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Abstract Marine habitat maps are essential tools for marine spatial planning, providing information for decision‐making in conservation and resource management. Accurate classification of benthic habitats supports thei...

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...

Recently, in the image super-resolution (SR) domain, Transformers have outperformed Convolution Neural Networks (CNNs) with reduced computational complexity and parameters by modeling long-range dependencies input-depend...

This research contributes to ongoing, multi-faceted, and much-needed discussions about food systems change amidst rising rates of food insecurity in Canada (and globally). It does so by providing a comparative content an...

Abstract Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is con...

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,...

Background and aims Meat-borne Staphylococcus aureus (S. aureus) remains a leading global foodborne pathogen harbouring novel enterotoxin genes (NEGs) encoding superantigenic toxins with conditionally enhanced pathogenic...

ABSTRACT Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

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...

The rapid growth and increasing complexity of Internet of Things (IoT) networks require efficient real-time monitoring and anomaly detection mechanisms. Traditional machine learning approaches often struggle to handle th...

Abstract Neural circuits construct internal ‘world-models’ to guide behavior. The predictive processing framework posits that neural activity signaling sensory predictions and concurrently computing prediction-errors...

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,...

Abstract Seafloor networks detect earthquakes and tsunamis more quickly than those on the mainland in the subduction zones. N-net was constructed in the western portion of the Nankai Trough subduction zone to fill the ga...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Tensor network formalisms have emerged as powerful tools for simulating quantum state evolution. While widely applied in the study of optical quantum circuits, such as boson sampling, existing tensor network approaches f...

The ripening stage of a fruit is a crucial determinant of its quality. Traditional assessment methods for fruit ripeness are often subjective, error-prone, and time-consuming. Therefore, numerous attempts are being made ...

Abstract Background Prolificacy is a crucial economic trait in goat production, yet its underlying molecular mechanisms remain incompletely understood due to its polygenic nature. While previous studies have identified s...

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 Integrating healthcare systems with intelligent transportation networks represents a critical frontier in modern urban infrastructure, where efficient resource allocation and timely service delivery can signific...

Abstract Post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID, present a complex array of persistent symptoms that remain poorly understood. Identifying the central symptoms and their interrelationships is c...

Convolutional neural networks (CNNs) and visual Transformers have become the dominant approaches for hyperspectral image (HSI) classification due to their powerful feature representation capabilities. However, CNNs are l...

Ethylene is an important raw material, and ethylene cracking furnaces (ECFs) are the core equipment sources of ethylene plants. The quality of the operation of the ECF directly affects the overall economic benefits of th...

Abstract The current English grammar error correction model still has low accuracy when dealing with complex sentences and long sentence dependencies. Therefore, this study proposes a Sequence-to-Sequence (Seq2Seq) model...