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The drilling-hammer method is adopted for the breaking over submerged reefs in waterway regulation engineering. However, rocks with pre-drilled holes are highly susceptible to the repetitive impacts from drop hammers or drilling equipment. Exploring the dynamic responses and failure behaviors of drilled-hole rocks under repetitive impacting is important for promoting implementation of this technique. In this study, the repetitive impacting tests were conducted on the drilled rocks by the split Hopkinson pressure bar to investigate the rock bearing capacity, deformation property, failure behavior, and energy evolution. The results indicate that the presence of pre-drilled holes and the decreasing loading rates attenuate the bearing capacity of rocks subjected to repetitive impacting. In contrast, the rock deformation capacity is impacted subtly by the impact loading rate and increases with the number of impacts and borehole size. The drilled rock failure occurred with the prevalence of intergranular fractures; subsequently, the proportion of transgranular fractures increased, contributing to the loading rate-dependent bearing capacity. The inverted S-shaped damage evolution curve was assessed using the inverted logistic growth model. The specimen absorbed few incident energies for fracture generation and propagation, and the rock with a larger drill size displays higher energy utilization and larger fragments. • Illustrated the influences of repetitive impacting on the bearing capacity and deformability of pre-cracked hole rocks. • Revealed the failure behavior and fracture mechanism of pre-cracked hole rocks under repetitive impacting. • Depicted the damage evolution of pre-cracked hole rocks under repetitive impacting by the inverted logistic growth model. • Investigated the dynamic energy dissipation of pre-cracked hole rocks under repetitive impacting. [ABSTRACT FROM AUTHOR]

• Proposed a key bone extraction network based on YOLOv5. • The GRU and Unet networks are integrated to achieve high-quality segmentation of key bones. • The proposed two-stage key bone segmentation was verified by experiments. • Evaluate the accuracy of partial baseline target detection network, semantic segmentation network and the proposed method. Automatic segmentation of hand bone X-ray images is an important process in skeletal bone age assessment (BAA). The segmentation process is extremely difficult and complicated due to the complex structure and tiny size of hand bone features, which may lead to inaccurate feature localization and incomplete segmentation. A two-stage segmentation method is proposed in this paper. In the first stage, the OSA-YOLOv5 network is used to extract hand bones, and in the second stage, GRU-UNet is used to separate extracted hand bones. The hand bone X-ray dataset consists of a mixed dataset of 1000 left-hand bone X-ray images of adolescents from licenced local hospitals and 1000 left-hand bone X-ray images from the RSNA public dataset. The training efficiency of the OSA-YOLOv5 network is 28 % higher than that of the traditional network, and the proposed network exhibits with a higher extraction accuracy. The segmentation accuracy of the GRU-Unet segmentation model 14.70 % higher than that if Unet. The spatial sequence features with spatial rules are found to have a positive correlation in GRU-Unet. Experimental results show that the proposed segmentation method has good generalization and robustness, which provides a good foundation for subsequent BAA. [ABSTRACT FROM AUTHOR]

The current two-dimensional (2D) material based NH 3 sensors generally suffer from low response values and sluggish recovery dynamics, which is resulted from their inferior conductivity. Herein, high conductivity (0.045 S/m) of 2D hydrogen substituted graphyne (HsGY) nanosheets are successfully synthesized employing aqueous/organic interface method and using them for the first time for the detection of NH 3 at room temperature. The resultant gas sensing performance shows that the 2D HsGY nanosheets exhibit a high gas response value (4.9) to 100 ppm NH 3 and fast recovery time (108 s) at the room temperature. The NH 3 gas sensing mechanism is discussed by utilizing density functional theory (DFT) calculations. The present study provides novel gas sensing material for the development of high-performance room temperature NH 3 sensors. This study successfully synthesized two-dimensional hydrogen substituted graphyne (HsGY) nanosheets using an aqueous/organic interface method and applied them for the detection of NH 3 at room temperature for the first time. HsGY nanosheets exhibit excellent sensing performance towards NH 3 , due to their high conductivity and continuous thin gauze like morphology, which facilitates gas transport. [Display omitted] [ABSTRACT FROM AUTHOR]