Matrix-assisted diffusion-ordered spectroscopy:application of surfactant solutions to the resolution of isomer spectra

The component spectra of a mixture of isomers with nearly identical diffusion coefficients cannot normally be distinguished in a standard diffusion-ordered spectroscopy (DOSY) experiment but can often be easily resolved using matrix-assisted DOSY, in which diffusion behaviour is manipulated by the addition of a co-solute such as a surfactant. Relatively little is currently known about the conditions required for such a separation, for example, how the choice between normal and reverse micelles affects separation or how the isomer structures themselves affect the resolution. The aim of this study was to explore the application of sodium dodecyl sulfate (SDS) normal micelles in aqueous solution and sodium 1,4-bis(2-ethylhexyl)sulfosuccinate (AOT) aggregates in chloroform, at a range of concentrations, to the diffusion resolution of some simple model sets of isomers such as monomethoxyphenols and short chain alcohols. It is shown that SDS micelles offer better resolution where these isomers differ in the position of a hydroxyl group, whereas AOT aggregates are more effective for isomers differing in the position of a methyl group. For both the normal SDS micelles and the less well-defined AOT aggregates, differences in the resolution of the isomers can in part be rationalised in terms of differing degrees of hydrophobicity, amphiphilicity and steric effects. Copyright © 2012 John Wiley & Sons, Ltd.

Quantitative interpretation of diffusion-ordered NMR spectra:can we rationalize small molecule diffusion coefficients?

Appealingly simple: A new method is described that allows the diffusion coefficient of a small molecule to be estimated given only the molecular weight and the viscosity of the solvent used. This method makes possible the quantitative interpretation of the diffusion domain of diffusion-ordered NMR spectra (see picture). © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prediction of phytoplankton pigment concentration from absorption spectra

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

An investigation of the fluorescence of Britishs bituminous coals:an analysis of fluorescent spectra of coal macerals

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

The detection of p-waves in ambulatory ECG recordings by the use of wavelet transforms

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Impact of FBGs reflectivity shape on spectra of radiation in 10 km Raman fibre laser

We study the impact of the shape of fibre Bragg gratings spectral reflectivity on spectral broadening in a 10 km Raman fibre laser. We show that, at high powers, spectral characteristics are determined by intra-cavity processes rather than by the gratings profile.

Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Rotation invariance is important for an iris recognition system since changes of head orientation and binocular vergence may cause eye rotation. The conventional methods of iris recognition cannot achieve true rotation invariance. They only achieve approximate rotation invariance by rotating the feature vector before matching or unwrapping the iris ring at different initial angles. In these methods, the complexity of the method is increased, and when the rotation scale is beyond the certain scope, the error rates of these methods may substantially increase. In order to solve this problem, a new rotation invariant approach for iris feature extraction based on the non-separable wavelet is proposed in this paper. Firstly, a bank of non-separable orthogonal wavelet filters is used to capture characteristics of the iris. Secondly, a method of Markov random fields is used to capture rotation invariant iris feature. Finally, two-class kernel Fisher classifiers are adopted for classification. Experimental results on public iris databases show that the proposed approach has a low error rate and achieves true rotation invariance. © 2010.

Double-Wavelet Neuron Based on Analytical Activation Functions

In this paper a new double-wavelet neuron architecture obtained by modification of standard wavelet neuron, and its learning algorithm are proposed. The offered architecture allows to improve the approximation properties of wavelet neuron. Double-wavelet neuron and its learning algorithm are examined for forecasting non-stationary chaotic time series.

Segmentation of a Speech Signal with Application of Fast Wavelet Transformation

The article describes the method of preliminary segmentation of a speech signal with wavelet transformation use, consisting of two stages. At the first stage there is an allocation of sibilants and pauses, at the second – the further segmentation of the rest signal parts.

Outliers Resistant Learning Algorithm for Radial-basis-fuzzy-wavelet-neural Network in Stomach Acute Injury Diagnosis Tasks

In this paper an outliers resistant learning algorithm for the radial-basis-fuzzy-wavelet-neural network based on R. Welsh criterion is proposed. Suggested learning algorithm under consideration allows the signals processing in presence of significant noise level and outliers. The robust learning algorithm efficiency is investigated and confirmed by the number of experiments including medical applications.

Volume strain sensor based on spectra analysis of in-fiber modal interferometer

An optical in-fiber modal interferometer-based volume strain sensor for earthquake prediction is proposed and experimentally demonstrated. The sensing element is formed by wrapping a multimode-singlemode-multimode fiber structure onto a polyurethane hollow column. Due to the modal interference between the excited guided modes in the fiber, strong interference pattern could be observed in the transmission spectrum. Theoretical analysis verifies that the resonant wavelength shifts as a result of the volume strain variation caused by the column deformation with square root relationship. Sensitivity > 3.93 pm/με within the volume strain ranging from 0 to 1300 με is also experimentally demonstrated. By taking the response of bidirectional change of volume strain and the sluggish character of the employed sensing material into consideration, the sensing system presents good repeatability and stability. © 2001-2012 IEEE.

Application of Wavelet Decomposition to Document Line Segmentation

ACM Computing Classification System (1998): I.7, I.7.5.

Content-Based Image Retrieval for Computer Tomography Images Using Wavelet Descriptors

An approach to building a CBIR-system for searching computer tomography images using the methods of wavelet-analysis is presented in this work. The index vectors are constructed on the basis of the local features of the image and on their positions. The purpose of the proposed system is to extract visually similar data from the individual personal records and from analogous analysis of other patients.