Research around practice partnerships: An example of building partnerships to address overweight and obesity in children

Prevention and management of childhood overweight and obesity is a health priority for governments and communities throughout the developed world. A conceptual model, Research around Practice in Childhood Obesity (RAPICO), has been developed to guide capacity building in a coordinated 'bench to fieldwork' initiative to address this public health problem. Translation of research findings into sustainable responses with optimal fit requires consideration of context-specific relevance, cost-effectiveness, feasibility and levels of available support. The RAPICO model uses program theory to describe a framework for progressing practitionercommunityresearch partnerships to address low, medium and high levels of risk for childhood overweight and obesity within community settings. A case study describing the development of a logic model to inform risk-linked responses to childhood overweight and obesity is presented for the Ipswich community in south-east Queensland.

The application of building information modeling to enhance organisational learning

The construction industry is a knowledge-based industry where various actors with diverse expertise create unique information within different phases of a project. The industry has been criticized by researchers and practitioners as being unable to apply newly created knowledge effectively to innovate. The fragmented nature of the construction industry reduces the opportunity of project participants to learn from each other and absorb knowledge. Building Information Modelling (BIM), referring to digital representations of constructed facilities, is a promising technological advance that has been proposed to assist in the sharing of knowledge and creation of linkages between firms. Previous studies have mainly focused on the technical attributes of BIM and there is little evidence on its capability to enhance learning in construction firms. This conceptual paper identifies six ‘functional attributes’ of BIM that act as triggers to stimulate learning: (1) comprehensibility; (2) predictability; (3) accuracy; (4) transparency; (5) mutual understanding and; (6) integration.

Exploring accuracy factors in cost estimating practice towards implementing Building Information Modelling (BIM)

Cost estimating has been acknowledged as a crucial component of construction projects. Depending on available information and project requirements, cost estimates evolve in tandem with project lifecycle stages; conceptualisation, design development, execution and facility management. The premium placed on the accuracy of cost estimates is crucial to producing project tenders and eventually in budget management. Notwithstanding the initial slow pace of its adoption, Building Information Modelling (BIM) has successfully addressed a number of challenges previously characteristic of traditional approaches in the AEC, including poor communication, the prevalence of islands of information and frequent reworks. Therefore, it is conceivable that BIM can be leveraged to address specific shortcomings of cost estimation. The impetus for leveraging BIM models for accurate cost estimation is to align budgeted and actual cost. This paper hypothesises that the accuracy of BIM-based estimation, as more efficient, process-mirrors of traditional cost estimation methods, can be enhanced by simulating traditional cost estimation factors variables. Through literature reviews and preliminary expert interviews, this paper explores the factors that could potentially lead to more accurate cost estimates for construction projects. The findings show numerous factors that affect the cost estimates ranging from project information and its characteristic, project team, clients, contractual matters, and other external influences. This paper will make a particular contribution to the early phase of BIM-based project estimation.

Cost estimating practice incorporating Building Information Modelling (BIM): Malaysian Quantity Surveyors perspectives

Cost estimating is a key task within Quantity Surveyors’ (QS) offices. Provision of an accurate estimate is vital to ensure that the objectives of the client are met by staying within the client’s budget. Building Information Modelling (BIM) is an evolving technology that has gained attention in the construction industries all over the world. Benefits from the use of BIM include cost and time savings if the processes used by the procurement team are adapted to maximise the benefits of BIM. BIM can be used by QSs to automate aspects of quantity take-off and the preparation of estimates, decreasing turnaround time and assist in controlling errors and inaccuracies. The Malaysian government has decided to require the use of BIM for its projects beginning from 2016. However, slow uptake is reported in the use of BIM both within companies and to support collaboration within the Malaysian industry. It has been recommended that QSs to start evaluating the impact of BIM on their practices. This paper reviews the perspectives of QSs in Malaysia towards the use of BIM to achieve more dependable results in their cost estimating practice. The objectives of this paper include identifying strategies in improving practice and potential adoption drivers that lead QSs to BIM usage in their construction projects. From the expert interviews, it was found out that, despite still using traditional methods and not practising BIM, the interviewees still acquire limited knowledge related to BIM. There are some drivers that potentially motivate them to employ BIM in their practices. These include client demands, innovation in traditional methods, speed in estimating costs, reduced time and costs, improvement in practices and self-awareness, efficiency in projects, and competition from other companies. The findings of this paper identify the potential drivers in encouraging Malaysian Quantity Surveyors to exploit BIM in their construction projects.

Building an evaluation instrument for China's hospital emergency preparedness: A systematic review of preparedness instruments

Objectives: The aim of this report is to identify from the literature common themes relating to the concept of hospital preparedness for emergencies to develop an agreed framework for evaluation. Method: A systematic literature search identified appropriate articles for critical appraisal. A meta-ethnography approach was used to synthesize the findings, using both reciprocal translation and line-of-argument synthesis. Results: From an initial 2162 articles, we identified 13 articles that specifically addressed the aims of this review and formed the basis of the intended analysis. Conclusion: Hospital emergency preparedness is essential for effective disaster relief. Developing a systematic and structured methodology is necessary to assess hospital preparedness. (Disaster Med Public Health Preparedness: 2014:0:1-9)

Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method

Background Biochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need for numerical methods that are both fast and accurate. The Bulirsch-Stoer method is an established method for solving ordinary differential equations that possesses both of these qualities. Results In this paper, we present the Stochastic Bulirsch-Stoer method, a new numerical method for simulating discrete chemical reaction systems, inspired by its deterministic counterpart. It is able to achieve an excellent efficiency due to the fact that it is based on an approach with high deterministic order, allowing for larger stepsizes and leading to fast simulations. We compare it to the Euler τ-leap, as well as two more recent τ-leap methods, on a number of example problems, and find that as well as being very accurate, our method is the most robust, in terms of efficiency, of all the methods considered in this paper. The problems it is most suited for are those with increased populations that would be too slow to simulate using Gillespie’s stochastic simulation algorithm. For such problems, it is likely to achieve higher weak order in the moments. Conclusions The Stochastic Bulirsch-Stoer method is a novel stochastic solver that can be used for fast and accurate simulations. Crucially, compared to other similar methods, it better retains its high accuracy when the timesteps are increased. Thus the Stochastic Bulirsch-Stoer method is both computationally efficient and robust. These are key properties for any stochastic numerical method, as they must typically run many thousands of simulations.