Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

Reduction in scar thickness post myocardial infarction is secondary to increase in regional left ventricular volumes

We sought to determine the relative impact of myocardial scar and viability on post-infarct left ventricular (LV) remodeling in medically-treated patients with LV dysfunction. Forty patients with chronic ischemic heart disease (age 64±9, EF 40±11%) underwent rest-redistribution Tl201 SPECT (scar = 50% transmural extent), A global index of scarring for each patient (CMR scar score) was calculated as the sum of transmural extent scores in all segts. LV end diastolic volumes (LVEDV) and LV end systolic volumes (LVESV) were measured by real-time threedimensional echo at baseline and median of 12 months follow-up. There was a significant positive correlation between change in LVEDV with number of scar segts by all three imaging techniques (LVEDV: SPECT scar, r = 0.62, p < 0.001; DbE scar, r = 0.57, p < 0.001; CMR scar, r = 0.52, p < 0.001) but change in LV volumes did not the correlate with number of viable segments. ROC curve analysis showed that remodeling (LVEDV> 15%) was predicted bySPECTscars(AUC= 0.79),DbEscars(AUC= 0.76),CMR scars (AUC= 0.70), and CMR scar score (AUC 0.72). There were no significant differences between any of the ROC curves (Z score

Weight reduction in patients with chronic HCV reduces circulating insulin levels

Steatosis occurs in >50% of patients with chronic HCV. In patients with viral genotype 3, steatosis may be a cytopathic effect of the virus. However in many patients with HCV, the pathogenesis of steatosis appears to be the same as for patients with non-alcoholic fatty liver disease (NAFLD) ie related to increased body mass index (BMI). We studied the effect of a 12 week weight reduction program on metabolic parameters in subjects with chronic HCV genotype 1 (Group 1, n = 16), genotype 3 (Group 2, n = 13) and patients with NAFLD (Group 3, n = 13). A liver biopsy was performed prior to and 3-6 months after the intervention period in 15 patients. The mean (SD) BMI of subjects in groups 1, 2 and 3 was 30.7 (4.0), 29.0 (5.2) and 33.3 (7.7), respectively. There was no significant difference in the amount of weight loss, change in waist circumference, change in ALT or reduction in steatosis between the 3 groups. Mean (SD) weight loss was 5.1 (3.7) kg. In those patients who lost weight, serum insulin (mean (SD) mU/L) changed from 17.8 (7.8) to 11.5 (4.8) (p = 0.003), 12.4 (5.0) to 8.4 (4.3) (p = 0.02), and 16.9 (7.3) to 17.8 (8.1) (p = 0.76) in Groups 1, 2 and 3, respectively. A small amount of weight loss is associated with a reduction in circulating insulin levels in patients with chronic HCV, particularly in genotype 1. In patients with NAFLD, the lack of a significant decrease in circulating insulin with weight reduction may reflect the higher initial BMI or may be due to the pathogenesis of this disorder.

(Review) Body mass index and risk of diabetes mellitus in the Asia-Pacific region

Few prospective data from the Asia Pacific region are available relating body mass index to the risk of diabetes. Our objective was to provide reliable age, sex and region specific estimates of the associations between body mass index and diabetes. Twenty-seven cohort studies from Asia, New Zealand and Australia, including 154,989 participants, contributed 1,244,793 person-years of follow-up. Outcome data included a combination of incidence of diabetes (based on blood glucose measurements) and fatal diabetes events. Hazard ratios were calculated from Cox models, stratified by sex and cohort, and adjusted for age at risk and smoking. During follow-up (mean = 8 years), 75 fatal diabetes events and 242 new cases of diabetes were documented. There were continuous positive associations between baseline body mass index and risk of diabetes with each 2 kg/m(2) lower body mass index associated with a 27% (23-30%) lower risk of diabetes. The associations were stronger in younger age groups, and regional comparisons demonstrated slightly stronger associations in Asian than in Australasian cohorts (P = 0.04). This overview provides evidence of a strong continuous association between body mass index and diabetes in the Asia Pacific region. The results indicate considerable potential for reduction in incidence of diabetes with population-wide lowering of body mass index in this region.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Techniques to determine ignition, flame stability and burnout of blended coals in p.f. power station boilers

The blending of coals has become popular to improve the performance of coals, to meet specifications of power plants and, to reduce the cost of coals, This article reviews the results and provides new information on ignition, flame stability, and carbon burnout studies of blended coals. The reviewed studies were conducted in laboratory-, pilot-, and full-scale facilities. The new information was taken in pilot-scale studies. The results generally show that blending a high-volatile coal with a low-volatile coal or anthracite can improve the ignition, flame stability and burnout of the blends. This paper discusses two general methods to predict the performance of blended coals: (1) experiment; and (2) indices. Laboratory- and pilot-scale tests, at least, provide a relative ranking of the combustion performance of coal/blends in power station boilers. Several indices, volatile matter content, heating value and a maceral index, can be used to predict the relative ranking of ignitability and flame stability of coals and blends. The maceral index, fuel ratio, and vitrinite reflectance can also be used to predict the absolute carbon burnout of coal and blends within limits. (C) 2000 Elsevier Science Ltd. All rights reserved.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

A four-stage index 2 Diagonally Implicit Runge-Kutta method

High index Differential Algebraic Equations (DAEs) force standard numerical methods to lower order. Implicit Runge-Kutta methods such as RADAU5 handle high index problems but their fully implicit structure creates significant overhead costs for large problems. Singly Diagonally Implicit Runge-Kutta (SDIRK) methods offer lower costs for integration. This paper derives a four-stage, index 2 Explicit Singly Diagonally Implicit Runge-Kutta (ESDIRK) method. By introducing an explicit first stage, the method achieves second order stage calculations. After deriving and solving appropriate order conditions., numerical examples are used to test the proposed method using fixed and variable step size implementations. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.

Effect of weight reduction on liver histology and biochemistry in patients with chronic hepatitis C

Background: Steatosis occurs in more than 50% of patients with chronic hepatitis C and is associated with increased hepatic fibrosis. In many of these patients the pathogenesis of steatosis appears to be the some as for patients with non-alcoholic fatty liver disease-that is, related to visceral adiposity and obesity. Methods: The effect of a three month weight reduction programme on liver biochemistry and metabolic parameters was examined in 19 subjects with steatosis and chronic hepatitis C. Paired liver biopsies were performed in 10 subjects, prior to and 3-6 months following the intervention, to determine the effect of weight loss on liver histology. Results: There was a mean weight loss of 5.9 (3.2) kg and a mean reduction in waist circumference of 9.0 (5.0) cm. In 16 of the 19 patients, serum alanine aminotransferase levels fell progressively with weight loss. Mean fasting insulin fell from 16 (7) to 11 (4) mmol/l (p

Preparation and characterization of copper catalysts supported on mesoporous Al2O3 nanofibers for N2O reduction to N2

A series of mesoporous Al2O3 samples with different porous structures and phases were prepared and used as supports for Cu/Al2O3 catalysts. These catalysts were characterized by N-2 adsorption, NMR, TGA, XRD, and UV - vis spectroscopic techniques and tested for the catalytic reaction of N2O decomposition. The activity increased with the increasing calcination temperatures of supports from 450 to 900 degreesC; however, a further increase in calcination temperature up to 1200 degreesC resulted in a significant reduction in activity. Characterization revealed that the calcination temperatures of supports influenced the porous structures and phases of the supports, which in turn affected the dispersions, phases, and activities of the impregnated copper catalyst. The different roles of surface spinel, bulk CuAl2O4, and bulk CuO is clarified for N2O catalytic decomposition. Two mechanism schemes were thus proposed to account for the varying activities of different catalysts.

Kinetics of reduction of lead smelting slags with solid carbon

Research techniques and a methodology have been developed that enable the reduction kinetics of molten lead smelting slags with solid carbon to be studied. The rates of reduction of PbO-FeO-Fe2O3-CaO-SiO2 slags with carbon have been measured for a range of slag compositions for PbO concentrations between 3 and 100 weight percent, and temperatures between 1423 and 1573 K. The reduction rates were determined for both graphite and coke. Within the range of process conditions examined, it has been shown that the reaction rates are almost independent of carbon reactivity, SiO2/CaO and SiO2/Fe ratio in the range of compositions investigated and are not influenced by the presence of sulphur in the slag.The apparent first order rate constants for oxygen removal increase with increasing PbO concentration and oxygen activity in the slag. The data indicate that the rate limiting reaction step for the reduction of lead slags with solid carbon is the chemical reaction at the gas/slag interface.

Use of real-time three-dimensional echocardiography to measure left atrial volume: Comparison with other echocardiographic techniques

Objectives: Left atrial (LA) volume (LAV) is a prognostically important biomarker for diastolic dysfunction, but its reproducibility on repeated testing is not well defined. LA assessment with 3-dimensional. (3D) echocardiography (3DE) has been validated against magnetic resonance imaging, and we sought to assess whether this was superior to existing measurements for sequential echocardiographic follow-up. Methods: Patients (n = 100; 81 men; age 56 +/- 14 years) presenting for LA evaluation were studied with M-mode (MM) echocardiography, 2-dimensional (2D) echocardiography, and 3DE. Test-retest variation was performed by a complete restudy by a separate sonographer within 1 hour without alteration of hemodynamics or therapy. In all, 20 patients were studied for interobserver and intraobserver variation. LAVs were calculated by using M-mode diameter and planimetered atrial area in the apical. 4-chamber view to calculate an assumed sphere, as were prolate ellipsoid, Simpson's biplane, and biplane area-length methods. All were compared with 3DE. Results: The average LAV was 72 +/- 27 mL by 3DE. There was significant underestimation of LAV by M-mode (35 +/- 20 mL, r = 0.66, P < .01). The 3DE and various 2D echocardiographic techniques were well correlated: LA planimetry (85 +/- 38 mL, r = 0.77, P < .01), prolate ellipsoid (73 +/- 36 mL, r = 0.73, P = .04), area-length (64 +/- 30 mL, r = 0.74, P < .01), and Simpson's biplane (69 +/- 31 mL, r = 0.78, P = .06). Test-retest variation for 3DE was most favorable (r = 0.98, P < .01), with the prolate ellipsoid method showing most variation. Interobserver agreement between measurements was best for 3DE (r = 0.99, P < .01), with M-mode the worst (r = 0.89, P < .01). Intraobserver results were similar to interobserver, the best correlation for 3DE (r = 0.99, P < .01), with LA planimetry the worst (r = 0.91, P < .01). Conclusions. The 2D measurements correlate closely with 3DE. Follow-up assessment in daily practice appears feasible and reliable with both 2D and 3D approaches.

Effect of body mass index changes between ages 5 and 14 on blood pressure at age 14 - Findings from a birth cohort study

Weight reduction in clinical populations of severely obese children has been shown to have beneficial effects on blood pressure, but little is known about the effect of weight gain among children in the general population. This study compares the mean blood pressure at 14 years of age with the change in overweight status between ages 5 and 14. Information from 2794 children born in Brisbane, Australia, and who were followed up since birth and had body mass index (BMI) and blood pressure measurements at ages 5 and 14 were used. Systolic and diastolic blood pressure at age 14 was the main outcomes and different patterns of change in BMI from age 5 to 14 were the main exposure. Those who changed from being overweight at age 5 to having normal BMI at age 14 had similar mean blood pressures to those who had a normal BMI at both time points: age- and sex-adjusted mean difference in systolic blood pressure 1.54 ( - 0.38, 3.45) mm Hg and in diastolic blood pressure 0.43 ( - 0.95, 1.81) mm Hg. In contrast, those who were overweight at both ages or who had a normal BMI at age 5 and were overweight at age 14 had higher blood pressure at age 14 than those who had a normal BMI at both times. These effects were independent of a range of potential confounding factors. Our findings suggest that programs that successfully result in children changing from overweight to normal-BMI status for their age may have important beneficial effects on subsequent blood pressure.

Electricity market price spike forecast with data mining techniques

Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

An adaptive and dynamic dimensionality reduction method for high-dimensional indexing

The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approach to overcome degradation in performance with respect to increasing dimensions is to reduce the dimensionality of the original dataset before constructing the index. However, identifying the correlation among the dimensions and effectively reducing them are challenging tasks. In this paper, we present an adaptive Multi-level Mahalanobis-based Dimensionality Reduction (MMDR) technique for high-dimensional indexing. Our MMDR technique has four notable features compared to existing methods. First, it discovers elliptical clusters for more effective dimensionality reduction by using only the low-dimensional subspaces. Second, data points in the different axis systems are indexed using a single B+-tree. Third, our technique is highly scalable in terms of data size and dimension. Finally, it is also dynamic and adaptive to insertions. An extensive performance study was conducted using both real and synthetic datasets, and the results show that our technique not only achieves higher precision, but also enables queries to be processed efficiently. Copyright Springer-Verlag 2005