Multicomponent Kinetic Determination by Wavelet Packet Transform Based Elman Recurrent Neural Network Method

This paper covers a novel method named wavelet packet transform based Elman recurrent neural network(WPTERNN) for the simultaneous kinetic determination of periodate and iodate. The wavelet packet representations of signals provide a local time-frequency description, thus in the wavelet packet domain, the quality of the noise removal can be improved. The Elman recurrent network was applied to non-linear multivariate calibration. In this case, by means of optimization, the wavelet function, decomposition level and number of hidden nodes for WPTERNN method were selected as D4, 5 and 5 respectively. A program PWPTERNN was designed to perform multicomponent kinetic determination. The relative standard error of prediction(RSEP) for all the components with WPTERNN, Elman RNN and PLS were 3.23%, 11.8% and 10.9% respectively. The experimental results show that the method is better than the others.

SIMULTANEOUS DETERMINATION OF MULTICOMPONENT IN MIXED ACIDS BY MATHEMATICAL METHOD

A new method for the determination of components in mixed acids has been developed.The mathematical model is obtained from samples of known composition and is then used to predict the concentrations of components in unknown sample.The practical utility of this method is demonstrated for simultaneous determination of two systems of ternary mixed acids and the results are satisfactory.

Simultaneous determination of seven caffeoylquinic acids and three flavonoids in Pyrrosia petiolosa(Christ) Ching by RP-UFLC-DAD

An efficient, sensitive, accurate and rapid analytical ultra-fast liquid chromatography （UFLC） method for quality evaluations ofPyrrosia petiolosa （Christ） Ching from 20 regions of China was developed in this study. Ten marker compounds were simultaneously quantified, including 5-caffeoylquinic acid （5-CQA）, 3-caffeoylquinic acid （3-CQA）, 4-caffeoylquinic acid （4-CQA）, 1-caffeoylquinic acid （1-CQA）, 3,5-dicaffeoylquinic acid （3,5-diCQA）, 4,5-dicaffeoylquinic acid （4,5-diCQA）, 3,4-dicaffeoylquinic acid （3,4-diCQA）, astragalin, kaempferol-3,7-di-O-glucoside and （±）eriodictyol-7-O-β-D-glucuronide. Chromatography was performed on a Kromasil 100-2.5C18 （100 mm×2.1 mm, 2.5 μm） C18 column with gradient elution. The mobile phases consisted of 0.1% formic acid/water （A） and 0.1% formic acid/methanol （B）. The detection wavelength was set at 326 nm and the flow rate was 0.4 mL/min. Ten components were separated well with good linearity （r2〉0.9998）, precision, repeatability, stability. The recovery was in the range of 99.08%-102.77%. The results showed that the content determination using RP-UFLC-DAD fingerprint technique provides an efficient, sensitive, accurate and rapid analytical method for quality assessment ofP. petiolosa （Christ） Ching. Cluster analysis and principal components analysis were successfully applied to analyze 20 samples, the results revealed that the method was efficient and authentic to distinguish producing areas and the source of P. petiolosa （Christ） Ching. Keywords： Pyrrosiapetiolosa （Christ） Ching, Caffeoylquinic acids, Flavonoids, Multicomponent determination, UFLC