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A large-scale synthetic dataset of 15 million credit card transactions is generated for fraud detection research. It is divided into four segments: A_Established (40%), B_Regular (30%), C_New (20%), and D_Guest (10%), with segment-wise fraud rates of 2.5%, 4.0%, 7.0%, and 12.0% respectively. Overall, 95.10% of transactions are legitimate and 4.90% are fraudulent. Segments A, B, and C are based on persistent customer profiles that include behavioral attributes such as baseline spending, usual merchant category, account age, and credential change history. Segment D represents anonymous transactions generated from global distributions without historical customer context. Each record includes 33 features covering transaction amount, geographic behavior, device and network signals, authentication details, and behavioral patterns. Fraud cases are generated using four compound signal clusters: Card-Not-Present, Bot/Card Testing, Account Takeover, and Geo-Velocity. Controlled label noise is introduced in borderline cases to simulate real-world uncertainty. The dataset is generated using a reproducible and memory-efficient pipeline built with Python, NumPy, Pandas, and PyArrow. It is provided in Snappy-compressed Parquet format for efficient storage and in CSV format for easy accessibility. This dataset is suitable for understanding and assessing fraud behavior in realistic financial transaction settings.

The objectives of this study were to establish normative ranges for envelope following response (EFR) magnitude in a population at low risk for cochlear synaptopathy and then compare EFRs from a population at high risk for synaptopathy to those normative ranges. The low-risk sample consisted of young adults with normal audiograms, minimal reported lifetime noise exposure, and no auditory complaints. Normative ranges were generated using rectangular amplitude modulated (RAM) or sinusoidal amplitude modulated (SAM) EFR stimuli and were adjusted for sex and distortion product otoacoustic emission (DPOAE) levels. The high-risk sample consisted of military Veterans with normal audiograms who reported at least one auditory complaint (tinnitus, decreased sound tolerance, or speech-in-noise difficulty). The RAM EFR normative ranges for a 4 kHz carrier resulted in the biggest separation of the low- and high-risk samples, with 31-34% of Veterans falling below the lower bound of the normative range. There were no consistent effects of DPOAE adjustment on the normative ranges across sex and stimulus condition and computational modeling suggests that adjusting for DPOAEs may not be necessary in individuals with normal audiograms. These results suggest that EFR normative ranges for the 4 kHz RAM EFR will allow for clinical identification of patients with normal audiograms who may have significant degrees of cochlear deafferentation.

This dataset contains the qualitative and quantitative raw data underlying the article “AI-generated podcasts in higher education: Do they deliver? An author-based pilot study on the quality and didactic potential of automated audio summaries of scientific papers.”

This registration includes two files: a dataset and R analytic code for the study entitled “Going Digital, Becoming United: Video-Based Online Intergroup Contact Reduces Intergroup Bias.” Please note that the manuscript will undergo the peer review process, and the title may change during revision.

original file of western blot

The Ecological Impacts of Artificial Intelligence from YouTube Comments dataset is a collection of YouTube user comments discussing the environmental impacts of Artificial Intelligence (AI), including energy consumption, water usage in data centers, carbon emissions, and the concept of Green AI. This dataset is used to analyze public perceptions and discourse regarding the ecological issues of AI through approaches such as text mining, sentiment analysis, and topic modeling (LDA), helping researchers understand public awareness of the sustainability impacts of AI technology.

Transcriptome data of Serratia marcescens HBQT before and after selenite treatment.

Replication package for: Cilliers, Jacobus, and James Habyarimana. 2026. "Addressing Weak Links in Government Implementation at Scale: Experimental Evidence from a School Governance Reform in Tanzania." Journal of Development Economics

Research data to show the reproducibility of our experiments and provide editors and reviewers with more information about our work.

Questionnaire Data Set Responses