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We aim to determine the average efficiency levels of the Argentine Labor Courts and their individual behavior with respect to the average. We also seek to establish the determinants of the relative efficiency levels of t...

Three-dimensional electron diffraction (3D ED) has become increasingly popular over the last two decades, challenging the limits of established single-crystal X-ray diffraction experiments. In particular, continuous-rota...

BackgroundDigital tools are reshaping public health education and training, yet evidence on whether large language models (LLMs) can generate specialist ophthalmic teaching materials remains limited. High myopia (HM), a ...

Abstract Background No mandatory policies currently exist to address food environments in Belgium. Monitoring commitments and practices by food industry actors is essential for increasing accountability. The aim of this ...

Modern edge–cloud deployments integrate devices, edge servers, private networks, and cloud platforms into heterogeneous, multi-layer systems. Each layer exposes distinct metrics, measurement granularities, and tim...

In the face of socioeconomic challenges, this paper develops and empirically demonstrates the Gondauri Index (GI) as a reproducible, diagnostics-first composite framework for benchmarking macro-financial resilience acros...

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffi...

Sarfaraz K Niazi Department of Pharmaceutical Sciences, University of Illinois, Chicago, IL, 60612, USACorrespondence: Sarfaraz K Niazi, Email sniazi3@uic.eduAbstract: Quantum technologies—quantum computing, quantum se...

The article is devoted to the issue of economic justification for management decisions on tax planning at Ukrainian enterprises. The research objective is to elaborate an approach to comparative analysis of tax alternati...

IntroductionLarge language models (LLMs) may support clinical reasoning, yet real-world outpatient studies integrating structured clinical data with chest radiographs (CXRs) remain limited. We compared three LLMs for pul...

The systematic comparison of 3D-ED methods in terms of data quality presented by Schmitt et al. [IUCrJ (2026), 13, 291–303] is discussed.

Abstract Objectives To develop and evaluate a deep learning model for diagnosing untreated rheumatoid arthritis (RA) using digital camera images of bilateral dorsal hands, benchmarking its performance against the widely-...

Abstract Graph Neural Networks (GNNs) are powerful tools for predicting chemical shifts in Nuclear Magnetic Resonance (NMR) spectroscopy. In this paper, we improve the state-of-the-art mean absolute error (MAE) on the Il...

Abstract Biochar yield prediction plays a critical role in optimizing pyrolysis processes and advancing sustainable biomass utilization. This study introduces a hybrid machine learning framework that integrates Decision ...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

Abstract This paper presents the optimization performance of non-uniform linear antenna array with optimized inter-element spacing and excitation amplitude using Particle Swarm Optimization (PSO). The aim of the proposed...

Introduction: The advancement of AI-assisted oral disease diagnosis critically relies on the availability of annotated, high-quality datasets and resilient deep learning architectures. Nevertheless, progress in this doma...

Abstract Objective Acute heart failure (AHF) is a common but underrecognized cause of dyspnea. Chest computed tomography (CT) can accurately assess pulmonary congestion, but radiologist reporting capacity may limit clini...

Abstract Risk of bias assessment is a crucial step in evidence synthesis. The traditionally adopted tool, however, is complex, resource-intensive, and unreliable. While prior investigations have focused on whether Large ...

This paper proposes an innovative automated multiphysics Microelectromechanical systems (MEMS) co-optimization platform integrating the embedded reduced-order modeling offered by Coventor MEMS+ with MATLAB’s numerical ...

Abstract The application of Bayesian statistics in pivotal clinical trials has gained increasing attention, particularly for underpowered confirmatory trials such as those in pediatric and rare disease populations. Bayes...

Abstract Many codecs with different error-correction approaches have been implemented for DNA data storage to date. However, no studies have systematically benchmarked codec implementations to establish their current sta...

The formation of household savings is a key prerequisite for sustainable economic development and investment recovery in Ukraine. This article explores the role of credit unions as specific non-banking financial institut...