing a sharper image when specimens larger than a few centimetres are set to fill the frame optimally.
Figure 4 from: Mertens JEJ, Van Roie M, Merckx J, Dekoninck W (2017) The use of low cost compact cameras with focus stacking functionality in entomological digitization projects. ZooKeys 712: 141-154. https://doi.org/10.3897/zookeys.712.20505
Figure 4 - Images of different taxonomic groups, shot by the compact camera in manual mode (narrow setting). A large fruit-tree tortrix (Archips podana (Lepidoptera - Tortricidae)) B European paper wasp (Polistes dominula (Hymenoptera - Vespidae)), and C common earwig (Forficula auricularia (Dermaptera - Forficulidae)).
Figure 2 from: Mertens JEJ, Van Roie M, Merckx J, Dekoninck W (2017) The use of low cost compact cameras with focus stacking functionality in entomological digitization projects. ZooKeys 712: 141-154. https://doi.org/10.3897/zookeys.712.20505
Figure 2 - Visualization of the variation in image quality, level of detail and proportion of the specimen fitting the frame (insets) at different levels of optical magnification (1–4 times) and distance from the lens (11–5 cm). Every image, shot with the compact camera, is composed of 29 manually stacked images at the narrow setting and cropped to equal dimensions (approx. 1/24 of the original image). Quality and detail improve as lens distance decreases and/or the zoom increases at the cost of reduced depth of field and a smaller portion of the specimen fitting the image frame.
Figure 1 from: Mertens JEJ, Van Roie M, Merckx J, Dekoninck W (2017) The use of low cost compact cameras with focus stacking functionality in entomological digitization projects. ZooKeys 712: 141-154. https://doi.org/10.3897/zookeys.712.20505
Figure 1 - Comparison of the Elytrimitatrix digitized with the professional setup (A shot with the 60 mm macro lens and B with the Canon MP-E 65 mm lens), the compact camera's manual focus stacking mode (C) and internal stacking mode (D). A depicts the whole specimen as would be shot for publication purposes. The red box indicates the section shown in B, C, D and the blue box indicates how the specimen was framed in these three images. Note that the stronger reflections in C, D are the result of a different lighting setup.
What Edits Are Done on The Highly Answered Questions in Stack Overflow? An Empirical Study
<p>This contains the data set and the code we take advantage of to process data and make analyzation.</p>
Replication Data for: Direct observation of van der Waals stacking dependent interlayer magnetism
<p>Data repository for: <strong>Direct observation of van der Waals stacking dependent interlayer magnetism</strong></p> <p><em>Data description.pdf </em>describes the uploaded data.<br> <em>Fig1.xlsx</em> to <em>Fig4.xlsx</em> is the data represented in the main text.<br> <em>FigS1.xlsx</em> to <em>FigS17.xlsx</em> is the data represented in the Supplementary Materials.</p>
Stacked receiver functions of SE Tibet
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Training data (bead stacks) for the red channel of the Zeiss microscope
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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.