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.

Global surface net-radiation at 5 km from MODIS Terra

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott’s index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W∙m−2 in boreal to 72.0 ± 4.1 W∙m−2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° × 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth’s Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10 W•m−2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth’s surface.

The role of presenilin 1 and presenilin 2 in IL-1β-, LPS- and TNFα- mediated signalling events

The importance of γ-secretase protease activities in development, neurogenesis and the immune system are highlighted by the diversity of its substrates and phenotypic characterization of Presenilin (PS)-deficient transgenic animals. Since the discovery of Amyloid precursor protein (APP) and it’s cleavage by γ-secretase complexes, over 90 other type I membrane proteins have been identified as γ-secretase substrates. We have identified interleukin-1 (IL-1) receptor type I (IL-1R1), toll-like receptor 4 (TLR4) and tumour necrosis factor-α (TNFα) receptor-1 (TNFR1) as novel substrates for - secretase cleavage, which play an important role in innate immunity. In this study, using PS-deficient cells and PS-knockout animal models we examined the role of PS proteins, PS1 and PS2, in IL-1R1-, TLR4- and TNFR1- mediated inflammatory responses. Data presented show that in response to IL- 1β, lipopolysaccharide (LPS) or TNFα, immortalised fibroblasts from PS2- deficient animals have diminished production of specific cytokines and chemokine, with differential reduction in nuclear factor-κB (NF-κB) and (mitogen activated protein kinase) MAPK activities. In contrast, no defect in the response to IL-1β, LPS or TNFα was observed in PS1-deficient immortalised fibroblasts. These observations were confirmed using bone marrow-derived macrophages from PS2-null mice, which also display impaired responsiveness to IL-1β- and LPS, with decreased production of inflammatory cytokines. Furthermore, in whole animal in vivo responses, we show that PS2-deficient animals display ligand (IL-1β, LPS and TNFα)-dependent alterations in the production of specific pro-inflammatory cytokines or chemokines. Importantly, this reduced responsiveness to IL-1β, LPS or TNFα is independent of γ- secretase protease activity and γ-secretase cleavage of TNFR1, IL-1R1 or TLR4. These observations suggest a novel γ-secretase-independent role of PS2 in the regulation of innate immune responsiveness and challenge current concepts regarding the regulation of IL-1β-, LPS- and TNFα-mediated immune signalling.