Exact solution to the exit-time problem for an undamped free particle driven by Gaussian white noise

In a recent paper [Phys. Rev. Lett. 75, 189 (1995)] we have presented the exact analytical expression for the mean exit time, T(x,v), of a free inertial process driven by Gaussian white noise out of a region (0,L) in space. In this paper we give a detailed account of the method employed and present results on asymptotic properties and averages of T(x,v).

Bistability driven by dichotomous noise: A comment

Two recently reported treatments [J. M. Porrà et al., Phys. Rev. A 44, 4866 (1991) and I. L¿Heureux and R. Kapral, J. Chem. Phys. 88, 7468 (1988)] of the problem of bistability driven by dichotomous colored noise with a small correlation time are brought into agreement with each other and with the exact numerical results of L¿Heureux and Kapral [J. Chem. Phys. 90, 2453 (1989)].

Mean first-passage time for system driven by the coin-toss square wave

We study the mean-first-passage-time problem for systems driven by the coin-toss square-wave signal. Exact analytic solutions are obtained for the driftless case. We also obtain approximate solutions for the potential case. The mean-first-passage time exhibits discontinuities and a remarkable nonsmooth oscillatory behavior which, to our knowledge, has not been observed for other kinds of driving noise.

Postmortem pump-driven reperfusion of the vascular system of porcine lungs: towards a new model for surgical training.

PURPOSE: The objective of this experiment is to establish a continuous postmortem circulation in the vascular system of porcine lungs and to evaluate the pulmonary distribution of the perfusate. This research is performed in the bigger scope of a revascularization project of Thiel embalmed specimens. This technique enables teaching anatomy, practicing surgical procedures and doing research under lifelike circumstances. METHODS: After cannulation of the pulmonary trunk and the left atrium, the vascular system was flushed with paraffinum perliquidum (PP) through a heart-lung machine. A continuous circulation was then established using red PP, during which perfusion parameters were measured. The distribution of contrast-containing PP in the pulmonary circulation was visualized on computed tomography. Finally, the amount of leak from the vascular system was calculated. RESULTS: A reperfusion of the vascular system was initiated for 37 min. The flow rate ranged between 80 and 130 ml/min throughout the experiment with acceptable perfusion pressures (range: 37-78 mm Hg). Computed tomography imaging and 3D reconstruction revealed a diffuse vascular distribution of PP and a decreasing vascularization ratio in cranial direction. A self-limiting leak (i.e. 66.8% of the circulating volume) towards the tracheobronchial tree due to vessel rupture was also measured. CONCLUSIONS: PP enables circulation in an isolated porcine lung model with an acceptable pressure-flow relationship resulting in an excellent recruitment of the vascular system. Despite these promising results, rupture of vessel walls may cause leaks. Further exploration of the perfusion capacities of PP in other organs is necessary. Eventually, this could lead to the development of reperfused Thiel embalmed human bodies, which have several applications.

Dynamics of driven three-dimensional thin films: from hdrophilic to superhydrophobic substrates

We study the forced displacement of a thin film of fluid in contact with vertical and inclined substrates of different wetting properties, that range from hydrophilic to hydrophobic, using the lattice-Boltzmann method. We study the stability and pattern formation of the contact line in the hydrophilic and superhydrophobic regimes, which correspond to wedge-shaped and nose-shaped fronts, respectively. We find that contact lines are considerably more stable for hydrophilic substrates and small inclination angles. The qualitative behavior of the front in the linear regime remains independent of the wetting properties of the substrate as a single dispersion relation describes the stability of both wedges and noses. Nonlinear patterns show a clear dependence on wetting properties and substrate inclination angle. The effect is quantified in terms of the pattern growth rate, which vanishes for the sawtooth pattern and is finite for the finger pattern. Sawtooth shaped patterns are observed for hydrophilic substrates and low inclination angles, while finger-shaped patterns arise for hydrophobic substrates and large inclination angles. Finger dynamics show a transient in which neighboring fingers interact, followed by a steady state where each finger grows independently.

An adaptive multiscale method for density-driven instabilities

Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Online teaching of inflammatory skin pathology by a French-speaking international university network

Introduction: Developments in technology, webbased teaching and whole slide imaging have broadened the teaching horizon in anatomic pathology. Creating online learning material including many types of media like radiologic images, videos, clinical and macroscopic photographs and whole slides imaging is now accessible to almost every university. Unfortunately, a major limiting factor to maintain and update the learning material is the amount of work, time and resources needed. In this perspective, a French national university network was initiated in 2011 to build mutualised online teaching pathology modules with clinical cases and tests. This network has been extended to an international level in 2012-2014 (Quebec, Switzerland and Ivory Coast). Method: One of the first steps of the international project was to build a learning module on inflammatory skin pathology intended for interns and residents of pathology and dermatology. A pathology resident from Quebec spent 6 weeks in France and Switzerland to develop the contents and build the module on an e-learning Moodle platform (http: //moodle.sorbonne-paris-cite.fr) under the supervision of two dermatopathologists (BV, MB). The learning module contains text, interactive clinical cases, tests with feedback, whole slides images (WSI), images and clinical photographs. For that module, the virtual slides are decentralized in 2 universities (Bordeaux and Paris 7). Each university is responsible of its own slide scanning, image storage and online display with virtual slide viewers. Results: The module on inflammatory skin pathology includes more than 50 web pages with French original content, tests and clinical cases, links to over 45 WSI and more than 50 micro and clinical photographs. The whole learning module is currently being revised by four dermatopathologists and two senior pathologists. It will be accessible to interns and residents in spring 2014. The experience and knowledge gained from that work will be transferred to the next international fellowship intern whose work will be aimed at creating lung and breast pathology learning modules. Conclusion: The challenges of sustaining a project of this scope are numerous. The technical aspect of whole-slide imaging and storage needs to be developed by each university or group. The content needs to be regularly updated, completed and its use and existence needs to be promoted by the different actors in pathology. Of the great benefits of that kind of project are the international partnerships and connections that have been established between numerous Frenchspeaking universities and pathologists with the common goals of promoting education in pathology and the use of technology including whole slide imaging. * The Moodle website is hosted by PRES Sorbonne Paris Cité, and financial supports for hardware have been obtained from UNF3S (http://www.unf3s.org/) and PRES Sorbonne Paris Cité. Financial support for international fellowships has been obtained from CFQCU (http://www.cfqcu.org/).

Mean first-passage time of continuous non-Markovian processes driven by colored noise

An equation for mean first-passage times of non-Markovian processes driven by colored noise is derived through an appropriate backward integro-differential equation. The equation is solved in a Bourret-like approximation. In a weak-noise bistable situation, non-Markovian effects are taken into account by an effective diffusion coefficient. In this situation, our results compare satisfactorily with other approaches and experimental data.

Dynamics of a paramagnetic colloidal particle driven on a magnetic-bubble lattice

We present a theoretical study of the recently observed dynamical regimes of paramagnetic colloidal particles externally driven above a regular lattice of magnetic bubbles [P. Tierno, T. H. Johansen, and T. M. Fischer, Phys. Rev. Lett. 99, 038303 (2007)]. An external precessing magnetic field alters the potential generated by the surface of the film in such a way to either drive the particle circularly around one bubble, ballistically through the array, or in triangular orbits on the interstitial regions between the bubbles. In the ballistic regime, we observe different trajectories performed by the particles phase locked with the external driving. Superdiffusive motion, which was experimentally found bridging the localized and delocalized dynamics, emerge only by introducing a certain degree of randomness into the bubbles size distribution.

Programa de mentoria online para professores iniciantes: fases de um processo

Neste artigo analisamos as fases evidenciadas no desenvolvimento do Programa de Mentoria do Portal dos Professores da Universidade Federal de São Carlos (SP). O programa se caracteriza por ser online e é dirigido para professores dos anos iniciais do ensino fundamental com até cinco anos de experiência. Foi conduzido por três pesquisadoras e onze mentoras (professoras experientes) que acompanharam individualmente, a distância e por meio de correspondências eletrônicas, 56 professoras iniciantes durante períodos entre seis meses a dois anos e meio. Do ponto de vista teórico consideramos a literatura relativa à aprendizagem e desenvolvimento profissional da docência; início da carreira docente; processos de mentoria e educação a distância. Metodologicamente desenvolvemos uma pesquisa-ação a partir de estratégias construtivo-colaborativas. As principais fontes de dados foram as correspondências trocadas entre mentoras e professoras iniciantes; diários reflexivos de mentoras e professoras iniciantes; redação de casos de ensino pelas professoras iniciantes; registros de observação das reuniões semanais ocorridos entre pesquisadoras e mentoras. Os resultados apontam que os processos de mentoria investigados ocorrem segundo fases distintas (fase inicial ou de aproximação; fase de desenvolvimento ou aprofundamento; fase de desligamento) com características, objetivos e procedimentos próprios.

The InterActive Choice Aid: A new approach to supporting online consumer decision making

Interactive Choice Aid (ICA) is a decision aid, introduced in this paper, that systematically assists consumers with online purchase decisions. ICA integrates aspects from prescriptive decision theory, insights from descriptive decision research, and practical considerations; thereby combining pre-existing best practices with novel features. Instead of imposing an objectively ideal but unnatural decision procedure on the user, ICA assists the natural process of human decision-making by providing explicit support for the execution of the user's decision strategies. The application contains an innovative feature for in-depth comparisons of alternatives through which users' importance ratings are elicited interactively and in a playful way. The usability and general acceptance of the choice aid was studied; results show that ICA is a promising contribution and provides insights that may further improve its usability.