Interactive image manipulation for surgical planning

The Australian e-Health Research Centre in collaboration with the Queensland University of Technology's Paediatric Spine Research Group is developing software for visualisation and manipulation of large three-dimensional (3D) medical image data sets. The software allows the extraction of anatomical data from individual patients for use in preoperative planning. State-of-the-art computer technology makes it possible to slice through the image dataset at any angle, or manipulate 3D representations of the data instantly. Although the software was initially developed to support planning for scoliosis surgery, it can be applied to any dataset whether obtained from computed tomography, magnetic resonance imaging or any other imaging modality.

An examination of the relationships between lifestyle factors and mental health among Australian midlife and older women

Background It is well known that lifestyle factors including overweight/obesity, physical inactivity, smoking and alcohol use are largely related with morbidity and mortality of chronic diseases including diabetes and cardiovascular diseases. The effect of lifestyle factors on people’s mental health who have a chronic disease is less defined in the research. The World Health Organisation has defined health as “a state of complete physical, mental and social well-being”. It is important, therefore to develop an understanding of the relationships between lifestyle and mental health as this may have implications for maximising the efficacy of health promotion in people with chronic diseases. Objectives The overall aim of the research was to examine the relationships between lifestyle factors and mental health among Australian midlife and older women. Methodology The current research measured four lifestyle factors including weight status, physical activity, smoking and alcohol use. Three interconnecting studies were undertaken to develop a comprehensive understanding of the relationships between lifestyle factors and mental health. Study 1 investigated the longitudinal effect of lifestyle factors on mental health by using midlife and older women randomly selected from the community. Study 2 adopted a cross-sectional design, and compared the effect of lifestyle factors on mental health between midlife and older women with and without diabetes. Study 3 examined the mediating effect of self-efficacy in the relationships between lifestyle factors and mental health among midlife and older women with diabetes. A questionnaire survey was chosen as the means to gather information, and multiple linear regression analysis was conducted as the primary statistical approach. Results The research showed that the four lifestyle factors including weight status, physical activity, smoking and alcohol use did impact on mental health among Australian midlife and older women. First, women with a higher BMI had lower levels of mental health than women with normal weight, but as women age, the mental health of women who were overweight and obese becomes better than that of women with normal weight. Second, women who were physically active had higher levels of mental health than those who were not. Third, smoking adversely impacted on women’s mental health. Finally, those who were past-drinkers had less anxiety symptoms than women who were non-drinkers as they age. Women with diabetes appeared to have lower levels of mental health compared to women without. However, the disparities of mental health between two groups were confounded by low levels of physical activity and co-morbidities. This finding underlines the effect of physical activity on women’s mental health, and highlights the potential of reducing the gap of mental health by promoting physical activity. In addition, self-efficacy was shown to be the mediator of the relationships between BMI, physical activity and depression, suggesting that enhancing people’s self-efficacy may be useful for mental health improvement. Conclusions In conclusion, Australian midlife and older women who live with a healthier lifestyle have higher levels of mental health. It is suggested that strategies aiming to improve people’s mental health may be more effective if they focus on enhancing people’s self-efficacy levels. This study has implications to both health education and policy development. It indicates that health professionals may need to consider clients’ mental health as an integrated part of lifestyle changing process. Furthermore, given that lifestyle factors impact on both physical and mental health, lifestyle modification should continue to be the focus of policy development.

Nursing Sans Frontieres: A Three Year Case Study of Multi-State Registration of Support Nursing Practice Using Information Technology

Objective: To highlight the registration issues for nurses who wish to practice nationally, particularly those practicing within the telehealth sector. Design: As part of a national clinical research study, applications were made to every state and territory for mutual recognition of nursing registration and fee waiver for telenursing cross boarder practice for a period of three years. These processes are described using a case study approach. Outcome: The aim of this case study was to achieve registration in every state and territory of Australia without paying multiple fees by using mutual recognition provisions and the cross-border fee waiver policy of the nurse regulatory authorities in order to practice telenursing. Results: Mutual recognition and fee waiver for cross-border practice was granted unconditionally in two states: Victoria (Vic) and Tasmania (Tas), and one territory: the Northern Territory (NT). The remainder of the Australian states and territories would only grant temporary registration for the period of the project or not at all, due to policy restrictions or nurse regulatory authority (NRA) Board decisions. As a consequence of gaining fee waiver the annual cost of registration was a maximum of $145 per annum as opposed to the potential $959 for initial registration and $625 for annual renewal. Conclusions: Having eight individual nurses Acts and NRAs for a population of 265,000 nurses would clearly indicate a case for over regulation in this country. The structure of regulation of nursing in Australia is a barrier to the changing and evolving role of nurses in the 21st century and a significant factor when considering workforce planning.

A comprehensive literature review of the pelvis and the lower extremity digital human models under quasi-static conditions

Finite Element Modeling (FEM) has become a vital tool in the automotive design and development processes. FEM of the human body is a technique capable of estimating parameters that are difficult to measure in experimental studies with the human body segments being modeled as complex and dynamic entities. Several studies have been dedicated to attain close-to-real FEMs of the human body (Pankoke and Siefert 2007; Amann, Huschenbeth et al. 2009; ESI 2010). The aim of this paper is to identify and appraise the state of-the art models of the human body which incorporate detailed pelvis and/or lower extremity models. Six databases and search engines were used to obtain literature, and the search was limited to studies published in English since 2000. The initial search results identified 636 pelvis-related papers, 834 buttocks-related papers, 505 thigh-related papers, 927 femur-related papers, 2039 knee-related papers, 655 shank-related papers, 292 tibia-related papers, 110 fibula-related papers, 644 ankle related papers, and 5660 foot-related papers. A refined search returned 100 pelvis-related papers, 45 buttocks related papers, 65 thigh-related papers, 162 femur-related papers, 195 kneerelated papers, 37 shank-related papers, 80 tibia-related papers, 30 fibula-related papers and 102 ankle-related papers and 246 foot-related papers. The refined literature list was further restricted by appraisal against a modified LOW appraisal criteria. Studies with unclear methodologies, with a focus on populations with pathology or with sport related dynamic motion modeling were excluded. The final literature list included fifteen models and each was assessed against the percentile the model represents, the gender the model was based on, the human body segment/segments included in the model, the sample size used to develop the model, the source of geometric/anthropometric values used to develop the model, the posture the model represents and the finite element solver used for the model. The results of this literature review provide indication of bias in the available models towards 50th percentile male modeling with a notable concentration on the pelvis, femur and buttocks segments.

Integrated approach for HP-LNG pump diagnosis and prognostics based on health state probability estimation

This paper presents an innovative prognostics model based on health state probability estimation embedded in the closed loop diagnostic and prognostic system. To employ an appropriate classifier for health state probability estimation in the proposed prognostic model, the comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault levels of three faults in HP-LNG pump. Two sets of impeller-rubbing data were employed for the prediction of pump remnant life based on estimation of discrete health state probability using an outstanding capability of SVM and a feature selection technique. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Green Exercise in the UK Countryside: Effects on Health and Psychological Well-being and Implications for Policy and Planning

There is evidence that contact with the natural environment and green space promotes good health. It is also well known that participation in regular physical activity generates physical and psychological health benefits. The authors have hypothesised that ‘green exercise’ will improve health and psychological well-being, yet few studies have quantified these effects. This study measured the effects of 10 green exercise case studies (including walking, cycling, horse-riding, fishing, canal-boating and conservation activities) in four regions of the UK on 263 participants. Even though these participants were generally an active and healthy group, it was found that green exercise led to a significant improvement in self-esteem and total mood disturbance (with anger-hostility, confusion-bewilderment, depression-dejection and tension-anxiety all improving post-activity). Self-esteem and mood were found not to be affected by the type, intensity or duration of the green exercise, as the results were similar for all 10 case studies. Thus all these activities generated mental health benefits, indicating the potential for a wider health and well-being dividend from green exercise. Green exercise thus has important implications for public and environmental health, and for a wide range of policy sectors.

Towards a comprehensive and integrated knowledge-based urban development model : status quo and directions

Incorporating knowledge based urban development (KBUD) strategies in the urban planning and development process is a challenging and complex task due to the fragmented and incoherent nature of the existing KBUD models. This paper scrutinizes and compares these KBUD models with an aim of identifying key and common features that help in developing a new comprehensive and integrated KBUD model. The features and characteristics of the existing KBUD models are determined through a thorough literature review and the analysis reveals that while these models are invaluable and useful in some cases, lack of a comprehensive perspective and absence of full integration of all necessary development domains render them incomplete as a generic model. The proposed KBUD model considers all central elements of urban development and sets an effective platform for planners and developers to achieve more holistic development outcomes. The proposed model, when developed further, has a high potential to support researchers, practitioners and particularly city and state administrations that are aiming to a knowledge-based development.

Strategic planning in a non profit organistion : valuing the process

Non-profit organisations by their very nature are staffed by a variety of different people with a range of backgrounds, experiences and reasons for participation. These differences can lead to “distancing” of certain groups and with little time or money for boundary spanning the organisation can find itself in a fractured state that hampers not just its goal realisation, but its goal determination. Strategic planning is often seen as an expensive, time consuming process that many smaller non-profit organisations can little afford to indulge in. In addition, the ruling elite, whether historical or professional may view the process as unnecessary or threatening. However, strategic planning can offer processes and potential outcomes that non profit organisations can not afford to ignore. This paper provides an analysis through one case study involving a non-profit, health related organisation that moved through a process of strategic planning that ultimately encouraged development and group cohesion through goal identification and determination as well as strategy formulation. The results indicate the importance of valuing the strategic planning process itself rather than the form it takes. Challenging the rulership of the historical or professional elite can be difficult in a non-profit organisation, but diversity of involvement rather than uniformity proved to be a successful strategy. Organisational cohesion through consensus building was the ultimate outcome.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

From 'what' to 'how' : capacity building in health promotion for HIV/AIDS prevention in the Solomon Islands

This paper describes a capacity building process undertaken within the HIV/AIDS prevention project of the Adventist Development and Relief Agency (ADRA) in the Solomon Islands. ADRA HIV/AIDS has recently reoriented its project structure, moving beyond its awareness raising approach to incorporate health promotion frameworks, theories, strategies and assumptions. These have been used to inform project practice in project planning, delivery and evaluation. This paper shares what has worked and not worked in the capacity building process, including a project evaluation of the initial HIV/AIDS awareness raising project and the application of a number of capacity building strategies, including utilising a volunteer Australian Youth Ambassador for Development (AYAD) funded by the Australian Agency for International Development (AusAID). Existing and new projects are outlined. The underlying theme is that any capacity building exercise must include structural support (e.g. management, national frameworks) to ensure the incorporation of new initiatives and approaches. With time this enables ownership by counterparts and external partnerships to develop. The presence of an AYAD volunteer has been an effective strategy to achieve this. Reflections from the evaluators, the AYAD volunteer and the HIV/AIDS team are included.

Machine prognostics based on health state estimation using SVM

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

Archival analysis of enterprise resource planning systems : the current state and future directions

Research on Enterprise Resource Planning (ERP) Systems is becoming a well-established research theme in Information Systems (IS) research. Enterprise Resource Planning Systems, given its unique differentiations with other IS applications, have provided an interesting backdrop to test and re-test some of the key and fundamental concepts in IS. While some researchers have tested well-established concepts of technology acceptance, system usage and system success in the context of ERP Systems, others have researched how new paradigms like cloud computing and social media integrate with ERP Systems. Moreover, ERP Systems provided the context for cross disciplinary research such as knowledge management, project management and business process management research. Almost after two-decades since its inception in IS research, this paper provides a critique of 198 papers published on ERP Systems since 2006-2012. We observe patterns on ES research, provide comparisons to past studies and provide future research directions.

Bearing fault prognosis based on health state probability estimation

In condition-based maintenance (CBM), effective diagnostic and prognostic tools are essential for maintenance engineers to identify imminent fault and predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedule of production if necessary. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of bearings based on health state probability estimation and historical knowledge embedded in the closed loop diagnostics and prognostics system. The technique uses the Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation process to provide long term prediction. To validate the feasibility of the proposed model, real life fault historical data from bearings of High Pressure-Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life (RUL). The results obtained were very encouraging and showed that the proposed prognosis system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.