A novel glucose-assisted ultrasonic cavitation exfoliation (GAUCE) method was proposed to prepare BNNSs, and its preparing mechanism was revealed.

MoAlB ceramic coatings were prepared on a 316 steel surface by atmospheric plasma spraying with different arc power levels. The phase composition, microstructure and wear resistance of coatings against GCr15 and Si₃N₄ counterparts were studied. The MoAlB ceramic decomposed and was oxidized to form MoB and Al₂O₃ during plasma spraying. With the increase of the arc power, MoAlB experienced more decomposition, but the coatings became denser. When the arc power increased from 30 to 36 kW, the wear rates of coatings against GCr15 and Si₃N₄ balls reduced by 91% and 78%, respectively. The characterization of wear tracks shows that when against GCr15 counterparts, the main wear mechanisms are abrasive and adhesive wear, and when against Si₃N₄ counterparts, fatigue and abrasive wear are dominant. The refinement of wear resistance by increasing arc power can be attributed to the improvement of density and adhesive strength among splats.

Computer vision, being a pivotal element of artificial intelligence, has witnessed significant advancements in theoretical methodologies, key technologies, and practical applications after years of development, which has shown great application prospects in medical, industrial, transportation, military, public safety, and other fields. Therefore, it is necessary to review the current development and application of computer vision technology to comprehensively evaluate its future development trend and potential. Firstly, this paper reviews the development history of computer technology. Then, aiming at the specific tasks of computer vision, the typical methods and models based on depth learning in recent years are summarized, including image classification, target detection, image segmentation, etc. Then, the application and research progress of computer vision technology in various vital fields are introduced respectively. Finally, the current challenges and critical research problems in computer vision technology are analyzed.