999 resultados para Topology change


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- Objective To compare health service cost and length of stay between a traditional and an accelerated diagnostic approach to assess acute coronary syndromes (ACS) among patients who presented to the emergency department (ED) of a large tertiary hospital in Australia. - Design, setting and participants This historically controlled study analysed data collected from two independent patient cohorts presenting to the ED with potential ACS. The first cohort of 938 patients was recruited in 2008–2010, and these patients were assessed using the traditional diagnostic approach detailed in the national guideline. The second cohort of 921 patients was recruited in 2011–2013 and was assessed with the accelerated diagnostic approach named the Brisbane protocol. The Brisbane protocol applied early serial troponin testing for patients at 0 and 2 h after presentation to ED, in comparison with 0 and 6 h testing in traditional assessment process. The Brisbane protocol also defined a low-risk group of patients in whom no objective testing was performed. A decision tree model was used to compare the expected cost and length of stay in hospital between two approaches. Probabilistic sensitivity analysis was used to account for model uncertainty. - Results Compared with the traditional diagnostic approach, the Brisbane protocol was associated with reduced expected cost of $1229 (95% CI −$1266 to $5122) and reduced expected length of stay of 26 h (95% CI −14 to 136 h). The Brisbane protocol allowed physicians to discharge a higher proportion of low-risk and intermediate-risk patients from ED within 4 h (72% vs 51%). Results from sensitivity analysis suggested the Brisbane protocol had a high chance of being cost-saving and time-saving. - Conclusions This study provides some evidence of cost savings from a decision to adopt the Brisbane protocol. Benefits would arise for the hospital and for patients and their families.

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Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

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Online groups rely on contributions from their members to flourish, but in the context of behaviour change individuals are typically reluctant to participate actively before they have changed successfully. We took inspiration from CSCW research on objects to address this problem by shifting the focus of online participation from the exchange of personal experiences to more incidental interactions mediated by objects that offer support for change. In this article we describe how we designed, deployed and studied a smartphone application that uses different objects, called distractions and tips, to facilitate social interaction amongst people trying to quit smoking. A field study with 18 smokers revealed different forms of interaction: purely instrumental interactions with the objects, subtle engagement with other users through receptive and covert interactions, as well as explicit interaction with other users through disclosure and mutual support. The distraction objects offered a stepping-stone into interaction, whereas the tips encouraged interaction with the people behind the objects. This understanding of interaction through objects complements existing frameworks of online participation and adds to the current discourse on object-centred sociality. Furthermore, it provides an alternative approach to the design of online support groups, which offers the users enhanced control about the information they share with other users. We conclude by discussing how researchers and practitioners can apply the ideas of interaction around objects to other domains where individuals may have a simultaneous desire and reluctance to interact.

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This article introduces the theme issue on social interaction and reflection for behaviour change. A large body of research exists on systems designed to help users in changing their behaviours, for instance, to exercise more regularly or to reduce energy consumption. Increasingly, these systems focus on multiple users, often to encourage open-ended reflection rather than prescribing a particular course of action. As background for this theme issue, this article presents a literature review on behaviour change support systems that focus on social interaction and reflection. The review highlights five key approaches amongst these systems: social traces, social support, collective use, reflection-in-action, and reflection-on-action. Each approach offers unique benefits, but also challenges for the design of behaviour change support systems. We highlight how the articles in this theme issue contribute to our current understanding of these five approaches, and beyond that, set out some broad directions for future work.

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The First International Workshop on Behavior Change Support Systems attracted a great research interest. The selected papers focused on abstraction, implementation and evaluation of Behavior Change Support Systems. The workshop is an evidence of how researchers from around the globe have their own perspective of behavior change interventions. In this abstract, we have attempted to outline core issues that can enhance persuasiveness of such support systems. Finally, we highlight important research questions relating to the development of effective Behavior Change Support Systems.

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Technologies that facilitate the collection and sharing of personal information can feed people's desire for enhanced self-knowledge and help them to change their behaviour, yet for various reasons people can also be reluctant to use such technologies. This paper explores this tension through an interview study in the context of smoking cessation. Our findings show that smokers and recent ex-smokers were ambivalent about their behaviour change as well as about collecting personal information through technology and sharing it with other users. We close with a summary of three challenges emerging from such ambivalence and directions to address them.

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The dissertation consists of an introductory chapter and three essays that apply search-matching theory to study the interaction of labor market frictions, technological change and macroeconomic fluctuations. The first essay studies the impact of capital-embodied growth on equilibrium unemployment by extending a vintage capital/search model to incorporate vintage human capital. In addition to the capital obsolescence (or creative destruction) effect that tends to raise unemployment, vintage human capital introduces a skill obsolescence effect of faster growth that has the opposite sign. Faster skill obsolescence reduces the value of unemployment, hence wages and leads to more job creation and less job destruction, unambiguously reducing unemployment. The second essay studies the effect of skill biased technological change on skill mismatch and the allocation of workers and firms in the labor market. By allowing workers to invest in education, we extend a matching model with two-sided heterogeneity to incorporate an endogenous distribution of high and low skill workers. We consider various possibilities for the cost of acquiring skills and show that while unemployment increases in most scenarios, the effect on the distribution of vacancy and worker types varies according to the structure of skill costs. When the model is extended to incorporate endogenous labor market participation, we show that the unemployment rate becomes less informative of the state of the labor market as the participation margin absorbs employment effects. The third essay studies the effects of labor taxes on equilibrium labor market outcomes and macroeconomic dynamics in a New Keynesian model with matching frictions. Three policy instruments are considered: a marginal tax and a tax subsidy to produce tax progression schemes, and a replacement ratio to account for variability in outside options. In equilibrium, the marginal tax rate and replacement ratio dampen economic activity whereas tax subsidies boost the economy. The marginal tax rate and replacement ratio amplify shock responses whereas employment subsidies weaken them. The tax instruments affect the degree to which the wage absorbs shocks. We show that increasing tax progression when taxation is initially progressive is harmful for steady state employment and output, and amplifies the sensitivity of macroeconomic variables to shocks. When taxation is initially proportional, increasing progression is beneficial for output and employment and dampens shock responses.

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Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

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One of the most popular topics in tourism research is destination image. That is, measuring consumers’ perceptions of a destination. The importance of the topic is a no brainer given travellers are spoilt by choice of destinations, and that the images they hold of a place are as important as the tangible tourism features. This is underpinned by the old adage perception is reality, a theory promoted by two academics back in 1928 who proposed “what people believe to be true will be real in its consequences”. So, every place marketer knows consumer perceptions play a major role in the competitiveness of their destination.

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Measurements of both the velocity and the temperature field have been made in the thermal layer that grows inside a turbulent boundary layer which is subjected to a small step change in surface heat flux. Upstream of the step, the wall heat flux is zero and the velocity boundary layer is nearly self-preserving. The thermal-layer measurements are discussed in the context of a self-preserving analysis for the temperature disturbance which grows underneath a thick external turbulent boundary layer. A logarithmic mean temperature profile is established downstream of the step but the budget for the mean-square temperature fluctuations shows that, in the inner region of the thermal layer, the production and dissipation of temperature fluctuations are not quite equal at the furthest downstream measurement station. The measurements for both the mean and the fluctuating temperature field indicate that the relaxation distance for the thermal layer is quite large, of the order of 1000θ0, where θ0 is the momentum thickness of the boundary layer at the step. Statistics of the thermal-layer interface and conditionally sampled measurements with respect to this interface are presented. Measurements of the temperature intermittency factor indicate that the interface is normally distributed with respect to its mean position. Near the step, the passive heat contaminant acts as an effective marker of the organized turbulence structure that has been observed in the wall region of a boundary layer. Accordingly, conditional averages of Reynolds stresses and heat fluxes measured in the heated part of the flow are considerably larger than the conventional averages when the temperature intermittency factor is small.

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Motivated by a problem from fluid mechanics, we consider a generalization of the standard curve shortening flow problem for a closed embedded plane curve such that the area enclosed by the curve is forced to decrease at a prescribed rate. Using formal asymptotic and numerical techniques, we derive possible extinction shapes as the curve contracts to a point, dependent on the rate of decreasing area; we find there is a wider class of extinction shapes than for standard curve shortening, for which initially simple closed curves are always asymptotically circular. We also provide numerical evidence that self-intersection is possible for non-convex initial conditions, distinguishing between pinch-off and coalescence of the curve interior.

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The amount of financial loss from online fraud suffered by people in Western Australia has almost halved, dropping from A$16.8 million in 2014 to A$9.8 million for 2015, according to a statement this January from the state’s Attorney General and Minister for Commerce, Michael Mischin. In addition, the minister noted that losses from relationship and dating fraud have fallen by 55%, to A$4.9 million lost last year. These are both impressive claims, and at face value, there is truth to the statistics. Both assertions are based on data received by WA’s Scamnet, which is the public interface between consumer protection and citizens. While it is good to see a reduction in the number of losses overall, particularly to relationship and dating fraud, it is highly unlikely that the statistics tell the full story.

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This book investigates the ethical values that inform the global carbon integrity system, and reflects on alternative norms that could or should do so. The global carbon integrity system comprises the emerging international architecture being built to respond to the climate change. This architecture can be understood as an 'integrity system'- an inter-related set of institutions, governance arrangements, regulations and practices that work to ensure the system performs its role faithfully and effectively. This volume investigates the ways ethical values impact on where and how the integrity system works, where it fails, and how it can be improved. With a wide array of perspectives across many disciplines, including ethicists, philosophers, lawyers, governance experts and political theorists, the chapters seek to explore the positive values driving the global climate change processes, to offer an understanding of the motivations justifying the creation of the regime and the way that social norms impact upon the operation of the integrity system. The collection focuses on the nexus between ideal ethics and real-world implementation through institutions and laws. The book will be of interest to policy makers, climate change experts, carbon taxation regulators, academics, legal practitioners and researchers.

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In this article, we propose a denoising algorithm to denoise a time series y(i) = x(i) + e(i), where {x(i)} is a time series obtained from a time- T map of a uniformly hyperbolic or Anosov flow, and {e(i)} a uniformly bounded sequence of independent and identically distributed (i.i.d.) random variables. Making use of observations up to time n, we create an estimate of x(i) for i<n. We show under typical limiting behaviours of the orbit and the recurrence properties of x(i), the estimation error converges to zero as n tends to infinity with probability 1.