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Dataset results
31 results for “Core Developer”
Supplementary Material for Work Practices and Perceptions from Women Core Developers in OSS Communities
<p>Supplementary Material for Work Practices and Perceptions from Women Core Developers in OSS Communities which allows to reproduce and extend the results presented in the paper study.</p>
Expert consensus on core topics of sustainable development online learning module for family physicians: A Delphi study
<p><strong>Objectives</strong></p> <p>Medical institutions must provide learning experiences that enhance the knowledge and perspectives of Sustainable Development (SD) to prepare trainees of family medicine to become competent global citizens. The aim of this study was to develop an SD online learning module for trainees of family medicine.</p> <p><strong>Design</strong></p> <p>This mixed-methods study was conducted from January 2020 to May 2021, beginning with a literature review concerning Sustainable Development Goals (SDG) and Education for Sustainable Development (ESD) in medicine. In-depth interviews were held to assess the relevant needs of family medic<span>ine</span> training, followed by a two-round Delphi survey with experienced educators (n = 21) in family medicine to refine and achieve consensus on the appropriate SDG topics for family physicians.</p> <p><strong>Setting</strong></p> <p>All residency training programmes in Thailand.</p> <p><strong>Participants</strong></p> <p>Members of the Residency Training Committee, Royal College of Family Physicians of Thailand.</p> <p><strong>Results</strong></p> <p>The literature review and in-depth interviews identified 12 topics of SD that were required for family physicians. The first round of the Delphi survey was concluded by identifying 7 core topics with additional suggestions. In the second round, a consensus was obtained among the experienced educators regarding 7 core topics: 1) A definition of SD, 2) Principles of SD, 3) SDG, 4) A new concept of SD, 5) SD in the context of Thailand, 6) SD and principles of family medicine and 7) SD and family practice. These core topics were grouped within three main objectives and three sub-modules.</p> <p><strong>Conclusions</strong></p> <p>An online <span>learning module of SD for family physicians was developed using a modified Delphi method. This included three sub-modules: 1) Concept and principles of SD, 2) SDG and 3) SD and its integration with family practice. This online learning module will provide additional resources for trainees of family medicine and Thai family physicians to expand their knowledge and perspectives of sustainable development.</span></p>
Expert consensus on core topics of sustainable development online learning module for family physicians: A Delphi study
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Data from: Genome-wide assessment of population structure and genetic diversity and development of a core germplasm set for sweet potato based on specific length amplified fragment (SLAF) sequencing
Sweet potato, Ipomoea batatas (L.) Lam., is an important food crop that is cultivated worldwide. However, no genome-wide assessment of the genetic diversity of sweet potato has been reported to date. In the present study, the population structure and genetic diversity of 197 sweet potato accessions most of which were from China were assessed using 62,363 SNPs. A model-based structure analysis divided the accessions into three groups: group 1, group 2 and group 3. The genetic relationships among the accessions were evaluated using a phylogenetic tree, which clustered all the accessions into three major groups. A principal component analysis (PCA) showed that the accessions were distributed according to their population structure. The mean genetic distance among accessions ranged from 0.290 for group 1 to 0.311 for group 3, and the mean polymorphic information content (PIC) ranged from 0.232 for group 1 to 0.251 for group 3. The mean minor allele frequency (MAF) ranged from 0.207 for group 1 to 0.222 for group 3. Analysis of molecular variance (AMOVA) showed that the maximum diversity was within accessions (89.569%). Using CoreHunter software, a core set of 39 accessions was obtained, which accounted for approximately 19.8% of the total collection. The core germplasm set of sweet potato developed will be a valuable resource for future sweet potato improvement strategies.
Resulting Pseudonymized Classification Data for "Automatic Core-Developer Identification on GitHub: A Validation Study"
<p>Resulting pseudonymized classification data of the study "Automatic Core-Developer Identification on GitHub: A Validation Study". The corresponding input data, from which the output data have been derived, can be found here: https://zenodo.org/record/7775078</p>
Pseudonymized Raw Data for "Automatic Core-Developer Identification on GitHub: A Validation Study"
<p>Pseudonymized raw data (i.e., commit data and issue data for 25 GitHub projects) that has been used as input for the study published as "Automatic Core-Developer Identification on GitHub: A Validation Study".</p> <p>The pseudonymized raw data has been extracted via the tools <a href="https://github.com/se-sic/codeface/">Codeface</a>, <a href="https://github.com/se-sic/GitHubWrapper/">GitHubWrapper</a>, <a href="https://github.com/mehdigolzadeh/BoDeGHa">BoDeGHa</a>, and <a href="https://github.com/se-sic/codeface-extraction/">codeface-extraction</a> (and additional manual corrections after sanity checks).</p>
Core Stability Measures as a Risk Factor for the Development of Lower Extremity Injuries in Physical Education Students
ClinicalTrials.gov study NCT03343379. IPD Sharing: NO. Countries: 1. Publications: 4.
Data-driven Development of a Core Dataset for Difficult Airway Alerts
ClinicalTrials.gov study NCT07275567. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Development a Core Set for Adults With Cystic Fibrosis Based on the ICF
ClinicalTrials.gov study NCT06128499. IPD Sharing: NO. Countries: 1. Publications: 18.
Development of an ICF Core Set for Geriatric Patients in Primary Care
ClinicalTrials.gov study NCT03384732. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Data from: Genome-wide assessment of population structure and genetic diversity and development of a core germplasm set for sweet potato based on specific length amplified fragment (SLAF) sequencing
Open the record for dataset details and reuse information.
On The Development of Multidimensional Progenitor Models For Core-collapse Supernovae
<p>Eight multi-dimensional core-collapse supernova progenitor models from work, 'On The Development of Multidimensional Progenitor Models For Core-collapse Supernovae'. Works that utilize these progenitor models are required to cite article. All models are given at 424 seconds, less than a second before iron core-collapse. The 3D 4pi models were evolved to 424.31 seconds, the collapse time according to the 1D MESA model. All data are in FLASH4 format using the HDF5 data structure. </p>
Supplementary material 2 from: Woodburn M, Buschbom J, Grant S, Jones J, Norton B, Trekels M, Vincent S, Webbink K (2023) No Pain No Gain: Standards mapping in Latimer Core development. Biodiversity Information Science and Standards 7: e113053. https://doi.org/10.3897/biss.7.113053
Extended SSSOM mappings
Supplementary material 1 from: Woodburn M, Buschbom J, Grant S, Jones J, Norton B, Trekels M, Vincent S, Webbink K (2023) No Pain No Gain: Standards mapping in Latimer Core development. Biodiversity Information Science and Standards 7: e113053. https://doi.org/10.3897/biss.7.113053
SKOS mappings
A quantitative computational framework for allopolyploid single-cell data integration and core gene ranking in development [scRNA-seq]
GEO Series GSE224228. Triticum aestivum. 2 samples. Type: Expression profiling by high throughput sequencing.
A network of core promoter factors in developing Drosophila brains
GEO Series GSE120433. Drosophila melanogaster. 20 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Ronin governs early heart development by controlling core gene programs
GEO Series GSE103959. Mus musculus. 22 samples. Type: Expression profiling by array.
Pitx1 directly controls the core limb development program to implement hindlimb identity
GEO Series GSE100734. Mus musculus. 36 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Pitx1 directly controls the core limb development program to implement hindlimb identity [ChIP-Seq]
GEO Series GSE100728. Mus musculus. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Supplementary Website, Data, and Scripts for the Paper "Automatic Core-Developer Identification on GitHub: A Validation Study"
<p>Supplementary website containing result plots, pseudonymized input data, resulting pseudonymized classification data, analysis scripts, and Dockerfile used to produce the results of the paper "Automatic Core-Developer Identification on GitHub: A Validation Study".</p> <p>The pseudonymized input data is also availble separately here: https://zenodo.org/record/7775078</p> <p>The resulting pseudonymized classification data is also available separately here: https://zenodo.org/record/7775385</p>
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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)
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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.