A computer model to simulate scoliosis surgery

Use of patient-specific computer models as a pre-operative planning tool permits predictions of the likely deformity correction and allows a more detailed investigation of the biomechanical influence of different surgical procedures on the scoliotic spinal anatomy. In this paper, patient-specific computer models are used of adolescent idiopathic scoliosis patients who underwent a single rod anterior procedure at the Mater Children’s Hospital in Brisbane, to predict deformity correction and to investigate the change in biomechanics of the scoliotic spine due to surgical compressive forces applied during implant placement.

Polycaprolactone-based scaffold plus recombinant human bone morphogenetic protein (rhBMP-2) in an ovine model of anterior spinal fusion

Synthetic scaffolds combined with growth factors have the potential to replace allograft or autograft as a graft material for spinal interbody fusion. Such tissue engineering approaches may be useful in Adolescent Idiopathic Scoliosis (AIS) surgery, however there are no studies to date examining the use of such biodegradable implants in combination with biologics in a thoracic spine model. This in vivo study examines the use of biodegradable polycaprolactone (PCL) based scaffolds with rhBMP-2 as a bone graft substitute in a sheep thoracic fusion model, where an anterior approach is used to simulate minimally invasive surgical deformity correction in the setting of AIS.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Physically sound vehicle-driver model for realistic microscopic simulation

In microscopic traffic simulators, the interaction between vehicles is considered. The dynamics of the system then becomes an emergent property of the interaction between its components. Such interactions include lane-changing, car-following behaviours and intersection management. Although, in some cases, such simulators produce realistic prediction, they do not allow for an important aspect of the dynamics, that is, the driver-vehicle interaction. This paper introduces a physically sound vehicle-driver model for realistic microscopic simulation. By building a nanoscopic traffic simulation model that uses steering angle and throttle position as parameters, the model aims to overcome unrealistic acceleration and deceleration values, as found in various microscopic simulation tools. A physics engine calculates the driving force of the vehicle, and the preliminary results presented here, show that, through a realistic driver-vehicle-environment simulator, it becomes possible to model realistic driver and vehicle behaviours in a traffic simulation.

Reversal of acute coagulopathy during hypotensive resuscitation using small-volume 7.5% NaCl adenocaine and Mg2+ in the rat model of severe hemorrhagic shock

OBJECTIVE: : Acute traumatic coagulopathy occurs early in hemorrhagic trauma and is a major contributor to mortality and morbidity. Our aim was to examine the effect of small-volume 7.5% NaCl adenocaine (adenosine and lidocaine, adenocaine) and Mg on hypotensive resuscitation and coagulopathy in the rat model of severe hemorrhagic shock. DESIGN: : Prospective randomized laboratory investigation. SUBJECTS: : A total of 68 male Sprague Dawley Rats. INTERVENTION: : Post-hemorrhagic shock treatment for acute traumatic coagulopathy. MEASUREMENTS AND METHODS: : Nonheparinized male Sprague-Dawley rats (300-450 g, n = 68) were randomly assigned to either: 1) untreated; 2) 7.5% NaCl; 3) 7.5% NaCl adenocaine; 4) 7.5% NaCl Mg; or 5) 7.5% NaCl adenocaine/Mg. Hemorrhagic shock was induced by phlebotomy to mean arterial pressure of 35-40 mm Hg for 20 mins (~40% blood loss), and animals were left in shock for 60 mins. Bolus (0.3 mL) was injected into the femoral vein and hemodynamics monitored. Blood was collected in Na citrate (3.2%) tubes, centrifuged, and the plasma snap frozen in liquid N2 and stored at -80°C. Coagulation was assessed using activated partial thromboplastin times and prothrombin times. RESULTS: : Small-volume 7.5% NaCl adenocaine and 7.5% NaCl adenocaine/Mg were the only two groups that gradually increased mean arterial pressure 1.6-fold from 38-39 mm Hg to 52 and 64 mm Hg, respectively, at 60 mins (p < .05). Baseline plasma activated partial thromboplastin time was 17 ± 0.5 secs and increased to 63 ± 21 secs after bleeding time, and 217 ± 32 secs after 60-min shock. At 60-min resuscitation, activated partial thromboplastin time values for untreated, 7.5% NaCl, 7.5% NaCl/Mg, and 7.5% NaCl adenocaine rats were 269 ± 31 secs, 262 ± 38 secs, 150 ± 43 secs, and 244 ± 38 secs, respectively. In contrast, activated partial thromboplastin time for 7.5% NaCl adenocaine/Mg was 24 ± 2 secs (p < .05). Baseline prothrombin time was 28 ± 0.8 secs (n = 8) and followed a similar pattern of correction. CONCLUSIONS: : Plasma activated partial thromboplastin time and prothrombin time increased over 10-fold during the bleed and shock periods prior to resuscitation, and a small-volume (~1 mL/kg) IV bolus of 7.5% NaCl AL/Mg was the only treatment group that raised mean arterial pressure into the permissive range and returned activated partial thromboplastin time and prothrombin time clotting times to baseline at 60 mins.

Testing a model of physical activity among mothers and fathers of young children: integrating self-determined motivation, planning, and the theory of planned behavior

Parents are at risk for inactivity; however, research into understanding parental physical activity (PA) is scarce. We integrated self-determined motivation, planning, and the theory of planned behavior (TPB) to better understand parental PA. Parents (252 mothers, 206 fathers) completed a main questionnaire assessing measures underpinning these constructs and a 1-week follow-up of PA behavior to examine whether self-determined motivation indirectly influenced intention via the TPB variables (i.e., attitude, subjective norm, and perceived behavioral control) and intention indirectly influenced behavior via planning. We found self-determined motivation on intention was fully mediated by the TPB variables and intention on behavior was partially mediated by the planning variables. In addition, slight differences in the model’s paths between the sexes were revealed. The results illustrate the range of important determinants of parental PA and provide support for the integrated model in explaining PA decision making as well as the importance of examining sex differences.

A holistic blended design studio model : Exploring and expanding learning opportunities

This book involves a comprehensive study of the learning environment by adopting Grounded Theory methodology in a qualitative comparative way.It explores the limitations and benefits of a face-to-face and a virtual design studio as experienced by architecture students and educators at an Australian university in order to find the optimal combination for a blended environment to enhance the students’ experience. The main outcome:holistic multidimensional blended learning model,that through the various modalities,provides adaptive capacity in a range of settings.The model facilitates learning through self-determination,self-management,and the personalisation of the learning environment. Another outcome:a conceptual design education framework,provides a basic tool for educators to evaluate existing learning environments and to develop new learning environments with enough flexibility to respond effectively to a highly dynamic and increasingly technological world.The provision of a practical framework to assist design schools to improve their educational settings according to a suitable pedagogy that meets today’s needs and accommodates tomorrow’s changes.

Smart grid-demand side response model for optimization air conditioning

The growing demand of air-conditioning is one of the largest contributors to Australia’s overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.

A hybrid model for studying spatial aspects of infectious diseases

We consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

Practical stability of approximating discrete-time filters with respect to model mismatch

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Practical stability is established in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.

Challenges in passenger terminal design : a conceptual model of passenger experience

In recent years, de-regulation in the airline industry and the introduction of low-cost carriers have conspired to produce significant changes in the airport landscape. From an airport operator’s perspective, one of the most notable has been the shift of capital revenue from traditional airline sources (through exclusive use, long term lease arrangements) to passengers (by way of fees collected from ticket sales). As a result of these developments, passengers have become recognized as major stakeholders who have the power to influence airport profitability. This link between passenger satisfaction and profitability has generated industry wide interest in the “passenger experience”. In this paper, we define the factors which influence passenger experience, namely (a) artifacts, (b) services and (c) the terminal building, and explore the challenges that exist in the current approaches to terminal design. On the basis of these insights, we propose a conceptual model of passenger experience, and motivate its use as a framework for further research into improving terminal design from a passenger oriented perspective.

Assessing occupational stress in psychiatric nurses using the full job strain model the value of social support to nurses

The present research examined the effects of occupational stress in psychiatric nursing on employee well!being using the full Job Strain Model.The Job Strain Model was assessed for its ability to predict employee well!being in terms of job satisfaction and mental health. The original Job Strain Model was expanded to include social support based on previous research concerning the impact of social support on well!being[ In the present study\ both work support and non-work were assessed for their contribution to wellbeing.The results of this study indicate that the full Job Strain Model can be used to significantly predict job satisfaction and mental health in this sample of Australian psychiatric nurses. Furthermore social support was shown to be an important component of the Job Strain Model.

Verifying a Student Engagement, Success and Retention Maturity Model (SESR-MM): A reality check of the model using data derived from three universities

Australian higher education institutions (HEIs) have entered a new phase of regulation and accreditation which includes performance-based funding relating to the participation and retention of students from social and cultural groups previously underrepresented in higher education. However, in addressing these priorities, it is critical that HEIs do not further disadvantage students from certain groups by identifying them for attention because of their social or cultural backgrounds, circumstances which are largely beyond the control of students. In response, many HEIs are focusing effort on university-wide approaches to enhancing the student experience because such approaches will enhance the engagement, success and retention of all students, and in doing so, particularly benefit those students who come from underrepresented groups. Measuring and benchmarking student experiences and engagement that arise from these efforts is well supported by extensive collections of student experience survey data. However no comparable instrument exists that measures the capability of institutions to influence and/or enhance student experiences where capability is an indication of how well an organisational process does what it is designed to do (Rosemann & de Bruin, 2005). We have proposed that the concept of a maturity model (Marshall, 2010; Paulk, 1999) may be useful as a way of assessing the capability of HEIs to provide and implement student engagement, success and retention activities and we are currently articulating a Student Engagement, Success and Retention Maturity Model (SESR-MM), (Clarke, Nelson & Stoodley, 2012; Nelson, Clarke & Stoodley, 2012). Our research aims to address the current gap by facilitating the development of an SESR-MM instrument that aims (i) to enable institutions to assess the capability of their current student engagement and retention programs and strategies to influence and respond to student experiences within the institution; and (ii) to provide institutions with the opportunity to understand various practices across the sector with a view to further improving programs and practices relevant to their context. Our research extends the generational approach which has been useful in considering the evolutionary nature of the first year experience (FYE) (Wilson, 2009). Three generations have been identified and explored: First generation approaches that focus on co-curricular strategies (e.g. orientation and peer programs); Second generation approaches that focus on curriculum (e.g. pedagogy, curriculum design, and learning and teaching practice); and third generation approaches—also referred to as transition pedagogy—that focus on the production of an institution-wide integrated holistic intentional blend of curricular and co-curricular activities (Kift, Nelson & Clarke, 2010). Our research also moves beyond assessments of students’ experiences to focus on assessing institutional processes and their capability to influence student engagement. In essence, we propose to develop and use the maturity model concept to produce an instrument that will indicate the capability of HEIs to manage and improve student engagement, success and retention programs and strategies. The issues explored in this workshop are (i) whether the maturity model concept can be usefully applied to provide a measure of institutional capability for SESR; (ii) whether the SESR-MM can be used to assess the maturity of a particular set of institutional practices; and (iii) whether a collective assessment of an institution’s SESR capabilities can provide an indication of the maturity of the institution’s SESR activities. The workshop will be approached in three stages. Firstly, participants will be introduced to the key characteristics of maturity models, followed by a discussion of the SESR-MM and the processes involved in its development. Secondly, participants will be provided with resources to facilitate the development of a maturity model and an assessment instrument for a range of institutional processes and related practices. In the final stage of the workshop, participants will “assess” the capability of these practices to provide a collective assessment of the maturity of these processes. References Australian Council for Educational Research. (n.d.). Australasian Survey of Student Engagement. Retrieved from http://www.acer.edu.au/research/ausse/background Clarke, J., Nelson, K., & Stoodley, I. (2012, July). The Maturity Model concept as framework for assessing the capability of higher education institutions to address student engagement, success and retention: New horizon or false dawn? A Nuts & Bolts presentation at the 15th International Conference on the First Year in Higher Education, “New Horizons,” Brisbane, Australia. Department of Education, Employment and Workplace Relations. (n.d.). The University Experience Survey. Advancing quality in higher education information sheet. Retrieved from http://www.deewr.gov.au/HigherEducation/Policy/Documents/University_Experience_Survey.pdf Kift, S., Nelson, K., & Clarke, J. (2010) Transition pedagogy - a third generation approach to FYE: A case study of policy and practice for the higher education sector. The International Journal of the First Year in Higher Education, 1(1), pp. 1-20. Marshall, S. (2010). A quality framework for continuous improvement of e-Learning: The e-Learning Maturity Model. Journal of Distance Education, 24(1), 143-166. Nelson, K., Clarke, J., & Stoodley, I. (2012). An exploration of the Maturity Model concept as a vehicle for higher education institutions to assess their capability to address student engagement. A work in progress. Submitted for publication. Paulk, M. (1999). Using the Software CMM with good judgment, ASQ Software Quality Professional, 1(3), 19-29. Wilson, K. (2009, June–July). The impact of institutional, programmatic and personal interventions on an effective and sustainable first-year student experience. Keynote address presented at the 12th Pacific Rim First Year in Higher Education Conference, “Preparing for Tomorrow Today: The First Year as Foundation,” Townsville, Australia. Retrieved from http://www.fyhe.com.au/past_papers/papers09/ppts/Keithia_Wilson_paper.pdf

Evaluation of the GHR car following model for traffic safety studies

Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

Experimenting with affirmative action : the Coate and Loury Model

Coate and Loury (1993) suggest the impact of affirmative action on a negative stereotype is theoretically ambiguous leading to either: a benign equilibrium in which affirmative action eradicates the negative stereotype and leads to equal proportional representation of the two groups; or alternatively a patronising equilibrium in which the stereotype persists. The current paper examines this theoretical ambiguity within the context of a laboratory experiment. Although benign and patronising equilibria are equally plausible in theory, the laboratory experiments easily replicate most features of the benign equilibrium, but diverge from the theoretically predicted patronising equilibrium.