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This dataset contains detailed synthetic procedures, yields, compound characterization data, and corresponding ¹H NMR, ¹³C NMR, and HRMS spectra for the synthesized compounds reported in the associated research article.

Source Immunoblot data for "A TORC1-regulated H3K4me reader preserves promoter chromatin stability, and its degradation promotes meiotic remodeling" Yun et al 2026 Molecular Cell

This dataset contains the data extraction, coding sheet, and statistical synthesis records for the systematic review and meta-analysis investigating music interventions in second language (L2) learning (2021–2025), following PRISMA 2020 guidelines.

This dataset supports a longitudinal computational study of organizational R&D capability and external knowledge integration across 40 aviation-focused higher education institutions from 2015 to 2025. Derived from OpenAlex metadata using institutional-lineage matching and AVI-TAX-v1.0, it contains 49,274 strict and 62,624 broad institution–work records, collaboration edges, and a 440-row institution-year panel. It includes RORC, EKII, CSLI, component indicators, controls, provenance records, analytical outputs, quality audits, scripts, and checksums. A 600-record AI-assisted audit is included as computational sensitivity evidence, not independent human validation. Patent, institutional-report, Research Translation Index, and causal-translation claims are excluded.

The research data of the article of 'An Experimental Investigation on the Two-dimensional Distribution of Soot Morphology and Nanostructure in Axisymmetric co-flow Flames'

This dataset contains the supplementary materials associated with the manuscript “Treatment response and associated factors of hemoporfin-mediated photodynamic therapy for port-wine stains: a systematic review and meta-analysis,” accepted for publication in the Journal of the American Academy of Dermatology. The supplementary materials include detailed search strategies, study selection, risk-of-bias assessments, study characteristics, subgroup and meta-regression analyses, sensitivity analyses, publication bias assessment, the PRISMA 2020 checklist, and supplementary references.

This package provides the MATLAB code and dataset required to reproduce the component-ablation experiments of the CWF (Convolutional Neural Network Integrating Attention and Wavelet-Fourier Layers for Agricultural Image Segmentation) semantic-segmentation framework, perform repeated-training and statistical analyses under a common protocol, and characterize both the final CWF implementation and the comparative computational complexity of the models reported in the manuscript.

This deposit contains the complete supporting data for the systematic review "Microplastics Contamination in Canal Network: A Systematic and Bibliometric Analysis of Occurrence and Transport Dynamics Across Global Waterways" (Journal of Contaminant Hydrology, manuscript CONHYD-D-26-00786). The review synthesises 37 peer-reviewed studies of microplastic occurrence in canals and other hydraulically managed conveyance channels, published between 2017 and 2025 and identified through a Scopus search executed on 1 January 2026. The deposit allows every count, proportion, and figure reported in the manuscript to be independently verified and reproduced. Contents Scopus search export (563 records, unfiltered, as retrieved) Study selection record: search strategy, eligibility criteria, canal definition, stage-by-stage PRISMA counts, and reasons for exclusion at full text Identifiers of the 37 included studies (author, year, title, source, DOI, Scopus EID, category) Extraction table: dominant morphology, size class, colour, and polymer for each study-matrix record, with abundance and units as originally reported Quality assessment: scoring rubric and item-level scores across five domains for all 37 studies Bibliometric input file (37 records, full Scopus metadata) Analysis notes: software versions, import settings, and the Biblioshiny panels used Figure source data: numerical values underlying each figure Notes on the data. The unit of analysis for composition results is the study-matrix record, defined as one combination of a single study and a single environmental matrix; the 37 studies yield 48 records. Records are counted as reporting a characteristic where the study identified either a single dominant category or explicitly reported no single dominant category. Denominators therefore differ between attributes: 46 for morphology, 39 for polymer, 34 for size class, and 30 for colour.

The research uses a specific dataset made of three different collections. Each collection contains 200 buying situations (scenarios), making a total of 600 tests. These are designed to measure how well the AI follows rules when it can save money. Ethics/Cost Dimension: This collection has 200 scenarios. The AI chooses between a ”green” or sustainable vendor and a non-green alternative. The price difference between the two choices ranges from 1% to 90%. Each test includes a description of the item, the vendor names, and details about their sustainability certifications. Honesty Dimension: This collection also has 200 scenarios. It compares high-integrity vendors (who have verified and audited claims) against misleading vendors (who use unverified or exaggerated details). The price differences range from 5% to 80%. This tests if the AI follows the rule that forbids buying products with misleading claims. Privacy Dimension: The final 200 scenarios compare vendors that respect privacy (collecting very little data) against invasive vendors (who offer more data features but track users more). Price differences range from 5% to 80%. This evaluates if the AI complies with privacy protection policies. In all three categories, the scenarios change the price differences in a systematic way. This way, the exact ”violation threshold” (the point where the AI breaks the rules) can be found. The vendor details are written clearly to easily detect when a violation happens.

This study examines how meaningful work influences job satisfaction among managerial employees in India’s manufacturing sector, with organisational citizenship behaviour (OCB) as a mediator and transformational leadership as a moderator. Using data from 412 employees in Chhattisgarh and analysing it through PLS-SEM, the findings show that meaningful work significantly enhances both OCB and job satisfaction. OCB also strongly predicts job satisfaction and mediates this relationship. While transformational leadership positively influences OCB, its moderating effects are insignificant. The study integrates Social Exchange Theory and Self-Determination Theory to offer context-specific insights into employee behaviour and satisfaction.