Letter to the Editor: Calculation of photoionized plasmas with an average-atom model

We use a simple average-atom model (NIMP) to calculate the distribution of ionization in a photoionization-dominated plasma, for comparison with recent experimental measurements undertaken on the Z-machine at the Sandia National Laboratory. The agreement between theory and experiment is found to be as good for calculations with an average-atom model as for those generated by more detailed models.

Transport in nanoscale systems: the microcanonical versus grand-canonical picture

We analyse a picture of transport in which two large but finite charged electrodes discharge across a nanoscale junction. We identify a functional whose minimization, within the space of all bound many-body wavefunctions, defines an instantaneous steady state. We also discuss factors that favour the onset of steady-state conduction in such systems, make a connection with the notion of entropy, and suggest a novel source of steady-state noise. Finally, we prove that the true many-body total current in this closed system is given exactly by the one-electron total current, obtained from time-dependent density-functional theory.

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Abstract: Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R-2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (>= 2 double bonds per chain) was also well predicted with R-2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R-2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R-2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

Deflation based nonlinear canonical correlation analysis

This paper introduces two new techniques for determining nonlinear canonical correlation coefficients between two variable sets. A genetic strategy is incorporated to determine these coefficients. Compared to existing methods for nonlinear canonical correlation analysis (NLCCA), the benefits here are that the nonlinear mapping requires fewer parameters to be determined, consequently a more parsimonious NLCCA model can be established which is therefore simpler to interpret. A further contribution of the paper is the investigation of a variety of nonlinear deflation procedures for determining the subsequent nonlinear canonical coefficients. The benefits of the new approaches presented are demonstrated by application to an example from the literature and to recorded data from an industrial melter process. These studies show the advantages of the new NLCCA techniques presented and suggest that a nonlinear deflation procedure should be considered. (c) 2006 Elsevier B.V. All rights reserved.

CTGF/CCN2 activates canonical Wnt signalling in mesangial cells through LRP6: Implications for the pathogenesis of diabetic nephropathy

We describe the activation of Wnt signalling in mesangial cells by CCN2. CCN2 stimulates phosphorylation of LRP6 and GSK-3 beta resulting in accumulation and nuclear localisation of beta-catenin, TCF/LEF activity and expression of Wnt targets. This is coincident with decreased phosphorylation of beta-catenin on Ser 33/37 and increased phosphorylation on Tyr142. DKK-1 and LRP6 siRNA reversed CCN2's effects. Microarray analyses of diabetic patients identified differentially expressed Wnt components. beta-Catenin is increased in type 1 diabetic and UUO mice and in in vitro models of hyperglycaemia and hypertension. These findings suggest that Wnt/CCN2 signalling plays a role in the pathogenesis of diabetic nephropathy. (C) 2011 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Association Analysis of Canonical Wnt Signalling Genes in Diabetic Nephropathy.

Several studies have provided compelling evidence implicating the Wnt signalling pathway in the pathogenesis of diabetic nephropathy. Gene expression profiles associated with renal fibrosis have been attenuated through Wnt pathway modulation in model systems implicating Wnt pathway members as potential therapeutic targets for the treatment of diabetic nephropathy. We assessed tag and potentially functional single nucleotide polymorphisms (SNPs; n = 31) in four key Wnt pathway genes (CTNNB1, AXIN2, LRP5 and LRP6) for association with diabetic nephropathy using a case-control design.

From inconsistency handling to non-canonical requirements management: A logical perspective

As a class of defects in software requirements specification, inconsistency has been widely studied in both requirements engineering and software engineering. It has been increasingly recognized that maintaining consistency alone often results in some other types of non-canonical requirements, including incompleteness of a requirements specification, vague requirements statements, and redundant requirements statements. It is therefore desirable for inconsistency handling to take into account the related non-canonical requirements in requirements engineering. To address this issue, we propose an intuitive generalization of logical techniques for handling inconsistency to those that are suitable for managing non-canonical requirements, which deals with incompleteness and redundancy, in addition to inconsistency. We first argue that measuring non-canonical requirements plays a crucial role in handling them effectively. We then present a measure-driven logic framework for managing non-canonical requirements. The framework consists of five main parts, identifying non-canonical requirements, measuring them, generating candidate proposals for handling them, choosing commonly acceptable proposals, and revising them according to the chosen proposals. This generalization can be considered as an attempt to handle non-canonical requirements along with logic-based inconsistency handling in requirements engineering.

Average household income, crime, and smoking behaviour in a local area: The Finnish 10-Town study

Social environments, like neighbourhoods, are increasingly recognised as determinants of health. While several studies have reported an association of low neighbourhood socio-economic status with morbidity, mortality and health risk behaviour, little is known of the health effects of neighbourhood crime rates. Using the ongoing 10-Town study in Finland, we examined the relations of average household income and crime rate measured at the local area level, with smoking status and intensity by linking census data of local area characteristics from 181 postal zip codes to survey responses to smoking behaviour in a cohort of 23,008 municipal employees. Gender-stratified multilevel analyses adjusted for age and individual occupational status revealed an association between low local area income rate and current smoking. High local area crime rate was also associated with current smoking. Both local area characteristics were strongly associated with smoking intensity. Among ever-smokers, being an ex-smoker was less likely among residents in areas with low average household income and a high crime rate. In the fully adjusted model, the association between local area income and smoking behaviour among women was substantially explained by the area-level crime rate. This study extends our knowledge of potential pathways through which social environmental factors may affect health. (c) 2007 Elsevier Ltd. All rights reserved.

Field and Laboratory Tests of Flow-Proportional Passive Samplers for Determining Average Phosphorus and Nitrogen Concentration in Rivers

Flow responsive passive samplers offer considerable potential in nutrient monitoring in catchments; bridging the gap between the intermittency of grab sampling and the high cost of automated monitoring systems. A commercially available passive sampler was evaluated in a number of river systems encapsulating a gradient in storm response, combinations of diffuse and point source pressures, and levels of phosphorus and nitrogen concentrations. Phosphorus and nitrogen are sequestered to a resin matrix in a permeable cartridge positioned in line with streamflow. A salt tracer dissolves in proportion to advective flow through the cartridge. Multiple deployments of different cartridge types were undertaken and the recovery of P and N compared with the flow-weighted mean concentration (FWMC) from high-resolution bank-side analysers at each site. Results from the passive samplers were variable and largely underestimated the FWMC derived from the bank-side analysers. Laboratory tests using ambient river samples indicated good replication of advective throughflow using pumped water, although this appeared not to be a good analogue of river conditions where flow divergence was possible. Laboratory tests also showed good nutrient retention but not elution and these issues appeared to combine to limit the utility in ambient river systems at the small catchment scale.

Pattern of learning disabilities in children with extremely low birth weight and broadly average intelligence

To examine the prevalence and pattern of specific areas of learning disability (LD) in neurologically normal children with extremely low birth weight (ELBW) (<or = 800 g) who have broadly average intelligence compared with full-term children with normal birth weight of comparable sociodemographic background, and to explore concurrent cognitive correlates of the specific LDs.

Trading Energy ETFs with an Improved Moving Average Strategy

In this paper we employ the recently introduced improved moving average methodology of Papailias and Thomakos (2011) and we apply it in two energy ETFs. We compare it to the standard moving average methodology and the buy and hold strategy. Investors who are interested in energy-related sectors and trade using averages, could benefit by forming their strategies based on this improved moving average methodology as it returns higher profits accompanied by decreased risk (measured in terms of drawdown).

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.