Analysis of lipoproteins using 2D diffusion-edited NMR spectroscopy and multi-way chemometrics

This study represents the first application of multi-way calibration by N-PLS and multi-way curve resolution by PARAFAC to 2D diffusion-edited H-1 NMR spectra. The aim of the analysis was to evaluate the potential for quantification of lipoprotein main- and subtractions in human plasma samples. Multi-way N-PLS calibrations relating the methyl and methylene peaks of lipoprotein lipids to concentrations of the four main lipoprotein fractions as well as 11 subfractions were developed with high correlations (R = 0.75-0.98). Furthermore, a PARAFAC model with four chemically meaningful components was calculated from the 2D diffusion-edited spectra of the methylene peak of lipids. Although the four extracted PARAFAC components represent molecules of sizes that correspond to the four main fractions of lipoproteins, the corresponding concentrations of the four PARAFAC components proved not to be correlated to the reference concentrations of these four fractions in the plasma samples as determined by ultracentrifugation. These results indicate that NMR provides complementary information on the classification of lipoprotein fractions compared to ultracentrifugation. (C) 2004 Elsevier B.V. All rights reserved.

The prevalence of childhood obesity in primary school children in urban Khon Kaen, Northeast Thailand

Childhood obesity is a serious public health problem because of its strong association with adulthood obesity and the related adverse health consequences. The published literature indicates a rising prevalence of childhood obesity in both developed and developing countries. However no data exists on the prevalence in Northeast Thailand, one of the poorest regions of the country and one that has experienced a recent economic transition. The objective of this study was to estimate the prevalence of obesity in seven to nine year old children in urban Khon Kaen, Northeast Thailand. A cross-sectional school based survey was conducted to determine the prevalence of obesity in children of urban Khon Kaen, Thailand. Multi-staged cluster sampling was used to select 12 school clusters of 72 children each between the ages of 7 and 9 years, in primary school grades 1, 2 and 3 from government, private and demonstration schools. A total of 864 seven to nine year old school children were studied. Anthropometric measurements of standing height and weight were taken for all subjects to the nearest tenth of a centimetre and tenth of a kilogram respectively. Childhood obesity was defined as a weight-for-height Z-score above 2.0 standard deviations of the National Center for Health Statistics/World Health Organisation reference population median. The prevalence of childhood obesity was 10.8% (95% CI: 7.6, 13.9). Obesity was significantly more prevalent in boys than girls. The biggest difference was observed between the three school types, with the highest prevalence of obesity found at teacher training demonstration schools and the lowest at the government schools. This study provides the first data on childhood obesity prevalence in Northeast Thailand. The prevalence of 10.8 per cent is lower than that found in two other urban areas of Thailand but slightly higher than expected for this relatively poor region. If this prevalence rate increases, as observed in other countries in economic transition, the incidence of non-communicable diseases associated with obesity is also likely to increase, thus raising cause for concern and reason for intervention to both control and prevent obesity during childhood.

Exploring composite acoustic features for efficient music similarity query

Music similarity query based on acoustic content is becoming important with the ever-increasing growth of the music information from emerging applications such as digital libraries and WWW. However, relative techniques are still in their infancy and much less than satisfactory. In this paper, we present a novel index structure, called Composite Feature tree, CF-tree, to facilitate efficient content-based music search adopting multiple musical features. Before constructing the tree structure, we use PCA to transform the extracted features into a new space sorted by the importance of acoustic features. The CF-tree is a balanced multi-way tree structure where each level represents the data space at different dimensionalities. The PCA transformed data and reduced dimensions in the upper levels can alleviate suffering from dimensionality curse. To accurately mimic human perception, an extension, named CF+-tree, is proposed, which further applies multivariable regression to determine the weight of each individual feature. We conduct extensive experiments to evaluate the proposed structures against state-of-art techniques. The experimental results demonstrate superiority of our technique.

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

Galaxy threshing and ultra-compact dwarfs in the Fornax cluster

We have discovered a new type of galaxy in the Fornax Cluster: 'ultra-compact' dwarfs (UCDs). The UCDs are unresolved in ground-based imaging and have spectra typical of old stellar systems. Although the UCDs resemble overgrown globular clusters, based on VLT UVES echelle spectroscopy, they appear to be dynamically distinct systems with higher internal velocity dispersions and M/L ratios for a given luminosity than Milky Way or M31 globulars. Our preferred explanation for their origin is that they are the remnant nuclei of dwarf elliptical galaxies which have been tidally stripped, or 'threshed' by repeated encounters with the central cluster galaxy, NGC1399. If correct, then tidal stripping of nucleated dwarfs to form UCDs may, over a Hubble time, be an important source of the plentiful globular cluster population in the halo of NGC1399, and, by implication, other cD galaxies. In this picture, the dwarf elliptical halo contents, up to 99% of the original dwarf luminosity, contribute a significant fraction of the populations of intergalactic stars, globulars, and gas in galaxy clusters.

Cluster-state quantum computation

This article is a short introduction to and review of the cluster-state model of quantum computation, in which coherent quantum information processing is accomplished via a sequence of single-qubit measurements applied to a fixed quantum state known as a cluster state. We also discuss a few novel properties of the model, including a proof that the cluster state cannot occur as the exact ground state of any naturally occurring physical system, and a proof that measurements on any quantum state which is linearly prepared in one dimension can be efficiently simulated on a classical computer, and thus are not candidates for use as a substrate for quantum computation.

Cluster measurement and benchmarking - A recent Welsh approach

Drawing on extensive academic research and theory on clusters and their analysis, the methodology employed in this pilot study (sponsored by the Welsh Assembly Government’s Economic Research Grants Assessment Board) seeks to create a framework for reviewing and monitoring clusters in Wales on an ongoing basis, and generate the information necessary for successful cluster development policy to occur. The multi-method framework developed and tested in the pilot study is designed to map existing Welsh sectors with cluster characteristics, uncover existing linkages, and better understand areas of strength and weakness. The approach adopted relies on synthesising both quantitative and qualitative evidence. Statistical measures, including the size of potential clusters, are united with other evidence on input-output derived inter-linkages within clusters and to other sectors in Wales and the UK, as well as the export and import intensity of the cluster. Multi Sector Qualitative Analysis is then designed for competencies/capacity, risk factors, markets, types and crucially, the perceived strengths of cluster structures and relationships. The approach outlined above can, with the refinements recommended through the review process, provide policy-makers with a valuable tool for reviewing and monitoring individual sectors and ameliorating problems in sectors likely to decline further.