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Citation metrics are widely used and misused. We have created a publicly available database of top-cited scientists that provides standardized information on citations, h-index, co-authorship adjusted hm-index, citations to papers in different authorship positions and a composite indicator (c-score). Separate data are shown for career-long and single recent year impact. Metrics with and without self-citations, ratio of citations to citing papers, retracted papers (based on Retraction Watch database) and citations to/from retracted papers are also shown to facilitate mapping of potential research integrity issues. Scientists are classified into 20 scientific fields and 174 sub-fields (Science-Metrix classification). Field- and subfield-specific percentiles are also provided for all scientists with at least 5 papers. Career-long data are updated to end-of-2025 and single recent year data pertain to citations received during calendar year 2025. The selection is based on the top 100,000 scientists by c-score (with and without self-citations) or a percentile rank of 2% or above in the sub-field. This version (9) is based on the August 1, 2026 snapshot from Scopus, updated to end of citation year 2025. Calculations were performed using all Scopus author profiles as of August 1, 2026. The c-score focuses on impact (citations) rather than productivity (number of publications) and it also incorporates information on co-authorship and author positions (single, first, last author). We make the data publicly available to facilitate transparency and research, but some websites that disseminate the data may interpret them in misleading ways, e.g. as absolute evidence of excellence. If an author is not on the list, it is simply because the composite indicator value was not high enough to appear on the list. It does not mean that the author does not do good work. PLEASE ALSO NOTE THAT THE DATABASE HAS BEEN PUBLISHED IN AN ARCHIVAL FORM AND WILL NOT BE CHANGED. The published version reflects Scopus author profiles at the time of calculation. We advise authors to ensure that their Scopus profiles are accurate. REQUESTS FOR CORRECTIONS OF SCOPUS DATA (INCLUDING CORRECTIONS IN AFFILIATIONS) SHOULD NOT BE SENT TO US. Instead, please sign in using the Scopus Author Feedback Wizard to submit such requests so that correct data can be used in future annual updates of the citation indicator databases. For any additional questions, see attached file on FREQUENTLY ASKED QUESTIONS. All citation metrics have limitations and their use should be tempered and judicious, e.g. see the Leiden manifesto: https://www.nature.com/articles/520429a

This repository contains the processed and derived data supporting the study, “Measurement sensitivity of a national food-access indicator to road-network distance: Evidence from the 2025 USDA SNAP-authorized Retailer Access Map.” The dataset was created from publicly available 2025 U.S. Department of Agriculture Economic Research Service SNAP-authorized Retailer Access Map (SRAM) data. The study evaluates how the choice between straight-line and road-network distance affects national food-access indicators while holding the retailer universe, census-tract geography, population data, and indicator definitions constant. The processed dataset covers 84,119 U.S. census tracts across the 50 states and the District of Columbia and includes variables used to evaluate paired straight-line and road-network accessibility measures. Derived outputs support analyses of low-access reclassification, population burden, threshold sensitivity, urban-rural heterogeneity, socioeconomic and demographic patterns, and spatial dependence. The repository includes processed tract-level analytical data, a data dictionary, manuscript-supporting tables, and derived results used in the study. Key derived measures include the Network Accessibility Penalty (NAP), defined as the road-network minus straight-line low-access population share, together with reclassification and population-based accessibility summaries. The primary 1-mile urban/10-mile rural comparison showed that 16.09% of census tracts changed low-access classification, while the estimated population beyond the corresponding access threshold increased by 33.87 million residents under road-network measurement. This repository contains processed and derived research data only. The original source data remain publicly available from USDA Economic Research Service through the Food Access Research Atlas and the 2025 SNAP-authorized Retailer Access Map. Users should consult the original USDA documentation for authoritative definitions, source methodology, and raw data.

Single-nucleus RNA-sequencing dataset from paired human myocardial tissue samples collected before and after cardiopulmonary bypass, generated to characterize dynamic transcriptional responses to acute cardiac ischemic stress.

This dataset contains public input data and processed benchmark outputs for deformation-induced energy-yield loss assessment in flexible photovoltaic mounting structures. It includes NASA POWER and PVGIS hourly inputs, extracted carbon-factor records, regional energy-mechanics benchmark tables, mechanics verification outputs, temporal loss diagnostics, Pareto scenario data, uncertainty/sensitivity results, and checksum metadata. The package is restricted to data files only, including CSV, JSON, MAT, and XLSX formats. It excludes manuscript files, figures, source code, executable workflows, LaTeX files, and documentation artifacts. China carbon records are provided as evidence-graded diagnostic data, while Phoenix eGRID conversion is the verified regional carbon case.

Adult mammalian Müller glia (MG) cells typically undergo a gliotic response following retinal injury, limiting endogenous neuronal regeneration. Previous studies demonstrated that the potent and selective α7 nicotinic acetylcholine receptor (nAChR) agonist, PNU-282987, induces a neurogenic response in adult mammalian MG through signaling initiated in retinal pigment epithelial (RPE) cells. In the present study, we further investigate the cellular and transcriptomic responses underlying α7 nAChR-mediated MG reprogramming using primary mouse MG and RPE cell cultures. Primary MG cells from adult mice were co-cultured with RPE cells treated with either PNU-282987 or DMSO, and phenotypic changes associated with proliferation and progenitor formation were evaluated using immunocytochemistry. PNU-282987-treated primary MG cultures demonstrated a significant increase in Ki67-positive and Pax6-positive cells compared to DMSO-control primary MG cultures. To further characterize the responses, RNA sequencing was performed to characterize transcriptomic effects associated with α7 nAChR activation. Differential expression analyses identified several candidate regulators associated with glial plasticity, progenitor formation, and developmental signaling. These results provide insight into receptor-mediated responses that can enhance the neurogenic potential of central nervous system glia. Moreover, these studies are foundational for future experiments examining the precise mechanism of how PNU-282987 elicits changes in adult mammalian MG cells.

This study examines the utilization of 21st-century Information and Communication Technology (ICT) tools in the teaching and learning of Technology and Vocational Education courses in a Nigerian public university.

This dataset contains the data supporting a study of least-cost and low-carbon electricity supply for twelve mining and petroleum developments in Kenya and Malawi. The developments are oil, rare earths, gold, rutile–graphite, niobium–tantalum, uranium, ilmenite, fluorspar and coal projects with peak demand of 2–60 MW. The study compares five supply configurations at each site: diesel only; captive solar PV–battery–diesel hybrids; grid extension; grid with on-site solar PV; and grid with on-site solar PV and battery storage. Associated gas is an additional option at South Lokichar. The comparison uses an hourly techno-economic model and a 5,000-draw Monte Carlo uncertainty analysis, and the results are aggregated into four national energy-strategy pathways to 2032. The Excel workbook contains 1. README: an index of all sheets with sources. 2. Tables 1–23: every table in the manuscript. These cover: a -the review of literature and national strategies; b -mineral resources and power-system indicators; c - development cases and demand; d - cost assumptions, grid-connection calibration and supply designs; e - levelised costs, emissions, savings and electricity cost per unit of product; f - network connections, sensitivity and Monte Carlo results; g - financing instruments, regulatory instruments, strategic pathways and SDG 7 contributions. 3. Tables A1–A2: resource occurrence registers for Kenya and Malawi. 4. Tables B1–B12: profiles of the twelve developments. 5. Source data for Figs 4, 5, 7–14 and 16: installed capacity; peak demand; LCOE by site and option; LCOE cost components; cost and carbon per unit of product; national adequacy; hourly dispatch profiles; break-even spur lengths; grid-availability sweep; Monte Carlo probabilities; and strategic pathway indicators. 6. Model inputs: site data (energy, peak load, grid node, route length, voltage, PV capacity factor, annual output) and 35 techno-economic parameters with tested ranges. All costs are in 2026 US dollars (real) at a 10% weighted average cost of capital (WACC) Related publication Ochieng, F.X. Powering the Critical-Minerals Boom: An Energy Strategy for Least-Cost Captive Supply, Grid Integration and Decarbonisation of Mining in Kenya and Malawi. Energy Strategy Reviews (submitted, 2026).

De-identified derived data and analysis code for a reliability-audited synthesis of the multilingual DID case literature. Three independently developed large language models applied one frozen coding instrument to 232 full-text sources in 19 languages, yielding 358 analytic records spanning 1882 to 2026, audited by thirteen human coder units across 31 variables. The deposit contains the frozen consensus value for every record, the coding instrument, the source-level covariates and the full-text screening record, the inter-model and human-model reliability results, the registered descriptive and inferential results including all 851 primary and sensitivity rows, the frozen analysis registers, and the analysis code with the environment of the run of record. Source documents are not redistributed, because of copyright and the risk of reproducing identifiable clinical narratives.

This reproducibility package supports the study “SL-BB: A State-Lifetime-Aware Branch-and-Bound FPGA Architecture for High-Throughput Exact Permutation Flow Shop Scheduling.” It contains the source code for the three evaluated FPGA architectures Conventional B&B, Unpipelined SL-BB, and Pipelined SL-BB together with state-lifetime profiling outputs, cycle-accurate RTL transaction results, clean post-route utilization, timing and power reports, and PL-side ZedBoard validation artifacts. The package is organized to distinguish profiling, architectural comparison, physical implementation, and board-validation evidence. The corresponding development repository is maintained on GitHub under the project name SL-BB-PFSP-FPGA.

H1: For a specified target-year recorded risk outcome, the audit-reporting indicator has a positive association after conditioning on the machine-risk rank and measured firm characteristics. H2: The conditional log-odds association of AuditSignal with a recorded outcome becomes more positive as RiskPredRank increases. The complete 2014–2025 dataset was assembled from the CSMAR and Wind financial databases and announcements published on the China Securities Regulatory Commission (CSRC) website. It contains 38,964 unique firm–target-year observations, including 16,107 in the 2021–2024 main test. The analytic file contains 96 historical machine inputs, three event labels, and audit flags for the preceding fiscal year. We checked numeric completeness of the machine inputs, firm-year uniqueness, the union defining the composite outcome, and the arithmetic of each two-year change; binary fields stored as text were converted to numeric. The analysis uses this complete annual dataset for 2014–2025.