This study aims to develop several optimization techniques for predicting advance rate of tunnel boring machine(TBM)in different weathered zones of granite.For this purpose,extensive field and laboratory studies have ...This study aims to develop several optimization techniques for predicting advance rate of tunnel boring machine(TBM)in different weathered zones of granite.For this purpose,extensive field and laboratory studies have been conducted along the 12,649 m of the Pahang-Selangor raw water transfer tunnel in Malaysia.Rock properties consisting of uniaxial compressive strength(UCS),Brazilian tensile strength(BTS),rock mass rating(RMR),rock quality designation(RQD),quartz content(q)and weathered zone as well as machine specifications including thrust force and revolution per minute(RPM)were measured to establish comprehensive datasets for optimization.Accordingly,to estimate the advance rate of TBM,two new hybrid optimization techniques,i.e.an artificial neural network(ANN)combined with both imperialist competitive algorithm(ICA)and particle swarm optimization(PSO),were developed for mechanical tunneling in granitic rocks.Further,the new hybrid optimization techniques were compared and the best one was chosen among them to be used for practice.To evaluate the accuracy of the proposed models for both testing and training datasets,various statistical indices including coefficient of determination(R^2),root mean square error(RMSE)and variance account for(VAF)were utilized herein.The values of R^2,RMSE,and VAF ranged in 0.939-0.961,0.022-0.036,and 93.899-96.145,respectively,with the PSO-ANN hybrid technique demonstrating the best performance.It is concluded that both the optimization techniques,i.e.PSO-ANN and ICA-ANN,could be utilized for predicting the advance rate of TBMs;however,the PSO-ANN technique is superior.展开更多
Competitiveness for nodulation of Bradyrhizobium japonicum strains plays a key role in symbiotic nitrogen fixation. In order to reveal the difference in competitiveness, B. japonicum 4534 with high competitiveness and...Competitiveness for nodulation of Bradyrhizobium japonicum strains plays a key role in symbiotic nitrogen fixation. In order to reveal the difference in competitiveness, B. japonicum 4534 with high competitiveness and B. japonicum 4222 with low competitiveness for nodulation were analyzed by proteomic technique. The results showed that differential proteins were fewer when two strains were treated with just daidzein. Only 24 and 10 differential proteins were detected with an up-regulated rate of 58 and 40% in B. japonicum 4534 and B. japonicum 4222, respectively. However, more differential proteins were detected upon treatment with daidzein and mutual extracellular materials simultaneously. There were 78 differential proteins detected in B. japonicum 4534 with 43 being up-regulated and 35 being down-regulated. These differential proteins, such as metabolism-related proteins, transporters, transcription-related proteins, translation-related proteins, and flagellin, were found to be associated with nodulation process. 25 up-regulated and 22 down-regulated proteins were detected in B. japonicum 4222. Some of these proteins were not related to nodulation. More differential proteins associated with nodulation in B. japonicum 4534 may be the reason for its high competitiveness. The results can provide a guide to the selection and inoculation of effective strains and are significant to biological nitrogen fixation.展开更多
文摘This study aims to develop several optimization techniques for predicting advance rate of tunnel boring machine(TBM)in different weathered zones of granite.For this purpose,extensive field and laboratory studies have been conducted along the 12,649 m of the Pahang-Selangor raw water transfer tunnel in Malaysia.Rock properties consisting of uniaxial compressive strength(UCS),Brazilian tensile strength(BTS),rock mass rating(RMR),rock quality designation(RQD),quartz content(q)and weathered zone as well as machine specifications including thrust force and revolution per minute(RPM)were measured to establish comprehensive datasets for optimization.Accordingly,to estimate the advance rate of TBM,two new hybrid optimization techniques,i.e.an artificial neural network(ANN)combined with both imperialist competitive algorithm(ICA)and particle swarm optimization(PSO),were developed for mechanical tunneling in granitic rocks.Further,the new hybrid optimization techniques were compared and the best one was chosen among them to be used for practice.To evaluate the accuracy of the proposed models for both testing and training datasets,various statistical indices including coefficient of determination(R^2),root mean square error(RMSE)and variance account for(VAF)were utilized herein.The values of R^2,RMSE,and VAF ranged in 0.939-0.961,0.022-0.036,and 93.899-96.145,respectively,with the PSO-ANN hybrid technique demonstrating the best performance.It is concluded that both the optimization techniques,i.e.PSO-ANN and ICA-ANN,could be utilized for predicting the advance rate of TBMs;however,the PSO-ANN technique is superior.
基金supported by the National High-Tech R&D Program of China (2010AA10A203)the Basic Scientific Research Special Fund of Public Research Institutions of Central Government, China (2010-12 and 2010-34)the Special Fund for Establishment of Modern Agricultural R&D System, Ministry of Finance and Ministry of Agriculture, China (nycytx-004)
文摘Competitiveness for nodulation of Bradyrhizobium japonicum strains plays a key role in symbiotic nitrogen fixation. In order to reveal the difference in competitiveness, B. japonicum 4534 with high competitiveness and B. japonicum 4222 with low competitiveness for nodulation were analyzed by proteomic technique. The results showed that differential proteins were fewer when two strains were treated with just daidzein. Only 24 and 10 differential proteins were detected with an up-regulated rate of 58 and 40% in B. japonicum 4534 and B. japonicum 4222, respectively. However, more differential proteins were detected upon treatment with daidzein and mutual extracellular materials simultaneously. There were 78 differential proteins detected in B. japonicum 4534 with 43 being up-regulated and 35 being down-regulated. These differential proteins, such as metabolism-related proteins, transporters, transcription-related proteins, translation-related proteins, and flagellin, were found to be associated with nodulation process. 25 up-regulated and 22 down-regulated proteins were detected in B. japonicum 4222. Some of these proteins were not related to nodulation. More differential proteins associated with nodulation in B. japonicum 4534 may be the reason for its high competitiveness. The results can provide a guide to the selection and inoculation of effective strains and are significant to biological nitrogen fixation.
