The origin of a large (>3km) maar volcano by coalescence of multiple shallow craters: Lake Purrumbete maar, southeastern Australia

Lake Purrumbete maar is located in the intraplate, monogenetic Newer Volcanics Province in southeastern Australia. The extremely large crater of 3000. m in diameter formed on an intersection of two fault lines and comprises at least three coalesced vents. The evolution of these vents is controlled by the interaction of the tectonic setting and the properties of both hard and soft rock aquifers. Lithics in the maar deposits originate from country rock formations less than 300. m deep, indicating that the large size of the crater cannot only be the result of the downwards migration of the explosion foci in a single vent. Vertical crater walls and primary inward dipping beds evidence that the original size of the crater has been largely preserved. Detailed mapping of the facies distributions, the direction of transport of base surges and pyroclastic flows, and the distribution of ballistic block fields, form the basis for the reconstruction of the complex eruption history,which is characterised by alternations of the eruption style between relatively dry and wet phreatomagmatic conditions, and migration of the vent location along tectonic structures. Three temporally separated eruption phases are recognised, each starting at the same crater located directly at the intersection of two local fault lines. Activity then moved quickly to different locations. A significant volcanic hiatus between two of the three phases shows that the magmatic system was reactivated. The enlargement of especially the main crater by both lateral and vertical growth led to the interception of the individual craters and the formation of the large circular crater. Lake Purrumbete maar is an excellent example of how complicated the evolution of large, seemingly simple, circular maar volcanoes can be, and raises the question if these systems are actually monogenetic.

Substation Automation Systems – Future possibilities for commissioning

Substation Automation Systems have undergone many transformational changes triggered by improvements in technologies. Prior to the digital era, it made sense to confirm that the physical wiring matched the schematic design by meticulous and laborious point to point testing. In this way, human errors in either the design or the construction could be identified and fixed prior to entry into service. However, even though modern secondary systems today are largely computerised, we are still undertaking commissioning testing using the same philosophy as if each signal were hard wired. This is slow and tedious and doesn’t do justice to modern computer systems and software automation. One of the major architectural advantages of the IEC 61850 standard is that it “abstracts” the definition of data and services independently of any protocol allowing the mapping of them to any protocol that can meet the modelling and performance requirements. On this basis, any substation element can be defined using these common building blocks and are made available at the design, configuration and operational stages of the system. The primary advantage of accessing data using this methodology rather than the traditional position method (such as DNP 3.0) is that generic tools can be created to manipulate data. Self-describing data contains the information that these tools need to manipulate different data types correctly. More importantly, self-describing data makes the interface between programs robust and flexible. This paper proposes that the improved data definitions and methods for dealing with this data within a tightly bound and compliant IEC 61850 Substation Automation System could completely revolutionise the need to test systems when compared to traditional point to point methods. Using the outcomes of an undergraduate thesis project, we can demonstrate with some certainty that it is possible to automatically test the configuration of a protection relay by comparing the IEC 61850 configuration extracted from the relay against its SCL file for multiple relay vendors. The software tool provides a quick and automatic check that the data sets on a particular relay are correct according to its CID file, thus ensuring that no unexpected modifications are made at any stage of the commissioning process. This tool has been implemented in a Java programming environment using an open source IEC 61850 library to facilitate the server-client association with the relay.

Engaging a multiple-track approach to building capacity for 21st Century engineering, opportunities and challenges for rapid curriculum renewal

‘Complexity’ is a term that is increasingly prevalent in conversations about building capacity for 21st Century professional engineers. Society is grappling with the urgent and challenging reality of accommodating seven billion people, meeting needs and innovating lifestyle improvements in ways that do not destroy atmospheric, biological and oceanic systems critical to life. Over the last two decades in particular, engineering educators have been active in attempting to build capacity amongst professionals to deliver ‘sustainable development’ in this rapidly changing global context. However curriculum literature clearly points to a lack of significant progress, with efforts best described as ad hoc and highly varied. Given the limited timeframes for action to curb environmental degradation proposed by scientists and intergovernmental agencies, the authors of this paper propose it is imperative that curriculum renewal towards education for sustainable development proceeds rapidly, systemically, and in a transformational manner. Within this context, the paper discusses the need to consider a multiple track approach to building capacity for 21st Century engineering, including priorities and timeframes for undergraduate and postgraduate curriculum renewal. The paper begins with a contextual discussion of the term complexity and how it relates to life in the 21st Century. The authors then present a whole of system approach for planning and implementing rapid curriculum renewal that addresses the critical roles of several generations of engineering professionals over the next three decades. The paper concludes with observations regarding engaging with this approach in the context of emerging accreditation requirements and existing curriculum renewal frameworks.

Revising history for cost-informed process improvement

Organisations are constantly seeking new ways to improve operational efficiencies. This study investigates a novel way to identify potential efficiency gains in business operations by observing how they were carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how these trade-offs can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A number of optimisation techniques are proposed to explore and assess alternative execution scenarios. The objective function is represented by a cost structure that captures different process dimensions. An experimental evaluation is conducted to analyse the performance and scalability of the optimisation techniques: integer linear programming (ILP), hill climbing, tabu search, and our earlier proposed hybrid genetic algorithm approach. The findings demonstrate that the hybrid genetic algorithm is scalable and performs better compared to other techniques. Moreover, we argue that the use of ILP is unrealistic in this setup and cannot handle complex cost functions such as the ones we propose. Finally, we show how cost-related insights can be gained from improved execution scenarios and how these can be utilised to put forward recommendations for reducing process-related cost and overhead within organisations.

Structural identification of a laboratory-based steel through truss cantilevered bridge with suspended span using a layered genetic algorithm with patternsearch step (GAPS)

Structural identification (St-Id) can be considered as the process of updating a finite element (FE) model of a structural system to match the measured response of the structure. This paper presents the St-Id of a laboratory-based steel through-truss cantilevered bridge with suspended span. There are a total of 600 degrees of freedom (DOFs) in the superstructure plus additional DOFs in the substructure. The St-Id of the bridge model used the modal parameters from a preliminary modal test in the objective function of a global optimisation technique using a layered genetic algorithm with patternsearch step (GAPS). Each layer of the St-Id process involved grouping of the structural parameters into a number of updating parameters and running parallel optimisations. The number of updating parameters was increased at each layer of the process. In order to accelerate the optimisation and ensure improved diversity within the population, a patternsearch step was applied to the fittest individuals at the end of each generation of the GA. The GAPS process was able to replicate the mode shapes for the first two lateral sway modes and the first vertical bending mode to a high degree of accuracy and, to a lesser degree, the mode shape of the first lateral bending mode. The mode shape and frequency of the torsional mode did not match very well. The frequencies of the first lateral bending mode, the first longitudinal mode and the first vertical mode matched very well. The frequency of the first sway mode was lower and that of the second sway mode was higher than the true values, indicating a possible problem with the FE model. Improvements to the model and the St-Id process will be presented at the upcoming conference and compared to the results presented in this paper. These improvements will include the use of multiple FE models in a multi-layered, multi-solution, GAPS St-Id approach.

Pull the plug or take the plunge: Multiple opportunities and the speed of venturing decisions in the Australian mining industry

Effectively capturing opportunities requires rapid decision-making. We investigate the speed of opportunity evaluation decisions by focusing on firms' venture termination and venture advancement decisions. Experience, standard operating procedures, and confidence allow firms to make opportunity evaluation decisions faster; we propose that a firm's attentional orientation, as reflected in its project portfolio, limits the number of domains in which these speed-enhancing mechanisms can be developed. Hence firms' decision speed is likely to vary between different types of decisions. Using unique data on 3,269 mineral exploration ventures in the Australian mining industry, we find that firms with a higher degree of attention toward earlier-stage exploration activities are quicker to abandon potential opportunities in early development but slower to do so later, and that such firms are also slower to advance on potential opportunities at all stages compared to firms that focus their attention differently. Market dynamism moderates these relationships, but only with regard to initial evaluation decisions. Our study extends research on decision speed by showing that firms are not necessarily fast or slow regarding all the decisions they make, and by offering an opportunity evaluation framework that recognizes that decision makers can, in fact often do, pursue multiple potential opportunities simultaneously.

Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

Labeling white matter tracts in hardi by fusing multiple tract atlases with applications to genetics

Accurate identification of white matter structures and segmentation of fibers into tracts is important in neuroimaging and has many potential applications. Even so, it is not trivial because whole brain tractography generates hundreds of thousands of streamlines that include many false positive fibers. We developed and tested an automatic tract labeling algorithm to segment anatomically meaningful tracts from diffusion weighted images. Our multi-atlas method incorporates information from multiple hand-labeled fiber tract atlases. In validations, we showed that the method outperformed the standard ROI-based labeling using a deformable, parcellated atlas. Finally, we show a high-throughput application of the method to genetic population studies. We use the sub-voxel diffusion information from fibers in the clustered tracts based on 105-gradient HARDI scans of 86 young normal twins. The whole workflow shows promise for larger population studies in the future.

Automatic population HARDI white matter tract clustering by label fusion of multiple tract atlases

Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

Predicting white matter integrity from multiple common genetic variants

Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

Multiple stages classification of Alzheimer’s disease based on structural brain networks using generalized low rank approximations (GLRAM)

To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

Estimating the under-reporting of road crash injuries to police using multiple linked data collections

The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries.

Grassland productivity limited by multiple nutrients

Terrestrial ecosystem productivity is widely accepted to be nutrient limited1. Although nitrogen (N) is deemed a key determinant of aboveground net primary production (ANPP)2,3, the prevalence of co-limitation by N and phosphorus (P) is increasingly recognized4,​5,​6,​7,​8. However, the extent to which terrestrial productivity is co-limited by nutrients other than N and P has remained unclear. Here, we report results from a standardized factorial nutrient addition experiment, in which we added N, P and potassium (K) combined with a selection of micronutrients (K+μ), alone or in concert, to 42 grassland sites spanning five continents, and monitored ANPP. Nutrient availability limited productivity at 31 of the 42 grassland sites. And pairwise combinations of N, P, and K+μ co-limited ANPP at 29 of the sites. Nitrogen limitation peaked in cool, high latitude sites. Our findings highlight the importance of less studied nutrients, such as K and micronutrients, for grassland productivity, and point to significant variations in the type and degree of nutrient limitation. We suggest that multiple-nutrient constraints must be considered when assessing the ecosystem-scale consequences of nutrient enrichment.

Teaching engineering tribology: Elements of assessment design for different learning styles

This study involves teaching engineering students concepts in lubrication engineering that are heavily dependent on mathematics. Excellent learning outcomes have been observed when assessment tasks are devised for a diversity of learning styles. Providing different pathways to knowledge reduces the probability that a single barrier halts progress towards the ultimate learning objective. The interdisciplinary nature of tribology can be used advantageously to tie together multiple elements of engineering to solve real physical problems—an approach that seems to benefit a majority of engineering students. To put this into practice, various assessment items were devised on the study of hydrodynamics, culminating in a project to provide a summative evaluation of the students’ learning achievement. A survey was also conducted to assess other aspects of students’ learning experiences under the headings: ‘perception of learning’ and ‘overall satisfaction’. High degrees of achievement and satisfaction were observed. An attempt has been made to identify the elements contributing to success so that they may be applied to other challenging concepts in engineering education.

Non-parametric consistency test for multiple-sensing-modality data fusion

Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.