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Data Availability of "Multi-parameter MRI Assessment of Metformin and Exercise Effects on Skeletal Muscle in Prediabetes: A Randomized Controlled Trial"

ODD SPOT is a next generation mnemonic and associated educational tool encompassing validated photos, words, descriptions and caution graphics for basal cell carcinoma, squamous cell carcinoma and melanoma. It is written in plain, clear language and scores high on readability and clear communication. It is designed to educate the general public about skin cancer in an approachable and easy-to use tool.

This dataset contains supplementary tables used in the analysis of evaluator expertise and indicator clustering with Self-Organizing Maps (SOMs). Each table reports the hyperparameter settings and performance metrics for SOM training, including: Initial and final sigma values Initial and final learning rates Initial, final, and minimum quantization error Number of neurons used Distribution of indicators across neurons The dataset supports the reproducibility of the clustering analysis presented in the manuscript Self-Organizing Maps and Evaluator Expertise for Transparent and Reproducible Consensus-Based Indicator Selection. Future versions of this dataset will include additional processed files and Jupyter notebooks used in the analysis.

Replication files

The data files are placed in the corresponding directories named after the numbers of figures of the submitted manuscript.

This dataset contains experimental results from the synthesis and characterization of Laser-Induced Graphene (LIG) on polyimide substrates and its application in the development of sensing devices. The data covers the analysis of LIG produced under different laser conditions (CO2 at 10600 nm, blue at 450 nm, and UV at 355 nm), as well as the characterization of nanostructured semiconductor metal oxides (SMOx) and their LIG-SMOx nanocomposites. The explored applications include the development of a flexible electronic tongue (e-tongue) based on LIG and gas sensors. The repository includes data from multiple characterization techniques. Structural and morphological analysis was performed by Raman Spectroscopy, X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), and Scanning Electron Microscopy (SEM). Electrical properties were investigated through Hall Effect measurements (Van der Pauw method) and Electrochemical Impedance Spectroscopy (EIS). The e-tongue data is primarily based on EIS measurements on both bare and SMOx-functionalized interdigitated electrodes (IDEs). The data is organized into three main folders: 1) Characterization of Laser Induced Graphene and SMOx nanoparticles 2) E-tongue based on LIG Development (e-tongue device data) 3) LIG-SMOx nanocomposites for gas sensing aaplications Within each folder, subdirectories are named after the characterization technique (e.g., 'Raman', 'SEM'). Each contains a 'raw' folder with unprocessed data and a 'visualization' folder with plots (HTML) for quick preview. A root file named 'sample_code' (.csv and .xlsx) provides the metadata linking each sample to its synthesis parameters.

This study investigates the sociological foundations of Turkish adolescents’ sharing behaviors on social media, focusing on digital disclosure and exposure practices. Drawing on the concept of omnioptic surveillance, where individuals act simultaneously as observers and the observed, data were collected from 350 students across seven high schools using a 61-item structured questionnaire. A cross-sectional descriptive design guided the research, with analyses conducted through frequency distributions, percentages, means, t-tests, and ANOVA. Results revealed that adolescents actively reproduce omnioptic surveillance in their routine online interactions, perceiving digital disclosure and exposure not as a violation of privacy but as a normative social practice. While gender differences were insignificant, variations emerged across grade levels and school types. These findings suggest that adolescents sustain a digital culture in which privacy boundaries are fluid and continuously renegotiated. The study contributes to debates on adolescent digital literacy, privacy awareness, and the sociological dynamics of networked surveillance.

Water security is a crucial issue in arid and semi-arid regions like the Lower Awash Basin, Ethiopia, where increasing population and economic development put pressure on limited water resources. This study evaluates the suitability of sand dam sites using a multi-criteria evaluation approach combined with geospatial techniques. Meteorological data were carefully tested for consistency and homogeneity through double mass curves, Pettitt’s test, and Mann-Kendall analysis. Key biophysical factors such as slope, stream order, soil type, land use/land cover (LULC), runoff depth, and proximity to roads were reclassified and weighted according to their importance for sand dam feasibility. Runoff depths ranged from 682-934 mm, with 69% of the basin receiving 820-930 mm, indicating abundant water availability. Slope analysis showed that 47.4% of the land has gentle gradients (0–5.23°), suitable for dam stability. However, limited feasibility was observed due to stream networks, with only 4.78% of the basin being moderately or highly suitable. Soil assessment identified Fluvisols (21.91%) and Regosols (2.5%) as ideal, whereas Leptosols (43.06%) were unsuitable. LULC mapping revealed that rangelands dominate (71.6%) and provide moderate suitability, while water bodies and flooded vegetation (~2.3%) are highly favorable. Areas more than 4,000 meters from roads (79.6%) were considered optimal to reduce flooding risks near infrastructure. Overall, the integrated analysis found only 1.2% (36,855 ha) of the basin as highly suitable and 10.96% as moderately suitable for sand dam construction, while 47.74% was unsuitable. Results show limited ideal sites and stress the need for localized assessments to ensure sustainable sand dam development.

Commodity-level mirror statistics of Sri Lanka's exports with 19 largest trading partners from 2012 - 2023 (excluding 2018).

This dataset contains anonymized clinical and laboratory data of 154 patients diagnosed with peripheral arterial disease (PAD) who underwent peripheral angiography at our tertiary cardiovascular center between July 2024 and July 2025. The dataset includes demographic characteristics, laboratory biomarkers (including CRP, albumin, lymphocyte count, NT-proBNP, sodium levels), lesion complexity (TASC II classification), and treatment outcome. The data were collected retrospectively and fully anonymized to protect patient confidentiality. This dataset supports the findings reported in the manuscript entitled “[The Role of OPS in Assessing Lesion Complexity and Predicting Treatment Outcomes in Patients with Infrapopliteal Peripheral Artery Disease].