Drying kinetic analysis of municipal solid waste using modified page model and pattern search method

This work studied the drying kinetics of the organic fractions of municipal solid waste (MSW) samples with different initial moisture contents and presented a new method for determination of drying kinetic parameters. A series of drying experiments at different temperatures were performed by using a thermogravimetric technique. Based on the modified Page drying model and the general pattern search method, a new drying kinetic method was developed using multiple isothermal drying curves simultaneously. The new method fitted the experimental data more accurately than the traditional method. Drying kinetic behaviors under extrapolated conditions were also predicted and validated. The new method indicated that the drying activation energies for the samples with initial moisture contents of 31.1 and 17.2 % on wet basis were 25.97 and 24.73 kJ mol−1. These results are useful for drying process simulation and industrial dryer design. This new method can be also applied to determine the drying parameters of other materials with high reliability.

The n-tuple classifier: too good to ignore

The n-tuple pattern recognition method has been tested using a selection of 11 large data sets from the European Community StatLog project, so that the results could be compared with those reported for the 23 other algorithms the project tested. The results indicate that this ultra-fast memory-based method is a viable competitor with the others, which include optimisation-based neural network algorithms, even though the theory of memory-based neural computing is less highly developed in terms of statistical theory.

Susceptibility to pattern glare following stroke

The aim of this work was to measure susceptibility to pattern glare within a stroke group, employing a direct method of assessment. Twenty stroke subjects, aged 38-85 years, were recruited, along with an age-matched control group (n = 20). Assessment of pattern glare susceptibility was undertaken using the pattern glare test. An abnormal degree of pattern glare is present when individuals score >1 on the mid-high spatial frequency difference variable, a relative score that allows for normalization of the subject, or >3 when viewing the mid spatial frequency grating. Stroke subjects demonstrate elevated levels of pattern glare compared to normative data values and a control population, as determined using the pattern glare test. This was most notable when considering the output measure for the mid-high difference variable. The mean score for the mid-high difference variable was 2.15 SD 1.27 for the stroke subjects versus 0.10 SD 1.12 for the control subjects. When considering the mid-high difference variable, 75% of the stroke group recorded an abnormal level of pattern glare compared to 5% in the control group. This study demonstrates an association between stroke subjects and elevated levels of pattern glare. Cortical hyperexcitability has been shown to present following stroke, and this has been proposed as a plausible explanation for the perceptual distortions experienced by individuals susceptible to pattern glare. Further work to assess the benefits of spectral filters in reducing perceptual distortions in stroke patients is currently underway.

Polarisation mode dispersion correlations with the coarse-step method

Having a fixed differential-group delay (DGD) term b′ in the coarse-step method results in a repetitive pattern in the autocorrelation function (ACF). We solve this problem by inserting a varying DGD term at each integration step. Furthermore we compute the range of values needed for b′ and simulate the phenomenon of polarisation mode dispersion for different statistical distributions of b′. We examine systematically the modified coarse-step method compared to the analytical model, through our simulation results. © 2006 Elsevier B.V. All rights reserved.

Numerical implementation of the coarse step method with a varying differential group delay

The effect of having a fixed differential group delay term in the coarse step method results in a periodic pattern in the inserting a varying DGD term at each integration step, according to a Gaussian distribution. Simulation results are given to illustrate the phenomenon and provide some evidence about its statistical nature.

The spatial pattern of senile plaques, neurofibrillary tangles and A4 deposits in Alzheimer's disease

The spatial patterns of senile plaques (SP) and neurofibrillary tangles (NFT) as visualised using the Gallyas stain and of discrete A4 protein deposits were determined in coronal serial sections from a variety of brain regions in six elderly patients with Alzheimer's disease (AD). These lesions showed clustering in virtually all tissues examined with many of the clusters being regularly spaced. These spatial patterns were compared with the clustering observed for SP and NFT stained by the Glees and Marsland method in the same tissues. The data suggest that on average, while the regular clusters of A4 deposits and NFT were of approximately the same mean diameter (3600 microns), clusters of both Glees and Gallyas SP were approximately half this diameter (1800 - 2000 microns). If SP develop in local areas of the brain where both A4 deposition and neurofibrillary changes have occurred, the data suggest that the SP clusters would represent the region of overlap of the A4 deposits and neurofibrillary changes. Various hypothese are advocated to explain the regular clsuetring of the A4 deposits.

Analysis of spatial patterns in histological sections of brain tissue using a method based on regression

A method of determining the spatial pattern of any histological feature in sections of brain tissue which can be measured quantitatively is described and compared with a previously described method. A measurement of a histological feature such as density, area, amount or load is obtained for a series of contiguous sample fields. The regression coefficient (β) is calculated from the measurements taken in pairs, first in pairs of adjacent samples and then in pairs of samples taken at increasing degrees of separation between them, i.e. separated by 2, 3, 4,..., n units. A plot of β versus the degree of separation between the pairs of sample fields reveals whether the histological feature is distributed randomly, uniformly or in clusters. If the feature is clustered, the analysis determines whether the clusters are randomly or regularly distributed, the mean size of the clusters and the spacing of the clusters. The method is simple to apply and interpret and is illustrated using simulated data and studies of the spatial patterns of blood vessels in the cerebral cortex of normal brain, the degree of vacuolation of the cortex in patients with Creutzfeldt-Jacob disease (CJD) and the characteristic lesions present in Alzheimer's disease (AD). Copyright (C) 2000 Elsevier Science B.V.

Spatial pattern analysis of beta-amyloid (A beta) deposits in Alzheimer disease by linear regression

The spatial patterns of discrete beta-amyloid (Abeta) deposits in brain tissue from patients with Alzheimer disease (AD) were studied using a statistical method based on linear regression, the results being compared with the more conventional variance/mean (V/M) method. Both methods suggested that Abeta deposits occurred in clusters (400 to <12,800 mu m in diameter) in all but 1 of the 42 tissues examined. In many tissues, a regular periodicity of the Abeta deposit clusters parallel to the tissue boundary was observed. In 23 of 42 (55%) tissues, the two methods revealed essentially the same spatial patterns of Abeta deposits; in 15 of 42 (36%), the regression method indicated the presence of clusters at a scale not revealed by the V/M method; and in 4 of 42 (9%), there was no agreement between the two methods. Perceived advantages of the regression method are that there is a greater probability of detecting clustering at multiple scales, the dimension of larger Abeta clusters can be estimated more accurately, and the spacing between the clusters may be estimated. However, both methods may be useful, with the regression method providing greater resolution and the V/M method providing greater simplicity and ease of interpretation. Estimates of the distance between regularly spaced Abeta clusters were in the range 2,200-11,800 mu m, depending on tissue and cluster size. The regular periodicity of Abeta deposit clusters in many tissues would be consistent with their development in relation to clusters of neurons that give rise to specific neuronal projections.

The influence of age on the pattern and flash visual evoked field

We have investigated the effect of ageing on the visual system using the relatively new technique of magentoencephalography (MEG). This technique measures the magnetic signals produced by the visual system using a SQUID magnetometer. The magnetic visual evoked field (VEF) was measured over the occipital cortex to pattern and flash stimuli in 86 normal subjects aged 15 - 86 years. Factors that influenced subject defocussing or defixating the stimulus or selective attention were controlled as far as possible. The latency of the major positive component to the pattern reversal stimulus (P100M) increased with age particularly after the age of 55 years while the amplitude of the P100M decreased over the life span. The latency of the major flash component (P2M) increased much more slowly with age, while its amplitude decreased in only a proportion of elderly subjects. Changes in the P100M with age may reflect senile changes in the eye and optic nerve, e.g. senile miosis or degenerative changes in the retina. The P2M may be more susceptible to senile changes in the retina. The data suggest that the spatial frequency channels deteriorate more rapidly with age than the luminance channels and that MEG may be an effective method of studying ageing in the visual system.

The use of flow control devices to improve the flow pattern and throughput of sieve trays

Compared to packings trays are more cost effective column internals because they create a large interfacial area for mass transfer by the interaction of the vapour on the liquid. The tray supports a mass of froth or spray which on most trays (including the most widely used sieve trays) is not in any way controlled. The two important results of the gas/liquid interaction are the tray efficiency and the tray throughput or capacity. After many years of practical experience, both may be predicted by empirical correlations, despite the lack of understanding. It is known that the tray efficiency is in part determined by the liquid flow pattern and the throughput by the liquid froth height which in turn depends on the liquid hold-up and vapour velocity. This thesis describes experimental work on sieve trays in an air-water simulator, 2.44 m in diameter. The liquid flow pattern, for flow rates similar to those used in commercial scale distillation, was observed experimentally by direct observation; by water-cooling, to simulate mass transfer; use of potassium permanganate dye to observe areas of longer residence time; and by height of clear liquid measurements across the tray and in the downcomer using manometers. This work presents experiments designed to evaluate flow control devices proposed to improve the gas liquid interaction and hence improve the tray efficiency and throughput. These are (a) the use of intermediate weirs to redirect liquid to the sides of the tray so as to remove slow moving/stagnant liquid and (b) the use of vapour-directing slots designed to use the vapour to cause liquid to be directed towards the outlet weir thus reducing the liquid hold-up at a given rate i.e. increased throughput. This method also has the advantage of removing slow moving/stagnant liquid. In the experiments using intermediate weirs, which were placed in the centre of the tray. it was found that in general the effect of an intermediate weir depends on the depth of liquid downstream of the weir. If the weir is deeper than the downstream depth it will cause the upstream liquid to be deeper than the downstream liquid. If the weir is not as deep as deep as the downstream depth it may have little or no effect on the upstream depth. An intermediate weir placed at an angle to the direction of flow of liquid increases the liquid towards the sides of the tray without causing an increase in liquid hold-up/ froth height. The maximum proportion of liquid caused to flow sideways by the weir is between 5% and 10%. Experimental work using vapour-directing slots on a rectangular sieve tray has shown that the horizontal momentum that is imparted to the liquid is dependent upon the size of the slot. If too much momentum is transferred to the liquid it causes hydraulic jumps to occur at the mouth of the slot coupled with liquid being entrained, The use of slots also helps to eliminate the hydraulic gradient across sieve trays and provides a more uniform froth height on the tray. By comparing the results obtained of the tray and point efficiencies, it is shown that a slotted tray reduces both values by approximately 10%. This reduction is due to the fact that with a slotted tray the liquid has a reduced residence time Ion the tray coupled also with the fact that large size bubbles are passing through the slots. The effectiveness of using vapour-directing slots on a full circular tray was investigated by using dye to completely colour the biphase. The removal of the dye by clear liquid entering the tray was monitored using an overhead camera. Results obtained show that the slots are successful in their aim of reducing slow moving liquid from the sides of the tray, The net effect of this is an increase in tray efficiency. Measurements of slot vapour-velocity found it to be approximately equal to the hole velocity.

Mitigation of pattern sensitivity in full-field electronic dispersion compensation

We investigate the pattern-dependent decoding failures in full-field electronic dispersion compensation (EDC) by offline processing of experimental signals, and find that the performance of such an EDC receiver may be degraded by an isolated "1" bit surrounded by long strings of consecutive "0s". By reducing the probability of occurrence of this kind of isolated "1" and using a novel adaptive threshold decoding method, we greatly improve the compensation performance to achieve 10-Gb/s on-off keyed signal transmission over 496-km field-installed single-mode fiber without optical dispersion compensation.

Interactions between landcover pattern and geospatial processing methods:effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

Examination of the predictive value of structural magnetic resonance scans in bipolar disorder:a pattern classification approach

Background - Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method - GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. Results - The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. Conclusions - Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Numerical implementation of the coarse step method with a varying differential group delay

The effect of having a fixed differential-group delay term in the coarse-step method results in a periodic pattern in the autocorrelation function. We solve this problem by inserting a varying DGD term at each integration step, according to a Gaussian distribution. Simulation results are given to illustrate the phenomenon and provide some evidence, about its statistical nature.

Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties

Subunit vaccine discovery is an accepted clinical priority. The empirical approach is time- and labor-consuming and can often end in failure. Rational information-driven approaches can overcome these limitations in a fast and efficient manner. However, informatics solutions require reliable algorithms for antigen identification. All known algorithms use sequence similarity to identify antigens. However, antigenicity may be encoded subtly in a sequence and may not be directly identifiable by sequence alignment. We propose a new alignment-independent method for antigen recognition based on the principal chemical properties of protein amino acid sequences. The method is tested by cross-validation on a training set of bacterial antigens and external validation on a test set of known antigens. The prediction accuracy is 83% for the cross-validation and 80% for the external test set. Our approach is accurate and robust, and provides a potent tool for the in silico discovery of medically relevant subunit vaccines.