Model atmosphere and kinematical analyses of early-type stars from the Edinburgh-Cape Survey

We present high-resolution spectroscopic observations of 21 B- type stars, selected from the Edinburgh-Cape Blue Object Survey. Model atmosphere analyses confirm that 14 of these stars are young, main-sequence B-type objects with Population I chemical compositions. The remaining seven are found to be evolved objects, including subdwarfs, horizontal branch and post-AGB objects. A kinematical analysis shows that all 14 young main-sequence stars could have formed in the disc and subsequently been ejected into the halo. These results are combined with the analysis of a previous subsample of stars taken from the Survey. Of the complete sample, 31 have been found to be young, main-sequence objects, with formation in the disc, and subsequent ejection into the halo, again being found to be a plausible scenario.

The use of Raman microscopy to determine and localize vitamin E in biological samples

Alpha-tocopherol (aT), the predominant form of vitamin E in mammals, is thought to prevent oxidation of polyunsaturated fatty acids. In the lung, aT is perceived to be accumulated in alveolar type II cells and secreted together with surfactant into the epithelial lining fluid. Conventionally, determination of aT and related compounds requires extraction with organic solvents. This study describes a new method to determine and image the distribution of aT and related compounds within cells and tissue sections using the light-scattering technique of Raman microscopy to enable high spatial as well as spectral resolution. This study compared the nondestructive analysis by Raman microscopy of vitamin E, in particular aT, in biological samples with data obtained using conventional HPLC analysis. Raman spectra were acquired at spatial resolutions of 2-0.8 microm. Multivariate analysis techniques were used for analyses and construction of corresponding maps showing the distribution of aT, alpha-tocopherol quinone (aTQ), and other constituents (hemes, proteins, DNA, and surfactant lipids). A combination of images enabled identification of colocalized constituents (heme/aTQ and aT/surfactant lipids). Our data demonstrate the ability of Raman microscopy to discriminate between different tocopherols and oxidation products in biological specimens without sample destruction. By enabling the visualization of lipid-protein interactions, Raman microscopy offers a novel method of investigating biological characterization of lipid-soluble compounds, including those that may be embedded in biological membranes such as aT.

Determining factors of the innovative behavior of cooperatives: an analysis of the case of Castilla y León

Cooperatives have a long historical experience in the Spanish economy and have demonstrated their ability to compete against traditional firms in the market. To maintain this capability, while taking advantage of the competitive advantages associated with their idiosyncrasies as social economy enterprises, they should take into consideration that the economy is increasingly globalized and increasingly knowledge-based, especially with regards to technological content. As a consequence, the innovative capacity appears to be a key aspect in order to be able to challenge competitors. This article characterizes the innovative behavior of cooperatives in the region of Castile and Leon and analyses the internal and external factors affecting their innovative performance, based on data from a survey of 581 cooperatives. The results of the empirical analysis, which is performed by multivariate binary logistic regression on various types of innovation, lead us to identify the size of the organizations, the existence of planning, the R & D activities and the human capital as the main determining factors.

Multivariate prediction of clarified butter composition using Raman spectroscopy

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R-2=0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was 1.25%. The Raman method has the best prediction ability for unsaturated FA (R-2=0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 tDelta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R-2=0.80) and solid fat content at low temperature (R-2=0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R-2=0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.

Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.

Genetic association analyses of non-synonymous single nucleotide polymorphisms in diabetic nephropathy

Aims/hypothesis: Diabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.

Methods: White type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A ? 2 test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.

Results: We assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.

Conclusions/interpretation: The nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.