Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

Systematic variation of the severity of motor vehicle accident-related traumatic brain injury vignettes produces different post-concussion symptom reports

This study investigated the specificity of the post-concussion syndrome (PCS) expectation-as-etiology hypothesis. Undergraduate students (n = 551) were randomly allocated to one of three vignette conditions. Vignettes depicted either a very mild (VMI), mild (MI), or moderate-to-severe (MSI) motor vehicle-related traumatic brain injury (TBI). Participants reported the PCS and PTSD symptoms that they imagined the depicted injury would produce. Secondary outcomes (knowledge of mild TBI, and the perceived undesirability of TBI) were also assessed. After data screening, the distribution of participants by condition was: VMI (n = 100), MI (n = 96), and MSI (n = 71). There was a significant effect of condition on PCS symptomatology, F(2, 264) = 16.55, p < .001. Significantly greater PCS symptomatology was expected in the MSI condition compared to the other conditions (MSI > VMI; medium effect, r = .33; MSI > MI; small-to-medium effect, r = .22). The same pattern of group differences was found for PTSD symptoms, F(2, 264) = 17.12, p < .001. Knowledge of mild TBI was not related to differences in expected PCS symptoms by condition; and the perceived undesirability of TBI was only associated with reported PCS symptomatology in the MSI condition. Systematic variation in the severity of a depicted TBI produces different PCS and PTSD symptom expectations. Even a very mild TBI vignette can elicit expectations of PCS symptoms.

Does legal heritage affect obesity? The channel of motor vehicle dependence

We find a robust relationship between motor vehicle ownership, its interaction with legal heritage and obesity in OECD countries. Our estimates indicate that an increase of 100 motor vehicles per thousand residents is associated with about a 6% point increase in obesity in common law countries, whereas it has a much smaller or insignificant impact in civil law countries. These relations hold whether we examine trend data and simple correlations, or conduct cross-section or panel data regression analysis. Our results suggest that obesity rises with motor vehicle ownership in countries following a common law tradition where individual liberty is encouraged, whereas the link is small or statistically non-existent in countries with a civil law background where the rights of the individual tend to be circumscribed by the power of the state.

Power system sensitivity analysis considering induction motor loads

Power system operation and planning are facing increasing uncertainties especially with the deregulation process and increasing demand for power. Probabilistic power system stability assessment and probabilistic power system planning have been identified by EPRI as one of the important trends in power system operations and planning. Probabilistic small signal stability assessment studies the impact of system parameter uncertainties on system small disturbance stability characteristics. Researches in this area have covered many uncertainties factors such as controller parameter uncertainties and generation uncertainties. One of the most important factors in power system stability assessment is load dynamics. In this paper, composite load model is used to consider the uncertainties from load parameter uncertainties impact on system small signal stability characteristics. The results provide useful insight into the significant stability impact brought to the system by load dynamics. They can be used to help system operators in system operation and planning analysis.

Principles of motor learning in ecological dynamics : a comment on functions of learning and the acquisition of motor skills (with reference to sport)

This paper provides a commentary on the contribution by Dr Chow who questioned whether the functions of learning are general across all categories of tasks or whether there are some task-particular aspects to the functions of learning in relation to task type. Specifically, they queried whether principles and practice for the acquisition of sport skills are different than what they are for musical, industrial, military and human factors skills. In this commentary we argue that ecological dynamics contains general principles of motor learning that can be instantiated in specific performance contexts to underpin learning design. In this proposal, we highlight the importance of conducting skill acquisition research in sport, rather than relying on empirical outcomes of research from a variety of different performance contexts. Here we discuss how task constraints of different performance contexts (sport, industry, military, music) provide different specific information sources that individuals use to couple their actions when performing and acquiring skills. We conclude by suggesting that his relationship between performance task constraints and learning processes might help explain the traditional emphasis on performance curves and performance outcomes to infer motor learning.

The effect of exercise repetition on the frequency characteristics of motor output force : Implications for Achilles tendinopathy rehabilitation

Objectives: To investigate the frequency characteristics of the ground reaction force (GRF) recorded throughout the eccentric Achilles tendon rehabilitation programme described by Alfredson. Design: Controlled laboratory study, longitudinal. Methods: Nine healthy adult males performed six sets (15 repetitions per set) of eccentric ankle exercise. Ground reaction force was recorded throughout the exercise protocol. For each exercise repetition the frequency power spectrum of the resultant ground reaction force was calculated and normalised to total power. The magnitude of peak relative power within the 8-12 Hz bandwidth and the frequency at which this peak occurred was determined. Results: The magnitude of peak relative power within the 8-12 Hz bandwidth increased with each successive exercise set and following the 4th set (60 repetitions) of exercise the frequency at which peak relative power occurred shifted from 9 to 10 Hz. Conclusions: The increase in magnitude and frequency of ground reaction force vibrations with an increasing number of exercise repetitions is likely connected to changes in muscle activation with fatigue and tendon conditioning. This research illustrates the potential for the number of exercise repetitions performed to influence the tendons' mechanical environment, with implications for tendon remodelling and the clinical efficacy of eccentric rehabilitation programmes for Achilles tendinopathy.

Motor Accident Insurance Act 1994 - request for information

In Angus v Conelius [2007] QCA 190 the Queensland Court of Appeal concluded that the obligations under the Motor Accident Insurance Act 1994 (Qld), and in particular s 45 of the Act (duty of claimant to cooperate with insurer), continue beyond the commencement of court proceedings

Mixing and dispersion of pollutants emitted from an outboard motor

This paper quantifies the mixing and dispersion from an outboard motor by field experiments in a small subtropical waterway. Organic dye was used as a surrogate for exhaust emissions and was mixed with uncontaminated creek water before being dispersed into the creek. Dye concentrations were measured with an array of concentration probes stationed in the creek. The data were then processed and fitted with a power law function. The corresponding dispersion constants agreed well with the literature. However, the amplitude was lower than the IMO equation but higher than the correlation from laboratory tests. Results for dye concentration intermittency (presence of dye) are presented for the first time from such field measurements and show significant mixing in-homogeneity.

Vehicle energy throughput analysis as a drivetrain motor design aid

There are many variables to consider in the design of an electric motor. However, meeting the performance requirements for an electric vehicle drive may cause a designer to loose focus on its typical operation and hence fail to optimise the motor in the region where it processes the most power. This paper investigates operating requirements of electric vehicle motor drives using the University concept vehicle as an example. The paper outlines a methodology for determining primary operating region of a vehicle drive. The methodology is applied to standard driving cycles that are commonly used in the design and testing of vehicles.

Design considerations in an indirectly coupled multilevel motor controller

Permanent magnet (PM) motors utilising ironless stator structures have been incorporated into a wide variety of applications where high efficiency and stringent torque control are required. With recent developments in magnetic materials, improved design strategies, and power outputs of up to 40kW, PM motors have become an attractive candidate for traction drives in electric and hybrid electric vehicles. However, due to their large air gaps and ironless stators these motors can have inductances as low as 2μH, imposing increased requirements on the converter to minimise current ripple. Multilevel converters with n cells can effectively increase the motor inductance by a factor of n2 and are an excellent approach to minimise the motor ripple current. Furthermore by indirectly coupling the outputs of each cell, improvements in converter input and cell ripple current can also be realised. This paper examines the issues in designing a high current indirectly coupled multilevel motor controller for an ironless BLDC traction drive and highlights the limitations of the common ladder core structure.

Ironless wheel motor for a direct drive vehicle application

An ironless motor for use as direct wheel drive is presented. The motor is intended for use in a lightweight (600kg), low drag, series hybrid commuter vehicle under development at The University of Queensland. The vehicle will utilise these ironless motors in each of its rear wheels, with each motor producing a peak torque output of 500Nm and a maximum rotational speed of 1500rpm. The axial flux motor consists of twin Ironless litz wire stators with a central magnetic ring and simplified Halbach magnet arrays on either side. A small amount of iron is used to support the outer Halbach arrays and to improve the peak magnetic flux density. Ducted air cooling is used to remove heat from the motor and will allow for a continuous torque rating of 250Nm. Ironless machines have previously been shown to be effective in high speed, high frequency applications (+1000Hz). They are generally regarded as non-optimal for low speed applications as iron cores allow for better magnet utilisation and do not significantly increase the weight of a machine. However, ironless machines can also be seen to be effective in applications where the average torque requirement is much lower than the peak torque requirement such as in some vehicle drive applications. The low spinning losses in ironless machines are shown to result in very high energy throughput efficiency in a wide range of vehicle driving cycles.

How Can Models of Motor Control Be Useful for Understanding Low Back Pain?

Introduction. The purpose of this chapter is to address the question raised in the chapter title. Specifically, how can models of motor control help us understand low back pain (LBP)? There are several classes of models that have been used in the past for studying spinal loading, stability, and risk of injury (see Reeves and Cholewicki (2003) for a review of past modeling approaches), but for the purpose of this chapter we will focus primarily on models used to assess motor control and its effect on spine behavior. This chapter consists of 4 sections. The first section discusses why a shift in modeling approaches is needed to study motor control issues. We will argue that the current approach for studying the spine system is limited and not well-suited for assessing motor control issues related to spine function and dysfunction. The second section will explore how models can be used to gain insight into how the central nervous system (CNS) controls the spine. This segues segue nicely into the next section that will address how models of motor control can be used in the diagnosis and treatment of LBP. Finally, the last section will deal with the issue of model verification and validity. This issue is important since modelling accuracy is critical for obtaining useful insight into the behavior of the system being studied. This chapter is not intended to be a critical review of the literature, but instead intended to capture some of the discussion raised during the 2009 Spinal Control Symposium, with some elaboration on certain issues. Readers interested in more details are referred to the cited publications.

Visibility-related characteristics of crashes involving bicyclists and motor vehicles – Responses from an online questionnaire study

Bicyclists are among the most vulnerable of road users, with high fatal crash rates. Although visibility aids have been widely advocated to help prevent bicycle-vehicle conflicts, to date no study has investigated, among crash-involved cyclists, the kind of visibility aids they were using at the time of the crash. This study undertook a detailed investigation of visibility factors involved in bicyclist-motor-vehicle crashes. We surveyed 184 bicyclists (predominantly from Australia via internet cycling forums) who had been involved in motor vehicle collisions regarding the perceived cause of the collision, ambient weather and general visibility, as well as the clothing and bicycle lights used by the bicyclist. Over a third of the crashes occurred in low light levels (dawn, dusk or night-time), which is disproportionate given that only a small proportion of bicyclists typically ride at these times. Importantly, 19% of these bicyclists reported not using bicycle lights at the time of the crash, and only 34% were wearing reflective clothing. Only two participants (of 184) nominated bicyclist visibility as the cause of the crash: 61% attributed the crash to driver inattention. These findings demonstrate that crash-involved bicyclists tend to under-rate and under-utilise visibility aids as a means of improving their safety.