Ocular characteristics of anisometropia

Animal models of refractive error development have demonstrated that visual experience influences ocular growth. In a variety of species, axial anisometropia (i.e. a difference in the length of the two eyes) can be induced through unilateral occlusion, image degradation or optical manipulation. In humans, anisometropia may occur in isolation or in association with amblyopia, strabismus or unilateral pathology. Non-amblyopic myopic anisometropia represents an interesting anomaly of ocular growth, since the two eyes within one visual system have grown to different endpoints. These experiments have investigated a range of biometric, optical and mechanical properties of anisometropic eyes (with and without amblyopia) with the aim of improving our current understanding of asymmetric refractive error development. In the first experiment, the interocular symmetry in 34 non-amblyopic myopic anisometropes (31 Asian, 3 Caucasian) was examined during relaxed accommodation. A high degree of symmetry was observed between the fellow eyes for a range of optical, biometric and biomechanical measurements. When the magnitude of anisometropia exceeded 1.75 D, the more myopic eye was almost always the sighting dominant eye. Further analysis of the optical and biometric properties of the dominant and non-dominant eyes was conducted to determine any related factors but no significant interocular differences were observed with respect to best-corrected visual acuity, corneal or total ocular aberrations during relaxed accommodation. Given the high degree of symmetry observed between the fellow eyes during distance viewing in the first experiment and the strong association previously reported between near work and myopia development, the aim of the second experiment was to investigate the symmetry between the fellow eyes of the same 34 myopic anisometropes following a period of near work. Symmetrical changes in corneal and total ocular aberrations were observed following a short reading task (10 minutes, 2.5 D accommodation demand) which was attributed to the high degree of interocular symmetry for measures of anterior eye morphology, and corneal biomechanics. These changes were related to eyelid shape and position during downward gaze, but gave no clear indication of factors associated with near work that might cause asymmetric eye growth within an individual. Since the influence of near work on eye growth is likely to be most obvious during, rather than following near tasks, in the third experiment the interocular symmetry of the optical and biometric changes was examined during accommodation for 11 myopic anisometropes. The changes in anterior eye biometrics associated with accommodation were again similar between the eyes, resulting in symmetrical changes in the optical characteristics. However, the more myopic eyes exhibited slightly greater amounts of axial elongation during accommodation which may be related to the force exerted by the ciliary muscle. This small asymmetry in axial elongation we observed between the eyes may be due to interocular differences in posterior eye structure, given that the accommodative response was equal between eyes. Using ocular coherence tomography a reduced average choroidal thickness was observed in the more myopic eyes compared to the less myopic eyes of these subjects. The interocular difference in choroidal thickness was correlated with the magnitude of spherical equivalent and axial anisometropia. The symmetry in optics and biometrics between fellow eyes which have undergone significantly different visual development (i.e. anisometropic subjects with amblyopia) is also of interest with respect to refractive error development. In the final experiment the influence of altered visual experience upon corneal and ocular higher-order aberrations was investigated in 21 amblyopic subjects (8 refractive, 11 strabismic and 2 form deprivation). Significant differences in aberrations were observed between the fellow eyes, which varied according to the type of amblyopia. Refractive amblyopes displayed significantly higher levels of 4th order corneal aberrations (spherical aberration and secondary astigmatism) in the amblyopic eye compared to the fellow non-amblyopic eye. Strabismic amblyopes exhibited significantly higher levels of trefoil, a third order aberration, in the amblyopic eye for both corneal and total ocular aberrations. The results of this experiment suggest that asymmetric visual experience during development is associated with asymmetries in higher-order aberrations, proportional to the magnitude of anisometropia and dependent upon the amblyogenic factor. This suggests a direct link between the development of higher-order optical characteristics of the human eye and visual feedback. The results from these experiments have shown that a high degree of symmetry exists between the fellow eyes of non-amblyopic myopic anisometropes for a range of biomechanical, biometric and optical parameters for different levels of accommodation and following near work. While a single specific optical or biomechanical factor that is consistently associated with asymmetric refractive error development has not been identified, the findings from these studies suggest that further research into the association between ocular dominance, choroidal thickness and higher-order aberrations with anisometropia may improve our understanding of refractive error development.

Application of operations research techniques to improve efficiency in the emergency department

The main aim of this thesis is to analyse and optimise a public hospital Emergency Department. The Emergency Department (ED) is a complex system with limited resources and a high demand for these resources. Adding to the complexity is the stochastic nature of almost every element and characteristic in the ED. The interaction with other functional areas also complicates the system as these areas have a huge impact on the ED and the ED is powerless to change them. Therefore it is imperative that OR be applied to the ED to improve the performance within the constraints of the system. The main characteristics of the system to optimise included tardiness, adherence to waiting time targets, access block and length of stay. A validated and verified simulation model was built to model the real life system. This enabled detailed analysis of resources and flow without disruption to the actual ED. A wide range of different policies for the ED and a variety of resources were able to be investigated. Of particular interest was the number and type of beds in the ED and also the shift times of physicians. One point worth noting was that neither of these resources work in isolation and for optimisation of the system both resources need to be investigated in tandem. The ED was likened to a flow shop scheduling problem with the patients and beds being synonymous with the jobs and machines typically found in manufacturing problems. This enabled an analytic scheduling approach. Constructive heuristics were developed to reactively schedule the system in real time and these were able to improve the performance of the system. Metaheuristics that optimised the system were also developed and analysed. An innovative hybrid Simulated Annealing and Tabu Search algorithm was developed that out-performed both simulated annealing and tabu search algorithms by combining some of their features. The new algorithm achieves a more optimal solution and does so in a shorter time.

Overlapping medical alarms are almost indiscriminable

Objective: We explore how accurately and quickly nurses can identify melodic medical equipment alarms when no mnemonics are used, when alarms may overlap, and when concurrent tasks are performed. Background: The international standard IEC 60601-1-8 (International Electrotechnical Commission, 2005) has proposed simple melodies to distinguish seven alarm sources. Previous studies with nonmedical participants reveal poor learning of melodic alarms and persistent confusions between some of them. The effects of domain expertise, concurrent tasks, and alarm overlaps are unknown. Method: Fourteen intensive care and general medical unit nurses learned the melodic alarms without mnemonics in two sessions on separate days. In the second half of Day 2 the nurses identified single alarms or pairs of alarms played in sequential, partially overlapping, or nearly completely overlapping configurations. For half the experimental blocks nurses performed a concurrent mental arithmetic task. Results: Nurses' learning was poor and was no better than the learning of nonnurses in a previous study. Nurses showed the previously noted confusions between alarms. Overlapping alarms were exceptionally difficult to identify. The concurrent task affected response time but not accuracy. Conclusion: Because of a failure of auditory stream segregation, the melodic alarms cannot be discriminated when they overlap. Directives to sequence the sounding of alarms in medical electrical equipment must be strictly adhered to, or the alarms must redesigned to support better auditory streaming. Application: Actual or potential uses of this research include the implementation of IEC 60601-1-8 alarms in medical electrical equipment.

Modeling ion channel dynamics through reflected stochastic differential equations

Ion channels are membrane proteins that open and close at random and play a vital role in the electrical dynamics of excitable cells. The stochastic nature of the conformational changes these proteins undergo can be significant, however current stochastic modeling methodologies limit the ability to study such systems. Discrete-state Markov chain models are seen as the "gold standard," but are computationally intensive, restricting investigation of stochastic effects to the single-cell level. Continuous stochastic methods that use stochastic differential equations (SDEs) to model the system are more efficient but can lead to simulations that have no biological meaning. In this paper we show that modeling the behavior of ion channel dynamics by a reflected SDE ensures biologically realistic simulations, and we argue that this model follows from the continuous approximation of the discrete-state Markov chain model. Open channel and action potential statistics from simulations of ion channel dynamics using the reflected SDE are compared with those of a discrete-state Markov chain method. Results show that the reflected SDE simulations are in good agreement with the discrete-state approach. The reflected SDE model therefore provides a computationally efficient method to simulate ion channel dynamics while preserving the distributional properties of the discrete-state Markov chain model and also ensuring biologically realistic solutions. This framework could easily be extended to other biochemical reaction networks. © 2012 American Physical Society.

Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise

In this paper we extend the ideas of Brugnano, Iavernaro and Trigiante in their development of HBVM($s,r$) methods to construct symplectic Runge-Kutta methods for all values of $s$ and $r$ with $s\geq r$. However, these methods do not see the dramatic performance improvement that HBVMs can attain. Nevertheless, in the case of additive stochastic Hamiltonian problems an extension of these ideas, which requires the simulation of an independent Wiener process at each stage of a Runge-Kutta method, leads to methods that have very favourable properties. These ideas are illustrated by some simple numerical tests for the modified midpoint rule.

Modelling passenger flow at airport terminals : individual agent decision model for stochastic passenger behaviour

Airport system is complex. Passenger dynamics within it appear to be complicate as well. Passenger behaviours outside standard processes are regarded more significant in terms of public hazard and service rate issues. In this paper, we devised an individual agent decision model to simulate stochastic passenger behaviour in airport departure terminal. Bayesian networks are implemented into the decision making model to infer the probabilities that passengers choose to use any in-airport facilities. We aim to understand dynamics of the discretionary activities of passengers.

Teacher decision making in early childhood education

The study investigated early childhood teacher decision making at the preschool level in the state of Victoria, Australia. Victorian teachers at the preschool level were in an interesting position in 2004. Unlike most other Australian states Victoria did not have a curriculum framework guiding educational content and pedagogy. Consequently, this study was able to take advantage of this situation and examine teacher decision making at a time when early childhood teachers were relatively autonomous in deciding curriculum content. The opportunity to study teacher decision making in this way has since passed, as Victorian preschool teachers are now regulated by newly introduced state and national curricula frameworks. To identify influences affecting teacher decision making three preschool teachers were interviewed and curricula related policies were analysed. The data were analysed using Fairclough’s critical discourse analysis (CDA) technique. Critical discourse analysis enabled a close analysis of influences on teacher decision making illustrating how discourse is legitimated, marginalised, and silenced in certain curricula practices. Critical theory was the underpinning framework used for the study and enabled taken-for-granted understandings to be uncovered within early childhood policies and teacher interviews. Key findings were that despite there not being a government-mandated curricula framework for Victorian preschool education in 2004, teachers were held accountable for their curricula practice. Yet as professionals, early childhood teachers were denied public acknowledgment of their expertise as they were almost invisible in policy. Subsequently, teachers’ authority as professionals with curricula knowledge was diminished. The study found that developmentally appropriate practice (DAP) was a dominant discourse influencing teacher decision making (TDM). It operated as legitimated discourse in the 2004 Victorian preschool context. Additionally, the study found that teacher directed practice was legitimated, marginalised, and silenced by teachers. The findings have implications for early childhood teacher decision making at the practice, research, and policy levels. Findings show that the dominance of the DAP discourse informing teacher decision making limits other ways of thinking and practising.

Stable strong order 1.0 schemes for solving stochastic ordinary differential equations

The Balanced method was introduced as a class of quasi-implicit methods, based upon the Euler-Maruyama scheme, for solving stiff stochastic differential equations. We extend the Balanced method to introduce a class of stable strong order 1. 0 numerical schemes for solving stochastic ordinary differential equations. We derive convergence results for this class of numerical schemes. We illustrate the asymptotic stability of this class of schemes is illustrated and is compared with contemporary schemes of strong order 1. 0. We present some evidence on parametric selection with respect to minimising the error convergence terms. Furthermore we provide a convergence result for general Balanced style schemes of higher orders.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

Numerical simulation of stochastic ordinary differential equations in biomathematical modelling

In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type.

Numerical methods for strong solutions of stochastic differential equations : an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

Order conditions of stochastic Runge-Kutta methods by B-series

In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.