Two novel numerical methods for solving the two-dimensional fractional Fitzhugh-Nagumo-monodomain model

Fractional mathematical models represent a new approach to modelling complex spatial problems in which there is heterogeneity at many spatial and temporal scales. In this paper, a two-dimensional fractional Fitzhugh-Nagumo-monodomain model with zero Dirichlet boundary conditions is considered. The model consists of a coupled space fractional diffusion equation (SFDE) and an ordinary differential equation. For the SFDE, we first consider the numerical solution of the Riesz fractional nonlinear reaction-diffusion model and compare it to the solution of a fractional in space nonlinear reaction-diffusion model. We present two novel numerical methods for the two-dimensional fractional Fitzhugh-Nagumo-monodomain model using the shifted Grunwald-Letnikov method and the matrix transform method, respectively. Finally, some numerical examples are given to exhibit the consistency of our computational solution methodologies. The numerical results demonstrate the effectiveness of the methods.

Hepatitis C : a socio-cultural perspective on the effects of a new virus on a community’s health

Since the emergence of diagnostic medical tests in Australia in 1990, hepatitis C (HCV) has been shown to account for over 90 percent of all non-A non-B hepatitis, revealing it to be a widespread and major public health problem. The diagnosis of HCV involves a diverse range of issues for affected persons, introducing identity and lifestyle changes, which are commonly articulated through psychological concepts. In this article we argue that it is important to examine the broader social and cultural contexts that contribute to the experiences of persons affected by HCV. The thematic analysis of qualitative data from six individuals diagnosed with HCV is included to exemplify some of the processes that are involved in the changing identity of a person following a positive diagnosis. The theoretical framework for the interpretation of these processes is interpretive interactionism. In this research, we are attempting to extend the understanding of the effects of HCV diagnoses beyond internal, psychological processes by examining how these diagnoses transform some of the processes of self-formation and expression. The participants’ experiences indicate that there are at least four dimensions of self that were significant to their changing sense of self: relationship of self to others; the emotional self; self-stories and identity; and self-scrutiny and relationships. We conclude that a socio-cultural perspective contributes to the explanation of the transition period following a HCV-positive diagnosis and the redefinition of self towards a HCV status.

Mapping Multiple Literacies: An Introduction to Deleuzian Literacy Studies

Mapping Multiple Literacies brings together the latest theory and research in the fields of literacy study and European philosophy, Multiple Literacies Theory (MLT) and the philosophical work of Gilles Deleuze. It frames the process of becoming literate as a fluid process involving multiple modes of presentation, and explains these processes in terms of making maps of our social lives and ways of doing things together. For Deleuze, language acquisition is a social activity of which we are a part, but only one part amongst many others. Masny and Cole draw on Deleuze's thinking to expand the repertoires of literacy research and understanding. They outline how we can understand literacy as a social activity and map the ways in which becoming literate may take hold and transform communities. The chapters in this book weave together theory, data and practice to open up a creative new area of literacy studies and to provoke vigorous debate about the sociology of literacy.

Preparation and characterization of TiO2/acid leached serpentinite tailings composites and their photocatalytic reduction of Chromium(VI)

Composite TiO2/acid leached serpentine tailings (AST) were synthesized through the hydrolysis–deposition method and characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energydispersive X-ray spectrometry (EDS), Fourier-transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and surface area measurement (BET). The XRD analysis showed that TiO2 coated on the surface of acid leached serpentine tailings was mixed crystal phases of rutile and anatase, the grain size of which is 10–30 nm. SEM, TEM, and EDS analysis exhibited that nano-TiO2 particles were deposited on the surface and internal cavities of acid leaching serpentine tailings. The XPS and FT-IR analysis demonstrated that the coating process of TiO2 on AST was a physical adsorption process. The large specific surface area, porous structure, and plentiful surface hydroxyl group of TiO2/AST composite resulted in the high adsorption capacity of Cr(VI). The experimental results demonstrated that initial concentration of Cr(VI), the amount of the catalyst, and pH greatly influenced the removal efficiency of Cr(VI). The removal kinetics of Cr(VI) at a relative low initial concentration was fitted well with Langmuir–Hinshelwood kinetics model with R2 value of about unity. The asprepared composites exhibited strong adsorption and photocatalytic capacity for the removal of Cr(VI), and the possible photocatalytic reduction mechanism was studied. The photodecomposition of Cr(VI) was as high as 95% within 2 h, and the reusability of the photocatalysis was proven.

Beijing : a media capital in the making

In the two decades since 2001, when China joined the World Trade Organization,the commercialization of the Chinese media has become a significant force. With the increasing demand for original content and a possible “cultural trade deficit” in media content, there has been much discussion about agglomeration and clustering. Beijing, as the national media centre of China, has witnessed the process of media agglomeration while facing the problem of cultural export during the commercialization of the media. Michael Curtin’s idea of media capital, which sees it as absorbing media resources and personnel and exporting media products transnationally, provides a dynamic perspective on understanding media agglomeration and dispersion under different political social and cultural circumstances. Hence, the question of whether Beijing will transform into a transnational media capital is worth studying in order to observe and comprehend China’s media industry in transition. Drawing on Michael Curtin’s three media capital trajectories, this paper interprets tensions and challenges generated in the process of media industry agglomeration and growth in Beijing. Emphasis is placed on the third trajectory, socio-cultural variation.

Online calibration of stereo rigs for long-term autonomy

Stereo-based visual odometry algorithms are heavily dependent on an accurate calibration of the rigidly fixed stereo pair. Even small shifts in the rigid transform between the cameras can impact on feature matching and 3D scene triangulation, adversely affecting pose estimates and applications dependent on long-term autonomy. In many field-based scenarios where vibration, knocks and pressure change affect a robotic vehicle, maintaining an accurate stereo calibration cannot be guaranteed over long periods. This paper presents a novel method of recalibrating overlapping stereo camera rigs from online visual data while simultaneously providing an up-to-date and up-to-scale pose estimate. The proposed technique implements a novel form of partitioned bundle adjustment that explicitly includes the homogeneous transform between a stereo camera pair to generate an optimal calibration. Pose estimates are computed in parallel to the calibration, providing online recalibration which seamlessly integrates into a stereo visual odometry framework. We present results demonstrating accurate performance of the algorithm on both simulated scenarios and real data gathered from a wide-baseline stereo pair on a ground vehicle traversing urban roads.

Generating transgenic banana (cv. Sukali Ndizi) resistant to Fusarium Wilt

Banana is one of the world’s most popular fruit crops and Sukali Ndizi is the most popular dessert banana in the East African region. Like other banana cultivars, Sukali Ndizi is threatened by several constraints, of which the Fusarium wilt disease is the most destructive. Fusarium wilt is caused by a soil-borne fungus, Fusarium oxysporum f.sp. cubense (Foc). No effective control strategy currently exists for this disease and although disease resistance exists in some banana cultivars, introducing resistance into commercial cultivars by conventional breeding is difficult because of low fertility. Considering that conventional breeding generates hybrids with additional undesirable traits, transformation is the most suitable way of introducing resistance in the banana genome. The success of this strategy depends on the availability of genes for genetic transformation. Recently, a novel strategy involving the expression of anti-apoptosis genes in plants was shown to result in resistance against several necrotrophic fungi, including Foc race 1 in banana cultivar Lady Finger. This thesis explores the potential of a plant-codon optimised nematode anti-apoptosis gene (Mced9) to provide resistance against Foc race 1 in dessert banana cultivar Sukali Ndizi. Agrobacterium-mediated transformation was used to transform embryogenic cell suspension of Sukali Ndizi with plant expression vector pYC11, harbouring maize ubiquitin promoter driven Mced9 gene and nptII as a plant selection marker. A total of 42 independently transformed lines were regenerated and characterized. The transgenic lines were multiplied, infected and evaluated for resistance to Foc race 1 in a small pot bioassay. The pathogenicity of the Ugandan Foc race 1 isolate used for infection was pre-determined and the spore concentration was standardised for consistent infection and symptom development. This process involved challenging tissue culture plants of Sukali Ndizi, a Foc race 1 susceptible cultivar and Nakinyika, an East African Highland cultivar known to be resistant to Foc race 1, with Fusarium inoculum and observing external and internal disease symptom development. Rhizome discolouration symptoms were the best indicators of Fusarium wilt with yellowing being an early sign of disease. Three transgenic lines were found to show significantly less disease severities compared to the wild-type control plants after 13 weeks of infection, indicating that Mced9 has the potential to provide tolerance to Fusarium wilt in Sukali Ndizi.

Robust image hash functions using higher order spectra

Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

Essays on volatility and liquidity in financial markets

The price formation of financial assets is a complex process. It extends beyond the standard economic paradigm of supply and demand to the understanding of the dynamic behavior of price variability, the price impact of information, and the implications of trading behavior of market participants on prices. In this thesis, I study aggregate market and individual assets volatility, liquidity dimensions, and causes of mispricing for US equities over a recent sample period. How volatility forecasts are modeled, what determines intradaily jumps and causes changes in intradaily volatility and what drives the premium of traded equity indexes? Are they induced, for example, by the information content of lagged volatility and return parameters or by macroeconomic news, changes in liquidity and volatility? Besides satisfying our intellectual curiosity, answers to these questions are of direct importance to investors developing trading strategies, policy makers evaluating macroeconomic policies and to arbitrageurs exploiting mispricing in exchange-traded funds. Results show that the leverage effect and lagged absolute returns improve forecasts of continuous components of daily realized volatility as well as jumps. Implied volatility does not subsume the information content of lagged returns in forecasting realized volatility and its components. The reported results are linked to the heterogeneous market hypothesis and demonstrate the validity of extending the hypothesis to returns. Depth shocks, signed order flow, the number of trades, and resiliency are the most important determinants of intradaily volatility. In contrast, spread shock and resiliency are predictive of signed intradaily jumps. There are fewer macroeconomic news announcement surprises that cause extreme price movements or jumps than those that elevate intradaily volatility. Finally, the premium of exchange-traded funds is significantly associated with momentum in net asset value and a number of liquidity parameters including the spread, traded volume, and illiquidity. The mispricing of industry exchange traded funds suggest that limits to arbitrage are driven by potential illiquidity.

CUOL – "See You Online" : teaching strategies for digital literacy practices in the English curriculum

Literacy educator Kathy Mills, observes that creating multimodal and digital texts is an essential part of the national English curriculum in Australia. Here, she presents five practical and engaging ways to transform conventional writing tasks in a digital world.

Fabrication and characterisation of graphene oxide-epoxy nanocomposite

Adequate amount of graphene oxide (GO) was firstly prepared by oxidation of graphite and GO/epoxy nanocomposites were subsequently prepared by typical solution mixing technique. X-ray diffraction (XRD) pattern, X-ray photoelectron (XPS), Raman and Fourier transform infrared (FTIR) spectroscopy indicated the successful preparation of GO. Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) images of the graphite oxide showed that they consist of a large amount of graphene oxide platelets with a curled morphology containing of a thin wrinkled sheet like structure. AFM image of the exfoliated GO signified that the average thickness of GO sheets is ~1.0 nm which is very similar to GO monolayer. Mechanical properties of as prepared GO/epoxy nanocomposites were investigated. Significant improvements in both Young’s modulus and tensile strength were observed for the nanocomposites at very low level of GO loading. The Young’s modulus of the nanocomposites containing 0.5 wt% GO was 1.72 GPa, which was 35 % higher than that of the pure epoxy resin (1.28 GPa). The effective reinforcement of the GO based epoxy nanocomposites can be attributed to the good dispersion and the strong interfacial interactions between the GO sheets and the epoxy resin matrices.

Detection of dugongs from unmanned aerial vehicles

Monitoring and estimation of marine populations is of paramount importance for the conservation and management of sea species. Regular surveys are used to this purpose followed often by a manual counting process. This paper proposes an algorithm for automatic detection of dugongs from imagery taken in aerial surveys. Our algorithm exploits the fact that dugongs are rare in most images, therefore we determine regions of interest partially based on color rarity. This simple observation makes the system robust to changes in illumination. We also show that by applying the extended-maxima transform on red-ratio images, submerged dugongs with very fuzzy edges can be detected. Performance figures obtained here are promising in terms of degree of confidence in the detection of marine species, but more importantly our approach represents a significant step in automating this type of surveys.

High altitude stereo visual odometry

Stereo visual odometry has received little investigation in high altitude applications due to the generally poor performance of rigid stereo rigs at extremely small baseline-to-depth ratios. Without additional sensing, metric scale is considered lost and odometry is seen as effective only for monocular perspectives. This paper presents a novel modification to stereo based visual odometry that allows accurate, metric pose estimation from high altitudes, even in the presence of poor calibration and without additional sensor inputs. By relaxing the (typically fixed) stereo transform during bundle adjustment and reducing the dependence on the fixed geometry for triangulation, metrically scaled visual odometry can be obtained in situations where high altitude and structural deformation from vibration would cause traditional algorithms to fail. This is achieved through the use of a novel constrained bundle adjustment routine and accurately scaled pose initializer. We present visual odometry results demonstrating the technique on a short-baseline stereo pair inside a fixed-wing UAV flying at significant height (~30-100m).

Thermal treatment of natural goethite : thermal transformation and physical properties

XRD (X-ray diffraction), XRF (X-ray fluorescence), TG (thermogravimetry), FT-IES (Fourier transform infrared emission spectroscopy), FESEM (field emission scanning electron microscope), TEM (transmission electron microscope) and nitrogen–adsorption–desorption analysis were used to characterize the composition and thermal evolution of the structure of natural goethite. The in situ FT-IES demonstrated the start temperature (250 °C) of the transformation of natural goethite to hematite and the thermodynamic stability of protohematite between 250 and 600 °C. The heated products showed a topotactic relationship to the original mineral based on SEM analysis. Finally, the nitrogen–adsorption–desorption isotherm provided the variation of surface area and pore size distribution as a function of temperature. The surface area displayed a remarkable increase up to 350 °C, and then decreased above this temperature. The significant increase in surface area was attributed to the formation of regularly arranged slit-shaped micropores running parallel to elongated direction of hematite microcrystal. The main pore size varied from 0.99 nm to 3.5 nm when heating temperature increases from 300 to 400 °C. The hematite derived from heating goethite possesses high surface area and favors the possible application of hematite as an adsorbent as well as catalyst carrier.

A hybrid genetic algorithm for the minimum interconnection cut problem

In the real world there are many problems in network of networks (NoNs) that can be abstracted to a so-called minimum interconnection cut problem, which is fundamentally different from those classical minimum cut problems in graph theory. Thus, it is desirable to propose an efficient and effective algorithm for the minimum interconnection cut problem. In this paper we formulate the problem in graph theory, transform it into a multi-objective and multi-constraint combinatorial optimization problem, and propose a hybrid genetic algorithm (HGA) for the problem. The HGA is a penalty-based genetic algorithm (GA) that incorporates an effective heuristic procedure to locally optimize the individuals in the population of the GA. The HGA has been implemented and evaluated by experiments. Experimental results have shown that the HGA is effective and efficient.