Effects of free flow state highway traffic parameters on the performance of amplify and forward cooperative multi-hop vehicular networks

In this paper we analyse the effects of highway traffic flow parameters like vehicle arrival rate and density on the performance of Amplify and Forward (AF) cooperative vehicular networks along a multi-lane highway under free flow state. We derive analytical expressions for connectivity performance and verify them with Monte-Carlo simulations. When AF cooperative relaying is employed together with Maximum Ratio Combining (MRC) at the receivers the average route error rate shows 10-20 fold improvement compared to direct communication. A 4-8 fold increase in maximum number of traversable hops can also be observed at different vehicle densities when AF cooperative communication is used to strengthen communication routes. However the theorical upper bound of maximum number of hops promises higher performance gains.

Lattice-free models of cell invasion : discrete simulations and travelling waves

Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.

Synthesis and characterisation of titanium sol-gels in varied gravity environments

Sol-gel synthesis in varied gravity is only a relatively new topic in the literature and further investigation is required to explore its full potential as a method to synthesise novel materials. Although trialled for systems such as silica, the specific application of varied gravity synthesis to other sol-gel systems such as titanium has not previously been undertaken. Current literature methods for the synthesis of sol-gel material in reduced gravity could not be applied to titanium sol-gel processing, thus a new strategy had to be developed in this study. To successfully conduct experiments in varied gravity a refined titanium sol-gel chemical precursor had to be developed which allowed the single solution precursor to remain un-reactive at temperatures up to 50oC and only begin to react when exposed to a pressure decrease from a vacuum. Due to the new nature of this precursor, a thorough characterisation of the reaction precursors was subsequently undertaken with the use of techniques such as Nuclear Magnetic Resonance, Infra-red and UV-Vis spectroscopy in order to achieve sufficient understanding of precursor chemistry and kinetic stability. This understanding was then used to propose gelation reaction mechanisms under varied gravity conditions. Two unique reactor systems were designed and built with the specific purpose to allow the effects of varied gravity (high, normal, reduced) during synthesis of titanium sol-gels to be studied. The first system was a centrifuge capable of providing high gravity environments of up to 70 g’s for extended periods, whilst applying a 100 mbar vacuum and a temperature of 40-50oC to the reaction chambers. The second system to be used in the QUT Microgravity Drop Tower Facility was also required to provide the same thermal and vacuum conditions used in the centrifuge, but had to operate autonomously during free fall. Through the use of post synthesis characterisation techniques such as Raman Spectroscopy, X-Ray diffraction (XRD) and N2 adsorption, it was found that increased gravity levels during synthesis, had the greatest effect on the final products. Samples produced in reduced and normal gravity appeared to form amorphous gels containing very small particles with moderate surface areas. Whereas crystalline anatase (TiO2), was found to form in samples synthesised above 5 g with significant increases in crystallinity, particle size and surface area observed when samples were produced at gravity levels up to 70 g. It is proposed that for samples produced in higher gravity, an increased concentration gradient of water is forms at the bottom of the reacting film due to forced convection. The particles formed in higher gravity diffuse downward towards this excess of water, which favours the condensation reaction of remaining sol gel precursors with the particles promoting increased particle growth. Due to the removal of downward convection in reduced gravity, particle growth due to condensation reaction processes are physically hindered hydrolysis reactions favoured instead. Another significant finding from this work was that anatase could be produced at relatively low temperatures of 40-50oC instead of the conventional method of calcination above 450oC solely through sol-gel synthesis at higher gravity levels. It is hoped that the outcomes of this research will lead to an increased understanding of the effects of gravity on chemical synthesis of titanium sol-gel, potentially leading to the development of improved products suitable for diverse applications such as semiconductor or catalyst materials as well as significantly reducing production and energy costs through manufacturing these materials at significantly lower temperatures.

Interferon-free therapy for hepatitis C, how prepared is Australia for biosimilars?

The Hepatitis C virus (HCV) affects some 150 million people worldwide. However, unlike hepatitis A and B there is no vaccination for HCV and approximately 75% of people exposed to HCV develop chronic hepatitis. In Australia, around 226,700 people live with chronic HCV infection costing the government approximately $252 million per year. Historically, the standard approved/licenced treatment for HCV is pegylated interferon with ribavirin. There are major drawbacks with interferon-based therapy including side effects, long duration of therapy, limited access and affordability. Our previous survey of an at-risk population reported HCV treatment coverage of only 5%. Since April 2013, a new class of interferon-free treatments for chronic HCV is subsidised under the Pharmaceutical Benefits Scheme: boceprevir and telaprevir - estimated to cost the Australian Government in excess of $220 million over five years. Other biologic interferon-free therapeutic agents are scheduled to enter the Australian market. Use of small molecule generic pharmaceuticals has been advocated as a means of public cost savings. However, with the new biologic agents, generics (biosimilars) may not be feasible or straightforward, due to long patent life; marketing exclusivity; and regulatory complexity for these newer products.

Precedent-free fault isolation in a diesel engine EGR valve system

In this paper, a framework for isolating unprecedented faults for an EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the recently introduced Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for an EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors.

Precedent-free fault isolation in a diesel engine exhaust gas recirculation system

In this paper, a recently introduced model-based method for precedent-free fault detection and isolation (FDI) is modified to deal with multiple input, multiple output (MIMO) systems and is applied to an automotive engine with exhaust gas recirculation (EGR) system. Using normal behavior data generated by a high fidelity engine simulation, the growing structure multiple model system (GSMMS) approach is used to construct dynamic models of normal behavior for the EGR system and its constituent subsystems. Using the GSMMS models as a foundation, anomalous behavior is detected whenever statistically significant departures of the most recent modeling residuals away from the modeling residuals displayed during normal behavior are observed. By reconnecting the anomaly detectors (ADs) to the constituent subsystems, EGR valve, cooler, and valve controller faults are isolated without the need for prior training using data corresponding to particular faulty system behaviors.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

Lattice-free descriptions of collective motion with crowding and adhesion

Cell-to-cell adhesion is an important aspect of malignant spreading that is often observed in images from the experimental cell biology literature. Since cell-to-cell adhesion plays an important role in controlling the movement of individual malignant cells, it is likely that cell-to-cell adhesion also influences the spatial spreading of populations of such cells. Therefore, it is important for us to develop biologically realistic simulation tools that can mimic the key features of such collective spreading processes to improve our understanding of how cell-to-cell adhesion influences the spreading of cell populations. Previous models of collective cell spreading with adhesion have used lattice-based random walk frameworks which may lead to unrealistic results, since the agents in the random walk simulations always move across an artificial underlying lattice structure. This is particularly problematic in high-density regions where it is clear that agents in the random walk align along the underlying lattice, whereas no such regular alignment is ever observed experimentally. To address these limitations, we present a lattice-free model of collective cell migration that explicitly incorporates crowding and adhesion. We derive a partial differential equation description of the discrete process and show that averaged simulation results compare very well with numerical solutions of the partial differential equation.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Reconsidering the agency of a privately appointed receiver and manager in three specific circumstances

Where a secured lender elects to appoint a receiver and manager, the appointment document standardly provides for the receiver and manager to act as the agent of the debtor. This article considers the significance of this agency in the context of three specific issues that have the potential to arise in the receivership of a corporate borrower across all Australian jurisdictions.

Simulating the effect of acoustic treatment types for residential balconies with road traffic noise

Development of design guides to estimate the difference in speech interference level due to road traffic noise between a reference position and balcony position or façade position is explored. A previously established and validated theoretical model incorporating direct, specular and diffuse reflection paths is used to create a database of results across a large number of scenarios. Nine balcony types with variable acoustic treatments are assessed to provide acoustic design guidance on optimised selection of balcony acoustic treatments based on location and street type. In total, the results database contains 9720 scenarios on which multivariate linear regression is conducted in order to derive an appropriate design guide equation. The best fit regression derived is a multivariable linear equation including modified exponential equations on each of nine deciding variables, (1) diffraction path difference, (2) ratio of total specular energy to direct energy, (3) distance loss between reference position and receiver position, (4) distance from source to balcony façade, (5) height of balcony floor above street, (6) balcony depth, (7) height of opposite buildings, (8) diffusion coefficient of buildings, and; (9) balcony average absorption. Overall, the regression correlation coefficient, R2, is 0.89 with 95% confidence standard error of ±3.4 dB.

Mesoporous titania microspheres composed of exposed active faceted nanosheets and their catalytic activities for solvent-free synthesis of azoxybenzenes

Mesoporous titania microspheres composed of nanosheets with exposed active facets were prepared by hydrothermal synthesis in the presence of hexafluorosilicic acid. They exhibited superior catalytic activity in the solvent-free synthesis of azoxybenzene by oxidation of aniline and could be used for 7 cycles with slight loss of activity.

Serum HE4 as a prognostic marker in endometrial cancer : a population based study

Objective HE4 has emerged as a promising biomarker in gynaecological oncology. The purpose of this study was to evaluate serum HE4 as a biomarker for high-risk phenotypes in a population-based endometrial cancer cohort. Methods Peri-operative serum HE4 and CA125 were measured in 373 patients identified from the prospective Australian National Endometrial Cancer Study (ANECS). HE4 and CA125 were quantified on the ARCHITECT instrument in a clinically accredited laboratory. Receiver operator curves (ROC), Spearman rank correlation coefficient, and chi-squared and Mann–Whitney tests were used for statistical analysis. Survival analysis was performed using Kaplan–Meier and Cox multivariate regression analyses. Results Median CA125 and HE4 levels were higher in stage III and IV tumours (p < 0.001) and in tumours with outer-half myometrial invasion (p < 0.001). ROC analysis demonstrated that HE4 (area under the curve (AUC) = 0.76) was a better predictor of outer-half myometrial invasion than CA125 (AUC = 0.65), particularly in patients with low-grade endometrioid tumours (AUC 0.77 vs 0.64 for CA125). Cox multivariate analysis demonstrated that elevated HE4 was an independent predictor of recurrence-free survival (HR = 2.40, 95% CI 1.19–4.83, p = 0.014) after adjusting for stage and grade of disease, particularly in the endometrioid subtype (HR = 2.86, 95% CI 1.25–6.51, p = 0.012). Conclusion These findings demonstrate the utility of serum HE4 as a prognostic biomarker in endometrial cancer in a large, population-based study. In particular they highlight the utility of HE4 for pre-operative risk stratification to identify high-risk patients within low-grade endometrioid endometrial cancer patients who might benefit from lymphadenectomy.

Architecture for a free subjectivity

In October 2012, Simone presented her book Architecture for a Free Subjectivity to the University of Michigan, Taubman College of Architecture and Urban Planning. This book explores the architectural significance of Deleuze’s philosophy of subjectivization, and Guattari’s overlooked dialogue on architecture and subjectivity. In doing so, it proposes that subjectivity is no longer the exclusive provenance of human beings, but extends to the architectural, the cinematic, the erotic, and the political. It defines a new position within the literature on Deleuze and architecture, while highlighting the neglected issue of subjectivity in contemporary discussion.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.