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This dataset supports the research article Artificial Feeds Induce Hepatic Steatosis and Metabolic Reprogramming in Mandarin Fish (Siniperca chuatsi). It includesraw LC-MS untargeted metabolomic data from a 150-day feeding trial comparing mandarin fish fed artificial feeds (AF) and natural live feeds (NF), with 8 biological replicates per group.

Dataset to accompany the paper: Diamond-like-Carbon, Microdiamonds, Titanium Spherules and New UHT Minerals in Impact Debris from the SW Egypt Regolith: Possible Relations to the Extraterrestrial Carbonaceous Pebble “Hypatia” and the Libyan Desert Glass By: Marco A.G. Andreoli1, Rudolph Erasmus2, Jasper Knight3, Vittoria Pischedda4, George Belyanin5, Chiara Elmi6, Hassina Mouri5, Simo Huotari7, Aki Kallonen7, Mpho Lekgoathi8, Romano Serra9, Roger Gibson1, John M. Saul10, and Mario Di Martino11 1School of Geosciences, University of the Witwatersrand, Johannesburg 2050, South Africa; 2School of Physics, University of the Witwatersrand, Johannesburg 2050, South Africa; 3School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg 2050, South Africa; 4Institut Lumière Matière, Université Claude Bernard Lyon1, UMR5306-CNRS, 69622 Villeurbanne, France; 5Department of Geology, University of Johannesburg, South Africa; 6James Madison University, USA; 7Department of Physics, University of Helsinki, Helsinki, Finland; 8The South African Nuclear Energy Corporation SOC LTD, South Africa; 9Museo del Cielo e della Terra, S. Giovanni in Persiceto, Italy; 10Oryx, Paris, France; 11INAF, Osservatorio Astrofisico di Torino, Pino Torinese, Italy Submitted to: JGR - Planets (May 2026) For queries please contact: Marco Andreoli (marco.andreoli@wits.ac.za) Jasper Knight (jasper.knight@wits.ac.za)

This dataset contains the public, processed data-code package supporting the revised manuscript "Climate and traits are differentially associated with range extent and range geometry in global butterflies" (ECOLIND-57847). The package contains public GBIF download metadata, occurrence-processing summaries, CoordinateCleaner and sampling-support summaries, occurrence-derived alpha-hull range-metric summaries, RLI diagnostics, EIV climate-axis summaries, trait-axis and imputation summaries, final model assembly tables, model-comparison and posterior predictive diagnostics, direct/indirect/total/PM posterior summaries, PM stability flags, CTC/IND covariance-source summaries, climate-zone and balanced-subsampling summaries, sensitivity summaries, nonlinearity/caveat summaries, figure plot-data tables, supplementary-table source files, scripts, manifests, checksums and QC reports. Raw GBIF occurrence archives, selected occurrence CSV.gz batches, cleaned occurrence Parquet/DuckDB datasets, raw posterior-draw arrays and large model objects are not duplicated in this package because of file size. These excluded files are documented in the excluded-files manifest. Raw occurrence records can be retrieved from GBIF using the public occurrence download DOI values and download keys listed in the package metadata and Table S26. The package is intended to support reviewer inspection, data-lineage transparency, and future reproducibility of the processed outputs used in the manuscript.

This dataset contains 761 records of slime moulds, representing 80 identified species, obtained by field collection and moist chamber culture in Jałówka, Krzemianka, and Las Cieliczański forest nature reserves, north-eastern Poland. The study lasted from June 2025 to April 2026. Field surveys were route-based, conducted from June to November 2025. Records were made on dead wood, bark, litter, plant debris, herbaceous remains, bryophytes, logs, branches, twigs, stumps, and other dead organic matter. The file contains the following columns: Taxon - scientific name of the identified slime mould taxon. Nomenclature follows Nomen.eumycetozoa.com: Lado, C. (2005-2026). An on line nomenclatural information system of Eumycetozoa. Real Jardín Botánico, CSIC, Madrid, Spain. https://eumycetozoa.com, accessed 13.05.2026. Acquisition Method - Field collection or Moist chamber culture. Reserve Name - reserve where the record was obtained. Collection Date - date of field collection or, for moist chambers, harvesting of mature sporocarps. Moist Chamber Setup Date - date when the culture was established; empty for field collections. Moist Chamber Code - unique moist chamber culture code. Moist Chamber Harvest Date - date when mature sporocarps were harvested. Substrate Type - substrate or microhabitat, e.g. wood, bark, litter, twigs, bryophytes, or plant debris. Substrate Species - plant or tree species associated with the substrate, when identified. pH - pH value measured for the substrate from moist chamber culture. Elevation (m a.s.l.) - locality elevation in metres above sea level. Latitude - geographic latitude in decimal degrees. Longitude - geographic longitude in decimal degrees. Coordinate Precision (m) - estimated coordinate precision in metres. Collector(s) - person or persons who collected the specimen or substrate material. Determiner(s) - person or persons who identified the slime mould taxon. Full Forest Address - complete forest-address identifier of the sampling locality. Forest District - forest district of the locality. Forest Site Type - forest site type assigned to the locality. Degradation Degree - habitat transformation category (source: BDL - Bank Danych o Lasach), e.g. Natural (N1), Near-Natural (N2), or Distorted (Z1). Moisture Variant - moisture or hydrological category (source: BDL), e.g. Fresh, Moist, Wet, Flooded, or Not Flooded. Plant Community - plant community recorded for the locality, when available in BDL. Natural Habitat Code - natural habitat code(s) assigned to the locality; multiple codes are separated by semicolons. Source: BDL

The CSV file represents the survey results for the 2x2 experiment aimed at investigating how personalized and warm answers influence the persuasiveness of AI answers and the user's reliance on them. AI agents are manipulated to be either personalized vs. non-personalized, or warm vs. neutral. Personal information of participants is only gathered for the personalized condition, and does not involve any personally identifying fields. The dependent variables are the difference between PreDV_Slider_1 and PostDV_Slider_1, and the difference between PreDV_Binary and PostDV_Binary. The differences represent how much the participant's opinion has shifted before and after the treatment.

This database contains comprehensive experimental records related to tibial morphology and bone development in growing Japanese quail (Coturnix japonica) subjected to different dietary nutritional strategies. The dataset includes detailed morphometric measurements of tibial structures, allowing the evaluation of skeletal growth, bone integrity, and potential nutritional effects on bone development. Variables comprise quantitative measurements such as tibia weight, length, width, diaphysis dimensions, and additional structural parameters associated with bone quality and morphophysiological development. The data were generated under controlled experimental conditions and are intended to support research in animal nutrition, poultry science, mineral supplementation, intestinal health, and skeletal physiology. In particular, the database may contribute to studies evaluating the effects of chelated trace minerals, probiotic supplementation, and functional feed additives on bone morphology and productive performance in avian models. This dataset represents a valuable resource for comparative analyses, meta-analytical approaches, and the development of evidence-based nutritional strategies aimed at improving animal health, welfare, and productive efficiency in poultry systems.

Effects of Conservation Agriculture on Multiple Ecosystem Services of Global Black Soils

Supplementary Material of the article titled genetic potential for nitrogen cycling in the globally distributed psychrophile Psychromonas. The integrated dataset comprises: (i) genomic sequences and their corresponding annotations from the project execution; (ii) structural datasets from protein modeling studies; (iii) results from pan-genome analyses; (iv) phylogenetic tree files; and (v) gene expression data.

This dataset was used for the manuscript entitled “A Machine Learning-Assisted Multi-Criteria Decision Making Framework for Chemical Reactor Channel Geometry Selection”. For questions or additional requests, please contact me by email.