A novel trilinear decomposition algorithm： Three-dimension non-negative matrix factorization

Non-negative matrix factorization(NMF)is a technique for dimensionality reduction by placing non-negativity constraints onthe matrix.Based on the PARAFAC model,NMF was extended for three-dimension data decomposition.The three-dimension non-negative matrix factorization(NMF3)algorithm,which was concise and easy to implement,was given in this paper.The NMF3algorithm implementation was based on elements but not on vectors.It could decompose a data array directly without unfolding,which was not similar to that the traditional algorithms do.It has been applied to the simulated data array decomposition andobtained reasonable results.It showed that NMF3 could be introduced for curve resolution in chemometrics.     

化学计量学研究及其应用

本文介绍了化学计量学的产生、发展、研究内容及主要应用,对有关工作进行了评述。     

电分析化学中的化学计量学方法及其应用进展

本文综述了电分析化学领域中化学计量学方法的应用进展，引用文献65篇。     

Detection of soil pollution by hydrocarbons using headspace-mass spectrometry and identification of compounds by headspace-fast gas chromatography-mass spectrometry

The direct coupling of a headspace sampler with a mass spectrometer is proposed as a screening tool for the rapid detection of soil pollution by hydrocarbons from petroleum and derivatives. The samples are subjected to the headspace generation process, with no prior treatment, and the volatiles generated are introduced directly into the mass spectrometer, thereby obtaining a fingerprint of the sample analysed. Suitable treatment of the signal by chemometric techniques allows unequivocal characterisation of the different types of sample. The use of fast gas chromatography with a mass spectrometer detector coupled to the headspace sampler allows identification of the major hydrocarbons present in the mineral and organic polluted samples, interpretation of the results obtained, and demonstrates the analytical potential of headspace-mass spectrometry coupling.     

A computer program for searching the best model for describing different experimental systems

An algorithm for searching the best polynomial analytical function for describing different experimental systems is presented. It is based

1. (1)on the generation of all possible analytical functions of a given order, with a given number of terms and with a given number of independent variables, and

2. (2)on the calculation of the parameters of all selected functions using the linear regression method.

To show the ability of the program two different examples are given:

1. (1) searching the best univariate polynomial model, and

2. (2) modelling of the stability of a two-component mixture as a function of three factors.

Quantitative determination of Malathion in pesticide by modified attenuated total reflectance-Fourier transform infrared spectrometry applying genetic algorithm wavelength selection method

A simple and environment friendly method was developed for determination of Malathion content of analytical and commercial insecticide samples with no special preparation. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectra were characterized and 1000-2000 cm⁻¹ region was selected for quantitative analysis utilizing partial least square (PLS) and two wavelength selection methods: (a) principal component regression (PCR) and (b) genetic algorithm (GA). Relative error of prediction (REP) was calculated in PLS, PCR-PLS and GA-PLS methods and was 3.536, 1.656 and 0.188, respectively. Proposed method is successfully applicable for quantification of Malathion in commercial grade samples and reliable results in comparison with known methods, confirms this idea.     

Mineral content and botanical origin of Spanish honeys

Eleven elements (Zn, P, B, Mn, Mg, Cu, Ca, Ba, Sr, Na and K) were determined by inductively plasma coupled spectrometry in 40 honey samples from different places of Spain and four different botanical origins: Eucalyptus (Eucalyptus sp.), Heather (Erica sp.), Orange-blossom (Citrus sinensis) and Rosemary (Rosmarinus officinalis). K, Ca and P show the higher levels with average concentrations ranged between 434.1-1935 mg kg⁻¹ for K; 42.59-341.0 mg kg⁻¹ for Ca and 51.17-154.3 mg kg⁻¹ for P. Levels of Cu (0.531-2.117 mg kg⁻¹), Ba (0.106-1.264 mg kg⁻¹) and Sr (0.257-1.462 mg kg⁻¹) are the lowest in all honey samples. Zn (1.332-7.825 mg kg⁻¹), Mn (0.133-9.471 mg kg⁻¹), Mg (13.26-74.38 mg kg⁻¹) and Na (11.69-218.5 mg kg⁻¹) concentrations were found strongly dependent on the kind of botanical origin.Results were submitted to pattern recognition procedures, unsupervised methods such as cluster and principal components analysis and supervised learning methods like linear discriminant analysis in order to evaluate the existence of data patterns and the possibility of differentiation of Spanish honeys from different botanical origins according to their mineral content. Cluster analysis shows four clusters corresponding to the four botanical origins of honey and PCA explained 71% of the variance with the first two PC variables. The best-grouped honeys were those from heather; eucalyptus honeys formed a more dispersed group and finally orange-blossom and rosemary honeys formed a less distinguishable group.     

Explorative data analysis of two-dimensional electrophoresis gels

Methods for classification of two-dimensional (2-DE) electrophoresis gels based on multivariate data analysis are demonstrated. Two-dimensional gels of ten wheat varieties are analyzed and it is demonstrated how to classify the wheat varieties in two qualities and a method for initial screening of gels is presented. First, an approach is demonstrated in which no prior knowledge of the separated proteins is used. Alignment of the gels followed by a simple transformation of data makes it possible to analyze the gels in an automated explorative manner by principal component analysis, to determine if the gels should be further analyzed. A more detailed approach is done by analyzing spot volume lists by principal components analysis and partial least square regression. The use of spot volume data offers a mean to investigate the spot pattern and link the classified protein patterns to distinct spots on the gels for further investigation. The explorative approach in analysis of 2-D gels makes it possible, in a fast and convenient way, to screen many gels in order to determine the protein patterns that form clusters and could be selected for further examination.     

速差动力学分析及其应用进展

速差动力学分析是不经分离同时或连续测定混合物中性质密切相关的多组份的重要方法。本文综述了该法在１９８９－１９９２年间国内外新进展，尤着重其在有机，生物混合物中多组份分析的应用及新的计算方法，化学计量学的引入。引用最新文献６７篇。