Investigating the cost Performance of UK Credit Unions using Radial and Non-Radial Efficiency Measures

This paper examines the relative efficiency of UK credit unions. Radial and non-radial measures of input cost efficiency plus associated scale efficiency measures are computed for a selection of input output specifications. Both measures highlighted that UK credit unions have considerable scope for efficiency gains. It was mooted that the documented high levels of inefficiency may be indicative of the fact that credit unions, based on clearly defined and non-overlapping common bonds, are not in competition with each other for market share. Credit unions were also highlighted as suffering from a considerable degree of scale inefficiency with the majority of scale inefficient credit unions subject to decreasing returns to scale. The latter aspect highlights that the UK Government's goal of larger credit unions must be accompanied by greater regulatory freedom if inefficiency is to be avoided. One of the advantages of computing non-radial measures is that an insight into potential over- or under-expenditure on specific inputs can be obtained through a comparison of the non-radial measure of efficiency with the associated radial measure. Two interesting findings emerged, the first that UK credit unions over-spend on dividend payments and the second that they under-spend on labour costs.

Numerical and Experimental Study of the Performance Effects of Varying Vaneless Space and Vane Solidity in Radial Inflow Turbine Stators.

An extensive experimental program has been carried out on a 135?mm tip diameter radial turbine using a variety of stator designs, in order to facilitate direct performance comparisons of varying stator vane solidity and the effect of varying the vaneless space. A baseline vaned stator was designed using commercial blade design software, having 15 vanes and a vane trailing edge to rotor leading edge radius ratio (Rte/rle) of 1.13. Two additional series of stator vanes were designed and manufactured; one series having varying vane numbers of 12, 18, 24, and 30, and a further series with Rte/rle ratios of 1.05, 1.175, 1.20, and 1.25. As part of the design process a series of CFD simulations were carried out in order to guide design iterations towards achieving a matched flow capacity for each stator. In this way the variations in the measured stage efficiency could be attributed to the stator passages only, thus allowing direct comparisons to be made. Interstage measurements were taken to capture the static pressure distribution at the rotor inlet and these measurements were then used to validate subsequent numerical models. The overall losses for different stators have been quantified and the variations in the measured and computed efficiency were used to recommend optimum values of vane solidity and Rte/rle.

Functional Interleukin-17 Receptor A is Expressed in Central Nervous System Glia and Upregulated in Experimental Autoimmune Encephalomyelitis

Background: Interleukin-17A (IL-17A) is the founding member of a novel family of inflammatory cytokines that plays a critical role in the pathogenesis of many autoimmune diseases, including multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE). IL-17A signals through its receptor, IL-17RA, which is expressed in many peripheral tissues; however, expression of IL-17RA in the central nervous system (CNS) and its role in CNS inflammation are not well understood. Methods: EAE was induced in C57Bl/6 mice by immunization with myelin oligodendroglial glycoprotein. IL-17RA expression in the CNS was compared between control and EAE mice using RT-PCR, in situ hybridization, and immunohistochemistry. Cell-type specific expression was examined in isolated astrocytic and microglial cell cultures. Cytokine and chemokine production was measured in IL-17A treated cultures to evaluate the functional status of IL-17RA. Results: Here we report increased IL-17RA expression in the CNS of mice with EAE, and constitutive expression of functional IL-17RA in mouse CNS tissue. Specifically, astrocytes and microglia express IL-17RA in vitro, and IL-17A treatment induces biological responses in these cells, including significant upregulation of MCP-1, MCP-5, MIP-2 and KC chemokine secretion. Exogenous IL-17A does not significantly alter the expression of IL-17RA in glial cells, suggesting that upregulation of chemokines by glial cells is due to IL-17A signaling through constitutively expressed IL-17RA. Conclusion: IL-17RA expression is significantly increased in the CNS of mice with EAE compared to healthy mice, suggesting that IL-17RA signaling in glial cells can play an important role in autoimmune inflammation of the CNS and may be a potential pathway to target for therapeutic interventions. © 2009 Sarma et al; licensee BioMed Central Ltd.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

A Comparison of the Flow Structures and Losses Within Vaned and Vaneless Stators for Radial Turbines

This paper details the numerical analysis of different vaned and vaneless radial inflow turbine stators. Selected results are presented from a test program carried out to determine performance differences between the radial turbines with vaned stators and vaneless volutes under the same operating conditions. A commercial computational fluid dynamics code was used to develop numerical models of each of the turbine configurations, which were validated using the experimental results. From the numerical models, areas of loss generation in the different stators were identified and compared, and the stator losses were quantified. Predictions showed the vaneless turbine stators to incur lower losses than the corresponding vaned stator at matching operating conditions, in line with the trends in measured performance.. Flow conditions at rotor inlet were studied and validated with internal static pressure measurements so as to judge the levels of circumferential nonuniformity for each stator design. In each case, the vaneless volutes were found to deliver a higher level of uniformity in the rotor inlet pressure field. [DOI: 10.1115/1.2988493]

Hyperglycaemia-induced pro-inflammatory responses by retinal Müller glia are regulated by the receptor for advanced glycation end-products (RAGE)

Aims/hypothesis: Up-regulation of the receptor for AGEs (RAGE) and its ligands in diabetes has been observed in various tissues. Here, we sought to determine levels of RAGE and one of its most important ligands, S100B, in diabetic retina, and to investigate the regulatory role of S100B and RAGE in Müller glia.

Methods: Streptozotocin-diabetes was induced in Sprague-Dawley rats. RAGE, S100B and glial fibrillary acidic protein (GFAP) were detected in retinal cryosections. In parallel, the human retinal Müller cell line, MIO-M1, was maintained in normal glucose (5.5 mmol/l) or high glucose (25 mmol/l). RAGE knockdown was achieved using small interfering RNA (siRNA), while soluble RAGE was used as a competitive inhibitor of RAGE ligand binding. RAGE, S100B and cytokines were detected using quantitative RT-PCR, western blotting, cytokine protein arrays or ELISA. Activation of mitogen-activated protein kinase (MAPK) by RAGE was determined by western blotting.

Results: Compared with non-diabetic controls, RAGE and S100B were significantly elevated in the diabetic retina with apparent localisation in the Müller glia, occurring concomitantly with upregulation of GFAP. Exposure of MIO-M1 cells to high glucose induced increased production of RAGE and S100B. RAGE signalling via MAPK pathway was linked to cytokine production. Blockade of RAGE prevented cytokine responses induced by high glucose and S100B in Müller glia.

Conclusions/interpretation: Hyperglycaemia in vivo and in vitro exposure to high glucose induce upregulation of RAGE and its ligands, leading to RAGE signalling, which links to pro-inflammatory responses by retinal Müller glia. These data shed light on the potential clinical application of RAGE blockade to inhibit the progression of diabetic retinopathy.