984 resultados para heterogeneous sources


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Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. Results We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. Conclusions We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers

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In this paper, we analyse the impact of a (small) heterogeneity of jump type on the most simple localized solutions of a 3-component FitzHugh–Nagumo-type system. We show that the heterogeneity can pin a 1-front solution, which travels with constant (non-zero) speed in the homogeneous setting, to a fixed, explicitly determined, distance from the heterogeneity. Moreover, we establish the stability of this heterogeneous pinned 1-front solution. In addition, we analyse the pinning of 1-pulse, or 2-front, solutions. The paper is concluded with simulations in which we consider the dynamics and interactions of N-front patterns in domains with M heterogeneities of jump type (N = 3, 4, M ≥ 1).

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Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

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A global, online quantitative study among 300 consumers of digital technology products found the most reliable information sources were friends, family or word of mouth (WOM) from someone they knew, followed by expert product reviews, and product reviews written by other consumers. The most unreliable information sources were advertising or infomercials, automated recommendations based on purchasing patterns or retailers. While a very small number of consumers evaluated products online, rating of products and online discussions were more frequent activities. The most popular social media websites for reviews were Facebook, Twitter, Amazon and e-Bay, indicating the importance of WOM in social networks and online media spaces that feature product reviews as it is the most persuasive piece of information in both online and offline social networks. These results suggest that ‘social customers’ must be considered as an integral part of a marketing strategy.

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An increased interest in utilising groups of Unmanned Aerial Vehicles (UAVs) with heterogeneous capabilities and autonomy is presenting the challenge to effectively manage such during missions and operations. This has been the focus of research in recent years, moving from a traditional UAV management paradigm of n-to-1 (n operators for one UAV, with n being at least two operators) toward 1-to-n (one operator, multiple UAVs). This paper has expanded on the authors’ previous work on UAV functional capability framework, by incorporating the concept of Functional Level of Autonomy (F-LOA) with two configurations: The lower F-LOA configuration contains sufficient information for the operator to generate solutions and make decisions to address perturbation events. Alternatively, the higher F-LOA configuration presents information reflecting on the F-LOA of the UAV, allowing the operator to interpret solutions and decisions generated autonomously, and decide whether to veto from this decision.

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This paper deals with causal effect estimation strategies in highly heterogeneous empirical settings such as entrepreneurship. We argue that the clearer used of modern tools developed to deal with the estimation of causal effects in combination with our analysis of different sources of heterogeneity in entrepreneurship can lead to entrepreneurship with higher internal validity. We specifically lend support from the counterfactual logic and modern research of estimation strategies for causal effect estimation.

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These notes were compiled from several authorities to be used for teaching and learning purposes here at QUT, with the focus on first and second year landscape architecture design studio units.

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Spreadsheet for Creative City Index 2012

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This research was a step forward in developing a data integration framework for Electronic Health Records. The outcome of the research is a conceptual and logical Data Warehousing model for integrating Cardiac Surgery electronic data records. This thesis investigated the main obstacles for the healthcare data integration and proposes a data warehousing model suitable for integrating fragmented data in a Cardiac Surgery Unit.

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The objective of this PhD research program is to investigate numerical methods for simulating variably-saturated flow and sea water intrusion in coastal aquifers in a high-performance computing environment. The work is divided into three overlapping tasks: to develop an accurate and stable finite volume discretisation and numerical solution strategy for the variably-saturated flow and salt transport equations; to implement the chosen approach in a high performance computing environment that may have multiple GPUs or CPU cores; and to verify and test the implementation. The geological description of aquifers is often complex, with porous materials possessing highly variable properties, that are best described using unstructured meshes. The finite volume method is a popular method for the solution of the conservation laws that describe sea water intrusion, and is well-suited to unstructured meshes. In this work we apply a control volume-finite element (CV-FE) method to an extension of a recently proposed formulation (Kees and Miller, 2002) for variably saturated groundwater flow. The CV-FE method evaluates fluxes at points where material properties and gradients in pressure and concentration are consistently defined, making it both suitable for heterogeneous media and mass conservative. Using the method of lines, the CV-FE discretisation gives a set of differential algebraic equations (DAEs) amenable to solution using higher-order implicit solvers. Heterogeneous computer systems that use a combination of computational hardware such as CPUs and GPUs, are attractive for scientific computing due to the potential advantages offered by GPUs for accelerating data-parallel operations. We present a C++ library that implements data-parallel methods on both CPU and GPUs. The finite volume discretisation is expressed in terms of these data-parallel operations, which gives an efficient implementation of the nonlinear residual function. This makes the implicit solution of the DAE system possible on the GPU, because the inexact Newton-Krylov method used by the implicit time stepping scheme can approximate the action of a matrix on a vector using residual evaluations. We also propose preconditioning strategies that are amenable to GPU implementation, so that all computationally-intensive aspects of the implicit time stepping scheme are implemented on the GPU. Results are presented that demonstrate the efficiency and accuracy of the proposed numeric methods and formulation. The formulation offers excellent conservation of mass, and higher-order temporal integration increases both numeric efficiency and accuracy of the solutions. Flux limiting produces accurate, oscillation-free solutions on coarse meshes, where much finer meshes are required to obtain solutions with equivalent accuracy using upstream weighting. The computational efficiency of the software is investigated using CPUs and GPUs on a high-performance workstation. The GPU version offers considerable speedup over the CPU version, with one GPU giving speedup factor of 3 over the eight-core CPU implementation.

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The control paradigms of the distributed generation (DG) sources in the smart grid are realised by either utilising virtual power plant (VPP) or by employing MicroGrid structures. Both VPP and MicroGrid are presented with the problem of control of power flow between their comprising DG sources. This study depicts this issue for VPP and proposes a novel and improved universal active and reactive power flow controllers for three-phase pulse width modulated voltage source inverters (PWM-VSI) operating in the VPP environment. The proposed controller takes into account all cases of R-X relationship, thus allowing it to function in systems operating at high, medium (MV) and low-voltage (LV) levels. Also proposed control scheme for the first time in an inverter control takes into account the capacitance of the transmission line which is an important factor to accurately represent medium length transmission lines. This allows the proposed control scheme to be applied in VPP structures, where DG sources can operate at MV LV levels over a short/medium length transmission line. The authors also conducted small signal stability analysis of the proposed controller and compared it against the small signal study of the existing controllers.

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Eco-feedback interventions are capable of producing reductions in household energy consumption. Yet less is known about exactly how this reduction is achieved, how to maximise user engagement, or how to effectively translate engagement into energy saving. This paper discusses design opportunities for eco-feedback systems through observations of domestic energy use in both Western and rural developing world contexts. Drawing on case studies from these two contexts including 21 empirical interviews, we present an alternative framework for human-resource interaction, highlighting design opportunities for a transition towards more engaged and sustainable energy consumption among users.

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This thesis represents a major step forward in understanding the link between the development of combustion related faults in diesel engines and the generation of acoustic emissions. The findings presented throughout the thesis provide a foundation so that future diesel engine monitoring systems are able to more effectively detect and monitor developing faults. In undertaking this research knowledge concerning engine function and relevant failure mechanisms was combined with different modelling methods to generate a framework that was used to effectively identify fault related activity within acoustic emissions recorded from different engines.

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Generating nano-sized materials of a controlled size and chemical composition is essential for the manufacturing of materials with enhanced properties on an industrial scale, as well as for research purposes, such as toxicological studies. Among the generation methods for airborne nanoparticles (also known as aerosolisation methods), liquid-phase techniques have been widely applied due to the simplicity of their use and their high particle production rate. The use of a collison nebulizer is one such technique, in which the atomisation takes place as a result of the liquid being sucked into the air stream and injected toward the inner walls of the nebulizer reservoir via nozzles, before the solution is dispersed. Despite the above-mentioned benefits, this method also falls victim to various sources of impurities (Knight and Petrucci 2003; W. LaFranchi, Knight et al. 2003). Since these impurities can affect the characterization of the generated nanoparticles, it is crucial to understand and minimize their effect.

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A novel method was developed for studying the genetic relatedness of Pseudomonas aeruginosa isolates from clinical and environmental sources. This bacterium is ubiquitous in the natural environment and is an important pathogen known to infect Cystic Fibrosis (CF) patients. The transmission route of strains has not yet been defined; current theories include acquisition from an environmental source or through patient-to-patient spread. A highly discriminatory, bioinformatics based, DNA typing method was developed to investigate the relatedness of clinical and environmental isolates. This study found a similarity between the environmental and several CF clonal strains and also highlighted occurrence of environmental P. aeruginosa strains in CF infections.