Kinetic study of the thermal degradation of high density polyethylene

The thermal degradation of high density polyethylene has been modelled by the random breakage of polymer bonds, using a set of population balance equations. A model was proposed in which the population balances were lumped into representative sizes so that the experimentally determined molecular weight distribution of the original polymer could be used as the initial condition. This model was then compared to two different cases of the unlumped population balance which assumed unimolecular initial distributions of 100 and 500 monomer units, respectively. The model that utilised the experimentally determined molecular weight distribution was found to best describe the experimental data. The model fits suggested a second mechanism in addition to random breakage at slow reaction rates. (c) 2005 Elsevier Ltd. All rights reserved.

Onset of sheath extension and duration of lamina extension are major determinants of the response of maize lamina length to plant density

Background and Aims Plants regulate their architecture strongly in response to density, and there is evidence that this involves changes in the duration of leaf extension. This questions the approximation, central in crop models, that development follows a fixed thermal time schedule. The aim of this research is to investigate, using maize as a model, how the kinetics of extension of grass leaves change with density, and to propose directions for inclusion of this regulation in plant models. • Methods Periodic dissection of plants allowed the establishment of the kinetics of lamina and sheath extension for two contrasting sowing densities. The temperature of the growing zone was measured with thermocouples. Two-phase (exponential plus linear) models were fitted to the data, allowing analysis of the timing of the phase changes of extension, and the extension rate of sheaths and blades during both phases. • Key Results The duration of lamina extension dictated the variation in lamina length between treatments. The lower phytomers were longer at high density, with delayed onset of sheath extension allowing more time for the lamina to extend. In the upper phytomers—which were shorter at high density—the laminae had a lower relative extension rate (RER) in the exponential phase and delayed onset of linear extension, and less time available for extension since early sheath extension was not delayed. • Conclusions The relative timing of the onset of fast extension of the lamina with that of sheath development is the main determinant of the response of lamina length to density. Evidence is presented that the contrasting behaviour of lower and upper phytomers is related to differing regulation of sheath ontogeny before and after panicle initiation. A conceptual model is proposed to explain how the observed asynchrony between lamina and sheath development is regulated.

Longitudinal Genetic Analysis of Plasma Lipids

The consensus from published studies is that plasma lipids are each influenced by genetic factors, and that this contributes to genetic variation in risk of cardiovascular disease. Heritability estimates for lipids and lipoproteins are in the range .48 to .87, when measured once per study participant. However, this ignores the confounding effects of biological variation measurement error and ageing, and a truer assessment of genetic effects on cardiovascular risk may be obtained from analysis of longitudinal twin or family data. We have analyzed information on plasma high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, and triglycerides, from 415 adult twins who provided blood on two to five occasions over 10 to 17 years. Multivariate modeling of genetic and environmental contributions to variation within and across occasions was used to assess the extent to which genetic and environmental factors have long-term effects on plasma lipids. Results indicated that more than one genetic factor influenced HDL and LDL components of cholesterol, and triglycerides over time in all studies. Nonshared environmental factors did not have significant long-term effects except for HDL. We conclude that when heritability of lipid risk factors is estimated on only one occasion, the existence of biological variation and measurement errors leads to underestimation of the importance of genetic factors as a cause of variation in long-term risk within the population. In addition our data suggest that different genes may affect the risk profile at different ages.

Influence of nanowire density on the shape and optical properties of ternary InGaAs nanowires

We have synthesized ternary InGaAs nanowires on (111)B GaAs surfaces by metal-organic chemical vapor deposition. Au colloidal nanoparticles were employed to catalyze nanowire growth. We observed the strong influence of nanowire density on nanowire height, tapering, and base shape specific to the nanowires with high In composition. This dependency was attributed to the large difference of diffusion length on (111)B surfaces between In and Ga reaction species, with In being the more mobile species. Energy dispersive X-ray spectroscopy analysis together with high-resolution electron microscopy study of individual InGaAs nanowires shows large In/Ga compositional variation along the nanowire supporting the present diffusion model. Photoluminescence spectra exhibit a red shift with decreasing nanowire density due to the higher degree of In incorporation in more sparsely distributed InGaAs nanowires.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.

The effect of residence time and aeration on coal recovery within the high density zone of a flotation machine

The high intensity zone within the Jameson Cell is the downcomer. It is largely external and separated from the flotation tank. This, together with operation of the downcomer under vacuum, rather than at elevated pressure and the absence of moving parts, allows ready access to the high intensity zone for measurement and analysis. Experimentation was conducted allowing measurements of recovery for residence times of between 20 milliseconds and ten seconds within the downcomer of a Jameson Cell. The affect of aeration rate on the recovery of different particle sizes was also studied.

Issues of robustness and high dimensionality in cluster analysis

Finite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena. While normal mixture models are often used to cluster data sets of continuous multivariate data, a more robust clustering can be obtained by considering the t mixture model-based approach. Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data where the number of observations n is very large relative to their dimension p. As the approach using the multivariate normal family of distributions is sensitive to outliers, it is more robust to adopt the multivariate t family for the component error and factor distributions. The computational aspects associated with robustness and high dimensionality in these approaches to cluster analysis are discussed and illustrated.

Quantification of axonal loss in Alzheimer’s disease: an image analysis study

The density of axons in the optic nerve, olfactory tract and corpus callosum was quantified in non-demented elderly subjects and in Alzheimer’s disease (AD) using an image analysis system. In each fibre tract, there was significant reduction in the density of axons in AD compared with non-demented subjects, the greatest reductions being observed in the olfactory tract and corpus callosum. Axonal loss in the optic nerve and olfactory tract was mainly of axons with smaller myelinated cross-sectional areas. In the corpus callosum, a reduction in the number of ‘thin’ and ‘thick’ fibres was observed in AD, but there was a proportionally greater loss of the ‘thick’ fibres. The data suggest significant degeneration of white matter fibre tracts in AD involving the smaller axons in the two sensory nerves and both large and small axons in the corpus callosum. Loss of axons in AD could reflect an associated white matter disorder and/or be secondary to neuronal degeneration.

The identification of pathological subtypes of Alzheimer's disease using cluster analysis

A culster analysis was performed on 78 cases of Alzheimer's disease (AD) to identify possible pathological subtypes of the disease. Data on 47 neuropathological variables, inculding features of the gross brain and the density and distribution of senile plaques (SP) and neurofibrillary tangles (NFT) were used to describe each case. Cluster analysis is a multivariate statistical method which combines together in groups, AD cases with the most similar neuropathological characteristics. The majority of cases (83%) were clustered into five such groups. The analysis suggested that an initial division of the 78 cases could be made into two major groups: (1) a large group (68%) in which the distribution of SP and NFT was restricted to a relatively small number of brain regions, and (2) a smaller group (15%) in which the lesions were more widely disseminated throughout the neocortex. Each of these groups could be subdivided on the degree of capillary amyloid angiopathy (CAA) present. In addition, those cases with a restricted development of SP/NFT and CAA could be divided further into an early and a late onset form. Familial AD cases did not cluster as a separate group but were either distributed between four of the five groups or were cases with unique combinations of pathological features not closely related to any of the groups. It was concluded that multivariate statistical methods may be of value in the classification of AD into subtypes. © 1994 Springer-Verlag.

Probabilistic principal component analysis

Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.

Probabilistic principal component analysis

Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.

Statistical mechanics of low-density parity-check codes

We review recent theoretical progress on the statistical mechanics of error correcting codes, focusing on low-density parity-check (LDPC) codes in general, and on Gallager and MacKay-Neal codes in particular. By exploiting the relation between LDPC codes and Ising spin systems with multispin interactions, one can carry out a statistical mechanics based analysis that determines the practical and theoretical limitations of various code constructions, corresponding to dynamical and thermodynamical transitions, respectively, as well as the behaviour of error-exponents averaged over the corresponding code ensemble as a function of channel noise. We also contrast the results obtained using methods of statistical mechanics with those derived in the information theory literature, and show how these methods can be generalized to include other channel types and related communication problems.

A statistical-mechanical analysis of coded CDMA with regular LDPC codes

We analyze, using the replica method of statistical mechanics, the theoretical performance of coded code-division multiple-access (CDMA) systems in which regular low-density parity-check (LDPC) codes are used for channel coding.