http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Wang, He,Yang, Ruijin,Hua, Xiao,Zhang, Wenbin,Zhao, Wei The Korean Society for Microbiology and Biotechnol 2016 Journal of microbiology and biotechnology Vol.26 No.7
Currently, enzymatic synthesis of lactulose, a synthetic prebiotic disaccharide, is commonly performed with glycosyl hydrolases. In this work, a new type of lactulose-producing biocatalyst was developed by displaying β-galactosidase from Bacillus stearothermophilus IAM11001 (Bs-β-Gal) on the surface of Bacillus subtilis 168 spores. Localization of β-Gal on the spore surface as a fusion to CotX was verified by western blot analysis, immunofluorescence microscopy, and flow cytometry. The optimum pH and temperature for the resulting spore-displayed β-Gal was 6.0 and 75℃, respectively. Under optimal conditions, it showed maximum activity of 0.42 U/mg spores (dry weight). Moreover, the spore-displayed CotX-β-Gal was employed as a whole cell biocatalyst to produce lactulose, yielding 8.8 g/l from 200 g/l lactose and 100 g/l fructose. Reusability tests showed that the spore-displayed CotX-β-Gal retained around 30.3% of its initial activity after eight successive conversion cycles. These results suggest that the CotX-mediated spore-displayed β-Gal may provide a promising strategy for lactulose production.
He Wang,Ruijin Yang,Xiao Hua,Wei Zhao,Wenbin Zhang 한국식품과학회 2015 Food Science and Biotechnology Vol.24 No.5
Two model proteins of an enhanced green fluorescent protein (EGFP) and a tetrameric β- Galactosidase (β-Gal) from Bacillus stearothermophilus IAM11001 were fused to the C-terminus of the crust proteins Y (CotY) and Z (CotZ) from B. subtilis 168. Surface-expression of the resulting fusion proteins CotY-EGFP, CotZ-EGFP, CotY-β-Gal, and CotZ-β-Gal were then evaluated. Fluorescence intensity analysis of the transformed strains indicated that the CotY-EGFP and CotZ-EGFP fusion proteins were successfully displayed on spores. β-Gal was anchored on the surface of B. subtilis spores, confirmed based on western blotting and immunofluorescence microscopy. Results of a β-Gal assay showed that when fused to CotY and CotZ, the obtained enzyme activities of spore-displayed β-Gals were 0.12 and 0.25 U/mg of spores (dry weight), respectively. CotY and CotZ were, thus, shown to be suitable candidate carriers for display of multimeric enzymes on the spore surface.
( He Wang ),( Ruijin Yang ),( Xiao Hua ),( Wenbin Zhang ),( Wei Zhao ) 한국미생물 · 생명공학회 2016 Journal of microbiology and biotechnology Vol.26 No.6
Currently, enzymatic synthesis of lactulose, a synthetic prebiotic disaccharide, is commonly performed with glycosyl hydrolases. In this work, a new type of lactulose-producing biocatalyst was developed by displaying β-galactosidase from Bacillus stearothermophilus IAM11001 (Bs-β-Gal) on the surface of Bacillus subtilis 168 spores. Localization of β-Gal on the spore surface as a fusion to CotX was verified by western blot analysis, immunofluorescence microscopy, and flow cytometry. The optimum pH and temperature for the resulting sporedisplayed β-Gal was 6.0 and 75oC, respectively. Under optimal conditions, it showed maximum activity of 0.42 U/mg spores (dry weight). Moreover, the spore-displayed CotX-β- Gal was employed as a whole cell biocatalyst to produce lactulose, yielding 8.8 g/l from 200 g/l lactose and 100 g/l fructose. Reusability tests showed that the spore-displayed CotX-β- Gal retained around 30.3% of its initial activity after eight successive conversion cycles. These results suggest that the CotX-mediated spore-displayed β-Gal may provide a promising strategy for lactulose production.
Yiyi Zhang,Hua Wei,Ruijin Liao,Youyuan Wang,Lijun Yang,Chunyu Yan 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.2
Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.
Zhang, Yiyi,Wei, Hua,Liao, Ruijin,Wang, Youyuan,Yang, Lijun,Yan, Chunyu The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.12 No.2
Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.