基于遗传算法优化的约束背景双线性分解算法用于改进高效液相色谱灰色分析体系的校正结果

该文采用约束背景双线性分解算法(CBBL)对以高效液相色谱(HPLC)方法分离分析的灰色分析体系进行了多元校正研究。针对采用包括CBBL在内的矩阵校正方法处理HPLC灰色分析体系的固有缺陷,即在相关组分的色谱保留时间重现性较低的情形下多元校正的结果不理想,对CBBL方法进行了改进,即将待测组分的浓度与组分的色谱保留时间同时作为优化的参量引入CBBL,并采用遗传算法(GA)优化CBBL,对于模拟的组分保留时间飘移严重的HPLC灰色分析体系及保留时间重现性不佳的多种酚类化合物组成的实际HPLC灰色分析体系进行了多元校正分析,成功克服了经典CBBL的固有缺陷,取得了较理想的多元校正结果。另外,该研究所建议的方法的校正结果也显著优于传统的残差双线性分解法(RBL)以及秩消失因子分析法(RAFA)。     

Quality control of cosmetic mixtures by NIR spectroscopy

Cosmetic preparations typically consist of mixtures of various compounds of natural origin or their derivatives. Their analysis is made rather difficult by their usually high complexity and is utterly impossible with a single analytical method; also, there is usually little to be gained by determining every individual component of the mixture. Rather, analyses are aimed at ensuring a proper balance between the contents of each component and thus require the use of methods capable of delivering global information. The combined use of near-infrared (NIR) spectroscopy and multivariate spectral processing chemometric techniques has enabled the development of effective methods for establishing the composition of complex samples with acceptable levels of analytical properties, such as accuracy, precision and throughput. In this work, we developed partial least squares calibration models for the determination of each component in a cosmetic mixture, and global indices (viz. the hydroxyl value), simply from the NIR spectrum of the sample. The models thus obtained are accurate enough for use in quality control analyses of cosmetic preparations and provide an effective alternative to existing conventional global methods. Experimental setup for measurement     

Speciation of antimony by adsorptive stripping voltammetry using pyrogallol

This paper describes a new procedure for the determination of Sb (III) and Sb (V) by differential pulse adsorptive stripping voltammetry (DPAdSV) using pyrogallol as a complexing agent. The selection of the experimental conditions was made using experimental design methodology. The detection limits obtained were 1.03 × 10⁻¹⁰ and 9.48 × 10⁻⁹ mol dm⁻³ for Sb (III) and Sb (V), respectively.In order to carry out the simultaneously determination of both antimony species a partial least squares regression (PLS) is employed to resolve the voltammetric signals from mixtures of Sb (III) and Sb (V) in the presence of pyrogallol. The relative error in absolute value is less than 0.5% when concentrations of several mixtures are calculated. Moreover, the solution is analyzed for any possible effects of foreign ions. The procedure is successfully applied to the speciation of antimony in pharmaceutical preparations and water samples.     

Improvement of prediction ability of PLS models employing the wavelet packet transform: A case study concerning FT-IR determination of gasoline parameters

The wavelet packet transform (WPT) is a variant of the standard wavelet transform that offers greater flexibility in the decomposition of instrumental signals. Although encouraging results have been published concerning the use of WPT for signal compression and denoising, its application in multivariate calibration problems has received comparatively little attention, with very few contributions reported in the literature. This paper presents an investigation concerning the use of WPT as a feature extraction tool to improve the prediction ability of PLS models. The optimization of the wavelet packet tree is accomplished by using the classic dynamic programming algorithm and an entropy cost function modified to take into account the variance explained by the WPT coefficients. The selection of WPT coefficients for inclusion in the PLS model is carried out on the basis of correlation with the dependent variable, in order to exploit the joint statistics of the instrumental response and the parameter of interest. This WPT-PLS strategy is applied in a case study involving FT-IR spectrometric determination of four gasoline parameters, namely specific mass (SM) and the distillation temperatures at which 10%, 50%, 90% of the sample has evaporated. The dataset comprises 103 gasoline samples collected from gas stations and 6144 wavelengths in the range 2500-15000 nm. By applying WPT to the FT-IR spectra, considerable compression with respect to the original wavelength domain is achieved. The effect of varying the wavelet and the threshold level on the prediction ability of the resulting models is investigated. The results show that WPT-PLS outperforms standard PLS in most wavelet-threshold combinations for all determined parameters.     

Analysis of amoxicillin in human urine by photo-activated generation of fluorescence excitation-emission matrices and artificial neural networks combined with residual bilinearization

Fluorescence excitation-emission data recorded for amoxicillin after photo-activated reaction with periodate have been processed by a novel second-order multivariate method based on the combination of artificial neural networks and residual bilinearization (ANN/RBL), since the signals bear a strong non-linear relation with the analyte concentration. The selected chemometric methodology is employed for the first time to evaluate experimental non-linear second-order spectral information. Due to severe overlapping between the emission profiles for the analyte reaction product and for the urine background, calibration was done using different spiked urine samples. This allowed for the determination of amoxicillin in test spiked urines, other than those employed for calibration. When new urine samples containing a fluorescent anti-inflammatory were analyzed, accurate prediction in the presence of unexpected components required the achievement of the second-order advantage, which is provided by the post-training RBL procedure. Amoxicillin was also determined by ANN/RBL in a series of real urine samples, which allowed one to perform a comparison study with the reference high-performance liquid chromatographic technique.     

Complete quality analysis of commercial surface-active products by Fourier-transform near infrared spectroscopy

Using proper calibration data Fourier-transform near infrared spectroscopy is used for developing multivariate calibrations for different analytical determinations routinely used in the surfactants industry. Four products were studied: oleyl-cetyl alcohol polyethoxylated, cocamidopropyl betaine (CAPB), sodium lauryl sulfate (SLS) and nonylphenol polyethoxylated (NPEO). Calibrations for major as well as very low concentrated compounds were achieved and every model was validated through linearity, bias, accuracy and precision tests, showing good results and the viability of NIR spectroscopy as a full quality control method for this products. Duplicate and complete analysis on a single sample takes at most 3 min, requiring neither sample preparation nor the use of reagents. The analytical reference procedures involved in this work represent the typical ones used in the industry and the NIR method shows good results in the analysis of components with weight concentrations less than 1%.     

三维荧光二阶校正法用于尿液样和血浆样中左旋多巴的定量测定

本文采用激发发射荧光光谱分别与化学计量学中平行因子分析(PARAFAC)和交替三线性分解(ATLD)二阶校正法相结合,对尿液样和血浆样中左旋多巴含量进行定量测定。实验不需对尿液和血浆预测样进行萃取等分离预处理。在尿液样中,当组分数取2时,用PARAFAC算法和ATLD算法获得的平均回收率分别为(98.9±2.3)%和(99.6±2.8)%。在血浆样中,当组分数取3时,PARAFAC算法和ATLD算法获得的平均回收率分别为(103.1±3.7)%和(99.2±4.2)%。研究结果表明,该法能够解决尿液样和血浆样中左旋多巴因尿液和血浆内源物质与待分析物光谱重叠所引起的难分辨的问题,可用于未知干扰共存下左旋多巴含量的直接快速定量测定。     

Integration of Commercial Screen‐printed Electrodes into a Voltammetric Electronic Tongue for the Analysis of Aminothiols

A voltammetric sensor array (or electronic tongue) is developed for the simultaneous quantification of cysteine, glutathione and homocysteine without need of previous separation. It is based on the integration of three commercial screen‐printed electrodes (gold curated at high and low temperature and carbon modified with carbon nanotubes). Linear sweep voltammograms measured simultaneously by all three sensors are processed by Partial Least Squares (PLS) regression and different variables selection algorithms such as Genetic Algorithm and interval‐Partial Least Squares. The method was applied to synthetic mixtures and successfully validated, with correlation coefficients of prediction (R_p²) of 0.9542, 0.9429 and 0.9589 for cysteine, glutathione, and homocysteine respectively.     

多元校正-光度法同时测定食品中的香兰素和乙基麦芽酚

香兰素、乙基麦芽酚在紫外区均有吸收,其吸收光谱严重重叠。在pH=2．87的B-R缓冲溶液中对香兰素和乙基麦芽酚两组分混合溶液进行光度测定,所得重叠光谱数据分别用经典最小二乘法(CLS)、偏最小二乘法(PLS)、主成分回归法(PCR)处理,并用于食品样品的测定,获得了较好的定量分析结果。香兰素和乙基麦芽酚的线性范围均为1．0～20．0mg／L;检出限分别为0．478mg／L和0．559mg／L。