A systematic approach to error isolation in computerized wastewater simulation models

Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Specification, refinement and verification of concurrent systems - An integration of Object-Z and CSP

This paper presents a method of formally specifying, refining and verifying concurrent systems which uses the object-oriented state-based specification language Object-Z together with the process algebra CSP. Object-Z provides a convenient way of modelling complex data structures needed to define the component processes of such systems, and CSP enables the concise specification of process interactions. The basis of the integration is a semantics of Object-Z classes identical to that of CSP processes. This allows classes specified in Object-Z to he used directly within the CSP part of the specification. In addition to specification, we also discuss refinement and verification in this model. The common semantic basis enables a unified method of refinement to be used, based upon CSP refinement. To enable state-based techniques to be used fur the Object-Z components of a specification we develop state-based refinement relations which are sound and complete with respect to CSP refinement. In addition, a verification method for static and dynamic properties is presented. The method allows us to verify properties of the CSP system specification in terms of its component Object-Z classes by using the laws of the the CSP operators together with the logic for Object-Z.

Detection of lateral gene transfer among microbial genomes

An increasingly comprehensive assessment is being developed of the extent and potential significance of lateral gene transfer among microbial genomes. Genomic sequences can be identified as being of putatively lateral origin by their unexpected phyletic distribution, atypical sequence composition, differential presence or absence in closely related genomes, or incongruent phylogenetic trees. These complementary approaches sometimes yield inconsistent results. Not only more data but also quantitative models and simulations are needed urgently.

Detection and differentiation of human polyomaviruses JC and BK by LightCycler PCR

Human polyomaviruses JC and BK may cause several clinical manifestations in immunocompromised hosts, including progressive multifocal leukoencephalopathy and hemorrhagic cystitis. Molecular detection by PCR is recognized as a sensitive and specific method for detecting human polyomaviruses in clinical samples. In this study, a real-time PCR assay using the LightCycler platform was evaluated and compared to an in-house PCR assay using a conventional detection method. A total of 122 urine specimens were tested, and human polyomavirus was detected in 49 specimens (40%) by both conventional PCR and LightCycler PCR. The remaining 73 specimens (60%) were found negative by both assays. For 46 of the 49 positive specimens, LightCycler PCR and conventional PCR identified the same polyomavirus type. These samples included 30 samples with JC virus (JCV), 14 samples with BK virus (BKV), and 2 samples in which both viruses were detected. In the remaining three samples, both JCV and BKV were detected by the conventional assay, but only JCV was detected by the LightCycler assay. The results of this study show that the LightCycler PCR assay displays sensitivity and specificity similar to those of a conventional PCR assay. These data, combined with its rapid turnaround time for results and decreased hands-on time, make the LightCycler PCR assay highly suitable for the rapid detection and differentiation of JCV and BKV in the clinical laboratory.

Detection of dengue viral RNA in Aedes aegypti (Diptera : Culicidae) exposed to sticky lures using reverse-transcriptase polymerase chain reaction

Active surveillance for dengue (DEN) virus infected mosquitoes can be an effective way to predict the risk of dengue infection in a given area. However, doing so may pose logistical problems if mosquitoes must be kept alive or frozen fresh to detect DEN virus. In an attempt to simplify mosquito processing, we evaluated the usefulness of a sticky lure and a seminested reverse-transcriptase polymerase chain reaction assay (RT-PCR) for detecting DEN virus RNA under laboratory conditions using experimentally infected Aedes aegypti (L.) mosquitoes. In the first experiment, 40 male mosquitoes were inoculated with 0.13 mul of a 10(4) pfu/ml DEN-2 stock solution. After a 7-d incubation period, the mosquitoes were applied to the sticky lure and kept at room temperatures of 23-30 degreesC. Following 7,10,14, and 28 d application, 10 mosquitoes each were removed from the lure pooled and assayed for virus. DEN virus nucleic acid was clearly detectable in all pools up to 28 d after death. A second study evaluated sensitivity and specificity using one, two, and five DEN-infected mosquitoes removed after 7, 10, 14, 21 and 30 d application and tested by RT-PCR. All four DEN serotypes were individually inoculated in mosquitoes and evaluated using the same procedures as experiment 1. The four serotypes were detectable in as few as one mosquito 30 d after application to the lure with no evidence of cross-reactivity. The combination of sticky lures and RT-PCR show promise for mosquito and dengue virus surveillance and warrant further evaluation.

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.

Modern scientific methods and their potential in wastewater science and technology

Application of novel analytical and investigative methods such as fluorescence in situ hybridization, confocal laser scanning microscopy (CLSM), microelectrodes and advanced numerical simulation has led to new insights into micro-and macroscopic processes in bioreactors. However, the question is still open whether or not these new findings and the subsequent gain of knowledge are of significant practical relevance and if so, where and how. To find suitable answers it is necessary for engineers to know what can be expected by applying these modern analytical tools. Similarly, scientists could benefit significantly from an intensive dialogue with engineers in order to find out about practical problems and conditions existing in wastewater treatment systems. In this paper, an attempt is made to help bridge the gap between science and engineering in biological wastewater treatment. We provide an overview of recently developed methods in microbiology and in mathematical modeling and numerical simulation. A questionnaire is presented which may help generate a platform from which further technical and scientific developments can be accomplished. Both the paper and the questionnaire are aimed at encouraging scientists and engineers to enter into an intensive, mutually beneficial dialogue. (C) 2002 Elsevier Science Ltd. All rights reserved.

Brief note on the variation of constants formula for fuzzy differential equations

This note gives a theory of state transition matrices for linear systems of fuzzy differential equations. This is used to give a fuzzy version of the classical variation of constants formula. A simple example of a time-independent control system is used to illustrate the methods. While similar problems to the crisp case arise for time-dependent systems, in time-independent cases the calculations are elementary solutions of eigenvalue-eigenvector problems. In particular, for nonnegative or nonpositive matrices, the problems at each level set, can easily be solved in MATLAB to give the level sets of the fuzzy solution. (C) 2002 Elsevier Science B.V. All rights reserved.

Detection and description of non-linear interdependence in normal multichannel human EEG data

Objectives: This study examines human scalp electroencephalographic (EEG) data for evidence of non-linear interdependence between posterior channels. The spectral and phase properties of those epochs of EEG exhibiting non-linear interdependence are studied. Methods: Scalp EEG data was collected from 40 healthy subjects. A technique for the detection of non-linear interdependence was applied to 2.048 s segments of posterior bipolar electrode data. Amplitude-adjusted phase-randomized surrogate data was used to statistically determine which EEG epochs exhibited non-linear interdependence. Results: Statistically significant evidence of non-linear interactions were evident in 2.9% (eyes open) to 4.8% (eyes closed) of the epochs. In the eyes-open recordings, these epochs exhibited a peak in the spectral and cross-spectral density functions at about 10 Hz. Two types of EEG epochs are evident in the eyes-closed recordings; one type exhibits a peak in the spectral density and cross-spectrum at 8 Hz. The other type has increased spectral and cross-spectral power across faster frequencies. Epochs identified as exhibiting non-linear interdependence display a tendency towards phase interdependencies across and between a broad range of frequencies. Conclusions: Non-linear interdependence is detectable in a small number of multichannel EEG epochs, and makes a contribution to the alpha rhythm. Non-linear interdependence produces spatially distributed activity that exhibits phase synchronization between oscillations present at different frequencies. The possible physiological significance of these findings are discussed with reference to the dynamical properties of neural systems and the role of synchronous activity in the neocortex. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.