Chemical Pattern Recognition And Multi-way Calibration Methodologies And Their Applications To Complex System Analysis

With the rapid development of modern science and technology, a large number of new multi-channel even high-order analytical instruments are emerging, The application system become more and more complex, analytical chemistry researchers are faced with many problems such as two-dimensional, three-dimensional and even four-dimensional data arrays rather than just simple scalar or vector response data analysis. Development of chemometrics theoretic can provide various efficaciously methods for extracting useful chemical information from these complexity data arrays, thereinto, chemical pattern recognition and multi-way calibration are two important research areas. The research work in this thesis mainly focuses on these methodologies and their applications for two-way data, three-way data analysis and four-way data analysis of complex chemical systems. Study works presented in the thesis primarily deal with the following aspects:1 Chemical pattern recognition methods and near infrared spectroscopy for quality analysis and discrimination of Chinese medicines (Chapter 2 to Chapter 3):The qualitay of traditional Chinese herbs are not only closely related to geographical origins but also affected by adulteration, while the quality of Chinese traditional medicine preparation processed are closely related to not only the raw Chinese herbs but also the technological process of the medicine production in various manufacturers. Therefore, discrimination of genuineness, geographical origins and production manufactures of Chinese herbs is a significant aspect of the quality control of traditional chinese medicine, where chemical pattern recognition methods are frequently used to extract relevant information from near infrared reflectance (NIR) spectral data and provide an alternative criterion for identification and quality control of traditional chinese medicine. Move windowns partial least square discriminate anaysis (MWPLSDA) is proposed to treat fingerprints of different kinds of bezoar samples and Liuwei Dihuang Pills from different manufacturers by NIR spectroscopy. The results demonstrate that MWPLSDA is superior to some conventional linear pattern recognition methods including PCA, LDA and MWPLSDA, and it could remove non-class-related wavelength regions and other uninformative non-composition-related factors, hereby is more effective to treat NIR spectral fingerprint information of these samples. MWPLSDA is a feasible and promising method for quality control and discrimination of traditional Chinese medicine.2 First-order calibration: new algorithm and multivariate spectal anaysis (Chapter 4):Least squares-support vector machine (LS-SVM) has been introduced into first-order calibration by some investigators for its attractive features and promising empirical performance. However, the performance of LS-SVM is strongly dependent upon the uniformity of the training data and the homogeneity of the model errors. To ensure the applicability of the developed model to unknown samples, the representation of training samples and the concept of weighted sampling for multivariate specral anaysis are considered. However, due to the high-dimensionality and complexity of spectral data space and the uncertainty involved in sampling process, the representation of training samples in the whole sample space is difficult to evaluate and select representative training samples for multivariate calibration, which depends largely on experiential methods. If the training samples fail to represent the sample space, the predictions of new samples can be degraded. In order to solve this problem, an intelligentized algorithm called optimized sample-weighted LS-SVM (OSWLS-SVM) by incorporating weighted sampling into LS-SVM is suggested to solve the problem of the representation of samples. PSO is used to search for multiple parameters of OSWLS-SVM model including the best non-negative sample-weighting vectors as an optimized rescaling of the samples in certain sense and LS-SVM hyper-parameters to simultaneously optimize calibration of the original training set and prediction of an independent validation set. Three real data sets are investigated and the results demonstrated that OSWLS-SVM models can improve the ability of prediction for a model when the representation of original calibration samples is poor. Moreover, the stability and efficiency of OSWLS-SVM is also surveyed, the results revealed that the proposed method could obtain desirable results within moderate PSO cycles. The overall conclusion is that OSWLS-SVM is a promising multivariate calibration method for more practical applications, especially when the data may encounter some factors including non-uniformly distributed samples, heteroscedastic noises and so on. The algorithm is universal, so it also can be used to improve the other first-order calibration algorithms.3 Second-order calibration and three-dimensional fluorescence for direct or indirect quantification of drugs in body fluids (Chapter 5 to Chapter 6):Drug analysis in body fluids is an important one in biomedical field. Chromatographic separation techniques are usually used in drug analysis. However, HPLC inherently suffer from tedious pretreation and optimization of the separate conditions, even possible lower recoveries owing to the greater loss of sample during the more intensive extraction and clean-up. An alternative strategy for simple, rapid and sensitive quantification of drug in biological body fluids is excitation-emission matrix (EEM) fluorescence with the aide of second-order calibration methodologies based on PARAFAC and ANWE. EEM data of CPT-11 in biological matrixs shows a trilinear structure that were mathematically decomposed to make serious overlapped peaks into their pure spectral profiles and concentration profiles with the aid of second-order advantage based on second-order calibration algorithms. The method was presented with the potential advantages of rapid, green and low cost for the highly sensitive quantification of CPT-11 in human body fluid samples. Moreover, the second-order calibration methods combined with the excitation-emission matrix fluorescence based on enhance or derivatization were developed to analyze metoclopramide with isogenous interferer in plasma samples, and meloxicam in human urine samples. This is an attractive alternative strategy for indirectly determine other the kinds of medicines without fluorescence in more complex system.4 New third-order calibration algorithms (Chapter7 to Chapter 8):The use of higher-order data for the resolution of complex analytical problems will increase in the near future, due to the associated advantages. This calls for appropriate chemometric methods for calibrating with data structures of higher complexity. Four-way data arrays are used to construct quantitative calibration models only in a few cases, because the related theories on four-way calibration analysis are still immature, it is very significative to further study more related theories and applications for exploring advantages of four-way calibration analysis.A novel third-order calibration algorithm, Alternating Weighted Residue Constraint Quadrilinear Decomposition (AWRCQLD) algorithm is developed to analyze four-way data arrays. To our knowledge, not-fully stretched matrix forms of quardilinear model were first employed to design quadrilinear decomposition algorithm. the AWRCQLD algorithm is based on the new scheme that introduces the four unique weighted residual functions as constrain parts to fit loss fuction of quardilinear model. Simulation and the experimental data are arranged and analyzed in both forms of three-way data arrays and four-way data arrays to explore additional third-order advantage differing from second-order advantage. Meanwhile, performance of the proposed algorithm has been compared with that of four-way PARAFAC and APQLD. The results demonstrated third-order advantages lie in that more inherent information can be obtained from data for improving the resolved and quantitative capability of trilinear second-order calibration especially in serious high collinear system. It means that four-way data array is not a simple collection of three-way data array, it have unique internal relations in each three-way data arrays. Moreover, compared with four-way PARAFAC, the new algorithm AWRCQLD has the advantages of fast convergence and being insensitive to the excess component number used in the model. Compared with APQLD, AWRCQLD has better capability of anti-highnoise. This predominant features will facilitate the analysis of four-way data arrays.Discovery of second-order advantage, it great impeled development of chemometrics. Let's make a prediction, third-order advantage would eventually emerge in more paractical application. This calls for more chemometric methods for calibrating with data structures of higher complexity. Based on not fully stretched matrix form of the quadrilinear model, a new algorithm called self restrain alternating quadrilinear decomposition (SRAQLD) algorithm is developed to exploit the solution. The objective functions with strong intrinsic relationship were constructed, where the two loss functionS in the every objective function are optimized and constrained mutually. A new approach to quantification even in presence of a matrix effect caused by the background. The excitation-emission matrix (EEM) fluorescence determination of chlorpromazine in a hunman plasma used to show the ineffectiveness of second-order calibration and the second-order standard addition method in these conditions in spite of the trilinear model fitted with the experimental tensor. Therefore, it is the alteration of the fluorescence quantum yield by changing the levels of matrix plasma quantity providing a four-way tensor which let us the determination of chlorpromazine concentration. The four third-order calibration methods based on PARAFAC, APQLD, AWRCQLD and SRAOLD, respectively, are tested with suitable results, which are slight better for proposed SRAQLD in this system. Moreover, proposed AWRCQLD can be expected to play its advantage in other system with low-signal rate. Undoubtedly, more practical study should be implemented to continually explore and recognize the third-order calibration. In adition, the research work provided the theory and reference for studying more new thid-order calibration methods in the further.