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252 papers

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Bayesian Multi-Modal Latent-State Inference for n=4 Deep-Space Crew Analogues: A Reproducible Methodology Pipeline for the NASA Artemis II Human Research Data Challenge

This paper presents a reproducible Bayesian multi-modal latent-state inference pipeline that successfully identifies a significant spaceflight signature in a small n=4 deep-space analogue dataset by fusing seven high-dimensional modalities, demonstrating that integrated multi-modal analysis outperforms individual biomarker detection in the p >> n regime.

Maria Jesús Puerta angulo2026-07-06
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Assessing Methodological Distortions in the Clarivate Highly Cited Researchers List: International Comparisons and a Reform Framework

This paper critiques the methodological limitations of the Clarivate Highly Cited Researchers list by demonstrating how factors like whole counting and citation disparities distort international comparisons, and proposes a reform framework to address these biases through fractional counting, field normalization, and improved author disambiguation.

F. PACHECO-TORGAL2026-07-06
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Functional Autoregressive Modeling with Exogenous Variables for Day-Ahead Electricity Price Forecasting in the Croatian Electricity Market

This paper demonstrates that functional autoregressive models with exogenous variables (FARX(p)) significantly outperform traditional statistical and machine learning methods in forecasting day-ahead electricity prices in the Croatian market by effectively capturing high-frequency volatility, temporal dependencies, and demand-driven effects.

Laila A. AL-Essa, Faheem Jan, Mehwish Tahir, Muhammad Wisal Khan2026-07-03
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Interpretable Forecasting of FIFA World Cup Tournament Progression Using Penalized Logistic Regression and Bootstrap Stability Selection

This study presents an interpretable forecasting framework using penalized logistic regression and bootstrap stability selection on historical team data to predict FIFA World Cup progression, identifying key predictors like market value and FIFA ranking while forecasting Argentina, France, Spain, England, Germany, and the Netherlands as top contenders for the 2026 tournament.

Francis Okyere, Francis Mawutor Amuyao, Sherif Mohammed2026-07-03✓ Author reviewed ⓘ
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One Truncated Likelihood Expansion: Estimation, Testing, and Classification as a Single Captured-Fraction Functional

This paper unifies parameter estimation, hypothesis testing, and signal classification by demonstrating that all three tasks can be evaluated through a single functional—the captured fraction of a log-likelihood expansion in a fixed basis—which reveals their shared efficiency, termination conditions, and optimality across diverse distributions, including those where traditional orthogonal bases fail.

Serhii Zabolotnii2026-07-03
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Integrated Yield and Demand Forecasting for Air Cargo in MEASA Emerging Markets: A Multi-Method Statistical Framework

This paper presents an integrated statistical framework combining OLS, SUR, ARIMAX, and Random Forest models within a Power BI environment to enhance air cargo yield and demand forecasting in MEASA emerging markets by addressing geopolitical disruptions, non-linear load factor interactions, and commodity mix dynamics while mathematically bridging academic modeling with commercial reporting metrics.

Shaista Kanwal2026-07-02
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Stability and Interrelationships of Classical Test Theory Indicators Under Varying Difficulty Conditions: A Monte Carlo Simulation Study

This Monte Carlo simulation study demonstrates that under structural independence, Classical Test Theory item-level indicators exhibit mathematically determined relationships—such as the perfect functional equivalence of binary item statistics and the stability of discrimination-total correlations across difficulty levels—while test-level reliability remains low due to the absence of inter-item covariance.

Ammar Yasser2026-07-02
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Logistics-driven proactive drone epidemic intervention model

This paper proposes a logistics-driven proactive epidemic intervention model that integrates an RM-SIR mathematical framework with an intelligent drone delivery system to enable precise, rural-prioritized resource scheduling, effectively transforming logistics from a passive transport function into an active epidemic control tool that significantly reduces outbreak peaks and duration while maintaining high cost-effectiveness.

Jiaen Zheng2026-07-02