Preface to special issue on digital human modelling for vehicle design and manufacturing

The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.

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).

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Using staffing ratios for workforce planning : evidence on nine allied health professions - a narrative review

Background: Modern healthcare managers are faced with pressure to deliver effective, efficient services within the context of fixed budget constraints. This requires decisions regarding the skill mix of the workforce particularly when staffing new services. One measure used to identify numbers and mix of staff in healthcare settings is workforce ratio. The aim of this study was to identify workforce ratios in nine allied health professions and to identify whether these measures are useful for planning allied health workforce requirements. Method: A systematic literature search using relevant MeSH headings of business, medical and allied health databases and relevant grey literature for the period 2000-2008 was undertaken. Results: Twelve articles were identified which described the use of workforce ratios in allied health services. Only one of these was a staffing ratio linked to clinical outcomes. The most comprehensive measures were identified in rehabilitation medicine. Conclusions: The evidence for use of staffing ratios for allied health practitioners is scarce and lags behind the fields of nursing and medicine.

A coupled SPH-DEM model for fluid and solid mechanics of apple parenchyma cells during drying

A coupled SPH-DEM based two-dimensional (2-D) micro-scale single cell model is developed to predict basic cell-level shrinkage effects of apple parenchyma cells during air drying. In this newly developed drying model, Smoothed Particle Hydrodynamics (SPH) is used to model the low Reynolds Number fluid motions of the cell protoplasm, and a Discrete Element Method (DEM) is employed to simulate the polymer-like cell wall. Simulations results reasonably agree with published experimental drying results on cellular shrinkage properties such as cellular area, diameter and perimeter. These preliminary results indicate that the model is effective for the modelling and simulation of apple parenchyma cells during air drying.

A particle-based micromechanics approach to simulate structural changes of plant cells during drying

This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

A simulation-based training system for surgical wound debridement

A simulation-based training system for surgical wound debridement was developed and comprises a multimedia introduction, a surgical simulator (tutorial component), and an assessment component. The simulator includes two PCs, a haptic device, and mirrored display. Debridement is performed on a virtual leg model with a shallow laceration wound superimposed. Trainees are instructed to remove debris with forceps, scrub with a brush, and rinse with saline solution to maintain sterility. Research and development issues currently under investigation include tissue deformation models using mass-spring system and finite element methods; tissue cutting using a high-resolution volumetric mesh and dynamic topology; and accurate collision detection, cutting, and soft-body haptic rendering for two devices within the same haptic space.

Challenging Mining Workforce Practices : Implications for Frontline Rural Communities

Global demand for minerals and energy products has fuelled Australia’s recent ‘resources boom’ and led to the rapid expansion of mining projects not solely in remote regions but increasingly in long-settled traditionally agriculture-dependent rural areas. Not only has this activity radically changed the economic geography of the nation but a fundamental shift has also occurred to accommodate the acceleration in industry labour demands. In particular, the rush to mine has seen the entrenchment of workforce arrangements largely dependent on fly-in, fly-out (FIFO) and drive–in, drive–out (DIDO) workers. This form of employment has been highly contentious in rural communities at the frontline of resource sector activities. In the context of structural sweeping changes, the selection of study locations informed by a range of indices of violence. Serendipitously we carried out fieldwork in communities undergoing rapid change as a result of expanding resource sector activities. The presence of large numbers of non-resident FIFO and DIDO workers was transforming these frontline communities. This chapter highlights some implications of these changes, drawing upon one particular location, which historically depended on agriculture but has undergone redefinition through mining.

Micromarrows—Three-dimensional coculture of hematopoietic stem cells and mesenchymal stromal cells

Hematopoietic stem cell (HSC) transplant is a well established curative therapy for some hematological malignancies. However, achieving adequate supply of HSC from some donor tissues can limit both its application and ultimate efficacy. The theory that this limitation could be overcome by expanding the HSC population before transplantation has motivated numerous laboratories to develop ex vivo expansion processes. Pioneering work in this field utilized stromal cells as support cells in cocultures with HSC to mimic the HSC niche. We hypothesized that through translation of this classic coculture system to a three-dimensional (3D) structure we could better replicate the niche environment and in turn enhance HSC expansion. Herein we describe a novel high-throughput 3D coculture system where murine-derived HSC can be cocultured with mesenchymal stem/stromal cells (MSC) in 3D microaggregates—which we term “micromarrows.” Micromarrows were formed using surface modified microwells and their ability to support HSC expansion was compared to classic two-dimensional (2D) cocultures. While both 2D and 3D systems provide only a modest total cell expansion in the minimally supplemented medium, the micromarrow system supported the expansion of approximately twice as many HSC candidates as the 2D controls. Histology revealed that at day 7, the majority of bound hematopoietic cells reside in the outer layers of the aggregate. Quantitative polymerase chain reaction demonstrates that MSC maintained in 3D aggregates express significantly higher levels of key hematopoietic niche factors relative to their 2D equivalents. Thus, we propose that the micromarrow platform represents a promising first step toward a high-throughput HSC 3D coculture system that may enable in vitro HSC niche recapitulation and subsequent extensive in vitro HSC self-renewal.

Young children’s metarepresentational competence in data modelling

longitudinal study of data modelling across grades 1-3. The activity engaged children in designing, implementing, and analysing a survey about their new playground. Data modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. The core components of data modelling addressed here are children’s structuring and representing of data, with a focus on their display of metarepresentational competence (diSessa, 2004). Such competence includes students’ abilities to invent or design a variety of new representations, explain their creations, understand the role they play, and critique and compare the adequacy of representations. Reported here are the ways in which the children structured and represented their data, the metarepresentational competence displayed, and links between their metarepresentational competence and conceptual competence.

Welfare reform, surveillance and new paternalism

This paper discusses the situation of welfare claimants, often constructed as faulty citizens and flawed welfare subjects. Many are on the receiving end of complex, multi-layered forms of surveillance aimed at securing socially responsible and compliant behaviours. In Australia, as in other Western countries, neoliberal economic regimes with their harsh and often repressive treatment of welfare recipients operate in tandem with a burgeoning and costly arsenal of CCTV and other surveillance and governance assemblages. The Australian Government’s Centrelink BasicsCard is but one example of welfare surveillance, whereby a percentage of a welfare claimant’s allowances must be spent on ‘approved’ items. The BasicsCard which has perhaps slipped under the radar of public discussion and is expanding nationally, raises significant questions about whether it is possible to encourage people to take responsibility for themselves if they no longer have real control over the most important aspects of their lives. Resistance and critical feedback, particularly from Indigenous people, points to a loss of dignity around the imposition of income management, operational complexity and denial of individual agency in using the BasicsCard, alongside the contradiction of apparently becoming ‘self-reliant’ through being income managed by the welfare state. This paper highlights the lack of solid evidence for the implementation/imposition of the BasicsCard and points to the importance of developing critically based research to inform the enactment of evidence based policy, also acting as a touchstone for governmental accountability. In highlighting issues around the BasicsCard this paper makes a contribution to the largely under discussed area of income management and the growth of welfare surveillance in Australia.

Front interactions in a three-component system

The three-component reaction-diffusion system introduced in [C. P. Schenk et al., Phys. Rev. Lett., 78 (1997), pp. 3781–3784] has become a paradigm model in pattern formation. It exhibits a rich variety of dynamics of fronts, pulses, and spots. The front and pulse interactions range in type from weak, in which the localized structures interact only through their exponentially small tails, to strong interactions, in which they annihilate or collide and in which all components are far from equilibrium in the domains between the localized structures. Intermediate to these two extremes sits the semistrong interaction regime, in which the activator component of the front is near equilibrium in the intervals between adjacent fronts but both inhibitor components are far from equilibrium there, and hence their concentration profiles drive the front evolution. In this paper, we focus on dynamically evolving N-front solutions in the semistrong regime. The primary result is use of a renormalization group method to rigorously derive the system of N coupled ODEs that governs the positions of the fronts. The operators associated with the linearization about the N-front solutions have N small eigenvalues, and the N-front solutions may be decomposed into a component in the space spanned by the associated eigenfunctions and a component projected onto the complement of this space. This decomposition is carried out iteratively at a sequence of times. The former projections yield the ODEs for the front positions, while the latter projections are associated with remainders that we show stay small in a suitable norm during each iteration of the renormalization group method. Our results also help extend the application of the renormalization group method from the weak interaction regime for which it was initially developed to the semistrong interaction regime. The second set of results that we present is a detailed analysis of this system of ODEs, providing a classification of the possible front interactions in the cases of $N=1,2,3,4$, as well as how front solutions interact with the stationary pulse solutions studied earlier in [A. Doelman, P. van Heijster, and T. J. Kaper, J. Dynam. Differential Equations, 21 (2009), pp. 73–115; P. van Heijster, A. Doelman, and T. J. Kaper, Phys. D, 237 (2008), pp. 3335–3368]. Moreover, we present some results on the general case of N-front interactions.

ASAP ECMO : antibiotic, sedative and analgesic pharmacokinetics during extracorporeal membrane oxygenation : a multi-centre study to optimise drug therapy during ECMO

BACKGROUND: Given the expanding scope of extracorporeal membrane oxygenation (ECMO) and its variable impact on drug pharmacokinetics as observed in neonatal studies, it is imperative that the effects of the device on the drugs commonly prescribed in the intensive care unit (ICU) are further investigated. Currently, there are no data to confirm the appropriateness of standard drug dosing in adult patients on ECMO. Ineffective drug regimens in these critically ill patients can seriously worsen patient outcomes. This study was designed to describe the pharmacokinetics of the commonly used antibiotic, analgesic and sedative drugs in adult patients receiving ECMO. METHODS: This is a multi-centre, open-label, descriptive pharmacokinetic (PK) study. Eligible patients will be adults treated with ECMO for severe cardiac and/or respiratory failure at five Intensive Care Units in Australia and New Zealand. Patients will receive the study drugs as part of their routine management. Blood samples will be taken from indwelling catheters to investigate plasma concentrations of several antibiotics (ceftriaxone, meropenem, vancomycin, ciprofloxacin, gentamicin, piperacillin-tazobactum, ticarcillin-clavulunate, linezolid, fluconazole, voriconazole, caspofungin, oseltamivir), sedatives and analgesics (midazolam, morphine, fentanyl, propofol, dexmedetomidine, thiopentone). The PK of each drug will be characterised to determine the variability of PK in these patients and to develop dosing guidelines for prescription during ECMO. DISCUSSION: The evidence-based dosing algorithms generated from this analysis can be evaluated in later clinical studies. This knowledge is vitally important for optimising pharmacotherapy in these most severely ill patients to maximise the opportunity for therapeutic success and minimise the risk of therapeutic failure

The case for good reviewing

After some years of remarkable growth, the scholarly field of Project Management (PM) research currently finds itself in a crucial stage of development. In this editorial, we make an analysis of submissions to PM's premier specialty journal, the International Journal of Project Management over the period 2007–2010, and argue that one of the most important ways in which PM research can further evolve is to pay more attention to the mundane, yet important, act of good reviewing — an activity that we believe has received relatively little attention in the PM community thus far. Let us begin by considering the crucial juncture that, as a scholarly discipline, PM is currently at. On the one hand, the PM research field is characterized by signs of major progress. For one, there has been a strong growth in terms of published output: recent years have seen the publication of three major edited volumes with a central focus on PM, published by top-tier publishers (Cattani et al., 2011, Kenis et al., 2009 and Morris et al., 2011); the PM/temporary organizations literature published in ISI ranked peer-reviewed articles is growing exponentially (Bakker, 2010); and besides some of the long-standing PM specialty journals, the field has recently seen the rise of a number of new journals, including the International Journal of Managing Projects in Business, the International Journal of Project Organisation and Management, and the Journal of Project, Program, and Portfolio Management.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.