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Real-time routing on large-scale road networks remains a critical challenge for intelligent transportation systems, particularly under high query loads and increasing graph sizes. While classical shortest path algorithms...

The rapid expansion of whole-genome sequencing (WGS) has highlighted the important contribution of noncoding variants to human disease, yet their pathogenic mechanisms remain difficult to resolve. Traditional statistical...

"A rapid and sensitive analytical method for the trace determination of aflatoxin M1 in domestic waters was developed using chitosan as a sorbent and HPLC with fluorescence detection (HPLC-FLD). Computational simulations...

Gradient-based optimization offers significant efficiency advantages for wind turbine blade design, but its application has often been limited by the cost and accuracy of finite-difference derivative calculations, especi...

Abstract Secure multiparty computation enables collaborative computations across multiple users while preserving individual privacy, which has a wide range of applications in finance, machine learning and healthcare. Sec...

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cholinergic dysfunction, making acetylcholinesterase (AChE) a key therapeutic target. Although Garcinia kola has been widely reported ...

With the constant advancement of the smart grid, zero-day attack processes in Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) networks are also continually evolving. This study...

Salinity distribution is a critical determinant in the management of water resources and the protection of ecological integrity in coastal regions, drawing particular concerns in the context of increasing saltwater intru...

Abstract A Schiff base ligand L 1 was synthesized via the condensation reaction between from 2-hydroxy-1-naphthaldehyde and 4-methoxyaniline. This Schiff base was employed for the preparation of metal complexes of type [...

Zernike moments are well-suited for unmanned aerial vehicle scene matching because of their rotation invariance and robustness to noise. However, their high computational complexity poses challenges for meeting the real-...

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...

Introduction. The performance reliability of electric vehicles (EVs) is an important factor in evaluating their suitability for widespread adoption. The reliability and lifespan of an EV depend on several critical factor...

In recent years, generative artificial intelligence represented by large language models (LLMs) and multimodal large language models (MLLMs) has achieved remarkable progress. These ultra-large-scale and complex models im...

Abstract Alkaline water electrolysis represents a promising pathway for green hydrogen production, yet comprehensive multi-physics simulation remains computationally prohibitive for practical design optimization. This st...

Abstract This study presents a computational investigation into the aerodynamic and thermal performance enhancement of a solar chimney power plant (SCPP) through the integration of wavy geometries along the collector roo...

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 ...

Nonlinear response conception in rotating machinery, particularly in systems with squeeze film dampers (SFDs), pose significant challenges for established time-domain numerical methods due to bifurcations and critical po...

IntroductionThis article investigates the linguistic and computational challenges of detecting antisemitism in digital communication, integrating discourse-analytical and artificial intelligence (AI) perspectives. It con...

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 Machine learning surrogate models of Kohn-Sham Density Functional Theory Hamiltonians provide a powerful tool for accelerating the prediction of electronic properties of materials, such as electronic band struct...

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...

Abstract Corollary discharge denotes internal signals about the expected sensory consequences of one’s own actions, leading to reduced sensory responses to self-generated stimulation. To investigate the underlying neur...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

Context. Astronomical environments are governed by a complex interplay of physical processes, including gravitational dynamics, radiative transfer, stellar evolution, chemistry, and hydrodynamics. These processes span a ...