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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
15,241 datasets
605 employees across five automated manufacturing plants participated in a two-wave panel study on technostress and worker well-being. The dataset contains BIC values from Latent Profile Analysis used to model the relationships between technostress, job resources, psychosocial safety climate, and outcomes like mental health and safety. Researcher Umet Elbir published the data on figshare in April 2026 under a CC-BY-4.0 license.
Crew-level means for Psychosocial Safety Climate (PSC) derived from a two-wave panel study of 605 employees at baseline and 450 at follow-up across five automated manufacturing plants. The dataset, created by Umut Elbir and last updated in April 2026, supports analysis of organizational factors influencing worker well-being. It was collected to investigate the role of PSC and job resources in mitigating technostress effects on mental health, burnout, engagement, and safety.
450 employee responses from a two-wave panel study across five automated manufacturing plants, collected at a four-week follow-up. The dataset was created by Umut Elbir and investigates the influence of technostress on mental health, burnout, engagement, and safety, examining job resources and psychosocial safety climate as protective factors. It was last updated on 2026-04 03.
A two-wave panel dataset from a study of 605 employees across five automated manufacturing plants. The data investigates relationships between technostress, mental health, burnout, engagement, and safety outcomes, with job resources and psychosocial safety climate as moderators. The dataset was created by Umut Elbir and last updated on April 3, 2026.
A two-wave panel dataset from a study of 605 employees at baseline and 450 at a four-week follow-up across five automated manufacturing plants. The data examines relationships between technostress, mental health, burnout, engagement, safety outcomes, and protective factors like job resources and psychosocial safety climate. Umut Elbir published the dataset on figshare in 2026 under a CC-BY-4.0 license.
A two-wave panel study of 605 employees across five automated manufacturing plants investigates the impact of technostress on mental health, burnout, engagement, and safety. The dataset, created by Umut Elbir and published on figshare in April 2026, likely contains survey responses measuring job resources, psychosocial safety climate, and worker outcomes. It employs a multilevel framework to analyze how contextual factors buffer the effects of technological stressors.
605 employee responses at baseline and 450 at a four-week follow-up provide panel data on technostress, mental health, burnout, engagement, and safety outcomes. The dataset, authored by Umut Elbir and last updated in April 2026, likely contains survey results from five automated manufacturing plants. It was collected using a two-wave panel design to investigate the role of job resources and psychosocial safety climate.
Umut Elbir's dataset, published on figshare in April 2026, contains survey measures from a two-wave panel study on technostress in manufacturing. The data was collected from 605 employees at baseline and 450 at a four-week follow-up across five automated manufacturing plants. It examines relationships between technostress, mental health, burnout, engagement, safety outcomes, and protective factors like job resources and psychosocial safety climate.
A multimodal human activity dataset organized per-episode and per-modality. It contains face-blurred RGB video, raw stereo pair images, full-hand tactile sensing, and distributed body IMU data captured during everyday household tasks. The dataset was created by humanarchive and released on Hugging Face, with a last update recorded on 2026-05-21.
Monthly mean simulation results from 2015 to 2017 for Canada's Atlantic, Pacific, and Arctic Oceans. The dataset is derived from a moderate to high-resolution (ā0.25Ā°, 75 levels) numerical model that assesses biogeochemical parameters. It was validated against satellite ocean color, surface pCO2, and depth profiles of oxygen and nitrate.
Myanmar Synthetic Syllable Glyphs (MSSG) is a massive-scale, high-fidelity synthetic image dataset containing 14,295,552 heavily augmented glyph images. The images are 128x64 pixels in grayscale and represent the structural combinatorial matrix of the Burmese script. It was developed by Khant Sint Heinn and is published and maintained by DatarrX.
Australia's continental margin is covered by a set of digital grids for bathymetry, gravity, and magnetic data at 250-1000 meter resolution. This dataset represents a major upgrade of marine ship-track data, integrated with satellite and onshore sources and corrected using levelling techniques. It is intended as a fundamental product for geological interpretation of Australian waters.
Soil sampling data from a large-scale survey across a 3,000-kilometer aridity gradient on the Tibetan Plateau. The dataset, created by Junxiao Pan and last updated in April 2026, examines factors like microbial carbon use efficiency and physicochemical protection in relation to soil organic carbon dynamics. It is a 20.0 KB CSV file shared under a CC-BY-4.0 license.
A dataset from a research paper describes the development of a base editing system for the bacterium Shewanella oneidensis MR-1. The work, authored by Lei Cheng from the University of Science and Technology of China, engineered strains with expanded carbon source utilization, which exhibited higher degradation rates for azo dyes and organoarsenic compounds compared to the wild type. The base editing system achieved an 87.5% efficiency for double-locus simultaneous editing.
Microbial community data from an experiment simulating a nitrate surge in sulfide-rich river sediments. The dataset likely contains compositional and functional profiles tracking the shift from methanogen-dominated communities to those enriched with chemolithotrophic denitrifiers like Thiobacillus and Luteimonas. It was produced by Enze Li of the Institute of Microbiology and shared via paperswithcode.
An experimental manipulation sequentially removed four generalist plants from real plant-pollinator networks. The study recorded effects on species and interaction extinctions, network structure, and interaction rewiring. Data was collected by Paolo Biella from the University of Milano-Bicocca.
Controlled aquarium experiments using Gammarus pulex L. (Amphipoda) investigate the relationship between detectable environmental DNA (eDNA), time, pH, and organic material levels. The study by Kees van Bochove of Wageningen University & Research found eDNA degrades faster with added organic material, while pH had no significant effect. Results suggest eDNA concentration could be corrected for local environmental conditions to improve population density estimates.
Organic geochemical studies of reduced organic material in sedimentary rocks provide insight into sediment origin and history. The data likely contains information on organic matter source, depositional environment, biodegradation, and maturity derived from biological marker distributions. It is published by Geoscience Australia Data and was last updated on 2026-04-20.
32.50 g/L of succinic acid was produced from 80 g/L xylan using a co-cultivation system. The dataset, from a study by Jiasheng Lu of Nanjing Tech University, documents the bioconversion process of lignocellulosic biomass into bio-chemicals. It includes results from process optimization and demonstrates production from corn cob.
This layer shows the location of drainage headwalls, which are retaining walls at stormwater pipe inlets or outlets, within the Metropolitan Region of Western Australia. The dataset includes attributes such as Headwall_No, Asset_Owner, Road_No, Data_Status, Mapping_Comments, and Confidence_Rating. It is provided by Main Roads Western Australia for reference only.