Anaerobic, aerobic, and facultative bacteria are all present in corrosive environments. However, as previous studies to address corrosion in the marine environment have largely focused on anaerobic bacteria, limited a...Anaerobic, aerobic, and facultative bacteria are all present in corrosive environments. However, as previous studies to address corrosion in the marine environment have largely focused on anaerobic bacteria, limited attention has been paid to the composition and function of aerobic and facultative bacteria in this process. For analysis in this study, ten samples were collected from rust layers on steel plates that had been immersed in seawater for diff erent periods (i.e., six months and eight years) at Sanya and Xiamen, China. The cultivable aerobic bacterial community structure as well as the number of sulfate-reducing bacteria (SRB) were analyzed in both cases, while the proportion of facultative SRB among the isolated aerobic bacteria in each sample was also evaluated using a novel approach. Bacterial abundance results show that the proportions are related to sea location and immersion time;abundances of culturable aerobic bacteria (CAB) and SRB from Sanya were greater in most corrosion samples than those from Xiamen, and abundances of both bacterial groups were greater in samples immersed for six months than for eight years. A total of 213 isolates were obtained from all samples in terms of CAB community composition, and a phylogenetic analysis revealed that the taxa comprised four phyla and 31 genera. Bacterial species composition is related to marine location;the results show that Firmicutes and Proteobacteria were the dominant phyla, accounting for 98.13% of the total, while Bacillus and Vibrio were the dominant genera, accounting for 53.06% of the total. An additional sixfacultative SRB strains were also screened from the isolates obtained and were found to encompass the genus Vibrio (four strains), Staphylococcus (one strain), and Photobacterium (one strain). It is noteworthy that mentions of Photobacterium species have so far been absent from the literature, both in terms of its membership of the SRB group and its relationship to corrosion.展开更多
The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is...The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is designed. The recursive prediction error (RPE)algorithm which yields faster convergence than back propagation (BP) algorithm is applied to trainthe neural networks. The realization of RPE algorithm is given. The difference of modeling ofartificial muscles using neural networks with different input nodes and different hidden layer nodesis discussed. On this basis the nonlinear control scheme using neural networks for artificialmuscle system has been introduced. The experimental results show that the nonlinear control schemeyields faster response and higher control accuracy than the traditional linear control scheme.展开更多
基金Supported by the National Basic Research Program of China(973 Program)(No.2014CB643304)the National Natural Science Foundation of China(No.41576080)the Key Research and Development Program of Shandong Province(No.2018GHY115003)
文摘Anaerobic, aerobic, and facultative bacteria are all present in corrosive environments. However, as previous studies to address corrosion in the marine environment have largely focused on anaerobic bacteria, limited attention has been paid to the composition and function of aerobic and facultative bacteria in this process. For analysis in this study, ten samples were collected from rust layers on steel plates that had been immersed in seawater for diff erent periods (i.e., six months and eight years) at Sanya and Xiamen, China. The cultivable aerobic bacterial community structure as well as the number of sulfate-reducing bacteria (SRB) were analyzed in both cases, while the proportion of facultative SRB among the isolated aerobic bacteria in each sample was also evaluated using a novel approach. Bacterial abundance results show that the proportions are related to sea location and immersion time;abundances of culturable aerobic bacteria (CAB) and SRB from Sanya were greater in most corrosion samples than those from Xiamen, and abundances of both bacterial groups were greater in samples immersed for six months than for eight years. A total of 213 isolates were obtained from all samples in terms of CAB community composition, and a phylogenetic analysis revealed that the taxa comprised four phyla and 31 genera. Bacterial species composition is related to marine location;the results show that Firmicutes and Proteobacteria were the dominant phyla, accounting for 98.13% of the total, while Bacillus and Vibrio were the dominant genera, accounting for 53.06% of the total. An additional sixfacultative SRB strains were also screened from the isolates obtained and were found to encompass the genus Vibrio (four strains), Staphylococcus (one strain), and Photobacterium (one strain). It is noteworthy that mentions of Photobacterium species have so far been absent from the literature, both in terms of its membership of the SRB group and its relationship to corrosion.
基金This project is supported by Foundation of Public Laboratory on Robotics of Chinese Academy of Sciences.
文摘The pneumatic artificial muscles are widely used in the fields of medicalrobots, etc. Neural networks are applied to modeling and controlling of artificial muscle system. Asingle-joint artificial muscle test system is designed. The recursive prediction error (RPE)algorithm which yields faster convergence than back propagation (BP) algorithm is applied to trainthe neural networks. The realization of RPE algorithm is given. The difference of modeling ofartificial muscles using neural networks with different input nodes and different hidden layer nodesis discussed. On this basis the nonlinear control scheme using neural networks for artificialmuscle system has been introduced. The experimental results show that the nonlinear control schemeyields faster response and higher control accuracy than the traditional linear control scheme.
