Design Considerations for a Disaster eHealth Appliance

Disaster eHealth is a new area of research and endeavour. In order to make a practical contribution Disaster eHealth approaches should consider the role of a Disaster eHealth appliance. Both disaster management and disaster medicine may find that such approaches allow critical information to be gathered and situational awareness improved. This paper proposes the development of a Disaster eHealth appliance to support self-care of chronic disease and caregiving by others. Injuries and disease caused by the disaster may be also supported by this approach. It also attempts to address some of the potential problems and suggest some solutions for the use of such appliances. Re-using existing devices may offer a relatively low-cost and sustainable approach to providing such devices, and infrastructure to use them. &nbsp

Pinpointing What is Wrong With Cross-Agency Collaboration in Disaster Healthcare

A disaster is an event in which a hazard has a destructive environmental or ecological impact on such a scale that the effects cannot be managed within local community resources. In disaster healthcare, the main responders to provide emergency relief are usually emergency management and health personnel. Although these two sectors share the same vision of providing public health services to disaster victims, post-disaster analysis reflects poor communication between them leading to delayed, substandard and even unavailable healthcare. This paper investigates the barriers to smooth and effective communication between health and emergency management personnel in a disaster, with the aim of pinpointing possible points of improvement. The paper presents a comprehensive review of the available literature on the subject and suggests suitable interventions to enhance healthcare delivery through cross-agency collaboration and information exchange based on a projected telehealth system

Investigation into the bond strength of bitumen-fibre mastic

The loss of bond strength in road pavement surfacing due to high traffic loads or moisture is a recurring problem, creating distresses such as ravelling, fatigue and rutting. It is, therefore, important to find a way to prevent or at least delay the loss of bond strength in asphalt mixtures. Such an improvement would lead to longer service life and a more comfortable drive for road users. This study describes how the pneumatic adhesion tensile testing instrument (PATTI) was used to examine the mechanism by which fibres influence the pull-off tensile strength of asphalt mastic. This study assesses the potential for chemical modification of the binder due to the presence of fibres, by means of work of cohesion and work of adhesion calculations, based on surface energy parameters and a binder drainage test. The study also evaluates the influence of different filler-bitumen ratios and fibre percentages on pull-off tensile strength. The test results indicate that the fibres enhance the pull-off tensile strength of the mastic, in addition to changing the failure mode from cohesive to hybrid, implying an improvement in the cohesive strength of the mastic

Meta-analytic framework for efficiently identifying progression groups in highway condition analysis

The minimum message length two-dimensional segmenter (MML2DS) criterion is a powerful technique for road condition data analysis developed at the Nottingham Transportation Engineering Centre (NTEC), University of Nottingham. The criterion analyses condition data sets by simultaneously identifying optimum trends in condition progression, the position in time and space of maintenance interventions, longitudinal segments within links, and the error likelihood of each measurement. This is done in an unsupervised manner through classification and regression models on the basis of the minimum message length (MML) metric. Use of MML, however, often requires an exhaustive comparison of all possible models, which naturally raises considerable search-control issues. This is precisely the case with the MML2DS approach. This paper presents an efficient meta-analytic framework for controlling the generation of progression groups, which considerably reduces the search space before the application of MML2DS. This is achieved by identifying founder sets of longitudinal segments, around which families of segments are likely to be formed. An effective subset of these families is then selected, after which the MML2DS criterion is used as the final arbiter to determine ultimate model configurations and fits. This approach has proved to be very powerful, resulting in significant improvements in efficiency to the effect that accurate results are obtained in a few minutes where it previously took weeks with much smaller data sets. The indications are that this approach can be applied to other techniques besides MML2DS

Immediate effects of some corrective maintenance interventions on flexible pavements

Different maintenance interventions have different ability to address distresses on flexible pavements. Understanding the maintenance effects can benefit pavement maintenance decision-making. In this study, the immediate maintenance effects on roughness and rutting of three interventions including overlay, overlay with an additional base layer and mill and fill were studied and compared. A method was introduced to validate maintenance effect models, using the pavement management information from Virginia Department of Transportation. The method included a data mining process to extract data and apply regression analysis of maintenance effect models. The outliers in the analysis were detected and removed using the method of Cook’s distance. It was found that the immediate maintenance effects of overlay with base layer were greatest and mill and fill was least when treating pavements with moderate roughness (50–100 in/mi (≈ 0.8–1.6 m/km)). However, mill and fill was more useful for treating pavements with high roughness (>100 in/mi (≈1.6 m/km)). Furthermore, suggestions were proposed on data collection for road authorities to improve the prediction of maintenance effects

A machine learning approach for the estimation of fuel consumption related to road pavement rolling resistance for large fleets of trucks

There remains a level of uncertainty concerning the methodological assumptions and parameters to consider in the estimation of road vehicle fuel consumption due to the condition of road pavements. In fact, recent studies highlighted how existing models can lead to very different results and that because of this, they are not fully ready to be implemented as standard in the life-cycle assessment (LCA) framework. This study presents an innovative approach, based on the application of the Boruta algorithm (BA) and neural networks (NN), for the assessment and calculation of the fuel consumption of a large fleet of truck, which can be used to estimate the use phase emissions of road pavements. The study shows that neural networks are suitable to analyse the large quantities of data, coming from fleet and road asset management databases, effectively and that the developed NN model is able to estimate the impact of rolling resistance-related parameters (pavement roughness and macrotexture) on truck fuel consumption

Modelling the Environmental and Economic Life Cycle Performance of Maximizing Asphalt Recycling on Road Pavement Surfaces in Europe

The road pavement industry, worldwide, has often shown reluctance in quickly implementing innovative practices; however, in the case of raw material consumption, a cultural change is necessary and, in this sense, sustainability assessment could play a major role. Along these lines, this research study aims to provide evidence to all the involved stakeholders (material producers, pavement contractors, and road authorities) of how life cycle-based techniques can be crucial in evaluating whether the adoption of asphalt mixtures with high contents of reclaimed asphalt (RA) for wearing courses is actually a sustainable practice for major European roads. An evaluation framework composed of a life cycle assessment, to calculate the carbon footprint of both pavement materials and pavement activities, and a life cycle cost assessment, performed to determine the overall economic burden of the related road pavement surface courses and maintenance strategies over a sixty-year analysis period, is presented and applied to selected case studies. These were developed together with three major European national road authorities and include scenarios involving the construction of road surfaces with asphalt mixtures containing up to 90% RA. Results have shown that whenever high-content RA mixes do not under-perform against conventional mixtures, up to 50% CO2eq savings can be registered and up to 60% economic cost reductions can be reported. The durability of road pavement layers remains a key parameter for any road pavement sustainability assessment exercises; therefore, in order to adapt the obtained results to other contexts, researchers should always consider conducting a sensitivity analysis of the reference service life and/or road authorities should somehow request road pavement durability as a pre-requisite within procurement practices

Disaster E-Health Framework for Community Resilience

Disaster management and the health sector ought to be natural allies, but there are few examples of the collaborative planning and application of disaster healthcare involving emergency managers and care practitioners. The different origins, culture, and priorities of the various agencies tasked with disaster healthcare mean that communication and coordination between them is often lacking, leading to delayed, sub-standard, or inappropriate care for disaster victims. The potential of the new e-health technologies, such as the electronic health record, telehealth and mobile health, that are revolutionizing non-disaster healthcare, is also not being realised. These circumstances have led to an international project to develop a disaster e-health framework that can inform national disaster and health strategies. This paper describes this project and its extension to embrace community resilience that strengthens preparedness, safeguards life during the disaster phase, and assists long-term recovery to preserve the health and basic values of citizens

The case for internalising externalities in a sustainable rail asset base

Although the concept of sustainability and Sustainable development has tended to be mostly associated with the management of natural resources and the consequent environmental impact, the most accepted definition draws together its social, economic and environmental dimensions. The rail industry, as provider of a low carbon transport system, is well placed to have a significant role to play in promoting an environmental, economic and social balance that can be sustained and afforded for the foreseeable future. The paper suggests that a more comprehensive perspective on the scope of a sustainable intervention in rail infrastructure assets is needed, arguing that the necessary whole life evaluation process should include an additional positive externality: the uplift in knowledge, skill and expertise that comes about as a result of participation in projects and programmes. The inclusion of this benefit would provide a more accurate representation of value to support investment decision making and strengthen the case for a broader funding base. And that the demonstration of the correlation between participation in projects and programmes and the consequent uplift in skill, knowledge and expertise could be used to shift the emphasis in rail project planning

Evaluating the effects of climate change on road maintenance intervention strategies and Life-Cycle Costs

Climate change has the potential to impact long-term road pavement performance. Consequently, to maintain pavements within the same ranges of serviceability as before, current pavement maintenance strategies need to be re assessed and, if necessary, changed. Changes in maintenance may lead to different agency costs and user costs as a consequence. This paper commences by defining an assessment procedure, showing how maintenance intervention strategies and Life-Cycle Costs (LCC) may be affected by future climate. A typical Virginia flexible pavement structure and anticipated climate change was used as an example. This example is believed to be representative for a great number of localities in the United States. A method using historical climatic data and climate change projections to predict pavement performance using Mechanistic-Empirical Pavement Design Guide (MEPDG) under current or future climate was introduced. Based on pavement performance prediction, maintenance interventions were planned and optimized. The maintenance effects of three treatments (thin overlay, thin overlay with an intermediate layer, and mill & fill) were considered. A Life-Cycle Cost analysis is reported that used binary non-linear programming to minimize the costs (either agency costs or total costs) by optimizing intervention strategies in terms of type and application time. By these means, the differences in maintenance planning and LCC under current and future climate can be derived. It was found, that for this simplified case study, pavement maintenance and LCC may be affected by climate change Optimized maintenance may improve resilience to climate change in terms of intervention strategy and LCC, compared to responsive maintenance