Virtual training environments to improve train driver's crisis decision making

This paper reports on a current research project in which virtual reality simulators are being investigated as a means of simulating hazardous Rail work conditions in order to allow train drivers to practice decision-making under stress. When working under high stress conditions train drivers need to move beyond procedural responses into a response activated through their own problem-solving and decision-making skills. This study focuses on the use of stress inoculation training which aims to build driver’s confidence in the use of new decision-making skills by being repeatedly required to respond to hazardous driving conditions. In particular, the study makes use of a train cab driving simulator to reproduce potentially stress inducing real-world scenarios. Initial pilot research has been undertaken in which drivers have experienced the training simulation and subsequently completed surveys on the level of immersion experienced. Concurrently drivers have also participated in a velocity perception experiment designed to objectively measure the fidelity of the virtual training environment. Baseline data, against which decision-making skills post training will be measured, is being gathered via cognitive task analysis designed to identify primary decision requirements for specific rail events. While considerable efforts have been invested in improving Virtual Reality technology, little is known about how to best use this technology for training personnel to respond to workplace conditions in the Rail Industry. To enable the best use of simulators for training in the Rail context the project aims to identify those factors within virtual reality that support required learning outcomes and use this information to design training simulations that reliably and safely train staff in required workplace accident response skills.

User guide for shock and blast simulation with the OctVCE code (version 3.5+), Department of Mechanical Engineering Report 2007/13

OctVCE is a cartesian cell CFD code produced especially for numerical simulations of shock and blast wave interactions with complex geometries. Virtual Cell Embedding (VCE) was chosen as its cartesian cell kernel as it is simple to code and sufficient for practical engineering design problems. This also makes the code much more ‘user-friendly’ than structured grid approaches as the gridding process is done automatically. The CFD methodology relies on a finite-volume formulation of the unsteady Euler equations and is solved using a standard explicit Godonov (MUSCL) scheme. Both octree-based adaptive mesh refinement and shared-memory parallel processing capability have also been incorporated. For further details on the theory behind the code, see the companion report 2007/12.

Gaze angle: a possible mechanism of visual stress in virtual reality headsets

It is known that some Virtual Reality (VR) head-mounted displays (HMDs) can cause temporary deficits in binocular vision. On the other hand, the precise mechanism by which visual stress occurs is unclear. This paper is concerned with a potential source of visual stress that has not been previously considered with regard to VR systems: inappropriate vertical gaze angle. As vertical gaze angle is raised or lowered the 'effort' required of the binocular system also changes. The extent to which changes in vertical gaze angle alter the demands placed upon the vergence eye movement system was explored. The results suggested that visual stress may depend, in part, on vertical gaze angle. The proximity of the display screens within an HMD means that a VR headset should be in the correct vertical location for any individual user. This factor may explain some previous empirical results and has important implications for headset design. Fortuitously, a reasonably simple solution exists.

A reproducible method for automated extraction of brain volumes from 3D human head MR images

An automated method for extracting brain volumes from three commonly acquired three-dimensional (3D) MR images (proton density, T1 weighted, and T2-weighted) of the human head is described. The procedure is divided into four levels: preprocessing, segmentation, scalp removal, and postprocessing. A user-provided reference point is the sole operator-dependent input required, The method's parameters were first optimized and then fixed and applied to 30 repeat data sets from 15 normal older adult subjects to investigate its reproducibility. Percent differences between total brain volumes (TBVs) for the subjects' repeated data sets ranged from .5% to 2.2%. We conclude that the method is both robust and reproducible and has the potential for wide application.

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

Applications of accurate, high-precision Pb isotope ratio measurement by multi-collector ICP-MS

The isotope composition of Ph is difficult to determine accurately due to the lack of a stable normalisation ratio. Double and triple-spike addition techniques provide one solution and presently yield the most accurate measurements. A number of recent studies have claimed that improved accuracy and precision could also be achieved by multi-collector ICP-MS (MC-ICP-MS) Pb-isotope analysis using the addition of Tl of known isotope composition to Pb samples. In this paper, we verify whether the known isotope composition of Tl can be used for correction of mass discrimination of Pb with an extensive dataset for the NIST standard SRM 981, comparison of MC-ICP-MS with TIMS data, and comparison with three isochrons from different geological environments. When all our NIST SRM 981 data are normalised with one constant Tl-205/Tl-203 of 2.38869, the following averages and reproducibilities were obtained: Pb-207/Pb-206=0.91461+/-18; Pb-208/Ph-206 = 2.1674+/-7; and (PbPh)-Pb-206-Ph-204 = 16.941+/-6. These two sigma standard deviations of the mean correspond to 149, 330, and 374 ppm, respectively. Accuracies relative to triple-spike values are 149, 157, and 52 ppm, respectively, and thus well within uncertainties. The largest component of the uncertainties stems from the Ph data alone and is not caused by differential mass discrimination behaviour of Ph and Tl. In routine operation, variation of sample introduction memory and production of isobaric molecular interferences in the spectrometer's collision cell currently appear to be the ultimate limitation to better reproducibility. Comparative study of five different datasets from actual samples (bullets, international rock standards, carbonates, metamorphic minerals, and sulphide minerals) demonstrates that in most cases geological scatter of the sample exceeds the achieved analytical reproducibility. We observe good agreement between TIMS and MC-ICP-MS data for international rock standards but find that such comparison does not constitute the ultimate. test for the validity of the MC-ICP-MS technique. Two attempted isochrons resulted in geological scatter (in one case small) in excess of analytical reproducibility. However, in one case (leached Great Dyke sulphides) we obtained a true isochron (MSWD = 0.63) age of 2578.3 +/- 0.9 Ma, which is identical to and more precise than a recently published U-Pb zircon age (2579 3 Ma) for a Great Dyke websterite [Earth Planet. Sci. Lett. 180 (2000) 1-12]. Reproducibility of this age by means of an isochron we regard as a robust test of accuracy over a wide dynamic range. We show that reliable and accurate Pb-isotope data can be obtained by careful operation of second-generation MC-ICP magnetic sector mass spectrometers. (C) 2002 Elsevier Science B.V. All rights reserved.

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they sample. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 'near-isolines' of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 'drought environment types' (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.