Detecting overlapping communities in networks via dominant label propagation

Community detection is an important methodology for understanding the intrinsic structure and function of a realworld network.In this paper,we propose an effective and efficient algorithm,called Dominant Label Propagation Algorithm(Abbreviated as DLPA),to detect communities in complex networks.The algorithm simulates a special voting process to detect overlapping and non-overlapping community structure in complex networks simultaneously.Our algorithm is very efficient,since its computational complexity is almost linear to the number of edges in the network.Experimental results on both real-world and synthetic networks show that our algorithm also possesses high accuracies on detecting community structure in networks.     

盐酸苯达莫司汀杂质的合成

以[1-甲基-2-(4′-丁酸乙酯基)-5-氨基]-1H-苯并咪唑为原料,与氯乙醇经-N-单羟乙基化反应制得[1-甲基-2-(4′-丁酸乙酯基)-5-(2′-羟基乙基)氨基]-1H-苯并咪唑(A); A与氯化亚砜经氯化反应制得[1-甲基-2-(4′-丁酸乙酯基)-5-(2′-氯乙基)氨基]-1H-苯并咪唑(B); B在浓盐酸中经水解成盐反应合成了盐酸苯达莫司汀杂质[1-甲基-2-(4′-丁酸基)-5-(2′-氯乙基)氨基]-1H-苯并咪唑盐酸盐,总收率24.5%,纯度98.12%,其结构经¹H NMR, ¹³C NMR和HR-MS(ESI)确证。