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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...

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...

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 ...

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...

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 ...

Abstract We present MIMIC-III-Ext-PPG, a large-scale, quality-assessed photoplethysmography (PPG) dataset derived from the matched waveform subset of MIMIC-III. Our dataset provides 30-second PPG segments with annotation...