On the order of the fractional Laplacian in determining the spatio-temporal evolution of a space-fractional model of cardiac electrophysiology

Space-fractional operators have been used with success in a variety of practical applications to describe transport processes in media characterised by spatial connectivity properties and high structural heterogeneity altering the classical laws of diffusion. This study provides a systematic investigation of the spatio-temporal effects of a space-fractional model in cardiac electrophysiology. We consider a simplified model of electrical pulse propagation through cardiac tissue, namely the monodomain formulation of the Beeler-Reuter cell model on insulated tissue fibres, and obtain a space-fractional modification of the model by using the spectral definition of the one-dimensional continuous fractional Laplacian. The spectral decomposition of the fractional operator allows us to develop an efficient numerical method for the space-fractional problem. Particular attention is paid to the role played by the fractional operator in determining the solution behaviour and to the identification of crucial differences between the non-fractional and the fractional cases. We find a positive linear dependence of the depolarization peak height and a power law decay of notch and dome peak amplitudes for decreasing orders of the fractional operator. Furthermore, we establish a quadratic relationship in conduction velocity, and quantify the increasingly wider action potential foot and more pronounced dispersion of action potential duration, as the fractional order is decreased. A discussion of the physiological interpretation of the presented findings is made.

Evaluation of Australian Performing Arts Market 2014-2018 REPORT TWO APAM inter-year report 2015 DECEMBER

The report follows up on data and trends tabled in August 2015 that collected data from two key sources – six identified case study productions that have been tracked for eighteen months, and an online survey delivered to all APAM 2014 delegates. The comparative report has been constructed through an analysis of data reported from the August 2015 and the most recent online survey to all 2104 PM delegates conducted in late November 2015. The report highlights six key trends emerging from the data: The majority of survey respondents will return to APAM 2016; The central reason for attending is the networking opportunities the Market affords; Respondents are confident that a range of new relationships forged at the Market will afford long-term interest and buying opportunities and that as a result of the 2014 event, real touring outcomes were realised for some respondents; Respondents would like to see greater attention to a greater number of networking activities within the program to enable touring outcomes; The multi-venue model is still of concern, and is a recurrent issue from earlier surveys; The level of expense incurred by producers to present work at APAM. Throughout the report, extracted data from the online survey responses will be tabled to develop a narrative in response to the key research aims outlined in the Brisbane Powerhouse Tender document (2011). A full version of the collated responses to the survey questions can be found in the appendices of the report.

A novel approach to 6-DOF adaptive trajectory tracking control of an AUV in the presence of parameter uncertainties

In this paper, the trajectory tracking control of an autonomous underwater vehicle (AUVs) in six-degrees-of-freedom (6-DOFs) is addressed. It is assumed that the system parameters are unknown and the vehicle is underactuated. An adaptive controller is proposed, based on Lyapunov׳s direct method and the back-stepping technique, which interestingly guarantees robustness against parameter uncertainties. The desired trajectory can be any sufficiently smooth bounded curve parameterized by time even if consist of straight line. In contrast with the majority of research in this field, the likelihood of actuators׳ saturation is considered and another adaptive controller is designed to overcome this problem, in which control signals are bounded using saturation functions. The nonlinear adaptive control scheme yields asymptotic convergence of the vehicle to the reference trajectory, in the presence of parametric uncertainties. The stability of the presented control laws is proved in the sense of Lyapunov theory and Barbalat׳s lemma. Efficiency of presented controller using saturation functions is verified through comparing numerical simulations of both controllers.

Learning with symmetric label noise: The importance of being unhinged

Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2008] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing. This ostensibly shows that convex losses are not SLN-robust. In this paper, we propose a convex, classification-calibrated loss and prove that it is SLN-robust. The loss avoids the Long and Servedio [2008] result by virtue of being negatively unbounded. The loss is a modification of the hinge loss, where one does not clamp at zero; hence, we call it the unhinged loss. We show that the optimal unhinged solution is equivalent to that of a strongly regularised SVM, and is the limiting solution for any convex potential; this implies that strong l2 regularisation makes most standard learners SLN-robust. Experiments confirm the unhinged loss’ SLN-robustness.

A Story of Organized Crime: Constructing Criminality and Building Institutions

This is a narrative about the way in which a category of crime-to-be-combated is constructed through the discipline of criminology and the agents of discipline in criminal justice. The aim was to examine organized crime through the eyes of those whose job it is to fight it (and define it), and in doing so investigate the ways social problems surface as sites for state intervention. A genealogy of organized crime within criminological thought was completed, demonstrating that there are a range of different ways organized crime has been constructed within the social scientific discipline, and each of these were influenced by the social context, political winds and intellectual climate of the time. Following this first finding, in-depth qualitative interviews were conducted with individuals who had worked at the apex of the policing of organized crime in Australia, in order to trace their understandings of organized crime across recent history. It was found that organized crime can be understood as an object of the discourse of the politics of law and order, the discourse of international securitization, new public management in policing business, and involves the forging of outlaw identities. Therefore, there are multiple meanings of organized crime that have arisen from an interconnected set of social, political, moral and bureaucratic discourses. The institutional response to organized crime, including law and policing, was subsequently examined. An extensive legislative framework has been enacted at multiple jurisdictional levels, and the problem of organized crime was found to be deserving of unique institutional powers and configurations to deal with it. The social problem of organized crime, as constituted by the discourses mapped out in this research, has led to a new generation of increasingly preemptive and punitive laws, and the creation of new state agencies with amplified powers. That is, the response to organized crime, with a focus on criminalization and enforcement, has been driven and shaped by the four discourses and the way in which the phenomenon is constructed within them. An appreciation of the nexus between the emergence of the social problem, and the formation of institutions in response to it, is important in developing a more complete understanding of the various dimensions of organized crime.

A bottom-up integration of vision and actions to create cognitive humanoids

In recent years more and more complex humanoid robots have been developed. On the other hand programming these systems has become more difficult. There is a clear need for such robots to be able to adapt and perform certain tasks autonomously, or even learn by themselves how to act. An important issue to tackle is the closing of the sensorimotor loop. Especially when talking about humanoids the tight integration of perception with actions will allow for improved behaviours, embedding adaptation on the lower-level of the system.

Making the most of spatial information in health: A tutorial in Bayesian disease mapping for areal data

Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease. Bayesian models have become a standard approach to disease mapping in recent decades. This article aims to provide a basic understanding of the key concepts involved in Bayesian disease mapping methods for areal data. It is anticipated that this will help in interpretation of published maps, and provide a useful starting point for anyone interested in running disease mapping methods for areal data. The article provides detailed motivation and descriptions on disease mapping methods by explaining the concepts, defining the technical terms, and illustrating the utility of disease mapping for epidemiological research by demonstrating various ways of visualising model outputs using a case study. The target audience includes spatial scientists in health and other fields, policy or decision makers, health geographers, spatial analysts, public health professionals, and epidemiologists.

Editorial of "International Journal of Critical Indigenous Studies Volume 4, Number 2, 2011"

This special edition of the International Journal of Critical Indigenous Studies focuses upon the work scholars within the growing discipline of Aboriginal and Torres Strait Islander health studies. The lamentable state of Indigenous health in Australia is reflected in Indigenous populations elsewhere, especially where settler colonialism has left an indelible mark. This special edition therefore speaks to where Indigenous health outcomes and the efficacy of remedies are causing concern. Common to all is the demand that Indigenous people are placed front and centre of all attempts to improve health outcomes and that improvements are sought in culturally sensitive ways. Terry Dunbar presents findings from a research study that set out to investigate the Indigenous experiences of health and family services in the Northern Territory, Australia. The study asserts that cultural security is an integral and vital element of any policy that will impact upon Indigenous peoples. Dunbar concludes by arguing that in seeking positive change with regard to cultural security or otherwise, the most vociferous champions of that change are likely to be the Aboriginal communities affected. The article by Bronwyn Fredericks, Karen Adams, Sandra Angus and Melissa Walker also highlights the need to involve Aboriginal and Torres Strait Islander people, in this case women, in the design and development of strategies affecting their lives. Utilising routine communication methods such the ‘talking circle’ and the process referred to as ‘talkin’ up’, where women ‘talk back’ to one another about issues of personal importance, the article argues that the health strategy which emerged through these consultation approaches was more accurately informed by and responsive to women’s health need. Indeed, the resulting strategy reflected the women’s sense of themselves and the clear direction they felt their health services and polices should take.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7T

PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

Revocation and update of trust in autonomous delay tolerant networks

A Delay Tolerant Network (DTN) is a dynamic, fragmented, and ephemeral network formed by a large number of highly mobile nodes. DTNs are ephemeral networks with highly mobile autonomous nodes. This requires distributed and self-organised approaches to trust management. Revocation and replacement of security credentials under adversarial influence by preserving the trust on the entity is still an open problem. Existing methods are mostly limited to detection and removal of malicious nodes. This paper makes use of the mobility property to provide a distributed, self-organising, and scalable revocation and replacement scheme. The proposed scheme effectively utilises the Leverage of Common Friends (LCF) trust system concepts to revoke compromised security credentials, replace them with new ones, whilst preserving the trust on them. The level of achieved entity confidence is thereby preserved. Security and performance of the proposed scheme is evaluated using an experimental data set in comparison with other schemes based around the LCF concept. Our extensive experimental results show that the proposed scheme distributes replacement credentials up to 35% faster and spreads spoofed credentials of strong collaborating adversaries up to 50% slower without causing any significant increase on the communication and storage overheads, when compared to other LCF based schemes.

A semi-analytical solution for multilayer diffusion in a composite medium consisting of a large number of layers

Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.

Appendiceal sonography in children: A retrospective analysis as a platform for potential implementation of diagnostic categories

- Background Sonography is an important diagnostic tool in children with suspected appendicitis. Reported accuracy and appendiceal visualisation rates vary significantly, as does the management of equivocal ultrasound findings. The aim of this study was to audit appendiceal sonography at a tertiary children's hospital, and provide baseline data for a future prospective study. - Summary of work Records of children who underwent ultrasound studies for possible appendicitis between January 2008 and December 2010 were reviewed. Variables included patient demographics, sonographic appendix characteristics, and secondary signs. Descriptive statistics and analysis using ANOVA, Mann-Whitney U test, and ROC curves were performed. Mater Human Research Ethic Committee approval was granted. - Summary of results There were 457 eligible children. Using a dichotomous diagnostic model (including equivocal results), sensitivity was 89.6%, specificity 91.6%, and diagnostic yield of 40.7%. ROC curve analysis of a 6mm diameter cut-off was 0.88 AUC (95% CI 0.80 to 0.95). - Discussion and conclusions Sonography is an accurate test for acute appendicitis in children, with a high sensitivity and negative predictive value. A diameter of 6mm as an absolute cut-off in a binary model can lead to false findings. Results were compared with available literature. Recent publications propose categorising diameter1 and integrating secondary signs2 to improve accuracy and provide more meaningful results to clinicians. This study will be a benchmark for future studies with multiple diagnostic categorisation.