RES, an expert system for the set-up and interpretation of a ruggedness test in HPLC method validation: Part 1: The ruggedness test in HPLC method validation

In method validation, an intralaboratory repeatability study and an interlaboratory reproducibility study can be performed as part of a precision test. In HPLC, an intralaboratory ruggedness test can be performed to detect problems that would otherwise be encountered in a reproducibility study. In a ruggedness test, variations in ambient factors that are expected to occur in practice, are simulated. Several steps determine the success of a ruggedness test. The complexity and lack of standard procedures for some of these steps is the main reason why ruggedness testing is still not widely accepted.     

Pinpointing biomarkers in proteomic LC/MS data by moving-window discriminant analysis

The identification of differential patterns in data originating from combined measurement techniques such as LC/MS is pivotal to proteomics. Although "shotgun proteomics" has been employed successfully to this end, this method also has severe drawbacks, because of its dependence on largely untargeted MS/MS sequencing and databases for statistical analyses. Alternatively, several MS-signal-based (MS/MS-independent) methods have been published that are mainly based on (univariate) Student's t-tests. Here, we present a more robust multivariate alternative employing linear discriminant analysis. Like the t-test-based methods, it is applied directly to LC/MS data, instead of using MS/MS measurements. We demonstrate the method on a number of simulated data sets, as well as on a spike-in LC/MS data set, and show its superior performance over t-tests.     

Tracing the geographical origin of honeys based on volatile compounds profiles assessment using pattern recognition techniques

The goal of this study was to examine the possibility of verifying the geographical origin of honeys based on the profiles of volatile compounds. A head-space solid phase microextraction (SPME) combined with comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOFMS) was used to analyze the volatiles in honeys with various geographical and floral origins. Once the analytical data were collected, supervised pattern recognition techniques were applied to construct classification/discrimination rules to predict the origin of samples on the basis of their profiles of volatile compounds. Specifically, linear discriminant analysis (LDA), soft independent modeling of class analogies (SIMCA), discriminant partial least squares (DPLS) and support vector machines (SVM) with the recently proposed Pearson VII universal kernel (PUK) were used in our study to discriminate between Corsican and non-Corsican honeys. Although DPLS and LDA provided models with high sensitivities and specificities, the best performance was achieved by the SVM using PUK. The results of this study demonstrated that GC × GC–TOFMS combined with methods like LDA, DPLS and SVM can be successfully applied to detect mislabeling of Corsican honeys.     

Detection and classification of latent defects and diseases on raw French fries with multispectral imaging

This paper describes an application of both multispectral imaging and red/green/blue (RGB) colour imaging for the discrimination between different defect and diseases on raw French fries. Four different potato cultivars generally used for French fries production are selected from which fries are cut. Both multispectral images and RGB colour images are classified with parametric and non‐parametric classifiers. The effect of applying different preprocessing techniques on the spectra was also investigated. The best classification results in terms of accuracy, yield and purity are obtained with a modified version of standard normal variate (snv_mod) preprocessing for different classifiers and potato cultivars. The classification results of the multispectral images are compared with RGB images. The results show that the support vector classifier gives the best classification performance for the snv_mod preprocessed multispectral images and k‐nearest neighbours classifier gives the best classification performance for raw RGB images. The detection of the latent greening defect in French fries with the exploration of multispectral images shows the additional value of multispectral imaging for French fries. A comparison between the multispectral images and the RGB colour images confirms this since this type of defect is not visible in the colour images. Copyright © 2005 Society of Chemical Industry     

A chemometric approach for brain tumor classification using magnetic resonance imaging and spectroscopy

A new classification approach was developed to improve the noninvasive diagnosis of brain tumors. Within this approach, information is extracted from magnetic resonance imaging and spectroscopy data, from which the relative location and distribution of selected tumor classes in feature space can be calculated. This relative location and distribution is used to select the best information extraction procedure, to identify overlapping tumor classes, and to calculate probabilities of class membership. These probabilities are very important, since they provide information about the reliability of classification and might provide information about the heterogeneity of the tissue. Classification boundaries were calculated by setting thresholds for each investigated tumor class, which enabled the classification of new objects. Results on histopathologically determined tumors are excellent, demonstrated by spatial maps showing a high probability for the correctly identified tumor class and, moreover, low probabilities for other tumor classes.     

Thickness variations during MOVPE growth on patterned substrates

Experiments have been carried out to investigate thickness variations between epitaxial layers grown on ridges or channels and the surrounding planar surface. Results show a remarkable variation in growth velocity, even for relatively wide channels and ridges. Using these findings, a novel laser/waveguide coupling technique, which uses a single epitaxial growth step, is proposed.     

A comparison of methods to relate grass reflectance to soil metal contamination

Grass-dominated vegetation covers large areas of the Dutch river floodplains. Remotely sensed data on the conditions under which this vegetation grows may yield information about the degree of soil contamination. This paper explores the relationship between grassland canopy reflectance and zinc (Zn) contamination in the soil under semi-field conditions. A field radiometer was used to record reflectance spectra of perennial ryegrass (Lolium perenne) in an experimental field with Zn concentrations in the soil ranging from 32 to 1800mgkg^?1. Several spectral vegetation indices (VIs) and a multivariate approach using partial least squares (PLS) regression were investigated to evaluate their potential use in estimating Zn contamination levels. Compared to the best PLS model (RMSEP = 181.4 mg kg^?1), the narrow band vegetation index MSAVI2mm performed better (RMSEP = 162.9 mg kg^?1). Both MSAVI2mm and PLS gave a high user accuracy for the strongly contaminated soil class (100% and 91%, respectively), while the total accuracy was satisfactory (60% and 55%, respectively). Results from this feasibility study indicate the potential of using remote sensing techniques for the classification of contaminated areas in river floodplains. But as the results from this study may be both resolution- and location-dependent, research on field and image scale is now required to test the established relations and to assess their susceptibility to seasonal influences, species heterogeneity, and increased levels of spectral noise.     

Amplitude modulation and beam-steering properties of active binary phase gratings with reconfigurable absorption areas

By combining a binary phase grating and materials with a controllable absorption, it is shown theoretically that it is possible to modulate the light in a zero-order diffraction beam and that a high contrast level for the beam modulation can be obtained. The intensity of higher diffraction orders also changes, but it is calculated that high contrasts cannot be achieved for these higher-order beams with the active gratings that we examine. This specific modulator design that we use can be applied both for transmitted and for reflected light. Using the same ideas, one may build a beam-deflection device by varying the period of the grating by selectively changing the absorption levels in the grating. The deflection efficiency of the device can be improved compared with other designs by use of a grating with a reduced intensity of the nondeflected zero-order beam.