Composite load model decomposition : induction motor contribution

In this thesis, a new technique has been developed for determining the composition of a collection of loads including induction motors. The application would be to provide a representation of the dynamic electrical load of Brisbane so that the ability of the power system to survive a given fault can be predicted. Most of the work on load modelling to date has been on post disturbance analysis, not on continuous on-line models for loads. The post disturbance methods are unsuitable for load modelling where the aim is to determine the control action or a safety margin for a specific disturbance. This thesis is based on on-line load models. Dr. Tania Parveen considers 10 induction motors with different power ratings, inertia and torque damping constants to validate the approach, and their composite models are developed with different percentage contributions for each motor. This thesis also shows how measurements of a composite load respond to normal power system variations and this information can be used to continuously decompose the load continuously and to characterize regarding the load into different sizes and amounts of motor loads.

Decomposition of aggregated load : finding induction motor fraction in real load

The main contribution of this paper is decomposition/separation of the compositie induction motors load from measurement at a system bus. In power system transmission buses load is represented by static and dynamic loads. The induction motor is considered as the main dynamic loads and in the practice for major transmission buses there will be many and various induction motors contributing. Particularly at an industrial bus most of the load is dynamic types. Rather than traing to extract models of many machines this paper seeks to identify three groups of induction motors to represent the dynamic loads. Three groups of induction motors used to characterize the load. These are the small groups (4kw to 11kw), the medium groups (15kw to 180kw) and the large groups (above 630kw). At first these groups with different percentage contribution of each group is composite. After that from the composite models, each motor percentage contribution is decomposed by using the least square algorithms. In power system commercial and the residential buses static loads percentage is higher than the dynamic loads percentage. To apply this theory to other types of buses such as residential and commerical it is good practice to represent the total load as a combination of composite motor loads, constant impedence loads and constant power loads. To validate the theory, the 24hrs of Sydney West data is decomposed according to the three groups of motor models.

Thermal decomposition of Bayer precipitates formed at varying temperatures

Bayer hydrotalcites prepared using the seawater neutralisation (SWN) process of Bayer liquors are characterised using X-ray diffraction and thermal analysis techniques. The Bayer hydrotalcites are synthesised at four different temperatures (0, 25, 55, 75 °C) to determine the effect on the thermal stability of the hydrotalcite structure, and to identify other precipitates that form at these temperatures. The interlayer distance increased with increasing synthesis temperature, up to 55 °C, and then decreased by 0.14 Å for Bayer hydrotalcites prepared at 75 °C. The three mineralogical phases identified in this investigation are; 1) Bayer hydrotalcite, 2), calcium carbonate species, and 3) hydromagnesite. The DTG curve can be separated into four decomposition steps; 1) the removal of adsorbed water and free interlayer water in hydrotalcite (30 – 230 °C), 2) the dehydroxylation of hydrotalcite and the decarbonation of hydrotalcite (250 – 400 °C), 3) the decarbonation of hydromagnesite (400 – 550 °C), and 4) the decarbonation of aragonite (550 – 650 °C).

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Botanical matrix

Botanical matrix is a graphic map produced via a process involving an initial site installation (350 m contour transect), a botanical survey and photographic documentation of species. The site is a housing subdivision at Point Henry, on the SE coast of Western Australia which is a landscape which is host the most botanically diverse vegetation found worldwide - known locally as 'kwongan'. Notoriously difficult vegetation to measure and map, kwongan is a visual 'engima', for paradoxically it appears to the lay person as visually bland and highly homogenous. There is thus is a critical need for the development of new forms of representation which overcome the barriers between the perception and reality of this botanical condition. Botanical Matrix is one result of the author's research which seeks to address this important problem.

The osteogenic differentiation of adipose tissue-derived precursor cells in A 3D scaffold/matrix environment

Abstract: This paper details an in-vitro study using human adipose tissue-derived precursor/stem cells (ADSCs) in three-dimensional (3D) tissue culture systems. ADSCs from 3 donors were seeded onto NaOH-treated medical grade polycaprolactone-tricalcium phosphate (mPCL-TCP) scaffolds with two different matrix components; fibrin glue and lyophilized collagen. ADSCs within these scaffolds were then induced to differentiate along the osteogenic lineage for a 28-day period and various assays and imaging techniques were performed at Day 1, 7, 14, 21 and 28 to assess and compare the ADSC’s adhesion, viability, proliferation, metabolism and differentiation along the osteogenic lineage when cultured in the different scaffold/matrix systems. The ADSC cells were proliferative in both collagen and fibrin mPCL-TCP scaffold systems with a consistently higher cell number (by comparing DNA amounts) in the induced group over the non-induced groups for both scaffold systems. In response to osteogenic induction, these ADSCs expressed elevated osteocalcin, alkaline phosphatase and osteonectin levels. Cells were able to proliferate within the pores of the scaffolds and form dense cellular networks after 28 days of culture and induction. The successful cultivation of osteogenic by FDM process manufactured ADSCs within a 3D matrix comprising fibrin glue or collagen, immobilized within a robust synthetic scaffold is a promising technique which should enhance their potential usage in the regenerative medicine arena, such as bone tissue engineering.

A hydrogen tethered inhibitor of matrix metalloproteinases

During wound repair, the balance between matrix metalloproteinases (MMPs) and their natural inhibitors (the TIMPs) is crucial for the normal extra cellular matrix turnover. However, the over expression of several MMPs including MMP-1, 2, 3, 8, 9 and MMP-10, combined with abnormally high levels of activation or low expression of TIMPs, may contribute to excessive degradation of connective tissue and formation of chronic ulcers. There are many groups exploring strategies for promoting wound healing involving delivery of growth factors, cells, ECM components and small molecules. Our approach for improving the balance of MMPs is not to add anything more to the wound, but instead to neutralise the over-expressed MMPs using inhibitors tethered to a bandage-like hydrogel. Our in vitro experiments using designed synthetic pseudo peptide inhibitors have been demonstrated to inhibit MMP activity in standard solutions. These inhibitors have also been tethered to polyethylene glycol hydrogels using a facile reaction between the linker unit on the inhibitor and the gel. After tethering the inhibition of MMPs diminishes to some extent and we postulate that this arises due to poor diffusion of the MMPs into the gels. When the tethered inhibitors were tested against chronic wound fluid obtained against patients we observed over 40% inhibition in proteolytic activity suggesting our approach may prove useful in rebalancing MMPs within chronic wounds.

A peptidomimetic inhibitor of matrix metalloproteinases containing a tetherable linker group

Successful wound repair and normal turnover of the extracellular matrix relies on a balance between matrix metalloproteinases (MMPs) and their natural inhibitors (the TIMPs). When over-expression of MMPs and abnormally high levels of activation or low expression of TIMPs are encountered, excessive degradation of connective tissue and the formation of chronic ulcers can occur. One strategy to rebalance MMPs and TIMPs is to use inhibitors. We have designed a synthetic pseudopeptide inhibitor with an amine linker group based on a known high-affinity peptidomimetic MMP inhibitor have demonstrated inhibition of MMP-1, -2, -3 and -9 activity in standard solutions. The inhibitor was also tethered to a polyethylene glycol hydrogel using a facile reaction between the linker unit on the inhibitor and the hydrogel precursors. After tethering, we observed inhibition of the MMPs although there was an increase in the IC50s which was attributed to poor diffusion of the MMPs into the hydrogels, reduced activity of the tethered inhibitor or incomplete incorporation of the inhibitor into the hydrogels. When the tethered inhibitors were tested against chronic wound fluid we observed significant inhibition in proteolytic activity suggesting our approach may prove useful in rebalancing MMPs within chronic wounds.

Does physical protection of soil organic matter attenuate temperature sensitivity?

Global climate change may induce accelerated soil organic matter (SOM) decomposition through increased soil temperature, and thus impact the C balance in soils. We hypothesized that compartmentalization of substrates and decomposers in the soil matrix would decrease SOM sensitivity to temperature. We tested our hypothesis with three short-term laboratory incubations with differing physical protection treatments conducted at different temperatures. Overall, CO2 efflux increased with temperature, but responses among physical protection treatments were not consistently different. Similar respiration quotient (Q(10)) values across physical protection treatments did not support our original hypothesis that the largest Q(10) values would be observed in the treatment with the least physical protection. Compartmentalization of substrates and decomposers is known to reduce the decomposability of otherwise labile material, but the hypothesized attenuation of temperature sensitivity was not detected, and thus the sensitivity is probably driven by the thermodynamics of biochemical reactions as expressed by Arrhenius-type equations.

Experimental warming shows that decomposition temperature sensitivity increases with soil organic matter recalcitrance

Soil C decomposition is sensitive to changes in temperature, and even small increases in temperature may prompt large releases of C from soils. But much of what we know about soil C responses to global change is based on short-term incubation data and model output that implicitly assumes soil C pools are composed of organic matter fractions with uniform temperature sensitivities. In contrast, kinetic theory based on chemical reactions suggests that older, more-resistant C fractions may be more temperature sensitive. Recent research on the subject is inconclusive, indicating that the temperature sensitivity of labile soil organic matter (OM) decomposition could either be greater than, less than, or equivalent to that of resistant soil OM. We incubated soils at constant temperature to deplete them of labile soil OM and then successively assessed the CO2-C efflux in response to warming. We found that the decomposition response to experimental warming early during soil incubation (when more labile C remained) was less than that later when labile C was depleted. These results suggest that the temperature sensitivity of resistant soil OM pools is greater than that for labile soil OM and that global change-driven soil C losses may be greater than previously estimated.