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Gao, Hui,Li, Jinglin,Sivakumar, Dakshinamurthy,Kim, Tae-Su,Patel, Sanjay K.S.,Kalia, Vipin C.,Kim, In-Won,Zhang, Ye-Wang,Lee, Jung-Kul Elsevier 2019 INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES Vol.123 No.-
<P><B>Abstract</B></P> <P>Pyridine nucleotide cofactors play important roles in biocatalytic processes that generate value-added chemicals for the pharmaceutical and food industries. Because of the high price of these pyridine cofactors, cofactor regeneration is highly desirable. However, recycling the oxidized form of cofactors, especially NADP<SUP>+</SUP>, remains a challenge. Here, we cloned and characterized an NADH oxidase from <I>Lactobacillus reuteri</I> (LreNox) which can oxidize both NADH and NADPH. Unlike many other Noxs, LreNox showed equal catalytic efficiency towards NADH and NADPH. To the best our knowledge, LreNox has the highest activity towards NADPH as a substrate compared to other wild type Noxs. Homology modeling and substrate docking studies provided insights into the dual substrate specificity of LreNox. Gly155, Ser179, and His184 in the LreNox substrate binding pocket, which are absent in other Noxs structures, are crucial for NADPH recognition, providing more space for interactions with the additional phosphate group present in NADPH. We also explored the utility of LreNox for NADP<SUP>+</SUP> regeneration in <SMALL>L</SMALL>-sorbose production by coupling it with a sorbitol dehydrogenase. The turn over number (TTN) improved ~53-fold after using LreNox as the NADP<SUP>+</SUP> recycling enzyme. This study demonstrates that LreNox could potentially be used for the regeneration of NAD(P)<SUP>+</SUP> in commercial applications.</P>
GAO Hui,SONG Qi-chao,Huang Jun 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.7
Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. In view of the above problems, a method based on least square support vector regression (LSTSVR) and real-coded quantum evolutionary algorithm (RQEA) is proposed. Firstly, the LSTSVR parameter is chosen as a combinatorial optimization problem, and determining the objective function of the combinatorial optimization problem, then, using RQEA to solve the combinatorial optimization problem and optimize the LSTSVR parameters, Finaly, LSTSVR-RQEA is used to sovle the prediction of subgrade settlement. The simulation results show that RQEA is an effective method to select LSTSVR parameters, and has excellent performance when applied to the prediction of subgrade settlement.
Gao Hui,Huang Jun 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
Due to the normal forecasting methods for subgrade settlement using observation data have different applicability and disadvantages, The Combined forecasting model is put forward based on support vector machine (SVM) and real-coded quantum evolutionary algorithm (RQEA) in this paper. Its core is that, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve which has S-type characteristic are chosen as single forecasting model, then support vector machine is used to combine the predicting results of each single forecasting model, at the same time, RQEA is adopted to optimize support vector machine parameter to improve the SVM’s performance. The analytical result of engineering practice indicates that the proposed combined forecasting model of subgrade settlement base on SVM and RQEA can not only improve the predicting accuracy, but also reduce the predicting risk, and can meet engineering demand.
Visualization of Tooth for Non-Destructive Evaluation from CT Images
Gao, Hui,Chae, Oksam The Korean Society for Nondestructive Testing 2009 한국비파괴검사학회지 Vol.29 No.3
This paper reports an effort to develop 3D tooth visualization system from CT sequence images as a part of the non-destructive evaluation suitable for the simulation of endodontics, orthodontics and other dental treatments. We focus on the segmentation and visualization for the individual tooth. In dental CT images teeth are touching the adjacent teeth or surrounded by the alveolar bones with similar intensity. We propose an improved level set method with shape prior to separate a tooth from other teeth as well as the alveolar bones. Reconstructed 3D model of individual tooth based on the segmentation results indicates that our technique is a very conducive tool for tooth visualization, evaluation and diagnosis. Some comparative visualization results validate the non-destructive function of our method.
GAO Hui,Song Qi-chao,Huang Jun 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.6
Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. The Combined forecasting model of subgrade settlement based on Least Square twin support vector regession is put forward in this paper. At the first, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve with the S-type characteristics are choosed as single forcasting model; Then taking prediction results of each individual model as the least square support vector regression model input and to construct the combined forecasting model of subgrade settlement. The result of engineering practice shows that the proposed method has better prediction accuracy and stability.
Application of Twin Support Vector Regression in Subgrade Settlement Prediction
Gao Hui,Song Qi-chao,Huang Jun 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.7
Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. In view of the above problems, based on the twin support vector regression tool, the settlement prediction model is established by combining with the measured roadbed settlement data; The related parameters of the prediction model are given and compared with the standard support vector regression machine, the comparison tests show that the twins support vector regression is a new method to predict the settlement of the roadbed, and is superior in forecasting accuracy to the standard support vector regression.
Gaohui Feng,Liqiang Yuan,Zhengming Zhao,Junjie Ge,Xiuxi Ye,Ting Lu 전력전자학회 2016 JOURNAL OF POWER ELECTRONICS Vol.16 No.2
This paper focuses on an improvement in the transient performance of Boost converters when the load changes abruptly. This is achieved on the basis of the nature trajectory in Boost converters. Three key aspects of the transient performance are analyzed including the storage energy change law in the inductors and capacitors of converters during the transient process, the ideal minimum voltage deviation in the transient process, and the minimum voltage deviation control trajectory. The changing relationship curve between the voltage deviation and the recovery time is depicted through analysis and simulations when the load suddenly increases. In addition, the relationship curve between the current fluctuation and the recovery time is obtained when the load suddenly decreases. Considering the aspects of an increasing and decreasing load, this paper proposes the transient performance synthetic optimized trajectory and control laws. Through simulation and experimental results, the transient performances are compared with the other typical three control methods, and the ability of proposed synthetic trajectory and control law to achieve optimal transient performance is verified.
Feng, Gaohui,Yuan, Liqiang,Zhao, Zhengming,Ge, Junjie,Ye, Xiuxi,Lu, Ting The Korean Institute of Power Electronics 2016 JOURNAL OF POWER ELECTRONICS Vol.16 No.2
This paper focuses on an improvement in the transient performance of Boost converters when the load changes abruptly. This is achieved on the basis of the nature trajectory in Boost converters. Three key aspects of the transient performance are analyzed including the storage energy change law in the inductors and capacitors of converters during the transient process, the ideal minimum voltage deviation in the transient process, and the minimum voltage deviation control trajectory. The changing relationship curve between the voltage deviation and the recovery time is depicted through analysis and simulations when the load suddenly increases. In addition, the relationship curve between the current fluctuation and the recovery time is obtained when the load suddenly decreases. Considering the aspects of an increasing and decreasing load, this paper proposes the transient performance synthetic optimized trajectory and control laws. Through simulation and experimental results, the transient performances are compared with the other typical three control methods, and the ability of proposed synthetic trajectory and control law to achieve optimal transient performance is verified.