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Abstract In order to address health monitoring issues on offshore wind turbines, while taking into account engineering know-how and constraints, we propose a robust model identification procedure based on reliability of ...

Designing floating wind turbine systems requires integrated load assessments (ILA) using fully coupled hydro-servo-aero-elastic models. In most cases, floater hydrodynamics are represented using potential-flow models for...

We reconstruct the late-time expansion history of the Universe in a fully model-independent manner. By combining observations from cosmic chronometers (CCs), the Dark Energy Spectroscopic Instrument (DESI) baryon acousti...

Reconstructing the early spatiotemporal dynamics of emerging infectious diseases (EIDs) is essential for effective public health response but remains difficult due to reporting delays, heterogeneous surveillance systems,...

Calibration of low-cost air quality sensors (LCSs) for total volatile organic compound (TVOC) and benzene, toluene, ethylbenzene, and xylenes (BTEX) quantification remains challenging due to the sensors' cross-sensitivit...

The configuration of the Northern Hemisphere ice sheets during the Last and Penultimate Glacial Maxima (LGM; PGM) influenced millennial-scale climate changes, as well as solid Earth and sea level changes that occurred du...

BackgroundEarly detection of diabetic retinopathy (DR) remains challenging in primary care, where access to ophthalmic screening is limited. We developed and validated a prediction model using routinely collected health ...

BackgroundTo explore the changes in various laboratory parameters in children with Kawasaki disease, analyze their correlations with complete and incomplete Kawasaki disease as well as coronary artery lesions and non-cor...

Abstract Background This study aims to explore spatial heterogeneity within tumors, establish and validate an interpretable machine learning model combining habitat radiomics and deep learning, and investigate its predic...

This study presents a comparative analysis of the effectiveness of various regression models for estimating forest stand phytomass stocks in spruce forests developed on Al-Fe-humic podzols at the northern tree line in th...

Brain–computer interfaces (BCIs) based on motor imagery (MI) provide a transformative direct communication pathway for patients with severe motor disabilities. However, the high inter-subject variability and non-statio...

Abstract Background Delayed ambulation recovery following major abdominal surgery presents a significant prognostic challenge, contributes to increased morbidity, mortality, and prolonged hospital stay. Despite recommend...

BackgroundIntracranial infection (ICI) is a serious complication following spontaneous intracerebral hemorrhage (ICH) and is associated with prolonged intensive care, increased morbidity, and poor functional outcomes. Ea...

Abstract Background Patients with AIDS Suffering from sepsis secondary to pulmonary infections admitted to intensive care units (ICUs) carry a high burden of morbidity and mortality. Therefore, rapid identification and t...

Abstract Background Neonatal seizures are sudden, abnormal brain activities that occur during the neonatal period, are the most common neurological emergencies in newborns, and are associated with high morbidity and mort...

Abstract Background With the widespread adoption of percutaneous coronary intervention (PCI), patients experiencing acute myocardial infarction (AMI) complicated by ventricular arrhythmia (VA) continue to encounter a sig...

BackgroundAdhesive intestinal obstruction (AIO) is a recognized complication following laparoscopic surgery for acute appendicitis (AA), although its overall incidence remains relatively low. This study aimed to develop ...

Abstract Background Surgical site infections (SSIs) continue to exert a substantial burden on healthcare systems, particularly in resource-limited settings where they contribute to prolonged hospitalizations, escalated c...

To address the short comings of the Lee-Tarver ignition and growth reaction rate equation, which comprises numerous parameters (15) and is difficult to calibrate, semi-periodic trigonometric functions were introduced to ...

BackgroundProlonged hospitalization for pyogenic liver abscess (PLA) burdens patients and health systems. We examined whether admission high-density lipoprotein cholesterol (HDL-C) predicts length of stay (LOS) and wheth...

Accurate seed-yield prediction is essential for optimizing nitrogen (N) management in buffalograss seed production. However, current UAV-based approaches often rely directly on vegetation indices (VIs), which provide lim...

Abstract Background Biomarkers are widely used in oncology research to study disease progression and predict survival outcomes. Pooling biomarker data across studies can improve precision, but pooled analyses are often a...

ObjectiveTo evaluate a novel multichannel deep learning (DL) model using contrast-enhanced ultrasound (CEUS) data with multiple regions of interest (ROIs) and time-intensity curve (TIC)-derived key frames for predicting ...

Background Large language models (LLMs) have demonstrated promising capabilities in medical diagnostic reasoning, yet their performance in specialized clinical domains such as rheumatology remains incompletely characteri...