The Vortex-Wave equation with a single vortex as the limit of the Euler equation

In this article we consider the physical justification of the Vortex-Wave equation introduced by Marchioro and Pulvirenti in the case of a single point vortex moving in an ambient vorticity. We consider a sequence of solutions for the Euler equation in the plane corresponding to initial data consisting of an ambient vorticity in $L^1\cap L^\infty$ and a sequence of concentrated blobs which approach the Dirac distribution. We introduce a notion of a weak solution of the Vortex-Wave equation in terms of velocity (or primitive variables) and then show, for a subsequence of the blobs, the solutions of the Euler equation converge in velocity to a weak solution of the Vortex-Wave equation.Comment: 24 pages, to appea

Vanishing viscosity limit for an expanding domain in space

We study the limiting behavior of viscous incompressible flows when the fluid domain is allowed to expand as the viscosity vanishes. We describe precise conditions under which the limiting flow satisfies the full space Euler equations. The argument is based on truncation and on energy estimates, following the structure of the proof of Kato's criterion for the vanishing viscosity limit. This work complements previous work by the authors, see [Kelliher, Comm. Math. Phys. 278 (2008), 753-773] and [arXiv:0801.4935v1].Comment: 23 pages, submitted for publicatio

Arguments using ontological and causal knowledge (FoIKS 2014)

International audienceWe explore an approach to reasoning about causes via argumentation. We consider a causal model for a physical system, and we look for arguments about facts. Some arguments are meant to provide explanations of facts whereas some challenge these explanations and so on. At the root of argumentation here, are causal links ({A_1, ... ,A_n} causes B) and also ontological links (c_1 is_a} c_2). We introduce here a logical approach which provides a candidate explanation ({A_1, ... ,A_n} explains {B_1, ... ,B_m}) by resorting to an underlying causal link substantiated with appropriate ontological links. Argumentation is then at work from these various explanation links. A case study is developed: a severe storm Xynthia that devastated a county in France in 2010, with an unaccountably high number of casualties

Mitoxantrone in metastatic apudomas: a phase II study of the EORTC Gastro-Intestinal Cancer Cooperative Group.

We performed a phase II study with mitoxantrone in patients with carcinoid tumours, islet cell tumours and medullary carcinomas of the thyroid. Thirty-five eligible patients received mitoxantrone 12 mg m-2 i.v. every 3 weeks. Among 18 previously untreated patients, three responded (17%, 95% CI = 4-41%); no responses were achieved in 17 previously treated patients. Of the 21 patients who had carcinoid tumours, 11 were previously untreated and two achieved a response (18%, 95% CI = 2-52%). Overall response rate was 9% (95% CI = 2-23%). At a median follow-up of 43 months, median overall survival was 16 months. The median survival of 21 patients with a normal alkaline phosphatase was 29 months and 9 months for 14 patients with elevated serum levels (P = 0.005). A similar observation was noticed for gamma-glutamyltransferase (P = 0.007). We concluded that mitoxantrone is not active in APUD tumours. Elevated alkaline phosphatase and gamma-glutamyltransferase are associated with a poor prognosis

Impact of Bayesian network model structure on the accuracy of medical diagnostic systems

While Bayesian network models may contain a handful of numerical parameters that are important for their quality, several empirical studies have confirmed that overall precision of their probabilities is not crucial. In this paper, we study the impact of the structure of a Bayesian network on the precision of medical diagnostic systems. We show that also the structure is not that important - diagnostic accuracy of several medical diagnostic models changes minimally when we subject their structures to such transformations as arc removal and arc reversal. © 2014 Springer International Publishing

Factors related to teaching quality: a validated questionnaire to assess teaching in Spanish higher education

1. Introduction 2. Method 3. Results 4. Conclusions Disclosure statement Additional information References Full Article Figures & data References Citations Metrics Licensing Reprints & Permissions View PDF View EPUB Abstract Quality in higher education requires the evaluation of the teaching-learning and assessment methodologies used by the teachers, the adaptation of the students, as well as the resources used. To respond to this need, this study aims to analyze the validity and reliability of the Factors Related to Teaching Quality (FRTQ) questionnaire, developed for this research. The sample was obtained among Spanish undergraduate students (n = 291). Validation was performed by a content and construct analysis through a review of the literature on the dimensions of teaching, learning and assessment, in addition to obtaining the measure of sampling adequacy and a factor extraction. Reliability was determined by Cronbach’s alpha. The validity and reliability of the questionnaire was confirmed, and the factor analysis showed a six-factor structured model: Functions of the assessment; Attention to diversity, Clarity and control of the educational process; Learning resources; Teaching resources; Assessment resources. The conclusions indicate the importance of approaching some aspects of the educational process from the dimensions of teaching and learning at the same time due to their transversal nature, as well as the relevance of having a useful instrument to evaluate the processes of change and improvement of teaching in Spanish higher education.La calidad en la educación superior requiere la evaluación de las metodologías de enseñanza-aprendizaje y evaluación utilizadas por los docentes, la adecuación de los estudiantes, así como los recursos utilizados. Para responder a esta necesidad, este estudio tiene como objetivo analizar la validez y confiabilidad del cuestionario Factores Relacionados con la Calidad de la Enseñanza (FRTQ), desarrollado para esta investigación. La muestra se obtuvo entre estudiantes universitarios españoles (n = 291). La validación se realizó mediante un análisis de contenido y constructo a través de una revisión de la literatura sobre las dimensiones de enseñanza, aprendizaje y evaluación, además de obtener la medida de adecuación muestral y una extracción factorial. La confiabilidad fue determinada por el alfa de Cronbach. Se confirmó la validez y confiabilidad del cuestionario, y el análisis factorial mostró un modelo estructurado de seis factores: Funciones de la evaluación; Atención a la diversidad, Claridad y control del proceso educativo; recursos de aprendizaje; Recursos didacticos; Recursos de evaluación. Las conclusiones señalan la importancia de abordar algunos aspectos del proceso educativo desde las dimensiones de enseñanza y aprendizaje a la vez por su carácter transversal, así como la pertinencia de contar con un instrumento útil para evaluar los procesos de cambio y mejora de la docencia. en la educación superior española

Explanations of Black-Box Model Predictions by Contextual Importance and Utility

The significant advances in autonomous systems together with an immensely wider application domain have increased the need for trustable intelligent systems. Explainable artificial intelligence is gaining considerable attention among researchers and developers to address this requirement. Although there is an increasing number of works on interpretable and transparent machine learning algorithms, they are mostly intended for the technical users. Explanations for the end-user have been neglected in many usable and practical applications. In this work, we present the Contextual Importance (CI) and Contextual Utility (CU) concepts to extract explanations that are easily understandable by experts as well as novice users. This method explains the prediction results without transforming the model into an interpretable one. We present an example of providing explanations for linear and non-linear models to demonstrate the generalizability of the method. CI and CU are numerical values that can be represented to the user in visuals and natural language form to justify actions and explain reasoning for individual instances, situations, and contexts. We show the utility of explanations in car selection example and Iris flower classification by presenting complete (i.e. the causes of an individual prediction) and contrastive explanation (i.e. contrasting instance against the instance of interest). The experimental results show the feasibility and validity of the provided explanation methods