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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...

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 ...

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...

Materias / palabras clave: OpenAIRE; Research Graph; publications; Medicine; Public aspects of medicine; RA1-1270; Revista Española de Salud Pública v.90 2016; instname:Instituto de Salud Carlos III (ISCIII); Revista Española de Salud Pública,...

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...

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...

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...

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...

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...

Abstract Smart Contract (SC) vulnerabilities are programming errors or design flaws that can lead to financial loss or functional failure, making accurate detection essential. Although Machine Learning (ML) is widely app...

Online advertising platforms commonly employ Cost-Per-Click (CPC) and Cost-Per-Thousand-Impressions (CPM) models to determine advertiser fees based on user engagement and exposure metrics. While these pricing arrangement...

Abstract Background The European Reference Network for rare Inherited and Congenital Anomalies (ERNICA) aims to improve care for patients with rare and complex digestive and gastrointestinal diseases across Europe throug...

3D printing is transforming soft robotics by enabling complex geometries, rapid iteration, and cofabrication of structure, actuation, and sensing. Central to this progress are functional materials that provide stretchabl...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...