Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

Biological wastes as plant growth substrate amendments

Globally, agriculture is being intensified with mechanization and increased use of synthetic fertilizers and pesticides. There has been a scaling up of production to satisfy the demands of supermarket distribution. Problems associated with intensification of production, trade globalisation and a larger market demand for greater volumes of fresh produce, include consumers' concern about pesticide residues and leaching of nutrients and pesticides into the environment, as well as increases in the transmission of human food-poisoning pathogens on raw vegetables and in fruit juices. The first part of this research was concerned with the evaluation of a biological control strategy for soil-borne pathogens, these are difficult to eliminate and the chemicals of which the most effective fumigants e.g. methyl bromide, are being withdrawn form use. Chitin-containing crustaceans shellfish waste was investigated as a selective growth substrate amendment in the field, in glasshouse and in storage trials against Sclerotinia disease of Helianthus tuberosus, Phytophthora fragariae disease of Fragaria vesca and Fusarium disease of Dianthus. Results showed that addition to shellfish waste stimulated substrate microbial populations and lytic activity and induced plant defense proteins, namely chitinases and cellulases. Protective effects were seen in all crop models but the results indicate that further trials are required to confirm long-term efficacy. The second part of the research investigated the persistence of enteric bacteria in raw salad vegetables using model food poisoning isolates. In clinical investigations plants are sampled for bacterial contamination but no attempt is made to differentiate between epiphytes and endophytes. Results here indicate that the mode isolates persist endophytically thereby escaping conventional chlorine washes and they may also induce host defenses, which results in their suppression and in negative results in conventional plate count screening. Finally a discussion of criteria that should be considered for a HACCP plan for safe raw salad vegetable production is presented.

The Rpf/DSF system and the regulation of virulence in the plant pathogen Xanthomonas campestris

The full virulence of Xanthomonas campestris pv. campestris (Xcc) to plants depends upon cell-to-cell signalling mediated by the signal molecule DSF (for diffusible signal factor), that has been characterised as cis-11-methyl-2-dodecenoic acid. DSF-mediated signalling regulates motility, biofilm dynamics and the synthesis of particular virulence determinants. The synthesis and perception of the DSF signal molecule involves products of the rpf (regulation of pathogenicity factors) gene cluster. DSF synthesis is fully dependent on RpfF, which encodes a putative enoyl-CoA hydratase. A two-component system, comprising the complex sensor histidine kinase RpfC and the HD-GYP domain regulator RpfG, is implicated in DSF perception. The HD-GYP domain of RpfG is a phosphodiesterase working on cyclic di-GMP; DSF perception is thereby linked to the turnover of this intracellular second messenger. The full range of regulatory influences of the Rpf/DSF system and of cyclic di-GMP in Xcc has yet to be established. In order to further characterise the Rpf/DSF regulatory network in Xcc, a proteomic approach was used to compare protein expression in the wildtype and defined rpf mutants. This work shows that the Rpf/DSF system regulates a range of biological functions that are associated with virulence and biofilm formation but also reveals new functions mediated by DSF regulation. These functions include antibiotic resistance, detoxification and stress tolerance. Mutational analysis showed that several of these regulated protein functions contribute to virulence in Chinese radish. Interestingly, it was demonstrated that different patterns of protein expression are associated with mutations of rpfF, rpfC and rpfG. This suggests that RpfG and RpfC have broader roles in regulation other than perception and transduction of DSF. Taken together, this analysis indicates the broad and complex regulatory role of Rpf/DSF system and identifies a number of new functions under Rpf/DSF control, which were shown to play a role in virulence.