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ZooMS spectra of specimens analysed from Maxta I

This data repository contains the raw simulation results and the GIS maps for visualizing the simulations results for the study on how cell temperature effects photovoltaic power generation at global scale. The data note is expected to be published at F1000 Research. Article info: Wu,C. (2026). Impact of Cell Temperature on Photovoltaic Power Generation at Global Scale. F1000Research. The full paper including the analysis and the conclusion of the study is accepted for publication at the SimBuild 2026 Conference. Article info: Wu, C. (2026). Simulating the Impact of Photovoltaic Cell Temperature on Electricity Production under Various Global Climates. In Proceedings of SimBuild Conference.

"The dataset consists of hourly meteorological parameters (solar radiation, ambient temperature, humidity) and power output recorded from a 20 MW solar plant in [Ghardaia, Algeria] over a period of 2 months (January and December 2023). Data were collected using high-precision sensors and SCADA systems."

This repository contains the primary analytical input, replication code, and selected derived outputs supporting the community-level analyses reported in the associated manuscript on insect assemblages associated with declining riparian black alder stands in the valleys of the Utrata and Łutownia rivers, Poland. The deposit is designed as a compact reproducibility package: it includes the cleaned analytical matrix, the metadata required to interpret that matrix, and machine-readable outputs needed to verify the published diversity, beta-diversity, NMDS, and rarefaction/extrapolation results. Files included: Insects_list.xlsx — Primary input file containing the taxon abundance data arranged by river and distance classes used by the replication workflow. Replication_Code.R — R script that reads the input data, performs the community-level analyses, and generates the reproducible outputs deposited in this repository. clean_species_by_stratum.csv — Cleaned taxon-by-stratum abundance matrix used as the principal analytical dataset for the published results. sample_metadata.csv — Metadata table linking each analytical stratum to river identity and distance from the channel margin. taxon_lookup.csv — Lookup table linking analytical taxon identifiers to the reported taxonomic names used in the study. diversity_bootstrap_CI_long.csv — Full bootstrap output for richness, diversity, evenness, and sample-coverage metrics by stratum. beta_pairwise_long.csv — Complete pairwise Sørensen beta-diversity table, including turnover and nestedness components, for all stratum combinations. nmds_site_scores.csv — Coordinates of the six analytical strata in the exploratory NMDS ordination. nmds_species_scores.csv — Taxon scores from the exploratory NMDS ordination for interpretive use outside the main text. rarefied_richness_to_min_N.csv — Rarefied richness estimates standardised to the smallest observed stratum abundance. iNEXT_AsyEst.csv — Asymptotic richness and diversity estimates generated by iNEXT. iNEXT_iNextEst.csv — Interpolation and extrapolation estimates generated by iNEXT across sample-size and coverage gradients. nmds_diagnostics.txt — Diagnostic summary for the NMDS solution, including stress and dimensionality. README_dataset.txt — Plain-text repository guide containing the title, repository description, and reproduction instructions. The repository does not prioritise technical helper files used only for column detection, automatically regenerated distance matrices, or figure files already shown in the manuscript. These products can be recreated directly from Insects_list.xlsx and Replication_Code.R, so the deposited package remains concise while still fully supporting verification, re-use, and re-analysis.

A sample of 379 MSMEs from the municipality of Oaxaca de Juárez, in Mexico, was collected between 2019 and 2020. Only data validated by the PLS-SEM measurement model are shown. The variables include one categorical grouping variable, gender (sexo), with values 1 for male and 2 for female. The constructs validated in the scale are the organizational component (ORG), the individual component (IND), and the environmental component (ENV). The items for the organizational construct include Market Share (org_1), Openness to Change (org_2), Profitability (org_3), Sales (org_4), and Innovation (org_5). The individual construct items are Job Satisfaction (ind_1), Training (ind_2), Employee Motivation (ind_3), Sense of Belonging (ind_4), and Willingness to Change (ind_5). The environmental construct items are Organizational Culture (env_1) and Organizational Climate (env_2). The scale used for all items was a five-point Likert-type scale, ranging from “strongly disagree” to “strongly agree”.

Tethysuchian evolutionary relationships have been intensively investigated, in particular those of Dyrosauridae. In order to provide the most up to date phylogenetic hypothesis, we performed a phylogenetic analysis including Brachiosuchus kababishensis and Wadisuchus kassabi, with goniopholidids and tethysuchians (= pholidosaurids and dyrosaurids). The dataset we propose here is based on several previous analyses (e.g. Jouve et al. 2005a, b, 2008; Hastings et al. 2015; Young et al. 2017) and includes 225 characters and 44 taxa. Compared with previous iterations of this character list (Jouve 2020; Jouve and Jalil 2020; Jouve et al. 2021), several definitions have been clarified, and the final character in the matrix is new. Two new taxa have been added, Brachiosuchus kababishensis and Wadisuchus kassabi, and numerous characters and other taxa have been rescored.

This dataset was gathered in the context of Optical Mark Recognition (OMR), where the objective is to automatically detect the selected answers in a multiple-choice exam. OMR is the first step in developing automatic grading for Multiple Choice Question (MCQ) exams. This dataset contains 5721 scanned images of four-choice exam answer sheets completed by high school students. Each image is accompanied by a text file containing the human-observed labels for each item. The exams were administered in 2024 to 10th-, 11th-, and 12th-grade students at 42 high schools in Tamaulipas, Mexico. To protect the student's privacy, we developed an anonymization process based on geometric image processing. Of the answer sheets, 3669 from 10th and 12th grades contain 90 items, while 2052 from 11th grade contain 100 items, totaling 535,020 items. The variety of styles used to mark the items, as well as noise and artifacts due to human and digitization errors, makes this dataset valuable in the design of automatic OMR algorithms for real-life applications in automatic MCQ exam grading, based on machine learning or classical image processing.

Description Bile Acid measurements (µM) in healthy volunteers, idiosyncratic drug-induced liver injury (DILI) and nonDILI cases for TransBioLine project. Background: The liver maintains bile acid (BA) homeostasis; circulating BA levels are used as a biomarker in certain cholestatic conditions. BAs can initiate processes in the pathogenesis of drug-induced liver injury (DILI), an unpredictable occurrence which can lead to liver failure. As such, this study aimed to explore whether changes in plasma BA profiles can serve as useful biomarkers for diagnostic and prognostic purposes in patients presenting with suspected DILI. Methods: In a prospective, nested case-control observational study, adult patients presenting with acute liver injury potentially due to DILI (at secondary care centres in 6 European countries) were sampled and followed through standard clinical care with severity and outcomes monitored. After review, cases were adjudicated as DILI (n=120) or nonDILI (alternate causes; n=49). Plasma BA levels and profile were quantified by University of Salamanca and compared to those in healthy volunteers (n=25). This is linked to publication 'Usefulness of plasma bile acid profile as a prognostic biomarker for drug-induced liver injury'. Values reported to 4 decimal places. Mean recovery (±SEM) for samples in the DILI group (n=120) was 89.0±0.8%, which was very close to that for the NonDILI group (n=49; 87.0±1.6%). The accuracy of calibration curves was calculated at an intermediate point of the concentration range, i.e., 5 µM. The results indicated that the average value (±SEM) was 91.6±0.8% for 230 calibration curves, with no significant differences among bile acid species. Reproducibility was calculated at two concentrations of the calibration curve for each of the 22 BAs analyzed. The coefficients of variation (CVs) were lower than 15% (range 2.8-14.5%) at 1 µM, and lower than 2% (range 0.8-1.8%) at 25 µM.

This dataset corresponds to the study "Green Food Choices under Mortality Salience: A Dual-path Mechanism of Self-esteem and Cultural Worldview" (with its Chinese title: 死亡凸显下绿色食品选择的双路径机制：自尊与文化世界观的作用). It aims to verify the impact of Mortality Salience (MS) on individuals' green food choice behavior and examine the dual mediating role of "Self-esteem" and "Cultural Worldview" in this process. The dataset records the raw data of all observed variables during the experiment, which can be used to reproduce research conclusions, conduct secondary analyses (such as the expansion of moderating effects and subgroup analyses), or provide data support for relevant research in the fields of mortality salience theory and green consumption behavior.

Over 30% of veterans of the 1990-91 Gulf War experience a chronic multi-symptom disorder, Gulf War Illness, that has been associated with underlying persistent neuroinflammation as a result of chemical and physiological exposures experienced during deployment. Current research is largely focused on identifying effective treatment strategies for the underlying cause of Gulf War Illness instead of treating specific sets of symptoms. Through the computational evaluation of blood biomarkers and gene expression in veterans with Gulf War Illness, we previously identified that a combination of anti-inflammatory and anti-glucocorticoid treatment may prove effective in treating the underlying neuroimmune dysfunction associated with Gulf War Illness. Here, we have evaluated combined treatment with the anti-TNFα drug, etanercept, and anti-glucocorticoid, mifepristone, in an established long-term mouse model of Gulf War Illness of combined physiological stress and nerve agent exposure. Supporting the computational modeling of this treatment, we found that this drug combination significantly alleviates the underlying neuroinflammation associated with Gulf War Illness. The fusion of computational and in vivo preclinical treatment evaluation may provide a highly useful and translationally-relevant means by which to identify successful treatment paradigms for Gulf War Illness.