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Official dataset related to the paper: Overcoming data scarcity in roadside thermal imagery: A new dataset and weakly supervised incremental learning framework The paper is available at https://doi.org/10.3390/s25072340. Please cite the paper when using the dataset.

This dataset contains the following files to support the research paper "Volcanic Lithology Logging Identification Based on ADASYN-KNN-Random Forest Ensemble Model Taking the Carboniferous System on the Hanging Wall of Kebai Fault Zone as an Example": Raw_Data.xlsx: Thin-Section Data: High-resolution measurements/images of volcanic rock samples with lithology labels (e.g., basalt, andesite). Logging Data: Corresponding well-logging responses (gamma ray, density, neutron porosity) for each sample. Columns: Sample_ID, Depth (m), GR (API), DEN (g/cm³), CNL (%), Lithology_Label, Mineral_Composition (%). ADASYN_Resampled_Data.xlsx: Balanced dataset generated after applying ADASYN (Adaptive Synthetic Sampling) oversampling to address class imbalance. Includes synthetic samples for minority lithology classes. ML_Code.zip: ADASYN_Oversampling.py: Python script for adaptive oversampling (uses imbalanced-learn). KNN_RF_Classification.py: Combined script for KNN and Random Forest training/prediction. Requirements.txt: Dependencies (e.g., Python 3.13, pandas, scikit-learn).

Type IV hydrogen storage vessels have been widely adopted in hydrogen-powered transportation systems. The Boss, a critical connecting component of type IV hydrogen storage vessels, plays a pivotal role in their overall safety evaluation, particularly with regard to its failure modes. This dataset is about the raw data of Boss, including chemical composition content and raw geometric data of Boss components. The Energy Dispersive Spectrometer (EDS) report provides elemental analysis results for Zone A and Zone B of the Boss fracture surface.

The data is about the application of DHIMS2 and LHIMS in Ghana.

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

The data in the file correspond to responses from potential electric vehicle customers in Ecuador. The Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) served as the theoretical basis for this study. The participants ranged in age from 18 to 65 years and resided in the cities of Quito and Guayaquil. The first variables in the file represent the demographic information of the individuals. The constructions utilized in the model are shortened and assigned a numerical identifier.

This dataset contains supplementary data supporting the study with the same name, authored by Gerardo Valadez Huerta, Kaoru Hisama, Katsutoshi Sato, Katsutoshi Nagaoka, and Michihisa Koyama. The study focuses on N₂ dissociation on Ru/La₀.₅Ce₀.₅O₁.₇₅₋ₓ catalysts, as described in the manuscript and supporting information. It enables full reproduction of the simulations. Please refer to the paper for details or contact the corresponding authors for further information.

Data for Experiments 1-3

Data of the survey conducted for the research titled, "Social Media Freedom During Karnataka State Election 2023 Perceptions of Young Voters". Corresponding author: Vinay B S