Model-based analysis of anaerobic acetate uptake by a mixed culture of polyphosphate-accumulating and glycogen-accumulating organisms

An increasing number of studies shows that the glycogen-accumulating organisms (GAOs) can survive and may indeed proliferate under the alternating anaerobic/aerobic conditions found in EBPR systems, thus forming a strong competitor of the polyphosphate-accumulating organisms (PAOs). Understanding their behaviors in a mixed PAO and GAO culture under various operational conditions is essential for developing operating strategies that disadvantage the growth of this group of unwanted organisms. A model-based data analysis method is developed in this paper for the study of the anaerobic PAO and GAO activities in a mixed PAO and GAO culture. The method primarily makes use of the hydrogen ion production rate and the carbon dioxide transfer rate resulting from the acetate uptake processes by PAOs and GAOs, measured with a recently developed titration and off-gas analysis (TOGA) sensor. The method is demonstrated using the data from a laboratory-scale sequencing batch reactor (SBR) operated under alternating anaerobic and aerobic conditions. The data analysis using the proposed method strongly indicates a coexistence of PAOs and GAOs in the system, which was independently confirmed by fluorescent in situ hybridization (FISH) measurement. The model-based analysis also allowed the identification of the respective acetate uptake rates by PAOs and GAOs, along with a number of kinetic and stoichiometric parameters involved in the PAO and GAO models. The excellent fit between the model predictions and the experimental data not involved in parameter identification shows that the parameter values found are reliable and accurate. It also demonstrates that the current anaerobic PAO and GAO models are able to accurately characterize the PAO/GAO mixed culture obtained in this study. This is of major importance as no pure culture of either PAOs or GAOs has been reported to date, and hence the current PAO and GAO models were developed for the interpretation of experimental results of mixed cultures. The proposed method is readily applicable for detailed investigations of the competition between PAOs and GAOs in enriched cultures. However, the fermentation of organic substrates carried out by ordinary heterotrophs needs to be accounted for when the method is applied to the study of PAO and GAO competition in full-scale sludges. (C) 2003 Wiley Periodicals, Inc.

A modified Weibull distribution

A new lifetime distribution capable of modeling a bathtub-shaped hazard-rate function is proposed. The proposed model is derived as a limiting case of the Beta Integrated Model and has both the Weibull distribution and Type I extreme value distribution as special cases. The model can be considered as another useful 3-parameter generalization of the Weibull distribution. An advantage of the model is that the model parameters can be estimated easily based on a Weibull probability paper (WPP) plot that serves as a tool for model identification. Model characterization based on the WPP plot is studied. A numerical example is provided and comparison with another Weibull extension, the exponentiated Weibull, is also discussed. The proposed model compares well with other competing models to fit data that exhibits a bathtub-shaped hazard-rate function.

A new approach to control of MIMO processes with static nonlinearities using an extended IMC framework

In this paper, a new control design method is proposed for stable processes which can be described using Hammerstein-Wiener models. The internal model control (IMC) framework is extended to accommodate multiple IMC controllers, one for each subsystem. The concept of passive systems is used to construct the IMC controllers which approximate the inverses of the subsystems to achieve dynamic control performance. The Passivity Theorem is used to ensure the closed-loop stability. (c) 2005 Elsevier Ltd. All rights reserved.

The effect of pH on the competition between polyphosphate-accumulating organisms and glycogen-accumulating organisms

In enhanced biological phosphorus removal (EBPR) processes, glycogen-accumulating organisms (GAOs) may compete with polyphosphate-accumulating organisms (PAOs) for the often-limited carbon substrates, potentially resulting in disturbances to phosphorus removal. A detailed investigation of the effect of pH on the competition between PAOs and GAOs is reported in this study. The results show that a high external pH (similar to 8) provided PAOs with an advantage over GAOs in EBPR systems. The phosphorus removal performance improved due to a population shift favouring PAOs over GAOs, which was shown through both chemical and microbiological methods. Two lab-scale reactors fed with propionate as the carbon source were subjected to an increase in pH from 7 to 8. The phosphorus removal and PAO population (as measured by quantitative fluorescence in situ hybridisation analysis of Candidatus Accumulibacter phosphatis) increased in each system, where the PAOs appeared to out-compete a group of Alphaproteobacteria GAOs. A considerable improvement in the P removal was also observed in an acetate fed reactor, where the GAO population (primarily Candidatus Competibacter phosphatis) decreased substantially after a similar increase in the pH. The results from this study suggest that pH could be used as a control parameter to reduce the undesirable proliferation of GAOs and improve phosphorus removal in EBPR systems. (c) 2005 Elsevier Ltd. All rights reserved.

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

A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

Identification of a new ligand binding domain in the al subunit of the inhibitory glycine receptor

Four discontinuous extracellular sequence domains have been proposed to form the ligand binding sites of the ligand-gated ion channel receptor superfamily. In this study, we investigated the role of 12 contiguous residues of the inhibitory glycine receptor that define the proposed loop A ligand binding domain; Using the techniques of site-directed mutagenesis and patch-clamp electrophysiology, four of the 12 residues were shown to have impaired ligand binding. Three mutants, I93A, A101H, and N102A, resulted in significant (17-44-fold) increases in the agonist EC50 values as compared with the wild-type glycine receptor, whereas Hill coefficients, I-max values, and antagonist affinity remained largely unaffected. Consideration of receptor efficacy values indicates that these residues are involved in ligand binding rather than channel activation. A fourth mutant, W94A, failed to give rise to any glycine-activated currents, although cell-surface expression was observed, suggesting that this residue may also be involved in agonist binding. These data provide the most extensive characterization of the loop A ligand binding domain available to date and define two new residue locations, Ile(93) and Asn(102), as contributing to the four-loop model of ligand binding.

Identification of initiation sites for T4 lysozyme folding using CD and NMR spectroscopy of peptide fragments

Using CD and 2D H-1 NMR spectroscopy, we have identified potential initiation sites for the folding of T4 lysozyme by examining the conformational preferences of peptide fragments corresponding to regions of secondary structure. CD spectropolarimetry showed most peptides were unstructured in water, but adopted partial helical conformations in TFE and SDS solution. This was also consistent with the H-1 NMR data which showed that the peptides were predominantly disordered in water, although in some cases, nascent or small populations of partially folded conformations could be detected. NOE patterns, coupling constants, and deviations from random coil Her chemical shift values complemented the CD data and confirmed that many of the peptides were helical in TFE and SDS micelles. In particular, the peptide corresponding to helix E in the native enzyme formed a well-defined helix in both TFE and SDS, indicating that helix E potentially forms an initiation site for T4 lysozyme folding. The data for the other peptides indicated that helices D, F, G, and H are dependent on tertiary interactions for their folding and/or stability. Overall, the results from this study, and those of our earlier studies, are in agreement with modeling and IID-deuterium exchange experiments, and support an hierarchical model of folding for T4 lysozyme.

Identification of regions within the third FnIII-like domain of the IL-5R alpha involved in IL-5 interaction

Previously, two binding sites for interleukin 5 (IL-5) were identified on the IL-5 receptor alpha chain (IL-5R alpha). They are located within the CD loop of the first fibronectin type III (FnIII)-like domain and the EF loop of the second FnIII-like domain. The first binding site was identified by exploiting the different abilities of human IL-5R alpha (hIL-5R alpha) and mouse IL-5R alpha (mIL-5R alpha) to bind hIL-5. Here we show that ovine IL-5 (oIL-5) has the ability to activate the hIL-5R alpha but not the mIL-5R alpha. By using chimeras of the mIL-5R alpha and hIL-5R alpha we demonstrate that residues within the first and third FnIII-like domains of mIL-5R alpha are responsible for this lack of activity. Furthermore, mutation of residues on hIL-5R alpha to mIL-5R alpha within the predicted DE and FG loop regions of the third FnIII domain reduces oIL-5 activity, These results show that regions of the third FnIII domain of IL-5R alpha are involved in binding, in addition to the regions in domains one and two of the IL-5R alpha that were identified in an earlier study. (C) 2000 Academic Press.

Identification of physiologically functional peptides in dairy products

A wide range of peptides produced from milk proteins have been demonstrated to produce a physiological response in model systems. These peptides may be released from intact proteins in the gastrointestinal tract by proteolytic digestion, but are also present in fermented products such as cheese and yogurt, as a result of the action of inherent proteases, such as plasmin, and/or bacterial proteases released by the starter culture. This study investigated the presence of peptides, previously reported to have bioactive properties, in commercially available yogurts and cheeses.

A model for predicting the future incidence of coronary heart disease within percentiles of coronary heart disease risk

Background We present a method (The CHD Prevention Model) for modelling the incidence of fatal and nonfatal coronary heart disease (CHD) within various CHD risk percentiles of an adult population. The model provides a relatively simple tool for lifetime risk prediction for subgroups within a population. It allows an estimation of the absolute primary CHD risk in different populations and will help identify subgroups of the adult population where primary CHD prevention is most appropriate and cost-effective. Methods The CHD risk distribution within the Australian population was modelled, based on the prevalence of CHD risk, individual estimates of integrated CHD risk, and current CHD mortality rates. Predicted incidence of first fatal and nonfatal myocardial infarction within CHD risk strata of the Australian population was determined. Results Approximately 25% of CHD deaths were predicted to occur amongst those in the top 10 percentiles of integrated CHD risk, regardless of age group or gender. It was found that while all causes survival did not differ markedly between percentiles of CHD risk before the ages of around 50-60, event-free survival began visibly to differ about 5 years earlier. Conclusions The CHD Prevention Model provides a means of predicting future CHD incidence amongst various strata of integrated CHD risk within an adult population. It has significant application both in individual risk counselling and in the identification of subgroups of the population where drug therapy to reduce CHD risk is most cost-effective. J Cardiovasc Risk 8:31-37 (C) 2001 Lippincott Williams & Wilkins.

Bayesian analysis of the error correction model

This paper presents a method for estimating the posterior probability density of the cointegrating rank of a multivariate error correction model. A second contribution is the careful elicitation of the prior for the cointegrating vectors derived from a prior on the cointegrating space. This prior obtains naturally from treating the cointegrating space as the parameter of interest in inference and overcomes problems previously encountered in Bayesian cointegration analysis. Using this new prior and Laplace approximation, an estimator for the posterior probability of the rank is given. The approach performs well compared with information criteria in Monte Carlo experiments. (C) 2003 Elsevier B.V. All rights reserved.

Identification of river sections for domestic water supply along the Yangtze River in Jiangsu Province, China

This paper presents major findings from a recent study aiming to systematically determine suitable river sections for local domestic water supply along the Yangtze River in Jiangsu Province, China. On the basis of analysis on the current riverbank utilization and bank stability, accessible and stable river sections in the region were selected. The water quality in these river sections was then studied using a two-dimensional unsteady flow and pollutant transport/transformation model, RBFVM-2D. The model was calibrated and verified against the hydrodynamic data, water quality data and remote sensing data collected from the river. The investigation on the pollution sources along the river identified 56 main pollution point sources. The pollution zones downstream of these point sources are the main threat for the water quality in the river. The model was used to compute the pollution zones. In particular, simulations were conducted to establish the relationship between the extent of the pollution zone and the wastewater discharge rate of the associated point source. These water quality simulation results were combined with the riverbank stability analysis to determine suitable river sections for local domestic water supply.