An algorithm for unsteady flows with strong convection

An implicit ADI numerical method for the calculation of 2-D unsteady flows with strong convection effects is described. The method is based on the conventional Crank-Nicholson approach for parabolic equations but an upwind-downwind differencing is used for the first order spatial derivatives associated with convection. The differencing is carried out in the current and previous time plane in such a way that the algorithm is second order accurate in both space and time. The difference equations are factored into sequential operators, one in each independent spatial variable; the solution at each time step may then be computed as a sequence of tridiagonal matrix problems. The method may be used in a noniterative manner although iteration at each time step is recommended in situations where the effects of convection are strong

The prediction of sea waves in transitional depth water

Thesis (M.Eng.Sc.) -- University of Adelaide, Dept. of Civil Engineering, 198

Ordering and Visualisation of Many-objective Populations

In many everyday tasks it is necessary to compare the performance of the individuals in a population described by two or more criteria, for example comparing products in order to decide which is the best to purchase in terms of price and quality. Other examples are the comparison of universities, countries, the infrastructure in a telecommunications network, and the candidate solutions to a multi- or many-objective problem. In all of these cases, visualising the individuals better allows a decision maker to interpret their relative performance. This thesis explores methods for understanding and visualising multi- and many-criterion populations. Since people cannot generally comprehend more than three spatial dimensions the visualisation of many-criterion populations is a non-trivial task. We address this by generating visualisations based on the dominance relation which defines a structure in the population and we introduce two novel visualisation methods. The first method explicitly illustrates the dominance relationships between individuals as a graph in which individuals are sorted into Pareto shells, and is enhanced using many-criterion ranking methods to produce a finer ordering of individuals. We extend the power index, a method for ranking according to a single criterion, into the many-criterion domain by defining individual quality in terms of tournaments. The second visualisation method uses a new dominance-based distance in conjunction with multi-dimensional scaling, and we show that dominance can be used to identify an intuitive low-dimensional mapping of individuals, placing similar individuals close together. We demonstrate that this method can visualise a population comprising a large number of criteria. Heatmaps are another common method for presenting high-dimensional data, however they suffer from a drawback of being difficult to interpret if dissimilar individuals are placed close to each other. We apply spectral seriation to produce an ordering of individuals and criteria by which the heatmap is arranged, placing similar individuals and criteria close together. A basic version, computing similarity with the Euclidean distance, is demonstrated, before rank-based alternatives are investigated. The procedure is extended to seriate both the parameter and objective spaces of a multi-objective population in two stages. Since this process describes a trade-off, favouring the ordering of individuals in one space or the other, we demonstrate methods that enhance the visualisation by using an evolutionary optimiser to tune the orderings. One way of revealing the structure of a population is by highlighting which individuals are extreme. To this end, we provide three definitions of the “edge” of a multi-criterion mutually non-dominating population. All three of the definitions are in terms of dominance, and we show that one of them can be extended to cope with many-criterion populations. Because they can be difficult to visualise, it is often difficult for a decision maker to comprehend a population consisting of a large number of criteria. We therefore consider criterion selection methods to reduce the dimensionality with a view to preserving the structure of the population as quantified by its rank order. We investigate the efficacy of greedy, hill-climber and evolutionary algorithms and cast the dimension reduction as a multi-objective problem

Nitric oxide production by Biomphalaria glabrata haemocytes: effects of Schistosoma mansoni ESPs and regulation through the extracellular signal-regulated kinase pathway

BACKGROUND: Schistosoma mansoni uses Biomphalaria glabrata as an intermediate host during its complex life cycle. In the snail, the parasite initially transforms from a miracidium into a mother sporocyst and during this process excretory-secretory products (ESPs) are released. Nitric oxide (NO) and its reactive intermediates play an important role in host defence responses against pathogens. This study therefore aimed to determine the effects of S. mansoni ESPs on NO production in defence cells (haemocytes) from schistosome-susceptible and schistosome-resistant B. glabrata strains. As S. mansoni ESPs have previously been shown to inhibit extracellular signal-regulated kinase (ERK) phosphorylation (activation) in haemocytes from susceptible, but not resistant, B. glabrata the regulation of NO output by ERK in these cells was also investigated. RESULTS: Haemocytes from resistant snails challenged with S. mansoni ESPs (20 mug/ml) over 5 h displayed an increase in NO production that was 3.3 times greater than that observed for unchallenged haemocytes; lower concentrations of ESPs (0.1-10 mug/ml) did not significantly increase NO output. In contrast, haemocytes from susceptible snails showed no significant change in NO output following challenge with ESPs at any concentration used (0.1-20 mug/ml). Western blotting revealed that U0126 (1 muM or 10 muM) blocked the phosphorylation (activation) status of ERK in haemocytes from both snail strains. Inhibition of ERK signalling by U0126 attenuated considerably intracellular NO production in haemocytes from both susceptible and resistant B. glabrata strains, identifying ERK as a key regulator of NO output in these cells. CONCLUSION: S. mansoni ESPs differentially influence intracellular NO levels in susceptible and resistant B. glabrata haemocytes, possibly through modulation of the ERK signalling pathway. Such effects might facilitate survival of S. mansoni in its intermediate host

Hierarchical strategies for efficient fault recovery on the reconfigurable PAnDA device

A novel hierarchical fault-tolerance methodology for reconfigurable devices is presented. A bespoke multi-reconfigurable FPGA architecture, the programmable analogue and digital array (PAnDA), is introduced allowing fine-grained reconfiguration beyond any other FPGA architecture currently in existence. Fault blind circuit repair strategies, which require no specific information of the nature or location of faults, are developed, exploiting architectural features of PAnDA. Two fault recovery techniques, stochastic and deterministic strategies, are proposed and results of each, as well as a comparison of the two, are presented. Both approaches are based on creating algorithms performing fine-grained hierarchical partial reconfiguration on faulty circuits in order to repair them. While the stochastic approach provides insights into feasibility of the method, the deterministic approach aims to generate optimal repair strategies for generic faults induced into a specific circuit. It is shown that both techniques successfully repair the benchmark circuits used after random faults are induced in random circuit locations, and the deterministic strategies are shown to operate efficiently and effectively after optimisation for a specific use case. The methods are shown to be generally applicable to any circuit on PAnDA, and to be straightforwardly customisable for any FPGA fabric providing some regularity and symmetry in its structure

Glucocorticoid programming of neuroimmune function

Work attributed to the ideas presented within this manuscript was supported by the BBSRC (Biotechnology and Biological Sciences Research Council, UK) under the EASTBIO doctoral training program [grant no. BB/J01446X/1], awarded to DJW. KAS was also part funded by a BBSRC grant [no. BB/L002264/1].Throughout life physiological systems strive to maintain homeostasis and these systems are susceptible to exposure to maternal or environmental perturbations, particularly during embryonic development. In some cases, these perturbations may influence genetic and physiological processes that permanently alter the functioning of these physiological systems; a process known as developmental programming. In recent years, the neuroimmune system has garnered attention for its fundamental interactions with key hormonal systems, such as the hypothalamic pituitary adrenal (HPA) axis. The ultimate product of this axis, the glucocorticoid hormones, play a key role in modulating immune responses within the periphery and the CNS as part of the physiological stress response. It is well-established that elevated glucocorticoids induced by developmental stress exert profound short and long-term physiological effects, yet there is relatively little information of how these effects are manifested within the neuroimmune system. Pre and post-natal periods are prime candidates for manipulation in order to uncover the physiological mechanisms that underlie glucocorticoid programming of neuroimmune responses. Understanding the potential programming role of glucocorticoids may be key in uncovering vulnerable windows of CNS susceptibility to stressful experiences during embryonic development and improve our use of glucocorticoids as therapeutics in the treatment of neurodegenerative diseases.Publisher PDFPeer reviewe

Logistic Regression Under Sparse Data Conditions

The impact of sparse data conditions was examined among one or more predictor variables in logistic regression and assessed the effectiveness of the Firth (1993) procedure in reducing potential parameter estimation bias. Results indicated sparseness in binary predictors introduces bias that is substantial with small sample sizes, and the Firth procedure can effectively correct this bias

JMASM36: Nine Pseudo R^2 Indices for Binary Logistic Regression Models (SPSS)

This syntax program is an applied complement to Veall and Zimmermann (1994), Menard (2000), and Smith and McKenna (2013) and produces nine pseudo R2 indices, not readily accessible in statistical software such as SPSS, which are used to describe the results from binary logistic regression analyses

On the Disinfectant Properties of Hypochlorites of Sodium and Magnesium as Produced by Electrolysis.

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