Determination of amoxicillin in pharmaceuticals using sequential injection analysis and multivariate curve resolution

In this study, we report a method for quantifying amoxicillin in pharmaceuticals in the presence of interferents using sequential injection analysis (SIA) with a diode-array spectrophotometric detector and multivariate curve resolution with alternating least squares (MCR-ALS). With a suitable analytical sequence, we can use SIA to generate a pH gradient and, for each sample, obtain a data matrix. We used augmented matrices to resolve the system and obtain the spectra and concentration profiles of the components in the sample.We studied what are the effects of imposing trilinearity at the resolution stage, how to choose the species that will be used for quantification (acid, basic or the sum of the two), and which is the most suitable concentration of the reference standard. Once the optimum conditions were established, we performed the quantification in three amoxicillin-containing pharmaceuticals (flubiotic, augmentine, and clamoxyl). With this method, determination is quick, the reactants and instrumentation are inexpensive, and pretreatment of the sample is unnecessary.     

1H NMR and UV-visible data fusion for determining Sudan dyes in culinary spices

Two data fusion strategies (variable and decision level) combined with a multivariate classification approach (Partial Least Squares-Discriminant Analysis, PLS-DA) have been applied to get benefits from the synergistic effect of the information obtained from two spectroscopic techniques: UV-visible and ¹H NMR. Variable level data fusion consists of merging the spectra obtained from each spectroscopic technique in what is called “meta-spectrum” and then applying the classification technique. Decision level data fusion combines the results of individually applying the classification technique in each spectroscopic technique. Among the possible ways of combinations, we have used the fuzzy aggregation connective operators. This procedure has been applied to determine banned dyes (Sudan III and IV) in culinary spices. The results show that data fusion is an effective strategy since the classification results are better than the individual ones: between 80 and 100% for the individual techniques and between 97 and 100% with the two fusion strategies.     

Analytical applications of second-order calibration methods

Second-order calibration methods are gaining widespread acceptance among the analytical community mainly because: (1) a wide range of analytical instrumentation is available that enables high dimensionality data to be obtained; (2) the chemometric techniques for treating these data are highly developed; and (3) they have the so-called “second-order advantage”, i.e. they can predict the concentration of the analyte of interest even in the presence of unknown interferents. This also enables several analytes to be determined simultaneously.In this paper we describe the most common instrumental and chemometric techniques used in second-order calibration and discuss their applications since 2000. First, we introduce briefly the techniques and then we comment the applications. Given the practical nature of this paper, we have classified the techniques according to five fields of application: pharmaceuticals, biological matrices, foods, environmental matrices and synthetic matrices.     

Conservative methods for the Toda lattice equations

We are concerned with the numerical integration of the Todalattice equations by using different conservative methods. Numericalexperiments suggest that the global error for isospectral schemesdecreases exponentially with time but it is almost constantfor either symplectic or more general integrators. We providea theoretical explanation for these experimental findings.