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Mathematical datasets, statistical benchmarks, probability, optimization, operations research
2,446 datasets
Jun Qiao's statistical test results from a study on automated urban road crack detection. The dataset, last updated in April 2026, compares the performance of a novel U-net and ResNeXt fusion method against other detection techniques. It likely contains metrics evaluating detection accuracy, memory efficiency, and classification performance for different crack types.
A 2026 study by Swapan Samanta proposes an operational definition of liberation as perpetual self-transcendence. The framework employs mathematical formalization, comparative analysis across six traditions, and empirically testable criteria like the Liberation Coefficient (LC) and Self-Transcendence Rate (STR). It is shared as a 34.8 KB DOCX file under a CC-BY-4.0 license.
A 20.6 KB Excel file contains data for a probabilistic modeling framework assessing chemical risk to aquatic ecosystems at the watershed level across Europe. The dataset was created by Sophie Mentzel for the ENCORE project and last updated on May 4, 2026. It integrates prior exposure probabilities from process-based simulations with monitoring evidence from the Waterbase Water Quality dataset for Bayesian updating.
Three tobacco types—flue-cured, sun-cured yellow, and sun-cured red—from multiple producing regions were analyzed to identify components affecting sensory quality. Palmitic acid and chlorogenic acid were positively correlated with overall sensory scores, while citric acid and several furan and nitrogen-containing components were linked to negative qualities like irritancy and bitterness. The dataset, last updated May 4, 2026, was created by Tong Wang and shared under a CC-BY-4.0 license.
A probabilistic modeling framework developed for assessing chemical risk to aquatic ecosystems at the watershed level across Europe. The framework synthesizes multiple information sources, including process-based simulation data and the pan-European Waterbase Water Quality monitoring dataset. A pilot study using a subset of pesticides in Belgium serves as a proof-of-concept.
A probabilistic modeling framework developed within the ENCORE project assesses chemical risk to aquatic ecosystems at the European watershed level. The 4.1 MB file contains a pilot study using a subset of pesticides in Belgium to test a Bayesian network that integrates process-based simulation data with monitoring data from the Waterbase Water Quality dataset. This proof-of-concept, authored by Sophie Mentzel and last updated in May 2026, aims to identify high-risk chemicals by accounting for spatial and temporal exposure patterns.
Sophie Mentzel's supplementary file from the ENCORE project details a probabilistic framework for assessing chemical risk to aquatic ecosystems at the European watershed level. The 1.4 MB PDF, last updated in May 2026, describes a Bayesian network model that integrates process-based simulation data with monitoring data from the European Environment Agency's Waterbase Water Quality dataset. A pilot study focusing on a subset of pesticides in Belgium serves as a proof-of-concept for this risk modeling approach.
Frederick Currell's MIRaCLE toolkit data and code, published on figshare in April 2026. The dataset includes results and code for simulating the spatio-temporal evolution of radiolytic species like hydrated electrons and hydroxyl radicals. It supports a hybrid continuum/Monte Carlo method designed for fast calculation of time-dependent G-values across long timescales and extreme dose rates.
12.6 KB of statistical significance test results for RL-DE and six comparison algorithms on the CEC2022 benchmark suite. The table, authored by Yang Cao and last updated in May 2026, presents Friedman test average ranks and Wilcoxon signed-rank test pairwise p-values for 12 composite functions at two dimensions.
Mauricio A. Correa-Ochoa published a 19.5 MB RAR archive containing R and Python scripts alongside processed datasets. The materials are intended to replicate the Principal Component Analysis, HYSPLIT trajectory modeling, and statistical figures from an associated study. The archive was last updated on May 27, 2026, and is shared under a CC-BY-4.0 license.
Bethany Lyne's dataset summarizes definitions and findings from multiple studies on schistosome infection and alcohol use. The data includes study population details, exclusion criteria, participant counts, statistical methods, and observed associations. It was last updated on May 27, 2026, and is shared under a CC-BY-4.0 license.
Fitzroy River Basin, Queensland, Australia, sediment sources have been identified and quantified using an integrated geochemical and modelling approach. The dataset likely contains geochemical composition data and Bayesian model outputs revealing changes in catchment sediment sources over the Holocene. It was published by Geoscience Australia Data and last updated on 2026-05-14.
Nemotron-Math-Proofs-v2 contains 82,737 samples of mathematical proof-generation, verification, and meta-verification traces. The problems are sourced from the Art of Problem Solving subset of the nvidia/Nemotron-Math-Proofs-v1 dataset. Proofs were generated using DeepSeek-V4-Pro on Max inference mode.
Jianrong Cai published model parameters for a Dynamic pricing-based Stochastic Demand-Response Optimization (DSDRO) method on figshare in April 2026. The dataset supports a framework that uses spatiotemporal bike-sharing demand patterns to optimize pricing and resource allocation. Numerical experiments based on real operational data validated the approach.
A 5.5 KB Excel file summarizing 10 independent runs of a bike-sharing optimization algorithm. The dataset, created by Jianrong Cai and uploaded to figshare in April 2026, likely contains performance metrics from a proposed Dynamic pricing-based Stochastic Demand-Response Optimization (DSDRO) method.
A dataset containing results from numerical experiments validating a Dynamic pricing-based Stochastic Demand-Response Optimization (DSDRO) method for bike-sharing systems. The dataset likely includes performance metrics from real operational data, comparing revenue and profit improvements against baseline algorithms. It was authored by Jianrong Cai and last updated on April 16, 2026.
Jianrong Cai's dataset presents results from a Dynamic pricing-based Stochastic Demand-Response Optimization (DSDRO) method for bike-sharing systems. The dataset likely contains numerical experiment results validating the DSDRO framework, which uses spatiotemporal demand patterns and an improved Particle Swarm Optimization algorithm. The data was uploaded to figshare on 2026-04-16.
Data (Supplementary Information) contains performance metrics from a study on velocity-based resistance training with 15 college-level female basketball players. The dataset includes pre- and post-intervention test results for one-repetition maximum, squat jump, countermovement jump, and 20-meter sprint performance. Hiroki Kambara authored the study, with data last updated on 2026-04-13.
100 randomization iterations were performed for each model–predictor–target combination to assess model robustness. The dataset contains evaluation metrics like R², Q², RMSE, MAE, and p-values computed on randomized target variables. Authored by Mythili V and last updated on 2026-05-21, it is hosted on figshare under a CC-BY-4.0 license.
A dataset and analysis script quantifying escape response kinematics and timing in Spotted Ratfish (Hydrolagus colliei). The data, created by Vincent Mélançon and last updated in April 2026, likely contains measurements of turning rates and response latencies elicited by a mechano-acoustic stimulus. The findings suggest ratfish performance is intermediate between other chondrichthyans and teleosts.