Reconstructing the event stratigraphy from the complex structural - stratigraphic architecture of an Archaean volcanic – intrusive – sedimentary succession : the Boorara Domain, Eastern Goldfields Superterrane, Western Australia

Two main deformational phases are recognised in the Archaean Boorara Domain of the Kalgoorlie Terrane, Eastern Goldfields Superterrane, Yilgarn Craton, Western Australia, primarily involving southover- north thrust faulting that repeated and thickened the stratigraphy, followed by east northeast – west-southwest shortening that resulted in macroscale folding of the greenstone lithologies. The domain preserves mid-greenschist facies metamorphic grade, with an increase to lower amphibolite metamorphic grade towards the north of the region. As a result of the deformation and metamorphism, individual stratigraphic horizons are difficult to trace continuously throughout the entire domain. Volcanological and sedimentological textures and structures, primary lithological contacts, petrography and geochemistry have been used to correlate lithofacies between faultbounded structural blocks. The correlated stratigraphic sequence for the Boorara Domain comprises quartzo-feldspathic turbidite packages, overlain by high-Mg tholeiitic basalt (lower basalt), coherent and clastic dacite facies, intrusive and extrusive komatiite units, an overlying komatiitic basalt unit (upper basalt), and at the stratigraphic top of the sequence, volcaniclastic quartz-rich turbidites. Reconstruction of the stratigraphy and consideration of emplacement dynamics has allowed reconstruction of the emplacement history and setting of the preserved sequence. This involves a felsic, mafic and ultramafic magmatic system emplaced as high-level intrusions, with localised emergent volcanic centres, into a submarine basin in which active sedimentation was occurring.

Using process models to support design of airport terminals

The complex design process of airport terminal needs to support a wide range of changes in operational facilities for both usual and unusual/emergency events. Process model describes how activities within a process are connected and also states logical information flow of the various activities. The traditional design process overlooks the necessity of information flow from the process model to the actual building design, which needs to be considered as a integral part of building design. The current research introduced a generic method to obtain design related information from process model to incorporate with the design process. Appropriate integration of the process model prior to the design process uncovers the relationship exist between spaces and their relevant functions, which could be missed in the traditional design approach. The current paper examines the available Business Process Model (BPM) and generates modified Business Process Model(mBPM) of check-in facilities of Brisbane International airport. The information adopted from mBPM then transform into possible physical layout utilizing graph theory.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Wayfinding : a simple concept, a complex process

Wayfinding is the process of finding your way to a destination in a familiar or unfamiliar setting using any cues given by the environment. Due to its ubiquity in everyday life, wayfinding appears on the surface to be a simply characterised and understood process, however this very ubiquity and the resulting need to refine and optimise wayfinding has lead to a great number of studies that have revealed that it is in fact a deeply complex exercise. In this paper we examine the motivations for investigating wayfinding, with particular attention being paid to the unique challenges faced in transportation hubs, and discuss the associated principles and factors involved as they have been perceived from different research perspectives.We also review the approaches used to date in the modelling of wayfinding in various contexts. We attempt to draw together the different perspectives applied to wayfinding and postulate the importance of wayfinding and the need to understand this seemingly simple, but concurrently complex, process.

Teachers’ detecting and reporting child abuse and neglect : research into the determinants of complex professional behavior

Child abuse and neglect is prevalent and entails significant costs to children, families and society. Teachers are responsible for significant proportions of official notifications to statutory child protection agencies. Hence, their accurate and appropriate reporting is crucial for well-functioning child protection systems. Approximately one-quarter of Australian teachers indicate never detecting a case of child maltreatment across their careers, while a further 13-15% admit to not reporting suspected cases in some circumstances. The detection and reporting of child abuse and neglect are complex decision-making behaviors, influenced by: the nature of the maltreatment itself; the characteristics of the teacher; the school environment; and the broader legislative and policy environment. In this chapter, the authors provide a background to teachers’ involvement in detecting and reporting child abuse and neglect, and an overview of the role of teachers is provided. Results are presented from three Australian studies that examine the unique contributions of: case; teacher; and contextual characteristics to detection and reporting behaviors. The authors conclude by highlighting the key implications for enhancing teacher training in child abuse and neglect, and outline future research directions.

Analysing seasonal data

Many common diseases, such as the flu and cardiovascular disease, increase markedly in winter and dip in summer. These seasonal patterns have been part of life for millennia and were first noted in ancient Greece by both Hippocrates and Herodotus. Recent interest has focused on climate change, and the concern that seasons will become more extreme with harsher winter and summer weather. We describe a set of R functions designed to model seasonal patterns in disease. We illustrate some simple descriptive and graphical methods, a more complex method that is able to model non-stationary patterns, and the case–crossover for controlling for seasonal confounding.

Real, complex, and binary semantic vectors

This paper presents a combined structure for using real, complex, and binary valued vectors for semantic representation. The theory, implementation, and application of this structure are all significant. For the theory underlying quantum interaction, it is important to develop a core set of mathematical operators that describe systems of information, just as core mathematical operators in quantum mechanics are used to describe the behavior of physical systems. The system described in this paper enables us to compare more traditional quantum mechanical models (which use complex state vectors), alongside more generalized quantum models that use real and binary vectors. The implementation of such a system presents fundamental computational challenges. For large and sometimes sparse datasets, the demands on time and space are different for real, complex, and binary vectors. To accommodate these demands, the Semantic Vectors package has been carefully adapted and can now switch between different number types comparatively seamlessly. This paper describes the key abstract operations in our semantic vector models, and describes the implementations for real, complex, and binary vectors. We also discuss some of the key questions that arise in the field of quantum interaction and informatics, explaining how the wide availability of modelling options for different number fields will help to investigate some of these questions.

Shifting meanings : The role of metaphors in collective meaning–making in complex project leadership

This paper examines the use of metaphors in collective meaning-making in the work of managers and leaders of megaprojects, drawing on interviews with thirty-three leaders of complex projects in a case study organisation responsible for the delivery of major acquisitions. Recognising the notion of both contextualised and decontextualised approaches to either seeking to elicit or project metaphors, the paper describes the various ways in practising project leaders describe their work and the synergies these metaphors have with the broader social discourse and theorisation around complexity and the language of complex adaptive systems. The paper presents our case study findings where we outline our typology of meta-metaphors describing project leaders’ multiple roles and our interpretation of the significance of these choices.

Visualisation of complex flows using texture-based techniques

Complex flow datasets are often difficult to represent in detail using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

Visualisation of complex flows using texture-based techniques

Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution (LIC) [1], and Image based flow visualisation (IBFV) [18]. We evaluated these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads.

Maize streak virus: An old and complex 'emerging' pathogen

Maize streak virus (MSV; Genus Mastrevirus, Family Geminiviridae) occurs throughout Africa, where it causes what is probably the most serious viral crop disease on the continent. It is obligately transmitted by as many as six leafhopper species in the Genus Cicadulina, but mainly by C. mbila Naudé and C. storeyi. In addition to maize, it can infect over 80 other species in the Family Poaceae. Whereas 11 strains of MSV are currently known, only the MSV-A strain is known to cause economically significant streak disease in maize. Severe maize streak disease (MSD) manifests as pronounced, continuous parallel chlorotic streaks on leaves, with severe stunting of the affected plant and, usuallly, a failure to produce complete cobs or seed. Natural resistance to MSV in maize, and/or maize infections caused by non-maize-adapted MSV strains, can result in narrow, interrupted streaks and no obvious yield losses. MSV epidemiology is primarily governed by environmental influences on its vector species, resulting in erratic epidemics every 3-10 years. Even in epidemic years, disease incidences can vary from a few infected plants per field, with little associated yield loss, to 100% infection rates and complete yield loss. Taxonomy: The only virus species known to cause MSD is MSV, the type member of the Genus Mastrevirus in the Family Geminiviridae. In addition to the MSV-A strain, which causes the most severe form of streak disease in maize, 10 other MSV strains (MSV-B to MSV-K) are known to infect barley, wheat, oats, rye, sugarcane, millet and many wild, mostly annual, grass species. Seven other mastrevirus species, many with host and geographical ranges partially overlapping those of MSV, appear to infect primarily perennial grasses. Physical properties: MSV and all related grass mastreviruses have single-component, circular, single-stranded DNA genomes of approximately 2700 bases, encapsidated in 22 × 38-nm geminate particles comprising two incomplete T = 1 icosahedra, with 22 pentameric capsomers composed of a single 32-kDa capsid protein. Particles are generally stable in buffers of pH 4-8. Disease symptoms: In infected maize plants, streak disease initially manifests as minute, pale, circular spots on the lowest exposed portion of the youngest leaves. The only leaves that develop symptoms are those formed after infection, with older leaves remaining healthy. As the disease progresses, newer leaves emerge containing streaks up to several millimetres in length along the leaf veins, with primary veins being less affected than secondary or tertiary veins. The streaks are often fused laterally, appearing as narrow, broken, chlorotic stripes, which may extend over the entire length of severely affected leaves. Lesion colour generally varies from white to yellow, with some virus strains causing red pigmentation on maize leaves and abnormal shoot and flower bunching in grasses. Reduced photosynthesis and increased respiration usually lead to a reduction in leaf length and plant height; thus, maize plants infected at an early stage become severely stunted, producing undersized, misshapen cobs or giving no yield at all. Yield loss in susceptible maize is directly related to the time of infection: Infected seedlings produce no yield or are killed, whereas plants infected at later times are proportionately less affected. Disease control: Disease avoidance can be practised by only planting maize during the early season when viral inoculum loads are lowest. Leafhopper vectors can also be controlled with insecticides such as carbofuran. However, the development and use of streak-resistant cultivars is probably the most effective and economically viable means of preventing streak epidemics. Naturally occurring tolerance to MSV (meaning that, although plants become systemically infected, they do not suffer serious yield losses) has been found, which has primarily been attributed to a single gene, msv-1. However, other MSV resistance genes also exist and improved resistance has been achieved by concentrating these within individual maiz genotypes. Whereas true MSV immunity (meaning that plants cannot be symptomatically infected by the virus) has been achieved in lines that include multiple small-effect resistance genes together with msv-1, it has proven difficult to transfer this immunity into commercial maize genotypes. An alternative resistance strategy using genetic engineering is currently being investigated in South Africa. Useful websites: 〈http://www.mcb.uct.ac.za/MSV/mastrevirus.htm〉; 〈http://www. danforthcenter.org/iltab/geminiviridae/geminiaccess/mastrevirus/Mastrevirus. htm〉. © 2009 Blackwell Publishing Ltd.

Efficacy of oral or intrauterine device-delivered progestin in patients with complex endometrial hyperplasia with atypia or early endometrial adenocarcinoma : a meta-analysis and systematic review of the literature

Objectives: To investigate the efficacy of progestin treatment to achieve pathological complete response (pCR) in patients with complex atypical endometrial hyperplasia (CAH) or early endometrial adenocarcinoma (EC). Methods: A systematic search identified 3245 potentially relevant citations. Studies containing less than ten eligible CAH or EC patients in either oral or intrauterine treatment arm were excluded. Only information from patients receiving six or more months of treatment and not receiving other treatments was included. Weighted proportions of patients achieving pCR were calculated using R software. Results: Twelve studies met the selection criteria. Eleven studies reported treatment of patients with oral (219 patients, 117 with CAH, 102 with grade 1 Stage I EC) and one reported treatment of patients with intrauterine progestin (11 patients with grade 1 Stage IEC). Overall, 74% (95% confidence interval [CI] 65-81%) of patients with CAH and 72% (95% CI 62-80%) of patients with grade 1 Stage I EC achieved a pCR to oral progestin. Disease progression while on oral treatment was reported for 6/219 (2.7%), and relapse after initial complete response for 32/159 (20.1%) patients. The weighted mean pCR rate of patients with grade 1 Stage I EC treated with intrauterine progestin from one prospective pilot study and an unpublished retrospective case series from the Queensland Centre of Gynaecologic Oncology (QCGC) was 68% (95% CI 45- 86%). Conclusions: There is a lack of high quality evidence for the efficacy of progestin in CAH or EC. The available evidence however suggests that treatment with oral or intrauterine progestin is similarly effective. The risk of progression during treatment is small but longer follow-up is required. Evidence from prospective controlled clinical trials is warranted to establish how the efficacy of progestin for the treatment of CAH and EC can be improved further.

International students using online information resources to learn : complex experience and learning needs

This paper reports the findings of a qualitative study which investigated 25 international students’ use of online information resources for study purposes at two Australian universities. Using an expanded critical incident approach, the study viewed international students through an information literacy lens, as information-using learners. The findings are presented in two complementary parts: as a word picture that describes their whole experience of using online information resources to learn; and as a tabulated set of critical findings that summarises their associated information literacy learning needs. The word picture shows international students’ resource use as a complex interplay of eight inter-related elements: students; information-learning environment; interactions (with online resources); strengths-challenges; learning-help; affective responses; reflective responses; cultural-linguistic dimensions. In using online resources, the international students experience an array of strengths and challenges, and an apparent information literacy imbalance between their more developed information skills and less developed critical information use. The critical findings about information literacy needs provide a framework for developing an inclusive informed learning approach that responds to international students’ complex information using experiences and needs. While the study is situated in Australia, the findings are of potential interest to educators, information professionals and researchers worldwide who seek to support learning in culturally diverse higher education contexts.