857 resultados para run-time allocation


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Aims: Influenza is commonly spread by infectious aerosols; however, detection of viruses in aerosols is not sensitive enough to confirm the characteristics of virus aerosols. The aim of this study was to develop an assay for respiratory viruses sufficiently sensitive to be used in epidemiological studies. Method: A two-step, nested real-time PCR assay was developed for MS2 bacteriophage, and for influenza A and B, parainfluenza 1 and human respiratory syncytial virus. Outer primer pairs were designed to nest each existing real-time PCR assay. The sensitivities of the nested real-time PCR assays were compared to those of existing real-time PCR assays. Both assays were applied in an aerosol study to compare their detection limits in air samples. Conclusions: The nested real-time PCR assays were found to be several logs more sensitive than the real-time PCR assays, with lower levels of virus detected at lower Ct values. The nested real-time PCR assay successfully detected MS2 in air samples, whereas the real-time assay did not. Significance and Impact of the Study: The sensitive assays for respiratory viruses will permit further research using air samples from naturally generated virus aerosols. This will inform current knowledge regarding the risks associated with the spread of viruses through aerosol transmission.

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Review of 'The Pineapple Queen', La Boite Theatre Company, published in The Australian, 31 July 2009.

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Transportation disadvantage has been recognised to be the key source of social exclusion. Therefore an appropriate process is required to investigate and seek to resolve this problem. Currently, determination of Transportation Disadvantage is postulate based on income, poverty and mobility level. Transportation disadvantage may best regard be based on accessibility perspectives as they represent inability of the individual to access desired activities. This paper attempts to justify a process in determining transportation disadvantage by incorporating accessibility and social transporation conflict as the essence of a framework. The framework embeds space time organisation within the dimension of accessibility to identify a rigorous definition of transportation disadvantage. In developing the framework, the definition, dimension, component and measure of accessibility were scrutinised. The findings suggest the definition and dimension are the significant approach of research to evaluate travel experience of the disadvantaged. Concurrently, location accessibility measures will be incorprated to strenghten the determination of accessibility level. Literature review in social exclusion and mobility-related exclusion identified the dimension and source of transportation disadvantage. It was revealed that the appropriate approach to justify trasnportation disadvantaged is to incorporate space-time organisation within the studied components. The suggested framework is an inter-related process consisting of component of accessibility; individual, networking (transport system) and activities (destination). The integration and correlation among the components shall determine the level of transportation disadvantage. Prior findings are used to retrieve the spatial distribution of transportation disadvantaged and appropriate policies are developed to resolve the problems.

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Purpose Increased physical activity in colorectal cancer patients is related to improved recurrence free and overall survival. Psychological distress after cancer may place patients at risk of reduced physical activity; but paradoxically also act as a motivator for positive lifestyle change. The relationship between psychological distress and physical activity after cancer over time has not been described. Methods A prospective survey of 1966 (57% response) colorectal cancer survivors assessed the psychological distress variables of anxiety, depression, somatisation, cancer threat appraisal as predictors of physical activity five, 12, 24 and 36 months post-diagnosis 978 respondents had valid data for all time points. Results Higher somatisation was associated with greater physical inactivity (Relative risk ratio (RRR) =1.12; 95% CI=[1.1, 1.2]) and insufficient physical activity (RRR=1.05; [0.90, 1.0]). Respondents with a more positive appraisal of their cancer were significantly (p=0.031) less likely to be inactive (RRR=0.95; [0.90, 1.0]) or insufficiently active (RRR=0.96). Fatigued and obese respondents and current smokers were more inactive. Respondents whose somatisation increased between two time periods were less likely to increase their physical activity over the same period (p<0.001). Respondents with higher anxiety at one time period were less likely to have increased their activity at the next assessment (p=0.004). There was no association between depression and physical activity. Conclusions Cancer survivors who experience somatisation and anxiety are at greater risk of physical inactivity. The lack of a clear relationship between higher psychological distress and increasing physical activity argues against distress as a motivator to exercise in these patients.

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This paper examines a sequence of asynchronous interaction on the photosharing website, Flickr. In responding to a call for a focus on the performative aspects of online annotation (Wolff & Neuwirth, 2001), we outline and apply an interaction order approach to identify temporal and cultural aspects of the setting that provide for commonality and sharing. In particular, we study the interaction as a feature of a synthetic situation (Knorr Cetina, 2009) focusing on the requirements of maintaining a sense of an ongoing discussion online. Our analysis suggests that the rhetorical system of the Flickr environment, its appropriation by participants as a context for bounded activities, and displays of commonality, affiliation, and shared access provide for a common sense of participation in a time envelope. This, in turn, is argued to be central to new processes of consociation (Schutz, 1967; Zhao, 2004) occurring in the life world of Web 2.0 environments.

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Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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The epidemic of obesity is impacting an increasing proportion of children, adolescents and adults with a common feature being low levels of physical activity (PA). Despite having more knowledge than ever before about the benefits of PA for health and the growth and development of youngsters, we are only paying lip-service to the development of motor skills in children. Fun, enjoyment and basic skills are the essential underpinnings of meaningful participation in PA. A concurrent problem is the reported increase in sitting time with the most common sedentary behaviors being TV viewing and other screen-based games. Limitations of time have contributed to a displacement of active behaviors with inactive pursuits, which has contributed to reductions in activity energy expenditure. To redress the energy imbalance in overweight and obese children, we urgently need out-of-the-box multisectoral solutions. There is little to be gained from a shame and blame mentality where individuals, their parents, teachers and other groups are singled out as causes of the problem. Such an approach does little more than shift attention from the main game of prevention and management of the condition, which requires a concerted, whole-of-government approach (in each country). The failure to support and encourage all young people to participate in regular PA will increase the chance that our children will live shorter and less healthy lives than their parents. In short, we need novel environmental approaches to foster a systematic increase in PA. This paper provides examples of opportunities and challenges for PA strategies to prevent obesity with a particular emphasis on the school and home settings.

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Technological and societal change, along with organisational and market change (driven by contracting-out and privatisation), are “creating a new generation of infrastructures” [1]. While inter-organisational contractual arrangements can improve maintenance efficiency through consistent and repeatable patterns of action - unanticipated difficulties in implementation can reduce the performance of these arrangements. When faced with unsatisfactory performance of contracting-out arrangements, government organisations may choose to adapt and change these arrangements over time, with the aim of improving performance. This paper enhances our understanding of ‘next generation infrastructures’ by examining adaptation of the organisational arrangements for the maintenance of these assets, in a case study spanning 20 years.

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Reports on the reemergence of a concern with planning city centers as focal points in the 1980s. De-industrialization of older industrial areas; Revalorization of city center sites; Emergence of city-to-city competitiveness at a national and supranational level.

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This paper investigates the robust H∞ control for Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delay. By employing a new and tighter integral inequality and constructing an appropriate type of Lyapunov functional, delay-dependent stability criteria are derived for the control problem. Because neither any model transformation nor free weighting matrices are employed in our theoretical derivation, the developed stability criteria significantly improve and simplify the existing stability conditions. Also, the maximum allowable upper delay bound and controller feedback gains can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples are given to demonstrate the effectiveness of the proposed methods.

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Hope is a word that has re-emerged in light of Obama's stunning win in the United States election. In this time of economic gloom and the reality of bleak recession and unprecedented job losses the United States has embraced the hopeful message of Barack Obama. For many years 'hope' has been a word that has been lost, forgotten , and banished to the margins of romantic longing and wishful thinking. Hope is also a word that has been much discussed in relation to the iconic The Great Gatsby but usually in a negative fashion to demonstrate the unattainability of the American dream. Marcella Taylor called Gatsby "the unfinished American Epic" which focused on the "passing of the last utopian frontier" and suggested the significance of this passing on American society as a whole. In the last months, however, hope has made a return and one gets the feeling that Fitzgerald's words "but that's no matter-to-morrow we will run faster, stretch out our arms farther . . . And one fine morning' are once again being heard.

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While increasing numbers of young high school students engage in part-time work, there is no consensus about its impact on educational outcomes. Indeed this field has had a dearth of research. The present paper presents a review of recent research, primarily from Australia and the US, although it is acknowledged that there are considerable contextual differences. Suggestions for school counsellors to harness the students’ experiences to assist in educational and career decision-making are presented.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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Concern regarding the health effects of indoor air quality has grown in recent years, due to the increased prevalence of many diseases, as well as the fact that many people now spend most of their time indoors. While numerous studies have reported on the dynamics of aerosols indoors, the dynamics of bioaerosols in indoor environments are still poorly understood and very few studies have focused on fungal spore dynamics in indoor environments. Consequently, this work investigated the dynamics of fungal spores in indoor air, including fungal spore release and deposition, as well as investigating the mechanisms involved in the fungal spore fragmentation process. In relation to the investigation of fungal spore dynamics, it was found that the deposition rates of the bioaerosols (fungal propagules) were in the same range as the deposition rates of nonbiological particles and that they were a function of their aerodynamic diameters. It was also found that fungal particle deposition rates increased with increasing ventilation rates. These results (which are reported for the first time) are important for developing an understanding of the dynamics of fungal spores in the air. In relation to the process of fungal spore fragmentation, important information was generated concerning the airborne dynamics of the spores, as well as the part/s of the fungi which undergo fragmentation. The results obtained from these investigations into the dynamics of fungal propagules in indoor air significantly advance knowledge about the fate of fungal propagules in indoor air, as well as their deposition in the respiratory tract. The need to develop an advanced, real-time method for monitoring bioaerosols has become increasingly important in recent years, particularly as a result of the increased threat from biological weapons and bioterrorism. However, to date, the Ultraviolet Aerodynamic Particle Sizer (UVAPS, Model 3312, TSI, St Paul, MN) is the only commercially available instrument capable of monitoring and measuring viable airborne micro-organisms in real-time. Therefore (for the first time), this work also investigated the ability of the UVAPS to measure and characterise fungal spores in indoor air. The UVAPS was found to be sufficiently sensitive for detecting and measuring fungal propagules. Based on fungal spore size distributions, together with fluorescent percentages and intensities, it was also found to be capable of discriminating between two fungal spore species, under controlled laboratory conditions. In the field, however, it would not be possible to use the UVAPS to differentiate between different fungal spore species because the different micro-organisms present in the air may not only vary in age, but may have also been subjected to different environmental conditions. In addition, while the real-time UVAPS was found to be a good tool for the investigation of fungal particles under controlled conditions, it was not found to be selective for bioaerosols only (as per design specifications). In conclusion, the UVAPS is not recommended for use in the direct measurement of airborne viable bioaerosols in the field, including fungal particles, and further investigations into the nature of the micro-organisms, the UVAPS itself and/or its use in conjunction with other conventional biosamplers, are necessary in order to obtain more realistic results. Overall, the results obtained from this work on airborne fungal particle dynamics will contribute towards improving the detection capabilities of the UVAPS, so that it is capable of selectively monitoring and measuring bioaerosols, for which it was originally designed. This work will assist in finding and/or improving other technologies capable of the real-time monitoring of bioaerosols. The knowledge obtained from this work will also be of benefit in various other bioaerosol applications, such as understanding the transport of bioaerosols indoors.