928 resultados para Multivariate GARCH models


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Parallel interleaved converters are finding more applications everyday, for example they are frequently used for VRMs on PC main boards mainly to obtain better transient response. Parallel interleaved converters can have their inductances uncoupled, directly coupled or inversely coupled, all of which have different applications with associated advantages and disadvantages. Coupled systems offer more control over converter features, such as ripple currents, inductance volume and transient response. To be able to gain an intuitive understanding of which type of parallel interleaved converter, what amount of coupling, what number of levels and how much inductance should be used for different applications a simple equivalent model is needed. As all phases of an interleaved converter are supposed to be identical, the equivalent model is nothing more than a separate inductance which is common to all phases. Without utilising this simplification the design of a coupled system is quite daunting. Being able to design a coupled system involves solving and understanding the RMS currents of the input, individual phase (or cell) and output. A procedure using this equivalent model and a small amount of modulo arithmetic is detailed.

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This thesis concerns the mathematical model of moving fluid interfaces in a Hele-Shaw cell: an experimental device in which fluid flow is studied by sandwiching the fluid between two closely separated plates. Analytic and numerical methods are developed to gain new insights into interfacial stability and bubble evolution, and the influence of different boundary effects is examined. In particular, the properties of the velocity-dependent kinetic undercooling boundary condition are analysed, with regard to the selection of only discrete possible shapes of travelling fingers of fluid, the formation of corners on the interface, and the interaction of kinetic undercooling with the better known effect of surface tension. Explicit solutions to the problem of an expanding or contracting ring of fluid are also developed.

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This paper evaluates the efficiency of a number of popular corpus-based distributional models in performing discovery on very large document sets, including online collections. Literature-based discovery is the process of identifying previously unknown connections from text, often published literature, that could lead to the development of new techniques or technologies. Literature-based discovery has attracted growing research interest ever since Swanson's serendipitous discovery of the therapeutic effects of fish oil on Raynaud's disease in 1986. The successful application of distributional models in automating the identification of indirect associations underpinning literature-based discovery has been heavily demonstrated in the medical domain. However, we wish to investigate the computational complexity of distributional models for literature-based discovery on much larger document collections, as they may provide computationally tractable solutions to tasks including, predicting future disruptive innovations. In this paper we perform a computational complexity analysis on four successful corpus-based distributional models to evaluate their fit for such tasks. Our results indicate that corpus-based distributional models that store their representations in fixed dimensions provide superior efficiency on literature-based discovery tasks.

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In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modelling interactions between such species, we often make use of the mean field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean field approximation is only used in appropriate settings. In circumstances where the mean field approximation is unsuitable we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper we provide a method that overcomes many of the failures of the mean field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multi-species case, and show results specific to a two-species problem. We compare averaged discrete results to both the mean field approximation and our improved method which incorporates spatial correlations. We note that the mean field approximation fails dramatically in some cases, predicting very different behaviour from that seen upon averaging multiple realisations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behaviour in all cases, thus providing a more reliable modelling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.

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Electricity is the cornerstone of modern life. It is essential to economic stability and growth, jobs and improved living standards. Electricity is also the fundamental ingredient for a dignified life; it is the source of such basic human requirements as cooked food, a comfortable living temperature and essential health care. For these reasons, it is unimaginable that today's economies could function without electricity and the modern energy services that it delivers. Somewhat ironically, however, the current approach to electricity generation also contributes to two of the gravest and most persistent problems threatening the livelihood of humans. These problems are anthropogenic climate change and sustained human poverty. To address these challenges, the global electricity sector must reduce its reliance on fossil fuel sources. In this context, the object of this research is twofold. Initially it is to consider the design of the Renewable Energy (Electricity) Act 2000 (Cth) (Renewable Electricity Act), which represents Australia's primary regulatory approach to increase the production of renewable sourced electricity. This analysis is conducted by reference to the regulatory models that exist in Germany and Great Britain. Within this context, this thesis then evaluates whether the Renewable Electricity Act is designed effectively to contribute to a more sustainable and dignified electricity generation sector in Australia. On the basis of the appraisal of the Renewable Electricity Act, this thesis contends that while certain aspects of the regulatory regime have merit, ultimately its design does not represent an effective and coherent regulatory approach to increase the production of renewable sourced electricity. In this regard, this thesis proposes a number of recommendations to reform the existing regime. These recommendations are not intended to provide instantaneous or simple solutions to the current regulatory regime. Instead, the purpose of these recommendations is to establish the legal foundations for an effective regulatory regime that is designed to increase the production of renewable sourced electricity in Australia in order to contribute to a more sustainable and dignified approach to electricity production.

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Introduction. The purpose of this chapter is to address the question raised in the chapter title. Specifically, how can models of motor control help us understand low back pain (LBP)? There are several classes of models that have been used in the past for studying spinal loading, stability, and risk of injury (see Reeves and Cholewicki (2003) for a review of past modeling approaches), but for the purpose of this chapter we will focus primarily on models used to assess motor control and its effect on spine behavior. This chapter consists of 4 sections. The first section discusses why a shift in modeling approaches is needed to study motor control issues. We will argue that the current approach for studying the spine system is limited and not well-suited for assessing motor control issues related to spine function and dysfunction. The second section will explore how models can be used to gain insight into how the central nervous system (CNS) controls the spine. This segues segue nicely into the next section that will address how models of motor control can be used in the diagnosis and treatment of LBP. Finally, the last section will deal with the issue of model verification and validity. This issue is important since modelling accuracy is critical for obtaining useful insight into the behavior of the system being studied. This chapter is not intended to be a critical review of the literature, but instead intended to capture some of the discussion raised during the 2009 Spinal Control Symposium, with some elaboration on certain issues. Readers interested in more details are referred to the cited publications.

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This project’s aim was to create new experimental models in small animals for the investigation of infections related to bone fracture fixation implants. Animal models are essential in orthopaedic trauma research and this study evaluated new implants and surgical techniques designed to improve standardisation in these experiments, and ultimately to minimise the number of animals needed in future work. This study developed and assessed procedures using plates and inter-locked nails to stabilise fractures in rabbit thigh bones. Fracture healing was examined with mechanical testing and histology. The results of this work contribute to improvements in future small animal infection experiments.

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Pavlovian fear conditioning is a robust technique for examining behavioral and cellular components of fear learning and memory. In fear conditioning, the subject learns to associate a previously neutral stimulus with an inherently noxious co-stimulus. The learned association is reflected in the subjects' behavior upon subsequent re-exposure to the previously neutral stimulus or the training environment. Using fear conditioning, investigators can obtain a large amount of data that describe multiple aspects of learning and memory. In a single test, researchers can evaluate functional integrity in fear circuitry, which is both well characterized and highly conserved across species. Additionally, the availability of sensitive and reliable automated scoring software makes fear conditioning amenable to high-throughput experimentation in the rodent model; thus, this model of learning and memory is particularly useful for pharmacological and toxicological screening. Due to the conserved nature of fear circuitry across species, data from Pavlovian fear conditioning are highly translatable to human models. We describe equipment and techniques needed to perform and analyze conditioned fear data. We provide two examples of fear conditioning experiments, one in rats and one in mice, and the types of data that can be collected in a single experiment. © 2012 Springer Science+Business Media, LLC.

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Pavlovian fear conditioning, also known as classical fear conditioning is an important model in the study of the neurobiology of normal and pathological fear. Progress in the neurobiology of Pavlovian fear also enhances our understanding of disorders such as posttraumatic stress disorder (PTSD) and with developing effective treatment strategies. Here we describe how Pavlovian fear conditioning is a key tool for understanding both the neurobiology of fear and the mechanisms underlying variations in fear memory strength observed across different phenotypes. First we discuss how Pavlovian fear models aspects of PTSD. Second, we describe the neural circuits of Pavlovian fear and the molecular mechanisms within these circuits that regulate fear memory. Finally, we show how fear memory strength is heritable; and describe genes which are specifically linked to both changes in Pavlovian fear behavior and to its underlying neural circuitry. These emerging data begin to define the essential genes, cells and circuits that contribute to normal and pathological fear.

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The co-creation of cultural artefacts has been democratised given the recent technological affordances of information and communication technologies. Web 2.0 technologies have enabled greater possibilities of citizen inclusion within the media conversations of their nations. For example, the Australian audience has more opportunities to collaboratively produce and tell their story to a broader audience via the public service media (PSM) facilitated platforms of the Australian Broadcasting Corporation (ABC). However, providing open collaborative production for the audience gives rise to the problem, how might the PSM manage the interests of all the stakeholders and align those interests with its legislated Charter? This paper considers this problem through the ABC’s user-created content participatory platform, ABC Pool and highlights the cultural intermediary as the role responsible for managing these tensions. This paper also suggests cultural intermediation is a useful framework for other media organisations engaging in co-creative activities with their audiences.

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The co-creation of cultural artefacts has been democratised given the recent technological affordances of information and communication technologies. Web 2.0 technologies have enabled greater possibilities of citizen inclusion within the media conversations of their nations. For example, the Australian audience has more opportunities to collaboratively produce and tell their story to a broader audience via the public service media (PSM) facilitated platforms of the Australian Broadcasting Corporation (ABC). However, providing open collaborative production for the audience gives rise to the problem, how might the PSM manage the interests of all the stakeholders and align those interests with its legislated Charter? This paper considers this problem through the ABC’s user-created content participatory platform, ABC Pool and highlights the cultural intermediary as the role responsible for managing these tensions. This paper also suggests cultural intermediation is a useful framework for other media organisations engaging in co-creative activities with their audiences.

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Background The incidence of malignant mesothelioma is increasing. There is the perception that survival is worse in the UK than in other countries. However, it is important to compare survival in different series based on accurate prognostic data. The European Organisation for Research and Treatment of Cancer (EORTC) and the Cancer and Leukaemia Group B (CALGB) have recently published prognostic scoring systems. We have assessed the prognostic variables, validated the EORTC and CALGB prognostic groups, and evaluated survival in a series of 142 patients. Methods Case notes of 142 consecutive patients presenting in Leicester since 1988 were reviewed. Univariate analysis of prognostic variables was performed using a Cox proportional hazards regression model. Statistically significant variables were analysed further in a forward, stepwise multivariate model. EORTC and CALGB prognostic groups were derived, Kaplan-Meier survival curves plotted, and survival rates were calculated from life tables. Results Significant poor prognostic factors in univariate analysis included male sex, older age, weight loss, chest pain, poor performance status, low haemoglobin, leukocytosis, thrombocytosis, and non-epithelial cell type (p<0.05). The prognostic significance of cell type, haemoglobin, white cell count, performance status, and sex were retained in the multivariate model. Overall median survival was 5.9 (range 0-34.3) months. One and two year survival rates were 21.3% (95% CI 13.9 to 28.7) and 3.5% (0 to 8.5), respectively. Median, one, and two year survival data within prognostic groups in Leicester were equivalent to the EORTC and CALGB series. Survival curves were successfully stratified by the prognostic groups. Conclusions This study validates the EORTC and CALGB prognostic scoring systems which should be used both in the assessment of survival data of series in different countries and in the stratification of patients into randomised clinical studies.

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Matrix metalloproteinases (MMPs), in particular the gelatinases (MMP-2 and -9), play a significant role in tumour invasion and angiogenesis. The expression and activities of MMPs have not been characterised in malignant mesothelioma (MM) tumour samples. In a prospective study, gelatinase activity was evaluated in homogenised supernatants of snap frozen MM (n = 35), inflamed pleura (IP, n = 12) and uninflammed pleura (UP, n = 14) tissue specimens by semiquantitative gelatin zymography. Matrix metalloproteinases were correlated with clinicopathological factors and with survival using Kaplan-Meier and Cox proportional hazard models. In MM, pro- and active MMP-2 levels were significantly greater than for MMP-9 (P = 0.006, P<0.001). Active MMP-2 was significantly greater in MM than in UP (P=0.04). MMP-2 activity was equivalent between IP and MM, but both pro- and active MMP-9 activities were greater in IP (P=0.02, P=0.009). While there were trends towards poor survival with increasing total and pro-MMP-2 activity (P=0.08) in univariate analysis, they were both independent poor prognostic factors in multivariate analysis in conjunction with weight loss (pro-MMP-2 P = 0.03, total MMP-2 P = 0.04). Total and pro-MMP-2 also contributed to the Cancer and Leukemia Group B prognostic groups. MMP-9 activities were not prognostic. Matrix metalloproteinases, and in particular MMP-2, the most abundant gelatinase, may play an important role in MM tumour growth and metastasis. Agents that reduce MMP synthesis and/or activity may have a role to play in the management of MM. © 2003 Cancer Research UK.

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Malignant mesothelioma (MM) is a fatal tumour of increasing incidence which is related to asbestos exposure. This work evaluated expression in MM of Epidermal Growth Factor Receptor (EGFR) by immunohistochemistry in 168 tumour sections and its correlations with clinicopathological and biological factors. The microvessel density (MVD) was derived from CD34 immunostained sections. Hematoxylin and eosin stained sections were examined for intratumoural necrosis. COX-2 protein expression was evaluated with semi-quantitative Western blotting of homogenised tumour supernatants (n = 45). EGFR expression was correlated with survival by Kaplan-Meier and log rank analysis. Univariate and multivariate Cox proportional hazards models were used to compare the effects of EGFR with clinicopathological and biological prognostic factors and prognostic scoring systems. EGFR expression was identified in 74 cases (44%) and correlated with epithelioid cell type (p < 0.0001), good performance status (p < 0.0001), the absence of chest pain (p < 0.0001) and the presence of TN (p = 0.004), but not MVD or COX-2. EGFR expression was a good prognostic factor in univariate analysis (p = 0.01). Independent indicators of poor prognosis in multivariate analysis were non-epithelioid cell type (p = 0.0001), weight loss, performance status and WBC > 8.3 × 10 9 L -1. EGFR status was not an independent prognostic factor. EGFR expression in MM correlates with epithelioid histology and TN. EGFR may be a target for selective therapies in MM. © 2006 Elsevier Ireland Ltd. All rights reserved.

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Purpose: To identify a 15-KDa novel hypoxia-induced secreted protein in head and neck squamous cell carcinomas (HNSCC) and to determine its role in malignant progression. Methods: We used surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and tandem MS to identify a novel hypoxia-induced secreted protein in FaDu cells. We used immunoblots, real-time polymerase chain reaction (PCR), and enzyme-linked immunoabsorbent assay to confirm the hypoxic induction of this secreted protein as galectin-1 in cell lines and xenografts. We stained tumor tissues from 101 HNSCC patients for galectin-1, CA IX (carbonic anhydrase IX, a hypoxia marker) and CDS (a T-cell marker). Expression of these markers was correlated to each other and to treatment outcomes. Results: SELDI-TOF studies yielded a hypoxia-induced peak at 15 kDa that proved to be galectin-1 by MS analysis. Immunoblots and PCR studies confirmed increased galectin-1 expression by hypoxia in several cancer cell lines. Plasma levels of galectin-1 were higher in tumor-bearing severe combined immunodeficiency (SCID) mice breathing 10% O 2 compared with mice breathing room air. In HNSCC patients, there was a significant correlation between galectin-1 and CA IX staining (P = .01) and a strong inverse correlation between galectin-1 and CDS staining (P = .01). Expression of galectin-1 and CDS were significant predictors for overall survival on multivariate analysis. Conclusion: Galectin-1 is a novel hypoxia-regulated protein and a prognostic marker in HNSCC. This study presents a new mechanism on how hypoxia can affect the malignant progression and therapeutic response of solid tumors by regulating the secretion of proteins that modulate immune privilege. © 2005 by American Society of Clinical Oncology.