[Objective]The aim was to analyze the primary speciation of 6 microelements in Glycyrrhiza uralensis Fisch. and provide theoretical basis for explaining pharmacodynamic principle of liquorice and discussing quality co...[Objective]The aim was to analyze the primary speciation of 6 microelements in Glycyrrhiza uralensis Fisch. and provide theoretical basis for explaining pharmacodynamic principle of liquorice and discussing quality control of liquorice planting. [Method]The 6 elements Cu,Zn,Ca,Fe,Mg and Mn in roots of G.uralensis were extracted based on traditional decoction method and were separated into water-soluble state and suspension state by micro porous filtering film. The elements in water-soluble state were detected by flame atomic adsorption spectrophotometry （FAAS）. [Result]The results showed that extractive rates of the elements were in the range of 1.71%-60.06%,and immerse-residue ratio in 0.018 3-1.682 0; the results also indicated that the immerse-residue ratio of Zn was biggest （1.68）,Zn played an important medical role and might be considered as the best characteristic element in G.uralensis; the recoveries of the elements were ranged from 95.72% to 103.15% and relative standard deviations （RSD） were less than 2.38%. [Conclusion]Because of its high accuracy,FAAS method is feasible for analyzing primary speciation of microelements in G.uralensis.展开更多
Computer forensics and identification for traditional Chinese painting arts have caught the attention of various fields. Rice paper＇s feature extraction and analysis methods are of high significance for the rice pape...Computer forensics and identification for traditional Chinese painting arts have caught the attention of various fields. Rice paper＇s feature extraction and analysis methods are of high significance for the rice paper is an important carrier of traditional Chinese painting arts. In this paper, rice paper＇s morphological feature analysis is done using multi spectral imaging technology. The multispectral imaging system is utilized to acquire rice paper＇s spectral images in different wave- length channels, and then those spectral images are measured using texture parameter statistics to acquire sensitive bands for rice paper＇s feature. The mathematical morphology and grayscale statistical principle are utilized to establish a rice paper＇s morphological feature analytical model which is used to acquire rice paper＇ s one-dimensional vector. For the purpose of eval- uating these feature vectors＇ accuracy, they are entered into the support vector machine（SVM） classifier for detection and classification. The results show that the rice paper＇s feature is out loud in the spectral band 550 nm, and the average classifi- cation accuracy of feature vectors output from the analytical model is 96 %. The results indicate that the rice paper＇s feature analytical model can extract most of rice paper＇s features with accuracy and efficiency.展开更多
Modern opticai theory has shown that the far field or Fraunbofer diffraction equipment is identical to the Fourier spectral analyzer. In the Fourier speetral analyzer the Fourier spectra or the Fraunhofer diffaction p...Modern opticai theory has shown that the far field or Fraunbofer diffraction equipment is identical to the Fourier spectral analyzer. In the Fourier speetral analyzer the Fourier spectra or the Fraunhofer diffaction pattern of a graph is formed on the back focal plane when a laser beam is directed on the graph lying on the front foeal plane ; the Fourier spectra of the graph is also subjected to change during the deformation of the graph. Through analyzing the change of Fourier spectra the deformation of the graph can be obtained. A few years ago,based on the above principles the authors proposed a new technique of strain measurement by laser spectral analysis. Demonstration and discussion will be made in detail in this paper.展开更多
基金Supported by National Natural Science Foundation of China(30600806)Science and Technology Project of Higher Education of Ningxia Hui Autonomous Region (NJ0626)~~
文摘[Objective]The aim was to analyze the primary speciation of 6 microelements in Glycyrrhiza uralensis Fisch. and provide theoretical basis for explaining pharmacodynamic principle of liquorice and discussing quality control of liquorice planting. [Method]The 6 elements Cu,Zn,Ca,Fe,Mg and Mn in roots of G.uralensis were extracted based on traditional decoction method and were separated into water-soluble state and suspension state by micro porous filtering film. The elements in water-soluble state were detected by flame atomic adsorption spectrophotometry （FAAS）. [Result]The results showed that extractive rates of the elements were in the range of 1.71%-60.06%,and immerse-residue ratio in 0.018 3-1.682 0; the results also indicated that the immerse-residue ratio of Zn was biggest （1.68）,Zn played an important medical role and might be considered as the best characteristic element in G.uralensis; the recoveries of the elements were ranged from 95.72% to 103.15% and relative standard deviations （RSD） were less than 2.38%. [Conclusion]Because of its high accuracy,FAAS method is feasible for analyzing primary speciation of microelements in G.uralensis.
基金University-Industry-Science Partnership Project of Guangdong Province and Ministry of Education,China(No.2012B091000155)Strategic Emerging Industries Project of Guangdong Province(No.2011912027)
文摘Computer forensics and identification for traditional Chinese painting arts have caught the attention of various fields. Rice paper＇s feature extraction and analysis methods are of high significance for the rice paper is an important carrier of traditional Chinese painting arts. In this paper, rice paper＇s morphological feature analysis is done using multi spectral imaging technology. The multispectral imaging system is utilized to acquire rice paper＇s spectral images in different wave- length channels, and then those spectral images are measured using texture parameter statistics to acquire sensitive bands for rice paper＇s feature. The mathematical morphology and grayscale statistical principle are utilized to establish a rice paper＇s morphological feature analytical model which is used to acquire rice paper＇ s one-dimensional vector. For the purpose of eval- uating these feature vectors＇ accuracy, they are entered into the support vector machine（SVM） classifier for detection and classification. The results show that the rice paper＇s feature is out loud in the spectral band 550 nm, and the average classifi- cation accuracy of feature vectors output from the analytical model is 96 %. The results indicate that the rice paper＇s feature analytical model can extract most of rice paper＇s features with accuracy and efficiency.
文摘Modern opticai theory has shown that the far field or Fraunbofer diffraction equipment is identical to the Fourier spectral analyzer. In the Fourier speetral analyzer the Fourier spectra or the Fraunhofer diffaction pattern of a graph is formed on the back focal plane when a laser beam is directed on the graph lying on the front foeal plane ; the Fourier spectra of the graph is also subjected to change during the deformation of the graph. Through analyzing the change of Fourier spectra the deformation of the graph can be obtained. A few years ago,based on the above principles the authors proposed a new technique of strain measurement by laser spectral analysis. Demonstration and discussion will be made in detail in this paper.
