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Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy in which immune dysregulation and metabolic remodeling are common features. Laminin subunit alpha 3 (LAMA3), a component of lamini...

Abstract Chronic wounds represent a longstanding clinical problem due to impaired angiogenesis due to insufficient activation of vascular endothelial growth factor receptor 2 (VEGFR2). In this investigation, we used comp...

Abstract Accurate monitoring and prediction of Chlorophyll-a (Chl-a) concentrations are critical for protecting desalination systems from algal blooms. This study presents an advanced framework employing the Graph Neural...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Biotic and abiotic stresses reduce crop yields, yet existing image‑based diagnostic models are often crop‑specific, computationally intensive, and poorly interpretable. This study present: (i) a multi-crop diagnostic...

Abstract Nanofluids have emerged as promising heat transfer media due to their superior thermal performance associated to conventional fluids, yet their behavior under mutual impacts of radiation, heat source/sink, and m...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

Abstract Internet of Things (IoT) is increasingly realized through large scale deployments of heterogeneous devices and gateways operating under strict energy budgets and interference limited links, which motivates relia...

Abstract Human social behaviors involve complex interactions between individuals, and understanding how interbrain neural activity reflects and predicts these interactions is critical for advancing social cognitive neuro...

Abstract Quantum Machine Learning (QML) is emerging as a promising technology for tackling complex computational challenges, although its practical implementation faces significant obstacles owed to the inherent noise in...

Abstract The conversion of solar radiation into thermal energy has gained increasing attention due to the growing demand for renewable sources of heat and electricity. Nanofluids, owing to their enhanced heat transfer ca...

Abstract This paper presents an intelligent coordinated control framework for a hybrid standalone microgrid integrating solar photovoltaic, wind, and battery energy storage systems. The proposed Radial Basis Function Neu...

Abstract Background Reliable identification of protein‑protein interactions (PPIs) is crucial for deciphering cellular functional networks. Current research models still face limitations in aligning heterogeneous featu...

IntroductionLiver diseases continue to impose a major global health burden, and therapeutic progress is constrained by the limited availability of validated small-molecule modulators. TEAD4, a central Hippo-YAP effector,...

Abstract Collaborative filtering and neural recommendation models have advanced substantially over the past decade, yet they frequently struggle to capture the fine-grained structure of user preferences and the rich, mul...

Abstract Background N6-methyladenosine ( $$m^{6}A$$ ) plays a crucial role in enriching RNA functional and genetic information. While deep learning has advanced $$m^{6}A$$ site identification, current state-of-the-art me...

Abstract Long-range dependency processing is the core challenge of sequence modeling, and traditional sequence modeling algorithms suffer from information decay and low parallel computing efficiency in ultra long sequenc...

IntroductionAcute Lymphoblastic Leukemia (ALL) is a hematological malignancy, which is life-threatening and demands rapid and precise diagnosis to either enhance or worsen the survival chances. Traditional diagnostic met...

Aiming at the problem of power quality disturbance (PQD) classification, classification sub-models based on one-dimension CNN in the time domain (original signal), frequency domain (Fourier transform) and time-frequency ...

Pain after surgery is of major perioperative concern because it is associated with substantial complications, including chronic post-surgical pain (CPSP) development. The CPSP incidence is high, and its accurate predicti...

Abstract The growing deployment of grid-connected voltage source inverters (GC-VSIs) in the smart grids poses some significant issues that include harmonic distortion, grid impedance fluctuations, nonlinear loading, and ...

Accurate detection of pediatric fractures in radiographs remains challenging due to subtle visual cues and the high prevalence of false-positive detections produced by automated systems. To address this limitation, we pr...