The use of computerised simulators for training of transthoracic and transoesophageal echocardiography. The future of echocardiographic training?

Echocardiography is the commonest form of non-invasive cardiac imaging and is fundamental to patient management. However, due to its methodology, it is also operator dependent. There are well defined pathways in training and ongoing accreditation to achieve and maintain competency. To satisfy these requirements, significant time has to be dedicated to scanning patients, often in the time pressured clinical environment. Alternative, computer based training methods are being considered to augment echocardiographic training. Numerous advances in technology have resulted in the development of interactive programmes and simulators to teach trainees the skills to perform particular procedures, including transthoracic and transoesophageal echocardiography. 82 sonographers and TOE proceduralists utilised an echocardiographic simulator and assessed its utility using defined criteria. 40 trainee sonographers assessed the simulator and were taught how to obtain an apical 2 chamber (A2C) view and image the superior vena cava (SVC). 100% and 88% found the simulator useful in obtaining the SVC or A2C view respectively. All users found it easy to use and the majority found it helped with image acquisition and interpretation. 42 attendees of a TOE training day utilising the simulator assessed the simulator with 100% finding it easy to use, as well as the augmented reality graphics benefiting image acquisition. 90% felt that it was realistic. This study revealed that both trainee sonographers and TOE proceduralists found the simulation process was realistic, helped in image acquisition and improved assessment of spatial relationships. Echocardiographic simulators may play an important role in the future training of echocardiographic skills.

A qualitative investigation of older pedestrian views of influences on their road crossing safety

With Australia’s population rapidly ageing, older pedestrian safety has begun to receive greater attention from road safety researchers. However, reliance on simulator studies and observational techniques has limited current understanding of why older pedestrians adopt particular crossing behaviours, and how they perceive crossing the road. The current study aimed to investigate the psychological factors that may contribute to older pedestrians’ crash risk by examining their perceptions of the issues they encounter on the road. Qualitative semi-structured interviews with 18 pedestrians aged 55 years and older were conducted, and the interview transcripts underwent thematic analysis. From this analysis, four key themes emerged. Firstly, the physical design of the road was perceived as posing a significant threat for older pedestrians, particularly sloped, semi-mountable kerbs and designated crossings. Secondly, declines in older pedestrians’ confidence in their ability to cross the road were evident through fewer reported risks being taken. Additionally, older pedestrians sensed an increased threat from other road users when crossing the road, particularly from drivers and cyclists. Finally, older pedestrians referred to the informal rules and strategies used to guide their road crossing. The results suggest that the road environment is perceived as increasingly dangerous and hazardous environment for older pedestrians. Implications regarding the physical road design in areas with an existing high proportion of elderly people are discussed.

Do drivers respond emotionally and behaviourally differently to an intentionally anger provoking driving situation than to an ambiguous, but potentially provocative, one? Results of a self-report survey.

Aggressive driving is considered an important road-safety concern for drivers in highly motorised countries. However, understanding of the causes and maintenance factors fundamental to aggressive driving is limited. In keeping with theoretical advances from general aggression research such as the General Aggression Model (GAM), research has begun to examine the emotional and cognitive antecedents of aggressive driving in order to better understand the underlying processes motivating aggressive driving. Early findings in the driving area have suggested that greater levels of aggression are elicited in response to an intentionally aggressive on-road event. In contrast, general aggression research suggests that greater levels of aggression are elicited in response to an ambiguous event. The current study examined emotional and cognitive responses to two hypothetical driving scenarios with differing levels of aggressive intent (intentional versus ambiguous). There was also an interest in whether factors influencing responses were different for hostile aggression (that is, where the action is intended to harm the other) versus instrumental aggression (that is, where the action is motivated by an intention to remove an impediment or attain a goal). Results were that significantly stronger negative emotion and negative attributions, as well as greater levels of threat were reported in response to the scenario which was designed to appear intentional in nature. In addition, participants were more likely to endorse an aggressive behavioural response to a situation that appeared deliberately aggressive than to one where the intention was ambiguous. Analyses to determine if greater levels of negative emotions and cognitions are able to predict aggressive responses provided different patterns of results for instrumental aggression from those for hostile aggression. Specifically, for instrumental aggression, negative emotions and negative attributions were significant predictors for both the intentional and the ambiguous scenarios. In addition, perceived threat was also a significant predictor where the other driver’s intent was clearly aggressive. However, lower rather than higher, levels of perceived threat were associated with greater endorsement of an aggressive response. For hostile aggressive behavioural responses, trait aggression was the strongest predictor for both situations. Overall the results suggest that in the driving context, instrumental aggression is likely to be a much more common response than hostile aggression. Moreover, aggressive responses are more likely in situations where another driver’s behaviour is clearly intentional rather than ambiguous. The results also support the conclusion that there may be different underlying mechanisms motivating an instrumental aggressive response to those motivating a hostile one. In addition, understanding the emotions and cognitions underlying aggressive driving responses may be helpful in predicting and intervening to reduce driving aggression. The finding that drivers appear to regard tailgating as an instrumental response is of concern since this behaviour has the potential to result in crashes.

Ensemble-based DDoS detection and mitigation model

This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.

Comparison and modification of car following models toward a more accurate microscopic simulation parameters reproduction

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers of motor vehicles exhibit safe behaviours. Several car-following models are used in various micro-simulation models. This research compares the mainstream car following models’ capabilities of emulating precise driver behaviour parameters such as headways and Time to Collisions. The comparison firstly illustrates which model is more robust in the metric reproduction. Secondly, the study conducted a series of sensitivity tests to further explore the behaviour of each model. Based on the outcome of these two steps exploration of the models, a modified structure and parameters adjustment for each car-following model is proposed to simulate more realistic vehicle movements, particularly headways and Time to Collision, below a certain critical threshold. NGSIM vehicle trajectory data is used to evaluate the modified models performance to assess critical safety events within traffic flow. The simulation tests outcomes indicate that the proposed modified models produce better frequency of critical Time to Collision than the generic models, while the improvement on the headway is not significant. The outcome of this paper facilitates traffic safety assessment using microscopic simulation.

Tax evasion, inequality, and progressive taxes : a political economy perspective

The standard approach to tax compliance applies the economics-of-crime methodology pioneered by Becker (1968): in its first application, due to Allingham and Sandmo (1972) it models the behaviour of agents as a decision involving a choice of the extent of their income to report to tax authorities, given a certain institutional environment, represented by parameters such as the probability of detection and penalties in the event the agent is caught. While this basic framework yields important insights on tax compliance behavior, it has some critical limitations. Specifically, it indicates a level of compliance that is significantly below what is observed in the data. This thesis revisits the original framework with a view towards addressing this issue, and examining the political economy implications of tax evasion for progressivity in the tax structure. The approach followed involves building a macroeconomic, dynamic equilibrium model for the purpose of examining these issues, by using a step-wise model building procedure starting with some very simple variations of the basic Allingham and Sandmo construct, which are eventually integrated to a dynamic general equilibrium overlapping generations framework with heterogeneous agents. One of the variations involves incorporating the Allingham and Sandmo construct into a two-period model of a small open economy of the type originally attributed to Fisher (1930). A further variation of this simple construct involves allowing agents to initially decide whether to evade taxes or not. In the event they decide to evade, the agents then have to decide the extent of income or wealth they wish to under-report. We find that the ‘evade or not’ assumption has strikingly different and more realistic implications for the extent of evasion, and demonstrate that it is a more appropriate modeling strategy in the context of macroeconomic models, which are essentially dynamic in nature, and involve consumption smoothing across time and across various states of nature. Specifically, since deciding to undertake tax evasion impacts on the consumption smoothing ability of the agent by creating two states of nature in which the agent is ‘caught’ or ‘not caught’, there is a possibility that their utility under certainty, when they choose not to evade, is higher than the expected utility obtained when they choose to evade. Furthermore, the simple two-period model incorporating an ‘evade or not’ choice can be used to demonstrate some strikingly different political economy implications relative to its Allingham and Sandmo counterpart. In variations of the two models that allow for voting on the tax parameter, we find that agents typically choose to vote for a high degree of progressivity by choosing the highest available tax rate from the menu of choices available to them. There is, however, a small range of inequality levels for which agents in the ‘evade or not’ model vote for a relatively low value of the tax rate. The final steps in the model building procedure involve grafting the two-period models with a political economy choice into a dynamic overlapping generations setting with more general, non-linear tax schedules and a ‘cost-of evasion’ function that is increasing in the extent of evasion. Results based on numerical simulations of these models show further improvement in the model’s ability to match empirically plausible levels of tax evasion. In addition, the differences between the political economy implications of the ‘evade or not’ version of the model and its Allingham and Sandmo counterpart are now very striking; there is now a large range of values of the inequality parameter for which agents in the ‘evade or not’ model vote for a low degree of progressivity. This is because, in the ‘evade or not’ version of the model, low values of the tax rate encourages a large number of agents to choose the ‘not-evade’ option, so that the redistributive mechanism is more ‘efficient’ relative to the situations in which tax rates are high. Some further implications of the models of this thesis relate to whether variations in the level of inequality, and parameters such as the probability of detection and penalties for tax evasion matter for the political economy results. We find that (i) the political economy outcomes for the tax rate are quite insensitive to changes in inequality, and (ii) the voting outcomes change in non-monotonic ways in response to changes in the probability of detection and penalty rates. Specifically, the model suggests that changes in inequality should not matter, although the political outcome for the tax rate for a given level of inequality is conditional on whether there is a large or small or large extent of evasion in the economy. We conclude that further theoretical research into macroeconomic models of tax evasion is required to identify the structural relationships underpinning the link between inequality and redistribution in the presence of tax evasion. The models of this thesis provide a necessary first step in that direction.

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

Can slide positivity rates predict malaria transmission?

Background: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China. Methods: Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. Results: The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (beta = 1.244, p = 0.000) alone and combination (SPR, beta = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates. Conclusion: SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

Diversity of dicotyledenous-infecting geminiviruses and their associated DNA molecules in Southern Africa, including the South-west Indian Ocean Islands

The family Geminiviridae comprises a group of plant-infecting circular ssDNA viruses that severely constrain agricultural production throughout the temperate regions of the world, and are a particularly serious threat to food security in sub-Saharan Africa. While geminiviruses exhibit considerable diversity in terms of their nucleotide sequences, genome structures, host ranges and insect vectors, the best characterised and economically most important of these viruses are those in the genus Begomovirus. Whereas begomoviruses are generally considered to be either monopartite (one ssDNA component) or bipartite (two circular ssDNA components called DNA-A and DNA-B), many apparently monopartite begomoviruses are associated with additional subviral ssDNA satellite components, called alpha- (DNA-αs) or betasatellites (DNA-βs). Additionally, subgenomic molecules, also known as defective interfering (DIs) DNAs that are usually derived from the parent helper virus through deletions of parts of its genome, are also associated with bipartite and monopartite begomoviruses. The past three decades have witnessed the emergence and diversification of various new begomoviral species and associated DI DNAs, in southern Africa, East Africa, and proximal Indian Ocean islands, which today threaten important vegetable and commercial crops such as, tobacco, cassava, tomato, sweet potato, and beans. This review aims to describe what is known about these viruses and their impacts on sustainable production in this sensitive region of the world. © 2012 by the authors licensee MDPI, Basel, Switzerland.

Recombination, decreased host specificity and increased mobility may have driven the emergence of maize streak virus as an agricultural pathogen

Maize streak virus (MSV; family Geminiviridae, genus Mastrevirus), the causal agent of maize streak disease, ranks amongst the most serious biological threats to food security in subSaharan Africa. Although five distinct MSV strains have been currently described, only one of these - MSV-A - causes severe disease in maize. Due primarily to their not being an obvious threat to agriculture, very little is known about the 'grass-adapted' MSV strains, MSV-B, -C, -D and -E. Since comparing the genetic diversities, geographical distributions and natural host ranges of MSV-A with the other MSV strains could provide valuable information on the epidemiology, evolution and emergence of MSV-A, we carried out a phylogeographical analysis of MSVs found in uncultivated indigenous African grasses. Amongst the 83 new MSV genomes presented here, we report the discovery of six new MSV strains (MSV-F to -K). The non-random recombination breakpoint distributions detectable with these and other available mastrevirus sequences partially mirror those seen in begomoviruses, implying that the forces shaping these breakpoint patterns have been largely conserved since the earliest geminivirus ancestors. We present evidence that the ancestor of all MSV-A variants was the recombinant progeny of ancestral MSV-B and MSV-G/-F variants. While it remains unknown whether recombination influenced the emergence of MSV-A in maize, our discovery that MSV-A variants may both move between and become established in different regions of Africa with greater ease, and infect more grass species than other MSV strains, goes some way towards explaining why MSV-A is such a successful maize pathogen. © 2008 SGM.

Comparative analysis of panicum streak virus and maize streak virus diversity, recombination patterns and phylogeography

Background: Panicum streak virus (PanSV; Family Geminiviridae; Genus Mastrevirus) is a close relative of Maize streak virus (MSV), the most serious viral threat to maize production in Africa. PanSV and MSV have the same leafhopper vector species, largely overlapping natural host ranges and similar geographical distributions across Africa and its associated Indian Ocean Islands. Unlike MSV, however, PanSV has no known economic relevance. Results: Here we report on 16 new PanSV full genome sequences sampled throughout Africa and use these together with others in public databases to reveal that PanSV and MSV populations in general share very similar patterns of genetic exchange and geographically structured diversity. A potentially important difference between the species, however, is that the movement of MSV strains throughout Africa is apparently less constrained than that of PanSV strains. Interestingly the MSV-A strain which causes maize streak disease is apparently the most mobile of all the PanSV and MSV strains investigated. Conclusion: We therefore hypothesize that the generally increased mobility of MSV relative to other closely related species such as PanSV, may have been an important evolutionary step in the eventual emergence of MSV-A as a serious agricultural pathogen. The GenBank accession numbers for the sequences reported in this paper are GQ415386-GQ415401. © 2009 Varsani et al; licensee BioMed Central Ltd.

Negotiating family, navigating resettlement : family connectedness amongst resettled youth with refugee backgrounds living in Melbourne, Australia

Refugee adolescents resettling in a new country face many challenges, and being part of a supportive family is a critical factor in assisting them to achieve wellbeing and create positive futures. This longitudinal study documents experiences of family life in the resettlement context of 120 young people with refugee backgrounds living in Melbourne, Australia. Family instability was a core feature of the early settlement period. In this paper, we focus specifically on changing household composition, and levels of trust, attachment, discipline and conflict in family settings during young people’s first years of resettlement. Our results suggest that while families are central to the wellbeing of these young people, changing family dynamics can also pose a threat to wellbeing and successful settlement. We argue that youth focused settlement services must explicitly engage with family contexts in assisting refugee youth to achieve wellbeing and successfully resettle.

Cross layer optimization of VANET routing with multi-objective decision making

Vehicular Ad-hoc Networks (VANET) have different characteristics compared to other mobile ad-hoc networks. The dynamic nature of the vehicles which act as routers and clients are connected with unreliable radio links and Routing becomes a complex problem. First we propose CO-GPSR (Cooperative GPSR), an extension of the traditional GPSR (Greedy Perimeter Stateless Routing) which uses relay nodes which exploit radio path diversity in a vehicular network to increase routing performance. Next we formulate a Multi-objective decision making problem to select optimum packet relaying nodes to increase the routing performance further. We use cross layer information for the optimization process. We evaluate the routing performance more comprehensively using realistic vehicular traces and a Nakagami fading propagation model optimized for highway scenarios in VANETs. Our results show that when Multi-objective decision making is used for cross layer optimization of routing a 70% performance increment can be obtained for low vehicle densities on average, which is a two fold increase compared to the single criteria maximization approach.

Power-law viscous materials for analogue experiments: New data on the rheology of highly-filled silicone polymers

The selection of appropriate analogue materials is a central consideration in the design of realistic physical models. We investigate the rheology of highly-filled silicone polymers in order to find materials with a power-law strain-rate softening rheology suitable for modelling rock deformation by dislocation creep and report the rheological properties of the materials as functions of the filler content. The mixtures exhibit strain-rate softening behaviour but with increasing amounts of filler become strain-dependent. For the strain-independent viscous materials, flow laws are presented while for strain-dependent materials the relative importance of strain and strain rate softening/hardening is reported. If the stress or strain rate is above a threshold value some highly-filled silicone polymers may be considered linear visco-elastic (strain independent) and power-law strain-rate softening. The power-law exponent can be raised from 1 to ~3 by using mixtures of high-viscosity silicone and plasticine. However, the need for high shear strain rates to obtain the power-law rheology imposes some restrictions on the usage of such materials for geodynamic modelling. Two simple shear experiments are presented that use Newtonian and power-law strain-rate softening materials. The results demonstrate how materials with power-law rheology result in better strain localization in analogue experiments.

Negotiating : experiences of community nurses when contracting with clients

A community nurse is required to have excellent interpersonal, teaching, collaborative and clinical skills in order to develop effective individualised client care contracts. Using a descriptive qualitative design data was collected from two focus groups of fourteen community nurses to explore the issues surrounding negotiating and contracting client care contracts from the perspective of community nurses. Thematic analysis revealed three themes: ‘assessment of needs’, ‘education towards enablement’, and ‘negotiation’. ‘Assessment of needs’ identified that community nurses assess both the client’s requirements for health care as well as the ability of the nurse to provide that care. ‘Education towards enablement’ described that education of the client is a common strategy used by community nurses to establish realistic goals of health care as part of developing an ongoing care plan. The final theme, ‘negotiation’, involved an informed agreement between the client and the community nurse which forms the origin of the care contract that will direct the partnership between the client and the nurse. Of importance for community nurses is that development of successful person-centred care contracts requires skillful negotiation of care that strikes the balance between the needs of the client and the ability of the nurse to meet those needs.