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.

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.

An automated multi-unit composting facility for biodegradability evaluations

A system has been developed for studying the biodegradation of natural and synthetic polymeric material. The system is based on standard methods developed by the European Committee for Standardisation (CEN TC 261) (ISO/DIS 14855) and the American Society of Testing Materials, 'ASTM. Standard Test Method for Determining Aerobic. Biodegradation of Plastic Materials under Controlled Composting Conditions' (ASTM D 5338-92). A new low-cost compost facility has been used which satisfies the requirements of these standards. The system has been automated for data collection and has been run under the conditions specified by the standards. In the system, cellulose, newspaper and two starch-based polymers were treated with compost in a series of 3dm(3) vessels at 52 degreesC and under conditions of optimum moisture and pH. The degradation was followed over time by measuring the amount of carbon released as carbon dioxide. (C) 2001 Society of Chemical Industry.

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.