Ultra-thin porous silica coated silver-platinum alloy nano-particle as a new catalyst precursor

Templated sol-gel encapsulation of surfactant-stabilised micelles containing metal precursor(s) with ultra-thin porous silica coating allows solvent extraction of organic based stabiliser from the composites in colloidal state hence a new method of preparing supported alloy catalysts using the inorganic silica-stabilised nano-sized, homogenously mixed, silver - platinum (Ag-Pt) colloidal particles is reported.

Chylomicron particle size and number, factor VII activation and dietary monounsaturated fatty acids

This study evaluated the effects of substituting dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) on postprandial chylomicron (triacylglycerol (TAG), apolipoprotein B-48 (apo B-48) and retinyl ester (RE)), chylomicron particle size and factor VII (FVII) response when subjects were given a standard meal. In a controlled sequential design, 51 healthy young subjects followed an SFA-rich diet (Reference diet) for 8 weeks after which half of the subjects followed a moderate MUFA diet (n = 25) and half followed a high MUFA diet (n = 26) for 16 weeks. Fasting lipoprotein and lipid measurements were evaluated at baseline and at 8-week intervals during the Reference and MUFA diets. In 25 of the subjects (n = 12 moderate MUFA, n = 13 high MUFA), postprandial responses to a standard test meal containing RE and 13 C-tripalmitin were investigated at the end of the Reference and the MUFA diet periods. Although there were no differences in the postprandial lipid markers (TAG, RE, C-13-TAG) on the two diets, the postprandial apo B-48 response (incremental area under the curve (IAUC) was reduced by 21% on the moderate MUFA diet (NS) and by 54% on the high MUFA diet (P < 0.01). The postprandial peak concentrations of apo B-48 were reduced by 33% on the moderate MUFA diet (P < 0.01) and 48% on the high MUFA diet (P < 0.001). Fasting values for factor VII activity (FVIIc), activated factor VII (FVIIa) or factor VII antigen (FVIIag) did not differ significantly when subjects were transferred from Reference to MUFA diets. However, the postprandial increases in coagulation FVII activity (FVIIc) were 18% lower and of activated FVII (FVIIa) were 17% lower on the moderate MUFA diet (NS). Postprandial increases in FVIIc and FVIIa were 50% (P < 0.05) and 29% (P < 0.07) lower on the high MUFA diet and the area under the postprandial FVIIc response curve (AUC) was also lower on the high MUFA diet (P < 0.05). Significantly higher ratios of RE:apo B-48 (P < 0.001) and 13 C-palmitic acid:apo B-48 (P < 0.01) during both MUFA diets suggest that the CMs formed carry larger amounts of dietary lipids per particle, reflecting an adaptation to form larger lipid droplets in the enterocyte when increased amounts of dietary MUFAs are fed. Smaller numbers of larger chylomicrons may explain attenuated activation of factor VII during the postprandial state when the background diet is rich in MUFA. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Saturated fat-induced changes in S-f 60-400 particle composition reduces uptake of LDL by HepG2 cells

The ability of human postprandial triacylglycerol-rich lipoproteins (TRLs), isolated after meals enriched in saturated fatty acids (SFAs), n-6 PUFAs, and MUFAs, to inhibit the uptake of I-125-labeled LDL by the LDL receptor was investigated in HepG2 cells. Addition of TRLs resulted in a dose-dependent inhibition of heparin-releasable binding, cell-associated radioactivity, and degradation products of I-125-labeled LDL (P < 0.001). SFA-rich Svedberg flotation rate (S-f) 60-400 resulted in significantly greater inhibition of cell-associated radioactivity than PUFA-rich particles (P = 0.016) and total uptake of I-125-labeled LDL compared with PUFA- and MUFA-rich particles (P = 0.02). Normalization of the apolipoprotein (apo)E but not apoC-III content of the TRLs removed the effect of meal fatty acid composition, and addition of an anti-apoE antibody reversed the inhibitory effect of TRLs on the total uptake of I-125-labeled LDL. Real time RT-PCR showed that the SFA-rich Sf 60-400 increased the expression of genes involved in hepatic lipid synthesis (P < 0.05) and decreased the expression of the LDL receptor-related protein 1 compared with MUFAs (P = 0.008). In conclusion, these findings suggest an alternative or additional mechanism whereby acute fat ingestion can influence LDL clearance via competitive apoE-dependent effects of TRL on the LDL receptor.-Jackson, K. G., V. Maitin, D. S. Leake, P. Yaqoob, and C. M. Williams. Saturated fat-induced changes in Sf 60 400 particle composition reduces uptake of LDL by HepG2 cells.

Robust classification of SAR imagery

In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aperture (SAR) imagery data under the Multiplicative Model. The observed data, therefore, is assumed to obey a G(A)(0) (alpha; gamma, n) law, where the parameter n is related to the speckle noise, and (alpha, gamma) are related to the ground truth, giving information about the background. Therefore, maps generated by the estimation of (alpha, gamma) in each coordinate can be used as the input for classification methods. Maximum likelihood estimators are derived and used to form estimated parameter maps. This estimation can be hampered by the presence of corner reflectors, man-made objects used to calibrate SAR images that produce large return values. In order to alleviate this contamination, robust (M) estimators are also derived for the universal model. Gaussian Maximum Likelihood classification is used to obtain maps using hard-to-deal-with simulated data, and the superiority of robust estimation is quantitatively assessed.

Towards the automatic reconstruction of dendritic trees using particle filters

The 3D reconstruction of a Golgi-stained dendritic tree from a serial stack of images captured with a transmitted light bright-field microscope is investigated. Modifications to the bootstrap filter are discussed such that the tree structure may be estimated recursively as a series of connected segments. The tracking performance of the bootstrap particle filter is compared against Differential Evolution, an evolutionary global optimisation method, both in terms of robustness and accuracy. It is found that the particle filtering approach is significantly more robust and accurate for the data considered.

Improvement of classification accuracy for stochastic discrimination - Multi-class classification

In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

Classification of lactose and mandelic acid THz spectra using subspace and wavelet-packet algorithms

This work compares classification results of lactose, mandelic acid and dl-mandelic acid, obtained on the basis of their respective THz transients. The performance of three different pre-processing algorithms applied to the time-domain signatures obtained using a THz-transient spectrometer are contrasted by evaluating the classifier performance. A range of amplitudes of zero-mean white Gaussian noise are used to artificially degrade the signal-to-noise ratio of the time-domain signatures to generate the data sets that are presented to the classifier for both learning and validation purposes. This gradual degradation of interferograms by increasing the noise level is equivalent to performing measurements assuming a reduced integration time. Three signal processing algorithms were adopted for the evaluation of the complex insertion loss function of the samples under study; a) standard evaluation by ratioing the sample with the background spectra, b) a subspace identification algorithm and c) a novel wavelet-packet identification procedure. Within class and between class dispersion metrics are adopted for the three data sets. A discrimination metric evaluates how well the three classes can be distinguished within the frequency range 0. 1 - 1.0 THz using the above algorithms.

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is computationally more efficient.