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42 results for “Migration dataset”
Dataset for the research paper "How and Why Developers Migrate Python Tests from unittest to pytest"
<p>This is the dataset for the proposed paper "How and Why Developers Migrate Python Tests from unittest to pytest". <br> <br> <br> The `10_systems` zip file contains the aggregated and intermediate files for the systems used for precision and recall analysis.</p> <p>The `top_100_systems` zip file contains the aggregated and intermediate files for the top 100 python systems analyzes.</p> <p>The `__rq_reason` contains data to assess the advantages and disadvantages found in 100 issues or pull requests. The second column indicates whether issues/PRs were selected to be analyzed and the following columns indicate if the advantages (A) or disadvantages (D) are present or not.</p>
Dataset for the paper: Computational framework for radionuclide migration assessment in clay rocks
<p>This dataset contains OpenGeoSys-6 simulations results and scripts in Jupyter-notebook format for reproducing and visualizing the results of the paper:</p> <p>Garibay-Rodriguez J, Chen C, Shao H, Bilke L, Kolditz O, Montoya V and Lu R (2022) Computational Framework for Radionuclide Migration Assessment in Clay Rocks. Front. Nucl. Eng. 1:919541. doi: 10.3389/fnuen.2022.919541</p> <p>Details about the usage of the scripts can be found in the OpenGeoSys-6 user guide: https://www.opengeosys.org/</p>
Dataset for the article "Why Python Developers Migrate to Pytest"
<p>Dataset for the proposed article "Why Python Developers Migrate to Pytest"</p> <p>Each file shows a tabular representation, mapping which resource presents advantages and disadvantages (why_developers_migrate_themes.csv), what type of code examples they have (why_developers_migrate_code_examples.csv), and what tips we can find (why_developers_migrate_tips.csv). </p>
EUMEPLAT dataset - Migration
<p>Discussion about migration and social media</p>
Dataset part two to the publication "CAL-1 as Cellular Model System to Study CCR7-Guided Human Dendritic Cell Migration"
<p>Additional dataset to dataset part one (doi: 10.5281/zenodo.4719596) to the publication "CAL-1 as Cellular Model System to Study CCR7-Guided Human Dendritic Cell Migration"</p>
Data from: Forecasting nocturnal bird migration for dynamic aeroconservation: the value of short-term dataset
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Data from:Using a large citizen science dataset to uncover diverse patterns of elevational migration in Himalayan birds
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Dataset: A synthesis of the diversity of freshwater fish migrations in the Amazon basin
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Reservoir operating rules to create effective fish migration passages in a reservoir [Dataset]
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ARFM(Adaptive receiver function seismic migration): codes and dataset for application in SE Tibetan plateau
<p>We develop a post-stack adaptive receiver function (RF) seismic migration method to image subsurface disconitnuities. Contents of numerical experiments are in the compressed file 'program_synthetic_experiments.tar'. RF dataset and codes for the application of the adaptive receiver function migration method in southeastern Tibetan plateau are in other compressed files.</p>
Dataset for Supplementary Figures of "The macroeconomic effects of adapting to high-end sea-level rise via protection and migration"
<p>This dataset served as input data for the analysis as presented in the article "The macroeconomic effects of adapting to high-end sea-level rise via protection and migration" and allows to reproduce Supplementary Figures 3-26.</p>
From soil to sediment: Bedform migration shapes microbial communities from eroding bank soil during terrestrial-aquatic regime shift [dataset]
<p>This dataset contains raw data of metabolism measurements, microbial abundance, and nutrients that were assessed for the research paper entitled "From soil to sediment: Bedform migration shapes microbial communities from eroding bank soil during terrestrial-aquatic regime shift," which has been submitted to the Journal of Geophysics: Biogeosciences on October 19, 2024. Please note that raw sequencing data were already submitted to the NCBI library and are accessible via https://www.ncbi.nlm.nih.gov./sra/PRJNA1154565.</p> <p>The excel sheet (.xlsx) contains all relevant parameters that were used to detect the influence of environmental parameters on the microbial community structure, e.g. bacterial, fungal and algal abundance, nutrient concentrations, and final NCP and CR rates. The .zip archive contains all raw metabolism measurements during our experimental duration.</p>
Dataset for "Lateral Charge Migration in 1D Semiconductor-Metal Hybrid Photocatalytic Systems"
<p>This is the dataset including absorption, photoluminescence quantum yield, and transient absorption spectroscopy.</p>
Dataset, posterior summaries and posterior samples for quantifying fluctuating selection on seasonal migration versus residence in European shags
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Quantifying monolayer cell migration sample dataset
<p>The sample data to use with the Quantifying monolayer cell migration chapter of the 'Bioimage Data Analysis Workflows - Advanced Components and Methods' Neubias textbook.</p>
Dataset for SLR paper - Identification and Evaluation of Pitfalls in the Migration from IEC 61131-3 to IEC 61499: A Review
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Dataset used for: Breeding migrations by bighorn sheep males: searching for mates increases vulnerability to hunting
<p>In some species where male mating success largely depends on intrasexual competition, males can adopt migratory orresident strategies to seek breeding opportunities. The resulting mixture of resident and migrant tactics within a population can have important ecological, genetic and evolutionary consequences at the metapopulation level. Bighorn sheep <em>Ovis canadensis</em> males establish a linear dominance hierarchy that influences their mating tactics. Some males perform breeding migrations during the pre-rut and rut to seek mating opportunities, but little is known about these seasonal movements. We analysed presence/absence data for 62 marked bighorn males during six mating seasons (20-32 males/year) in the Sheep River Provincial Park, Alberta, Canada, where hunting was not allowed. On average, about half of males left their natal population to rut elsewhere. The proportion of males leaving (yearly range 15% - 69%) increased as the number of resident mature males increased and the populational sex ratio decreased, with fewer females during the pre-rut. Among those leaving the park, 24% did so in October, while the trophy sheep hunting season was open. Detailed monitoring of breeding migrations in protected populations could inform management strategies to limit evolutionary impacts of hunting.</p>
Dataset used for: Breeding migrations by bighorn sheep males: searching for mates increases vulnerability to hunting
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Dataset from: High consistency and repeatability in the breeding migrations of a benthic shark
<p>Dataset and scripts used for manuscript: High consistency and repeatability in the breeding migrations of a benthic shark. </p> <p>Project title: High consistency and repeatability in the breeding migrations of a benthic shark<br>Date:23/04/2024</p> <p>Folders:<br>- 1_Raw_data<br> - Perpendicular_Point_068151, Sanctuary_Point_068088, SST raw data, sst_nc_files, IMOS_animal_measurements, IMOS_detections, PS&Syd&JB tags, rainfall_raw, sample_size, Point_Perpendicular_2013_2019, Sanctuary_Point_2013_2019, EAC_transport<br>- 2_Processed_data<br> - SST (anomaly, historic_sst, mean_sst_31_years, week_1992_sst:week_2022_sst including week_2019_complete_sst)<br> - Rain (weekly_rain, weekly_rainfall_completed)<br> - Clean (clean, cleaned_data, cleaned_gam, cleaned_pj_data)<br>- 3_Script_processing_data<br> - Plots(dual_axis_plot (Fig. 1 & Fig. 4).R, period_plot (Fig. 2).R, sd_plot (Fig. 5).R, sex_plot (Fig. 3).R<br> - cleaned_data.R, cleaned_data_gam.R, weekly_rainfall_completed.R, descriptive_stats.R, sst.R, sst_2019b.R, sst_anomaly.R<br>- 4_Script_analyses<br> - gam.R, gam_eac.R, glm.R, lme.R, Repeatability.R<br>- 5_Output_doc<br> - Plots (arrival_dual_plot_with_anomaly (Fig. 1).png, period_plot (Fig.2).png, sex_arrival_departure (Fig. 3).png, departure_dual_plot_with_anomaly (Fig. 4).png, standard deviation plot (Fig. 5).png)<br> - Tables (gam_arrival_eac_selection_table.csv (Table S2), gam_departure_eac_selection_table (Table S5), gam_arrival_selection_table (Table. S3), gam_departure_selection_table (Table. S6), glm_arrival_selection_table, glm_departure_selection_table, lme_arrival_anova_table, lme_arrival_selection_table (Table S4), lme_departure_anova_table, lme_departure_selection_table (Table. S8))</p> <p> <br>Descriptions of scripts and files used:<br>- cleaned_data.R: script to extract detections of sharks at Jervis Bay. Calculate arrival and departure dates over the seven breeding seasons. Add sex and length for each individual. Extract moon phase (numerical value) and period of the day from arrival and departure times.<br> - IMOS_detections.csv: raw data file with detections of Port Jackson sharks over different sites in Australia.<br> - IMOS_animal_measurements.csv: raw data file with morphological data of Port Jackson sharks<br> - PS&Syd&JB tags: file with measurements and sex identification of sharks (different from IMOS, it was used to complete missing sex and length).<br> - cleaned_data.csv: file with arrival and departure dates of the final sample size of sharks (N=49) with missing sex and length for some individuals.<br> - clean.csv: completed file using PS&Syd&JB tags, note: tag ID 117393679 was wrongly identified as a male in IMOS and correctly identified as a female in PS&Syd&JB tags <br> file as indicated by its large size.<br> - cleaned_pj_data: Final data file with arrival and departure dates, sex, length, moon phase (numerical) and period of the day.</p> <p>- weekly_rainfall_completed.R: script to calculate average weekly rainfall and correlation between the two weather stations used (Point perpendicular and Sanctuary point).<br> - weekly_rain.csv: file with the corresponding week number (1-28) for each date (01-06-2013 to 13-12-2019)<br> - weekly_rainfall_completed.csv: file with week number (1-28), year (2013-2019) and weekly rainfall average completed with Sanctuary Point for week 2 of 2017<br> - Point_Perpendicular_2013_2019: Rainfall (mm) from 01-01-2013 to 31-12-2020 at the Point Perpendicular weather station<br> - Sanctuary_Point_2013_2019: Rainfall (mm) from 01-01-2013 to 31-12-2020 at the Sanctuary Point weather station<br> - IDCJAC0009_068088_2017_Data.csv: Rainfall (mm) from 01-01-2017 to 31-12-2017 at the Sanctuary Point weather station (to fill in missing value for average rainfall of week 2 of 2017)</p> <p>- cleaned_data_gam.R: script to calculate weekly counts of sharks to run gam models and add weekly averages of rainfall and sst anomaly<br> - cleaned_pj_data.csv<br> - anomaly.csv: weekly (1-28) average sst anomalies for Jervis Bay (2013-2019)<br> - weekly_rainfall_completed.csv: weekly (1-28) average rainfall for Jervis Bay (2013-2019_<br> - sample_size.csv: file with the number of sharks tagged (13-49) for each year (2013-2019)</p> <p>- sst.R: script to extract daily and weekly sst from IMOS nc files from 01-05 until 31-12 for the following years: 1992:2022 for Jervis Bay<br> - sst_raw_data: folder with all the raw weekly (1:28) csv files for each year (1992:2022) to fill in with sst data using the sst script<br> - sst_nc_files: folder with all the nc files downloaded from IMOS from the last 31 years (1992-2022) at the sensor (IMOS - SRS - SST - L3S-Single Sensor - 1 day - night time – Australia).<br> - SST: folder with the average weekly (1-28) sst data extracted from the nc files using the sst script for each of the 31 years (to calculate temperature anomaly).</p> <p>- sst_2019b.R: script to extract daily and weekly sst from IMOS nc file for 2019 (missing value for week 19) for Jervis Bay<br> - week_2019_sst: weekly average sst 2019 with a missing value for week 19<br> - week_2019b_sst: sst data from 2019 with another sensor (IMOS – SRS – MODIS - 01 day - Ocean Colour-SST) to fill in the gap of week 19<br> - week_2019_complete_sst: completed average weekly sst data from the year 2019 for weeks 1-28.</p> <p>- sst_anomaly.R: script to calculate mean weekly sst anomaly for the study period (2013-2019) using mean historic weekly sst (1992-2022) <br> - historic_sst.csv: mean weekly (1-28) and yearly (1992-2022) sst for Jervis Bay<br> - mean_sst_31_years.csv: mean weekly (1-28) sst across all years (1992-2022) for Jervis Bay<br> - anomaly.csv: mean weekly and yearly sst anomalies for the study period (2013-2019)</p> <p>- Descriptive_stats.R: script to calculate minimum and maximum length of sharks, mean Julian arrival and departure dates per individual per year, mean Julian arrival and departure dates per year for all sharks (Table. S10), summary of standard deviation of julian arrival dates (Table. S9)<br> - cleaned_pj_data.csv</p> <p>- gam.R: script used to run the Generalized additive model for rainfall and sea surface temperature<br> - cleaned_gam.csv</p> <p>- gam_eac.R: script to run the Generalized additive model for EAC strength, rainfall and sea surface temperature.<br> - EAC_transport.csv: raw data of EAC transport (Sv) with date, time, week, year<br> - cleaned_gam.csv</p> <p>- glm.R: script used to run the Generalized linear mixed models for the period of the day and moon phase<br> - cleaned_pj_data.csv<br> - sample_size.csv</p> <p>- lme.R: script used to run the Linear mixed model for sex and size<br> - cleaned_pj_data.csv</p> <p>- Repeatability.R: script used to run the Repeatability for Julian arrival and Julian departure dates <br> - cleaned_pj_data.csv</p>
Demo dataset for publication "Development of image analysis tool to evaluate Langerhans cell migration after exposure to isothiazolinones"
<p>This dataset consists of a QuPath project and two images that can be used to test the scripts produced by the publication </p> <p>"Development of image analysis tool to evaluate Langerhans cell migration after exposure to isothiazolinones"</p>
ScienceDex guides
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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.