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Differential settlement at the bridge approach between the deck and rail track on ground is often considered as a source of challenging technical and economical problem. This caused by the sudden stiffness changes between the bridge deck and the track on ground, and changes in soil stiffness of backfill and sub-grade with soil moisture content and loading history. To minimise the negative social and economic impacts due to poor performances of railway tracks at bridge transition zones, it is important, a special attention to be given at design, construction and maintenance stages. It is critically challenging to obtain an appropriate design solution for any given site condition and most of the existing conventional design approaches are unable to address the actual on-site behaviour due to their inherent assumptions of continuity and lack of clarifying of the local effects. An evaluation of existing design techniques is considered to estimate their contributions to a potential solution for bridge transition zones. This paper analyses five different approaches: the Chinese Standard, the European Standard with three different approaches, and the Australian approach. Each design approach is used to calculate the layer thicknesses, accounting critical design features such as the train speed, the axle load, the backfill subgrade condition, and the dynamic loading response. Considering correlation between track degradation and design parameters, this paper concludes that there is still a need of an optimised design approach for bridge transition zones.

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For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

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The cotton strip assay (CSA) is an established technique for measuring soil microbial activity. The technique involves burying cotton strips and measuring their tensile strength after a certain time. This gives a measure of the rotting rate, R, of the cotton strips. R is then a measure of soil microbial activity. This paper examines properties of the technique and indicates how the assay can be optimised. Humidity conditioning of the cotton strips before measuring their tensile strength reduced the within and between day variance and enabled the distribution of the tensile strength measurements to approximate normality. The test data came from a three-way factorial experiment (two soils, two temperatures, three moisture levels). The cotton strips were buried in the soil for intervals of time ranging up to 6 weeks. This enabled the rate of loss of cotton tensile strength with time to be studied under a range of conditions. An inverse cubic model accounted for greater than 90% of the total variation within each treatment combination. This offers support for summarising the decomposition process by a single parameter R. The approximate variance of the decomposition rate was estimated from a function incorporating the variance of tensile strength and the differential of the function for the rate of decomposition, R, with respect to tensile strength. This variance function has a minimum when the measured strength is approximately 2/3 that of the original strength. The estimates of R are almost unbiased and relatively robust against the cotton strips being left in the soil for more or less than the optimal time. We conclude that the rotting rate X should be measured using the inverse cubic equation, and that the cotton strips should be left in the soil until their strength has been reduced to about 2/3.

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Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

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As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

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The paradigm that mangroves are critical for sustaining production in coastal fisheries is widely accepted, but empirical evidence has been tenuous. This study showed that links between mangrove extent and coastal fisheries production could be detected for some species at a broad regional scale (1000s of kilometres) on the east coast of Queensland, Australia. The relationships between catch-per-unit-effort for different commercially caught species in four fisheries (trawl, line, net and pot fisheries) and mangrove characteristics, estimated from Landsat images were examined using multiple regression analyses. The species were categorised into three groups based on information on their life history characteristics, namely mangrove-related species (banana prawns Penaeus merguiensis, mud crabs Scylla serrata and barramundi Lates calcarifer), estuarine species (tiger prawns Penaeus esculentus and Penaeus semisulcatus, blue swimmer crabs Portunus pelagicus and blue threadfin Eleutheronema tetradactylum) and offshore species (coral trout Plectropomus spp.). For the mangrove-related species, mangrove characteristics such as area and perimeter accounted for most of the variation in the model; for the non-mangrove estuarine species, latitude was the dominant parameter but some mangrove characteristics (e.g. mangrove perimeter) also made significant contributions to the models. In contrast, for the offshore species, latitude was the dominant variable, with no contribution from mangrove characteristics. This study also identified that finer scale spatial data for the fisheries, to enable catch information to be attributed to a particular catchment, would help to improve our understanding of relationships between mangroves and fisheries production.

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Information on the variation available for different plant attributes has enabled germplasm collections to be effectively utilised in plant breeding. A world sourced collection of white clover germplasm has been developed at the White Clover Resource Centre at Glen Innes, New South Wales. This collection of 439 accessions was characterised under field conditions as a preliminary study of the genotypic variation for morphological attributes; stolon density, stolon branching, number of nodes. number of rooted nodes, stolon thickness, internode length, leaf length, plant height and plant spread, together with seasonal herbage yield. Characterisation was conducted on different batches of germplasm (subsets of accessions taken from the complete collection) over a period of five years. Inclusion of two check cultivars, Haifa and Huia, in each batch enabled adjustment of the characterisation data for year effects and attribute-by-year interaction effects. The component of variance for seasonal herbage yield among batches was large relative to that for accessions. Accession-by-experiment and accession-by-season interactions for herbage yield were not detected. Accession mean repeatability for herbage yield across seasons was intermediate (0.453). The components of genotypic variance among accessions for all attributes, except plant height, were larger than their respective standard errors. The estimates of accession mean repeatability for the attributes ranged from low (0.277 for plant height) to intermediate (0.544 for internode length). Multivariate techniques of clustering and ordination were used to investigate the diversity present among the accessions in the collection. Both cluster analysis and principal component analysis suggested that seven groups of accessions existed. It was also proposed from the pattern analysis results that accessions from a group characterised by large leaves, tall plants and thick stolons could be crossed with accessions from a group that had above average stolon density and stolon branching. This material could produce breeding populations to be used in recurrent selection for the development of white clover cultivars for dryland summer moisture stress environments in Australia. The germplasm collection was also found to be deficient in genotypes with high stolon density, high number of branches high number of rooted nodes and large leaves. This warrants addition of new germplasm accessions possessing these characteristics to the present germplasm collection.

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In 1993 the Auditing Practice Board (APB) in the United Kingdom issued Statement of Auditing Standard 600, Auditors’ Reports on Financial Statements. The new expanded audit report was issued in an attempt to reduce the audit expectations gap. Prior to the issuing of this standard the APB issued a Consultative Document in 1991 and an Exposure Draft in 1992. In this paper we investigate the comments made to the APB by respondents to these two documents. We found that a number of respondents doubted whether the new standard was of itself sufficient to reduce the expectations gap. In addition, we found that where respondents made substantive suggestions for changes to the proposed standard these generally were not implemented by the APB.

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The Climate Change Adaptation for Natural Resource Management (NRM) in East Coast Australia Project aims to foster and support an effective “community of practice” for climate change adaptation within the East Coast Cluster NRM regions that will increase the capacity for adaptation to climate change through enhancements in knowledge and skills and through the establishment of long‐term collaborations. It is being delivered by six consortium research partners: * The University of Queensland (project lead) * Griffith University * University of the Sunshine Coast * CSIRO * New South Wales Office of Environment and Heritage * Queensland Department of Science, IT, Innovation and the Arts (Queensland Herbarium). The project relates to the East Coast Cluster, comprising the six coastal NRM regions and regional bodies between Rockhampton and Sydney: * Fitzroy Basin Association (FBA) * Burnett‐Mary Regional Group (BMRG) * SEQ Catchments (SEQC) * Northern Rivers Catchment Management Authority (CMA) (NRCMA) * Hunter‐Central Rivers CMA (HCRCMA) * Hawkesbury Nepean CMA (HNCMA). The aims of this report are to summarise the needs of the regional bodies in relation to NRM planning for climate change adaptation, and provide a basis for developing the detailed work plan for the research consortium. Two primary methods were used to identify the needs of the regional bodies: (1) document analysis of the existing NRM/ Catchment Action Plans (CAPs) and applications by the regional bodies for funding under Stream 1 of the Regional NRM Planning for Climate Change Fund, and; (2) a needs analysis workshop, held in May 2013 involving representatives from the research consortium partners and the regional bodies. The East Coast Cluster includes five of the ten largest significant urban areas in Australia, world heritage listed natural environments, significant agriculture, mining and extensive grazing. The three NSW CMAs have recently completed strategic level CAPs, with implementation plans to be finalised in 2014/2015. SEQC and FBA are beginning a review of their existing NRM Plans, to be completed in 2014 and 2015 respectively; while BMRG is aiming to produce a NRM and Climate Variability Action Strategy. The regional bodies will receive funding from the Australian Government through the Regional NRM Planning for Climate Change Fund (NRM Fund) to improve regional planning for climate change and help guide the location of carbon and biodiversity activities, including wildlife corridors. The bulk of the funding will be available for activities in 2013/2014, with smaller amounts available in subsequent years. Most regional bodies aim to have a large proportion of the planning work complete by the end of 2014. In addition, NSW CMAs are undergoing major structural change and will be incorporated into semi‐autonomous statutory Local Land Services bodies from 2014. Boundaries will align with local government boundaries and there will be significant change in staff and structures. The regional bodies in the cluster have a varying degree of climate knowledge. All plans recognise climate change as a key driver of change, but there are few specific actions or targets addressing climate change. Regional bodies also have varying capacity to analyse large volumes of spatial or modelling data. Due to the complex nature of natural resource management, all regional bodies work with key stakeholders (e.g. local government, industry groups, and community groups) to deliver NRM outcomes. Regional bodies therefore require project outputs that can be used directly in stakeholder engagement activities, and are likely to require some form of capacity building associated with each of the outputs to maximise uptake. Some of the immediate needs of the regional bodies are a summary of information or tools that are able to be used immediately; and a summary of the key outputs and milestone dates for the project, to facilitate alignment of planning activities with research outputs. A project framework is useful to show the linkages between research elements and the relevance of the research to the adaptive management cycle for NRM planning in which the regional bodies are engaged. A draft framework is proposed to stimulate and promote discussion on research elements and linkages; this will be refined during and following the development of the detailed project work plan. The regional bodies strongly emphasised the need to incorporate a shift to a systems based resilience approach to NRM planning, and that approach is included in the framework. The regional bodies identified that information on climate projections would be most useful at regional and subregional scale, to feed into scenario planning and impact analysis. Outputs should be ‘engagement ready’ and there is a need for capacity building to enable regional bodies to understand and use the projections in stakeholder engagement. There was interest in understanding the impacts of climate change projections on ecosystems (e.g. ecosystem shift), and the consequent impacts on the production of ecosystem services. It was emphasised that any modelling should be able to be used by the regional bodies with their stakeholders to allow for community input (i.e. no black box models). The online regrowth benefits tool was of great interest to the regional bodies, as spatial mapping of carbon farming opportunities would be relevant to their funding requirements. The NSW CMAs identified an interest in development of the tool for NSW vegetation types. Needs relating to socio‐economic information included understanding the socio‐economic determinants of carbon farming uptake and managing community expectations. A need was also identified to understand the vulnerability of industry groups as well as community to climate change impacts, and in particular understanding how changes in the flow of ecosystem services would interact with the vulnerability of these groups to impact on the linked ecologicalsocio‐economic system. Responses to disasters (particularly flooding and storm surge) and recovery responses were also identified as being of interest. An ecosystem services framework was highlighted as a useful approach to synthesising biophysical and socioeconomic information in the context of a systems based, resilience approach to NRM planning. A need was identified to develop processes to move towards such an approach to NRM planning from the current asset management approach. Examples of best practice in incorporating climate science into planning, using scenarios for stakeholder engagement in planning and processes for institutionalising learning were also identified as cross‐cutting needs. The over‐arching theme identified was the need for capacity building for the NRM bodies to best use the information available at any point in time. To this end a planners working group has been established to support the building of a network of informed and articulate NRM agents with knowledge of current climate science and capacity to use current tools to engage stakeholders in NRM planning for climate change adaptation. The planners working group would form the core group of the community of practice, with the broader group of stakeholders participating when activities aligned with their interests. In this way, it is anticipated that the Project will contribute to building capacity within the wider community to effectively plan for climate change adaptation.

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Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

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A combined experimental and numerical program was conducted to study the in-plane shear behaviour of hollow concrete masonry panels containing reinforced grout cores. This paper is focused on the numerical program. A two dimensional macromodelling strategy was used to simulate the behaviour of the confined masonry (CM) shear panels. Both the unreinforced masonry and the confining element were modelled using macromasonry properties and the steel reinforcement was modelled as an embedded truss element located within the grout using perfectly bonded constraint. The FE model reproduced key behaviours observed in the experiments, including the shear strength, the deformation and the crack patterns of the unconfined and confined masonry panels. The predictions of the validated model were used to evaluate the existing in-plane shear expressions available in the national masonry standards and research publications.

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An experiment was conducted to investigate direction judgment in a curved corridor. Each participant walked through the curved corridor. A direction was presented to participants at the entrance, and they were asked to point this direction at two points within the corridor. The present study proposed two hypotheses : (a) participants underestimate the change of their traveling direction while walking; (b) participants use four-direction reference axes (front, back, left, and right) for direction judgment. Both hypotheses were supported, and it was suggested that participants estimated the change of their traveling direction to be approximately 90% of the actual change.

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This study explored the stress and wellbeing of Emergency Medical Dispatchers (EMD) who remotely provide crisis intervention to medical emergencies through telehealth support. Semi-structured interviews with 16 EMDs were conducted and Interpretative Phenomenological Analysis was used to identify themes in the data. These results indicated that despite their physical distance from the crisis scene, EMDs can experience vicarious trauma through acute and cumulative exposure to traumatic incidents and their perceived lack of control which can expound feelings of helplessness. Three superordinate themes of operational stress and trauma, organisational stress, and posttraumatic growth were identified. Practical implications are suggested to enable emergency services organisations to counteract this job related stress and promote more positive mental health outcomes.