974 resultados para free eletromagnetic field


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Due to their small collecting volume diodes are commonly used in small field dosimetry. However the relative sensitivity of a diode increases with decreasing small field size. Conversely, small air gaps have been shown to cause a significant decrease in the sensitivity of a detector as the field size is decreased. Therefore this study uses Monte Carlo simulations to look at introducing air upstream to diodes such that they measure with a constant sensitivity across all field sizes in small field dosimetry. Varying thicknesses of air were introduced onto the upstream end of two commercial diodes (PTW 60016 photon diode and PTW 60017 electron diode), as well as a theoretical unenclosed silicon chip using field sizes as small as 5 mm × 5 mm . The metric D_(w,Q)/D_(Det,Q) used in this study represents the ratio of the dose to a point of water to the dose to the diode active volume, for a particular field size and location. The optimal thickness of air required to provide a constant sensitivity across all small field sizes was found by plotting D_(w,Q)/D_(Det,Q) as a function of introduced air gap size for various field sizes, and finding the intersection point of these plots. That is, the point at which D_(w,Q)/D_(Det,Q) was constant for all field sizes was found. The optimal thickness of air was calculated to be 3.3 mm, 1.15 mm and 0.10 mm for the photon diode, electron diode and unenclosed silicon chip respectively. The variation in these results was due to the different design of each detector. When calculated with the new diode design incorporating the upstream air gap, k_(Q_clin 〖,Q〗_msr)^(f_clin 〖,f〗_msr ) was equal to unity to within statistical uncertainty (0.5 %) for all three diodes. Cross-axis profile measurements were also improved with the new detector design. The upstream air gap could be implanted on the commercial diodes via a cap consisting of the air cavity surrounded by water equivalent material. The results for the unclosed silicon chip show that an ideal small field dosimetry diode could be created by using a silicon chip with a small amount of air above it.

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In this paper we analyse the effects of highway traffic flow parameters like vehicle arrival rate and density on the performance of Amplify and Forward (AF) cooperative vehicular networks along a multi-lane highway under free flow state. We derive analytical expressions for connectivity performance and verify them with Monte-Carlo simulations. When AF cooperative relaying is employed together with Maximum Ratio Combining (MRC) at the receivers the average route error rate shows 10-20 fold improvement compared to direct communication. A 4-8 fold increase in maximum number of traversable hops can also be observed at different vehicle densities when AF cooperative communication is used to strengthen communication routes. However the theorical upper bound of maximum number of hops promises higher performance gains.

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Qualitative researchers in the discipline of criminology perform a wide range of challenging tasks. They interview prisoners, police officers, magistrates and judges. They speak with survivors of domestic violence, and drink tea with the mothers of murdered children. They observe courts and communities, investigate the decision-making processes of juries and immerse themselves in the data they collect. They ask ‘big’ questions – ‘how do we criminalise the producers of toxic toys?’ – as well as ‘little’ questions – ‘what should I wear to conduct this interview?’ Qualitative Criminology: Stories from the Field brings to life the stories behind the research of both emerging and established scholars in Australian criminology. The book’s contributors provided honest, reflective, and decidedly unsanitised accounts of their qualitative research journeys - the lively tales of what really happens when conducting research of this nature, the stories that often make for parenthetical asides in conference papers but tend to be excised from journal articles. This book considers the gap between research methods and the realities of qualitative research. As such, it aims to help researchers and students who conduct qualitative criminological research reflect upon their role as researchers, and the practical, ideological and ethical issues which may arise in the course of their research. It is also a call to criminologists to make public the ‘failures’ and missteps of their research endeavours so that we can learn from one another and become better informed and more reflexive qualitative criminologists.

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Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.

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The empirically established decline in law student well being during the first year of law school is a red-flagged imprimatur for first year curriculum change. This article suggests that by engaging law students with the concept of a positive professional identity, student engagement and intrinsic motivation will increase because they are working towards a career goal that has meaning and purpose. Law school is a time of professional transformation and the legal academy can take steps to ensure that this transformation is inculcated with positive messages. Literature from the fields of law and psychology is analysed in this article, to explain how a positive conception of the legal profession (and a student’s future role within it) can increase a student’s psychological well-being – at law school and beyond.

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Internationally, vocational education and training (VET) is challenged by increasing skills shortages in certain industries and rapidly changing skill requirements. Rigid and centralised state bureaucracies have proven inadequate to adapt to these challenges. Increasingly, partnerships between schools and industry have been established as a potential strategy to address local labour market demand and to provide school to work transition programs. Drawing on experiences in Australia, this paper reports on a case study of government-let partnerships between schools and industry. The Queensland Gateway schools initiative currently involves over 120 schools. The study aimed to understand how partnerships were constructed in this initiative. Selected partnerships were analysed in terms of the following principles of public-private partnerships – efficiency, effectiveness, sustainability, and beneficiaries. Although there are some benefits of partnership activities reported by both school and industry stakeholders, little evidence was found that the above underlying principles had been addressed to a significant extent in the Gateway school initiative. Further, these partnerships are often tenuously facilitated by individuals who have limited infrastructure or strategic support. Implications are that project stakeholders have not sufficiently accommodated theoretical perspectives on implementation and management of partnerships. Similar initiatives may be improved if stakeholders are cognisant of the underlying principles supporting successful public-private partnerships.

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Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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The Hepatitis C virus (HCV) affects some 150 million people worldwide. However, unlike hepatitis A and B there is no vaccination for HCV and approximately 75% of people exposed to HCV develop chronic hepatitis. In Australia, around 226,700 people live with chronic HCV infection costing the government approximately $252 million per year. Historically, the standard approved/licenced treatment for HCV is pegylated interferon with ribavirin. There are major drawbacks with interferon-based therapy including side effects, long duration of therapy, limited access and affordability. Our previous survey of an at-risk population reported HCV treatment coverage of only 5%. Since April 2013, a new class of interferon-free treatments for chronic HCV is subsidised under the Pharmaceutical Benefits Scheme: boceprevir and telaprevir - estimated to cost the Australian Government in excess of $220 million over five years. Other biologic interferon-free therapeutic agents are scheduled to enter the Australian market. Use of small molecule generic pharmaceuticals has been advocated as a means of public cost savings. However, with the new biologic agents, generics (biosimilars) may not be feasible or straightforward, due to long patent life; marketing exclusivity; and regulatory complexity for these newer products.

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Packaged software is pre-built with the intention of licensing it to users in domestic settings and work organisations. This thesis focuses upon the work organisation where packaged software has been characterised as one of the latest ‘solutions’ to the problems of information systems. The study investigates the packaged software selection process that has, to date, been largely viewed as objective and rational. In contrast, this interpretive study is based on a 21⁄2 year long field study of organisational experiences with packaged software selection at T.Co, a consultancy organisation based in the United Kingdom. Emerging from the iterative process of case study and action research is an alternative theory of packaged software selection. The research argues that packaged software selection is far from the rationalistic and linear process that previous studies suggest. Instead, the study finds that aspects of the traditional process of selection incorporating the activities of gathering requirements, evaluation and selection based on ‘best fit’ may or may not take place. Furthermore, even where these aspects occur they may not have equal weight or impact upon implementation and usage as may be expected. This is due to the influence of those multiple realities which originate from the organisational and market environments within which packages are created, selected and used, the lack of homogeneity in organisational contexts and the variously interpreted characteristics of the package in question.

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Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

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This paper illustrates the use of finite element (FE) technique to investigate the behaviour of laminated glass (LG) panels under blast loads. Two and three dimensional (2D and 3D) modelling approaches available in LS-DYNA FE code to model LG panels are presented. Results from the FE analysis for mid-span deflection and principal stresses compared well with those from large deflection plate theory. The FE models are further validated using the results from a free field blast test on a LG panel. It is evident that both 2D and 3D LG models predict the experimental results with reasonable accuracy. The 3D LG models give slightly more accurate results but require considerably more computational time compared to the 2D LG models.

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This paper presents a rigorous and a reliable analytical procedure using finite element (FE) techniques to study the blast response of laminated glass (LG) panel and predict the failure of its components. The 1st principal stress (σ11) is used as the failure criterion for glass and the von mises stress (σv) is used for the interlayer and sealant joints. The results from the FE analysis for mid-span deflection, energy absorption and the stresses at critical locations of glass, interlayer and structural sealant are presented in the paper. These results compared well with those obtained from a free field blast test reported in the literature. The tensile strength (T) of the glass has a significant influence on the behaviour of the LG panel and should be treated carefully in the analysis. The glass panes absorb about 80% of the blast energy for the treated blast load and this should be minimised in the design.

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Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.