Alejandro C. Olivieri

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The analytical performances of two algorithms, the recently introduced bilinear least-squares (BLLS) and the popular parallel factor analysis (PARAFAC), are compared as regards second-order fluorescence data recorded for the determination of the fluoroquinolone antibiotic ciprofloxacin in human urine samples. The applied chemometric methodologies employ(More)
The loading of albendazole into biodegradable polymeric microparticles provides an attractive alternative to improve the drug dissolution rate. Experimental design and optimization techniques were implemented for the development of albendazole-chitosan microparticles using the ionic interaction method. The effect of seven different factors (chitosan(More)
Four-way data were obtained by recording the kinetic evolution of excitation-emission fluorescence matrices for samples containing the analytes carbaryl and 1-naphthol, two widely employed pesticides, in the concentration ranges 0-363 μg L(-1) and 0-512 μg L(-1), respectively. The reaction followed was the alkaline hydrolysis of carbaryl to produce(More)
A new variable selection algorithm is described, based on ant colony optimization (ACO). The algorithm aim is to choose, from a large number of available spectral wavelengths, those relevant to the estimation of analyte concentrations or sample properties when spectroscopic analysis is combined with multivariate calibration techniques such as partial(More)
Organic pollutants include a very wide variety of chemical compounds with different structures, properties, functions and origins, which may produce diverse damages to the ecosystem and the human beings. This review presents the recent progress on the use of chemometrics to evaluate the occurrence of these substances in the environment. The main topics(More)
Four-way fluorescence data recorded by following the kinetic evolution of excitation-emission fluorescence matrices (EEMs) have been analyzed by parallel factor analysis and trilinear least-squares algorithms. These methodologies exploit the second-order advantage of the studied data, allowing analyte concentrations to be estimated even in the presence of(More)
A new equation is derived for estimating the sensitivity when the multivariate curve resolution-alternating least-squares (MCR-ALS) method is applied to second-order multivariate calibration data. The validity of the expression is substantiated by extensive Monte Carlo noise addition simulations. The multivariate selectivity can be derived from the new(More)
Liquid chromatographic-diode array detection data recorded for aqueous mixtures of 11 pesticides show the combined presence of strongly coeluting peaks, distortions in the time dimension between experimental runs, and the presence of potential interferents not modeled by the calibration phase in certain test samples. Due to the complexity of these(More)
A new expression is developed which allows estimating the sensitivity for the whole family of multivariate calibration algorithms based on partial least-squares regression combined with residual multilinearization. The sensitivity can be employed to compute other relevant figures of merit such as analytical sensitivity, limit of detection, limit of(More)
The kinetic evolution of UV-visible absorption spectra of amoxicillin in the presence of copper(II) ions has been processed by the second-order multivariate methods parallel factor analysis (PARAFAC) and also by a novel approach based on partial least-squares with residual bilinearization (PLS/RBL). The latter one is employed for the first time to evaluate(More)