Copula-based spatial modelling of geometallurgical variables

The most important aspect of modelling a geological variable, such as metal grade, is the spatial correlation. Spatial correlation describes the relationship between realisations of a geological variable sampled at different locations. Any method for spatially modelling such a variable should be capable of accurately estimating the true spatial correlation. Conventional kriged models are the most commonly used in mining for estimating grade or other variables at unsampled locations, and these models use the variogram or covariance function to model the spatial correlations in the process of estimation. However, this usage assumes the relationships of the observations of the variable of interest at nearby locations are only influenced by the vector distance between the locations. This means that these models assume linear spatial correlation of grade. In reality, the relationship with an observation of grade at a nearby location may be influenced by both distance between the locations and the value of the observations (ie non-linear spatial correlation, such as may exist for variables of interest in geometallurgy). Hence this may lead to inaccurate estimation of the ore reserve if a kriged model is used for estimating grade of unsampled locations when nonlinear spatial correlation is present. Copula-based methods, which are widely used in financial and actuarial modelling to quantify the non-linear dependence structures, may offer a solution. This method was introduced by Bárdossy and Li (2008) to geostatistical modelling to quantify the non-linear spatial dependence structure in a groundwater quality measurement network. Their copula-based spatial modelling is applied in this research paper to estimate the grade of 3D blocks. Furthermore, real-world mining data is used to validate this model. These copula-based grade estimates are compared with the results of conventional ordinary and lognormal kriging to present the reliability of this method.

Designing hubs for connected learning: social, spatial and technological insights from Coworking, Hackerspaces and Meetup groups

Connected learning, as a design approach, does not restrict learning to a dedicated learning space (school, university, etc.), but considers it to be an aggregation of individual experiences made through intrinsically motivated, active participation in and across various socio-cultural, every-day life environments. Urban places for meeting, interacting and connected learning with people from diverse backgrounds, cultures and areas of expertise are highly significant in the knowledge economy of our 21st century. However, little is yet known about best practices to design and curate such hubs that attract and support interest-driven and socially embedded learning experiences. The research study presented in this paper investigates design aspects that contribute to successful place-based spaces for connected learning. The paper reports findings from observations as well as interviews with users and managers of three different types of local, community-led learning environments, i.e., coworking spaces, hackerspaces, and meetup groups across Australia. The findings reveal social, spatial and technological interventions that these spaces apply to nourish a culture of connected learning, sharing and peer interaction. The discussion suggests a set of design implications for designers, managers and decision makers that have an interest in nourishing a connected learning culture among their user community.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.

Spatial governance: The metalanguage of spatiotemporal information and its infrastructure

‘Spatial governance’ involves a large number of situations where knowledge of place and time is important in achieving acceptable organisational outcomes. This paper argues that spatial governance calls for information-intensive activity in three main areas. The first establishes ‘authority’ in a legal entity to decide issues regarding resources within a territorial jurisdiction. The second involves planning the future use of resources. It engages a language of design, purpose, modeling, visualization, expectations and risk. The third involves monitoring of outcomes to see if expectations are met; and whether changes to authority and planning regimes need to be made in the light of experience. This engages a language of observing, recording, accounting, auditing, statistical indicators and accountability. ‘Authority’, ‘planning’ and ‘monitoring’ regimes can be constructed using a relatively small number of elements, in much the same way that a large number of words with recognisable meanings can be created using a relatively few standardised letters of the alphabet. Words can combine in a similar process of combinatorial explosion to create any message that can be imagined. Similarly, combining authority, planning and monitoring regimes can create a metalanguage of ‘spatial governance’ to give purpose, meaning and value to any spatiotemporal information system that can be imagined, described, interpreted and understood.

Early maternal deprivation reduces prepulse inhibition and impairs spatial learning ability in adulthood: No further effect of post-pubertal chronic corticosterone treatment

Prolonged maternal deprivation leads to long-term alterations in hypothalamic–pituitary–adrenal (HPA) axis activity, disturbances of auditory information processing and neurochemical changes in the adult brain, some of which are similar to that observed in schizophrenia. Here we report the adult behavioural effects of maternal deprivation (12 h on postnatal days 9 and 11) in Wistar rats on paradigms of auditory information processing (prepulse inhibition), sensitivity to dopamimetics (amphetamine-induced hyper-locomotion) and cognition (T-maze delayed alternation and Morris water-maze). In addition, we examined the long-lasting effect of chronic 21-day corticosterone treatment during the post-pubertal period (i.e., postnatal days 56–76) on each of these behavioural paradigms in maternally deprived and control rats. Behavioural testing commenced 2 weeks after the termination of corticosterone treatment. Maternal deprivation led to a significant reduction in PPI and impaired spatial learning ability in adulthood, but did not affect the behavioural response to amphetamine. Post-pubertal chronic corticosterone treatment did not have any major long-lasting effects on any of the behavioural measures in either maternally deprived or control rats. Our findings further support maternal deprivation as an animal model of specific aspects of schizophrenia.

Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

Where is spatial information and science in your world?

Skills in spatial sciences are fundamental to understanding our world in context. Increasing digital presence and the availability of data with accurate spatial components has allowed almost everything researchers and students do to be represented in a spatial context. Representing outcomes and disseminating information has moved from 2D to 4D with time series animation. In the next 5 years industry will not only demand QUT graduates have spatial skills along with analytical skills, graduates will be required to present their findings in spatial visualizations that show spatial, spectral and temporal contexts. Domains such as engineering and science will no longer be the leaders in spatial skills as social sciences, health, arts and the business community gain momentum from place-based research including human interactions. A university that can offer students a pathway to advanced spatial investigation will be ahead of the game.

Open access spatial data and collaboration

On 19 June 2015, representatives from over 40 Australian research institutions gathered in Canberra to launch their Open Data Collections. The one day event, hosted by the Australian National Data Service (ANDS), showcased to government and a range of national stakeholders the rich variety of data collections that have been generated through the Major Open Data Collections (MODC) project. Colin Eustace attended the showcase for QUT Library and presented a poster that reflected the work that he and Jodie Vaughan generated through the project. QUT’s Blueprint 4, the University’s five-year institutional strategic plan, outlines the key priorities of developing a commitment to working in partnership with industry, as well as combining disciplinary strengths with interdisciplinary application. The Division of Technology, Information and Learning Support (TILS) has undertaken a number of Australian National Data Service (ANDS) funded projects since 2009 with the aim of developing improved research data management services within the University to support these strategic aims. By leveraging existing tools and systems developed during these projects, the Major Open Data Collection (MODC) project delivered support to multi-disciplinary collaborative research activities through partnership building between QUT researchers and Queensland government agencies, in order to add to and promote the discovery and reuse of a collection of spatially referenced datasets. The MODC project built upon existing Research Data Finder infrastructure (which uses VIVO open source software, developed by Cornell University) to develop a separate collection, Spatial Data Finder (https://researchdatafinder.qut.edu.au/spatial) as the interface to display the spatial data collection. During the course of the project, 62 dataset descriptions were added to Spatial Data Finder, 7 added to Research Data Finder and two added to Software Finder, another separate collection. The project team met with 116 individual researchers and attended 13 school and faculty meetings to promote the MODC project and raise awareness of the Library’s services and resources for research data management.

Low voltage EPMA: Experiments on a new frontier in microanalysis—analytical spatial resolution

Field emission (FE) electron gun sources provide new capabilities for high lateral resolution EPMA. The determination of analytical lateral resolution is not as straightforward as that for electron microscopy imaging. Results from two sets of experiments to determine the actual lateral resolution for accurate EPMA are presented for Kα X-ray lines of Si and Al and Lα of Fe at 5 and 7 keV in a silicate glass. These results are compared to theoretical predictions and Monte Carlo simulations of analytical lateral resolution. The experiments suggest little is gained in lateral resolution by dropping from 7 to 5 keV in EPMA of this silicate glass.

Comparison of fractional and geodesic anisotropy in diffusion tensor images of 90 monozygotic and dizygotic twins

We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

Association study of genes related to bone formation and resorption and the extent of radiographic change in ankylosing spondylitis

Objective: To identify genetic associations with severity of radiographic damage in ankylosing spondylitis (AS). Method: We studied 1537 AS cases of European descent; all fulfilled the modified New York Criteria. Radiographic severity was assessed from digitised lateral radiographs of the cervical and lumbar spine using the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS). A two-phase genotyping design was used. In phase 1, 498 single nucleotide polymorphisms (SNPs) were genotyped in 688 cases; these were selected to capture >90% of the common haplotypic variation in the exons, exon-intron boundaries, and 5 kb flanking DNA in the 5' and 3' UTR of 74 genes involved in anabolic or catabolic bone pathways. In phase 2, 15 SNPs exhibiting p<0.05 were genotyped in a further cohort of 830 AS cases; results were analysed both separately and in combination with the discovery phase data. Association was tested by contingency tables after separating the samples into 'mild' and 'severe' groups, defined as the bottom and top 40% by mSASSS, adjusted for gender and disease duration. Results: Experiment-wise association was observed with the SNP rs8092336 (combined OR 0.32, p=1.2×10-5), which lies within RANK (receptor activator of NF?B), a gene involved in osteoclastogenesis, and in the interaction between T cells and dendritic cells. Association was also found with the SNP rs1236913 in PTGS1 (prostaglandin-endoperoxide synthase 1, cyclooxygenase 1), giving an OR of 0.53 (p=2.6×10-3). There was no observed association between radiographic severity and HLA-B*27. Conclusions: These findings support roles for bone resorption and prostaglandins pathways in the osteoproliferative changes in AS.

Integration of Geospatial and Built Environment - National Data Policy

Digital technology offers enormous benefits (economic, quality of design and efficiency in use) if adopted to implement integrated ways of representing the physical world in a digital form. When applied across the full extent of the built and natural world, it is referred to as the Digital Built Environment (DBE) and encompasses a wide range of approaches and technology initiatives, all aimed at the same end goal: the development of a virtual world that sufficiently mirrors the real world to form the basis for the smart cities of the present and future, enable efficient infrastructure design and programmed maintenance, and create a new foundation for economic growth and social well-being through evidence-based analysis. The creation of a National Data Policy for the DBE will facilitate the creation of additional high technology industries in Australia; provide Governments, industries and citizens with greater knowledge of the environments they occupy and plan; and offer citizen-driven innovations for the future. Australia has slipped behind other nations in the adoption and execution of Building Information Modelling (BIM) and the principal concern is that the gap is widening. Data driven innovation added $67 billion to the Australian economy in 20131. Strong open data policy equates to $16 billion in new value2. Australian Government initiatives such as the Digital Earth inspired “National Map” offer a platform and pathway to embrace the concept of a “BIM Globe”, while also leveraging unprecedented growth in open source / open data collaboration. Australia must address the challenges by learning from international experiences—most notably the UK and NZ—and mandate the use of BIM across Government, extending the Framework for Spatial Data Foundation to include the Built Environment as a theme and engaging collaboration through a “BIM globe” metaphor. This proposed DBE strategy will modernise the Australian urban planning and the construction industry. It will change the way we develop our cities by fundamentally altering the dynamics and behaviours of the supply chains and unlocking new and more efficient ways of collaborating at all stages of the project life-cycle. There are currently two major modelling approaches that contribute to the challenge of delivering the DBE. Though these collectively encompass many (often competing) approaches or proprietary software systems, all can be categorised as either: a spatial modelling approach, where the focus is generally on representing the elements that make up the world within their geographic context; and a construction modelling approach, where the focus is on models that support the life cycle management of the built environment. These two approaches have tended to evolve independently, addressing two broad industry sectors: the one concerned with understanding and managing global and regional aspects of the world that we inhabit, including disciplines concerned with climate, earth sciences, land ownership, urban and regional planning and infrastructure management; the other is concerned with planning, design, construction and operation of built facilities and includes architectural and engineering design, product manufacturing, construction, facility management and related disciplines (a process/technology commonly known as Building Information Modelling, BIM). The spatial industries have a strong voice in the development of public policy in Australia, while the construction sector, which in 2014 accounted for around 8.5% of Australia’s GDP3, has no single voice and because of its diversity, is struggling to adapt to and take advantage of the opportunity presented by these digital technologies. The experience in the UK over the past few years has demonstrated that government leadership is very effective in stimulating industry adoption of digital technologies by, on the one hand, mandating the use of BIM on public procurement projects while at the same time, providing comparatively modest funding to address the common issues that confront the industry in adopting that way of working across the supply chain. The reported result has been savings of £840m in construction costs in 2013/14 according to UK Cabinet Office figures4. There is worldwide recognition of the value of bringing these two modelling technologies together. Australia has the expertise to exercise leadership in this work, but it requires a commitment by government to recognise the importance of BIM as a companion methodology to the spatial technologies so that these two disciplinary domains can cooperate in the development of data policies and information exchange standards to smooth out common workflows. buildingSMART Australasia, SIBA and their academic partners have initiated this dialogue in Australia and wish to work collaboratively, with government support and leadership, to explore the opportunities open to us as we develop an Australasian Digital Built Environment. As part of that programme, we must develop and implement a strategy to accelerate the adoption of BIM processes across the Australian construction sector while at the same time, developing an integrated approach in concert with the spatial sector that will position Australia at the forefront of international best practice in this area. Australia and New Zealand cannot afford to be on the back foot as we face the challenges of rapid urbanisation and change in the global environment. Although we can identify some exemplary initiatives in this area, particularly in New Zealand in response to the need for more resilient urban development in the face of earthquake threats, there is still much that needs to be done. We are well situated in the Asian region to take a lead in this challenge, but we are at imminent risk of losing the initiative if we do not take action now. Strategic collaboration between Governments, Industry and Academia will create new jobs and wealth, with the potential, for example, to save around 20% on the delivery costs of new built assets, based on recent UK estimates.

Imagined Landscapes: Geovisualizing Australian Spatial Narratives

Imagined Landscapes teams geocritical analysis with digital visualization techniques to map and interrogate films, novels, and plays in which space and place figure prominently. Drawing upon A Cultural Atlas of Australia, a database-driven interactive digital map that can be used to identify patterns of representation in Australia’s cultural landscape, the book presents an integrated perspective on the translation of space across narrative forms and pioneers new ways of seeing and understanding landscape. It offers fresh insights on cultural topography and spatial history by examining the technical and conceptual challenges of georeferencing fictional and fictionalized places in narratives. Among the items discussed are Wake in Fright, a novel by Kenneth Cook, adapted iconically to the screen and recently onto the stage; the Australian North as a mythic space; spatial and temporal narrative shifts in retellings of the story of Alexander Pearce, a convict who gained notoriety for resorting to cannibalism after escaping from a remote Tasmanian penal colony; travel narratives and road movies set in Western Australia; and the challenges and spatial politics of mapping spaces for which there are no coordinates.

The role of environmental factors in the spatial distribution of Japanese encephalitis in mainland China

Japanese encephalitis (JE) is the most common cause of viral encephalitis and an important public health concern in the Asia-Pacific region, particularly in China where 50% of global cases are notified. To explore the association between environmental factors and human JE cases and identify the high risk areas for JE transmission in China, we used annual notified data on JE cases at the center of administrative township and environmental variables with a pixel resolution of 1 km×1 km from 2005 to 2011 to construct models using ecological niche modeling (ENM) approaches based on maximum entropy. These models were then validated by overlaying reported human JE case localities from 2006 to 2012 onto each prediction map. ENMs had good discriminatory ability with the area under the curve (AUC) of the receiver operating curve (ROC) of 0.82-0.91, and low extrinsic omission rate of 5.44-7.42%. Resulting maps showed JE being presented extensively throughout southwestern and central China, with local spatial variations in probability influenced by minimum temperatures, human population density, mean temperatures, and elevation, with contribution of 17.94%-38.37%, 15.47%-21.82%, 3.86%-21.22%, and 12.05%-16.02%, respectively. Approximately 60% of JE cases occurred in predicted high risk areas, which covered less than 6% of areas in mainland China. Our findings will help inform optimal geographical allocation of the limited resources available for JE prevention and control in China, find hidden high-risk areas, and increase the effectiveness of public health interventions against JE transmission.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings