981 resultados para observational methods


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The aim of this paper is to provide a contemporary summary of statistical and non-statistical meta-analytic procedures that have relevance to the type of experimental designs often used by sport scientists when examining differences/change in dependent measure(s) as a result of one or more independent manipulation(s). Using worked examples from studies on observational learning in the motor behaviour literature, we adopt a random effects model and give a detailed explanation of the statistical procedures for the three types of raw score difference-based analyses applicable to between-participant, within-participant, and mixed-participant designs. Major merits and concerns associated with these quantitative procedures are identified and agreed methods are reported for minimizing biased outcomes, such as those for dealing with multiple dependent measures from single studies, design variation across studies, different metrics (i.e. raw scores and difference scores), and variations in sample size. To complement the worked examples, we summarize the general considerations required when conducting and reporting a meta-analysis, including how to deal with publication bias, what information to present regarding the primary studies, and approaches for dealing with outliers. By bringing together these statistical and non-statistical meta-analytic procedures, we provide the tools required to clarify understanding of key concepts and principles.

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Dispersion characteristics of respiratory droplets in indoor environments are of special interest in controlling transmission of airborne diseases. This study adopts an Eulerian method to investigate the spatial concentration distribution and temporal evolution of exhaled and sneezed/coughed droplets within the range of 1.0~10.0μm in an office room with three air distribution methods, i.e. mixing ventilation (MV), displacement ventilation (DV), and under-floor air distribution (UFAD). The diffusion, gravitational settling, and deposition mechanism of particulate matters are well accounted in the one-way coupling Eulerian approach. The simulation results find that exhaled droplets with diameters up to 10.0μm from normal respiration process are uniformly distributed in MV, while they are trapped in the breathing height by thermal stratifications in DV and UFAD, resulting in a high droplet concentration and a high exposure risk to other occupants. Sneezed/coughed droplets are diluted much slower in DV/UFAD than in MV. Low air speed in the breathing zone in DV/UFAD can lead to prolonged residence of droplets in the breathing zone.

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Objectives: To report on the design, significance and potential impacts of the first documented human clinical trial assessing the anxiolytic and thymoleptic efficacy of an aqueous monoextract of Piper methysticum (kava). The significance of the qualitative element of our clinical trial is also explored. The Kava Anxiety Depression Spectrum Study (KADSS) is a 3-week placebocontrolled, double-blind, cross-over trial involving 60 adult participants (18—65) with elevated stable anxiety and varying levels of depressive symptoms. Aims: The aims of KADSS are: (1) to determine whether an aqueous standardised extract of kava is effective for the treatment of anxiety; (2) to assess the effects of kava on differing levels of depression; and (3) to explore participants’ experience of taking kava via qualitative research. The study also provides preliminary assessment of the safety of an aqueous extract of kava in humans. Conclusion: If results reveal that the aqueous kava preparation exerts significant anxiolytic effects and appears safe, potentially beneficial impacts may occur. Data supporting a safe and effective kava extract may encourage a re-introduction of kava to Europe, UK and Canada. This may provide a major socioeconomic benefit to Pacific Island nations, and to sufferers of anxiety disorders.

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Despite the advances that have been made in relation to the valuation of commercial, industrial and retail property, there has not been the same progress in relation to the valuation of rural property. Although the majority of rural property valuations also require the valuer to carry out a full analysis of the economic performance of the farming operations, this information is rarely used to assess the value of the property, nor is it even used for a secondary valuation method. Over the past 20 years the nature of rural valuation practice has required rural valuers to undertake studies in both agriculture (farm management) and valuation, especially if carrying out valuation work for financial institutions. The additional farm financial information obtained by rural valuers exceeds that level of information required to value commercial, retail and industrial by the capitalisation of net rent/profit valuation method and is very similar to the level of information required for the valuation of commercial and retail property by the Discounted Cash Flow valuation method. On this basis the valuers specialising in rural valuation practice should have the necessary skills and information to value rural properties by an income valuation method. Although the direct comparison method of valuation has been sufficient in the past to value rural properties the future use of the method as the main valuation method is limited and valuers need to adopt an income valuation method as at least a secondary valuation method to overcome the problems associated with the use of direct comparison as the only rural property valuation method. This paper will review the results of an extensive survey carried out by rural property valuers in New South Wales (NSW), Australia, in relation to the impact of farm management on rural property values and rural property income potential.

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This paper examines the enabling effect of using blended learning and synchronous internet mediated communication technologies to improve learning and develop a Sense of Community (SOC) in a group of post-graduate students consisting of a mix of on-campus and off-campus students. Both quantitative and qualitative data collected over a number of years supports the assertion that the blended learning environment enhanced both teaching and learning. The development of a SOC was pivotal to the success of the blended approach when working with geographically isolated groups within a single learning environment.

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Several protocols for isolation of mycobacteria from water exist, but there is no established standard method. This study compared methods of processing potable water samples for the isolation of Mycobacterium avium and Mycobacterium intracellulare using spiked sterilized water and tap water decontaminated using 0.005% cetylpyridinium chloride (CPC). Samples were concentrated by centrifugation or filtration and inoculated onto Middlebrook 7H10 and 7H11 plates and Lowenstein-Jensen slants and into mycobacterial growth indicator tubes with or without polymyxin, azlocillin, nalidixic acid, trimethoprim, and amphotericin B. The solid media were incubated at 32°C, at 35°C, and at 35°C with CO2 and read weekly. The results suggest that filtration of water for the isolation of mycobacteria is a more sensitive method for concentration than centrifugation. The addition of sodium thiosulfate may not be necessary and may reduce the yield. Middlebrook M7H10 and 7H11 were equally sensitive culture media. CPC decontamination, while effective for reducing growth of contaminants, also significantly reduces mycobacterial numbers. There was no difference at 3 weeks between the different incubation temperatures.

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The continued growth in popularity of motorcycling is an area of concern within the road safety domain due to the vulnerability of motorcyclists sustaining injury in the event of a crash. Currently in Australia only motorcycle helmets are mandatory for motorcyclists or pillions to wear and there is no legislative standard for other protective apparel. This paper reports the results obtained from a series of motorcyclists’ apparel observational studies undertaken in the Brisbane and Canberra regions. The sites selected for the research were designed to enable the observation of both recreational and commuter riders. The results highlight both similarities and differences in the type of protective apparel worn by motorcyclists and pillions observed across the two regions. Encouragingly, across all the sites the majority of riders were wearing protective apparel on their upper body. However, a lower proportion of riders were observed wearing protective apparel on their lower body, particularly at the commuter sites in Brisbane. Similarly, the wearing of full face helmets was very high, except at the commuter sites in Brisbane. The generally lower use of protective apparel among commuter riders in Brisbane would appear to reflect both situational factors, such as climate, and the higher proportion of scooters observed at the sites. The implications of these results are discussed and recommendations are made for future research to identify factors that influence the wearing of protective motorcycle apparel.

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This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

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Crucial to enhancing the status and quality of games teaching in schools is a developed understanding of the teaching strategies adopted by practitioners. In this paper, we will demonstrate that contemporary games‟ teaching is a product of individual, task and environmental constraints (Newell, 1986). More specifically, we will show that current pedagogy in the U.K., Australia and the United States is strongly influenced by historical, socio-cultural environmental and political constraints. In summary, we will aim to answer the question „why do teachers teach games the way they do.‟ In answering this question, we conclude that teacher educators, who are trying to influence pedagogical practice, must understand these potential constraints and provide appropriate pre-service experiences to give future physical education teachers the knowledge, confidence and ability to adopt a range of teaching styles when they become fully fledged teachers. Essential to this process is the need to enable future practitioners to base their pedagogical practice on a sound understanding of contemporary learning theories of skill acquisition.

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Matrix function approximation is a current focus of worldwide interest and finds application in a variety of areas of applied mathematics and statistics. In this thesis we focus on the approximation of A^(-α/2)b, where A ∈ ℝ^(n×n) is a large, sparse symmetric positive definite matrix and b ∈ ℝ^n is a vector. In particular, we will focus on matrix function techniques for sampling from Gaussian Markov random fields in applied statistics and the solution of fractional-in-space partial differential equations. Gaussian Markov random fields (GMRFs) are multivariate normal random variables characterised by a sparse precision (inverse covariance) matrix. GMRFs are popular models in computational spatial statistics as the sparse structure can be exploited, typically through the use of the sparse Cholesky decomposition, to construct fast sampling methods. It is well known, however, that for sufficiently large problems, iterative methods for solving linear systems outperform direct methods. Fractional-in-space partial differential equations arise in models of processes undergoing anomalous diffusion. Unfortunately, as the fractional Laplacian is a non-local operator, numerical methods based on the direct discretisation of these equations typically requires the solution of dense linear systems, which is impractical for fine discretisations. In this thesis, novel applications of Krylov subspace approximations to matrix functions for both of these problems are investigated. Matrix functions arise when sampling from a GMRF by noting that the Cholesky decomposition A = LL^T is, essentially, a `square root' of the precision matrix A. Therefore, we can replace the usual sampling method, which forms x = L^(-T)z, with x = A^(-1/2)z, where z is a vector of independent and identically distributed standard normal random variables. Similarly, the matrix transfer technique can be used to build solutions to the fractional Poisson equation of the form ϕn = A^(-α/2)b, where A is the finite difference approximation to the Laplacian. Hence both applications require the approximation of f(A)b, where f(t) = t^(-α/2) and A is sparse. In this thesis we will compare the Lanczos approximation, the shift-and-invert Lanczos approximation, the extended Krylov subspace method, rational approximations and the restarted Lanczos approximation for approximating matrix functions of this form. A number of new and novel results are presented in this thesis. Firstly, we prove the convergence of the matrix transfer technique for the solution of the fractional Poisson equation and we give conditions by which the finite difference discretisation can be replaced by other methods for discretising the Laplacian. We then investigate a number of methods for approximating matrix functions of the form A^(-α/2)b and investigate stopping criteria for these methods. In particular, we derive a new method for restarting the Lanczos approximation to f(A)b. We then apply these techniques to the problem of sampling from a GMRF and construct a full suite of methods for sampling conditioned on linear constraints and approximating the likelihood. Finally, we consider the problem of sampling from a generalised Matern random field, which combines our techniques for solving fractional-in-space partial differential equations with our method for sampling from GMRFs.

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In this paper, we consider a variable-order fractional advection-diffusion equation with a nonlinear source term on a finite domain. Explicit and implicit Euler approximations for the equation are proposed. Stability and convergence of the methods are discussed. Moreover, we also present a fractional method of lines, a matrix transfer technique, and an extrapolation method for the equation. Some numerical examples are given, and the results demonstrate the effectiveness of theoretical analysis.

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In this paper, a two-dimensional non-continuous seepage flow with fractional derivatives (2D-NCSF-FD) in uniform media is considered, which has modified the well known Darcy law. Using the relationship between Riemann-Liouville and Grunwald-Letnikov fractional derivatives, two modified alternating direction methods: a modified alternating direction implicit Euler method and a modified Peaceman-Rachford method, are proposed for solving the 2D-NCSF-FD in uniform media. The stability and consistency, thus convergence of the two methods in a bounded domain are discussed. Finally, numerical results are given.

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One of the new challenges in aeronautics is combining and accounting for multiple disciplines while considering uncertainties or variability in the design parameters or operating conditions. This paper describes a methodology for robust multidisciplinary design optimisation when there is uncertainty in the operating conditions. The methodology, which is based on canonical evolution algorithms, is enhanced by its coupling with an uncertainty analysis technique. The paper illustrates the use of this methodology on two practical test cases related to Unmanned Aerial Systems (UAS). These are the ideal candidates due to the multi-physics involved and the variability of missions to be performed. Results obtained from the optimisation show that the method is effective to find useful Pareto non-dominated solutions and demonstrate the use of robust design techniques.

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In this paper, we consider the numerical solution of a fractional partial differential equation with Riesz space fractional derivatives (FPDE-RSFD) on a finite domain. Two types of FPDE-RSFD are considered: the Riesz fractional diffusion equation (RFDE) and the Riesz fractional advection–dispersion equation (RFADE). The RFDE is obtained from the standard diffusion equation by replacing the second-order space derivative with the Riesz fractional derivative of order αset membership, variant(1,2]. The RFADE is obtained from the standard advection–dispersion equation by replacing the first-order and second-order space derivatives with the Riesz fractional derivatives of order βset membership, variant(0,1) and of order αset membership, variant(1,2], respectively. Firstly, analytic solutions of both the RFDE and RFADE are derived. Secondly, three numerical methods are provided to deal with the Riesz space fractional derivatives, namely, the L1/L2-approximation method, the standard/shifted Grünwald method, and the matrix transform method (MTM). Thirdly, the RFDE and RFADE are transformed into a system of ordinary differential equations, which is then solved by the method of lines. Finally, numerical results are given, which demonstrate the effectiveness and convergence of the three numerical methods.

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Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods—latent class analysis, grade of membership and grade of membership “fuzzy” clustering (Fanny)—to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.