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This repository provides the datasets supporting the manuscript “Longitudinal Changes in Psychological Flexibility and Emotional Well-Being Following a Brief Psychoeducational Intervention in Adults.” The files include data used to construct composite indices and to perform longitudinal linear mixed-effects modeling across three time points (pre-intervention, post-intervention, and follow-up) in a community adult sample following participation in the Introductory Course in Bioneuroemotion (CIB). Data are available in SPSS (.sav) and CSV (.csv) formats to ensure reproducibility and compatibility across statistical platforms.

This dataset contains the experimental data and processing scripts supporting the thermo-optical investigation of ultra-lean methane and CO2-diluted methane combustion in an optically accessible AVL 5402 single-cylinder research engine. The experiments were conducted under spark-ignition and ultra-lean conditions (λ ≈ 5.5). The dataset includes crank-angle-resolved in-cylinder pressure data, cylinder volume traces, calculated apparent heat release rate (HRR), mass fraction burned (MFB) metrics (CA10, CA50, CA90), IMEP values, and exhaust gas emissions (dry basis, ppm and vol.%). Python scripts used for signal filtering and combustion analysis are provided to ensure reproducibility. The dataset is made available for peer review and will be publicly accessible upon article acceptance.

This dataset contains the structured data extracted for a systematic literature review examining the multidimensional impact of programming and artificial intelligence (AI) education in primary school (ages 6–12). The dataset includes detailed information on included studies, screening and eligibility criteria, and analytical coding across four dimensions: cognitive, social, socioemotional, and technical outcomes. Studies were identified through systematic searches in multiple academic databases and selected according to predefined inclusion and exclusion criteria. Data were extracted and synthesised using a mixed-methods approach to identify pedagogical practices, reported impacts, methodological patterns, and persistent research gaps. This dataset supports transparency and replicability and may be useful for researchers, educators, and policymakers interested in digital competence development, AI literacy, and curriculum integration in primary education.

These are supplemental tables for a manuscript on using the Hybrid Mouse Diversity Panel's genomic, transcriptomic, and epigenomic layers to better understand the progression of heart failure

Replication package for "Working longer, feeling worse? How job quality shapes the mental health toll of delayed retirement" by Alexandra Lugova, Michele Belloni, Berangere Legendre, Jeremy Tanguy

The research hypothesis of this study is that the seismic response sensitivity of RC grid-like frames is primarily governed by structural geometry and member stiffness ratios rather than material strength properties. Specifically, it is hypothesized that higher-order geometric configurations, such as increased story height and specific bay aspect ratios, lead to a higher "Vulnerability Index" (β), where the rate of increase in structural drift relative to seismic intensity approaches unity. The data, generated through approximately 4,974 non-linear time history analyses using the ETABS API across 90 structural archetypes, supports this hypothesis. The primary dataset (ETABS_D.csv) includes variables such as story height (2 to 10 stories), bay aspect ratios (0.33 to 3.0), concrete strength (20 to 35 MPa), and various member dimensions. By relating the Peak Ground Acceleration (PGA) to the Maximum Interstory Drift Ratio (MaxIDR) using logarithmic power-law fits (EDP=a(IM)^b ), the data shows a clear divergence in seismic behavior based on height. Notable findings indicate that taller structures (9–10 stories) exhibit high sensitivity, with β values ranging from 0.93 to 0.96. Conversely, shorter buildings (2–5 stories) display a "hardening" response, with lower sensitivity indices between 0.57 and 0.65. Interestingly, the data demonstrates that concrete compressive strength has a negligible impact on response sensitivity, with β remaining relatively constant between 0.51 and 0.63 despite strength variations. The most critical factor identified is geometric stiffness; certain combinations of column and beam sizes achieved the highest vulnerability index of 0.98, suggesting that the "Strong-Column/Weak-Beam" principle is the most vital design consideration for these frames. To interpret this data, researchers should focus on the slope (β) of the Probabilistic Seismic Demand Model (PSDM). A β value closer to 1.0 indicates a linear relationship where seismic demand increases proportionately with intensity, representing higher vulnerability. Values significantly lower than 1.0 indicate a structure that possesses greater inherent reserve capacity or "hardening" against increased seismic loads. This data can be used to develop simplified fragility curves and to inform performance-based design strategies. By understanding which parametric configurations lead to higher β values, engineers can optimize member sizing to ensure that grid-like frames remain resilient under varying seismic intensities without relying solely on higher-grade materials. The dataset serves as a benchmark for validating simplified analytical models against rigorous non-linear simulation results. This enables a more nuanced understanding of how global structural parameters—rather than localized material upgrades—dictate the safety of grid-like reinforced concrete systems in seismically active regions.

This paper presents the design and implementation of a low-cost, reliable three-wavelength (3-λ) illumination device intended for photoplethysmography imaging (PPGI) measurements. The proposed system employs high-power light-emitting diodes operating in the green (520 nm), red (625 nm), and near-infrared (855 nm) spectral regions, enabling non-contact cardiovascular monitoring with flexible spectral configuration. The illumination module integrates seven green LEDs, eleven red LEDs, and fifteen infrared LEDs, a distribution selected to compensate for wavelength-dependent camera sensitivity while providing sufficient radiant intensity and spatial uniformity at low power consumption and cost. Each wavelength channel is independently driven using dedicated single-channel linear LED drivers with pulse-width modulation control, allowing precise adjustment of illumination intensity. System operation is managed by a microcontroller-based control platform, which ensures accurate timing, synchronization, and stable operation required for PPGI applications. The compact and modular design supports straightforward integration with camera-based imaging systems, while optional wireless control enhances usability in laboratory environments. Overall, the proposed illumination device represents a robust and cost-effective solution for experimental and applied PPGI measurements in research-oriented non-contact biosensing systems. All essential files for replication and further development are included: PCB_control_unit CAD Files PCB_illumination_unit CAD Files Protective_cover_top & bottom.stl CAD Files Illumination_device_app.m Matlab Files Illumination_device_firmware.rar Microchip studio Files

Ceilometer and Radiosonde data measured during November 2017. The ceilometer's data files are named according to the measurements' time of acquisition, where for example A7112616.DAT means that the file contains measurements acquired on the 26 of November 2017 starting at 4 PM. The structure of the file is explained in the CL51 manual. The radiosonde data files are named according to their time of flight, where for example 261117_1300.txt means that the radiosonde was floated on the 26 of November 2017 at 1 PM. The files are ASCII formatted in table form, where the column names are explained in the Meteomodem M10's manual.

This repository provides full methodological transparency materials for the LLM-assisted qualitative component of the study: Procedural Justice in AI-Mediated Return-to-Work Decisions: Privacy, Human Oversight, and Trust among Injured Workers. The package documents how a Large Language Model (LLM) was used as a structured analytic support tool within a human-led, theory-driven qualitative coding process. It includes coding scripts, prompts, validation procedures, example datasets, overlap metrics, and reproducibility materials. The LLM was used exclusively to assist structured extraction under predefined theoretical constructs. It did not generate new theory, replace human coding, or override human interpretive judgment. Purpose of the Repository The repository was created to ensure: Methodological transparency Replicability Parameter disclosure Prompt disclosure Validation transparency Stability testing documentation Compliance with emerging best practices in AI-assisted qualitative research It directly addresses editorial recommendations to open-source AI coding scripts and provide a clear step-by-step protocol.

dataset for SMAR model