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Globally, monitoring productivity, occupational health, and safety of construction workers has long been a significant concern. To address this issue, there is an urgent need for efficient methods to continuously monitor construction sites and recognize workers' actions in a timely manner. Recently, advances in electronic technology and pose estimation algorithms have made it easier to obtain skeleton and joint trajectories of human bodies. Deep learning algorithms have emerged as robust and automated tools for extracting and processing 3D skeleton information on construction sites, proving effective for workforce action assessment. However, most previous studies on action recognition have primarily focused on single-stream data, which limited the network's ability to capture more comprehensive worker action features. Therefore, this research proposes a Spatial-Temporal Multi-Feature Network (STMF-Net) designed to utilize six 3D skeleton-based features to monitor and capture the movements of construction workers, thereby recognizing their actions. The experimental results demonstrate an accuracy of 79.36%. The significance of this work lies in its potential to enhance management models within the construction industry, ultimately improving workers' health and work efficiency. [ABSTRACT FROM AUTHOR]

The medial prefrontal cortex (mPFC) has been implicated in the pathophysiology of social impairments, including social fear. However, the precise subcortical partners that mediate mPFC dysfunction on social fear behaviour have not been identified. Using a social fear conditioning paradigm, we induced robust social fear in mice and found that the lateral habenula (LHb) neurons and LHb-projecting mPFC neurons are activated synchronously during social fear expression. Moreover, optogenetic inhibition of the mPFC–LHb projection significantly reduced social fear responses. Importantly, consistent with animal studies, we observed an elevated prefrontal–habenular functional connectivity in subclinical individuals with higher social anxiety characterized by heightened social fear. These results unravel a crucial role of the prefrontal–habenular circuitry in social fear regulation and suggest that this pathway could serve as a potential target for the treatment of social fear symptoms often observed in many psychiatric disorders. [ABSTRACT FROM AUTHOR]

Shape-programmable magnetoresponsive soft actuators (SMSAs) are highly desirable for diverse applications in soft robotics and minimally invasive medicine. Current methods face challenges in achieving programmable magnetoresponsive three-dimensional (3D) shapes with non-uniform and continuously adjustable curvatures, which are crucial for the highly effective locomotion of SMSAs. Here, we propose an approach that integrates bioinspired pore design with mechanically guided magnetization, enabling programmable magnetoresponsive complex shapes with non-uniform and continuously adjustable curvatures. Various magnetoresponsive developable and non-developable surfaces, along with biomimetic 3D curved shapes, were prepared. The prepared SMSAs exhibit actuation rates of up to 20 s−1. Furthermore, an inchworm-inspired soft crawling robot capable of steering, navigation, obstacle crossing, and cargo transportation was developed, achieving a locomotion speed of up to 1.2 body lengths per second. This work breaks through the design possibilities for SMSAs, enhances the actuation rates of soft actuators, and advances the application of SMSAs in soft crawling robots. [ABSTRACT FROM AUTHOR]

Molybdenum carbide (MoC) integrated into a carbon matrix, known for its robust interfacial polarization, emerges as a promising ultra‐lightweight EM wave absorber. However, the fabrication of such materials remains a formidable challenge. Herein, a facile and scalable strategy for preparing MoC‐incorporated carbon matrix employing ZnMo‐HZIF foam material through ball‐milling foaming and calcination process as a promising electromagnetic wave materials (EWAMs). In detail, the 3D foam structure reaches impedance matching, and heterogeneous interfaces of N‐doped MoC‐incorporated carbon material (MoC/NC) promote the dipolar/interfacial polarization, confirmed by the hologram. Mo defects induced the charge transfers, displaying an enhanced interfacial polarization. At 15 wt.%, the minimum reflection loss of the obtained sample at 2.5 mm reaches −47.56 dB, and the effective absorption bandwidth spans 4.40 GHz, nearly covering the full X band. Additionally, the assembly device testing demonstrates their excellent self‐cleaning, heat‐insulation, flame retardancy, and infrared stealth properties. This work presents a new perspective on the synergistic effect of structure and components on electromagnetic wave absorption performance and provides a new approach for preparing lightweight and high‐performance MOF‐based electromagnetic wave absorbing materials. [ABSTRACT FROM AUTHOR]