A decision support process to compare Riparian revegetation options in Scheu Creek catchment in North Queensland

While riparian vegetation can play a major role in protecting land, water and natural habitat in catchments, there are high costs associated with tree planting and establishment and in diverting land from cropping. The distribution of costs and benefits of riparian revegetation creates conflicts in the objectives of various stakeholder groups. Multicriteria analysis provides an appropriate tool to evaluate alternative riparian revegetation options, and to accommodate the conflicting views of various stakeholder groups. This paper discusses an application of multicriteria analysis in an evaluation of riparian revegetation policy options for Scheu Creek, a small sub-catchment in the Johnstone River catchment in north Queensland, Australia. Clear differences are found in the rankings of revegetation options for different stakeholder groups with respect to environmental, social and economic impacts. Implementation of a revegetation option will involve considerable cost for landholders for the benefits of society. Queensland legislation does not provide a means to require farmers to implement riparian revegetation, hence the need for subsidies, tau incentives and moral suasion. (C) 2001 Academic Press.

The application of statistical process control charts to the detection and monitoring of hospital-acquired infections

The monitoring of infection control indicators including hospital-acquired infections is an established part of quality maintenance programmes in many health-care facilities. However, surveillance data use can be frustrated by the infrequent nature of many infections. Traditional methods of analysis often provide delayed identification of increasing infection occurrence, placing patients at preventable risk. The application of Shewhart, Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) statistical process control charts to the monitoring of indicator infections allows continuous real-time assessment. The Shewhart chart will detect large changes, while CUSUM and EWMA methods are more suited to recognition of small to moderate sustained change. When used together, Shewhart and EWMA methods are ideal for monitoring bacteraemia and multiresistant organism rates. Shewhart and CUSUM charts are suitable for surgical infection surveillance.

Integrating technology to improve the efficiency of qualitative data analysis - A note on methods

Qualitative data analysis (QDA) is often a time-consuming and laborious process usually involving the management of large quantities of textual data. Recently developed computer programs offer great advances in the efficiency of the processes of QDA. In this paper we report on an innovative use of a combination of extant computer software technologies to further enhance and simplify QDA. Used in appropriate circumstances, we believe that this innovation greatly enhances the speed with which theoretical and descriptive ideas can be abstracted from rich, complex, and chaotic qualitative data. © 2001 Human Sciences Press, Inc.

Identification of vaccine candidate antigens from a genomic analysis of Porphyomonas gingivalis

Porphyromonas gingivalis is a key periodontal pathogen which has been implicated in the etiology of chronic adult periodontitis. Our aim was to develop a protein based vaccine for the prevention and or treatment of this disease. We used a whole genome sequencing approach to identify potential vaccine candidates. From a genomic sequence, we selected 120 genes using a series of bioinformatics methods. The selected genes were cloned for expression in Escherichia coli and screened with P. gingivalis antisera before purification and testing in an animal model. Two of these recombinant proteins (PG32 and PG33) demonstrated significant protection in the animal model, while a number were reactive with various antisera. This process allows the rapid identification of vaccine candidates from genomic data. (C) 2001 Elsevier Science Ltd. All rights reserved.

On-line analysis of froth surface in coal and mineral flotation using JKFrothCam

The personal computer revolution has resulted in the widespread availability of low-cost image analysis hardware. At the same time, new graphic file formats have made it possible to handle and display images at resolutions beyond the capability of the human eye. Consequently, there has been a significant research effort in recent years aimed at making use of these hardware and software technologies for flotation plant monitoring. Computer-based vision technology is now moving out of the research laboratory and into the plant to become a useful means of monitoring and controlling flotation performance at the cell level. This paper discusses the metallurgical parameters that influence surface froth appearance and examines the progress that has been made in image analysis of flotation froths. The texture spectrum and pixel tracing techniques developed at the Julius Kruttschnitt Mineral Research Centre are described in detail. The commercial implementation, JKFrothCam, is one of a number of froth image analysis systems now reaching maturity. In plants where it is installed, JKFrothCam has shown a number of performance benefits. Flotation runs more consistently, meeting product specifications while maintaining high recoveries. The system has also shown secondary benefits in that reagent costs have been significantly reduced as a result of improved flotation control. (C) 2002 Elsevier Science B.V. All rights reserved.

Development of a novel titration and off-gas analysis (TOGA) sensor for study of biological processes in wastewater treatment systems

The development of the new TOGA (titration and off-gas analysis) sensor for the detailed study of biological processes in wastewater treatment systems is outlined. The main innovation of the sensor is the amalgamation of titrimetric and off-gas measurement techniques. The resulting measured signals are: hydrogen ion production rate (HPR), oxygen transfer rate (OTR), nitrogen transfer rate (NTR), and carbon dioxide transfer rate (CTR). While OTR and NTR are applicable to aerobic and anoxic conditions, respectively, HPR and CTR are useful signals under all of the conditions found in biological wastewater treatment systems, namely, aerobic, anoxic and anaerobic. The sensor is therefore a powerful tool for studying the key biological processes under all these conditions. A major benefit from the integration of the titrimetric and off-gas analysis methods is that the acid/base buffering systems, in particular the bicarbonate system, are properly accounted for. Experimental data resulting from the TOGA sensor in aerobic, anoxic, and anaerobic conditions demonstrates the strength of the new sensor. In the aerobic environment, carbon oxidation (using acetate as an example carbon source) and nitrification are studied. Both the carbon and ammonia removal rates measured by the sensor compare very well with those obtained from off-line chemical analysis. Further, the aerobic acetate removal process is examined at a fundamental level using the metabolic pathway and stoichiometry established in the literature, whereby the rate of formation of storage products is identified. Under anoxic conditions, the denitrification process is monitored and, again, the measured rate of nitrogen gas transfer (NTR) matches well with the removal of the oxidised nitrogen compounds (measured chemically). In the anaerobic environment, the enhanced biological phosphorus process was investigated. In this case, the measured sensor signals (HPR and CTR) resulting from acetate uptake were used to determine the ratio of the rates of carbon dioxide production by competing groups of microorganisms, which consequently is a measure of the activity of these organisms. The sensor involves the use of expensive equipment such as a mass spectrometer and requires special gases to operate, thus incurring significant capital and operational costs. This makes the sensor more an advanced laboratory tool than an on-line sensor. (C) 2003 Wiley Periodicals, Inc.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

High-speed MAS F-19 NMR analysis of an irradiated fluoropolymer

The effect of gamma-radiation on a perfluoroalkoxy (PFA) resin was examined using solid-state high-speed magic angle spinning (MAS) F-19 NMR spectroscopy. Samples were prepared for analysis by subjecting them to gamma-radiation in the dose range 0.5-3 MGy at either 303, 473, or 573 K. New structures identified include new saturated chain ends, short and long branches, and unsaturated groups. The formation of branched structures was found to increase with increasing irradiation temperature; however, at all temperatures the radiation chemical yield (G value) of new chain ends was greater than the G value of long branch points, suggesting that chain scission is the net process.

Work domain analysis and sensors II: Pasteurizer II case study

In this paper we use sensor-annotated abstraction hierarchies (Reising & Sanderson, 1996, 2002a,b) to show that unless appropriately instrumented, configural displays designed according to the principles of ecological interface design (EID) might be vulnerable to misinterpretation when sensors become unreliable or are unavailable. Building on foundations established in Reising and Sanderson (2002a) we use a pasteurization process control example to show how sensor-annotated AHs help the analyst determine the impact of different instrumentation engineering policies on a configural display that is part of an ecological interface. Our analyses suggest that configural displays showing higher-order properties of a system are especially vulnerable under some conservative instrumentation configurations. However, sensor-annotated AHs can be used to indicate where corrective instrumentation might be placed. We argue that if EID is to be effectively employed in the design of displays for complex systems, then the information needs of the human operator need to be considered while instrumentation requirements are being formulated. Rasmussen's abstraction hierarchy-and particularly its extension to the analysis of information captured by sensors and derived from sensors-may therefore be a useful adjunct to up-stream instrumentation design. (C) 2002 Elsevier Science Ltd. All rights reserved.

Phenotypic and genotypic analysis of Helicoverpa armigera nucleopolyhedrovirus serially passaged in cell culture

Rapid accumulation of few polyhedra (FP) mutants was detected during serial passaging of Helicoverpa armigera nucleopolyhedrovirus (HaSNPV) in cell culture. 100% FP infected cells were observed by passage 6. The specific yield decreased from 178 polyhedra per cell at passage 2 to two polyhedra per cell at passage 6. The polyhedra at passage 6 were not biologically active, with a 28-fold reduction in potency compared to passage 3. Electron microscopy studies revealed that very few polyhedra were produced in an FP infected cell (< 10 polyhedra per section) and in most cases these polyhedra contained no virions. A specific failure in the intranuclear nucleocapsid envelopment process in the FP infected cells, leading to the accumulation of naked nucleocapsids, was observed. Genomic restriction endonuclease digestion profiles of budded virus DNA from all passages did not indicate any large DNA insertions or deletions that are often associated with such FP phenotypes for the extensively studied Autographa californica nucleopolyhedrovirus and Gaileria mellonella nucleopolyhedrovirus. Within an HaSNPV 25K FP gene homologue, a single base-pair insertion (an adenine residue) within a region of repetitive sequences (seven adenine residues) was identified in one plaque-purified HaSNPV FP mutant. Furthermore, the sequences obtained from individual clones of the 25KFP gene PCR products of a late passage revealed point mutations or single base-pair insertions occurring throughout the gene. The mechanism of FP mutation in HaSNPV is likely similar to that seen for Lymantria dispar nucleopolyhedrovirus, involving point mutations or small insertions/deletions of the 25K FP gene.

Online titrimetric and off-gas analysis for examining nitrification processes in wastewater treatment

The two steps of nitrification, namely the oxidation of ammonia to nitrite and nitrite to nitrate, often need to be considered separately in process studies. For a detailed examination, it is desirable to monitor the two-step sequence using online measurements. In this paper, the use of online titrimetric and off-gas analysis (TOGA) methods for the examination of the process is presented. Using the known reaction stoichiometry, combination of the measured signals (rates of hydrogen ion production, oxygen uptake and carbon dioxide transfer) allows the determination of the three key process rates, namely the ammonia consumption rate, the nitrite accumulation rate and the nitrate production rate. Individual reaction rates determined with the TOGA sensor under a number of operation conditions are presented. The rates calculated directly from the measured signals are compared with those obtained from offline liquid sample analysis. Statistical analysis confirms that the results from the two approaches match well. This result could not have been guaranteed using alternative online methods. As a case study, the influences of pH and dissolved oxygen (DO) on nitrite accumulation are tested using the proposed method. It is shown that nitrite accumulation decreased with increasing DO and pH. Possible reasons for these observations are discussed. (C) 2003 Elsevier Science Ltd. All rights reserved.

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.

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.

Estimating Local Part Thickness in Midplane Meshes for Finite Element Analysis

Within the development of motor vehicles, crash safety (e.g. occupant protection, pedestrian protection, low speed damageability), is one of the most important attributes. In order to be able to fulfill the increased requirements in the framework of shorter cycle times and rising pressure to reduce costs, car manufacturers keep intensifying the use of virtual development tools such as those in the domain of Computer Aided Engineering (CAE). For crash simulations, the explicit finite element method (FEM) is applied. The accuracy of the simulation process is highly dependent on the accuracy of the simulation model, including the midplane mesh. One of the roughest approximations typically made is the actual part thickness which, in reality, can vary locally. However, almost always a constant thickness value is defined throughout the entire part due to complexity reasons. On the other hand, for precise fracture analysis within FEM, the correct thickness consideration is one key enabler. Thus, availability of per element thickness information, which does not exist explicitly in the FEM model, can significantly contribute to an improved crash simulation quality, especially regarding fracture prediction. Even though the thickness is not explicitly available from the FEM model, it can be inferred from the original CAD geometric model through geometric calculations. This paper proposes and compares two thickness estimation algorithms based on ray tracing and nearest neighbour 3D range searches. A systematic quantitative analysis of the accuracy of both algorithms is presented, as well as a thorough identification of particular geometric arrangements under which their accuracy can be compared. These results enable the identification of each technique’s weaknesses and hint towards a new, integrated, approach to the problem that linearly combines the estimates produced by each algorithm.