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ABSTRACT Bio‐inspired optimisation methods have been widely applied to complex real‐world problems, particularly in low‐carbon power and energy systems, where optimisation tasks often involve high‐dimensional, co...

ABSTRACT This paper presents an event‐triggered pinning observer‐based control of unknown large‐scale interconnected systems under false data injection attacks using distributed noisy data without any system identi...

ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive me...

Abstract Intertidal macrobenthos are vital bioindicators of coastal ecosystem health due to their ecological roles, limited mobility, and sensitivity to environmental disturbances. However, traditional field‐based moni...

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 and Aims While Masson's Trichrome is widely used for collagen visualization, its qualitative nature limits reproducibility and statistical comparison. A methodological gap persists in the quantitative...

Single-photon emitters (SPEs) hold the key to many quantum technologies including quantum computing. In particular, developing a scalable array of identical SPEs can play an important role in preparing single photons –...

ABSTRACT Deep learning profoundly impacts various areas, such as face recognition and language translation. Owing to the increasingly high computational costs of training neural architectures, it is intractable to manual...

Modeling data that falls within the [0,1] domain is a huge task in most scientific disciplines. This is because most classical distributions do not address the issues of complex data shapes as well as managing the dynami...