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AraSTEM is a dataset designed to evaluate the knowledge of large language models (LLMs) in STEM (Science, Technology, Engineering, and Mathematics) subjects in Arabic. It consists of multiple-choice questions covering various topics and difficulty levels, requiring models to demonstrate a deep understanding of scientific Arabic. The dataset includes the question, options, correct answer, subject, level, and a link to the resource.

Data and codes used in the paper "Drivers of the Global Financial Cycle"

Datasets used for developing the analysis presented in the paper: GEOCHEMICAL TYPOLOGY VALIDATION OF PARANÁ IGNEOUS PROVINCE IN THE STATE OF PARANÁ USING STATISTICAL MULTIVARIATE ANALYSIS

Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)

Hydrochemistry of porewater and dispersed ice from mineral soils, western Siberia, continous permafrost zone

A database of raw data containing the results of human semen quality analysis

The project aimed to investigate the growth variation, essential oil yield and composition of rosemary irrigated with aquaculture and Biofloc wastewater in comparison to fertigation under greenhouse conditions at two cuts. Data on plant growth parameters such as heights, number of side branches, fresh and dry yield was collected. Likewise, data on the nutrient composition of shoots, total phenolics, essential oil yield and composition was collected. T1, T2, and T3 represent irrigation treatments of fertigation, Biofloc wastewater, and aquaculture wastewater respectively

Supplementary data for the benefit of reviewers.

This dataset is linked to the study "Feeling touch through a mirror: the role of vision and body ownership in generating non-veridical tactile experiences." It includes behavioral and electrodermal activity (EDA) data from an experiment using the Tactile Quadrant Stimulation (TQS) protocol combined with a mirror box illusion paradigm. This study explores synchiric errors and mislocalization errors under three experimental conditions: Baseline, Mirror Condition Vision, and Mirror Condition Blind. The dataset is divided into three files: VTQS_COMPLETE_DATA: Full dataset with all collected data, including unprocessed variables and outliers. VTQS_MAIN_ANALYSIS_DATA: Preprocessed dataset excluding outliers, focusing on variables relevant to the main findings, such as error types and their distribution across conditions. VTQS_SUPPLEMENTARY_DATA: Preprocessed dataset excluding outliers, containing variables detailed in the supplementary materials. These files enable replication of the analyses in the main paper and supplementary materials and provide additional opportunities for secondary analyses.

This dataset shows hydrographic variables, phytoplankton abundance (potentially toxic taxa), and levels of marine biotoxins in bivalves from an offshore shellfish production area on the Basque coast (southeastern Bay of Biscay). Two zones were monitored: one at an aquaculture experimental site (from December 2013 to December 2023), and another at a mussel farm (from June 2019 to December 2023). Not all variables were measured throughout the entire monitoring period. Sampling frequency also varied, although generally, monthly or fortnightly surveys were conducted (except from September 2015 to March 2016). Hydrographic variables (temperature, salinity, density (sigma theta), light transmission, photosynthetically active radiation, chlorophyll "a", dissolved oxygen concentration, and oxygen saturation) were measured in situ at different depths using continuous vertical profilers, Sea-Bird SBE 25 and 25plus CTD instruments. Due to the multi-year duration of the monitoring, phytoplankton and biotoxin analyses were conducted by different laboratories. The Utermöhl method was employed for the identification and counting of phytoplankton, from May 2014 to May 2017 by the University of the Basque Country, and onwards by Oceansnell. Mussels and oysters were analysed to determine the concentration of toxins related to the Amnesic Shellfish Poisoning (ASP) and the Paralytic Shellfish Poisoning (PSP), together with several lipophilic phytotoxins (i.e., Okadaic Acid (OA), Dinophysistoxins (DTXs), Pectenotoxins (PTXs), Yessotoxins (YTXs) and Azaspiracids (AZAs)). These biotoxins were analysed by the laboratories of Intecmar (from December 2013 to December 2019) and Cecopesca-Anfaco (from January 2020 to June 2023) following the standardized methodology specified in the corresponding EU Regulations. This work was supported by the Fisheries and Aquaculture Directorate, Department of Economic Development, Sustainability and Environment of the Basque Government through the ACULAB Project.