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Institution

Pierre-and-Marie-Curie University

EducationParis, France
About: Pierre-and-Marie-Curie University is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Raman spectroscopy. The organization has 34448 authors who have published 56139 publications receiving 2392398 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors proposed a graphical approach for electrochemical impedance data using Bode plots, corrected for Ohmic resistance, logarithmic plots of the imaginary component of the impedance, and effective capacitance plots.
Abstract: Bode plots, corrected for Ohmic resistance, logarithmic plots of the imaginary component of the impedance, and effective capacitance plots are shown to be useful complements to the more traditionally used complex-plane and Bode representations for electrochemical impedance data. The graphical methods are illustrated by synthetic data and by experimental data associated with corrosion in saline environments. Bode plots are shown, in particular, to be confounded by the influence of electrolyte resistance. The plots proposed here provide useful guides to model development for both reactive and blocking systems. The logarithmic plots of the imaginary component of the impedance and effective capacitance plots are useful for all impedance data, and the correction for Ohmic resistance in Bode plots is useful when the solution resistance is not negligible.

399 citations

Journal ArticleDOI
TL;DR: ‘Universite Pierre et Marie Curie (Paris VI) and Groupe de Neurobiologie Appliqute, Laboratoire de Physiologie de la Nutrition, C. R. 7, 78350 Jouy en Josas (France)’

399 citations

Proceedings ArticleDOI
04 Dec 2006
TL;DR: The results show that the first four packets of a TCP connection are sufficient to classify known applications with an accuracy over 90% and to identify new applications as unknown with a probability of 60%.
Abstract: The automatic detection of applications associated with network traffic is an essential step for network security and traffic engineering. Unfortunately, simple port-based classification methods are not always efficient and systematic analysis of packet payloads is too slow. Most recent research proposals use flow statistics to classify traffic flows once they are finished, which limit their applicability for online classification. In this paper, we evaluate the feasibility of application identification at the beginning of a TCP connection. Based on an analysis of packet traces collected on eight different networks, we find that it is possible to distinguish the behavior of an application from the observation of the size and the direction of the first few packets of the TCP connection. We apply three techniques to cluster TCP connections: K-Means, Gaussian Mixture Model and spectral clustering. Resulting clusters are used together with assignment and labeling heuristics to design classifiers. We evaluate these classifiers on different packet traces. Our results show that the first four packets of a TCP connection are sufficient to classify known applications with an accuracy over 90% and to identify new applications as unknown with a probability of 60%.

398 citations

Journal ArticleDOI
TL;DR: A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings.
Abstract: Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work.

398 citations

Journal ArticleDOI
TL;DR: In places where planned vaginal delivery is a common practice and when strict criteria are met before and during labor,planned vaginal delivery of singleton fetuses in breech presentation at term remains a safe option that can be offered to women.

398 citations


Authors

Showing all 34671 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Guido Kroemer2361404246571
Krzysztof Matyjaszewski1691431128585
J. E. Brau1621949157675
E. Hivon147403118440
Kazuhiko Hara1411956107697
Simon Prunet14143496314
H. J. McCracken14057971091
G. Calderini1391734102408
Stefano Giagu1391651101569
Jean-Paul Kneib13880589287
G. Marchiori137159094277
J. Ocariz136156295905
Jean-Marie Tarascon136853137673
Alexis Brice13587083466
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202370
2022361
2021388
2020580
2019855