检索结果-南通市图书馆

维普期刊数据库博看期刊

Cloning and Expression of Rat liver S-Adenosylmethionine Synthetase

在线全文

学校读者我要写书评

暂无评论

Chemical Research in Chinese Universities 2006年第2期22卷 236-238页

作者： CUI wei HUANG Lei li wei wang li-ping College of life Science Jilin University Changchun 130021 P. R. China

The S-adenosylmethionine synthetase（SAM synthetase） is responsible for in vivo synthesis of S-adenosylmethionine（SAM）, which is a kind of biologically active molecules distributed in all body tissues and fluids and involved in a number of biochemical reactions. In this study, a cDNA containing the coding sequence for rat liver SAM synthetase was cloned into the prokaryotic expression vector pQE30 and expressed in E. coli M15. A major band corresponding to a protein of 48 kDa was detected on SDS-PAGE. The protein was distributed in both the soluble fraction and the insoluble fraction. In soluble fractions the protein was fully active.

关键词： SAM SAM synthetase, Cloning Expression HPLC

Focusing on the meso-scales of multi-scale phenomena-In search for a new paradigm in chemical engineering

在线全文

学校读者我要写书评

暂无评论

Particuology 2010年第6期8卷 634-639页

作者： Jinghai li wei Ge wei wang Ning Yang The EMMS Group State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China

To celebrate the 90th birthday of Professor Mooson Kwauk, who supervised the multi-scale research at this Institute in the last three decades, we dedicate this paper outlining our thoughts on this subject accumulated from our previous studies. In the process of developing, improving and extending the energy- minimization multi-scale （EMMS） method, we have gradually recognized that meso-scales are critical to the understanding of the different kinds of multi-scale structures and systems. It is a common challenge not only for chemical engineering but also for almost all disciplines of science and engineering, due to its importance in bridging micro- and macro-behaviors and in displaying complexity and diversity. It is believed that there may exist a common law behind meso-scales of different problems, possibly even in different fields. Therefore, a breakthrough in the understanding of meso-scales will help materialize a revolutionary progress, with respect to modeling, computation and application.

关键词： Meso-scale Multi-scale Complex system EMMS Multi-phase High performance computation

HETEROGENEITY, NONliNEARITY AND ENDOGENOUS MARKET VOLATIliTY

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2011年第6期24卷 1130-1142页

作者： Hongquan li Shouyang wang wei SHANG School of Business Hunan Normal University Changsha 410081 China Academy of Mathematics and Systems Sciences Chinese Academy of Sciences Beijing 100190 China

This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. An exogenous noise is introduced to the model with the assumption of IID normal innovations of the fundamental value in order to investigate how noisy dynamics interacts with deterministic process. The market is composed of two typical trader types： the rational fundamentalists and the boundedly rational traders governed by greed and fear. The interaction between noise and deterministic element determines the evolution process of the system as key parameters are changed. The authors find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S＆：P500 index, such as volatility clustering, fat tails （leptokurtosis）, autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. The authors also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.

关键词： Computational finance endogenous volatility heterogeneous agents noisy chaos nonlinearity stylized facts.

Crystal Structure of Norfloxacin Methanol Solvate: C_(16)H_(18)FN_3O_3·CH_3OH·H_2O

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Structural Chemistry 2005年第12期24卷 1359-1362页

作者： wang Ying SUN li-wei wang wei YAN lian-He Water Treatment Institute Nanjing University of Science and Technology Nanjing 210094 China

Norfloxacin methanol solvate （ 1 -ethyl-6-fluoro- 1,4-dihydro-4-oxo-7-（ 1 -piperazinyl）-3- quinoline carboxylic acid methanol solvate） has been prepared. The crystal and molecular structures of the title compound, C16H18FN3O3·CH3OH·H2O, were determined by X-ray diffraction method. The compound crystallizes in monoclinic, space group P21/c with a = 7.8660（16）, b = 22.525 （5）, c = 10.253（2）A, β= 108.31°, Mr = 369.39, V = 1724.7（6）A^3, Z = 4, Dc= 1.423 g/cm^3, F（000） = 784, R = 0.0557 and wR = 0.1224. The TGA analysis indicates that it decomposes completely at 723.75℃.

关键词： crystal structure norfloxacin methanol solvate

Detailed assessment of homology detection using different substitution matrices

在线全文

学校读者我要写书评

暂无评论

Chinese Science Bulletin 2006年第13期51卷 1538-1545页

作者： li Jing wang wei National Lab of Solid State Microstructure Department of Physics and Institute of Biophysics Nanjing University Nanjing 210093 China

Homology detection plays a key role in bioinformatics, whereas substitution matrix is one of the most important components in homology detec- tion. Thus, besides the improvement of alignment algorithms, another effective way to enhance the accuracy of homology detection is to use proper substitution matrices or even construct new matrices. A study on the features of various matrices and on the comparison of the performances between differ- ent matrices in homology detection enable us to choose the most proper or optimal matrix for some specific applications. In this paper, by taking BLOSUM matrices as an example, some detailed features of matrices in homology detection are stud- ied by calculating the distributions of numbers of recognized proteins over different sequence identities and sequence lengths. Our results clearly showed that different matrices have different preferences and abilities to the recognition of remote homologous proteins. Furthermore, detailed features of the vari- ous matrices can be used to improve the accuracy of homology detection.

关键词：替代矩阵序列一致性序列长度同种探测

The Infiltration Process and Texture Transition of 2D C/C Composites

在线全文

学校读者我要写书评

暂无评论

Journal of Materials Science & Technology 2009年第1期25卷 109-114页

作者： Hejun li Guozhong Xu Kezhi li Chuang wang wei li Miaoling li Carbon/carbon Composites Research Center Key Laboratory of Ultrahigh Temperature Composites Northwestern Polytechnical University Xi＇an 710072 China

2D needle-punched fiber felt was infiltrated by a kind of rapid isothermal chemical vapor infiltration technique. The infiltration process and texture transition of the infiltrated C/C composites were investigated. The porosity and the variations of the cumulative pore volume were determined by mercury porosimetry. The texture of matrix carbon was studied under a polarized light microscope. The results show that the relative mass gain of the sample increases directly as the infiltration time at the initial stage until 20 h, and subsequently the increasing rate of the relative mass gain decreases gradually with the prolonging of infiltration time. Three layers of pyrocarbon were formed around fibers. Low-textured pyrocarbon was obtained at the initial stage. With the densification going on, high-textured pyrocarbon was formed on the surface of low-textured pyrocarbon. Then, low-textured pyrocarbon was produced again during the final stage of densification. The texture transition is ascribed to the variation of the ratio of cumulative inner surface area to volume of pores and the gas partial pressure in pores.

关键词： C/C composites Isothermal chemical vapor infiltration (ICVI) Pyrocarbon Mercury porosimetry Polarized light microscope

Ni/MgO catalyst prepared via dielectric-barrier discharge plasma with improved catalytic performance for carbon dioxide reforming of methane

在线全文

学校读者我要写书评

暂无评论

Frontiers of Chemical Science and Engineering 2014年第2期8卷 133-140页

作者： Yan li Zhehao wei Yong wang Voiland School of Chemical Engineering and Bioengineering Washington State University Pullman WA 99164 USA

A Ni/MgO catalyst was prepared via novel dielectric-barrier discharge （DBD） plasma decomposition method. The combined characterization of Bmnauer- Emmett-Teller measurement, X-ray diffraction, hydrogen temperature-programmed reduction and transmission electron microscopy shows that DBD plasma treatment enhances the support-metal interaction of Ni/MgO catalyst and facilitates the formation of smaller Ni particles. Sphere-like Ni particles form on plasma treated Ni/MgO catalysts. The plasma treated Ni/MgO catalyst shows a significantly improved low temperature activity and good stability for CO2 reforming of methane to syngas.

关键词： CO2 reforming methane dielectric-barrierdischarge (DBD) plasma Ni/MgO

Zero-shot Fine-grained Classification by Deep Feature Learning with Semantics

在线全文

学校读者我要写书评

暂无评论

International Journal of Automation and computing 2019年第5期16卷 563-574页

作者： Ao-Xue li Ke-Xin Zhang li-wei wang The Key Laboratory of Machine Perception (MOE) School of Electronics Engineering and Computer SciencePeking University

Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task for two main reasons: lack of sufficient training data for every class and difficulty in learning discriminative features for representation. In this paper, to address the two issues, we propose a two-phase framework for recognizing images from unseen fine-grained classes, i.e., zeroshot fine-grained classification. In the first feature learning phase, we finetune deep convolutional neural networks using hierarchical semantic structure among fine-grained classes to extract discriminative deep visual features. Meanwhile, a domain adaptation structure is induced into deep convolutional neural networks to avoid domain shift from training data to test data. In the second label inference phase, a semantic directed graph is constructed over attributes of fine-grained classes. Based on this graph, we develop a label propagation algorithm to infer the labels of images in the unseen classes. Experimental results on two benchmark datasets demonstrate that our model outperforms the state-of-the-art zero-shot learning models. In addition, the features obtained by our feature learning model also yield significant gains when they are used by other zero-shot learning models, which shows the flexility of our model in zero-shot finegrained classification.

关键词： Fine-grained image classification zero-shot learning deep feature learning domain adaptation semantic graph

Nonlinear Dimensionality Reduction by Local Orthogonality Preserving Alignment

在线全文

学校读者我要写书评

暂无评论

Journal of Computer Science & Technology 2016年第3期31卷 512-524页

作者： Tong lin Yao liu Bo wang li-wei wang Hong-Bin Zha The Key Laboratory of Machine Perception (Ministry of Education) School of Electrical Engineering and Computer Sciences Peking University Beijing 100871 China

We present a new manifold learning algorithm called Local Orthogonality Preserving Alignment （LOPA）. Our algorithm is inspired by the Local Tangent Space Alignment （LTSA） method that aims to align multiple local neighborhoods into a global coordinate system using affine transformations. However, LTSA often fails to preserve original geometric quantities such as distances and angles. Although an iterative alignment procedure for preserving orthogonality was suggested by the authors of LTSA, neither the corresponding initialization nor the experiments were given. Procrustes Subspaces Alignment （PSA） implements the orthogonality preserving idea by estimating each rotation transformation separately with simulated annealing. However, the optimization in PSA is complicated and multiple separated local rotations may produce globally contradictive results. To address these difficulties, we first use the pseudo-inverse trick of LTSA to represent each local orthogonal transformation with the unified global coordinates. Second the orthogonality constraints are relaxed to be an instance of semi-definite programming （SDP）. Finally a two-step iterative procedure is employed to further reduce the errors in orthogonal constraints. Extensive experiments products, and neighborhoods of the original datasets. In that of PSA and comparable to that of state-of-the-art significantly faster than that of PSA, MVU and MVE. show that LOPA can faithfully preserve distances, angles, inner comparison, the embedding performance of LOPA is better than algorithms like MVU and MVE, while the runtime of LOPA is

关键词： manifold learning dimensionality reduction senti-definite programming Procrustes measure