Modeling corneal surfaces with three-dimensional basis functions

Purpose: To ascertain the effectiveness of object-centered three-dimensional representations for the modeling of corneal surfaces. Methods: Three-dimensional (3D) surface decomposition into series of basis functions including: (i) spherical harmonics, (ii) hemispherical harmonics, and (iii) 3D Zernike polynomials were considered and compared to the traditional viewer-centered representation of two-dimensional (2D) Zernike polynomial expansion for a range of retrospective videokeratoscopic height data from three clinical groups. The data were collected using the Medmont E300 videokeratoscope. The groups included 10 normal corneas with corneal astigmatism less than −0.75 D, 10 astigmatic corneas with corneal astigmatism between −1.07 D and 3.34 D (Mean = −1.83 D, SD = ±0.75 D), and 10 keratoconic corneas. Only data from the right eyes of the subjects were considered. Results: All object-centered decompositions led to significantly better fits to corneal surfaces (in terms of the RMS error values) than the corresponding 2D Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters (2, 4, 6, and 8 mm), and model orders (4th to 10th radial orders) The best results (smallest RMS fit error) were obtained with spherical harmonics decomposition which lead to about 22% reduction in the RMS fit error, as compared to the traditional 2D Zernike polynomials. Hemispherical harmonics and the 3D Zernike polynomials reduced the RMS fit error by about 15% and 12%, respectively. Larger reduction in RMS fit error was achieved for smaller corneral diameters and lower order fits. Conclusions: Object-centered 3D decompositions provide viable alternatives to traditional viewer-centered 2D Zernike polynomial expansion of a corneal surface. They achieve better fits to videokeratoscopic height data and could be particularly suited to the analysis of multiple corneal measurements, where there can be slight variations in the position of the cornea from one map acquisition to the next.

Fold back current control and admittance protection scheme for a distribution network containing distributed generators

Islanded operation, protection, reclosing and arc extinguishing are some of the challenging issues related to the connection of converter interfaced distributed generators (DGs) into a distribution network. The isolation of upstream faults in grid connected mode and fault detection in islanded mode using overcurrent devices are difficult. In the event of an arc fault, all DGs must be disconnected in order to extinguish the arc. Otherwise, they will continue to feed the fault, thus sustaining the arc. However, the system reliability can be increased by maximising the DG connectivity to the system: therefore, the system protection scheme must ensure that only the faulted segment is removed from the feeder. This is true even in the case of a radial feeder as the DG can be connected at various points along the feeder. In this paper, a new relay scheme is proposed which, along with a novel current control strategy for converter interfaced DGs, can isolate permanent and temporary arc faults. The proposed protection and control scheme can even coordinate with reclosers. The results are validated through PSCAD/EMTDC simulation and MATLAB calculations.

Using complex network metrics to predict the persistence of metapopulations with asymmetric connectivity patterns

Almost all metapopulation modelling assumes that connectivity between patches is only a function of distance, and is therefore symmetric. However, connectivity will not depend only on the distance between the patches, as some paths are easy to traverse, while others are difficult. When colonising organisms interact with the heterogeneous landscape between patches, connectivity patterns will invariably be asymmetric. There have been few attempts to theoretically assess the effects of asymmetric connectivity patterns on the dynamics of metapopulations. In this paper, we use the framework of complex networks to investigate whether metapopulation dynamics can be determined by directly analysing the asymmetric connectivity patterns that link the patches. Our analyses focus on “patch occupancy” metapopulation models, which only consider whether a patch is occupied or not. We propose three easily calculated network metrics: the “asymmetry” and “average path strength” of the connectivity pattern, and the “centrality” of each patch. Together, these metrics can be used to predict the length of time a metapopulation is expected to persist, and the relative contribution of each patch to a metapopulation’s viability. Our results clearly demonstrate the negative effect that asymmetry has on metapopulation persistence. Complex network analyses represent a useful new tool for understanding the dynamics of species existing in fragmented landscapes, particularly those existing in large metapopulations.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

The future of the internet economy : addressing challenges facing the implementation of the Australian national broadband network

Innovation is vital for the future of Australia.s internet economy. Innovations rely on businesses. ability to innovate. Businesses. ability to innovate relies on their employees. The more these individual end users engage in the internet economy, the better businesses. engagement will be. The less these individual end users engage, the less likely a business is to engage and innovate. This means, for the internet economy to function at its fullest potential, it is essential that individual Australians have the capacity to engage with it and participate in it. The Australian federal government is working to facilitate the internet economy through policies, legislation and practices that implement high-speed broadband. The National Broadband Network will be a vital tool for Australia.s internet economy. Its .chief importance¡® is that it will provide faster internet access speeds that will facilitate access to internet services and content. However, an appropriate infrastructure and internet speed is only part of the picture. As the Organisation for Economic Co-operation and Development identified, appropriate government policies are also needed to ensure that vital services are more accessible by consumers. The thesis identifies essential theories and principles underpinning the internet economy and from which the concept of connectedness is developed. Connectedness is defined as the ability of end users to connect with internet content and services, other individuals and organisations, and government. That is, their ability to operate in the internet economy. The NBN will be vital in ensuring connectedness into the future. What is not currently addressed by existing access regimes is how to facilitate end user access capacity and participation. The thesis concludes by making recommendations to the federal government as to what the governing principles of the Australian internet economy should include in order to enable individual end user access capacity.

Using strategic movement to calibrate a neural compass : a spiking network for tracking head direction in rats and robots

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that ‘grounding’ of modeled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

Rational design of serine protease inhibitors

Proteases regulate a spectrum of diverse physiological processes, and dysregulation of proteolytic activity drives a plethora of pathological conditions. Understanding protease function is essential to appreciating many aspects of normal physiology and progression of disease. Consequently, development of potent and specific inhibitors of proteolytic enzymes is vital to provide tools for the dissection of protease function in biological systems and for the treatment of diseases linked to aberrant proteolytic activity. The studies in this thesis describe the rational design of potent inhibitors of three proteases that are implicated in disease development. Additionally, key features of the interaction of proteases and their cognate inhibitors or substrates are analysed and a series of rational inhibitor design principles are expounded and tested. Rational design of protease inhibitors relies on a comprehensive understanding of protease structure and biochemistry. Analysis of known protease cleavage sites in proteins and peptides is a commonly used source of such information. However, model peptide substrate and protein sequences have widely differing levels of backbone constraint and hence can adopt highly divergent structures when binding to a protease’s active site. This may result in identical sequences in peptides and proteins having different conformations and diverse spatial distribution of amino acid functionalities. Regardless of this, protein and peptide cleavage sites are often regarded as being equivalent. One of the key findings in the following studies is a definitive demonstration of the lack of equivalence between these two classes of substrate and invalidation of the common practice of using the sequences of model peptide substrates to predict cleavage of proteins in vivo. Another important feature for protease substrate recognition is subsite cooperativity. This type of cooperativity is commonly referred to as protease or substrate binding subsite cooperativity and is distinct from allosteric cooperativity, where binding of a molecule distant from the protease active site affects the binding affinity of a substrate. Subsite cooperativity may be intramolecular where neighbouring residues in substrates are interacting, affecting the scissile bond’s susceptibility to protease cleavage. Subsite cooperativity can also be intermolecular where a particular residue’s contribution to binding affinity changes depending on the identity of neighbouring amino acids. Although numerous studies have identified subsite cooperativity effects, these findings are frequently ignored in investigations probing subsite selectivity by screening against diverse combinatorial libraries of peptides (positional scanning synthetic combinatorial library; PS-SCL). This strategy for determining cleavage specificity relies on the averaged rates of hydrolysis for an uncharacterised ensemble of peptide sequences, as opposed to the defined rate of hydrolysis of a known specific substrate. Further, since PS-SCL screens probe the preference of the various protease subsites independently, this method is inherently unable to detect subsite cooperativity. However, mean hydrolysis rates from PS-SCL screens are often interpreted as being comparable to those produced by single peptide cleavages. Before this study no large systematic evaluation had been made to determine the level of correlation between protease selectivity as predicted by screening against a library of combinatorial peptides and cleavage of individual peptides. This subject is specifically explored in the studies described here. In order to establish whether PS-SCL screens could accurately determine the substrate preferences of proteases, a systematic comparison of data from PS-SCLs with libraries containing individually synthesised peptides (sparse matrix library; SML) was carried out. These SML libraries were designed to include all possible sequence combinations of the residues that were suggested to be preferred by a protease using the PS-SCL method. SML screening against the three serine proteases kallikrein 4 (KLK4), kallikrein 14 (KLK14) and plasmin revealed highly preferred peptide substrates that could not have been deduced by PS-SCL screening alone. Comparing protease subsite preference profiles from screens of the two types of peptide libraries showed that the most preferred substrates were not detected by PS SCL screening as a consequence of intermolecular cooperativity being negated by the very nature of PS SCL screening. Sequences that are highly favoured as result of intermolecular cooperativity achieve optimal protease subsite occupancy, and thereby interact with very specific determinants of the protease. Identifying these substrate sequences is important since they may be used to produce potent and selective inhibitors of protolytic enzymes. This study found that highly favoured substrate sequences that relied on intermolecular cooperativity allowed for the production of potent inhibitors of KLK4, KLK14 and plasmin. Peptide aldehydes based on preferred plasmin sequences produced high affinity transition state analogue inhibitors for this protease. The most potent of these maintained specificity over plasma kallikrein (known to have a very similar substrate preference to plasmin). Furthermore, the efficiency of this inhibitor in blocking fibrinolysis in vitro was comparable to aprotinin, which previously saw clinical use to reduce perioperative bleeding. One substrate sequence particularly favoured by KLK4 was substituted into the 14 amino acid, circular sunflower trypsin inhibitor (SFTI). This resulted in a highly potent and selective inhibitor (SFTI-FCQR) which attenuated protease activated receptor signalling by KLK4 in vitro. Moreover, SFTI-FCQR and paclitaxel synergistically reduced growth of ovarian cancer cells in vitro, making this inhibitor a lead compound for further therapeutic development. Similar incorporation of a preferred KLK14 amino acid sequence into the SFTI scaffold produced a potent inhibitor for this protease. However, the conformationally constrained SFTI backbone enforced a different intramolecular cooperativity, which masked a KLK14 specific determinant. As a consequence, the level of selectivity achievable was lower than that found for the KLK4 inhibitor. Standard mechanism inhibitors such as SFTI rely on a stable acyl-enzyme intermediate for high affinity binding. This is achieved by a conformationally constrained canonical binding loop that allows for reformation of the scissile peptide bond after cleavage. Amino acid substitutions within the inhibitor to target a particular protease may compromise structural determinants that support the rigidity of the binding loop and thereby prevent the engineered inhibitor reaching its full potential. An in silico analysis was carried out to examine the potential for further improvements to the potency and selectivity of the SFTI-based KLK4 and KLK14 inhibitors. Molecular dynamics simulations suggested that the substitutions within SFTI required to target KLK4 and KLK14 had compromised the intramolecular hydrogen bond network of the inhibitor and caused a concomitant loss of binding loop stability. Furthermore in silico amino acid substitution revealed a consistent correlation between a higher frequency of formation and the number of internal hydrogen bonds of SFTI-variants and lower inhibition constants. These predictions allowed for the production of second generation inhibitors with enhanced binding affinity toward both targets and highlight the importance of considering intramolecular cooperativity effects when engineering proteins or circular peptides to target proteases. The findings from this study show that although PS-SCLs are a useful tool for high throughput screening of approximate protease preference, later refinement by SML screening is needed to reveal optimal subsite occupancy due to cooperativity in substrate recognition. This investigation has also demonstrated the importance of maintaining structural determinants of backbone constraint and conformation when engineering standard mechanism inhibitors for new targets. Combined these results show that backbone conformation and amino acid cooperativity have more prominent roles than previously appreciated in determining substrate/inhibitor specificity and binding affinity. The three key inhibitors designed during this investigation are now being developed as lead compounds for cancer chemotherapy, control of fibrinolysis and cosmeceutical applications. These compounds form the basis of a portfolio of intellectual property which will be further developed in the coming years.

Optimal distribution network reinforcement considering load growth, line loss, and reliability

In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of dispatchable distributed generators (DDG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DDG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called modified discrete particle swarm optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DDGs are included in the optimization.

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

From simulation to emulation : an integrated approach for network security evaluation

We present a virtual test bed for network security evaluation in mid-scale telecommunication networks. Migration from simulation scenarios towards the test bed is supported and enables researchers to evaluate experiments in a more realistic environment. We provide a comprehensive interface to manage, run and evaluate experiments. On basis of a concrete example we show how the proposed test bed can be utilized.

Assessment of neuroretinal function in a group of functional amblyopes with documented LGN deficits

Purpose In this study we examine neuroretinal function in five amblyopes, who had been shown in previous functional MRI (fMRI) studies to have compromised function of the lateral geniculate nucleus (LGN), to determine if the fMRI deficit in amblyopia may have its origin at the retinal level. Methods We used slow flash multifocal ERG (mfERG) and compared averaged five ring responses of the amblyopic and fellow eyes across a 35 deg field. Central responses were also assessed over a field which was about 6.3 deg in diameter. We measured central retinal thickness using optical coherence tomography. Central fields were measured using the MP1-Microperimeter which also assesses ocular fixation during perimetry. MfERG data were compared with fMRI results from a previous study. Results Amblyopic eyes had reduced response density amplitudes (first major negative to first positive (N1-P1) responses) for the central and paracentral retina (up to 18 deg diameter) but not for the mid-periphery (from 18 to 35 deg). Retinal thickness was within normal limits for all eyes, and not different between amblyopic and fellow eyes. Fixation was maintained within the central 4° more than 80% of the time by four of the five participants; fixation assessed using bivariate contour ellipse areas (BCEA) gave rankings similar to those of the MP-1 system. There was no significant relationship between BCEA and mfERG response for either amblyopic or fellow eye. There was no significant relationship between the central mfERG eye response difference and the selective blood oxygen level dependent (BOLD) LGN eye response difference previously seen in these participants. Conclusions Retinal responses in amblyopes can be reduced within the central field without an obvious anatomical basis. Additionally, this retinal deficit may not be the reason why the LGN BOLD (blood oxygen level dependent) responses are reduced for amblyopic eye stimulation.

The function and mechanisms of action of ghrelin and obestatin in ovarian cancer

In this study, we have demonstrated that the preproghrelin derived hormones, ghrelin and obestatin, may play a role in ovarian cancer. Ghrelin and obestatin stimulated an increase in cell migration in ovarian cancer cell lines and may play a role in cancer progression. Ovarian cancer is the leading cause of death among gynaecological cancers and is the sixth most common cause of cancer-related deaths in women in developed countries. As ovarian cancer is difficult to diagnose at a low tumour grade, two thirds of ovarian cancers are not diagnosed until the late stages of cancer development resulting in a poor prognosis for the patient. As a result, current treatment methods are limited and not ideal. There is an urgent need for improved diagnostic markers, as well better therapeutic approaches and adjunctive therapies for this disease. Ghrelin has a number of important physiological effects, including roles in appetite regulation and the stimulation of growth hormone release. It is also involved in regulating the immune, cardiovascular and reproductive systems and regulates sleep, memory and anxiety, and energy metabolism. Over the last decade, the ghrelin axis, (which includes the hormones ghrelin and obestatin and their receptors), has been implicated in the pathogenesis of many human diseases and it may t may also play an important role in the development of cancer. Ghrelin is a 28 amino acid peptide hormone that exists in two forms. Acyl ghrelin (usually referred to as ghrelin), has a unique n-octanoic acid post-translational modification (which is catalysed by ghrelin O-acyltransferase, GOAT), and desacyl ghrelin, which is a non-octanoylated form. Octanoylated ghrelin acts through the growth hormone secretagogue receptor type 1a (GHSR1a). GHSR1b, an alternatively spliced isoform of GHSR, is C-terminally truncated and does not bind ghrelin. Ghrelin has been implicated in the pathophysiology of a number of diseases Obestatin is a 23 amino acid, C-terminally amidated peptide which is derived from preproghrelin. Although GPR39 was originally thought to be the obestatin receptor this has been disproven, and its receptor remains unknown. Obestatin may have as diverse range of roles as ghrelin. Obestatin improves memory, inhibits thirst and anxiety, increases pancreatic juice secretion and has cardioprotective effects. Obestatin also has been shown to regulate cell proliferation, differentiation and apoptosis in some cell types. Prior to this study, little was known regarding the functions and mechanisms of action ghrelin and obestatin in ovarian cancer. In this study it was demonstrated that the full length ghrelin, GHSR1b and GOAT mRNA transcripts were expressed in all of the ovarian-derived cell lines examined (SKOV3, OV-MZ-6 and hOSE 17.1), however, these cell lines did not express GHSR1a. Ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for ghrelin, obestatin, and GOAT, but not GHSR1a, or GHSR1b. No correlations between cancer grade and the level of expression of these transcripts were observed. This study demonstrated for the first time that both ghrelin and obestatin increase cell migration in ovarian cancer cell lines. Treatment with ghrelin (for 72 hours) significantly increased cell migration in the SKOV3 and OV-MZ-6 ovarian cancer cell lines. Ghrelin (100 nM) stimulated cell migration in the SKOV3 (2.64 +/- 1.08 fold, p <0.05) and OV-MZ-6 (1.65 +/- 0.31 fold, p <0.05) ovarian cancer cell lines, but not in the representative normal cell line hOSE 17.1. This increase in migration was not accompanied by an increase in cell invasion through Matrigel. In contrast to other cancer types, ghrelin had no effect on proliferation. Ghrelin treatment (10nM) significantly decreased attachment of the SKOV3 ovarian cancer cell line to collagen IV (24.7 +/- 10.0 %, p <0.05), however, there were no changes in attachment to the other extracellular matrix molecules (ECM) tested (fibronectin, vitronectin and collagen I), and there were no changes in attachment to any of the ECM molecules in the OV-MZ-6 or hOSE 17.1 cell lines. It is, therefore, unclear if ghrelin plays a role in cell attachment in ovarian cancer. As ghrelin has previously been demonstrated to signal through the ERK1/2 pathway in cancer, we investigated ERK1/2 signalling in ovarian cancer cell lines. In the SKOV3 ovarian cancer cell line, a reduction in ERK1/2 phosphorylation (0.58 fold +/- 0.23, p <0.05) in response to 100 nM ghrelin treatment was observed, while no significant change in ERK1/2 signalling was seen in the OV-MZ-6 cell line with treatment. This suggests that this pathway is unlikely to be involved in mediating the increased migration seen in the ovarian cancer cell lines with ghrelin treatment. In this study ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for obestatin, however, no correlation between cancer grade and level of obestatin transcript expression was observed. In the ovarian-derived cell lines studied (SKOV3, OV-MZ-6 and hOSE 17.1) it was demonstrated that the full length preproghrelin mRNA transcripts were expressed in all cell lines, suggesting they have the ability to produce mature obestatin. This is the first study to demonstrate that obestatin stimulates cell migration and cell invasion. Obestatin induced a significant increase in migration in the SKOV3 ovarian cancer cell line with 10 nM (2.80 +/- 0.52 fold, p <0.05) and 100 nM treatments (3.12 +/- 0.68 fold, p <0.05) and in the OV-MZ-6 cancer cell line with 10 nM (2.04 +/- 0.10 fold, p <0.01) and 100 nM treatments (2.00 +/- 0.37 fold, p <0.05). Obestatin treatment did no affect cell migration in the hOSE 17.1normal ovarian epithelial cell line. Obestatin treatment (100 nM) also stimulated a significant increase in cell invasion in the OV-MZ-6 ovarian cancer cell line (1.45 fold +/- 0.13, p <0.05) and in the hOSE17.1 normal ovarian cell line cells (1.40 fold +/- 0.04 and 1.55 fold +/- 0.05 respectively, p <0.01) with 10 nM and 100 nM treatments. Obestatin treatment did not stimulate cell invasion in the SKOV3 ovarian cancer cell line. This lack of obestatin-stimulated invasion in the SKOV3 cell line may be a cell line specific result. In this study, obestatin did not stimulate cell proliferation in the ovarian cell lines and it has previously been shown to have no effect on cell proliferation in the BON-1 pancreatic neuroendocrine and GC rat somatotroph tumour cell lines. In contrast, obestatin has been shown to affect cell proliferation in gastric and thyroid cancer cell lines, and in some normal cell lines. Obestatin also had no effect on attachment of any of the cell lines to any of the ECM components tested (fibronectin, vitronectin, collagen I and collagen IV). The mechanism of action of obestatin was investigated further using a two dimensional-difference in gel electrophoresis (2D-DIGE) proteomic approach. After treatment with obestating (0, 10 and 100 nM), SKOV3 ovarian cancer and hOSE 17.1 normal ovarian cell lines were collected and 2D-DIGE analysis and mass spectrometry were performed to identify proteins that were differentially expressed in response to treatment. Twenty-six differentially expressed proteins were identified and analysed using Ingenuity Pathway Analysis (IPA). This linked 16 of these proteins in a network. The analysis suggested that the ERK1/2 MAPK pathway was a major mediator of obestatin action. ERK1/2 has previously been shown to be associated with obestatin-stimulated cell proliferation and with the anti-apoptotic effects of obestatin. Activation of the ERK1/2 signalling pathway by obestatin was, therefore, investigated in the SKOV3 and OV-MZ-6 ovarian cancer cell lines using anti-active antibodies and Western immunoblots. Obestatin treatment significantly decreased ERK1/2 phosphorylation at higher obestatin concentrations in both the SKOV3 (100 nM and 1000 nM) and OV-MZ-6 (1000 nM) cell lines compared to the untreated controls. Currently, very little is known about obestatin signalling in cancer. This thesis has demonstrated for the first time that the ghrelin axis may play a role in ovarian cancer migration. Ghrelin and obestatin increased cell migration in ovarian cancer cell lines, indicating that they may be a useful target for therapies that reduce ovarian cancer progression. Further studies investigating the role of the ghrelin axis using in vivo ovarian cancer metastasis models are warranted.

Modelling for the electricity distribution network

Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

Load leveling in LV network using coordianted Energy Storage Units

This paper proposes a new distributed coordination approach to make load leveling, using Energy Storage Units (ESUs) in LV network. The proposed distributed control strategy is based on consensus algorithm which shares the required active power equally among the ESUs with respect to their rating. To show the effectiveness of the proposed approach, a typical radial LV network is simulated as a case study.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).