934 resultados para Kenilworth (Ill.)
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Collection : Bibliothèque des merveilles
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Collection : Biblioteca dell'Accademia storico-giuridica ; 7
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Collection : Modern-théâtre ; 30
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UANL
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Les pédiatres intensivistes ont plusieurs éléments disponibles pour guider leurs décisions par rapport à la ventilation mécanique. Par contre, aucune étude prospective ne décrit les éléments auxquels les intensivistes se réfèrent pour modifier les paramètres du respirateur. Objectifs : Décrire la pratique actuelle de la modification des paramètres du respirateur aux soins intensifs du CHU Sainte-Justine, un hôpital pédiatrique tertiaire. Hypothèse : 80% des modifications des paramètres du respirateur influant sur l’épuration du CO2 sont liées à l’analyse de la PCO2 ou du pH et 80% des modifications des paramètres d’oxygénation sont liés à l’analyse de l’oxymétrie de pouls. Méthodes : En se servant d’un logiciel de recueil de données, les soignants ont enregistré un critère de décision primaire et tous les critères de décision secondaires menant à chaque modification de paramètre du respirateur au moment même de la modification. Résultats : Parmi les 194 modifications des paramètres du respirateur influant sur l’épuration du CO2, faites chez vingts patients, 42.3% ±7.0% avaient pour critère primaire la PCO2 ou le pH sanguin. Parmi les 41 modifications de la pression expiratoire positive et les 813 modifications de la fraction d’oxygène inspirée, 34.1% ±14.5% et 84.5% ±2.5% avaient pour critère primaire l’oxymétrie de pouls, respectivement. Conclusion : Les médecins surestiment le rôle de la PCO2 et du pH sanguins et sousestiment le rôle d’autres critères de décision dans la gestion de la ventilation mécanique. L’amélioration de notre compréhension de la pratique courante devrait aider à l’éboration des systèmes d’aide à la décision clinique en assistance respiratoire.
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A form for obtaining material from other libraries or institutions. Any type of material included.
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This paper examines the implications of policy fracture and arms length governance within the decision making processes currently shaping curriculum design within the English education system. In particular it argues that an unresolved ‘ideological fracture’ at government level has been passed down to school leaders whose response to the dilemma is distorted by the target-driven agenda of arms length agencies. Drawing upon the findings of a large scale on-line survey of history teaching in English secondary schools, this paper illustrates the problems that occur when policy making is divorced from curriculum theory, and in particular from any consideration of the nature of knowledge. Drawing on the social realist theory of knowledge elaborated by Young (2008), we argue that the rapid spread of alternative curricular arrangements, implemented in the absence of an understanding of curriculum theory, undermines the value of disciplined thinking to the detriment of many young people, particularly those in areas of social and economic deprivation.
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Optimal state estimation from given observations of a dynamical system by data assimilation is generally an ill-posed inverse problem. In order to solve the problem, a standard Tikhonov, or L2, regularization is used, based on certain statistical assumptions on the errors in the data. The regularization term constrains the estimate of the state to remain close to a prior estimate. In the presence of model error, this approach does not capture the initial state of the system accurately, as the initial state estimate is derived by minimizing the average error between the model predictions and the observations over a time window. Here we examine an alternative L1 regularization technique that has proved valuable in image processing. We show that for examples of flow with sharp fronts and shocks, the L1 regularization technique performs more accurately than standard L2 regularization.
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We consider four-dimensional variational data assimilation (4DVar) and show that it can be interpreted as Tikhonov or L2-regularisation, a widely used method for solving ill-posed inverse problems. It is known from image restoration and geophysical problems that an alternative regularisation, namely L1-norm regularisation, recovers sharp edges better than L2-norm regularisation. We apply this idea to 4DVar for problems where shocks and model error are present and give two examples which show that L1-norm regularisation performs much better than the standard L2-norm regularisation in 4DVar.