986 resultados para normative theory


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The aim of this study was to provide an insight into normative values of the ascending aorta in regards to novel endovascular procedures using ECG-gated multi-detector CT angiography. Seventy-seven adult patients without ascending aortic abnormalities were evaluated. Measurements at relevant levels of the aortic root and ascending aorta were obtained. Diameter variations of the ascending aorta during cardiac cycle were also considered. Mean diameters (mm) were as follows: LV outflow tract 20.3 +/- 3.4, coronary sinus 34.2 +/- 4.1, sino-tubular junction 29.7 +/- 3.4 and mid ascending aorta 32.7 +/- 3.8 with coefficients of variation (CV) ranging from 12 to 17%. Mean distances (mm) were: from the plane passing through the proximal insertions of the aortic valve cusps to the right brachio-cephalic artery (BCA) 92.6 +/- 11.8, from the plane passing through the proximal insertions of the aortic valve cusps to the proximal coronary ostium 12.1 +/- 3.7, and between both coronary ostia 7.2 +/- 3.1, minimal arc of the ascending aorta from left coronary ostium to right BCA 52.9 +/- 9.5, and the fibrous continuity between the aortic valve and the anterior leaflet of the mitral valve 14.6 +/- 3.3, CV 13-43%. Mean aortic valve area was 582.0 +/- 131.9 mm(2). The variation of the antero-posterior and transverse diameters of the ascending aorta during the cardiac cycle were 8.4% and 7.3%, respectively. Results showed large inter-individual variations in diameters and distances but with limited intra-individual variations during the cardiac cycle. A personalized approach for planning endovascular devices must be considered.

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The RuskSkinner formalism was developed in order to give a geometrical unified formalism for describing mechanical systems. It incorporates all the characteristics of Lagrangian and Hamiltonian descriptions of these systems (including dynamical equations and solutions, constraints, Legendre map, evolution operators, equivalence, etc.). In this work we extend this unified framework to first-order classical field theories, and show how this description comprises the main features of the Lagrangian and Hamiltonian formalisms, both for the regular and singular cases. This formulation is a first step toward further applications in optimal control theory for partial differential equations. 2004 American Institute of Physics.

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AIMS: The objectives of this study were to analyse (a) the distribution of risky single-occasion drinking (RSOD) among 19-year-old men in Switzerland and (b) to show the percentage of all alcohol consumption in the form of RSOD. METHODS: The study was based on a census of Swiss francophone 19-year-old men consecutively reporting for processing. The study was conducted at Army Recruitment Center. The participants were 4116 recruits consecutively enrolling for mandatory army recruitment procedures between 23 January and 29 August in 2007. The measures were alcohol consumption measured in drinks of approximately 10 g of pure alcohol, number of drinking occasions with six or more drinks (RSOD) in the past 12 months and a retrospective 1 week drinking diary. RESULTS: 264 recruits were never seen by the research staff, 3536 of the remaining 3852 conscripts completed a questionnaire which showed that 7.2% abstained from alcohol and 75.5% of those drinking had an RSOD day at least monthly. The typical frequency of drinking was 1-3 days per week on weekends. The average quantity on weekends was about seven drinks, 69.3% of the total weekly consumption was in the form of RSOD days, and of all the alcohol consumed, 96.2% was by drinkers who had RSOD days at least once a month. CONCLUSION: Among young men, RSOD constitutes the norm. Prevention consequently must address the total population and not only high-risk drinkers.

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This paper studies a risk measure inherited from ruin theory and investigates some of its properties. Specifically, we consider a value-at-risk (VaR)-type risk measure defined as the smallest initial capital needed to ensure that the ultimate ruin probability is less than a given level. This VaR-type risk measure turns out to be equivalent to the VaR of the maximal deficit of the ruin process in infinite time. A related Tail-VaR-type risk measure is also discussed.

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A new aggregation method for decision making is presented by using induced aggregation operators and the index of maximum and minimum level. Its main advantage is that it can assess complex reordering processes in the aggregation that represent complex attitudinal characters of the decision maker such as psychological or personal factors. A wide range of properties and particular cases of this new approach are studied. A further generalization by using hybrid averages and immediate weights is also presented. The key issue in this approach against the previous model is that we can use the weighted average and the ordered weighted average in the same formulation. Thus, we are able to consider the subjective attitude and the degree of optimism of the decision maker in the decision process. The paper ends with an application in a decision making problem based on the use of the assignment theory.

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A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.

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This paper examines key aspects of Allan Gibbard's psychological account of moral activity. Inspired by evolutionary theory, Gibbard paints a naturalistic picture of morality mainly based on two specific types of emotion: guilt and anger. His sentimentalist and expressivist analysis is also based on a particular conception of rationality. I begin by introducing Gibbard's theory before testing some key assumptions underlying his system against recent empirical data and theories. The results cast doubt on some crucial aspects of Gibbard's philosophical theory, namely his reduction of morality to anger and guilt, and his theory of 'normative governance'. Gibbard's particular version of expressivism may be undermined by these doubts.

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Schizophrenia is postulated to be the prototypical dysconnection disorder, in which hallucinations are the core symptom. Due to high heterogeneity in methodology across studies and the clinical phenotype, it remains unclear whether the structural brain dysconnection is global or focal and if clinical symptoms result from this dysconnection. In the present work, we attempt to clarify this issue by studying a population considered as a homogeneous genetic sub-type of schizophrenia, namely the 22q11.2 deletion syndrome (22q11.2DS). Cerebral MRIs were acquired for 46 patients and 48 age and gender matched controls (aged 6-26, respectively mean age = 15.20 ± 4.53 and 15.28 ± 4.35 years old). Using the Connectome mapper pipeline (connectomics.org) that combines structural and diffusion MRI, we created a whole brain network for each individual. Graph theory was used to quantify the global and local properties of the brain network organization for each participant. A global degree loss of 6% was found in patients' networks along with an increased Characteristic Path Length. After identifying and comparing hubs, a significant loss of degree in patients' hubs was found in 58% of the hubs. Based on Allen's brain network model for hallucinations, we explored the association between local efficiency and symptom severity. Negative correlations were found in the Broca's area (p < 0.004), the Wernicke area (p < 0.023) and a positive correlation was found in the dorsolateral prefrontal cortex (DLPFC) (p < 0.014). In line with the dysconnection findings in schizophrenia, our results provide preliminary evidence for a targeted alteration in the brain network hubs' organization in individuals with a genetic risk for schizophrenia. The study of specific disorganization in language, speech and thought regulation networks sharing similar network properties may help to understand their role in the hallucination mechanism.

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Planning with partial observability can be formulated as a non-deterministic search problem in belief space. The problem is harder than classical planning as keeping track of beliefs is harder than keeping track of states, and searching for action policies is harder than searching for action sequences. In this work, we develop a framework for partial observability that avoids these limitations and leads to a planner that scales up to larger problems. For this, the class of problems is restricted to those in which 1) the non-unary clauses representing the uncertainty about the initial situation are nvariant, and 2) variables that are hidden in the initial situation do not appear in the body of conditional effects, which are all assumed to be deterministic. We show that such problems can be translated in linear time into equivalent fully observable non-deterministic planning problems, and that an slight extension of this translation renders the problem solvable by means of classical planners. The whole approach is sound and complete provided that in addition, the state-space is connected. Experiments are also reported.

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The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.