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8,537 results for “Openness”
Artifact for "Inside Bug Report Templates: An Empirical Study on Bug Report Templates in Open-Source Software"
<p>This is the artifact for the paper "Inside Bug Report Templates: An Empirical Study on Bug Report Templates in Open-Source Software".</p> <p><strong>What the artifact does:</strong><br>1) a questionnaire that we used for our online survey (PDF);<br>2) the valid responses of our online survey (CSV).</p> <p>3) the code of preprocessing (.py).</p> <p>4) the dataset of preprocessing and labeling (CSV).</p>
Impact of open bioinformatics resources on industry (worked example for an ELIXIR deposition database)
Open the record for dataset details and reuse information.
Adaptive sampling-based structural prediction reveals opening of a GABAA receptor through the αβ interface
<p>These are the simulation of an open state of α1β2<span>γ</span><span>2 GABAA receptor. There are five replicates, each for 200 ns, saved with every ns freequency. The prot_masses.pdb is the desenstized starting state model and the .dcd files are simualtion frames of the open state. </span></p>
Estimating Usage Of Open Source Projects - Flutter Telemetry Case Study - MSR' 24
<p>This dataset (CSV) was assembled to support analysis within a case study that will be published in the proceedings of the <a href="https://conf.researchr.org/home/msr-2024">Mining Software Repositories</a> conference (MSR ‘24) April 14-15 2024: <a title="Estimating Usage Of Open Source Projects" href="https://doi.org/10.1145/3643991.3645066">Estimating Usage Of Open Source Projects.</a></p> <p>This case study explored whether publicly available metrics could serve as proxies to estimate usage of an open source project. Using the <a href="https://flutter.dev/">Flutter</a> project as our case study, we collected monthly proxy metrics from GitHub, StackOverflow and Slack to compare with Flutter’s monthly active user count over the same time period: January 2018 through February 2021.</p> <p>All metrics correspond to the last day of the month and/or represent aggregate activity in that month. Data from GitHub shows aggregate activity counts across the entire <a href="https://github.com/flutter">Flutter GitHub organization</a> (up to 33 repositories). </p> <p>Our specific metrics include:</p> <div> <table> <tbody> <tr> <td> <p>Source</p> </td> <td> <p>Metric</p> </td> <td> <p>Aggregation method</p> </td> <td> <p>Details</p> </td> </tr> <tr> <td> <p>Flutter</p> </td> <td> <p>Monthly Active Users (MAU)</p> </td> <td> <p>Google internal tooling</p> </td> <td> <p>Flutter users active in the last 30 days, collected on the last day of each month</p> </td> </tr> <tr> <td> <p>GitHub</p> </td> <td> <p>PullRequest Authors in month</p> </td> <td> <p><a href="https://chaoss.github.io/grimoirelab/">GrimoireLab</a>, hosted by <a href="http://bitergia.com">bitergia.com</a></p> </td> <td> <p>As Google governs changes to this code base, we excluded known Google employees in code change related metrics </p> </td> </tr> <tr> <td> <p>GitHub</p> </td> <td> <p>Issues Created in month</p> </td> <td> <p><a href="https://chaoss.github.io/grimoirelab/">GrimoireLab</a>, hosted by <a href="http://bitergia.com">bitergia.com</a></p> </td> <td> </td> </tr> <tr> <td> <p>GitHub</p> </td> <td> <p>Issue Authors in month</p> </td> <td> <p><a href="https://chaoss.github.io/grimoirelab/">GrimoireLab</a>, hosted by <a href="http://bitergia.com">bitergia.com</a></p> </td> <td> </td> </tr> <tr> <td> <p>GitHub</p> </td> <td> <p>Fork events in month</p> </td> <td> <p><a href="http://gharchive.org">gharchive.org</a></p> </td> <td> </td> </tr> <tr> <td> <p>GitHub</p> </td> <td> <p>Fork cumulative count at the end of month</p> </td> <td> <p><a href="http://gharchive.org">gharchive.org</a></p> </td> <td> </td> </tr> <tr> <td> <p>StackOverflow</p> </td> <td> <p>Question Authors in month</p> </td> <td> <p><a href="https://chaoss.github.io/grimoirelab/">GrimoireLab</a>, hosted by <a href="http://bitergia.com">bitergia.com</a></p> </td> <td> </td> </tr> <tr> <td> <p>StackOverflow</p> </td> <td> <p>Questions in month</p> </td> <td> <p><a href="https://chaoss.github.io/grimoirelab/">GrimoireLab</a>, hosted by <a href="http://bitergia.com">bitergia.com</a></p> </td> <td> </td> </tr> <tr> <td> <p>Slack</p> </td> <td> <p>Claimed (cumulative) members at the end of the month</p> </td> <td> <p>fluttercommunity.slack</p> </td> <td> </td> </tr> <tr> <td> <p>Slack</p> </td> <td> <p>Cumulative messages at the end of the month</p> </td> <td> <p>fluttercommunity.slack</p> </td> <td> </td> </tr> </tbody> </table> </div> <p>Tools: </p> <ul> <li> <p>We used an instance of <a href="https://chaoss.github.io/grimoirelab/">GrimoireLab</a> hosted by <a href="https://bitergia.com/">Bitergia</a> to aggregate GitHub PullRequest Authors, GitHub Issue Authors, GitHub Issues, across all repositories under the Flutter Organization, and StackOverflow Question Authors, and StackOverflow Questions for questions that mention Flutter. We used the <a href="http://github.com/chaoss/grimoirelab-sortinghat">Sorting Hat</a> of feature GrimoireLab to identify Google employees in this sample.</p> </li> </ul> <ul> <li> <p><a href="http://gharchive.org">GHArchive</a> via <a href="https://cloud.google.com/blog/topics/public-datasets/github-on-bigquery-analyze-all-the-open-source-code">BigQuery</a> was used to count GitHub Star and Fork events across all repositories under the Flutter Organization</p> </li> <li> <p>We pulled Slack activity directly from <a href="http://fluttercommunity.slack.com">Flutter's slack channel </a>dashboard</p> </li> </ul>
Intracorporeal vs. extracorporeal open and closed knot tying techniques in laparoscopy: A randomized, controlled study
<p><strong><span>Background:</span></strong><span> Suturing is one of the most challenging tasks in laparoscopic surgery. Ensuring both the ease and speed of suturing has benefits not only for the surgeon, but can dramatically decrease operating time. Therefore, this study aimed to compare extracorporeal and intracorporeal suturing techniques using a Szabo pelvic trainer model from the Gynaecological Endoscopic Surgical Education and Assessment program. </span></p> <p><strong><span>Methods:</span></strong><span> Fifty-seven medical students with no experience in laparoscopy performed intra and extracorporeal knots using closed and open jaw knot pushers. Using an artificial tissue suturing pad in a certified Szabo pelvic trainer, students made three knots using each technique according to block randomization. Task completion time, knot strength, knot-spread ability, and the number of errors were recorded. The Wilcoxon test and mixed-effects models were used to analyze the results. After completing the exercises, participants answered a questionnaire concerning the suturing techniques and their performance.</span></p> <p><strong><span>Results:</span></strong><span><strong> </strong>Open and closed extracorporeal suturing resulted in significantly faster (P<0.001, P<0.001, respectively), more precise (P=0.007, P=0.003) and decreased knot spread ability (P<0.001, P<0.001) when compared to intracorporeal suturing. Open vs. closed jaw knot pushers were shown to be equal in regard to speed (p=0.563), knot spread ability (p = 0.49) and precision (p=0.831). Open (30%) and closed (49%) extracorporeal suturing was rated as more intuitive than intracorporeal (21%) suturing by study participants. Better concentration was correlated with increased knot strength (p = 0.063) and significantly tighter knots (p = 0.011). </span></p> <p><strong><span>Conclusions:</span></strong><span> Students achieved significantly better results using extracorporeal suturing techniques compared to intracorporeal ones including greater speed, tighter knots, and optimized precision. These results suggest that beginners in the field of laparoscopy should be encouraged to practice extracorporeal suturing techniques.</span></p>
CDIPS Light Curves from the paper "Confirming the Tidal Tails of the Young Open Cluster Blanco 1 with TESS Rotation Periods"
<p>This dataset contains the CDIPS light curves used in the paper "Confirming the Tidal Tails of the Young Open Cluster Blanco 1 with TESS Rotation Periods". The abstract of the original paper is as follows.</p> <p>Blanco 1 is an ≈ 130 Myr open cluster located 240 pc from the Sun below the Galactic plane. Recent studies have reported the existence of diffuse tidal tails extending 50–60 pc from the cluster center, based on the positions and velocities measured by Gaia. To independently assess the reality and extent of this structure, we used light curves generated from TESS full-frame images to search for photometric rotation periods of stars in and around Blanco 1. We detected rotation periods down to a stellar effective temperature of ≈ 3100 K in 347 of the 603 cluster member candidates for which we have light curves. For cluster members in the core and candidate members in the tidal tails, both within a temperature range of 4400 to 6200 K, 74% and 72% of the rotation periods are consistent with the single-star gyrochronological sequence, respectively. In contrast, a comparison sample of field stars yielded gyrochrone-consistent rotation periods for only 8.5% of stars. The tidal tail candidates' overall conformance to the core members' gyrochrone sequence implies that their contamination ratio is consistent with zero and < 0.33 at the 2σ level. This result confirms the existence of Blanco 1 tidal tails and doubles the number of Blanco 1 members for which there are both spatio-kinematic and rotation-based cluster membership verification. Extending the strategy of using TESS light curves for gyrochronology to other nearby young open clusters and stellar associations may provide a viable strategy for mapping out their dissolution and broadening the search for young exoplanets.</p>
Kuopio Tomography Challenge 2023 open electrical impedance tomographic dataset (KTC 2023)
<p><strong>Notice: v3 update 17.4.2023. Ground truth images were corrected slightly. The older ground truth images had a geometric distortion caused by cropping the photographs to the outer boundary of the imaging chamber, instead of the inner boundary on which the measurement electrodes were located. In addition, version 3 now contains both the limited EIT data used in the challenge evaluation, as well as the full EIT data with no measurements left out.</strong></p> <p><strong>It is recommended to download version v3 and replace the v2 version with it if using the data for research purposes.</strong></p> <p>This dataset is primarily designed for the Kuopio Tomography Challenge 2023 (KTC 2023), but it can be used for generic algorithm research and development in 2D Electric Impedance Tomography (EIT) image reconstruction. The purpose of KTC 2023 is to develop algorithms for electric impedance tomography image reconstruction with limited data.</p> <p>The dataset contains electric impedance tomography data collected from phantoms made up of a cylindrical water chamber with inclusions of varying shapes and sizes present. The data consists of electrical measurements collected using electrodes placed at the chamber boundary, i.e. the values of electric current injected between two electrodes at a time, and the resulting voltages between adjacent electrode pairs. The data has been stored in the MATLAB .mat format.</p> <p>The training dataset contains data measured from five training phantoms. These are designed to facilitate algorithm development and benchmarking for the challenge itself. Four of the training phantoms contained inclusions, which were either resistive or conductive in comparison to the water in the imaging chamber. The fifth training phantom was the imaging chamber filled with only water. We encourage subsampling these datasets to create limited datasets and comparing the reconstruction results to the ground truth obtainable from the full electrode data.</p> <p>The actual challenge data is arranged into seven different difficulty levels, labeled 1-7, with each level containing three different phantoms, labeled A-C. As the difficulty level increases, the number of inclusions increases and their shapes become increasingly complex. Furthermore, the measurement data is made more limited by removing measurements collected by some of the electrodes. At each difficulty level above level 1, the data collected from two of the boundary electrodes is removed.</p> <p>To illustrate a solution to the KTC2023, we have included a simple example reconstruction algorithm, and a Finite Element Method based forward solver used by the reconstruction algorithm. These are provided as both Matlab and Python codes. The reconstructions were computed using linearized difference imaging, and the resulting (EIT) images were then segmented using Otsu's method.</p> <p>The competitors do not need to follow the above procedure, and are encouraged to explore various image reconstruction and segmentation techniques.</p> <p>The full data for all the test phantoms will be released after the Kuopio Tomography Challenge 2023 has ended. This data has now been added to this dataset as EvaluationData.zip.</p> <p>All measurements were conducted at the Process Tomography Laboratory at the University of Eastern Finland.</p> <p> </p> <p> </p>
Euonymus americanus (Celastraceae) - fruit - section or open
Image of Euonymus americanus (Celastraceae) - fruit - section or open
Rudbeckia amplexicaulis (Asteraceae) - fruit - section or open
Image of Rudbeckia amplexicaulis (Asteraceae) - fruit - section or open
Jeffersonia diphylla (Berberidaceae) - fruit - section or open
Image of Jeffersonia diphylla (Berberidaceae) - fruit - section or open
Jeffersonia diphylla (Berberidaceae) - fruit - section or open
Image of Jeffersonia diphylla (Berberidaceae) - fruit - section or open
Pinus resinosa (Pinaceae) - cone - female - mature open
Image of Pinus resinosa (Pinaceae) - cone - female - mature open
Pinus resinosa (Pinaceae) - cone - female - mature open
Image of Pinus resinosa (Pinaceae) - cone - female - mature open
Pinus strobus (Pinaceae) - cone - female - mature open
Image of Pinus strobus (Pinaceae) - cone - female - mature open
Xyris tennesseensis (Xyridaceae) - fruit - section or open
Image of Xyris tennesseensis (Xyridaceae) - fruit - section or open
Hedyotis crassifolia (Rubiaceae) - fruit - section or open
Image of Hedyotis crassifolia (Rubiaceae) - fruit - section or open
Hedyotis crassifolia (Rubiaceae) - fruit - section or open
Image of Hedyotis crassifolia (Rubiaceae) - fruit - section or open
Hedyotis crassifolia (Rubiaceae) - fruit - section or open
Image of Hedyotis crassifolia (Rubiaceae) - fruit - section or open
Xyris tennesseensis (Xyridaceae) - fruit - section or open
Image of Xyris tennesseensis (Xyridaceae) - fruit - section or open
Xyris tennesseensis (Xyridaceae) - fruit - section or open
Image of Xyris tennesseensis (Xyridaceae) - fruit - section or open
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.