RESUMO
Gate-level circuit partitioning is an important development trend for improving the efficiency of simulation in EDA software. In this paper, a gate-level circuit partitioning algorithm, based on clustering and an improved genetic algorithm, is proposed for the gate-level simulation task. First, a clustering algorithm based on betweenness centrality is proposed to quickly identify clusters in the original circuit and achieve the circuit coarse. Next, a constraint-based genetic algorithm is proposed which provides absolute and probabilistic genetic strategies for clustered circuits and other circuits, respectively. This new genetic strategy guarantees the integrity of clusters and is effective for realizing the fine partitioning of gate-level circuits. The experimental results using 12 ISCAS '89 and ISCAS '85 benchmark circuits show that the proposed algorithm is 5% better than Metis, 80% better than KL, and 61% better than traditional genetic algorithms for finding the minimum number of connections between subsets.
RESUMO
Idiosyncratic hepatotoxicity of Polygonum multiflorum has attracted a great attention in the world. The most toxic part of idiosyncratic hepatotoxicity was screened by MTT assay and flow cytometry, which was the 50% ethanol elute by macroporous adsorptive resins from alcohol-extraction of P. multiflorum. The fingerprints were collected by HPLC from 50% ethanol elute of crude and processed P. multiflorum from different habitats, then 14 common peaks were determined. Spectrum-toxicity relationship was analyzed by rough set theory(RST). Two main chemical components were predicted for idiosyncratic hepatotoxicity, in which TSG was the greater contributor. Idiosyncratic hepatotoxicity of TSG was tested in vitro, and the results indicated that TSG was the most important constituent contributed to idiosyncratic hepatotoxicity of P. multiflorum. The study showed the discovery of the main chemical components for idiosyncratic hepatotoxicity, and RST was effective for analyzing the spectrum-toxicity relationship, which could be a new method used in the effective/toxic constituents field of traditional Chinese medicine.