980 resultados para Cambridge University


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The free surface flow of a finite depth fluid past a semi-infinite body is considered. The fluid is assumed to have constant vorticity throughout and the free surface is assumed to attach smoothly to the front face of the body. Numerical solutions are found using a boundary integral method in the physical plane and it is shown that solutions exist for all supercritical Froude numbers. The related problem of the cusp-like flow due to a submerged sink in a corner is also considered. Vorticity is included in the flow and it is shown that the behaviour of the solutions is qualitatively the same as that found in the problem described above.

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Schizophrenia may not be a single disease, but the result of a diverse set of related conditions. Modern neuroscience is beginning to reveal some of the genetic and environmental underpinnings of schizophrenia; however, an approach less well travelled is to examine the medical disorders that produce symptoms resembling schizophrenia. This book is the first major attempt to bring together the diseases that produce what has been termed 'secondary schizophrenia'. International experts from diverse backgrounds ask the questions: does this medical disorder, or drug, or condition cause psychosis? If yes, does it resemble schizophrenia? What mechanisms form the basis of this relationship? What implications does this understanding have for aetiology and treatment? The answers are a feast for clinicians and researchers of psychosis and schizophrenia. They mark the next step in trying to meet the most important challenge to modern neuroscience – understanding and conquering this most mysterious of human diseases.

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In this work two different finite volume computational strategies for solving a representative two-dimensional diffusion equation in an orthotropic medium are considered. When the diffusivity tensor is treated as linear, this problem admits an analytic solution used for analysing the accuracy of the proposed numerical methods. In the first method, the gradient approximation techniques discussed by Jayantha and Turner [Numerical Heat Transfer, Part B: Fundamentals, 40, pp.367–390, 2001] are applied directly to the

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Introduction: Emergency prehospital medical care providers are frontline health workers during emergencies. However, little is known about their attitudes, perceptions, and likely behaviors during emergency conditions. Understanding these attitudes and behaviors is crucial to mitigating the psychological and operational effects of biohazard events such as pandemic influenza, and will support the business continuity of essential prehospital services. ----- ----- Problem: This study was designed to investigate the association between knowledge and attitudes regarding avian influenza on likely behavioral responses of Australian emergency prehospital medical care providers in pandemic conditions. ----- ----- Methods: Using a reply-paid postal questionnaire, the knowledge and attitudes of a national, stratified, random sample of the Australian emergency prehospital medical care workforce in relation to pandemic influenza were investigated. In addition to knowledge and attitudes, there were five measures of anticipated behavior during pandemic conditions: (1) preparedness to wear personal protective equipment (PPE); (2) preparedness to change role; (3) willingness to work; and likely refusal to work with colleagues who were exposed to (4) known and (5) suspected influenza. Multiple logistic regression models were constructed to determine the independent predictors of each of the anticipated behaviors, while controlling for other relevant variables. ----- ----- Results: Almost half (43%) of the 725 emergency prehospital medical care personnel who responded to the survey indicated that they would be unwilling to work during pandemic conditions; one-quarter indicated that they would not be prepared to work in PPE; and one-third would refuse to work with a colleague exposed to a known case of pandemic human influenza. Willingness to work during a pandemic (OR = 1.41; 95% CI = 1.0–1.9), and willingness to change roles (OR = 1.44; 95% CI = 1.04–2.0) significantly increased with adequate knowledge about infectious agents generally. Generally, refusal to work with exposed (OR = 0.48; 95% CI = 0.3–0.7) or potentially exposed (OR = 0.43; 95% CI = 0.3–0.6) colleagues significantly decreased with adequate knowledge about infectious agents. Confidence in the employer’s capacity to respond appropriately to a pandemic significantly increased employee willingness to work (OR = 2.83; 95% CI = 1.9–4.1); willingness to change roles during a pandemic (OR = 1.52; 95% CI = 1.1–2.1); preparedness to wear PPE (OR = 1.68; 95% CI = 1.1–2.5); and significantly decreased the likelihood of refusing to work with colleagues exposed to (suspected) influenza (OR = 0.59; 95% CI = 0.4–0.9). ----- ----- Conclusions:These findings indicate that education and training alone will not adequately prepare the emergency prehospital medical workforce for a pandemic. It is crucial to address the concerns of ambulance personnel and the perceived concerns of their relationship with partners in order to maintain an effective prehospital emergency medical care service during pandemic conditions.

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Introduction: Little is known about the risk perceptions and attitudes of healthcare personnel, especially of emergency prehospital medical care personnel, regarding the possibility of an outbreak or epidemic event. Problem: This study was designed to investigate pre-event knowledge and attitudes of a national sample of the emergency prehospital medical care providers in relation to a potential human influenza pandemic, and to determine predictors of these attitudes. Methods: Surveys were distributed to a random, cross-sectional sample of 20% of the Australian emergency prehospital medical care workforce (n = 2,929), stratified by the nine services operating in Australia, as well as by gender and location. The surveys included: (1) demographic information; (2) knowledge of influenza; and (3) attitudes and perceptions related to working during influenza pandemic conditions. Multiple logistic regression models were constructed to identify predictors of pandemic-related risk perceptions. Results: Among the 725 Australian emergency prehospital medical care personnel who responded, 89% were very anxious about working during pandemic conditions, and 85% perceived a high personal risk associated with working in such conditions. In general, respondents demonstrated poor knowledge in relation to avian influenza, influenza generally, and infection transmission methods. Less than 5% of respondents perceived that they had adequate education/training about avian influenza. Logistic regression analyses indicate that, in managing the attitudes and risk perceptions of emergency prehospital medical care staff, particular attention should be directed toward the paid, male workforce (as opposed to volunteers), and on personnel whose relationship partners do not work in the health industry. Conclusions: These results highlight the potentially crucial role of education and training in pandemic preparedness. Organizations that provide emergency prehospital medical care must address this apparent lack of knowledge regarding infection transmission, and procedures for protection and decontamination. Careful management of the perceptions of emergency prehospital medical care personnel during a pandemic is likely to be critical in achieving an effective response to a widespread outbreak of infectious disease.

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The Saffman-Taylor finger problem is to predict the shape and,in particular, width of a finger of fluid travelling in a Hele-Shaw cell filled with a different, more viscous fluid. In experiments the width is dependent on the speed of propagation of the finger, tending to half the total cell width as the speed increases. To predict this result mathematically, nonlinear effects on the fluid interface must be considered; usually surface tension is included for this purpose. This makes the mathematical problem suffciently diffcult that asymptotic or numerical methods must be used. In this paper we adapt numerical methods used to solve the Saffman-Taylor finger problem with surface tension to instead include the effect of kinetic undercooling, a regularisation effect important in Stefan melting-freezing problems, for which Hele-Shaw flow serves as a leading order approximation when the specific heat of a substance is much smaller than its latent heat. We find the existence of a solution branch where the finger width tends to zero as the propagation speed increases, disagreeing with some aspects of the asymptotic analysis of the same problem. We also find a second solution branch, supporting the idea of a countably infinite number of branches as with the surface tension problem.

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Asylum is being gradually denuded of the national institutional mechanisms (judicial, legislative and administrative) that provide the framework for a fair and effective asylum hearing. In this sense, there is an ongoing ‘denationalization’ or ‘deformalization’ of the asylum process. This chapter critically examines one of the linchpins of this trend: the erection of pre-entry measures at ports of embarkation in order to prevent asylum seekers from physically accessing the territory of the state. Pre-entry measures comprise the core requirement that foreigners possess an entry visa granting permission to enter the state of destination. Visa requirements are increasingly implemented by immigration officials posted abroad or by officials of transit countries pursuant to bilateral agreements (so-called ‘juxtaposed’ immigration controls). Private carriers, which are subject to sanctions if they bring persons to a country who do not have permission to enter, also engage in a form of de facto immigration control on behalf of states. These measures constitute a type of ‘externalized’ or ‘exported’ border that pushes the immigration boundaries of the state as far from its physical boundaries as possible. Pre-entry measures have a crippling impact on the ability of asylum seekers to access the territory of states to claim asylum. In effect, states have ‘externalized’ asylum by replacing the legal obligation on states to protect refugees arriving at ports of entry with what are perceived to be no more than moral obligations towards asylum seekers arriving at the external border of the state.

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We treat two related moving boundary problems. The first is the ill-posed Stefan problem for melting a superheated solid in one Cartesian coordinate. Mathematically, this is the same problem as that for freezing a supercooled liquid, with applications to crystal growth. By applying a front-fixing technique with finite differences, we reproduce existing numerical results in the literature, concentrating on solutions that break down in finite time. This sort of finite-time blow-up is characterised by the speed of the moving boundary becoming unbounded in the blow-up limit. The second problem, which is an extension of the first, is proposed to simulate aspects of a particular two-phase Stefan problem with surface tension. We study this novel moving boundary problem numerically, and provide results that support the hypothesis that it exhibits a similar type of finite-time blow-up as the more complicated two-phase problem. The results are unusual in the sense that it appears the addition of surface tension transforms a well-posed problem into an ill-posed one.

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This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics

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We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.