Application of Geographic Modeling Techniques to Quantify Spatial Access to Health Services Before and After an Acute Cardiac Event: The Cardiac ARIA Project

Background: Access to cardiac services is essential for appropriate implementation of evidence-based therapies to improve outcomes. The Cardiac Accessibility and Remoteness Index for Australia (Cardiac ARIA) aimed to derive an objective, geographic measure reflecting access to cardiac services. Methods: An expert panel defined an evidence-based clinical pathway. Using Geographic Information Systems (GIS), a numeric/alpha index was developed at two points along the continuum of care. The acute category (numeric) measured the time from the emergency call to arrival at an appropriate medical facility via road ambulance. The aftercare category (alpha) measured access to four basic services (family doctor, pharmacy, cardiac rehabilitation, and pathology services) when a patient returned to their community. Results: The numeric index ranged from 1 (access to principle referral center with cardiac catheterization service ≤ 1 hour) to 8 (no ambulance service, > 3 hours to medical facility, air transport required). The alphabetic index ranged from A (all 4 services available within 1 hour drive-time) to E (no services available within 1 hour). 13.9 million (71%) Australians resided within Cardiac ARIA 1A locations (hospital with cardiac catheterization laboratory and all aftercare within 1 hour). Those outside Cardiac 1A were over-represented by people aged over 65 years (32%) and Indigenous people (60%). Conclusion: The Cardiac ARIA index demonstrated substantial inequity in access to cardiac services in Australia. This methodology can be used to inform cardiology health service planning and the methodology could be applied to other common disease states within other regions of the world.

Mapping the dynamic of Project Management field : Project Management in action

Focusing on the role within and between organizations of the project management discipline to design and implement strategy, as source of competitive advantage, leads us to question the scientific field behind this discipline. This science should be the basis for the development and use of bodies of knowledge, standards, certification programs, education, and competencies, and beyond this as a source of value for people, organizations, and society. Thus the importance to characterize, define, and understand this field and its underlying strength, basis, and development is paramount. For this purpose we propose to give some insights on the current situation. This will lead us to clarify our epistemological position and demonstrate that both constructivism and positivist approaches are required to seize the full dimension and dynamics of the field.We will referee to sociology of actor-networks and qualitative scientometrics leading to the choice of the co-word analysis method in enabling us to capture the project management field and its dynamics.Results of a study based on the analysis of ABI Inform database will be presented and some future trends and scenarios proposed.

Strategic Management Practices in the Construction Industry : a Dynamic Capabilities View

This book is an empirical study of strategic management practices in the construction industry. It examines the dynamic capabilities paradigm within the context of the Indonesian construction industry. The characteristics of asset-capability combinations were found to be significant determinants of the competitive advantage of the Indonesian construction enterprises, and that such advantage sequentially contributes to organizational performance. In doing so, this study fills an important gap in the empirical literature and reinforces the dynamic capabilities framework’s recognition as a rigorous theory of strategic management. As the dynamic capabilities framework can work in the context of Indonesia, it suggests that the framework has potential applicability in other emerging and developing countries

Static and dynamic strain sensing using a polymer : carbon nanotube film strain sensor

The search for new multipoint, multidirectional strain sensing devices has received a new impetus since the discovery of carbon nanotubes. The excellent electrical, mechanical, and electromechanical properties of carbon nanotubes make them ideal candidates as primary materials in the design of this new generation of sensing devices. Carbon nanotube based strain sensors proposed so far include those based on individual carbon nanotubes for integration in nano or micro elecromechanical systems (NEMS/MEMS) [1], or carbon nanotube films consisting of spatially connected carbon nanotubes [2], carbon nanotube - polymer composites [3,4] for macroscale strain sensing. Carbon nanotube films have good strain sensing response and offer the possibility of multidirectional and multipoint strain sensing, but have poor performance due to weak interaction between carbon nanotubes. In addition, the carbon nanotube film sensor is extremely fragile and difficult to handle and install. We report here the static and dynamic strain sensing characteristics as well as temperature effects of a sandwich carbon nanotube - polymer sensor fabricated by infiltrating carbon nanotube films with polymer.

What explains the association between socioeconomic status and depression among Vietnamese adults?

Background Depression is a major public health problem worldwide and is currently ranked second to heart disease for years lost due to disability. For many decades, international research has found that depressive symptoms occur more frequently among low socioeconomic (SES) individuals than their more-advantaged peers. However, the reasons as to why those of low socioeconomic groups suffer more depressive symptoms are not well understood. Studies investigating the prevalence of depression and its association with SES emanate largely from developed countries, with little research among developing countries. In particular, there is a serious dearth of research on depression and no investigation of its association with SES in Vietnam. The aims of the research presented in this Thesis are to: estimate the prevalence of depressive symptoms among Vietnamese adults, examine the nature and extent of the association between SES and depression and to elucidate causal pathways linking SES to depressive symptoms Methods The research was conducted between September 2008 and November 2009 in Hue city in central Vietnam and used a combination of qualitative (in-depth interviews) and quantitative (survey) data collection methods. The qualitative study contributed to the development of the theoretical model and to the refinement of culturally-appropriate data collection instruments for the quantitative study. The main survey comprised a cross-sectional population–based survey with randomised cluster sampling. A sample of 1976 respondents aged between 25-55 years from ten randomly-selected residential zones (quarters) of Hue city completed the questionnaire (response rate 95.5%). Measures SES was classified using three indicators: education, occupation and income. The Center for Epidemiologic Studies-Depression (CES-D) scale was used to measure depressive symptoms (range0-51, mean=11.0, SD=8.5). Three cut-off points for the CES-D scores were applied: ‘at risk for clinical depression’ (16 or above), ‘depressive symptoms’ (above 21) and ‘depression’ (above 25). Six psychosocial indicators: life time trauma, chronic stress, recent life events, social support, self esteem, and mastery were hypothesized to mediate the association between SES and depressive symptoms. Analyses The prevalence of depressive symptoms were analysed using bivariate analyses. The multivariable analytic phase comprised of ordinary least squares regression, in accordance with Baron and Kenny’s three-step framework for mediation modeling. All analyses were adjusted for a range of confounders, including age, marital status, smoking, drinking and chronic diseases and the mediation models were stratified by gender. Results Among these Vietnamese adults, 24.3% were at or above the cut-off for being ‘at risk for clinical depression’, 11.9% were classified as having depressive symptoms and 6.8% were categorised as having depression. SES was inversely related to depressive symptoms: the least educated those with low occupational status or with the lowest incomes reported more depressive symptoms. Socioeconomicallydisadvantaged individuals were more likely to report experiencing stress (life time trauma, chronic stress or recent life events), perceived less social support and reported fewer personal resources (self esteem and mastery) than their moreadvantaged counterparts. These psychosocial resources were all significantly associated with depressive symptoms independent of SES. Each psychosocial factor showed a significant mediating effect on the association between SES and depressive symptoms. This was found for all measures of SES, and for males and females. In particular, personal resources (mastery, self esteem) and chronic stress accounted for a substantial proportion of the variation in depressive symptoms between socioeconomic groups. Social support and recent life events contributed modestly to socioeconomic differences in depressive symptoms, whereas lifetime trauma contributed the least to these inequalities. Conclusion This is the first known study in Vietnam or any developing country to systematically examine the extent to which psychosocial factors mediate the relationship between SES and depression. The study contributes new evidence regarding the burden of depression in Vietnam. The findings have practical relevance for advocacy, for mental health promotion and health-care services, and point to the need for programs that focus on building a sense of personal mastery and self esteem. More broadly, the work presented in this Thesis contributes to the international scientific literature on the social determinants of depression.

Functional and advanced functional and causal relationship diagrams for remote condition monitoring

Analysing the condition of an asset is a big challenge as there can be many aspects which can contribute to the overall functional reliability of the asset that have to be considered. In this paper we propose a two-step functional and causal relationship diagram (FCRD) to address this problem. In the first step, the FCRD is designed to facilitate the analysis of the condition of an asset by evaluating the interdependence (functional and causal) relationships between different components of the asset with the help of a relationship diagram. This is followed by the advanced FCRD (AFCRD) which refines the information from the FCRD into a comprehensive and manageable format. This new two-step methodology for asset condition monitoring is tested and validated for the case of a water treatment plant. © IMechE 2012.

Updating and verification for multi-scale finite element model of structure behavior

The method on concurrent multi-scale model of structural behavior (CMSM-of-SB) for the purpose of structural health monitoring including model updating and validating has been studied. The detailed process of model updating and validating is discussed in terms of reduced scale specimen of the steel box girder in longitudinal stiffening truss of a long span bridge. Firstly, some influence factors affecting the accuracy of the CMSM-of-SB including the boundary restraint regidity, the geometry and material parameters on the toe of the weld and its neighbor are analyzed using sensitivity method. Then, sensitivity-based model updating technology is adopted to update the developed CMSM-of-SB and model verification is carried out through calculating and comparing stresses on different locations under various loading from dynamic characteristic and static response. It can be concluded that the CMSM-of-SB based on the substructure method is valid.

Monte Carlo modeling of a 4 mm conical collimator for a Novalis Tx Linear Accelerator

The work presented in this poster outlines the steps taken to model a 4 mm conical collimator (BrainLab, Germany) on a Novalis Tx linear accelerator (Varian, Palo Alto, USA) capable of producing a 6MV photon beam for treatment of Stereotactic Radiosurgery (SRS) patients. The verification of this model was performed by measurements in liquid water and in virtual water. The measurements involved scanning depth dose and profiles in a water tank plus measurement of output factors in virtual water using Gafchromic® EBT3 film.

Modeling perceived collision risk in port water navigation

An increase in the likelihood of navigational collisions in port waters has put focus on the collision avoidance process in port traffic safety. The most widely used on-board collision avoidance system is the automatic radar plotting aid which is a passive warning system that triggers an alert based on the pilot’s pre-defined indicators of distance and time proximities at the closest point of approaches in encounters with nearby vessels. To better help pilot in decision making in close quarter situations, collision risk should be considered as a continuous monotonic function of the proximities and risk perception should be considered probabilistically. This paper derives an ordered probit regression model to study perceived collision risks. To illustrate the procedure, the risks perceived by Singapore port pilots were obtained to calibrate the regression model. The results demonstrate that a framework based on the probabilistic risk assessment model can be used to give a better understanding of collision risk and to define a more appropriate level of evasive actions.

Hierarchical modeling of perceived collision risks in port fairways

Navigational collisions are one of the major safety concerns in many seaports. Despite the extent of recent works done on port navigational safety research, little is known about harbor pilot’s perception of collision risks in port fairways. This paper uses a hierarchical ordered probit model to investigate associations between perceived risks and the geometric and traffic characteristics of fairways and the pilot attributes. Perceived risk data, collected through a risk perception survey conducted among the Singapore port pilots, are used to calibrate the model. Intra-class correlation coefficient justifies use of the hierarchical model in comparison with an ordinary model. Results show higher perceived risks in fairways attached to anchorages, and in those featuring sharper bends and higher traffic operating speeds. Lesser risks are perceived in fairways attached to shoreline and confined waters, and in those with one-way traffic, traffic separation scheme, cardinal marks and isolated danger marks. Risk is also found to be perceived higher in night.

Interplay effects during enhanced dynamic wedge deliveries

In this study the interplay effects for Enhanced Dynamic Wedge (EDW) treatments are experimentally investigated. Single and multiple field EDW plans for different wedge angles were delivered to a phantom and detector on a moving platform, with various periods, amplitudes for parallel and perpendicular motions. A four field 4D CT planned lung EDW treatment was delivered to a dummy tumor over four fractions. For the single field parallel case the amplitude and the period of motion both affect the interplay resulting in the appearance of a step function and penumbral cut off with the discrepancy worst where collimator-tumor speed is similar. For perpendicular motion the amplitude of tumor motion is the only dominant factor. For large wedge angle the dose discrepancy is more pronounced compared to the small wedge angle for the same field size and amplitude-period values. For a small field size i.e. 5 × 5 cm2 the loss of wedged distribution was observed for both 60º and 15º wedge angles for of parallel and perpendicular motions. Film results from 4D CT planned delivery displayed a mix of over and under dosages over 4 fractions, with the gamma pass rate of 40% for the averaged film image at 3%/1 mm DTA (Distance to Agreement). Amplitude and period of the tumor motion both affect the interplay for single and multi-field EDW treatments and for a limited (4 or 5) fraction delivery there is a possibility of non-averaging of the EDW interplay.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.