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This dataset supports the article “Mode I fracture and cohesive behavior of 1C-PUR bonded Chilean Pinus radiata D. Don: Effect of predominant crack propagation path” (Polymers). It contains the experimental data of the double cantilever beam (DCB) tests on Chilean radiata pine bonded with a one-component polyurethane (1C-PUR) adhesive, tested in the tangential–longitudinal (TL) and radial–longitudinal (RL) fracture planes, the GNU Octave scripts used for the numerical simulation and the identification of the cohesive parameters, and the files of the mesh convergence and sensitivity study of the numerical model

This dataset (ML-CFD-Wavy-Channel-Surrogate_v2.zip) supports the published article “Machine learning surrogate for CFD-based prediction of heat transfer and pressure drop in partially porous wavy channels” in AI Thermal Fluids. It contains the cleaned long-form CFD-derived dataset, fixed train-test split information, trained-model outputs, prediction files, validation tables, plot data, and the final reproducibility script used to train Random Forest surrogate models for predicting average Nusselt number and pressure drop. The dataset includes 4,608 CFD-derived samples generated from 18 geometric configurations and 256 operating-condition combinations. The input features are Reynolds number, Prandtl number, Darcy number, porosity, porous slab thickness, wave amplitude, and wavelength. The target outputs are average Nusselt number and pressure drop. The associated published article is available at: https://doi.org/10.1016/j.aitf.2026.100051

Research data and executable code accompanying “Contact model discrepancy and feasibility in surrogate assisted design of powered seat tracks” by Rahul Suryawanshi. The archive contains generated geometry data, retained contact-case and solver records, analytical screening and finite-compliance contact models, random seeds, analysis scripts, figure-generation code, and supplementary methods. The study compares contact-model representations and surrogate-assisted design feasibility. It includes a re-audit of 414 screening-selected geometries and a separate dataset of 1,024 geometries with 55,296 converged contact-load cases. All observations are computational; no physical or crash validation is claimed. Public NHTSA source decks are identified by retrieval links and checksums rather than redistributed. Historical JACM filenames are retained for reproducibility. AI assistance with implementation, analysis and writing is disclosed in the accompanying methods and manuscript.

This dataset contains the replication package for a preregistered laboratory experiment on the framing of reminders for preventive care. In the experiment, 372 participants in two Czech laboratories made 40 repeated decisions about a preventive check-up. The check-up cost working time in a real-effort task but halved the risk of a larger time loss from illness. All participants received a reminder, and five groups differed only in its wording: neutral, loss aversion, social norms, urgency, or positive reinforcement. The study was preregistered at OSF (https://osf.io/wb7ya/). The package contains: the anonymized decision data (14,880 participant-period observations) and participant data (372 participants), including questionnaire measures and answers to an open question on decision criteria; a SAS script that reproduces all tables, figures, and numbers reported in the paper; the z-Tree program and the reminder images; the instructions and screen texts in Czech with English translation; a README with a data dictionary and replication steps. Participant identifiers, session dates, year of birth, and field of study were removed. Two open answers containing personal health information were redacted.

As per the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses – Scoping Review extension) criteria, this research provides a unified bibliometric, patent analysis, and AI-based assessment of the PET research domain globally between 2010 and 2025. This research analysis is conducted using the database search performed in May 2026 and consists of a Scopus dataset of 1,125 papers and Lens.org dataset of 1,000 patents. The literature shows a 27-fold increase over 15 years and an acceleration due to the discovery of the PET-digesting enzyme PETase.

Model inputs, results and scripts behind the paper "Integrating an HTGR side stream with sewage sludge drying and pyrolysis: pinch, exergy and heat exchanger analysis". The paper assesses the delivery of side-stream heat from an HTR-PM high-temperature gas-cooled reactor through an intermediate helium loop and a hot-air loop to a belt dryer and indirectly heated rotary kilns. Plant totals refer to a notional central plant of 385.8 t dry solids per day. The package holds the Aspen Plus input files of the base case and 24 sensitivity cases, selected inputs and results of the Aspen Exchanger Design and Rating (EDR) runs of the three high-temperature exchangers in JSON form, the pinch inputs and targets, the meshes, scripts and results of the Ansys Fluent model of one kiln jacket, the result tables quoted in the paper, the check records behind the verification tables, and the scripts of the analysis, tables and figures. All files can be read without Aspen or Ansys software. Files in Aspen and Ansys formats are not included and are listed with their size and SHA-256 in OMITTED_FILES.csv. Running the models requires Aspen Plus V15, Aspen EDR V15, Aspen Energy Analyzer V15 and Ansys Fluent 2025 R1. These were used under the academic licences of Gebze Technical University. Start with README.md. PAPER_TO_FILES.csv maps each table, figure and section of the paper to its files and scripts, MANIFEST.csv lists every file with its checksum, and glossary.csv explains the stream, block and case names.

Python code reproducing all numerical results, Table 1 and Figure 1 of the paper and its supplementary appendix. The paper is theoretical, and no empirical data are used.

Data and analysis code of An easily shattered illusion: How changes in animacy shape mind attribution and responses to a humanoid robot’s direct gaze. The analyses were conducted in R. Contact: Samuli Linnunsalo (samuli.linnunsalo@tuni.fi)

A data set comparing sampling efficacy of insect orders using Bioquip UV lights versus Entoquip UV lights. Data set is comprised of three sheets in one Excel file.

The measured data is from the paper "From canopy reconfiguration to channel resistance: An effective length framework for submerged flexible vegetation"