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.

Molecular genetics of schizophrenia

1. Schizophrenia is a chronic, disabling brain disease that affects approxmately 1% of the world's population. It is characterized by delusions, hallucinations and formal thought disorder, together with a decline in socio-occupational functioning. While the causes for schizophrenia remain unknown, evidence from family, twin and adoption studies clearly demonstrates that it aggregates in families, with this clustering largely attributable to genetic rather than cultural or environmental factors. Identifying the genes involved, however, has proven to be a difficult task because schizophrenia is a complex trait characterized by an imprecise phenotype, the existence of phenocopies and the presence of low disease penetrance, 2. The current working hypothesis for schizophrenia causation is that multiple genes of small to moderate effect confer compounding risk through interactions with each other and with non-genetic risk factors, The same genes may be commonly involved in conferring risk across populations or they may vary in number and strength between different populations. To search for evidence of such genetic loci, both candidate gene and genome-wide linkage studies have been used in clinical cohorts collected from a variety of populations. Collectively, these works provide some evidence for the involvement of a number of specific genes (e.g. the 5-hydroxytryptamine (5-HT) type 2a receptor (5-HT2a) gene and the dopamine D-3 receptor gene) and as yet unidentified factors localized to specific chromosomal regions, including 6p, 6q, 8p, 13q and 22q, These data provide suggestive, but no conclusive, evidence for causative genes. 3. To enable further progress there is a need to: (i) collect fine-grained clinical datasets while searching the schizophrenia phenotype for subgroups or dimensions that may provide a more direct route to causative genes; and (ii) integrate recent refinements in molecular genetic technology, including modern composite marker maps, DNA expression assays and relevant animal models, while using the latest analytical techniques to extract maximum information in order to help distinguish a true result from a false-positive finding.

Mathematical methods for spatially cohesive reserve design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Genetic sources of covariation among P3(00) and online performance variables in a delayed-response working memory task

Genetic and environmental sources of covariation among the P3(00) and online performance elicited in a delayed-response working memory task, and psychometric IQ assessed by the multidimensional aptitude battery, were examined in an adolescent twin sample. An association between frontal P3 latency and task performance (phenotypic r = -0.33; genotypic r = -0.49) was indicated, with genes (i.e. twin status) accounting for a large part of the covariation ( > 70%). In contrast, genes influencing P3 amplitude mediated only a small part (2%) of the total genetic variation in task performance. While task performance mediated 15% of the total genetic variation in IQ (phenotypic r = 0.22; genotypic r = 0.39) there was no association between P3 latency and IQ or P3 amplitude with IQ. The findings provide some insight into the inter-relationships among psychophysiological, performance and psychometric measures of cognitive ability, and provide support for a levels-of-processing genetic model of cognition where genes act on specific sub-components of cognitive processes.

Anticipation of a non-aversive reaction time task facilitates the blink startle reflex

The conditions under which blink startle facilitation can be found in anticipation of a reaction time task were investigated to resolve inconsistent findings across previous studies. Four groups of participants (n = 64) were presented with two visual stimuli, one predicting a reaction time task (S+) and the second presented alone (S-). Participants were asked to make a speeded response to the offset of the S+ (S1 paradigm) or were asked to respond to a tactile stimulus presented at the offset of the S+ (S1-S2 paradigm). Half of the participants in each paradigm condition received performance feedback. Overall, blink latency shortening and magnitude facilitation were larger during S+ than during S-. More detailed analyses, however, found these differences to be reliable only in the Feedback conditions. Ratings of S+ pleasantness did not change across the experiment. Electrodermal responses to S+ were larger than to S- in all groups with differential electrodermal responding emerging earlier in the S1 paradigm. Taken together, the data support the notion that startle facilitation can occur during non-aversive Pavlovian conditioning. (C) 2002 Elsevier Science B.V. All rights reserved.

The influence of a concurrent cognitive task on the compensatory stepping response to a perturbation in balance-impaired and healthy elders

This study investigated the influence of a concurrent cognitive task on the compensatory stepping response in balance-impaired elders and the attentional demand of the stepping response. Kinetic, kinematic and neuromuscular measures of a forward recovery step were investigated in 15 young adults, 15 healthy elders and 13 balance-impaired elders in a single task (postural recovery only) and dual task (postural recovery and vocal reaction time task) situation. Results revealed that reaction times were longer in all subjects when performed concurrently with a compensatory step, they were longer for a step than an in-place response and longer for balance-impaired older adults compared with young adults. An interesting finding was that the latter group difference may be related to prioritization between the two tasks rather than attentional demand, as the older adults completed the step before the reaction time, whereas the young adults could perform both concurrently. Few differences in step characteristics were found between tasks, with the most notable being a delayed latency and reduced magnitude of the early automatic postural response in healthy and balance-impaired elders with a concurrent task. (C) 2002 Elsevier Science B.V. All rights reserved.