The optimal duration and delay of first aid treatment for deep partial thickness burn injuries

Using our porcine model of deep dermal partial thickness burn injury, various durations (10min, 20min, 30min or 1h) and delays (immediate, 10min, 1h, 3h) of 15 degrees C running water first aid were applied to burns and compared to untreated controls. The subdermal temperatures were monitored during the treatment and wounds observed weekly for 6 weeks, for re-epithelialisation, wound surface area and cosmetic appearance. At 6 weeks after the burn, tissue biopsies were taken of the scar for histological analysis. Results showed that immediate application of cold running water for 20min duration is associated with an improvement in re-epithelialisation over the first 2 weeks post-burn and decreased scar tissue at 6 weeks. First aid application of cold water for as little as 10min duration or up to 1h delay still provides benefit.

Strategies for rapid congestion recovery using ramp metering

This research investigated strategies for motorway congestion management from a different angle: that is, how to quickly recover motorway from congestion at the end of peak hours, given congestion cannot be eliminated due to excessive demand during the long peak hours nowadays. The project developed a zone recovery strategy using ramp metering for rapid congestion recovery, and a serious of traffic simulation investigations were included to evaluate the developed strategy. The results, from both microscopic and macroscopic simulation, demonstrated the effectiveness of the zone recovery strategy.

Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries

This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

Go with the flow : optimal AUV path planning in coastal environments

This paper describes a novel optimum path planning strategy for long duration AUV operations in environments with time-varying ocean currents. These currents can exceed the maximum achievable speed of the AUV, as well as temporally expose obstacles. In contrast to most other path planning strategies, paths have to be defined in time as well as space. The solution described here exploits ocean currents to achieve mission goals with minimal energy expenditure, or a tradeoff between mission time and required energy. The proposed algorithm uses a parallel swarm search as a means to reduce the susceptibility to large local minima on the complex cost surface. The performance of the optimisation algorithms is evaluated in simulation and experimentally with the Starbug AUV using a validated ocean model of Brisbane’s Moreton Bay.

Optimal distributed generation placement in radial distribution systems

Distributed generation (DG) resources are commonly used in the electric systems to obtain minimum line losses, as one of the benefits of DG, in radial distribution systems. Studies have shown the importance of appropriate selection of location and size of DGs. This paper proposes an analytical method for solving optimal distributed generation placement (ODGP) problem to minimize line losses in radial distribution systems using loss sensitivity factor (LSF) based on bus-injection to branch-current (BIBC) matrix. The proposed method is formulated and tested on 12 and 34 bus radial distribution systems. The classical grid search algorithm based on successive load flows is employed to validate the results. The main advantages of the proposed method as compared with the other conventional methods are the robustness and no need to calculate and invert large admittance or Jacobian matrices. Therefore, the simulation time and the amount of computer memory, required for processing data especially for the large systems, decreases.

Optimal sizing of combined PV-energy storage for a grid-connected residential building

In this paper, load profile and operational goal are used to find optimal sizing of combined PV-energy storage for a future grid-connected residential building. As part of this approach, five operational goals are introduced and the annual cost for each operation goal has been assessed. Finally, the optimal sizing for combined PV-energy storage has been determined, using direct search method. In addition, sensitivity of the annual cost to different parameters has been analyzed.

Sustainability in post disaster road infrastructure recovery projects and asset management

Civil infrastructure and especially roads are being impacted with increasing frequency by flood, Tsunami, cyclone related natural and manmade disasters in the world. Responding to such events and in preparing for more regular and intense climate-change induced events in future, the road governing agencies are reviewing how postdisaster road infrastructure recovery projects are best planned and delivered. In particular, there is awareness that rebuilding such infrastructure require sustainable asset management strategies across economic, environmental and social dimensions. A comprehensive asset management framework for pre and post disaster situations can minimize negative impacts on our communities, economy and environment. This research paper is focused on post disaster management in road infrastructures and road infrastructure asset management strategies used by road authorities. Analyzing the implications of disruption to transport network and associated services is an important part of preparing local and regional responses to the impacts of disasters. This research paper will contribute to strategic infrastructure asset planning, management leading to safe, efficient and integrated transport system that supports sustainable economic, social and environmental outcomes. This paper also focuses on proper asset management, governance and engineering principles which should be followed and adopted in post disaster recovery projects to maximize sustainability in environmental, social and economic dimensions.

Output feedback optimal control with contraints

In Chapters 1 through 9 of the book (with the exception of a brief discussion on observers and integral action in Section 5.5 of Chapter 5) we considered constrained optimal control problems for systems without uncertainty, that is, with no unmodelled dynamics or disturbances, and where the full state was available for measurement. More realistically, however, it is necessary to consider control problems for systems with uncertainty. This chapter addresses some of the issues that arise in this situation. As in Chapter 9, we adopt a stochastic description of uncertainty, which associates probability distributions to the uncertain elements, that is, disturbances and initial conditions. (See Section 12.6 for references to alternative approaches to model uncertainty.) When incomplete state information exists, a popular observer-based control strategy in the presence of stochastic disturbances is to use the certainty equivalence [CE] principle, introduced in Section 5.5 of Chapter 5 for deterministic systems. In the stochastic framework, CE consists of estimating the state and then using these estimates as if they were the true state in the control law that results if the problem were formulated as a deterministic problem (that is, without uncertainty). This strategy is motivated by the unconstrained problem with a quadratic objective function, for which CE is indeed the optimal solution (˚Astr¨om 1970, Bertsekas 1976). One of the aims of this chapter is to explore the issues that arise from the use of CE in RHC in the presence of constraints. We then turn to the obvious question about the optimality of the CE principle. We show that CE is, indeed, not optimal in general. We also analyse the possibility of obtaining truly optimal solutions for single input linear systems with input constraints and uncertainty related to output feedback and stochastic disturbances.We first find the optimal solution for the case of horizon N = 1, and then we indicate the complications that arise in the case of horizon N = 2. Our conclusion is that, for the case of linear constrained systems, the extra effort involved in the optimal feedback policy is probably not justified in practice. Indeed, we show by example that CE can give near optimal performance. We thus advocate this approach in real applications.

On optimal control of constrained linear systems with imperfect state information and stochastic disturbances

We address the problem of finite horizon optimal control of discrete-time linear systems with input constraints and uncertainty. The uncertainty for the problem analysed is related to incomplete state information (output feedback) and stochastic disturbances. We analyse the complexities associated with finding optimal solutions. We also consider two suboptimal strategies that could be employed for larger optimization horizons.

The impact of viral respiratory infection on the severity and recovery from an asthma exacerbation

Background Viral respiratory illness triggers asthma exacerbations, but the influence of respiratory illness on the acute severity and recovery of childhood asthma is unknown. Our objective was to evaluate the impact of a concurrent acute respiratory illness (based on a clinical definition and PCR detection of a panel of respiratory viruses, Mycoplasma pneumoniae and Chlamydia pneumoniae) on the severity and resolution of symptoms in children with a nonhospitalized exacerbation of asthma. Methods Subjects were children aged 2 to 15 years presenting to an emergency department for an acute asthma exacerbation and not hospitalized. Acute respiratory illness (ARI) was clinically defined. Nasopharyngeal aspirates (NPA) were examined for respiratory viruses, Chlamydia and Mycoplasma using PCR. The primary outcome was quality of life (QOL) on presentation, day 7 and day 14. Secondary outcomes were acute asthma severity score, asthma diary, and cough diary scores on days 5, 7,10, and 14. Results On multivariate regression, presence of ARI was statistically but not clinically significantly associated with QOL score on presentation (B = 0.36, P = 0.025). By day 7 and 14, there was no difference between groups. Asthma diary score was significantly higher in children with ARI (B = 0.41, P = 0.039) on day 5 but not on presentation or subsequent days. Respiratory viruses were detected in 54% of the 78 NPAs obtained. There was no difference in the any of the asthma outcomes of children grouped by positive or negative NPA. Conclusions The presence of a viral respiratory illness has a modest influence on asthma severity, and does not influence recovery from a nonhospitalized asthma exacerbation.

A lesson in costs recovery

In La Spina v Macdonnells Law [2014] QSC 44 the Queensland Court of Appeal set aside a judgment entered in circumstances where the appellant had not been given the requisite notice of the application under r31 of the Uniform Civil Procedure Rules 1999 (Qld)(UCPR). The court found there had been a denial of natural justice. The court also considered whether in any event the entry of judgment in the circumstances was a proper exercise of the powers which may be exercised on an application for directions under r743H of the UCPR.

The use of phospholipid fatty acid analysis to measure impact of acid rock drainage on microbial communities in sediments

The impact of acid rock drainage (ARD) and eutrophication on microbial communities in stream sediments above and below an abandoned mine site in the Adelaide Hills, South Australia, was quantified by PLFA analysis. Multivariate analysis of water quality parameters, including anions, soluble heavy metals, pH, and conductivity, as well as total extractable metal concentrations in sediments, produced clustering of sample sites into three distinct groups. These groups corresponded with levels of nutrient enrichment and/or concentration of pollutants associated with ARD. Total PLFA concentration, which is indicative of microbial biomass, was reduced by >70% at sites along the stream between the mine site and as far as 18 km downstream. Further downstream, however, recovery of the microbial abundance was apparent, possibly reflecting dilution effect by downstream tributaries. Total PLFA was >40% higher at, and immediately below, the mine site (0-0.1 km), compared with sites further downstream (2.5-18 km), even after accounting for differences in specific surface area of different sediment samples. The increased microbial population in the proximity of the mine source may be associated with the presence of a thriving iron-oxidizing bacteria community as a consequence of optimal conditions for these organisms while the lower microbial population further downstream corresponded with greater sediments' metal concentrations. PCA of relative abundance revealed a number of PLFAs which were most influential in discriminating between ARD-polluted sites and the rest of the sites. These PLFA included the hydroxy fatty acids: 2OH12:0, 3OH12:0, 2OH16:0; the fungal marker: 18:2ω6; the sulfate-reducing bacteria marker 10Me16:1ω7; and the saturated fatty acids 12:0, 16:0, 18:0. Partial constrained ordination revealed that the environmental parameters with the greatest bearing on the PLFA profiles included pH, soluble aluminum, total extractable iron, and zinc. The study demonstrated the successful application of PLFA analysis to rapidly assess the toxicity of ARD-affected waters and sediments and to differentiate this response from the effects of other pollutants, such as increased nutrients and salinity.

Mechanisms of change in psychotherapy for people diagnosed with schizophrenia : the role of narrative reflexivity in promoting recovery

Narrative reflexivity was investigated as a potential mechanism of therapeutic change during a 12 - 18 month trial of Metacognitive Narrative Psychotherapy for people diagnosed with schizophrenia. Participants were nine adult clients (8 male, 1 female) aged between 25-65 years (M = 44, SD = 12.76) with a diagnosis of schizophrenia consistent with DSM-IV criteria and seven female provisional psychologists aged between 25-29 years (M = 26.8 years, SD = 1.47 years). Recovery and narrative reflexivity were measured at three time points using the Recovery Assessment Scale (RAS) and the Narrative Processes Coding System (NPCS). Results were reported descriptively due to limited sample size (n = 9). The majority of clients (n = 7) reported an increase in recovery over the course of treatment. For six clients, an overall increase in recovery was associated with an increase in narrative reflexivity. This study provides preliminary support for narrative reflexivity as a potential mechanism of therapeutic change in the psychotherapy of people diagnosed with schizophrenia.

Optimal Bayesian experimental design for models with intractable likelihoods using indirect inference applied to biological process models

This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.