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This dataset contains processed ground-motion inputs, response-ratio datasets, and analysis scripts supporting the manuscript "Coupled Fault-Slip and Vibration Response in Fault-Crossing Tunnels: Statistical Characteristics and Correction-Based Prediction". The files include acceleration, velocity, and displacement time histories for recorded and simulated fault-crossing ground motions, datasets used to calculate fault-slip and vibration contribution ratios, datasets used for probability distribution fitting and Q-Q plots, and input data for the 1 Hz frequency-based decomposition of coupled fault-slip-and-vibration motions. The dataset supports the figures and statistical analyses reported in the manuscript, including the input-motion time histories, response-ratio histograms, distribution fitting, correction-parameter comparison, and frequency-decomposition illustration. Raw shaking-table response records are not included because they are project-specific experimental records generated within an ongoing infrastructure research program. The shared files are processed datasets and scripts sufficient for checking the analyses and reproducing the main plotted data used in the manuscript.

in today’s era where there is a lot of online shopping place like Tokopedia, Shopee, and tiktok, people are going to jump platform to find a better deal. And one way to attract new customers is to innovate, Gamification is one of the methods that can be used to attract or retain new or old customers. The purpose of this study is to examine the impact of gamification on whether gamification has any positive impact on customer loyalty on the online shopping platform called Shopee. The research method is a quantitative technique using a questionnaire with Google Form platform. The target recipients are people that use Shopee and play Shopee games. PLS SEM is used for data processing methods, the result obtained in general is that gamification does impact have positive in customer loyalty.

Data files in the repository provide access to all data that appear in all figures and tables in both the main paper and any supplement of the paper "Oxygen isotopic and chemical composition of chromites in the unique Washington County iron meteorite and implications for classification" by Vogt et al. (2026). Refer to the file name for the respective figures and tables in which the data appear.

This dataset comprises 972 georeferenced observations collected across Port Harcourt, Nigeria, for assessing urban environmental quality. Each observation includes the Urban Environmental Quality Index (UEQI) and its constituent sub-indices, along with spatial coordinates and cluster classifications. Variable Description lat, lon Geographic coordinates (WGS84) of each sampling location UEQI Urban Environmental Quality Index (0-100 scale), computed as a composite indicator of urban environmental conditions Cleanliness Sub-index measuring waste management and cleanliness Infrastructure Sub-index assessing urban infrastructure quality Traffic Sub-index for traffic congestion and mobility Environment Sub-index capturing environmental conditions Aesthetics Sub-index for visual aesthetics and green spaces UEQI_Cluster Classification of UEQI values into three categories: 1 = Low Quality, 2 = Moderate Quality, 3 = High Quality

This bibliographic review analyzes the development of AI-based digital technology to support human creativity in human-computer interaction. The use of AI as a tool has now become commonplace. In addition to assisting human work, this technology enables humans to work faster and opens up opportunities for new things. This rapid development increasingly emphasizes the role of AI as an active partner for humans in completing work, particularly in terms of creativity, where AI can support humans in developing broader creative ideas. Through the collaborative process between humans and AI, broader opportunities can be opened in the creation or discovery of new things that were previously difficult. AI can act as an initiator in generating ideas or as a corrector that can provide input for humans. On the other hand, human control over this technology still needs to be considered. The use of this technology must be accountable and used wisely.

This dataset contains the Python code described in the STAR Protocol of the same name and used in the associated research paper (iScience, Volume 28, Issue 5, 112470). The code in the associated research paper was released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license and is provided here in a reorganized, structured directory layout for direct use. The dataset includes example supported nanoparticle catalyst models and reference workflows that enable construction of SMSI systems, exploration of adsorption configurations, and analysis of simulated IR spectra. The dataset is intended to facilitate reproducibility, reuse, and extension of the methodology presented in the associated research paper and STAR Protocol.

Supplementary material.

A Weighted Sentiment Dataset for Indonesian Telemedicine Text Classification is a collection of Indonesian telemedicine user reviews that are annotated with weight and sentiment labels. The data were collected from user reviews of three telemedicine applications in Indonesia, named Alodokter, Halodoc, and KlikDokter. The dataset contains 19,680 rows of user reviews that used Indonesia language and mixed more than one language. Each user review is annotated manually by two human annotators following annotation guidelines created by psychological expertise. This dataset consists of 6 attributes: platform (application distributor platform), app_name (application name), rating (application user satisfaction score), review (Application user review), sentiment (data label), and weight (user review complexity label). The dataset supports experiments in advanced NLP technologies, including BERT, LSTM, and LLMs, such as a user review sentiment classification task.

A comprehensive dataset of health system indicators including UHC index, physician density, and health expenditure. Includes the dynamic ARDL model code and results exploring the impact of Vision 2030 reforms [54، 60، 62]. Keywords: Universal Health Coverage, Health Expenditure, ARDL, Saudi Arabia, Vision 2030

This dataset contains the original interaction pairs, protein–protein interaction networks, differential protein lists, enrichment analysis results, and statistical source data supporting the results of the manuscript submitted to Virulence.