Feasibility of agent-based modelling of articular cartilage including a conceptual representation of its structure

Articular cartilage is a complex structure with an architecture in which fluid-swollen proteoglycans constrained within a 3D network of collagen fibrils. Because of the complexity of the cartilage structure, the relationship between its mechanical behaviours at the macroscale level and its components at the micro-scale level are not completely understood. The research objective in this thesis is to create a new model of articular cartilage that can be used to simulate and obtain insight into the micro-macro-interaction and mechanisms underlying its mechanical responses during physiological function. The new model of articular cartilage has two characteristics, namely: i) not use fibre-reinforced composite material idealization ii) Provide a framework for that it does probing the micro mechanism of the fluid-solid interaction underlying the deformation of articular cartilage using simple rules of repartition instead of constitutive / physical laws and intuitive curve-fitting. Even though there are various microstructural and mechanical behaviours that can be studied, the scope of this thesis is limited to osmotic pressure formation and distribution and their influence on cartilage fluid diffusion and percolation, which in turn governs the deformation of the compression-loaded tissue. The study can be divided into two stages. In the first stage, the distributions and concentrations of proteoglycans, collagen and water were investigated using histological protocols. Based on this, the structure of cartilage was conceptualised as microscopic osmotic units that consist of these constituents that were distributed according to histological results. These units were repeated three-dimensionally to form the structural model of articular cartilage. In the second stage, cellular automata were incorporated into the resulting matrix (lattice) to simulate the osmotic pressure of the fluid and the movement of water within and out of the matrix; following the osmotic pressure gradient in accordance with the chosen rule of repartition of the pressure. The outcome of this study is the new model of articular cartilage that can be used to simulate and study the micromechanical behaviours of cartilage under different conditions of health and loading. These behaviours are illuminated at the microscale level using the socalled neighbourhood rules developed in the thesis in accordance with the typical requirements of cellular automata modelling. Using these rules and relevant Boundary Conditions to simulate pressure distribution and related fluid motion produced significant results that provided the following insight into the relationships between osmotic pressure gradient and associated fluid micromovement, and the deformation of the matrix. For example, it could be concluded that: 1. It is possible to model articular cartilage with the agent-based model of cellular automata and the Margolus neighbourhood rule. 2. The concept of 3D inter connected osmotic units is a viable structural model for the extracellular matrix of articular cartilage. 3. Different rules of osmotic pressure advection lead to different patterns of deformation in the cartilage matrix, enabling an insight into how this micromechanism influences macromechanical deformation. 4. When features such as transition coefficient were changed, permeability (representing change) is altered due to the change in concentrations of collagen, proteoglycans (i.e. degenerative conditions), the deformation process is impacted. 5. The boundary conditions also influence the relationship between osmotic pressure gradient and fluid movement at the micro-scale level. The outcomes are important to cartilage research since we can use these to study the microscale damage in the cartilage matrix. From this, we are able to monitor related diseases and their progression leading to potential insight into drug-cartilage interaction for treatment. This innovative model is an incremental progress on attempts at creating further computational modelling approaches to cartilage research and other fluid-saturated tissues and material systems.

Feasibility of using telecommunications technology in a Cardiac-Diabetes Self-Management Program

Background: Evidence demonstrates self-management programs are an effective approach to assist patients with chronic diseases such as type 2 diabetes or cardiac conditions to modify their lifestyle for better managing their conditions. Using information technology (IT) has great potential to support self-management programs and assist patients to fulfill their goals in managing their conditions more efficiently and effectively. Examples of different types of technology used in self-management programs that have limited research support include: text messages, telephone followup, web-based programs, and other internet-assisted education. But little is known about the applicability and feasiability of different forms of technology for patients with chronic diseases such as those with type 2 diabetes and critical cardiac conditions. Furthermore, although there is some evidence of the benefits of using IT in supporting self-management programs, further research on the use of IT in such programs is recommended. Objective: To develop and pilot test an integrated Cardiac- Diabetes Self-Management Program (CDSMP) incorporating telephone and text-message follow-up. Methods: A pilot study using randomised controlled trial is conducted in the coronary care unit (CCU) in a Brisbane metropolitan hospital in Australia to collect data on patients with type 2 diabetes admitted to CCU. The main outcomes included self-efficacy levels, knowledge, and quality of life. Results: Initial results reveal that patients with diabetes admitted to the CCU in the experimental group did improve their self-efficacy, and knowledge levels. Acknowledgements: This Project is funded by QUT Early Career Researcher Research Grant

The emerging role of the Board of Directors in enterprise business technology governance

In an increasingly business technology (BT) dependent world, the impact of the extraordinary changes brought about by the nexus of mobile and cloud technologies, social media and big data is increasingly being felt in the board room. As leaders of enterprises of every type and size, board directors can no longer afford to ignore, delegate or avoid BT-related decisions. Competitive, financial and reputational risk is increased if boards fail to recognize their role in governing technology as an asset and in removing barriers to improving enterprise business technology governance (EBTG). Directors’ awareness of the need for EBTG is increasing. However, industry research shows that board level willingness to rectify the gap between awareness and action is very low or non-existent. This literature review-based research identifies barriers to EBTG effectiveness. It provides a practical starting point for board analysis. We offer four outcomes that boards might focus on to ensure the organizations they govern are not left behind by those led by the upcoming new breed of technology-savvy leaders. Most extant research looks backward for examples, examining data pre-2010, the time when a tipping point in the personal and business use of multimedia and mobile-internet devices significantly deepened the impacts of the identified nexus technology forces, and began rapidly changing the way many businesses engage with their customers, employees and stakeholders. We situate our work amidst these nexus forces, discuss the board’s role in EBTG in this context, and modernize current definitions of enterprise technology governance. The primary limitation faced is the lack of scholarly research relating to EBTG in the rapidly changing digital economy. Although we have used recent (2011 - 2013) industry surveys, the volume of these surveys and congruence across them is significant in terms of levels of increased awareness and calls for increased board attention and competency in EBTG and strategic information use. Where possible we have used scholarly research to illustrate or discuss industry findings.

A hydrogen/methane sensor based on niobium tungsten oxide nanorods synthesised by hydrothermal method

An investigation on hydrogen and methane sensing performance of hydrothermally formed niobium tungsten oxide nanorods employed in a Schottky diode structure is presented herein. By implementing tungsten into the surface of the niobium lattice, we create Nb5+ and W5+ oxide states and an abundant number of surface traps, which can collect and hold the adsorbate charge to reinforce a greater bending of the energy bands at the metal/oxide interface. We show experimentally, that extremely large voltage shifts can be achieved by these nanorods under exposure to gas at both room and high temperatures and attribute this to the strong accumulation of the dipolar charges at the interface via the surface traps. Thus, our results demonstrate that niobium tungsten oxide nanorods can be implemented for gas sensing applications, showing ultra-high sensitivities.

Pt/Nanostructured RuO2/SiC Schottky Diode based hydrogen gas sensors

In this paper, we report the development of novel Pt/nanostructured RuO2/SiC Schottky diode based sensors for hydrogen gas applications. The nanostructured ruthenium oxide thin films were deposited on SiC substrates using radio frequency sputtering technique. Scanning electron microscopy revealed the sputtered RuO2 layer consists of nano-cubular structures with dimensions ranging between 10 and 50 nm. X-ray diffraction confirmed the presence of tetragonal ruthenium (IV) oxide, with preferred orientation along the (101) lattice plane. The current-voltage characteristics of the sensors were investigated towards hydrogen gas in synthetic air at different temperatures from 25 °C to 240 °C. The dynamic responses of the sensors were studied at an optimum temperature of 240 °C and a voltage shift of 304 mV was recorded toward 1% hydrogen gas.

Multidisciplinary team approach for a peer-support based cardiac-diabetes self-management program

Background: Cardiac patients with diabetes are at higher readmission rates (22%) compared to only 6% for those patients without diabetes. Evidence shows benefits of peer support and using information technology to improve chronic illness and achieve better health outcomes. However limited evidence suggests that cardiac or diabetes self-management programs incorporating peer supporters (patients with similar conditions) or telephone and text-messaging, have improved health outcomes and reduce health care utilisations. A multidisciplinary research team approach is crucial to accommodate the complex aspects of delivering intervention programs for these at-risk patients. However, challenges such as the inconsistency in significance of key concepts across research fields, as well as practical and operational issues within different contexts are often experienced. Aims: To develop an effective multidisciplinary team approach to deliver a peer support based cardiac-diabetes self-management program incorporating the preparation of lay personnel to provide telephone and text-messaging follow up support. Methods: The approach was used for a multidisciplinary project using randomised controlled trial. Results: The findings from multidisciplinary team approach reveal the feasibility of a Peer support based cardiac-diabetes self-management program.

Hydrogen Gas Sensor Based on Highly Ordered Polyaniline/Multiwall Carbon Nanotubes Composite

In this work, the structural and gas sensing properties of an electropolymerized, polyaniline (PANI)/multiwall carbon nanotube (MWNT) composite based surface acoustic wave (SAW) sensor are reported. Thin films made of PANI nanofibers were deposited onto 36 lithium tantalate (LiTaO3) SAW transducers using electropolymerization and were subsequently dedoped. Scanning electron microscopy (SEM) revealed the compact growth of the composites which is much denser than that of PANI nanofibers. The PANI/MWNT composite based SAW sensor was then exposed to different concentrations of hydrogen (H2) gas at room temperature with a demonstrated electrical response.

Pt/Nanograined ZnO/SiC Schottky diode based hydrogen and propene sensor

A nanostructured Schottky diode was fabricated to sense hydrogen and propene gases in the concentration range of 0.06% to 1%. The ZnO sensitive layer was deposited on SiC substrate by pulse laser deposition technique. Scanning electron microscopy and X-ray diffraction characterisations revealed presence of wurtzite structured ZnO nanograins grown in the direction of (002) and (004). The nanostructured diode was investigated at optimum operating temperature of 260 °C. At a constant reverse current of 1 mA, the voltage shifts towards 1% hydrogen and 1% propene were measured as 173.3 mV and 191.8 mV, respectively.

Integrating collaborative filtering and matching-based search for product recommendation

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and thus help them in making good decisions about which product to buy from the vast number of product choices available to them. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.