Second-order advantage with excitation–emission photoinduced fluorimetry for the determination of the antiepileptic carbamazepine in environmental waters

A photochemically induced fluorescence system combined with second-order chemometric analysis for the determination of the anticonvulsant carbamazepine (CBZ) is presented. CBZ is a widely used drug for the treatment of epilepsy and is included in the group of emerging contaminant present in the aquatic environment. CBZ is not fluorescent in solution but can be converted into a fluorescent compound through a photochemical reaction in a strong acid medium. The determination is carried out by measuring excitation–emission photoinduced fluorescence matrices of the products formed upon ultraviolet light irradiation in a laboratory-constructed reactor constituted by two simple 4 W germicidal tubes. Working conditions related to both the reaction medium and the photoreactor geometry are optimized by an experimental design. The developed approach enabled the determination of CBZ at trace levels without the necessity of applying separation steps, and in the presence of uncalibrated interferences which also display photoinduced fluorescence and may be potentially present in the investigated samples. Different second-order algorithms were tested and successful resolution was achieved using multivariate curve resolution-alternating least-squares (MCR-ALS). The study is employed for the discussion of the scopes and yields of each of the applied second-order chemometric tools. The quality of the proposed method is probed through the determination of the studied emerging pollutant in both environmental and drinking water samples. After a pre-concentration step on a C18 membrane using 50.0 mL of real water samples, a prediction relative error of 2% and limits of detection and quantification of 0.2 and 0.6 ng mL⁻¹ were respectively obtained.     

A nonsymmetric matrix with integer eigenvalues

A nonsymmetric N?×?N matrix with elements as certain simple functions of N distinct real or complex numbers r ₁, r ₂, …, r_N is presented. The matrix is special due to its eigenvalues???the consecutive integers 0,1,2, …, N?1. Theorems are given establishing explicit expressions of the right and left eigenvectors and formulas for recursive calculation of the right eigenvectors. A special case of the matrix has appeared in sampling theory where its right eigenvectors, if properly normalized, give the inclusion probabilities of the conditional Poisson sampling design.     

Multivariate Observations of the Distribution of Polychlorinated Biphenyls in Environmental Compartments of Two Harbours

Abstract

The objectives of this study were to identify, classify and categorize polychlorinated biphenyl (PCB) residues in samples collected from the Hamilton and Wheatley Harbour environmental compartments. The study is built around the use of a principal components analysis method, namely the soft independent modelling of class analogy (SIMCA) technique. This multivariate method is widely used for evaluating differences and observing similarities among multiple objects. The results obtained from this work confirm that the gas chromatographic data sets obtained with the samples provide a good approximation of the pattern derived from a determination of the composition of commercial Aroclors in water, sediment and biota samples. The data analysis technique provides insight into the origin of PCB contamination in environmental samples and indicates pathways for the environmental degradation or bioaccumulation of PCBs. This investigation contributes some evidence that multivariate reduction techniques are suitable for the investigation of complex data sets in environmental studies.     

Background parenchymal enhancement in the contralateral normal breast of patients undergoing neoadjuvant chemotherapy measured by DCE-MRI

The purpose of this study was to analyze background parenchymal enhancement (BPE) in the contralateral normal breast of cancer patients during the course of neoadjuvant chemotherapy (NAC).     

Speciation of adsorbates on surface of solids by infrared spectroscopy and chemometrics

Speciation, i.e. identification and quantification, of surface species on heterogeneous surfaces by infrared spectroscopy is important in many fields but remains a challenging task when facing strongly overlapped spectra of multiple adspecies. Here, we propose a new methodology, combining state of the art instrumental developments for quantitative infrared spectroscopy of adspecies and chemometrics tools, mainly a novel data processing algorithm, called SORB-MCR (SOft modeling by Recursive Based-Multivariate Curve Resolution) and multivariate calibration. After formal transposition of the general linear mixture model to adsorption spectral data, the main issues, i.e. validity of Beer–Lambert law and rank deficiency problems, are theoretically discussed. Then, the methodology is exposed through application to two case studies, each of them characterized by a specific type of rank deficiency: (i) speciation of physisorbed water species over a hydrated silica surface, and (ii) speciation (chemisorption and physisorption) of a silane probe molecule over a dehydrated silica surface. In both cases, we demonstrate the relevance of this approach which leads to a thorough surface speciation based on comprehensive and fully interpretable multivariate quantitative models. Limitations and drawbacks of the methodology are also underlined.     

基于截尾正态分布的最优过程均值的确定

过程均值的选择对生产率的提高以及产品质量改进非常重要,因为它直接影响到过程的缺陷率、材料费用、重加工费及产品性能偏离目标值对顾客造成的损失等.本文讨论了在不对称田口质量损失函数下截尾正态分布的最优过程均值的确定问题.通过灵敏度分析,研究了过程参数对过程均值选择的影响.