Letter to the editor : likelihood of tetraplegia after CT clearance of the cervical spine in obtunded blunt trauma patients

...the probabilistic computer simulation study by Dunham and colleagues evaluating the impact of different cervical spine management (CSM) strategies on tetraplegia and brain injury outcomes.1 Based on literature findings, expert opinion and with use of advances programming techniques the authors conclude that early collar removal without cervical spine magnetic resonance imaging (MRI) is a preferable CSM strategy for comatose, blunt trauma patients with extremity movement and a negative cervical spine computed tomography(CT) scan. Although we do not have the required expertise to comment on the applied statistical approach, we would like to comment on one of the medical assumptions raised by the authors, namely the likelihood of tetraplegia in this specific population....

Systematics of the Ustilago-Sporisorium-Macalpinomyces complex of smut fungi

Smut fungi are important pathogens of grasses, including the cultivated crops maize, sorghum and sugarcane. Typically, smut fungi infect the inflorescence of their host plants. Three genera of smut fungi (Ustilago, Sporisorium and Macalpinomyces) form a complex with overlapping morphological characters, making species placement problematic. For example, the newly described Macalpinomyces mackinlayi possesses a combination of morphological characters such that it cannot be unambiguously accommodated in any of the three genera. Previous attempts to define Ustilago, Sporisorium and Macalpinomyces using morphology and molecular phylogenetics have highlighted the polyphyletic nature of the genera, but have failed to produce a satisfactory taxonomic resolution. A detailed systematic study of 137 smut species in the Ustilago-Sporisorium- Macalpinomyces complex was completed in the current work. Morphological and DNA sequence data from five loci were assessed with maximum likelihood and Bayesian inference to reconstruct a phylogeny of the complex. The phylogenetic hypotheses generated were used to identify morphological synapomorphies, some of which had previously been dismissed as a useful way to delimit the complex. These synapomorphic characters are the basis for a revised taxonomic classification of the Ustilago-Sporisorium-Macalpinomyces complex, which takes into account their morphological diversity and coevolution with their grass hosts. The new classification is based on a redescription of the type genus Sporisorium, and the establishment of four genera, described from newly recognised monophyletic groups, to accommodate species expelled from Sporisorium. Over 150 taxonomic combinations have been proposed as an outcome of this investigation, which makes a rigorous and objective contribution to the fungal systematics of these important plant pathogens.

Trust-based automated recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbours, generated from a database made up of the preferences of past users. With sufficient background information of item ratings, its performance is promising enough but research shows that it performs very poorly in a cold start situation where there is not enough previous rating data. As an alternative to ratings, trust between the users could be used to choose the neighbour for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world "friend of a friend" recommendations. To extend the boundaries of the neighbour, an effective trust inference technique is required. This thesis proposes a trust interference technique called Directed Series Parallel Graph (DSPG) which performs better than other popular trust inference algorithms such as TidalTrust and MoleTrust. Another problem is that reliable explicit trust data is not always available. In real life, people trust "word of mouth" recommendations made by people with similar interests. This is often assumed in the recommender system. By conducting a survey, we can confirm that interest similarity has a positive relationship with trust and this can be used to generate a trust network for recommendation. In this research, we also propose a new method called SimTrust for developing trust networks based on user's interest similarity in the absence of explicit trust data. To identify the interest similarity, we use user's personalised tagging information. However, we are interested in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbours used in the automated recommender system. Our experimental results show that our proposed tag-similarity based method outperforms the traditional collaborative filtering approach which usually uses rating data.

CAT-SLAM : probabilistic localisation and mapping using a continuous appearance-based trajectory

This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

Novel methods and the maximum likelihood estimation technique for estimating traffic critical gap

Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.

Indigeneity and the likelihood of imprisonment in Queensland’s adult and children’s courts

Australian research on Indigenous sentencing disparities of the standard of international work is somewhat recent. Contrary to expectations based on international research, Australian studies generally have not found Indigenous offenders to be treated substantively more harshly than non-Indigenous offenders in similar circumstances. However, this research has primarily focused on adult higher courts, with little attention to lower courts and children’s courts. In this article, we examine whether Indigeneity has a direct impact on the judicial decision to incarcerate for three courts (adult higher, adult lower, children’s higher court) in Queensland. We found no significant differences in the likelihood of a sentence of incarceration in the higher courts (adult and children’s). In contrast, in the lower courts, Indigenous defendants were more likely to be imprisoned than non-Indigenous defendants when sentenced under statistically similar circumstances.

Exact and approximate Bayesian inference for low count time series models with intractable likelihoods

In this paper we present a new simulation methodology in order to obtain exact or approximate Bayesian inference for models for low-valued count time series data that have computationally demanding likelihood functions. The algorithm fits within the framework of particle Markov chain Monte Carlo (PMCMC) methods. The particle filter requires only model simulations and, in this regard, our approach has connections with approximate Bayesian computation (ABC). However, an advantage of using the PMCMC approach in this setting is that simulated data can be matched with data observed one-at-a-time, rather than attempting to match on the full dataset simultaneously or on a low-dimensional non-sufficient summary statistic, which is common practice in ABC. For low-valued count time series data we find that it is often computationally feasible to match simulated data with observed data exactly. Our particle filter maintains $N$ particles by repeating the simulation until $N+1$ exact matches are obtained. Our algorithm creates an unbiased estimate of the likelihood, resulting in exact posterior inferences when included in an MCMC algorithm. In cases where exact matching is computationally prohibitive, a tolerance is introduced as per ABC. A novel aspect of our approach is that we introduce auxiliary variables into our particle filter so that partially observed and/or non-Markovian models can be accommodated. We demonstrate that Bayesian model choice problems can be easily handled in this framework.

A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions

A quasi-maximum likelihood procedure for estimating the parameters of multi-dimensional diffusions is developed in which the transitional density is a multivariate Gaussian density with first and second moments approximating the true moments of the unknown density. For affine drift and diffusion functions, the moments are exactly those of the true transitional density and for nonlinear drift and diffusion functions the approximation is extremely good and is as effective as alternative methods based on likelihood approximations. The estimation procedure generalises to models with latent factors. A conditioning procedure is developed that allows parameter estimation in the absence of proxies.

School-based first aid training and the implications for traffic injury prevention : a randomised controlled trial

Adolescent injury remains a significant public health concern and is often the result of at-risk transport related behaviours. When a person is injured actions taken by bystanders are of crucial importance and timely first aid appears to reduce the severity of some injuries (Hussain & Redmond, 1994). Accordingly, researchers have suggested that first aid training should be more widely available as a potential strategy to reduce injury (Lynch et al., 2006). Further research has identified schools as an ideal setting for learning first aid skills as a means of injury prevention (Maitra, 1997). The current research examines the implications of school based first aid training for young adolescents on injury prevention, particularly relating to transport injuries. First aid training was integrated with peer protection and school connectedness within the Skills for Preventing Injury in Youth (SPIY) program (Buckley & Sheehan, 2009) and evaluated to determine if there was a reduction in the likelihood of transport related injuries at six months post-intervention. In Queensland, Australia, 35 high schools were recruited and randomly assigned to intervention and control conditions in early April 2012. A total of 2,000 Year nine students (mean age 13.5 years, 39% male) completed surveys six months post-intervention in November 2012. Analyses will compare the intervention students with control group students who self-reported i) first aid training with a teacher, professional or other adult and ii) no first aid in the preceding six months. Using the Extended Adolescent Injury Checklist (E-AIC) (Chapman, Buckley & Sheehan, 2011) the transport related injury experiences included being injured while “riding as a passenger in a car”, “driving a car off road” and “riding a bicycle”. It is expected that students taught first aid within SPIY will report significantly fewer transport related injuries in the previous three months, compared to the control groups described above. Analyses will be conducted separately for sex and socio-economic class of schools. Findings from this study will provide insight into the value of first aid in adolescent injury prevention and provide evidence as to whether teaching first aid skills within a school based health education curriculum has traffic safety implications.

Australian adolescents’ perceived school-based barriers and facilitators to engagement in physical activity

OBJECTIVE: School-aged youth spend a significant amount of time either in transit to and from school, or within school settings performing a range of varying learning-based activities. Adolescent physical activity has also been shown to increase the likelihood of maintaining physical activity throughout adulthood. The purpose of this study is to investigate adolescents’ perceived school-based barriers and facilitators to engagement in physical activity. METHODS: One-hundred and twenty four participants (38 males and 86 females) were recruited from two non-denominational same-sex private schools, in Brisbane, Australia. The mean age and standard deviation (SD) was 13.83 (0.56) and 14.40 (2.33) for males and females respectively. Participants responded to a series questions regarding perceived barriers and facilitators to engagement in physical activity. Quantitative data was analysed using descriptive statistics and frequency distributions, and qualitative data with thematic analysis. RESULTS: A total of 121 (97.6%) participants had complete data sets and were included in the analysis. School timetable (44.6%), homework (81.8%), and assessment (81.0%) were identified as the most prominent perceived factors, increasing the difficulty of physical activity engagement. Physical Education classes (71.9%) and school sport programs (80.2%) were identified as the most prominent perceived factors that facilitate engagement in physical activity. There was no significant gender effect. CONCLUSIONS: Each of the identified factors perceived by adolescent's as either barriers or facilitators to engagement in physical activity may be addressed by administrators at a school and government policy level. These may include strategies such as; increasing the assigned hours to physical education classes, providing additional extra-curricular sporting opportunities, and reviewing the time allocated to homework and assessment items. This may provide a simpler, low-cost solution to increasing youth physical activity, as opposed to contemporary higher-cost strategies utilising increased staff commitment, mass media, provision of equipment and counsellors and other health professionals.

Developing targets and strategies for school-based injury prevention programs to reduce alcohol associated transport risks

Background There is considerable and ongoing debate about the role and effectiveness of school-based injury prevention programs in reducing students’ later involvement in alcohol associated transport injuries. Most relevant literature is concerned with pre-driving and licensing programs for middle age range adolescents (15-17 years). This research team is concerned with prevention at an earlier stage by targeting interventions to young adolescents (13-14 years). There is strong evidence that young adolescents who engage in unsafe and illegal alcohol associated transport risks are significantly likely to incur serious related injuries in longitudinal follow up. For example, a state-wide representative sample of male adolescents (mean age 14.5 years) who reported being passengers of drink drivers were significantly more likely to have incurred a hospitalised injury related to traffic events at a 20 year follow up. Aim This paper reports on first aid training integrated with peer protection and school connectedness within the Skills for Preventing Injury in Youth (SPIY) program. A component of the intervention is concerned with providing strategies to reduce the likelihood of being a passenger of a drink driver and effectiveness is followed up at six months post-intervention. Method In early 2012 the study was undertaken in 35 high schools throughout Queensland that were randomly assigned to intervention and control conditions. A total of 2,521 Year 9 students (mean age 13.5years, 43% male) completed surveys prior to the intervention. Results Of these students 316 (13.7%) reported having ridden in a car with someone who has been drinking. This is a traffic safety behaviour that is particularly relevant to a peer protection intervention and the findings of the six month follow up will be reported. Discussion and conclusions This research will provide evidence as to whether this approach to the introduction of first aid skills within a school-based health education curriculum has traffic safety implications.

An intuitive dashboard for Bayesian network inference

Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

Odometry-driven inference to link multiple exemplars of a location

A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.

Mechanism based emulation of dynamic simulation models : concept and application in hydrology

Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emulators, by providing efficient interpolation between outputs of deterministic simulation models, can considerably extend the field of applicability of such computationally demanding techniques. So far, the dominant techniques for developing emulators have been priors in the form of Gaussian stochastic processes (GASP) that were conditioned with a design data set of inputs and corresponding model outputs. In the context of dynamic models, this approach has two essential disadvantages: (i) these emulators do not consider our knowledge of the structure of the model, and (ii) they run into numerical difficulties if there are a large number of closely spaced input points as is often the case in the time dimension of dynamic models. To address both of these problems, a new concept of developing emulators for dynamic models is proposed. This concept is based on a prior that combines a simplified linear state space model of the temporal evolution of the dynamic model with Gaussian stochastic processes for the innovation terms as functions of model parameters and/or inputs. These innovation terms are intended to correct the error of the linear model at each output step. Conditioning this prior to the design data set is done by Kalman smoothing. This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small. The feasibility and potential difficulties of the proposed approach are demonstrated by the application to a simple hydrological model.