Full-scale demonstration of biological nutrient removal in a single tank SBR process

Complete biological nutrient removal (BNR) in a single tank, sequencing batch reactor (SBR) process, is demonstrated here at full-scale on a typical domestic wastewater. The unique feature of the UniFed process is the introduction of the influent into the settled sludge blanket during the settling and decant periods of the SBR operation. This achieves suitable conditions for denitrification and anaerobic phosphate release which is critical to successful biological phosphorus removal, It also achieves a selector effect, which helps in generating a compact, well settling biomass in the reactor. The results of this demonstration show that it is possible to achieve well over 90% removal of GOD, nitrogen and phosphorus in such a process. Effluent quality achieved over a six-month operating period directly after commissioning was: 29 mg/l GOD, 0.5 mg/l NH4-N, 1.5 mg/l NOx-N and 1.5 mg/l PO4-P (50%-iles of daily samples). During an 8-day, intensive sampling period, the effluent BOD5 was

Evidence for a sub-morphological inflammatory process in the liver in haemochromatosis

Background/Aims: The role of cytokines in hepatic injury has been examined for many liver diseases however little is known of the cytokine involvement in haemochromatosis. The aim of the current study was to examine the hepatic gene expression of potential proinflammatory and profibrogenic cytokines in haemochromatosis. Methods: Interferon-gamma, interleukin-10, transforming growth factor-beta(1) and tumor necrosis factor-alpha mRNA expression was assessed in liver tissue from 20 haemochromatosis patients, eight controls and eight chronic hepatitis C patients. To assess the immunophenotype of the inflammatory infiltrate in haemochromatosis, liver sections were subjected to immunohistochemistry using markers for macrophages (CD68, HAM56, MAC387) or T cells (CD3 and CD45RO). Results: Interferon-gamma mRNA was increased in both haemochromatosis (0.29+/-0.08%, P=0.01) and hepatitis C patients (1.02+/-0.32%, P=0.03) compared to controls (0.04+/-0.01%). Interleukin-10 mRNA was significantly decreased in both haemochromatosis and hepatitis C patients (0.01+/-0.003%, P=0.008 and 0.03+/-0.015%, P=0.02, respectively) compared to controls (0.12+/-0.01%). CD3 positive T-cell number was significantly correlated with increasing hepatic iron concentration (r=0.56, P=0.03). Conclusions: This study has demonstrated a distinct pattern of cytokine gene expression in haemochromatosis, which resembles that of inflammatory conditions such as chronic hepatitis C. These factors may play a role in the development of iron-induced hepatic fibrosis in haemochromatosis. (C) 2003 European Association for the Study of the Liver. Published by Elsevier Science B.V. All rights reserved.

Knowledge-based system on optimum design of liquid retaining structures with genetic algorithms

This paper delineates the development of a prototype hybrid knowledge-based system for the optimum design of liquid retaining structures by coupling the blackboard architecture, an expert system shell VISUAL RULE STUDIO and genetic algorithm (GA). Through custom-built interactive graphical user interfaces under a user-friendly environment, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking, and member sizing optimization. For structural optimization, GA is applied to the minimum cost design of structural systems with discrete reinforced concrete sections. The design of a typical example of the liquid retaining structure is illustrated. The results demonstrate extraordinarily converging speed as near-optimal solutions are acquired after merely exploration of a small portion of the search space. This system can act as a consultant to assist novice designers in the design of liquid retaining structures.

A coupled knowledge-based expert system for design of liquid-retaining structures

This paper describes a coupled knowledge-based system (KBS) for the design of liquid-retaining structures, which can handle both the symbolic knowledge processing based on engineering heuristics in the preliminary synthesis stage and the extensive numerical crunching involved in the detailed analysis stage. The prototype system is developed by employing blackboard architecture and a commercial shell VISUAL RULE STUDIO. Its present scope covers design of three types of liquid-retaining structures, namely, a rectangular shape with one compartment, a rectangular shape with two compartments and a circular shape. Through custom-built interactive graphical user interfaces, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking and member sizing optimization. It is also integrated with various relational databases that provide the system with sectional properties, moment and shear coefficients and final member details. This system can act as a consultant to assist novice designers in the design of liquid-retaining structures with increase in efficiency and optimization of design output and automated record keeping. The design of a typical example of the liquid-retaining structure is also illustrated. (C) 2003 Elsevier B.V All rights reserved.

A genetic algorithm/method of moments approach to the optimization of an RF coil for MRI applications - Theoretical considerations - Abstract

A Combined Genetic Algorithm and Method of Moments design methods is presented for the design of unusual near-field antennas for use in Magnetic Resonance Imaging systems. The method is successfully applied to the design of an asymmetric coil structure for use at 190MHz and demonstrates excellent radiofrequency field homogeneity.

Nitrification of high strength ammonia wastewtaer treatment - process selection is the major factor.

Biological nitrogen removal via the nitrite pathway in wastewater treatment is very important in Saving the cost of aeration and as an electron donor for denitrification. Wastewater nitrification and nitrite accumulation were carried out in a biofilm airlift reactor with autotrophic nitrifying biofilm. The biofilm reactor showed almost complete nitrification and most of the oxidized ammonium was present as nitrite at the ammonium load of 1.5 to 3.5 kg N/m3.d. Nitrite accumulation was stably achieved by the selective inhibition of nitrite oxidizers with free ammonia and dissolved oxygen limitation. Stable 100% conversion to nitrite could also be achieved even under the absence of free ammonia inhibition on nitrite oxidizers. Batch ammonium oxidation and nitrite oxidation with nitrite accumulating nitrifying biofilm showed that nitrite Oxidation was completely inhibited when free ammonia is higher than 0.2 mg N/L. However, nitrite oxidation activity was recovered as soon as the free ammonia concentration was below the threshold level when dissolved oxygen concentration was not the limiting factor. Fluorescence in situ hybridization analysis of cryosectioned nitrite accumulating nitrifying biofilm showed that the β-subclass of Proteobacteria, where ammonia oxidizers belong, was distributed outside the biofilm whereas the α-subclass of Proteobacteria, where nitrite oxidizers belong, was found mainly in the inner part of the biofilm. It is likely that dissolved oxygen deficiency or limitation in the inner part of the nitrifying biofilm, where nitrite oxidizers exist, is responsible for the complete shut down of the nitrite oxidizers activity under the absence of free ammonia inhibition.

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant, Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.

Methodologies for calibration and predictive analysis of a watershed model

The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.