Simultaneous spectrophotometric determination of ethinylestradiol and levonorgestrel by partial least squares and principal component regression multivariate calibration

Two spectrophotometric methods for the determination of Ethinylestradiol (ETE) and Levonorgestrel (LEV) by using the multivariate calibration technique of partial least square (PLS) and principal component regression (PCR) are presented. In this study the PLS and PCR are successfully applied to quantify both hormones using the information contained in the absorption spectra of appropriate solutions. In order to do this, a calibration set of standard samples composed of different mixtures of both compounds has been designed. The results found by application of the PLS and PCR methods to the simultaneous determination of mixtures, containing 4–11 μg ml⁻¹ of ETE and 2–23 μg ml⁻¹ of LEV, are reported. Five different oral contraceptives were analyzed and the results were very similar to that obtained by a reference liquid Chromatographic method.     

Simultaneous Kinetic‐Spectrophotometric Determination of Hydrazine and its Derivatives by Partial Least Squares and Principle Component Regression Methods

Simultaneous kinetic‐spectrophotometric determination of a ternary mixture of hydrazine (HZ) and its derivatives by principal component regression (PCR) and partial least squares (PLS) calibration is described. The methods were based on the difference observed in the reduction rate of iron(III) with HZ, thiosemicarbazide (TSCZ) and phenylhydrazine (PHZ) in the presence of 2,2′‐bipyridine (Bpy). The colored complex of [Fe(Bpy)₃]²⁺ was formed in sodium dodecyl sulfate (SDS) as micellar media, and then monitored at 520 nm. The results showed that simultaneous determination of HZ, TSCZ and PHZ could be performed in their concentration ranges of 1.0–70.0, 0.2–6.0 and 0.1–10.0 μg mL^?1, respectively. The root mean squares errors of prediction (RMSEP) of HZ, TSCZ and PHZ were 0.719, 0.164 and 0.105 (for PLS) 0.788, 0.166 and 0.993 (for PCR), respectively. Both methods (PCR and PLS) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ, TSCZ and PHZ in water samples.     

Conjugate-gradient method for computing the Moore-Penrose inverse and rank of a matrix

A conjugate-gradient method is developed for computing the Moore-Penrose generalized inverseA of a matrix and the associated projectors, by using the least-square characteristics of both the method and the inverseA . Two dual algorithms are introduced for computing the least-square and the minimum-norm generalized inverses, as well asA . It is shown that (i) these algorithms converge for any starting approximation; (ii) if they are started from the zero matrix, they converge toA ; and (iii) the trace of a sequence of approximations multiplied byA is a monotone increasing function converging to the rank ofA. A practical way of compensating the self-correcting feature in the computation ofA is devised by using the duality of the algorithms. Comparison with Ben-Israel's method is made through numerical examples. The conjugate-gradient method has an advantage over Ben-Israel's method.After having completed the present paper, the author received from Professor M. R. Hestenes his paper entitledPseudo Inverses and Conjugate Gradients. This paper treated the same subject and appeared in Communications of the ACM, Vol. 18, pp. 40–43, 1975.     

Simultaneous kinetic spectrophotometric determination of cyanide and thiocyanate using the partial least squares (PLS) regression

The partial least squares (PLS-1) calibration model based on spectrophotometric measurement, for the simultaneous determination of CN⁻ and SCN⁻ ions is described. The method is based on the difference in the rate of the reaction between CN⁻ and SCN⁻ ions with chloramine-T in a pH 4.0 buffer solution and at 30 °C. The produced cyanogen chloride (CNCl) reacts with pyridine and the product condenses with barbituric acid and forms a final colored product. The absorption kinetic profiles of the solutions were monitored by measuring absorbance at 578 nm in the time range 20-180 s after initiation of the reaction with 2 s intervals. The experimental calibration matrix for partial least squares (PLS-1) calibration was designed with 31 samples. The cross-validation method was used for selecting the number of factors. The results showed that simultaneous determination could be performed in the range 10.0-900.0 and 50.0-1200.0 ng mL⁻¹ for CN⁻ and SCN⁻ ions, respectively. The proposed method was successfully applied to the simultaneous determination of cyanide and thiocyanate in water samples.     

Differential Pulse Voltammetric Simultaneous Determination of Four Anti‐Inflammatory Drugs by Using Soft Modelling

An application of a partial least squares calibration method for the simultaneous voltammetric determination of indomethacin, acemethacin, piroxicam and tenoxicam is suggested. It was shown that it is possible to resolve complex mixtures of analytes even when they have strongly overlapped signals. In order to check the proposed method, statistical analysis of the results was performed by mean of hypothesis tests. The method developed was applied to the electrochemical reduction region of four anti‐inflammatory drugs and allowed the drugs to be quantified at concentrations between 0.52 and 4.09 μg mL^?1 for acemethacin, 0.44 and 3.50 μg mL^?1 for indomethacin, 0.43 and 3.40 μg mL^?1 for piroxicam, and 0.42 and 3.30 μg mL^?1 for tenoxicam with good results. The average absolute value of relative errors was 2.25%, 4.31%, 1.68% and 2.49%, respectively.     

LapRLSR for NIR spectral modeling and its application to online monitoring of the column separation of Salvianolate

A novel near infrared (NIR) modeling method—Laplacian regularized least squares regression (LapRLSR) was presented, which can take the advantage of many unlabeled spectra to promote the prediction performance of the model even if there are only few calibration samples. Using LapRLSR modeling, NIR spectral analysis was applied to the online monitoring of the concentration of salvia acid B in the column separation of Salvianolate. The results demonstrated that LapRLSR outperformed partial least squares (PLS) significantly, and NIR online analysis was applicable.     

用于紫外光谱水质分析的Boosting-偏最小二乘法

为提高水质参数总有机碳(TOC)的紫外吸收光谱分析的预测精度,提出一种基于Boosting理论的迭代式回归建模算法,并根据统计学习理论提出一种新的迭代停止判据,可有效防止过拟合,显著提高模型预测精度。为评估所提算法的性能,分别采用本算法和3种常用的光谱分析方法,即偏最小二乘、主成分回归和人工神经网络,对自行研制的紫外光谱水质分析仪实测的一组数据进行了建模和预测。计算结果表明:相对于其他3种方法,本算法具有生成的模型预测精度高的显著优势。     

Prediction of intracellular storage polymers using quantitative image analysis in enhanced biological phosphorus removal systems

The present study focuses on predicting the concentration of intracellular storage polymers in enhanced biological phosphorus removal (EBPR) systems. For that purpose, quantitative image analysis techniques were developed for determining the intracellular concentrations of PHA (PHB and PHV) with Nile blue and glycogen with aniline blue staining. Partial least squares (PLS) were used to predict the standard analytical values of these polymers by the proposed methodology. Identification of the aerobic and anaerobic stages proved to be crucial for improving the assessment of PHA, PHB and PHV intracellular concentrations. Current Nile blue based methodology can be seen as a feasible starting point for further enhancement. Glycogen detection based on the developed aniline blue staining methodology combined with the image analysis data proved to be a promising technique, toward the elimination of the need for analytical off-line measurements.