Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion

The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

Turbulence characteristics of a small subtropical estuary during and after some moderate rainfall

In natural estuaries, scalar diffusion and dispersion are driven by turbulence. In the present study, detailed turbulence measurements were conducted in a small subtropical estuary with semi-diurnal tides under neap tide conditions. Three acoustic Doppler velocimeters were installed mid-estuary at fixed locations close together. The units were sampled simultaneously and continuously at relatively high frequency for 50 h. The results illustrated the influence of tidal forcing in the small estuary, although low frequency longitudinal velocity oscillations were observed and believed to be induced by external resonance. The boundary shear stress data implied that the turbulent shear in the lower flow region was one order of magnitude larger than the boundary shear itself. The observation differed from turbulence data in a laboratory channel, but a key feature of natural estuary flow was the significant three dimensional effects associated with strong secondary currents including transverse shear events. The velocity covariances and triple correlations, as well as the backscatter intensity and covariances, were calculated for the entire field study. The covariances of the longitudinal velocity component showed some tidal trend, while the covariances of the transverse horizontal velocity component exhibited trends that reflected changes in secondary current patterns between ebb and flood tides. The triple correlation data tended to show some differences between ebb and flood tides. The acoustic backscatter intensity data were characterised by large fluctuations during the entire study, with dimensionless fluctuation intensity I0b =Ib between 0.46 and 0.54. An unusual feature of the field study was some moderate rainfall prior to and during the first part of the sampling period. Visual observations showed some surface scars and marked channels, while some mini transient fronts were observed.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Reliability of ultrasonographic measurement of the architecture of the vastus lateralis and gastrocnemius medialis muscles in older adults

Objective To determine the test-retest reliability of measurements of thickness, fascicle length (Lf) and pennation angle (θ) of the vastus lateralis (VL) and gastrocnemius medialis (GM) muscles in older adults. Participants Twenty-one healthy older adults (11 men and ten women; average age 68·1 ± 5·2 years) participated in this study. Methods Ultrasound images (probe frequency 10 MHz) of the VL at two sites (VL site 1 and 2) were obtained with participants seated with knee at 90º flexion. For GM measures, participants lay prone with ankle fixed at 15º dorsiflexion. Measures were taken on two separate occasions, 7 days apart (T1 and T2). Results The ICCs (95% CI) were: VL site 1 thickness = 0·96(0·90–0·98); VL site 2 thickness = 0·96(0·90–0·98), VL θ = 0·87(0·68–0·95), VL Lf = 0·80(0·50–0·92), GM thickness = 0·97(0·92–0·99), GM θ = 0·85(0·62–0·94) and GM Lf =0·90(0·75–0·96). The 95% ratio limits of agreement (LOAs) for all measures, calculated by multiplying the standard deviation of the ratio of the results between T1 and T2 by 1·96, ranged from 10·59 to 38·01%. Conclusion The ability of these tests to determine a real change in VL and GM muscle architecture is good on a group level but problematic on an individual level as the relatively large 95% ratio LOAs in the current study may encompass the changes in architecture observed in other training studies. Therefore, the current findings suggest that B-mode ultrasonography can be used with confidence by researchers when investigating changes in muscle architecture in groups of older adults, but its use is limited in showing changes in individuals over time.

Mapping resilience : A framework for changing cities

Urban centres base their resilience on the ability to evolve and adapt as needed throughout their life. Although constantly developing, changing and subsuming nature for its needs, the current age of environmental awareness requires that cities progress in a more conscious and considered way. While they have become the dominant form of human habitation, there now exists a need to integrate 'green' solutions into urban centres to address social, physical and environmental wellbeing. The means of implementing the vast array of possible solutions without negative impacts is not clear; cities are complex systems, layering meaning, history and cultural memory ‐ they are a manifestation of shared cultural values, and as such, they do not allow a tabula rasa approach of 'blanket' solutions. All around us, cities are continuing to develop and change, and although their form is varied ‐ sprawling cities with density and sustainability problems; or collapsing cities with 'dead' centres and dilapidated districts – a common issue is the resilience of the local identity. The strength or resilience of cities lies in the elements which have become fixed points in the urban structure, giving character and identity to a shared urban experience. These elements need to be identified and either maintained or revitalised. Similarly, the identification of urban elements which can most viably be modified without compromising character and identity of place, will assist in making concrete contributions to increasing both the sustainability and experience of cities, making them more resilient. Through an examination of case studies, this paper suggests a framework to inform urban renewal assessing the widespread elements which generate an urban identity, beyond the traditional approach of heritage conservation for cultural or tourist purposes. The rapid contemporary alteration of urban structures requires an innovative methodology which satisfies on one side the need of new sustainable performances and, on the other, the resilience of the local character.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

The Profiling of Property, Plant & Equipment (PPE) Contributions in Australia and Malaysia Public Listed Construction Companies

The purpose of this paper is to study the profiling of property, plant and equipment (PPE) contributions in Australia and Malaysia construction companies. A company’s worth is usually based on the listed share price on the stock exchange. In arriving at the net profit, the contribution of PPE in the company’s assets is somehow being neglected. This paper will investigate the followings; firstly the level of PPE contribution in the construction firms by comparing the PPE contributions to the company’s asset as a whole which includes fixed (non-current) assets and current assets. This will determine the true strength of the companies, rather than relying on the share prices alone. Secondly, the paper will determine the trend of company’s asset ownership to show the company’s performance of the PPE ownership during the period of study. The data is based on the selected construction companies listed on the Australian Stock Exchange (ASX) and Malaysian Stock Exchange, known as Bursa Malaysia. The profiling will help to determine the strength of the construction firms based on the PPE holding, and the level of PPE ownerships in the two countries construction firms during the period of study.

Determinants of China’s regional innovation capacity

This paper investigates the determinants of China’s regional innovation capacity (RIC) and variations in these determinants between different types of regions. Based on the framework of national innovation capacity (NIC) and research on innovation system, this paper develops a framework of RIC in the Chinese context. Using panel data from 1991 to 2009, clustering analysis is first employed to classify regions according to their innovation development path. Panel data regressions with fixed effect model are conducted to explore the determinants of RIC and how these vary across the different regional clusters. We find that the 30 regions can be clustered into three groups, and there are considerable differences in the drivers of RIC between these different regional groups.

DispoMaps

The gathering of people in everyday life is intertwined with travelling to negotiated locations. As a result, mobile phones are often used to rearrange meetings when one or more participants are late or cannot make it on time. Our research is based on the hypothesis that the provision of location data can enhance the experience of people who are meeting each other in different locations. Disposable Maps allows users to select contacts from their phone’s address book who then receive up-to-date location data. The utilisation of peer-to-peer notifications and the application of unique URLs for location storage and presentation enable location sharing whilst ensuring users’ location privacy. In contrast to other location sharing services like Google Latitude, Disposable Maps enables ad hoc location sharing to actively selected location receivers for a fixed period of time in a specific given situation.

Produsage: a closer look at continuing developments

The concept of produsage developed from the realisation that new language was needed to describe the new phenomena emerging from the intersection of Web 2.0, user-generated content, and social media since the early years of the new millennium. When hundreds, thousands, maybe tens of thousands of participants utilise online platforms to collaborate in the development and continuous improvement of a wide variety of content – from software to informational resources to creative works –, and when this work takes place through a series of more or less unplanned, ad hoc, almost random cooperative encounters, then to describe these processes using terms which were developed during the industrial revolution no longer makes much sense. When – exactly because what takes place here is no longer a form of production in any conventional sense of the word – the outcomes of these massively distributed collaborations appear in the form of constantly changing, permanently mutable bodies of work which are owned at once by everyone and no-one, by the community of contributors as a whole but by none of them as individuals, then to conceptualise them as fixed and complete products in the industrial meaning of the term is missing the point. When what results from these efforts is of a quality (in both depth and breadth) that enables it to substitute for, replace, and even undermine the business model of long-established industrial products, even though precariously it relies on volunteer contributions, and when their volunteering efforts make it possible for some contributors to find semi- or fully professional employment in their field, then conventional industrial logic is put on its head.

Confirmatory factor analysis of the Behaviour of Young Novice Drivers Scale (BYNDS)

The greatly increased risk of being killed or injured in a car crash for the young novice driver has been recognised in the road safety and injury prevention literature for decades. Risky driving behaviour has consistently been found to contribute to traffic crashes. Researchers have devised a number of instruments to measure this risky driving behaviour. One tool developed specifically to measure the risky behaviour of young novice drivers is the Behaviour of Young Novice Drivers Scale (BYNDS) (Scott-Parker et al., 2010). The BYNDS consists of 44 items comprising five subscales for transient violations, fixed violations, misjudgement, risky driving exposure, and driving in response to their mood. The factor structure of the BYNDS has not been examined since its development in a matched sample of 476 novice drivers aged 17-25 years. Method: The current research attempted to refine the BYNDS and explore its relationship with the self-reported crash and offence involvement and driving intentions of 390 drivers aged 17-25 years (M = 18.23, SD = 1.58) in Queensland, Australia, during their first six months of independent driving with a Provisional (intermediate) driver’s licence. A confirmatory factor analysis was undertaken examining the fit of the originally proposed BYNDS measurement model. Results: The model was not a good fit to the data. A number of iterations removed items with low factor loadings, resulting in a 36-item revised BYNDS which was a good fit to the data. The revised BYNDS was highly internally consistent. Crashes were associated with fixed violations, risky driving exposure, and misjudgement; offences were moderately associated with risky driving exposure and transient violations; and road-rule compliance intentions were highly associated with transient violations. Conclusions: Applications of the BYNDS in other young novice driver populations will further explore the factor structure of both the original and revised BYNDS. The relationships between BYNDS subscales and self-reported risky behaviour and attitudes can also inform countermeasure development, such as targeting young novice driver non-compliance through enforcement and education initiatives.

Thomas Young’s investigations in gradient-index optics

Purpose: James Clerk Maxwell is usually recognized as being the first, in 1854, to consider using inhomogeneous media in optical systems. However, some fifty years earlier Thomas Young, stimulated by his interest in the optics of the eye and accommodation, had already modeled some applications of gradient-index optics. These applications included using an axial gradient to provide spherical aberration-free optics and a spherical gradient to describe the optics of the atmosphere and the eye lens. We evaluated Young’s contributions. Method: We attempted to derive Young’s equations for axial and spherical refractive index gradients. Raytracing was used to confirm accuracy of formula. Results: We did not confirm Young’s equation for the axial gradient to provide aberration-free optics, but derived a slightly different equation. We confirmed the correctness of his equations for deviation of rays in a spherical gradient index and for the focal length of a lens with a nucleus of fixed index surrounded by a cortex of reducing index towards the edge. Young claimed that the equation for focal length applied to a lens with part of the constant index nucleus of the sphere removed, such that the loss of focal length was a quarter of the thickness removed, but this is not strictly correct. Conclusion: Young’s theoretical work in gradient-index optics received no acknowledgement from either his contemporaries or later authors. While his model of the eye lens is not an accurate physiological description of the human lens, with the index reducing least quickly at the edge, it represented a bold attempt to approximate the characteristics of the lens. Thomas Young’s work deserves wider recognition.

Mind games : applying White’s principles of narrative therapy to the creation of a cabaret about depression and bipolar disorder

This PhD represents my attempt to make sense of my personal experiences of depression through the form of cabaret. I first experienced depression in 2006. Previously, I had considered myself to be a happy and optimistic person. I found the experience of depression to be a shock: both in the experience itself, and also in the way it effected my own self image. These personal experiences, together with my professional history as a songwriter and cabaret performer, have been the motivating force behind the research project. This study has explored the question: What are the implications of applying principles of Michael White’s narrative therapy to the creation of a cabaret performance about depression and bipolar disorder? There is a 50 percent weighting on the creative work, the cabaret performance Mind Games, and a 50 percent weighting on the written exegesis. This research has focussed on the illustration of therapeutic principles in order to play games of truth within a cabaret performance. The research project investigates ways of telling my own story in relation to others’ stories through three re-authoring principles articulated in Michael White’s narrative therapy: externalisation, an autonomous ethic of living and rich descriptions. The personal stories presented in the cabaret were drawn from my own experiences and from interviews with individuals with depression or bipolar disorder. The cabaret focussed on the illustration of therapeutic principles, and was not focussed on therapeutic ends for myself or the interviewees. The research question has been approached through a methodology combining autoethnographic, practice-led and action research. Auto ethnographic research is characterised by close investigation of assumptions, attitudes, and beliefs. The combination of autoethnographic, practice-led, action research has allowed me to bring together personal experiences of mental illness, research into therapeutic techniques, social attitudes and public discourses about mental illness and forms of contemporary cabaret to facilitate the creation of a one-woman cabaret performance. The exegesis begins with a discussion of games of truth as informed by Michel Foucault and Michael White and self-stigma as informed by Michael White and Erving Goffman. These concepts form the basis for a discussion of my own personal experiences. White’s narrative therapy is focused on individuals re-authoring their stories, or telling their stories in different ways. White’s principles are influenced by Foucault’s notions of truth and power. Foucault’s term games of truth has been used to describe the effect of a ‘truth in flux’ that occurs through White’s re-authoring process. This study argues that cabaret is an appropriate form to represent this therapeutic process because it favours heightened performativity over realism, and showcases its ‘constructedness’ and artificiality. Thus cabaret is well suited to playing games of truth. A contextual review compares two major cabaret trends, personal cabaret and provocative cabaret, in reference to the performer’s relationship with the audience in terms of distance and intimacy. The study draws a parallel between principles of distance and intimacy in Michael White’s narrative therapy and relates these to performative terms of distance and intimacy. The creative component of this study, the cabaret Mind Games, used principles of narrative therapy to present the character ‘Jo’ playing games of truth through: externalising an aspect of her personality (externalisation); exploring different life values (an autonomous ethic of living); and enacting multiple versions of her identity (rich descriptions). This constant shifting between distance and intimacy within the cabaret created the effect of a truth in ‘constant flux’, to use one of White’s terms. There are three inter-related findings in the study. The first finding is that the application of principles of White’s narrative therapy was able to successfully combine provocative and empathetic elements within the cabaret. The second finding is that the personal agenda of addressing my own self-stigma within the project limited the effective portrayal of a ‘truth in flux’ within the cabaret. The third finding presents the view that the cabaret expressed ‘Jo’ playing games of truth in order to journey towards her own "preferred identity claim" (White 2004b) through an act of "self care" (Foucault 2005). The contribution to knowledge of this research project is the application of therapeutic principles to the creation of a cabaret performance. This process has focussed on creating a self-revelatory cabaret that questions notions of a ‘fixed truth’ through combining elements of existing cabaret forms in new ways. Two major forms in contemporary cabaret, the personal cabaret and the provocative cabaret use the performer-audience relationship in distinctive ways. Through combining elements of these two cabaret forms, I have explored ways to create a provocative cabaret focussed on the act of self-revelation.

Innate Immunity in Lobsters: Partial Purification and Characterization of a Panulirus cygnus Anti-A Lectin

A lectin detected in haemolymph from the Australian spiny lobster Panulirus cygnus agglutinated human ABO Group A cells to a higher titre than Group O or B. The lectin also agglutinated rat and sheep erythrocytes, with reactivity with rat erythrocytes strongly enhanced by treatment with the proteolytic enzyme papain, an observation consistent with reactivity via a glycolipid. The lectin, purified by affinity chromatography on fixed rat-erythrocyte stroma, was inhibited equally by N-acetylglucosamine and N-acetylgalactosamine. Comparison of data from gel filtration of haemolymph (behaving as a 1,800,000 Da macromolecule), and polyacrylamide gel electrophoresis of purified lectin (a single 67,000 Da band), suggested that in haemolymph the lecin was a multimer. The purified anti-A lectin autoprecipitated unless the storage solution contained chaotropic inhibitors (125 mmol/L sucrose: 500 mmol/L urea). The properties of this anti-A lectin and other similar lectins are consistent with a role in innate immunity in these invertebrates.