Demonstration of glycated insulin in human diabetic plasma and decreased biological activity assessed by euglycemic-hyperinsulinemic clamp technique in humans

The presence and biological significance of circulating glycated insulin has been evaluated by high-pressure liquid chromatography (HPLC), electrospray ionization mass spectrometry (ESI-MS), radioimmunoassay (RIA), receptor binding, and hyperinsulinemic-euglycemic clamp techniques. ESI-MS analysis of an HPLC-purified plasma pool from four male type 2 diabetic subjects (HbA(1e) 8.1 +/- 0.2%, plasma glucose 8.7 +/- 1.3 mmol/l [means +/- SE]) revealed two major insulin-like peaks with retention times of 14-16 min. After spectral averaging, the peak with retention time of 14.32 min exhibited a prominent triply charged (M+3H)(3+) species at 1,991.1 m/z, representing monoglycated insulin with an intact M-r of 5,970.3 Da. The second peak (retention time 15.70 min) corresponded to native insulin (M-r 5,807.6 Da), with the difference between the two peptides (162.7 Da) representing a single glucitol adduct (theoretical 164 Da). Measurement of glycated insulin in plasma of type 2 diabetic subjects by specific RIA gave circulating levels of 10.1 +/- 2.3 pmol/l, corresponding to -9% total insulin. Biological activity of pure synthetic monoglycated insulin (insulin B-chain Phe(1)-glucitol adduct) was evaluated in seven overnight-fasted healthy nonobese male volunteers using two-step euglycemic-hyperinsulinemic clamps (2 h at 16.6 mug (.) kg(-1) (.) min(-1), followed by 2 h at 83.0 mug (.) kg(-1) (.) min(-1); corresponding to 0.4 and 2.0 mU (.) kg(-1) (.) min(-1)). At the lower dose, the exogenons glucose infusion rates required to maintain euglycemia during steady state were significantly lower with glycated insulin (P

Fast model based feature matching technique applied to airport lighting

The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting. The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade–Lucus–Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.

A novel shrinkage technique based on the normal inverse Gaussian density model

This paper proposes a novel image denoising technique based on the normal inverse Gaussian (NIG) density model using an extended non-negative sparse coding (NNSC) algorithm proposed by us. This algorithm can converge to feature basis vectors, which behave in the locality and orientation in spatial and frequency domain. Here, we demonstrate that the NIG density provides a very good fitness to the non-negative sparse data. In the denoising process, by exploiting a NIG-based maximum a posteriori estimator (MAP) of an image corrupted by additive Gaussian noise, the noise can be reduced successfully. This shrinkage technique, also referred to as the NNSC shrinkage technique, is self-adaptive to the statistical properties of image data. This denoising method is evaluated by values of the normalized signal to noise rate (SNR). Experimental results show that the NNSC shrinkage approach is indeed efficient and effective in denoising. Otherwise, we also compare the effectiveness of the NNSC shrinkage method with methods of standard sparse coding shrinkage, wavelet-based shrinkage and the Wiener filter. The simulation results show that our method outperforms the three kinds of denoising approaches mentioned above.

Efficient modelling technique for fractal electromagnetic band-gap arrays

An efficient modelling technique is proposed for the analysis of a fractal-element electromagnetic band-gap array. The modelling is based on a method of moments modal analysis in conjunction with an interpolation scheme, which significantly accelerates the computations. The plane-wave and the surface-wave responses of the structure have been studied by means of transmission coefficients and dispersion diagrams. The multiband properties and the compactness of the proposed structure are presented. The technique is general and can be applied to arbitrary-shaped element geometries.

A Virtual Inspection Technique for Assessing the Dimensional Accuracy of Forged Compressor Blades Using FE Modeling and CMM Inspection

This paper presents research for developing a virtual inspection system that evaluates the dimensional tolerance of forged aerofoil blades formed using the finite element (FE) method. Conventional algorithms adopted by modern coordinate measurement processes have been incorporated with the latest free-form surface evaluation techniques to provide a robust framework for the dimensional inspection of FE aerofoil models. The accuracy of the approach had been verified with a strong correlation obtained between the virtual inspection data and coordinate measurement data from corresponding aerofoil components.