947 resultados para G-extremal processes


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With the aim of elucidating the seasonal behaviour of rare earth elements (REEs), surface and groundwaters were collected under dry and wet conditions in different hydrological units of the Teviot Brook catchment (Southeast Queensland, Australia). Sampled waters showed a large degree of variability in both REE abundance and normalised patterns. Overall REE abundance ranged over nearly three orders of magnitude, and was consistently lower in the sedimentary bedrock aquifer (18ppt<∑REE<477ppt) than in the other hydrological systems studied. Abundance was greater in springs draining rhyolitic rocks (∑REE=300 and 2054ppt) than in springs draining basalt ranges (∑REE=25 and 83ppt), yet was highly variable in the shallow alluvial groundwater (16ppt<∑REE<5294ppt) and, to a lesser extent, in streamwater (85ppt<∑REE<2198ppt). Generally, waters that interacted with different rock types had different REE patterns. In order to obtain an unbiased characterisation of REE patterns, the ratios between light and middle REEs (R(M/L)) and the ratios between middle and heavy REEs (R(H/M)) were calculated for each sample. The sedimentary bedrock aquifer waters had highly evolved patterns depleted in light REEs and enriched in middle and heavy REEs (0.17processes and inter-aquifer mixing. They also underline the importance of conducting seasonal sampling campaigns to capture possible short-term variations in REE patterns and abundance, which is essential to enable a better understanding of hydrological and hydrochemical processes in complex geological settings

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Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity.

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Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.

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Due to ever increasing climate instability, the number of natural disasters affecting society and communities is expected to increase globally in the future, which will result in a growing number of casualties and damage to property and infrastructure. Such damage poses crucial challenges for recovery of interdependent critical infrastructures. Post-disaster reconstruction is a complex undertaking as it is not only closely linked to the well-being and essential functioning of society, but also requires a large financial commitment. Management of critical infrastructure during post-disaster recovery needs to be underpinned by a holistic recognition that the recovery of each individual infrastructure system (e.g. energy, water, transport and information and communication technology) can be affected by the interdependencies that exist between these different systems. A fundamental characteristic of these interdependencies is that failure of one critical infrastructure system can result in the failure of other interdependent infrastructures, leading to a cascade of failures, which can impede post-disaster recovery and delay the subsequent reconstruction process. Consequently, there is a critical need for developing a holistic strategy to assess the influence of infrastructure interdependencies, and for incorporating these interdependencies into a post-disaster recovery strategy. This paper discusses four key dimensions of interdependencies that need to be considered in a post-disaster reconstruction planning. Using key concepts and sub-concepts derived from the notion of interdependency, the paper examines how critical infrastructure interdependencies affect the recovery processes of damaged infrastructures.

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Common to many types of water and wastewater is the presence of sodium ions which can be removed by desalination technologies, such as reverse osmosis and ion exchange. The focus of this investigation was ion exchange as it potentially offered several advantages compared to competing methods. The equilibrium and column behaviour of a strong acid cation (SAC) resin was examined for the removal of sodium ions from aqueous sodium chloride solutions of varying normality as well as a coal seam gas water sample. The influence of the bottle-point method to generate the sorption isotherms was evaluated and data interpreted with the Langmuir Vageler, Competitive Langmuir, Freundlich, and Dubinin-Astakhov models. With the constant concentration bottle point method, the predicted maximum exchange levels of sodium ions on the resin ranged from 61.7 to 67.5 g Na/kg resin. The general trend was that the lower the initial concentration of sodium ions in the solution, the lower the maximum capacity of the resin for sodium ions. In contrast, the constant mass bottle point method was found to be problematic in that the isotherm profiles may not be complete, if experimental parameters were not chosen carefully. Column studies supported the observations of the equilibrium studies, with maximum sodium loading of ca. 62.9 g Na/kg resin measured, which was in excellent agreement with the predictions of the data from the constant concentration bottle point method. Equilibria involving coal seam gas water were more complex due to the presence of sodium bicarbonate in solution, albeit the maximum loading capacity for sodium ions was in agreement with the results from the more simple sodium chloride solutions.

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This paper reports on the results of a project aimed at creating a research-informed, pedagogically reliable, technology-enhanced learning and teaching environment that would foster engagement with learning. A first-year mathematics for engineering unit offered at a large, metropolitan Australian university provides the context for this research. As part of the project, the unit was redesigned using a framework that employed flexible, modular, connected e-learning and teaching experiences. The researchers, interested in an ecological perspective on educational processes, grounded the redesign principles in probabilistic learning design (Kirschner et al., 2004). The effectiveness of the redesigned environment was assessed through the lens of the notion of affordance (Gibson, 1977,1979, Greeno, 1994, Good, 2007). A qualitative analysis of the questionnaire distributed to students at the end of the teaching period provided insight into factors impacting on the successful creation of an environment that encourages complex, multidimensional and multilayered interactions conducive to learning.

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Hamstring strain injuries are the predominant injury in many sports, costing athletes and clubs a significant financial and performance burden. Therefore the ability to identify and intervene with individuals who are considered at a high risk of injury is important. One measure which has grown in popularity as an outcome variable following hamstring intervention/prevention studies and rehabilitation is the angle of peak knee flexor torque. This current opinion article will firstly introduce the measure and the processes behind it. Secondly, this article will summarise how the angle of peak knee flexor torque has been suggested to measure hamstring strain injury risk. Finally various limitations will be presented and outlined as to how they may influence the measure. These include the lack of muscle specificity, the common concentric contraction mode of assessment, reliability of the measure, various neural contributions (such as rate of force development and neuromuscular inhibition) as well as the lack of prospective data showing any predictive value in the measure.

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Design has become increasingly engaged with bringing about social change. Shifting domains and perspectives to conflict stricken contexts yield opportunities to explore emerging forms of design that enable the expression and articulation of difference in productive ways, which can contribute positively to efforts related to civic issues and struggles in urban settings from developing countries. We explore the recently developed notion of Adversarial Design to support the integration of diverging perspectives and grassroots voices in the design process. This paper presents the findings and design insights from our study with two grassroots organisations in Bogota, Colombia. We present three themes that expose ways in which conflict motivates bringing about change, the importance of the social and physical features of the urban landscape, and the way in which social change acts as catalyst for acquiring new knowledge. To finalise, we discuss two design areas and how design could be used to integrate dissimilar worldviews.

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Objective Certain mutations in ANKH, which encodes a multiple-pass transmembrane protein that regulates inorganic pyrophosphate (PPi) transport, are linked to autosomal-dominant familial chondrocalcinosis. This study investigated the potential for ANKH sequence variants to promote sporadic chondrocalcinosis. Methods ANKH variants identified by genomic sequencing were screened for association with chondrocalcinosis in 128 patients with severe sporadic chondrocalcinosis or pseudogout and in ethnically matched healthy controls. The effects of specific variants on expression of common markers were evaluated by in vitro transcription/translation. The function of these variants was studied in transfected human immortalized CH-8 articular chondrocytes. Results Sporadic chondrocalcinosis was associated with a G-to-A transition in the ANKH 5′-untranslated region (5′-UTR) at 4 bp upstream of the start codon (in homozygotes of the minor allele, genotype relative risk 6.0, P = 0.0006; overall genotype association P = 0.02). This -4-bp transition, as well as 2 mutations previously linked with familial and sporadic chondrocalcinosis (+14 bp C-to-T and C-terminal GAG deletion, respectively), but not the French familial chondrocalcinosis kindred 143-bp T-to-C mutation, increased reticulocyte ANKH transcription/ANKH translation in vitro. Transfection of complementary DNA for both the wild-type ANKH and the -4-bp ANKH protein variant promoted increased extracellular PPi in CH-8 cells, but unexpectedly, these ANKH mutants had divergent effects on the expression of extracellular PPi and the chondrocyte hypertrophy marker, type X collagen. Conclusion A subset of sporadic chondrocalcinosis appears to be heritable via a -4-bp G-to-A ANKH 5′-UTR transition that up-regulates expression of ANKH and extracellular PPi in chondrocyte cells. Distinct ANKH mutations associated with heritable chondrocalcinosis may promote disease by divergent effects on extracellular PPi and chondrocyte hypertrophy, which is likely to mediate differences in the clinical phenotypes and severity of the disease.

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The social economy as a regional development actor is gaining greater attention given its purported ability to address social and environmental problems. This growth in interest is occurring within a global environment that is calling for a more holistic understanding of development compared to traditionally economic-centric conceptions. While regional development policies and practices have long considered for-profit businesses as agents for regional growth, there is a relatively limited understanding of the role of the social economy as a development actor. The institutional environment is a large determinant of all kinds of entrepreneurial activity, and therefore understanding the relationships between the social economy and broader regional development processes is warranted. This paper moves beyond suggestions of an economic-centric focus of regional development by utilising institutional logics as a theoretical framework for understanding the role of social enterprise in regional development. A multiple case study of ten social enterprises in two regional locations in Australia suggests that social enterprise can represent competing logics to economic-centric institutional values and systems. The paper argues that dominant institutional logics can constrain or promote the inter-play between the social and the economic aspects of development, in the context of social enterprise.

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Introduction: A number of genetic-association studies have identified genes contributing to ankylosing spondylitis (AS) susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a 'snapshot' of the sampled cells' activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort. Methods: A total of 18 active AS patients, classified according to the New York criteria, and 18 gender- and age-matched controls were profiled using Illumina HT-12 whole-genome expression BeadChips which carry cDNAs for 48,000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan low density arrays (TLDAs). Results: A total of 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a P-value <0.0005 (80% confidence level of false discovery rate). Forty-seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 downregulated 1.3- to 2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300, which modulate cartilage and bone metabolism. Conclusions: We have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease.

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Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

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In this work, we consider subordinated processes controlled by a family of subordinators which consist of a power function of a time variable and a negative power function of an α-stable random variable. The effect of parameters in the subordinators on the subordinated process is discussed. By suitable variable substitutions and the Laplace transform technique, the corresponding fractional Fokker–Planck-type equations are derived. We also compute their mean square displacements in a free force field. By choosing suitable ranges of parameters, the resulting subordinated processes may be subdiffusive, normal diffusive or superdiffusive

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This paper proposes the Clinical Pathway Analysis Method (CPAM) approach that enables the extraction of valuable organisational and medical information on past clinical pathway executions from the event logs of healthcare information systems. The method deals with the complexity of real-world clinical pathways by introducing a perspective-based segmentation of the date-stamped event log. CPAM enables the clinical pathway analyst to effectively and efficiently acquire a profound insight into the clinical pathways. By comparing the specific medical conditions of patients with the factors used for characterising the different clinical pathway variants, the medical expert can identify the best therapeutic option. Process mining-based analytics enables the acquisition of valuable insights into clinical pathways, based on the complete audit traces of previous clinical pathway instances. Additionally, the methodology is suited to assess guideline compliance and analyse adverse events. Finally, the methodology provides support for eliciting tacit knowledge and providing treatment selection assistance.

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Molecular phylogenetic studies of homologous sequences of nucleotides often assume that the underlying evolutionary process was globally stationary, reversible, and homogeneous (SRH), and that a model of evolution with one or more site-specific and time-reversible rate matrices (e.g., the GTR rate matrix) is enough to accurately model the evolution of data over the whole tree. However, an increasing body of data suggests that evolution under these conditions is an exception, rather than the norm. To address this issue, several non-SRH models of molecular evolution have been proposed, but they either ignore heterogeneity in the substitution process across sites (HAS) or assume it can be modeled accurately using the distribution. As an alternative to these models of evolution, we introduce a family of mixture models that approximate HAS without the assumption of an underlying predefined statistical distribution. This family of mixture models is combined with non-SRH models of evolution that account for heterogeneity in the substitution process across lineages (HAL). We also present two algorithms for searching model space and identifying an optimal model of evolution that is less likely to over- or underparameterize the data. The performance of the two new algorithms was evaluated using alignments of nucleotides with 10 000 sites simulated under complex non-SRH conditions on a 25-tipped tree. The algorithms were found to be very successful, identifying the correct HAL model with a 75% success rate (the average success rate for assigning rate matrices to the tree's 48 edges was 99.25%) and, for the correct HAL model, identifying the correct HAS model with a 98% success rate. Finally, parameter estimates obtained under the correct HAL-HAS model were found to be accurate and precise. The merits of our new algorithms were illustrated with an analysis of 42 337 second codon sites extracted from a concatenation of 106 alignments of orthologous genes encoded by the nuclear genomes of Saccharomyces cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, S. castellii, S. kluyveri, S. bayanus, and Candida albicans. Our results show that second codon sites in the ancestral genome of these species contained 49.1% invariable sites, 39.6% variable sites belonging to one rate category (V1), and 11.3% variable sites belonging to a second rate category (V2). The ancestral nucleotide content was found to differ markedly across these three sets of sites, and the evolutionary processes operating at the variable sites were found to be non-SRH and best modeled by a combination of eight edge-specific rate matrices (four for V1 and four for V2). The number of substitutions per site at the variable sites also differed markedly, with sites belonging to V1 evolving slower than those belonging to V2 along the lineages separating the seven species of Saccharomyces. Finally, sites belonging to V1 appeared to have ceased evolving along the lineages separating S. cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, and S. bayanus, implying that they might have become so selectively constrained that they could be considered invariable sites in these species.