Catalysis Letters - The development of novel catalysts for the synthesis of cyclic carbonates under mild conditions remains a challenge. Herein, we designed the strategy of immobilizing DBU-based... 相似文献
Friction between yarns could greatly influence braiding processes, especially using carbon/glass fibers. However, as the points of friction are various and traveling all the time, it is quite difficult to measure the total value of frictions. To solve this problem, mathematical models have been developed to predict the friction in two braiding processes of triaxial circular braiding processes, the widely used end-face braiding process and the inner-face braiding process. To analyze the influence of the two braiding processes to the interacted friction between yarns, some definitions and initial conditions were introduced. Based on these conditions, the yarn net, which is formed during the braiding process, was divided into numerous segments. With the geometrical and force equilibrium relationships, each yarn nodes and segments were analyzed. Based on these equations and boundary conditions, the models of two braiding processes were established and solved by Matlab. A practical engineering implementation was shown to verify the validation of the model. The results shows that the inner-face braiding process of braiding process does have a better performance in eliminating the friction than the widely used end-face braiding process. 相似文献
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques, Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis. Therefore, WSI analysis has become the key to modern digital histopathology. Since 2004, WSI has been used widely in CAD. Since machine vision methods are usually based on semi-automatic or fully automatic computer algorithms, they are highly efficient and labor-saving. The combination of WSI and CAD technologies for segmentation, classification, and detection helps histopathologists to obtain more stable and quantitative results with minimum labor costs and improved diagnosis objectivity. This paper reviews the methods of WSI analysis based on machine learning. Firstly, the development status of WSI and CAD methods are introduced. Secondly, we discuss publicly available WSI datasets and evaluation metrics for segmentation, classification, and detection tasks. Then, the latest development of machine learning techniques in WSI segmentation, classification, and detection are reviewed. Finally, the existing methods are studied, and the application prospects of the methods in this field are forecasted.