997 resultados para Forecast methods
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Fractional differential equations are becoming increasingly used as a powerful modelling approach for understanding the many aspects of nonlocality and spatial heterogeneity. However, the numerical approximation of these models is demanding and imposes a number of computational constraints. In this paper, we introduce Fourier spectral methods as an attractive and easy-to-code alternative for the integration of fractional-in-space reaction-diffusion equations described by the fractional Laplacian in bounded rectangular domains ofRn. The main advantages of the proposed schemes is that they yield a fully diagonal representation of the fractional operator, with increased accuracy and efficiency when compared to low-order counterparts, and a completely straightforward extension to two and three spatial dimensions. Our approach is illustrated by solving several problems of practical interest, including the fractional Allen–Cahn, FitzHugh–Nagumo and Gray–Scott models, together with an analysis of the properties of these systems in terms of the fractional power of the underlying Laplacian operator.
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Whole genome sequences are generally accepted as excellent tools for studying evolutionary relationships. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignments could not be directly applied to the whole-genome comparison and phylogenomic studies. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. The “distances” used in these alignment-free methods are not proper distance metrics in the strict mathematical sense. In this study, we first review them in a more general frame — dissimilarity. Then we propose some new dissimilarities for phylogenetic analysis. Last three genome datasets are employed to evaluate these dissimilarities from a biological point of view.
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In this paper the issue of finding uncertainty intervals for queries in a Bayesian Network is reconsidered. The investigation focuses on Bayesian Nets with discrete nodes and finite populations. An earlier asymptotic approach is compared with a simulation-based approach, together with further alternatives, one based on a single sample of the Bayesian Net of a particular finite population size, and another which uses expected population sizes together with exact probabilities. We conclude that a query of a Bayesian Net should be expressed as a probability embedded in an uncertainty interval. Based on an investigation of two Bayesian Net structures, the preferred method is the simulation method. However, both the single sample method and the expected sample size methods may be useful and are simpler to compute. Any method at all is more useful than none, when assessing a Bayesian Net under development, or when drawing conclusions from an ‘expert’ system.
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Background Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. Methods We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Results Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Conclusions Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.
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The effects of tillage practises and the methods of chemical application on atrazine and alachlor losses through run-off were evaluated for five treatments: conservation (untilled) and surface (US), disk and surface, plow and surface, disk and preplant-incorporated, and plow and preplant-incorporated treatments. A rainfall simulator was used to create 63.5 mm h-1 of rainfall for 60 min and 127 mm h-1 for 15 min. Rainfall simulation occurred 24-36 h after chemical application. There was no significant difference in the run-off volume among the treatments but the untilled treatment significantly reduced erosion loss. The untilled treatments had the highest herbicide concentration and the disk treatments were higher than the plow treatments. The surface treatments showed a higher concentration than the incorporated treatments. The concentration of herbicides in the water decreased with time. Among the experimental sites, the one with sandy loam soil produced the greatest losses, both in terms of the run-off volume and herbicide loss. The US treatments had the highest loss and the herbicide incorporation treatments had smaller losses through run-off as the residue cover was effective in preventing herbicide losses. Incorporation might be a favorable method of herbicide application to reduce the herbicide losses by run-off.
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In this chapter we discuss how utilising the participatory visual methodology, photovoice, in an aged care context with its unique communal setting raised several ‘fuzzy boundary’ ethical dilemmas. To illustrate these challenges, we draw on immersive field notes from an ongoing qualitative longitudinal research (QLR) exploring the lived experience of aged care from the perspective of older residents, and focus on interactions with one participant, 81 year old Cassie. We explore how the camera, which is integral to the photovoice method, altered the researcher/participant ethical dynamics by becoming a continual ‘connector’ to the researcher. The camera took on a distinct agency, acting as a non-threatening ‘portal’ that lengthened contact, provided informal opportunities to alter the relationship dynamics and enabled unplanned participant revelation.
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Background: The use of large-volume electrolyte balanced solutions as preparation for colonoscopy often results in poor patient compliance and acceptance. The tolerance, safety, and efficacy of high-versus low volume colon-cleansing methods as preparation for colonoscopy in children were compared by randomized operator-blinded trial. Methods: Twenty-nine children ages 3.6-14.6 years had either high-volume nasogastric balanced polyethylene glycol electrolyte lavage (20 ml/kg/h) until the effluent was clear (n = 15), or two oral doses of sodium phosphate solution (22.5-45 ml) separated by oral fluid intake (n = 14). Results: Both preparations were equally effective. The low-volume preparation was better tolerated and caused less discomfort that the high-volume preparation, judging by serial nurse observations. The incidence of abdominal symptoms, diarrhea, sleep disturbance, and vomiting was not significantly different between the two groups. Both groups had a small reduction in mean hematocrit and serum calcium levels. The sodium phosphate preparation caused increases in mean serum sodium concentrations from 140 to 145 mmol/L and serum phosphate concentrations from 1.41 to 2.53 mmol/L. Ten hours after the commencement of the preanesthetic fast, these concentrations had returned to normal. Conclusions: There are advantages in terms of tolerance, discomfort, and case of administration with acceptable colonic cleansing with the use of the less-invasive oral sodium phosphate low-volume colon-cleansing preparation in children. Safe use requires ensuring an adequate oral fluid intake during the preparation time and avoidance of use in patients with renal insufficiency.
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Cancer is the leading contributor to the disease burden in Australia. This thesis develops and applies Bayesian hierarchical models to facilitate an investigation of the spatial and temporal associations for cancer diagnosis and survival among Queenslanders. The key objectives are to document and quantify the importance of spatial inequalities, explore factors influencing these inequalities, and investigate how spatial inequalities change over time. Existing Bayesian hierarchical models are refined, new models and methods developed, and tangible benefits obtained for cancer patients in Queensland. The versatility of using Bayesian models in cancer control are clearly demonstrated through these detailed and comprehensive analyses.
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There is a scarcity of research that informs Interface Health Service (IHS) development. This research applied a mixed methods approach to profile older emergency department patients and patterns of health service use and to explore their ED experiences in public hospital EDs in South-East Queensland. IHS was under-utilised by older people with complex co-morbidities. Lack of communication and need identification were factors that undermined the effectiveness of IHS in reaching this cohort which highlighted a need for change.
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Background: Haemodialysis nurses form long term relationships with patients in a technologically complex work environment. Previous studies have highlighted that haemodialysis nurses face stressors related to the nature of their work and also their work environments leading to reported high levels of burnout. Using Kanters (1997) Structural Empowerment Theory as a guiding framework, the aim of this study was to explore the factors contributing to satisfaction with the work environment, job satisfaction, job stress and burnout in haemodialysis nurses. Methods: Using a sequential mixed-methods design, the first phase involved an on-line survey comprising demographic and work characteristics, Brisbane Practice Environment Measure (B-PEM), Index of Work Satisfaction(IWS), Nursing Stress Scale (NSS) and the Maslach Burnout Inventory (MBI). The second phase involved conducting eight semi-structured interviews with data thematically analyzed. Results: From the 417 nurses surveyed the majority were female (90.9 %), aged over 41 years of age (74.3 %), and 47.4 % had worked in haemodialysis for more than 10 years. Overall the work environment was perceived positively and there was a moderate level of job satisfaction. However levels of stress and emotional exhaustion (burnout) were high. Two themes, ability to care and feeling successful as a nurse, provided clarity to the level of job satisfaction found in phase 1. While two further themes, patients as quasi-family and intense working teams, explained why working as a haemodialysis nurse was both satisfying and stressful. Conclusions: Nurse managers can use these results to identify issues being experienced by haemodialysis nurses working in the unit they are supervising.
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Interaction of tetrathiafulvalene (TTF) and tetracyanoethylene (TCNE) with few-layer graphene samples prepared by the exfoliation of graphite oxide (EG), conversion of nanodiamond (DG) and arc-evaporation of graphite in hydrogen (HG) has been investigated by Raman spectroscopy to understand the role of the graphene surface. The position and full-width at half maximum of the Raman G-band are affected on interaction with TTF and TCNE and the effect is highest with EG and least with HG. The effect of TTF and TCNE on the 2D-band is also maximum with EG. The magnitude of interaction between the donor/acceptor molecules varies in the same order as the surface areas of the graphenes. (C) 2009 Published by Elsevier B. V.
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In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.