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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...

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...

The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

"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...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

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 ...

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 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...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Abstract Autonomous driving systems critically rely on the precise detection of distant, small traffic signs to ensure safe and efficient navigation. Nonetheless, existing detection algorithms are confronted with several...

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...

Abstract Advances in AI are transforming decision making teams. A fundamental open question is whether AI agents elicit social conformity effects comparable to human peers. If so, a critical challenge is determining whet...

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...

Abstract Facial Expression Recognition (FER) demonstrates significant value in practical scenarios such as intelligent human–computer interaction. However, conventional FER methods often struggle to balance performance...