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.

Using clusters of computers for large QU-GENE simulation experiments

The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup.

Linear models of simple cells: Correspondence to real cell responses and space spanning properties

Despite their limitations, linear filter models continue to be used to simulate the receptive field properties of cortical simple cells. For theoreticians interested in large scale models of visual cortex, a family of self-similar filters represents a convenient way in which to characterise simple cells in one basic model. This paper reviews research on the suitability of such models, and goes on to advance biologically motivated reasons for adopting a particular group of models in preference to all others. In particular, the paper describes why the Gabor model, so often used in network simulations, should be dropped in favour of a Cauchy model, both on the grounds of frequency response and mutual filter orthogonality.

A DNA fingerprinting procedure for ultra high-throughput genetic analysis of insects

Existing procedures for the generation of polymorphic DNA markers are not optimal for insect studies in which the organisms are often tiny and background molecular Information is often non-existent. We have used a new high throughput DNA marker generation protocol called randomly amplified DNA fingerprints (RAF) to analyse the genetic variability In three separate strains of the stored grain pest, Rhyzopertha dominica. This protocol is quick, robust and reliable even though it requires minimal sample preparation, minute amounts of DNA and no prior molecular analysis of the organism. Arbitrarily selected oligonucleotide primers routinely produced similar to 50 scoreable polymorphic DNA markers, between individuals of three Independent field isolates of R. dominica. Multivariate cluster analysis using forty-nine arbitrarily selected polymorphisms generated from a single primer reliably separated individuals into three clades corresponding to their geographical origin. The resulting clades were quite distinct, with an average genetic difference of 37.5 +/- 6.0% between clades and of 21.0 +/- 7.1% between individuals within clades. As a prelude to future gene mapping efforts, we have also assessed the performance of RAF under conditions commonly used in gene mapping. In this analysis, fingerprints from pooled DNA samples accurately and reproducibly reflected RAF profiles obtained from Individual DNA samples that had been combined to create the bulked samples.

Long-term outcomes of genetic counseling in women at increased risk of developing hereditary breast cancer Information,

This multicenter study evaluated the impact of genetic counseling in 218 women at risk of developing hereditary breast cancer. Women were assessed prior to counseling and 12-month post-counseling using self-administered, mailed questionnaires. Compared to baseline, breast cancer genetics knowledge was increased significantly at follow-up. and greater increases in knowledge were associated with educational level. Breast cancer anxiety decreased significantly from baseline to follow-up, and these decreases were associated with improvements in perceived risk. A significant decrease in clinical breast examination was observed at the 12-month follow-up. Findings suggest that women with a family history of breast cancer benefit from attending familial cancer clinics as it leads to increases in breast cancer genetics knowledge and decreases in breast cancer anxiety. The lowered rates of clinical breast examination indicate that the content of genetic counseling may need to be reviewed to ensure that women receive and take away the right message. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.

A twin study of the etiology of prolonged fatigue and immune activation

Risk factors to prolonged fatigue syndromes (PFS) are controversial. Pre-morbid and/or current psychiatric disturbance, and/or disturbed cell-mediated immunity (CMI), have been proposed as etiologic factors. Self-report measures of fatigue and psychologic distress and three in vitro measures of CMI were collected from 124 twin pairs. Crosstwincrosstrait correlations were estimated for the complete monozygotic (MZ; 79 pairs) and dizygotic (DZ; 45 pairs) twin groups. Multivariate genetic and environmental models were fitted to explore the patterns of covariation between etiologic factors. For fatigue, the MZ correlation was more than double the DZ correlation (0.49 versus 0.16) indicating strong genetic control of familial aggregation. By contrast, for in vitro immune activation measures MZ and DZ correlations were similar (0.49–0.69 versus 0.42–0.53) indicating the etiologic role of shared environments. As small univariate associations were noted between prolonged fatigue and the in vitro immune measures (r = −0.07 to −0.12), multivariate models were fitted. Relevant etiologic factors included: a common genetic factor accounting for 48% of the variance in fatigue which also accounted for 4%, 6% and 8% reductions in immune activation; specific genetic factors for each of the in vitro immune measures; a shared environment factor influencing the three immune activation measures; and, most interestingly, unique environmental influences which increased fatigue but also increased markers of immune activation. PFS that are associated with in vitro measures of immune activation are most likely to be the consequence of current environmental rather than genetic factors. Such environmental factors could include physical agents such as infection and/or psychologic stress.