The influence of habitat heterogeneity on patterns of connectivity among rabbit populations in southern Queensland

Patterns of connectivity among local populations influence the dynamics of regional systems, but most ecological models have concentrated on explaining the effect of connectivity on local population structure using dynamic processes covering short spatial and temporal scales. In this study, a model was developed in an extended spatial system to examine the hypothesis that long term connectivity levels among local populations are influenced by the spatial distribution of resources and other habitat factors. The habitat heterogeneity model was applied to local wild rabbit populations in the semi-arid Mitchell region of southern central Queensland (the Eastern system). Species' specific population parameters which were appropriate for the rabbit in this region were used. The model predicted a wide range of long term connectivity levels among sites, ranging from the extreme isolation of some sites to relatively high interaction probabilities for others. The validity of model assumptions was assessed by regressing model output against independent population genetic data, and explained over 80% of the variation in the highly structured genetic data set. Furthermore, the model was robust, explaining a significant proportion of the variation in the genetic data over a wide range of parameters. The performance of the habitat heterogeneity model was further assessed by simulating the widely reported recent range expansion of the wild rabbit into the Mitchell region from the adjacent, panmictic Western rabbit population system. The model explained well the independently determined genetic characteristics of the Eastern system at different hierarchic levels, from site specific differences (for example, fixation of a single allele in the population at one site), to differences between population systems (absence of an allele in the Eastern system which is present in all Western system sites). The model therefore explained the past and long term processes which have led to the formation and maintenance of the highly structured Eastern rabbit population system. Most animals exhibit sex biased dispersal which may influence long term connectivity levels among local populations, and thus the dynamics of regional systems. When appropriate sex specific dispersal characteristics were used, the habitat heterogeneity model predicted substantially different interaction patterns between female-only and combined male and female dispersal scenarios. In the latter case, model output was validated using data from a bi-parentally inherited genetic marker. Again, the model explained over 80% of the variation in the genetic data. The fact that such a large proportion of variability is explained in two genetic data sets provides very good evidence that habitat heterogeneity influences long term connectivity levels among local rabbit populations in the Mitchell region for both males and females. The habitat heterogeneity model thus provides a powerful approach for understanding the large scale processes that shape regional population systems in general. Therefore the model has the potential to be useful as a tool to aid in the management of those systems, whether it be for pest management or conservation purposes.

An optimization-based algorithm for shunt active filter under distorted supply voltages

When the supply voltages are balanced and sinusoidal, load compensation can give both unity power factor (UPF) and perfect harmonic cancellation (PHC) source currents. But under distorted supply voltages, achieving both UPF and PHC currents are not possible and contradictory to each other. Hence there should be an optimal performance between these two important compensation goals. This paper presents an optimal control algorithm for load compensation under unbalanced and distorted supply voltages. In this algorithm source currents are compensated for reactive, imbalance components and harmonic distortions set by the limits. By satisfying the harmonic distortion limits and power balance, this algorithm gives the source currents which will provide the maximum achievable power factor. The detailed simulation results using MATLAB are presented to support the performance of the proposed optimal control algorithm.

Global trends in prescribing contact lenses for extended wear

Extended wear has long been the ‘holy grail’ of contact lenses by virtue of the increased convenience and freedom of lifestyle which they accord; however, this modality enjoyed only limited market success during the last quarter of the 20th century. The introduction of silicone hydrogel materials into the market at the beginning of this century heralded the promise of successful extended wear due to the superior oxygen performance of this lens type. To assess patterns of contact lens fitting, including extended wear, over the past decade, up to 1000 survey forms were sent to contact lens fitters in Australia, Canada, Japan, the Netherlands, Norway, the UK and the USA each year between 2000 and 2009. Practitioners were asked to record data relating to the first 10 contact lens fits or refits performed after receiving the survey form. Analysis of returned forms revealed that, averaged over this period, 9% of all soft lenses prescribed were for extended wear, with national figures ranging from 2% in Japan to 17% in Norway. The trend over the past decade has been for an increase from about 5% of all soft lens fits in 2000 to a peak of between 9 and 12% between 2002 and 2007, followed by a decline to around 7% in 2009. A person receiving extended wear lenses is likely to be an older female who is being refitted with silicone hydrogel lenses for full-time wear. Although extended wear has yet again failed to fulfil the promise of being the dominant contact lens wearing modality, it is still a viable option for many people.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

A snapshot of Australian nurse practitioners’ extended practice activities

Introduction The Australian Nurse Practitioner Project (AUSPRAC) was initiated to examine the introduction of nurse practitioners into the Australian health service environment. The nurse practitioner concept was introduced to Australia over two decades ago and has been evolving since. Today, however, the scope of practice, role and educational preparation of nurse practitioners is well defined (Gardner et al, 2006). Amendments to specific pre-existing legislation at a State level have permitted nurse practitioners to perform additional activities including some once in the domain of the medical profession. In the Australian Capital Territory, for example 13 diverse Acts and Regulations required amendments and three new Acts were established (ACT Health, 2006). Nurse practitioners are now legally authorized to diagnose, treat, refer and prescribe medications in all Australian states and territories. These extended practices differentiate nurse practitioners from other advanced practice roles in nursing (Gardner, Chang & Duffield, 2007). There are, however, obstacles for nurse practitioners wishing to use these extended practices. Restrictive access to Medicare funding via the Medicare Benefit Scheme (MBS) and the Pharmaceutical Benefit Scheme (PBS) limit the scope of nurse practitioner service in the private health sector and community settings. A recent survey of Australian nurse practitioners (n=202) found that two-thirds of respondents (66%) stated that lack of legislative support limited their practice. Specifically, 78% stated that lack of a Medicare provider number was ‘extremely limiting’ to their practice and 71% stated that no access to the PBS was ‘extremely limiting’ to their practice (Gardner et al, in press). Changes to Commonwealth legislation is needed to enable nurse practitioners to prescribe medication so that patients have access to PBS subsidies where they exist; currently patients with scripts which originated from nurse practitioners must pay in full for these prescriptions filled outside public hospitals. This report presents findings from a sub-study of Phase Two of AUSPRAC. Phase Two was designed to enable investigation of the process and activities of nurse practitioner service. Process measurements of nurse practitioner services are valuable to healthcare organisations and service providers (Middleton, 2007). Processes of practice can be evaluated through clinical audit, however as Middleton cautions, no direct relationship between these processes and patient outcomes can be assumed.

Freeway traffic estimation in Beijing based on particle filter

Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.

Bias in the nonlinear filter generator output sequence

Nonlinear filter generators are common components used in the keystream generators for stream ciphers and more recently for authentication mechanisms. They consist of a Linear Feedback Shift Register (LFSR) and a nonlinear Boolean function to mask the linearity of the LFSR output. Properties of the output of a nonlinear filter are not well studied. Anderson noted that the m-tuple output of a nonlinear filter with consecutive taps to the filter function is unevenly distributed. Current designs use taps which are not consecutive. We examine m-tuple outputs from nonlinear filter generators constructed using various LFSRs and Boolean functions for both consecutive and uneven (full positive difference sets where possible) tap positions. The investigation reveals that in both cases, the m-tuple output is not uniform. However, consecutive tap positions result in a more biased distribution than uneven tap positions, with some m-tuples not occurring at all. These biased distributions indicate a potential flaw that could be exploited for cryptanalysis

Robust multidisciplinary design optimisation using CFD and advanced evolutionary algorithms

Computation Fluid Dynamics (CFD) has become an important tool in optimization and has seen successful in many real world applications. Most important among these is in the optimisation of aerodynamic surfaces which has become Multi-Objective (MO) and Multidisciplinary (MDO) in nature. Most of these have been carried out for a given set of input parameters such as free stream Mach number and angle of attack. One cannot ignore the fact that in aerospace engineering one frequently deals with situations where the design input parameters and flight/flow conditions have some amount of uncertainty attached to them. When the optimisation is carried out for fixed values of design variables and parameters however, one arrives at an optimised solution that results in good performance at design condition but poor drag or lift to drag ratio at slightly off-design conditions. The challenge is still to develop a robust design that accounts for uncertainty in the design in aerospace applications. In this paper this issue is taken up and an attempt is made to prevent the fluctuation of objective performance by using robust design technique or Uncertainty.

An innovative robust reactive surgery assignment model

Online scheduling in the Operating Theatre Department is a dynamic process that deals with both elective and emergency patients. Each business day begins with an elective schedule determined in advance based on a mastery surgery schedule. Throughout the course of the day however, disruptions to this baseline schedule occur due to variations in treatment time, emergency arrivals, equipment failure and resource unavailability. An innovative robust reactive surgery assignment model is developed for the operating theatre department. Following the completion of each surgery, the schedule is re-solved taking into account any disruptions in order to minimise cancellations of pre-planned patients and maximise throughput of emergency cases. The single theatre case is solved and future work on the computationally more complex multiple theatre case under resource constraints is discussed.

A robust structure and motion replacement for bundle adjustment

This paper demonstrates the application of a robust form of pose estimation and scene reconstruction using data from camera images. We demonstrate results that suggest the ability of the algorithm to rival methods of RANSAC based pose estimation polished by bundle adjustment in terms of solution robustness, speed and accuracy, even when given poor initialisations. Our simulated results show the behaviour of the algorithm in a number of novel simulated scenarios reflective of real world cases that show the ability of the algorithm to handle large observation noise and difficult reconstruction scenes. These results have a number of implications for the vision and robotics community, and show that the application of visual motion estimation on robotic platforms in an online fashion is approaching real-world feasibility.

A simple orientation robust transmit polarization signalling scheme

A special transmit polarization signalling scheme is presented to alleviate the power reduction as a result of polarization mismatch from random antenna orientations. This is particularly useful for hand held mobile terminals typically equipped with only a single linearly polarized antenna, since the average signal power is desensitized against receiver orientations. Numerical simulations also show adequate robustness against incorrect channel estimations.

Robust tracking control of autonomous underwater vehicles in the presence of disturbance inputs

An autonomous underwater vehicle (AUV) is expected to operate in an ocean in the presence of poorly known disturbance forces and moments. The uncertainties of the environment makes it difficult to apply open-loop control scheme for the motion planning of the vehicle. The objective of this paper is to develop a robust feedback trajectory tracking control scheme for an AUV that can track a prescribed trajectory amidst such disturbances. We solve a general problem of feedback trajectory tracking of an AUV in SE(3). The feedback control scheme is derived using Lyapunov-type analysis. The results obtained from numerical simulations confirm the asymptotic tracking properties of the feedback control law. We apply the feedback control scheme to different mission scenarios, with the disturbances being initial errors in the state of the AUV.