945 resultados para marginal adaption


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Objective: the aim of this investigation was to evaluate the cervical adaptation of metal crowns under several conditions, namely (1) variations in the cervical finish line of the preparation, (2) application of internal relief inside the crowns, and (3) cementation using different luting materials. Method and Materials: One hundred eighty stainless-steel master dies were prepared simulating full crown preparations: 60 in chamfer (CH), 60 in 135-degree shoulder (OB), and 60 in rounded shoulder (OR). The finish lines were machined at approximate dimensions of a molar tooth preparation (height: 5.5 mm; cervical diameter: 8 mm; occlusal diameter: 6.4 mm; taper degree: 6; and cervical finish line width: 0.8 mm). One hundred eighty corresponding copings with the same finish lines were fabricated. A 30-mu m internal relief was machined 0.5 mm above the cervical finish line in 90 of these copings. The fit of the die and the coping was measured from all specimens (L0) prior to cementation using an optical microscope. After manipulation of the 3 types of cements (zinc phosphate, glass-ionomer, and resin cement), the coping was luted on the corresponding standard master die under 5-kgf loading for 4 minutes. Vertical discrepancy was again measured (L1), and the difference between L1 and L0 indicated the cervical adaptation. Results: Significant influence of the finish line, cement type, and internal relief was observed on the cervical adaptation (P < .001). The CH type of cervical finish line resulted in the best cervical adaptation of the metal crowns regardless of the cement type either with or without internal relief (36.6 +/- 3 to 100.8 +/- 4 mu m) (3-way analysis of variance and Tukey's test, alpha = .05). The use of glass-ionomer cement resulted in the least cervical discrepancy (36.6 +/- 3 to 115 +/- 4 mu m) than those of other cements (45.2 +/- 4 to 130.3 +/- 2 mu m) in all conditions. Conclusion: the best cervical adaptation was achieved with the chamfer type of finish line. The internal relief improved the marginal adaptation significantly, and the glass-ionomer cement led to the best cervical adaptation, followed by zinc phosphate and resin cement.

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The notion of routines as mechanisms for achieving stability and change in organisations is well established in the organisational theory literature (Becker, 2004). However the relationship between the dynamics of selection, adaptation and retention and the increase or decrease in the varieties of routines which are the result of these processes, is not as well established theoretically or empirically. This paper investigates the processes associated with the evolution of an inter-organisational routine over time. The paper contributes to theory by advancing a conceptual clarification between the dynamics of organisational routines which produce variation, and the varieties of routines which are generated as a result of such processes; and an explanation for the relationship between selection, adaptation and retention dynamics and the creation of variety. The research is supported by analysis of empirical data pertaining to the procurement of engineering assets in a large asset intensive organisation.

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While the role of executives’ cognition in organisations’ responses to change is a central topic in strategic cognition research, changes in firms’ environment are typically not measured directly but described either as an event (for example, new industry legislation) or represented by a time period (e.g. when a new technology impacted an industry). The Australian mining sector has witnessed a historically significant change in demand for its products and we begin by developing measures of changes in supply and demand for key commodities during the period 1992-2008. We identify sub-groups of firms based on their activities and commodity sector and examine the relation of these variables to executives’ cognition and to firms’ CapEx. We find industry, firm and cognitive variables are related to both strategic cognition and firms’ CapEx.

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Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

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The present paper presents and discusses the use of dierent codes regarding the numerical simulation of a radial-in ow turbine. A radial-in ow turbine test case was selected from published literature [1] and commercial codes (Fluent and CFX) were used to perform the steady-state numerical simulations. An in-house compressible- ow simulation code, Eilmer3 [2] was also adapted in order to make it suitable to perform turbomachinery simulations and preliminary results are presented and discussed. The code itself as well as its adaptation, comprising the addition of terms for the rotating frame of reference, programmable boundary conditions for periodic boundaries and a mixing plane interface between the rotating and non-rotating blocks are also discussed. Several cases with dierent orders of complexity in terms of geometry were considered and the results were compared across the dierent codes. The agreement between these results and published data is also discussed.

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Reasons for performing study: Many domestic horses and ponies are sedentary and obese due to confinement to small paddocks and stables and a diet of infrequent, high-energy rations. Severe health consequences can be associated with this altered lifestyle. Objectives: The aims of this study were to investigate the ability of horses to learn to use a dynamic feeder system and determine the movement and behavioural responses of horses to the novel system. Methods: A dynamic feed station was developed to encourage horses to exercise in order to access ad libitum hay. Five pairs of horses (n = 10) were studied using a randomised crossover design with each pair studied in a control paddock containing a standard hay feeder and an experimental paddock containing the novel hay feeder. Horse movement was monitored by a global positioning system (GPS) and horses observed and their ability to learn to use the system and the behavioural responses to its use assessed. Results: With initial human intervention all horses used the novel feeder within 1 h. Some aggressive behaviour was observed between horses not well matched in dominance behaviour. The median distance walked by the horses was less (P = 0.002) during a 4 h period (117 [57–185] m) in the control paddock than in the experimental paddock (630 [509–719] m). Conclusions: The use of an automated feeding system promotes increased activity levels in horses housed in small paddocks, compared with a stationary feeder.

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Vulnerable and marginalised populations are not only over-represented in the criminal justice system, but also in civil jurisdictions like the coronial system. Moreover, many of the personnel who deal with criminal matters, especially in rural and regional areas, are also those who manage the coronial death investigation. This movement back and forth between civil and criminal jurisdictions is difficult for the both professional personnel and the families, but especially for those families who may also have had dealings with these personnel in the criminal justice system, or who present as suspicious due to larger historical and global issues. While coronial legislation now allows families to raise cultural and religious concerns about the process, particularly to do with the autopsy of their loved one, this also requires them to identify themselves to police at the initial stage of the death investigation. This paper, part of a larger body of work on autopsy decision making, discusses the ways in which this information is gathered by police, how it is communicated through the system, the ways in which families are supported through the process, and the difficulties that ensue.

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The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables. Here an unbiased estimator of the likelihood replaces the true likelihood in order to produce a Bayesian algorithm that remains on the marginal space of the model parameter (with latent variables integrated out), with a target distribution that is still the correct posterior distribution. Very efficient proposal distributions can be developed on the marginal space relative to the joint space of model parameter and latent variables. Thus psuedo-marginal algorithms tend to have substantially better mixing properties. However, for pseudo-marginal approaches to perform well, the likelihood has to be estimated rather precisely. This can be difficult to achieve in complex applications. In this paper we propose to take advantage of multiple central processing units (CPUs), that are readily available on most standard desktop computers. Here the likelihood is estimated independently on the multiple CPUs, with the ultimate estimate of the likelihood being the average of the estimates obtained from the multiple CPUs. The estimate remains unbiased, but the variability is reduced. We compare and contrast two different technologies that allow the implementation of this idea, both of which require a negligible amount of extra programming effort. The superior performance of this idea over the standard approach is demonstrated on simulated data from a stochastic volatility model.

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This paper focuses on a case study of local postcard production in a rural community in Western Australia. Drawing on in-depth interviews with key producers of these postcards, the analysis presented explores perceptions of and contexts for the emergence of this production, in turn examining the notion of ‘creativity’ articulated and privileged by this cultural work. Connections are identified between the making of postcards, the broader historical field of local cultural work and the construction of community. This, in turn, forms the basis for consideration of the role and relativity of ‘marginality’.

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This article considers the rules relating to the use of marginal notes and headings in interpreting Queensland legislation, both in its original form and in reprinted legislation. It also examines the application of the principles of construction as to the use of section headings in the interpretation of provisions of the Criminal Code 1899 (Qld). Finally, it suggests that amendments should be made to the Acts Interpretation Act 1954 (Qld) in order to clarify the position as to the status of marginal notes and headings in statutory interpretation.

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We investigate the utility to computational Bayesian analyses of a particular family of recursive marginal likelihood estimators characterized by the (equivalent) algorithms known as "biased sampling" or "reverse logistic regression" in the statistics literature and "the density of states" in physics. Through a pair of numerical examples (including mixture modeling of the well-known galaxy dataset) we highlight the remarkable diversity of sampling schemes amenable to such recursive normalization, as well as the notable efficiency of the resulting pseudo-mixture distributions for gauging prior-sensitivity in the Bayesian model selection context. Our key theoretical contributions are to introduce a novel heuristic ("thermodynamic integration via importance sampling") for qualifying the role of the bridging sequence in this procedure, and to reveal various connections between these recursive estimators and the nested sampling technique.

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Several analytical methods for Dynamic System Optimum (DSO) assignment have been proposed but they are basically classified into two kinds. This chapter attempts to establish DSO by equilbrating the path dynamic marginal time (DMT). The authors analyze the path DMT for a single path with tandem bottlenecks and showed that the path DMT is not the simple summation of DMT associated with each bottleneck along the path. Next, the authors examined the DMT of several paths passing through a common bottleneck. It is shown that the externality at the bottleneck is shared by the paths in proportion to their demand from the current time until the queue vanishes. This share of the externality is caused by the departure rate shift under first in first out (FIFO) and the externality propagates to the downstream bottlenecks. However, the externalities propagates to the downstream are calculated out if downstream bottlenecks exist. Therefore, the authors concluded that the path DMT can be evaluated without considering the propagation of the externalities, but just as in the evaluation of the path DMT for a single path passing through a series of bottlenecks between the origin and destination. Based on the DMT analysis, the authors finally proposed a heuristic solution algorithm and verified it by comparing the numerical solution with the analytical one.

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A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.