957 resultados para spatial extent


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An experiment was conducted to investigate the process of reasoning about directions in an egocentric space. Each participant walked through a corridor containing an angular turn ranging in size from 0° to 90°, in 15° increments. A direction was given to participants at the entrance of the corridor and they were asked to answer this direction at the end of this corridor. Considering the fact that participants had to reason the direction in the featureless corridor, two hypotheses were proposed: (i) reasoning about directions falls into qualitative reasoning by using a small number of coarse angular categories (four 90° categories or eight 45° categories: 90° categories consist of front, back, left, right; 45° categories consist of 90° categories and the four intermediates) that reference axes generate; (ii) reasoning about directions would be done by recalling the rotation angle from the traveling direction to the direction that participants tried to answer. In addition, the configuration of reference axes that participants employed was examined. Both hypotheses were supported, and the data designated that reference axes consisted of eight directions: a pair of orthogonal axes and diagonals.

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The present study investigated how object locations learned separately are integrated and represented as a single spatial layout in memory. Two experiments were conducted in which participants learned a room-sized spatial layout that was divided into two sets of five objects. Results suggested that integration across sets was performed efficiently when it was done during initial encoding of the environment but entailed cost in accuracy when it was attempted at the time of memory retrieval. These findings suggest that, once formed, spatial representations in memory generally remain independent and integrating them into a single representation requires additional cognitive processes.

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Building Information Modelling (BIM) has been regarded as a one stop shop capable of addressing the ills of the construction industry. Yet, while some firms have accepted BIM as a new way to work and gone on to record success, others (which have not so done) have raised such questions as: ‘How is BIM defined? Is it a tool or a process? Which kinds and sizes of organisations stand to benefit from BIM?’ These questions form the basis of this research. Hence, having explored the relevant body of literature, this research investigates three organisations within the UK – described as the earliest adopters of BIM – and considers how they have fared in terms of project performance in the years since adopting BIM; focusing on project cost, delivery time and quality achievement. This investigation also probed two of the leading voices in BIM in the UK in search of the much needed answers. The findings of the research show that successful projects executed in the organisations that have used BIM is predicated on its adoption as a process, rather than as a tool of technology; a process that changes the way work in the construction industry is typically done. Moreover, the successes recorded in the firms researched give credence to project success consequent upon adopting BIM. Nevertheless, the findings of this research show that the cornerstone of this success is leadership-driven innovation.

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Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher’s equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations.

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This paper reports on the use of a local order measure to quantify the spatial ordering of a quantum dot array (QDA). By means of electron ground state energy analysis in a quantum dot pair, it is demonstrated that the length scale required for such a measure to characterize the opto-electronic properties of a QDA is of the order of a few QD radii. Therefore, as local order is the primary factor that affects the opto-electronic properties of an array of quantum dots of homogeneous size, this order was quantified through using the standard deviation of the nearest neighbor distances of the quantum dot ensemble. The local order measure is successfully applied to quantify spatial order in a range of experimentally synthesized and numerically generated arrays of nanoparticles. This measure is not limited to QDAs and has wide ranging applications in characterizing order in dense arrays of nanostructures.

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Marine sediments around volcanic islands contain an archive of volcaniclastic deposits, which can be used to reconstruct the volcanic history of an area. Such records hold many advantages over often incomplete terrestrial datasets. This includes the potential for precise and continuous dating of intervening sediment packages, which allow a correlatable and temporally-constrained stratigraphic framework to be constructed across multiple marine sediment cores. Here, we discuss a marine record of eruptive and mass-wasting events spanning ~250 ka offshore of Montserrat, using new data from IODP Expedition 340, as well as previously collected cores. By using a combination of high-resolution oxygen isotope stratigraphy, AMS radiocarbon dating, biostratigraphy of foraminifera and calcareous nannofossils and clast componentry, we identify five major events at Soufriere Hills volcano since 250 ka. Lateral correlation of these events across sediment cores collected offshore of the south and south west of Montserrat, have improved our understanding of the timing, extent and associations between events in this area. Correlations reveal that powerful and potentially erosive density-currents travelled at least 33 km offshore, and demonstrate that marine deposits, produced by eruption-fed and mass-wasting events on volcanic islands, are heterogeneous in their spatial distribution. Thus, multiple drilling/coring sites are needed to reconstruct the full chronostratigraphy of volcanic islands. This multidisciplinary study will be vital to interpreting the chaotic records of submarine landslides at other sites drilled during Expedition 340 and provides a framework that can be applied to the stratigraphic analysis of sediments surrounding other volcanic islands.

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Business literature reveals the importance of generating innovative products and services, but much of the innovation research has been conducted in large firms and not replicated in small firms. These firms are likely to have different perspectives on innovation, which means that they will probably behave differently to large firms. Our study aims to unpack how firms in Spatial Information perceive and engage in innovation as a part of their business operation. To investigate these questions we conduct 20 in depth interviews of top management team members in Spatial Information firms in Australia. We find that small firms define innovation very broadly and measure innovation by its effect on productivity or market success. Innovation is seen as crucial to survival and success in a competitive environment. Most firms engage in product and/or service innovations, while some also mentioned marketing, process and organisational innovations. Most innovations were more exploitative rather than exploratory with only a few being radical innovations. Innovation barriers include time and money constraints, corporate culture and Government tendering practices. Our study sheds a light on our understanding of innovation in an under-researched sector; that is spatial information industry.

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Background: The two most reported mosquito-borne diseases in Queensland, a northern state of Australia, are Ross River virus (RRV) disease and Barmah Forest virus (BFV) disease. Both diseases are endemic in Queensland and have similar clinical symptoms and comparable transmission cycles involving a complex inter-relationship between human hosts, various mosquito vectors, and a range of nonhuman vertebrate hosts, including marsupial mammals that are unique to the Australasian region. Although these viruses are thought to share similar vectors and vertebrate hosts, RRV is four times more prevalent than BFV in Queensland. Methods: We performed a retrospective analysis of BFV and RRV human disease notification data collected from 1995 to 2007 in Queensland to ascertain whether there were differences in the incidence patterns of RRV and BFV disease. In particular, we compared the temporal incidence and spatial distribution of both diseases and considered the relationship between their disease dynamics. We also investigated whether a peak in BFV incidence during spring was indicative of the following RRV and BFV transmission season incidence levels. Results: Although there were large differences in the notification rates of the two diseases, they had similar annual temporal patterns, but there were regional variations between the length and magnitude of the transmission seasons. During periods of increased disease activity, however, there was no association between the dynamics of the two diseases. Conclusions: The results from this study suggest that while RRV and BFV share similar mosquito vectors, there are significant differences in the ecology of these viruses that result in different epidemic patterns of disease incidence. Further investigation is required into the ecology of each virus to determine which factors are important in promoting RRV and BFV disease outbreaks.

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This project is led by scientists in conservation decision appraisal and brings together a group of experts working across the Lake Eyre Basin (LEB). The LEB covers a sixth of Australia, with an array of globally significant natural values that are threatened by invasive plants, among other things. Managers at various levels are investing in attempts to control, contain and eradicate these invasive plant species, under severe time and resources limitations. To date there has been no basin-wide assessment of which weed management strategies and locations provide the best investments for maximising outcomes for biodiversity per unit cost. Further, there has been no assessment of the extent of ecosystem intactness that may be lost without effective invasive plant species management strategies. Given that there are insufficient resources to manage all invasive plant species everywhere, this information has the potential to improve current investment decisions. Here, we provide a prioritisation of invasive plant management strategies in the LEB. Prioritisation was based on cost-effectiveness for biodiversity benefits. We identify the key invasive plant species to target to protect ecosystem intactness across the bioregions of the LEB, the level of investment required and the likely reduction in invasive species dominance gained per dollar spent on each strategy. Our focus is on strategies that are technically and socially feasible and reduce the likelihood that high impact invasive plant species will dominate native ecosystems, and therefore change their form and function. The outputs of this work are designed to help guide decision-making and further planning and investment in weed management for the Basin. Experts in weed management, policy-making, community engagement, biodiversity and natural values of the Basin, attended a workshop and agreed upon 12 strategies to manage invasive plants. The strategies focused primarily on 10 weeds which were considered to have a high potential for broad, significant impacts on natural ecosystems in the next 50 years and for which feasible management strategies could be defined. Each strategy consisted of one or more supporting actions, many of which were spatially linked to IBRA (Interim Biogeographical Regionalisation of Australia) bioregions. The first strategy was an over-arching recommendation for improved mapping, information sharing, education and extension efforts in order to facilitate the more specific weed management strategies. The 10 more specific weed management strategies targeted the control and/or eradication of the following high-impact exotic plants: mesquite, parkinsonia, rubber vine, bellyache bush, cacti, mother of millions, chinee apple, athel pine and prickly acacia, as well as a separate strategy for eradicating all invasive plants from one key threatened ecological community, the GAB (Great Artesian Basin dependant) mound springs. Experts estimated the expected biodiversity benefit of each strategy as the reduction in area that an invasive plant species is likely to dominate in over a 50-year period, where dominance was defined as more than 30% coverage at a site. Costs were estimated in present day terms over 50 years largely during follow up discussions post workshop. Cost-effectiveness was then calculated for each strategy in each bioregion by dividing the average expected benefit by the average annual costs. Overall, the total cost of managing 12 invasive plant strategies over the next 50 years was estimated at $1.7 billion. It was estimated that implementation of these strategies would result in a reduction of invasive plant dominance by 17 million ha (a potential 32% reduction), roughly 14% of the LEB. If only targeting Weeds of National Significance (WONS), the total cost was estimated to be $113 million over the next 50 years. Over the next 50 years, $2.3 million was estimated to eradicate all invasive plant species from the Great Artesian Basin Mound Springs threatened ecological community. Prevention and awareness programs were another key strategy targeted across the Basin and estimated at $17.5 million in total over 50 years. The cost of controlling, eradicating and containing buffel grass were the most expensive, over $1.5 billion over 50 years; this strategy was estimated to result in a reduction in buffel grass dominance of a million ha in areas where this species is identified as an environmental problem. Buffel grass has been deliberately planted across the Basin for pasture production and is by far the most widely distributed exotic species. Its management is contentious, having economic value to many graziers while posing serious threats to biodiversity and sites of high cultural and conservation interest. The strategy for containing and locally eradicating buffel grass was a challenge to cost based on expert knowledge, possibly because of the dual nature of this species as a valued pastoral grass and environmental weed. Based on our conversations with experts, it appears that control and eradication programs for this species, in conservation areas, are growing rapidly and that information on the most cost-effective strategies for this species will continue to develop over time. The top five most cost-effective strategies for the entire LEB were for the management of: 1) parkinsonia, 2) chinee apple, 3) mesquite, 4) rubber vine and 5) bellyache bush. Chinee apple and mother of millions are not WONS and have comparatively small populations within the semi-arid bioregions of Queensland. Experts felt that there was an opportunity to eradicate these species before they had the chance to develop into high-impact species within the LEB. Prickly acacia was estimated to have one of the highest benefits, but the costs of this strategy were high, therefore it was ranked 7th overall. The buffel grass strategy was ranked the lowest (10th) in terms of cost effectiveness. The top five most cost-effective strategies within and across the bioregions were the management of: 1) parkinsonia in the Channel Country, 2) parkinsonia in the Desert Uplands, 3) mesquite in the Mitchell Grass Downs, 4) parkinsonia in the Mitchell Grass Downs, and 5) mother of millions in the Desert Uplands. Although actions for several invasive plant species like parkinsonia and prickly acacia were concentrated in the Queensland part of the LEB, the actions involved investing in containment zones to prevent the spread of these species into other states. In the NT and SA bioregions of the LEB, the management of athel pine, parkinsonia and cacti were the main strategies. While outside the scientific research goals of study, this work highlighted a number of important incidental findings that led us to make the following recommendations for future research and implementation of weed management in the Basin: • Ongoing stakeholder engagement, extension and participation is required to ensure this prioritisation effort has a positive impact in affecting on-ground decision making and planning. • Short term funding for weed management was identified as a major reason for failure of current efforts, hence future funding needs to be secure and ongoing. • Improved mapping and information sharing is essential to implement effective weed management. • Due to uncertainties in the outcomes and impacts of management options, strategies should be implemented as part of an adaptive management program. The information provided in this report can be used to guide investment for controlling high-impact invasive plant species for the benefits of biodiversity conservation. We do not present a final prioritisation of invasive plant strategies for the LEB, and we have not addressed the cultural, socio-economic or spatial components necessary for an implementation plan. Cost-effectiveness depends on the objectives used; in our case we used the intactness of ecosystems as a surrogate for expected biodiversity benefits, measured by the extent that each invasive plant species is likely to dominate in a bioregion. When other relevant factors for implementation are considered the priorities may change and some actions may not be appropriate in some locations. We present the costs, ecological benefits and cost-effectiveness of preventing, containing, reducing and eradicating the dominance of high impact invasive plants through realistic management actions over the next 50 years. In doing so, we are able to estimate the size of the weed management problem in the LEB and provide expert-based estimates of the likely outcomes and benefits of implementing weed management strategies. The priorities resulting from this work provide a prospectus for guiding further investment in management and in improving information availability.

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Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.

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Given the drawbacks for using geo-political areas in mapping outcomes unrelated to geo-politics, a compromise is to aggregate and analyse data at the grid level. This has the advantage of allowing spatial smoothing and modelling at a biologically or physically relevant scale. This article addresses two consequent issues: the choice of the spatial smoothness prior and the scale of the grid. Firstly, we describe several spatial smoothness priors applicable for grid data and discuss the contexts in which these priors can be employed based on different aims. Two such aims are considered, i.e., to identify regions with clustering and to model spatial dependence in the data. Secondly, the choice of the grid size is shown to depend largely on the spatial patterns. We present a guide on the selection of spatial scales and smoothness priors for various point patterns based on the two aims for spatial smoothing.

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Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.