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363 results for “stack”
Dataset of the Paper "Architecture Decisions in Quantum Software Systems: An Empirical Study on Stack Exchange and GitHub"
<p>This dataset was collected from GitHub and Stack Exchange (including Stack Overflow, Quantum Computing Stack Exchange, and Computer Science Stack Exchange) to conduct an empirical study on architecture decisions in quantum software systems. We provide below a brief description of each file:</p><p><strong>1. Dataset (GitHub).xlsx</strong></p><p>contains selected quantum software projects from GitHub with project names, issue IDs, and issue URLs and the data extracted from the GitHub issues that are related to architecture decisions in quantum software development.</p><p><strong>2. Dataset (SO).xlsx</strong></p><p>contains the IDs and URLs of Stack Overflow (SO) labeled posts and the extracted data from the Stack Overflow posts that are related to architecture decisions in quantum software development.</p><p><strong>3. Dataset (QC).xlsx</strong></p><p>contains the IDs and URLs of Quantum Computing (QC) Stack Exchange labeled posts and the extracted data from the Quantum Computing Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p><strong>4. Dataset (CS).xlsx</strong></p><p>contains the IDs and URLs of Computer Science (CS) Stack Exchange labeled posts and the extracted data from the Computer Science Stack Exchange posts that are related to architecture decisions in quantum software development.</p><p><strong>5. Extracted Data (GitHub+SO+QC+CS).xlsx</strong></p><p>provides the final results of data extracted from the related GitHub issues, SO posts, QC posts, and CS posts.</p>
Replication materials for: Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow
<p>These are the replication materials for the paper:<br>Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow<br>By: Maria del Rio-Chanona, Nadzeya Laurentsyeva, and Johannes Wachs. <br>Preprint: https://arxiv.org/abs/2307.07367<br>Under Revision for PNAS Nexus</p> <p> </p>
Abundance Trend Indicator - Models, Prediction, Stacked Environmental Data and Training Set Similarity
<p># Readme</p> <p>These trained models can be used to predict the abundance trends of New Zealand's forest species and can be used together with the code in https://github.com/lnilya/abundance-trend-indicator</p> <p>Since the process of using the models requires coding expertise and some setting up, please make sure to reach out to ilya.shabanov@vuw.ac.nz for any questions. All files will require the code in the repository to be read and used. </p> <p>If you want to explore the results generated with these models, please visit https://ati-nz-predictions-7e6f3d514735.herokuapp.com/ for a user-friendly, interactive UI.</p> <p>## Contents</p> <p>_models: Contains the trained models (Artificial Neural Network (ANN), Random Forest (RF), SVMW (Support vector machine) and GLM (logistic regression)) at different degrees of noise filtering, different datasets and variable sets. The model files also contain test and training scores. To load the files please refer to the readme in the code repository: ttps://github.com/lnilya/abundance-trend-indicator</p> <p><br>_predictions/_environment: Contains the predictor variables for the study area (New Zealand, 1950-2019) that are needed by the models to make predictions. </p> <p>_predictions/_similarity: Contains the masks of areas that can be predicted by models and are similar to the training set.</p> <p>_predictions/_ati: Contain the predicted results for the abundance trend. These can be explored on https://ati-nz-predictions-7e6f3d514735.herokuapp.com/ </p> <p> </p>
Removal of developmentally regulated microexons has a minimal impact on larval zebrafish brain morphology and function - imaging stacks
<p>Results of brain activity mapping for zebrafish mutants with microexons removed. Both brain activity and structural data is included. These stacks are the significant signal that differs between the groups. They are compatable with the Z-Brain matlab viewer from Randlett, et al, 2015 Nature Methods.</p>
Dataset of the Paper "Exploring the Problems, their Causes and Solutions of AI Pair Programming: A Study on GitHub and Stack Overflow"
<p>The dataset collected from GitHub Discussions, GitHub Issues, and Stack Overflow is used to conduct an empirical study on the problems, causes, and solutions of using GitHub Copilot in practice. A brief description of each document in the dataset is provided below:</p> <p><br><strong>1. Dataset(GitHub_Discussions).xlsx</strong></p> <p>contains the Discussion IDs and URLs in the Copilot category of GitHub Discussions, and the data extracted from the related discussions along with analysis results.</p> <p><strong>2. Dataset(GitHub_Issues).xlsx</strong></p> <p>contains the Issue IDs and URLs of the labelled issues which are related to Copilot from GitHub Issues, and the data extracted from the related issues along with analysis results.</p> <p><strong>3. Dataset(SO_Posts).xlsx</strong></p> <p>contains the SO Post IDs and URLs of the labelled posts which are related to Copilot from Stack Overflow, and the data extracted from the related posts along with analysis results.</p> <p><strong>4. Extracted_Data.xlsx</strong></p> <p>contains the final results of the data extracted from GitHub Discussions, GitHub Issues, and SO posts.</p> <p><strong>5. pilot labelling folder</strong></p> <p>contains three .xlsx files (i.e., Pilot_Labelling(GitHub_Discussions).xlsx, Pilot_Labelling(GitHub_Issues), and Pilot_Labelling(SO)), with each file corresponding to one of the three data sources and containing the pilot data labelling results with the Cohen's kappa value.</p>
The Research Software Stack
<p>A description of the differnet layers that underlying research computing in bioinformatics (from top down: research computing, bioinformatics tools & libraries, scientific libraries and general purpose computing) with the people involved in creating them (posgraduates and faculty, research software engineers and systems engineers).</p>
Stacked Dense Denoise-Segmentation Volumetric Annotations
<p>The volumetric annotations of https://doi.org/10.5281/zenodo.2645838 and https://doi.org/10.5281/zenodo.2645965 used in the Stacked Dense Denoise-Segmentation Network. For the annotation the SuRVoS workbench was used (https://doi.org/10.5281/10.5281/zenodo.247547). We acknowledge Diamond Light Source for the time on I13-2 under proposal mt9396.</p>
Stacked Dense Denoise-Segmentation FBP reconstruction from 3601 projection
<p>The FBP recontruction from 3601 projection of the dataset used in the Stacked Dense Denoise-Segmentation Network. For the reconstruction the Savu Python package was used (https://doi.org/10.5281/zenodo.32840). We acknowledge Diamond Light Source for the time on I13-2 under proposal mt9396.</p>
Stacked Dense Denoise-Segmentation CGLS reconstruction from 91 projection
<p>The CGLS recontruction from 91 projection of the dataset used in the Stacked Dense Denoise-Segmentation Network. For the reconstruction the Savu Python package was used (https://doi.org/10.5281/zenodo.32840). We acknowledge Diamond Light Source for the time on I13-2 under proposal mt9396.</p>
[Dataset] ColocZStats: A Z-Stack Signal Colocalization Extension Tool for 3D Slicer
<p>To showcase the capabilities of ColocZStats discussed in its manuscript, we utilized confocal z-stack data collected during a study on the colocalization of DSS1 nuclear bodies with other nuclear body types. DSS1, also known as SEM1, is a gene that encodes a protein crucial for various cellular processes, most notably the function of the 26S proteasome complex in protein degradation. More specifically, a human ovarian clear cell carcinoma cell line (RMG-I) was seeded at 100,000 cells per well onto a coverslip in a 6-well plate and allowed to grow till 70\% confluency. On the day of staining, the cells were fixed with 4\% ice-cold paraformaldehyde for 15 mins at room temperature (RT) and blocked with 2\% Bovine Serum Albumin (BSA) in 0.1\% Phosphate Buffer Saline containing 0.1\% Triton-X (PBSTx) for 30 mins. Following fixation and blocking, the cells were incubated with a primary antibody cocktail containing anti-DSS1 (Catalogue\# NB100-1334, Novus Biologicals) and anti-PML (Catalogue\#sc-966, SCBT) for 1h at RT. After that, the cells were washed 3 times with 0.1\% PBSTx for 5 mins each and incubated with a secondary antibody cocktail containing anti-goat Alexa FluorTM 647 (for DSS1), anti-mouse Alexa FluorTM 488 (for PML) and Hoechst 33342 (Catalogue\# H3570, Invitrogen) for 1h at RT. Following this incubation, the cells were subjected to 3 washes, each lasting 5 mins, with 0.1\% PBSTx to ensure thorough cleansing. Subsequently, z-stack imaging was performed using a Zeiss LSM800 confocal microscope with Airyscan. The above process utilized three distinct dyes to specifically label DSS1 nuclear bodies (Red), promyelocytic leukemia (PML) nuclear bodies (Green), and the nucleus (Blue). The data file was named ‘Sample Image Stack.tif’.</p>
Spectral and Z stack images of sofa eye zebrafish
<p>This is a z-stacks with spectral imaging acquired in a Confocal Zeiss 880 LSM Microscope at the Institut Psteur Montevideo.</p> <p>Samples correspond to the eye of sofa zebrafish.</p> <p>For more informatio about the Sofa line, please see the following reference.</p> <p>Almeida AD, Boije H, Chow RW, He J, Tham J, Suzuki SC, Harris WA. Spectrum of Fates: a new approach to the study of the developing zebrafish retina. Development. 2014 May;141(9):1971-80. doi: 10.1242/dev.104760. Epub 2014 Apr 9. Erratum in: Development. 2014 Jul;141(14):2912. PMID: 24718991; PMCID: PMC3994774.</p>
Exploring Accessibility Trends and Challenges in Mobile App Development: A Study of Stack Overflow Questions
<p>This is the dataset for the paper: Exploring Accessibility Trends and Challenges in Mobile App Development: A Study of Stack Overflow Questions</p> <p>This paper was accepted for publication at the 58th Hawaii International Conference on System Sciences (HICSS) - Software Technology Track</p> <p>Preprint: <a href="https://arxiv.org/abs/2409.07945">https://arxiv.org/abs/2409.07945</a></p>
Mobile App Security Trends and Topics: An Examination of Questions From Stack Overflow
<p>This is the dataset for the paper: Mobile App Security Trends and Topics: An Examination of Questions From Stack Overflow</p> <p>This paper was accepted for publication at the 58th Hawaii International Conference on System Sciences (HICSS) - Software Technology Track</p> <p>Preprint: <a href="https://arxiv.org/abs/2409.07926">https://arxiv.org/abs/2409.07926</a></p>
Dataset: Stack pressure on lithium-ion pouch cells: a comparative study of constant pressure and fixed displacement devices
<p>Dataset for the paper Experimental Investigation of Power Available in Lithium-Ion Batteries.</p> <ul> <li>Battery: Melasta LCO 6.8Ah pouch cell</li> </ul> <p>Static Pressure Loss:</p> <ul> <li>Test 01: Fixed displacement device</li> <li>Test 02: Constant pressure (springs)</li> <li>Test 03: Constant pressure (pneumatic)</li> </ul> <p>Dynamic pressure variation:</p> <ul> <li>Test 04</li> </ul> <p>Spring stiffness investigation:</p> <ul> <li>Test 05</li> </ul> <p> </p>
Stack Overflow's Hidden Nuances: How Does Zip Code Define User Contribution? – Replication Package
<p>Collective intelligence constitutes a foundational element within online community question-and-answering (CQA) platforms, such as Stack Overflow, being the source of most programming-related issues. Despite this relevance, concerns remain regarding issues surrounding user participation. Precedent research tends to focus on simple numerical measurements to analyse participation, which may sideline the inherent, subtler aspects.</p> <p>The proposed study aims to bridge this gap by operationalising 11 distinct metrics to represent user participation, behaviour, and community value across different regions of the USA. The study also conducts inductive content analysis to understand the impact of regional contextual factors on users' knowledge sharing patterns.</p> <p>This replication package is provided for those interested in further examining our research methodology.</p>
A Cross-Continental Analysis of How Regional Cues Shape Developers' Stack Overflow Contributions – Replication Package
<p>Stack Overflow provides a wide range of knowledge for the software development community. Despite the importance of these platforms, several studies have shown that digital information tends to cluster geographically, which limits knowledge access that is otherwise necessary for innovation.</p> <p>The proposed study highlights the dynamics of users from different geographical backgrounds within Stack Overflow, which entails intra-country interactions, predominant topics of discourse, as well as their communication patterns. Finally, the study highlights that regional behavioural variations stem beyond cultural factors, encompassing technological advancement, entrepreneurial ventures, and workforce composition. </p> <p>This replication package is provided for those interested in further examining our research methodology.</p>
Stack Overflow's Hidden Nuances: How Does Zip Code Define User Contribution? – Replication Package
<p>Collective intelligence constitutes a foundational element within online community question-and-answering (CQA) platforms, such as Stack Overflow, being the source of most programming-related issues. Despite this relevance, concerns remain regarding issues surrounding user participation. Precedent research tends to focus on simple numerical measurements to analyse participation, which may sideline the inherent, subtler aspects.</p> <p>The proposed study aims to bridge this gap by operationalising 11 distinct metrics to represent user participation, behaviour, and community value across different regions of the USA. The study also conducts inductive content analysis to understand the impact of regional contextual factors on users' knowledge sharing patterns.</p> <p>This replication package is provided for those interested in further examining our research methodology.</p>
SAR Stack of Pichincha volcano in Ecuador, from Sentinel-1 processed with GAMMA
<p>A stack of Coregistered SLCs on Pichincha volcano, Ecuador</p> <p>Sensor: Sentinel-1 Descending track 142</p> <p>Time: 2016.04.19 - 2018.12.28, 52 acquisitions</p> <p>Processor: GAMMA</p> <p>This is an input dataset for the time series analysis with <a href="https://github.com/insarlab/MiaplPy">MiaplPy</a>.</p> <p>This dataset is similar to <a href="https://doi.org/10.5281/zenodo.6539952">SAR Stack of Pichincha volcano in Ecuador, from Sentinel-1</a>, but has been pre-processed with GAMMA software. </p>
FIGURE 3 in Substituting time-consuming pencil drawings in arthropod taxonomy using stacks of digital photographs
FIGURE 3. Creation of the drawing with the WACOM board using a crustacean appendage as an example. a, stacks of micrographs are imported in a drawing software and arranged into one picture; focus levels can be selected by clicking on the level selector (arrow); b, the outlines of the photos are made using the levels of the stacks that are in focus; c, once all details are drawn, the photos are deselected and the drawing can be used.
FIGURE 2 in Substituting time-consuming pencil drawings in arthropod taxonomy using stacks of digital photographs
FIGURE 2. Making of micrographs. a, stacks of photos are taken with a camera mounted on a microscope (1), directly transferred onto a computer (2) and drawn with a WACOM Intuous 2 DIN A3 drawing tablet (3); b, all camera functions are controlled by the remote capture task software, in the preview window of this software where focus of the microscope is being controlled. Moving the lever 1 up will zoom out the dark margins; pushing the button 2 will expose a picture and automatically transfers it onto the computer.
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.