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Transformer-based human skeleton action recognition has been developed for years. However, the complexity and high parameter count demands of these models hinder their practical applications, especially in resource-constrained environments. In this work, we propose FreqMixForemrV2, which was built upon the Frequency-aware Mixed Transformer (FreqMixFormer) for identifying subtle and discriminative actions with pioneered frequency-domain analysis. We design a lightweight architecture that maintains robust performance while significantly reducing the model complexity. This is achieved through a redesigned frequency operator that optimizes high-frequency and low-frequency parameter adjustments, and a simplified frequency-aware attention module. These improvements result in a substantial reduction in model parameters, enabling efficient deployment with only a minimal sacrifice in accuracy. Comprehensive evaluations of standard datasets (NTU RGB+D, NTU RGB+D 120, and NW-UCLA datasets) demonstrate that the proposed model achieves a superior balance between efficiency and accuracy, outperforming state-of-the-art methods with only 60% of the parameters. 

Abstract Metallic materials under high stress often exhibit deformation localization, manifesting as slip banding. Over seven decades ago, Frank and Read introduced the well-known model of dislocation multiplication at a source, explaining slip band formation. Here, we reveal two distinct types of slip bands (confined and extended) in compressed CrCoNi alloys through multi-scale testing and modeling from microscopic to atomic scales. The confined slip band, characterized by a thin glide zone, arises from the conventional process of repetitive full dislocation emissions at Frank–Read source. Contrary to the classical model, the extended band stems from slip-induced deactivation of dislocation sources, followed by consequent generation of new sources on adjacent planes, leading to rapid band thickening. Our findings provide insights into atomic-scale collective dislocation motion and microscopic deformation instability in advanced structural materials. 

This communication measures the inter-helical angle of the 10-23 DNAzyme-substrate complex by atomic force microscopy (AFM). specificity. Herein, we have devised a strategy to assemble the DNAzyme-substrate complex into a periodic DNA 2D array, which allows reliable study of the conformation of the 10-23 DNAzyme by AFM imaging and fast Fourier transform (FFT). Specifically, the angle between the two flanking helical domains of the catalytic core has been determined via the repeating distance of 2D array. We expect that the same strategy can generally be applicable for studying other nucleic acid structures. 

Deterministic assembly of metallic nanoparticles ( e.g. gold nanoparticles) into prescribed configurations has promising applications in many fields such as biosensing and drug delivery. DNA-directed bottom-up assembly has demonstrated unparalleled capability to precisely organize metallic nanoparticles into assemblies of designer configurations. However, the fabrication of assemblies comprising delicate nanoparticle arrangements, especially across large dimensions ( e.g. micron size), has remained challenging. In this report, we have designed DNA origami hexagon tiles that are capable of assembling into higher-order networks of honeycomb arrays or tubes with dimensions up to several microns. The versatile addressability of the unit tile enables precise and periodic positioning of nanoparticles onto these higher-order DNA origami frame structures. Overall, we have constructed a series of 9 gold nanoparticle architectures with programmable configurations ranging from nanometer-sized clusters to micrometer-sized lattices. We believe these architectures shall hold great application potential in numerous biomedical fields.