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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...

Given a positive integer k, the {k}-packing function problem ({k}PF) is to find in a given graph G, a function f of maximum weight that assigns a non-negative integer to the vertices of G in such a way that the sum of f(...

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...

The menstrual cycle affects many aspects of female physiology, from the immune system to behavioral and emotional regulation. It is unclear however if these physiological changes are reflected in everyday, naturalistic l...

An existing hybrid MPI-OpenMP scheme is augmented with a CUDA-based fine grain parallelization approach for multidimensional distributed Fourier transforms, in a well-characterized pseudospectral fluid turbulence code. B...

This work studies the performance of two open-source CFD codes, OpenFOAM and MFiX, to address bubbling fluidized bed system at different temperature and heat transfer conditions. Both codes are used to predict two parame...

Abstract Computational efficiency and accuracy always conflict with each other in molecular dynamics (MD) simulations. How to enhance the computational efficiency and keep accuracy at the same time is concerned by each c...

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...

"Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and pro...

Tearing of brittle thin elastic sheets, possibly adhered to a substrate, involves a rich interplay between nonlinear elasticity, geometry, adhesion, and fracture mechanics. In addition to its intrinsic and practical inte...

Semiconductor lasers (SLs) that are subject to delayed optical feedback and external optical injection have been demonstrated to perform information processing using the photonic reservoir computing paradigm. Optical inj...

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...