Currently, the research on mechanical behavior and cutting performance of functionally graded carbides is quite limited, which limits the rapid development of high-performance cemented carbide cutting tools. Based on WC-Co-Zr and WC-Ni-Zr, this study synthesized two kinds of cemented carbide cutters, i.e., the cemented carbide cutters with homogeneous microstructure and functionally graded carbide (FGC) cutters with FCC phase ZrN-enriched surfaces. Furthermore, TiAlN coating has been investigated on these carbide cutters. Mechanical behavior, friction, wear performance, and cutting behavior have been investigated for these coated carbides and their corresponding substrates. It was found that, as compared with coated cutters on WC-Co/Ni-Zr carbide substrates with homogeneous microstructures, the coated cutters on WC-Co/Ni-Zr FGC substrates with FCC phase-enriched surfaces show higher wear resistance and cutting life, and the wear mechanism during cutting is mainly adhesion wear.
Genetic data is very important for biological research, but it is hard to be obtained by experiment. In this paper, we introduce an algorithm for generating simulated genetic data based on K-mediods. A concept of Cluster Channel is proposed in this algorithm and used to generate simulated data. The noise of origin data could be eliminated using the proposed method. The experimental results show reliability of simulated genetic data. SAM is used to analyze the simulated data and original data, and we get a conclusion that the simulated data can effectively validate differentially expressed gene detected algorithm.
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