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This dataset contains the supplementary materials associated with the study “Comparative Hazards of Ocular Surface Disorders with IL-4/13 versus IL-13 Inhibitors in Atopic Dermatitis: A TriNetX Database Study.” The materials include detailed coding definitions, additional analyses, and supporting figures that complement the main manuscript and provide transparency for the analytic methods and results.

This dataset is linked to the study "Visitor characteristics and museum fatigue: a case study at the ETRU museum in Rome". It includes behavioural (position tracking) and physiological (heart rate) data from an experiment investigating the role of individual characteristics on museum fatigue. The dataset is divided into five files: ETRU_DATA_RAW: Full dataset with all collected data, including unprocessed variables and excluded participants ETRU_R_PROJECT: The R-Studio project with the script used for all the data analysis ETRU_DATASHEET_CATEGORIES: Demographic characteristics of participants (Age, Sex, Education, Public). The R-Studio project uses this file for cluster analysis. ETRU_DATASHEET_LONG: Preprocessed dataset in long format excluding participants not included in the analysis. The R-Studio project uses this file for spatial time-series analysis. ETRU_DATASHEET_WIDE: Preprocessed dataset in wide format excluding participants not included in the analysis. The R-Studio project uses this file for correlation analysis. These files enable replication of the analyses in the main paper and provide additional opportunities for secondary analyses.

Supporting Information for "Quantitative analysis of Calabrian planktic foraminifer assemblages and paleoecology of the Eastern Mediterranean from the onshore epibathyal sedimentary archives (Mersin, Turkey)"

This dataset provides model outputs, summary tables, and reproducible scripts supporting an evaluation of baseline RUSLE (LS) versus deformation-aware LS′ derived from PSInSAR, and the downstream implications for routed sediment redistribution using TLSD in two dryland watersheds (Yarkon-Ayalon and HaBsor). Outputs are provided for (i) gross detachment estimates from RUSLE and (ii) routed net erosion/deposition and sediment export derived from TLSD, enabling scenario comparison between DEM-based LS and PSInSAR-conditioned LS′. Included materials comprise (1) geospatial rasters (GeoTIFF) at the analysis resolution used in the study (e.g., LS and LS′ surfaces, gross erosion rate, TLSD deposition and net balance, sediment export, and SDR outputs), (2) PSInSAR spatial-support masks and associated summaries used to document where LS′ reverts to LS outside PS-supported areas, (3) block-aggregated land-use statistics based on non-overlapping 10×10 pixel blocks (modal land-use class; ≥70% valid coverage) and non-parametric comparisons (Kruskal-Wallis with ε²; Mann-Whitney with Holm correction; Cliff’s δ), and (4) Python scripts (rasterio + matplotlib) used to generate the main-paper and supplementary figures and tables. All p-values are reported descriptively given spatial dependence; effect sizes are provided to support interpretation. PSInSAR deformation is used to condition LS′ and does not directly measure erosion. Where third-party input datasets cannot be redistributed, the repository includes derived products and scripts/instructions to reproduce results from the original sources.

All model files (baseline and optimized), together with the corresponding Genetic Algorithm scripts and their associated input and output datasets, are provided to ensure transparency and reproducibility of the reported results.

This study experimentally evaluates the effectiveness of RFID technology for self-checkout applications in the Fast-Moving Consumer Goods (FMCG) sector, aiming to identify the key factors affecting reading accuracy. An experimental campaign was conducted using a fractional Design of Experiments (DoE) approach, considering shopping cart material, product quantity, presence of liquid products, presence of metal-containing products, and use of shielding bags as independent variables. Reading accuracy was analyzed through ANOVA to quantify the influence of physical and operational factors. The results show that reading accuracy ranges from 73% to 100%. The presence of liquid products emerges as the most significant factor, causing the largest performance degradation. The impact of metal-containing products, although difficult to isolate due to the pervasive presence of metal in carts and shielding bags, is statistically significant and mainly results in an increased performance variability. Product quantity exhibits a negligible effect. The highest accuracy is achieved under favorable configurations, particularly in the absence of liquids. Significant interaction effects are also observed, especially between cart material and the presence of metals. The study provides a quantitative assessment of RFID self-checkout performance in realistic FMCG environments, highlighting its current technical limitations, and offering practical insights for technology developers and retailers.

Long-term, repeated exposure to heat stress may contribute to chronic kidney disease (CKD), yet global evidence remains limited. In this ecological study, we aimed to examine the association of different categories of heat stress, as well as the overall heat stress score, with the incidence of CKD at the country/region level. Data from 174 countries/regions were analyzed. Annual numbers of days with moderate, strong, very strong, and extreme heat stress in each country/region between 1990 and 2021 were assessed using the Universal Thermal Climate Index. A weighted heat stress score was generated from these counts. Linear mixed-effects models were used to evaluate the association between heat stress score and CKD incidence. The results showed that all heat stress categories were positively associated with CKD incidence. In models using the weighted heat stress score, each standard deviation increase in the score was associated with an estimated 0.890 (95% CI: 0.717–1.063) additional incident cases per 100,000 population. In this ecological study, we observed country/region-level associations between heat stress and CKD incidence; nevertheless, further validation is warranted.

This dataset contains 761 valid survey responses from Indian Gen-Z consumers (aged 18-28) regarding their consumption behaviour of staple foods via Food Delivery Apps (FDAs) like Zomato and Swiggy. The data was collected between July and September 2025 using a judgemental sampling method. The research framework is grounded in the Theory of Consumption Value (TCV), measuring five key dimensions: functional, emotional, social, conditional, and epistemic values. The dataset includes Likert-scale responses for these values, as well as measures for consumer attitude, behavioural intention, and actual buying behaviour. Demographic variables such as sex, education level, family size, work setting, and ordering frequency are also included. This data was utilised to perform a dual-stage analysis: Structural Equation Modelling (SEM) for linear relationships and Multivariate Adaptive Regression Splines (MARS) for non-linear threshold effects.

The data offers a collection of article datasets exploring the use of blockchain technology and smart contracts in enhancing agricultural logistics. It includes research on automation, traceability, fraud reduction, and operational efficiency within supply chains, focusing on the integration of blockchain with IoT for real-time monitoring.

This supplementary table lists all ingredients with sensitizing/allergenic potential identified via composition analysis of 399 commercially available nail cosmetic products, ordered from most to least common.