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18,621 results for “development;”
Dataset for an article "Developing best practices for conducting STEM engineering projects in higher education"
<p>These articles are part of the dataset used in the article. </p> <p>These articles are anonymized manuscript drafts that were not published in the journal with other articles.</p> <p>Read more from LUMAT-B:<span> <a href="https://urn.fi/urn:nbn:fi:hulib:editori:lumatb.v9i17"> https://urn.fi/urn:nbn:fi:hulib:editori:lumatb.v9i17 </a> </span></p>
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0- Part 1: System description and preliminary experimental results
<table> <tbody> <tr> <td> <p><span>DA_BC</span></p> </td> <td> <p><span>Assimilating only BC surface observations while excluding operational meteorological observations</span></p> </td> </tr> <tr> <td> <p><span>DA_MET</span></p> </td> <td> <p><span>Assimilating only operational meteorological observations while excluding BC surface observations</span></p> </td> </tr> <tr> <td> <p><span>DA_MET_then_BC</span></p> </td> <td> <p><span>First assimilating operational meteorological observations, then assimilating BC surface observations</span></p> </td> </tr> <tr> <td> <p><span>DA_MET_BC_simult</span></p> </td> <td> <p><span>Assimilating both operational meteorological and BC surface observations </span><span>simultaneously</span></p> </td> </tr> <tr> <td>code.zip</td> <td>Including black carbon observation preprocessing codes, black carbon observation operator codes, black carbon module tangent and adjoint interface codes, the CMA-GFS-AERO 4D-Var main program,and drawing script.</td> </tr> </tbody> </table>
Analysis materials for "Defininig a Knowledge Graph Development Process through a Systematic Review"
<p>This depository stores the analysis materials for the article "Defining a Knowledge Graph Development Process through a Systematic Review". It includes:</p> <ul> <li><strong>Analysis of KG development process - Articles.csv </strong>- a table of summary of the articles included in the systematic review.</li> <li><strong>Analysis of KG development process - Tasks by level (count).csv</strong> - a table of counting the frequency of the tasks in the knowledge graph development process.</li> <li><strong>Analysis of KG development process - Tasks by level count (synonyms) (1).csv </strong>- a table of counting the frequency of the tasks in the knowledge graph development process after its been adjusted to synonyms.</li> <li><strong>Knowledge graph development processes - </strong>a folder of process figures from the articles that have been included in the systematic review.</li> </ul>
88.6 Million Developer Comments from GitHub
<p><em><strong>Description</strong></em></p> <p>This is a collection of developer comments from GitHub issues, commits, and pull requests. We collected 88,640,237 developer comments from 17,378 repositories. In total, this dataset includes:</p> <ul> <li>54,252,380 issue comments (from 13,458,208 issues)</li> <li>979,642 commit comments (from 49,710,108 commits)</li> <li>33,408,215 pull request comments (from 12,680,373 pull requests)</li> </ul> <p><strong>Warning:</strong> The uploaded dataset is compressed from <strong>185GB</strong> down to 25.1GB.</p> <p> </p> <p><em><strong>Purpose</strong></em></p> <p>The purpose of this dataset (corpus) is to provide a large dataset of software developer comments (natural language) for research. We intend to use this data in our own research, but we hope it will be helpful for other researchers.</p> <p> </p> <p><em><strong>Collection Process</strong></em></p> <p>Full implementation details can be found in the following publication:</p> <ul> <li>Benjamin S. Meyers. <a href="https://scholarworks.rit.edu/theses/11609/">Human Error Assessment in Software Engineering.</a> Rochester Institute of Technology. 2023.</li> </ul> <p>Data was downloaded using <a href="https://docs.github.com/en/graphql">GitHub's GraphQL API</a> via requests made with Python's <a href="https://docs.python-requests.org/en/master/">requests</a> library. We targeted 17,491 repositories with the following criteria:</p> <ul> <li>At least 850 stars.</li> <li>Primary language in the Top 50 from the <a href="https://www.tiobe.com/tiobe-index/">TIOBE Index</a> and/or listed as "popular" in GitHub's advanced search. Note that we collected the list of languages on August 31, 2021.</li> </ul> <p>Due to design decisions made by GitHub, we could only get a list of at most 1,000 repositories for each target language. Comments from 113 repositories could not be downloaded for various reasons (failing API queries, <a href="https://docs.python.org/3/library/json.html#json.JSONDecodeError">JSONDecoderErrors</a>, etc.). Eight target languages had no repositories matching the above criteria.</p> <p>After collection using the GraphQL API, data was written to CSV using Python's <a href="https://docs.python.org/3/library/csv.html?highlight=csv%20writer#csv.writer">csv.writer</a> class. We <strong>highly recommend</strong> using Python's <a href="https://docs.python.org/3/library/csv.html?highlight=csv%20writer#csv.reader">csv.reader</a> to parse these CSV files as <strong>no newlines</strong><strong> have been removed</strong> from developer comments.</p> <p> </p> <p><em><strong>88_million_developer_comments.zip</strong></em></p> <p>This zip file contains 135 CSV files; 3 per language. CSV names are formatted <em><code>_<language>.csv</em>, with <em><language></em> being the name of the primary language and <em><code></em> being one of <em>co</em> (commits), <em>is</em> (issues), or <em>pr</em> (pull requests).</p> <p>Languages included are: ABAP, Assembly, C, C# (C-Sharp), C++ (C-PlusPlus), Clojure, COBOL, CoffeeScript, CSS, Dart, D, DM, Elixir, Fortran, F# (F-Sharp), Go, Groovy, HTML, Java, JavaScript, Julia, Kotlin, Lisp, Lua, MATLAB, Nim, Objective-C, Pascal, Perl, PHP, PowerShell, Prolog, Python, R, Ruby, Rust, Scala, Scheme, Scratch, Shell, Swift, TSQL, TypeScript, VBScript, and VHDL.</p> <p>Details on the columns in each CSV file are described in the provided <em>README.md</em>.</p> <p> </p> <p><em><strong>Detailed_Breakdown.ods</strong></em></p> <p>This spreadsheet contains specific details on how many repositories, commits, issues, pull requests, and comments are included in <em>88_million_developer_comments.zip</em>.</p> <p> </p> <p><em><strong>Note On Completeness</strong></em></p> <p>We make no guarantee that <em><strong>every</strong></em> commit, issue, and/or pull request for each repository is included in this dataset. Due to the nature of the GraphQL API and data decoding difficulties, sometimes a query failed and that data is not included here.</p> <p> </p> <p><em><strong>Versioning</strong></em></p> <ul> <li><strong>v1.1:</strong> The original corpus had duplicate header rows in the CSV files. This has been fixed.</li> <li><strong>v1.0:</strong> Original corpus.</li> </ul> <p> </p> <p><em><strong>Contact</strong></em></p> <p>Please contact Benjamin S. Meyers (<a href="mailto:bsm9339@rit.edu">email</a>) with questions about this data and its collection.</p> <p> </p> <p><em><strong>Acknowledgments</strong></em></p> <ul> <li>Collection of this data has been sponsored in part by the National Science Foundation grant 1922169, and by a Department of Defense DARPA SBIR program (grant 140D63-19-C-0018).</li> <li>This data was collected using the compute resources from the <a href="https://www.rit.edu/researchcomputing/">Research Computing</a> department at the Rochester Institute of Technology. <a href="https://doi.org/10.34788/0S3G-QD15">doi:10.34788/0S3G-QD15</a></li> </ul>
Dataset for Temperature Development in Ultra-High-Performance Concrete-Filled Double-Skin Tubes Exposed to Fire
<p>This dataset presents extensive experimental data available in the literature for concrete-filled tubes (CFT) and ductile concrete-filled double-skin tubes (CFDST) exposed to fire. Different concrete grades, including normal strength (NS), high strength (HS), and ultra-high-strength (UHS) concrete, were tested, and the temperature developments within various cross-sections are provided in the supplementary data. The density, specific heat, and conductivity that are temperature-dependent, are documented by different researchers and current specifications. The preferred models are provided for carbon-steel, stainless-steel, and different grades of concrete. Numerical studies such as those conducted by the authors in a companion paper would find value in this data for validation and verification purposes</p>
Toward consumer-centric sustainability development model: A reverse logistics multi-criteria decision-making analysis datasets
<p>Toward consumer-centric sustainability development model: A reverse logistics multi-criteria decision-making analysis datasets</p>
Fig. 10 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 10. Trends in the relative abundance of trophic guilds in Lake Fenéki (Piscivores: y = 0.06 + 0.003x; R2 = 0.757; P> 0.00001)
Fig. 9 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 9. Proportion of each species in the cumulative abundance of non-native fish species in Lake Fenéki
Fig. 7 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 7. PCA biplot of the arcsin-square root transformed relative abundance data of the whole sampling period (1992–2011) (Variables: Sampling years; Objects: Relative abundances) (abbreviations were constructed from the Latin names of the species, using the first 3 characters of genus and species
Fig. 5 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 5. Estimated number of species (SD's ignored in order to improve visibility) as a function of number of individuals collected in each sampling year
Fig. 8 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 8. PCA biplot of the arcsin-square root transformed relative abundance data of the period 1994–2011 (Variables: Sampling years; Objects: Relative abundances)
Fig. 4 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 4. Relationships between the age of Lake Fenéki and the Shannon–Weaver index (y = 0.414ln(x) + 0.852; R2 = 0.772; P <0.0001)
Fig. 3 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 3. Relationships between the age of Lake Fenéki and the number of fish species (y = 4.141ln(x) + 3.807; R2 = 0.759; P <0.0001)
Fig. 1 in Long-Term Development Of Fish Assemblage In Lake Fenéki (Kis-Balaton Water Protection System, Hungary): Succession, Invasion And Stabilization
Fig. 1. Overlooking map of the Balaton-catchment, with the sampling site (Dark rectangle marked by the arrow indicates the flooded area of Lake Fenéki)
Transcription factors in moss development and defenses against abiotic and biotic stress_dataset
<p>Lists of <em>P. patens</em> genes encoding transcription factors belonging to AP2/ERF, bHLH, GRAS, MYB, NAC and WRKY families differentially expressed in transcriptomes related to response to biotic interactions, abiotic stress, and hormones.</p>
Survey on Developer and Researcher Views on the Ethics of Experiments on Open-Source Projects
<p>Results of a survey of 180 GitHub developers and 44 authors of research papers concerning the ethics of performing experiments on open source projects.</p>
Utetheisa ornatrix development and defence on four Crotalaria host plants
<p>This dataset consists of data from three experiments testing how four different Crotalaria host plants affect Utetheisa ornatrix development and defence against a spider.</p> <p>The data are to be published in a paper accepted in Entomologia Experimentalis et Applicata</p>
Novel disease state model finds most juvenile green turtles develop and recover from fibropapillomatosis
<p>Fibropapillomatosis (FP) is a sea turtle disease characterized by benign tumor development on skin, eyes, and/or internal organs. It primarily affects juvenile green turtles (Chelonia mydas) in coastal foraging sites. The Indian River Lagoon (IRL), Florida, USA, is a coastal green turtle foraging site where the observed FP annual rate averaged 49% between 1983 and 2018. FP is not a major cause of sea turtle mortality and most individuals fully recover; however, the overall dynamics of this disease are poorly understood because prior disease history is unknown for individuals without FP at capture time, and future disease outcome is unknown for individuals with FP at capture time. To better evaluate FP dynamics for green turtles in the IRL, we developed a hierarchical model for predicting disease state change. We used data from 4,149 captures of 3,700 individual green turtles captured in the IRL. The hierarchical disease state model contained two levels: level one modeled whether an individual would develop FP, and level two modeled disease state progression, including states for pre-FP affliction, active FP affliction, and full recovery from FP. From the hierarchical model, we estimated 99.8% (95% credibility intervals 99.1-100%) of juvenile green turtles in the IRL developed FP, indicating that nearly every individual in the IRL is affected by this disease. The model also suggested that turtles quickly developed FP upon recruitment to the IRL and then recovered at different rates, with most completely recovering before emigrating from the IRL as they mature. This is the first analysis of long-term sea turtle data suggesting nearly every turtle in an aggregation both develops and recovers from FP.</p>
Data Archive: 2021 Development of a Virtual Diagnostic for the Advanced Particle Accelerator Modeling Code WarpX
<p><strong>A current promising field of research, laser-driven ion acceleration has the potential to reduce the size, cost, and energy consumption of particle accelerators by orders of magnitude.</strong></p> <p> </p> <p><strong>To better refine the instrumentation, we have developed a virtual diagnostic to measure electromagnetic radiation such as radiation produced from scattered and transmitted laser beams which has been implemented into WarpX, an advanced Particle-in-Cell code that simulates laser-driven particle acceleration. This “FieldProbe” diagnostic provides field measurements and is parallelized using the Message Passing Interface (MPI) and can thus run on High Performance Computing systems such as the NERSC Cori cluster.</strong></p>
Replication Package for "Evaluating SZZ Implementations Through a Developer-informed Oracle"
<p>This is the replication package for the paper "Evaluating SZZ Implementations Through a Developer-informed Oracle" published in the 43rd International Conference on Software Engineering (ICSE 2021). <a href="https://arxiv.org/abs/2102.03300">https://arxiv.org/abs/2102.03300</a></p>
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.