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Search Results: 1 - 10 of 127099 matches for " Li Lijia "
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The Modeling and the Sensor Fault Diagnosis of a Continuous Stirred Tank Reactor with a Takagi-Sugeno Recurrent Fuzzy Neural Network
Li Shi,Lijia Wang,Zhizhong Wang
International Journal of Distributed Sensor Networks , 2009, DOI: 10.1080/15501320802524037
Abstract: In this paper, a novel Takagi-Sugeno recurrent fuzzy neural network (TSRFNN) is constructed for modeling and sensor fault diagnosis of a Continuous Stirred Tank Reactor (CSTR), a nonlinear dynamic system. The TSRFNN is composed of 9 layers, including premise network and consequence network. The temporal information is embedded in the TSRFNN by adding the feedback connections between the output layer and the input layer of the fuzzy neural network (FNN). It is assumed that the inputs are Gaussian membership functions; the product operation is utilized for the premise and implication, and the weighted center-average method is adopted for defuzzification. The network is a Fuzzy Basis Function(FBF). The general approximation characteristic of the network was proven by the theory reasoning. The identification of the TSRFNN consists of two steps: structure identification and parameter identification. Unsupervised clustering is used to determine the structure of the fuzzy system, the number of fuzzy rules, and the membership functions of the premise using the input-output data of a system. Then in the parameter identification, the Dynamic Backpropagation (DBP) is adopted to determine the membership functions of the conclusion of the fuzzy system.
Methylation of phytohormones by the SABATH methyltransferases
LiJia Qu,Shuang Li,ShuFan Xing
Chinese Science Bulletin , 2010, DOI: 10.1007/s11434-010-3245-x
Abstract: In plants, one of the most common modifications of secondary metabolites is methylation catalyzed by various methyltransferases. Recently, a new class of methyltransferases, the SABATH family of methyltransferases, was found to modify phytohormones and other small molecules. The SABATH methyltransferases share little sequence similarity with other well characterized methyltransferases. Arabidopsis has 24 members of the SABATH methyltransferase genes, and a subset of them has been shown to catalyze the formation of methyl esters with phytohormones and other small molecules. Physiological and genetic analyses show that methylation of phytohormones plays important roles in regulating various biological processes in plants, including stress responses, leaf development, and seed maturation/germination. In this review, we focus on phytohormone methylation by the SABATH family methyltransferases and the implication of these modifications in plant development.
A STUDY OF THE AURICULARIA FROM HAINAN ISLAND
海南岛木耳属的研究

Li Lijia,
李丽嘉

植物科学学报 , 1987,
Abstract: 子实体单生,鲜时坚韧的胶质,不透光,耳状,1-2×2.5-3.5cm,厚2-3.1mm,基部发达,呈黄褐色,不孕面有短柔毛和许多短的裂缝,栗褐色,干时棕黑色;子实层有粗条状隆起密集的结节,紫红色,干后紫黑色。柔毛层:毛长30-80(-100)μm,粗4-5.5μm,无色到褐黄色,不成簇,具狭窄的腔,顶园,易截断,基部明显膨大或再突然收缩成细而长的根状;致密层:20-50μm
Multiplicity fluctuations of net protons on the hydrodynamic freeze-out surface
Lijia Jiang,Pengfei Li,Huichao Song
Physics , 2015,
Abstract: This proceeding briefly summarizes our recent work on calculating the correlated fluctuations of net protons on the hydrodynamic freeze-out surface near the QCD critical point. For both Poisson and Binomial baselines, our calculations could roughly reproduce the energy dependent cumulant $C_4$ and $\kappa \sigma^2$ of net protons, but always over-predict $C_2$ and $C_3$ due to the positive contributions from the static critical fluctuations.
Correlated fluctuations near the QCD critical point
Lijia Jiang,Pengfei Li,Huichao Song
Physics , 2015,
Abstract: In this paper, we introduce a freeze-out scheme for the dynamical models near the QCD critical point through coupling the decoupled classical particles with the order parameter field. With a modified distribution function that satisfies specific static fluctuations, we calculate the correlated fluctuations of net protons on the hydrodynamic freeze-out surface. A comparison with recent STAR data shows that our model calculations could roughly reproduce energy dependent cumulant $C_4$ and $\kappa \sigma^2$ of net protons through tuning the related parameters. However, the calculated $C_2$ and $C_3$ with both Poisson and Binomial baselines are always above the experimental data due to the positive contributions from the static critical fluctuations. In order to qualitatively and quantitatively describe the experimental data, the dynamical critical fluctuations and more realistic non-critical fluctuation baselines should be investigated in the near future.
Laser Rapid Manufacturing of Stainless Steel 316L/Inconel718 Functionally Graded Materials: Microstructure Evolution and Mechanical Properties
Dongjiang Wu,Xiaokang Liang,Qian Li,Lijia Jiang
International Journal of Optics , 2010, DOI: 10.1155/2010/802385
Abstract: Two patterns of functionally graded materials (FGMs) were successfully fabricated whose compositions gradually varied from 100% stainless steel 316L to 100% Inconel718 superalloy using laser engineered net shaping process. The microstructure characterization, composition analysis, and microhardness along the graded direction were investigated. The comparison revealed the distinctions in solidification behavior, microstructure evolution of two patterns. In the end, the abrasive wear resistance of the material was investigated. 1. Introduction Since the mid-1980s, the processing of Functionally Graded Materials (FGMs) and structures has become an academic interest. They were developed mainly to satisfy the demand of ultra-high-temperature environment and to eliminate the stressed singularities [1]. Recently, they are also developed for various purposes such as abrasive and corrosion wear-resistant films to solve any specific tribological problem, and even emphasis on thermoelectric materials for applications in sensors and thermogenerators. Laser Engineered Net Shaping (LENS) process, as one type of rapid manufacturing technology [2], has demonstrated the capability to produce near-net shape and fully dense metallic parts [3]. This process has been used to deposit a broad range of materials, including stainless steels, nickel-based superalloys, copper alloys, and titanium alloys with enhanced physical and mechanical properties. Several studies have been conducted about fabricating FGMs, and most of them are focused on the traditional FGMs, whose graded direction is parallel to the deposition direction [4]. In this paper, attempts have been made to fabricate two patterns of Stainless Steel 316L(SS316L)/Inconel718 superalloy FGMs by LENS process, which will expand the application of the technology. Also, the microstructure characterization, composition analysis, microhardness, and abrasive wear-resistance along the graded direction are investigated. 2. Experiments In the present study, two patterns of FGM samples with compositions gradually changing from 100% (volume percent, v/o) SS316L to 100% Inconel718 are successfully fabricated (30?mm × 1?mm × 36?mm, 35?mm × 30?mm × 2?mm, resp.). Figure 1 shows the designed structures of the FGMs. Figure 1: Schematic of SS316L/Inconel718 FGMs. The LENS system (Figure 2) consists of a 1.2?kW continuous wave Nd:YAG laser (JK1002), a 3-axis numerical controlled working table, and 3-route powder feeding system. The feedstock materials are injected through a coaxial powder feeding nozzle and delivered by argon gas
The Aide Diagnosis of Cardiac Heart Diseases Using a Deoxyribonucleic Acid Based Backpropagation Neural Network
Li Shi,Zhizhong Wang,Lijia Wang,Jinying Zhang
International Journal of Distributed Sensor Networks , 2009, DOI: 10.1080/15501320802533418
Abstract: In this paper, a novel diagnostic scheme of cardiac heart diseases is presented using a Deoxyribonucleic Acid (DNA)-based BP(DNA-BP) Neural Network by distinguishing the shapes of ST segments automatically. First, wavelet transform is applied to extract the ST segments by identifying the characteristic points in the ECG. ECG signals are decomposed by aTrous Algorithm using dyadic spline wavelets. The relationship between the feature points of ECG signals and the modulus maximum pairs of the signals' wavelet transform is established, and the R-wave and ST segment's fiducial points are extracted at different wavelet scales. Second, in order to overcome the disadvantages of the BP neural network, a DNA optimization method is adopted to optimize the original weights and bias of a BP neural network. The BP algorithm is used to find the most optimal values of the weights and bias of the BP network. At last the effectiveness of the proposed aided diagnostic scheme is demonstrated via the experiments which the data are from the clinical study and MIT/BIH ECG data base. In order to validate the advantages of the DNA-based BP (DNA-BP) network and determine the best application conditions of the network, two types of experiments were conducted. In each experiment, 30 samples were selected as the training data and testing data respectively. In the first type of experiments, the data were obtained from the ECG of different people. While in the second type of experiments, the data were obtained from the ECG of one person at different times. The same data and the conditions were used in both BP and GA-based BP (GA-BP) networks to illustrate the advantages of the proposed DNA-based BP network. The experiment results illustrate that the proposed DNA-based BP network overcomes the limitation of the sloping method in identifying straight line ST segments and the limitation of function fitting method in fitting accuracy. It also surmounts the disadvantages of a BP network in terms of the local minimum, slow convergence, and the shortcomings of GA-BP in terms of its limitation in algorithm coding and evolution ways.
Nonlinear Adaptive Block Backstepping Control Using Command Filter and Neural Networks Approximation
Cao Lijia,Zhang Shengxiu,Li Xiaofeng,Liu Yinan
Information Technology Journal , 2011,
Abstract: A nonlinear adaptive block backstepping control approach is designed for a class of n-th order Multiple-input Multiple-output (MIMO) nonlinear systems with uncertainties and disturbances. The problem of explosion of complexity in traditional backstepping is avoided by using command filter to replace the differentiations of virtual control law. Radial Basis Function Neural Networks (RBF NNs) are employed to adaptively approximate the unknown nonlinear functions. The closed-loop system is guaranteed to be bounded and tracking errors are also proved to converge exponentially to a small residual set around the origin by Lyapunov approach. The nonlinear six Degrees-of-freedom (DOF) flight simulation on an Unmanned Aerial Vehicle (UAV) model is provided to demonstrate the effectiveness of the designed control scheme.
Study on Fault Detection of Rolling Element Bearing Based on Translation-Invariant Denoising and Hilbert-Huang Transform
Lijia Xu
Journal of Computers , 2012, DOI: 10.4304/jcp.7.5.1142-1146
Abstract: In order to detect rolling element bearing faults from strong background noise, a new method based on translation-invariant denoising (TID) and hilbert-huang transform (HHT) is proposed. Firstly, the original vibration signals are preprocessed using TID to suppress abnormal interference of noise to improve the decomposition quality of HHT. Secondly, the denoised signals are decomposed into a set of intrinsic mode functions (IMFs) during empirical mode decomposition (EMD) process of HHT. Hilbert spectral analysis is further played on IMFs to capture the bearing defect frequencies. The performance of the proposed method is tested, and the experiment results show that this method can effectively extract the fault features of bearing and recognize the faults successfully. So the proposed method is a good-suited technique for bearing fault detection.
Trichostatin A and 5-azacytidine both cause an increase in global histone H4 acetylation and a decrease in global DNA and H3K9 methylation during mitosis in maize
Fei Yang, Lu Zhang, Jun Li, Jing Huang, Ruoyu Wen, Lu Ma, Dongfeng Zhou, Lijia Li
BMC Plant Biology , 2010, DOI: 10.1186/1471-2229-10-178
Abstract: Treatment with trichostatin A, which inhibits histone deacetylases, resulted in increased histone H4 acetylation accompanied by the decondensation of interphase chromatin and a decrease in both global H3K9 dimethylation and DNA methylation during mitosis in maize root tip cells. These observations suggest that histone acetylation may affect DNA and histone methylation during mitosis. Treatment with 5-azacytidine, a cytosine analog that reduces DNA methylation, caused chromatin decondensation and mediated an increase in H4 acetylation, in addition to reduced DNA methylation and H3K9 dimethylation during interphase and mitosis. These results suggest that decreased DNA methylation causes a reduction in H3K9 dimethylation and an increase in H4 acetylation.The interchangeable effects of 5-azacytidine and trichostatin A on H4 acetylation, DNA methylation and H3K9 dimethylation indicate a mutually reinforcing action between histone acetylation, DNA methylation and histone methylation with respect to chromatin modification. Treatment with trichostatin A and 5-azacytidine treatment caused a decrease in the mitotic index, suggesting that H4 deacetylation and DNA and H3K9 methylation may contain the necessary information for triggering mitosis in maize root tips.The basic unit of chromatin in eukaryotes is the nucleosome, which is composed of ~146 base pairs of DNA wrapped around an octameric core of the histone molecules H2A, H2B, H3 and H4 [1,2]. The amino-terminal tails of these histones are subject to various post-translational modifications such as methylation, acetylation, phosphorylation, ubiquitination and ADP-ribosylation [3]. Various histone-modifying enzymes able to add or remove chromatin modifications, including histone acetyltransferases (HATs), histone deacetylases (HDACs) and lysine methyltransferases, have been identified [3]. In yeast, HATs and HDACs have been found to alter global histone acetylation levels over large regions of chromatin [4]. DNA itself may
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