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Spatiotemporal Dynamics and Optimal Control of a Two-Stage Infection-Age Structured Epidemic Model with Nonlocal Diffusion, Chemotactic Avoidance, and Intermittent Control Strategies

This paper establishes a novel two-stage infection-age epidemic model incorporating nonlocal diffusion, chemotactic avoidance, and waning immunity to prove global stability of equilibria and develop a bilevel optimal control framework with intermittent strategies that, validated by Berlin data, demonstrates the superiority of spatially targeted interventions over uniform approaches.

Yuhao zhou2026-08-28

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Dense Truths, Sparse Estimators: Making Lasso Work for Dense-Signal Logistic Regression

This paper challenges the conventional preference for Ridge regression in dense-signal high-dimensional settings by demonstrating that Lasso's underperformance stems from suboptimal tuning rather than inherent flaws, and introduces a novel posterior-predictive penalty selector that enables Lasso to achieve predictive accuracy comparable to or exceeding Ridge regression while retaining its crucial variable selection capabilities.

Jason Liao2026-08-28

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An Examination of the Performance of Variance Estimators in International Large-Scale Assessments

This Monte Carlo simulation study evaluates the performance of BRR, JK2, and Bootstrapping variance estimators in international large-scale assessments, finding that while JK2 offers superior precision for smooth statistics like means, Bootstrapping and BRR are more accurate for non-smooth statistics, and that Fay adjustments and non-response handling significantly influence estimator reliability.

Umut Atasever, Sabine Meinck, Diego Cortes2026-08-27

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Inverse Target Trial Emulation: A Method to Simulate Realistic Observational Data

This paper introduces Inverse Target Trial Emulation (ITTE), a Bayesian framework that generates realistic observational datasets from randomized controlled trial data by systematically inducing confounding and time-related biases, thereby enabling the rigorous evaluation and comparison of analytical strategies for adjusting these biases in non-randomized health research.

Luca Benetti, Gianluca Baio, Anna Heath2026-08-27

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What does Retraction Watch's "computer-generated content" reason capture? A metadata analysis of 9,161 retractions

This metadata analysis of 9,161 retractions reveals that the "computer-generated content" reason in Retraction Watch is heavily concentrated in a single publisher and strongly associated with paper mills, but these patterns reflect co-coding practices rather than providing definitive evidence about the actual presence of generative AI in the retracted articles.

Jonas Mandalunes2026-08-27

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AttribRank: An Open and Reproducible Framework for Diagnosing Attribution Sensitivity in Author-Level Research Assessment

This study introduces AttribRank, an open-source Python framework that quantifies how author-level research rankings shift based on evaluation choices like collaboration rules and indicator types, revealing that these variations are structured by disciplinary fields rather than random noise.

A Rong, Zhonglin Zhao, Hongju Zhao2026-08-27

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Beyond Citation Counts: A novel framework for Research Translation Analysis

This paper introduces the Research Translation Analysis (RTA) framework, a novel method that integrates guideline mapping with qualitative citation-content analysis to move beyond simple citation counts and systematically evaluate how biomedical research is actually interpreted, utilized, or misrepresented in clinical practice and subsequent studies.

Harriet Mactier, Kam Cheong Wong, Emily Saurman2026-08-27

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A flexible and robust approach to univariate Gaussian splitting using parameterized Gaussian mixtures

This paper presents a robust and straightforward algorithm that approximates a univariate Gaussian distribution with a mixture of smaller-variance homoscedastic Gaussians by minimizing the squared Euclidean norm, while also discussing its extension to non-Gaussian distributions.

Dmitry Mikhin, Athena Xiourouppa2026-08-27✓ Author reviewed ⓘ

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Development and Initial Psychometric Properties of a Household Energy Insecurity Scale in the US

This study develops and validates a comprehensive 25-item, six-dimensional Household Energy Insecurity (HEI) scale using data from 1,350 US respondents, providing a robust tool for identifying vulnerable households and guiding equitable energy policies.

Farah Mneimneh, Cristina Poleacovschi2026-08-27

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A New Generated Class: Theory and Inference with Application to Daily COVID-19 Cases in Region Aseer, Saudi Arabia

This paper introduces a flexible trigonometric-generated family of distributions, specifically a parsimonious NewWeibull special case, which is mathematically validated through theoretical derivations and Monte Carlo simulations to effectively model heterogeneous outbreak data, outperforming existing models when applied to daily COVID-19 cases in Saudi Arabia's Aseer Region.

Muhammad Arshad, Ali Algarni2026-08-27

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