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11.
Clinical trial results support a preference for using CLA preparations enriched with two isomers rather than four isomers in human studies 总被引:1,自引:0,他引:1
CLA mixtures are now commercially available. They differ from each other with respect to their content of CLA isomers and
their degree of purification. As a group of natural FA, CLA have been widely assumed to be safe. However, the suspected presence
of both impurities and particular isomers might induce undesirable side effects. Despite this potential health risk, only
a few CLA preparations have been tested under rigorous conditions for clinical efficacy and safety. Based on the limited results
available, it is possible to suggest that preparations enriched in c9,t11 and t10,c12 isomers are preferable for human consumption compared to preparations containing four isomers, in terms both of safety
and efficacy. 相似文献
12.
Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation
René Mandiau Alexis Champion Jean-Michel Auberlet Stéphane Espié Christophe Kolski 《Applied Intelligence》2008,28(2):121-138
This paper describes a multi-agent coordination mechanism applied to intersection simulation situations. In a goal of urban
traffic simulation, we must consider the dynamic interactions between autonomous vehicles. The field of multi-agent systems
provides us some studies for such systems, in particular on the coordination mechanisms. Conflicts between vehicles (i.e.
agents) are very frequent in such applications, and they may cause deadlocks, particularly at intersections such as crossroads.
Our approach is based on the solving of two player games/decision matrices which characterize three basic situations. An aggregation
method generalizes to n-player games for complex crossroads. The objective of this approach consists in searching basic two-player
matrices for solving n-agent problems. To explain the principle, we describe our approach for a particular case of crossroad
with three agents. Finally, the obtained results have been examined via a tool of road traffic simulation, ARCHISIM. We assume
also that the global traffic replicates the behavior of agents in different situations. 相似文献
13.
Julien Ah-Pine Marco Bressan Stephane Clinchant Gabriela Csurka Yves Hoppenot Jean-Michel Renders 《Multimedia Tools and Applications》2009,42(1):31-56
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing
that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media
pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering
them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal
similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity
measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can
frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text
illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications:
a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
Gabriela CsurkaEmail: |
Dr. Julien Ah-Pine joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities. 相似文献
14.
Cognitive control is a key tool for adaptation in dynamic situations. The aim of the study is to assess the relevance of a theoretical framework for cognitive control in dynamic situations, in order to understand brain-injured (BI) car drivers' cognitive impairment. The framework supports a cognitive control multimodality based on the crossing of two orthogonal dimensions: symbolic/subsymbolic; anticipative/reactive control. BI car drivers' behaviour was compared with that of a control group (CTRL) during driving simulator scenarios. Eye movement analysis, among other variables, revealed that BI car drivers made use of a more symbolic and reactive control than did CTRL drivers. CTRL drivers showed a more stable cognitive compromise than BI drivers. The latter became less symbolic and more reactive in the case of difficult scenarios. In addition, BI drivers focused on the main task of trajectory management, with fewer resources devoted to traffic interaction management. STATEMENT OF RELEVANCE: An explanation of differences between BI and CTRL drivers in terms of cognitive control requirements, attention and processing speed is put forward. From this, it is possible to derive some implications in terms of driver assistance (e.g. lane keeping or a warning assistance device) and rehabilitation. 相似文献
15.
This article introduces an improved approach for the characterization of in-plane rigid-body vibration, based on digital processing of stroboscopic images of the moving part. The method involves a sample preparation step, in order to pattern a periodic microstructure on the vibrating device, for instance, by focused ion beam milling. An image processing method has then been developed to perform the optimum reconstruction of this a priori known object feature. In-plane displacement and rotation are deduced simultaneously with a high resolution (10-2 pixel and 0.5 x 10(-3) rad, respectively). The measurement principle combines phase measurements-that provide the high resolution-with correlation-that unwraps the phase with the proper phase constants. The vibration modes of a tuning fork are used for demonstrating the capabilities of the method. For applications allowing the sample preparation, the proposed methodology is more convenient than common interference methods or image processing techniques for the characterization of the vibration modes, even for amplitudes in the nanometer range. 相似文献
16.
This paper introduces an accurate, efficient, and unified engine dedicated to dynamic animation of d-dimensional deformable objects. The objects are modelled as d-dimensional manifolds defined as functional combinations of a mesh of 3D control points, weighted by parametric blending
functions. This model ensures that, at each time step, the object shape conforms to its manifold definitions. The object motion
is deduced from the control points dynamic animation. In fact, control points should be viewed as the degrees of freedom of
the continuous object. The chosen dynamic equations (Lagrangian formalism) reflect this generic modelling scheme and yield
an exact and computationally efficient linear system. 相似文献
17.
Explicit boundary dissipative conditions are given for the exponential stability in -norm of one-dimensional linear hyperbolic systems of balance laws over a finite interval, when the matrix is marginally diagonally stable. The result is illustrated with an application to boundary feedback stabilisation of open channels represented by linearised Saint–Venant–Exner equations. 相似文献
18.
Jérôme Dinet Monik Favart & Jean-Michel Passerault 《Journal of Computer Assisted Learning》2004,20(5):338-346
Abstract Boolean systems still constitute most of the installed base of online public access catalogues (OPACs) in the French universities even if many studies have shown that Boolean operators are not frequently used by ‘non‐librarian’ users (by contrast with professional librarians). The first study examined the use of Boolean operators by French university students; In the second study, elaborated to evaluate the impact of information search expertise on this use, Boolean operators are explicitly presented and participants were explicitly invited to use them. We assumed that university students would not frequently use the operators in searching, and that even if they were explicitly invited to make use of them. Results obtained with the first study based on transaction logs analyses confirmed that French university students did not frequently use Boolean operators. The impact of information search expertise, analysed in the second study, compared three levels of expertise: Novice (university students), intermediate (future professional librarians), and expert (professional librarians). Results showed that, even if the three groups were invited to use Boolean operators, this use increased significantly with the level of information search expertise. University students, if they manage procedural functions of connectives in natural language, do not always manage the whole set of procedural functions carried by such connectives when used in the documentary language. So, the relevance of presenting explicit Boolean operators in the OPACs when users are ‘non‐librarians’ is questioned. 相似文献
19.
20.
Jolien Beeken Sofie Kessels Jean-Michel Rigo Yeranddy A. Alpizar Laurent Nguyen Bert Brne 《International journal of molecular sciences》2022,23(18)
p27kip1 is a multifunctional protein that promotes cell cycle exit by blocking the activity of cyclin/cyclin-dependent kinase complexes as well as migration and motility via signaling pathways that converge on the actin and microtubule cytoskeleton. Despite the broad characterization of p27kip1 function in neural cells, little is known about its relevance in microglia. Here, we studied the role of p27kip1 in microglia using a combination of in vitro and in situ approaches. While the loss of p27kip1 did not affect microglial density in the cerebral cortex, it altered their morphological complexity in situ. However, despite the presence of p27kip1 in microglial processes, as shown by immunofluorescence in cultured cells, loss of p27kip1 did not change microglial process motility and extension after applying laser-induced brain damage in cortical brain slices. Primary microglia lacking p27kip1 showed increased phagocytic uptake of synaptosomes, while a cell cycle dead variant negatively affected phagocytosis. These findings indicate that p27kip1 plays specific roles in microglia. 相似文献