On the development of an electric current accompanying the contraction of the muscular fibre

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Crucial role of sidewalls in velocity distributions in quasi-2D granular gases

Our experiments and three-dimensional molecular dynamics simulations of particles confined to a vertical monolayer by closely spaced frictional walls (sidewalls) yield velocity distributions with non-Gaussian tails and a peak near zero velocity. Simulations with frictionless sidewalls are not peaked. Thus interactions between particles and their container are an important determinant of the shape of the distribution and should be considered when evaluating experiments on a tightly constrained monolayer of particles.Comment: 4 pages, 4 figures, Added reference, model explanation charified, other minor change

Nurses\u27 Alumnae Association Bulletin, September 1958

Committee Reports Digest of Alumnae Meetings Graduation Awards - 1957 List of Wrong Addresses Marriages Necrology New Arrivals Physical Advances at Jefferson President\u27s Message School of Nursing Repor

Fusion of basic algorithms for detection and localization of vehicle plate numbers

Institut des Systèmes Intelligents et de Robotiqu

A systematic review of randomised controlled trials in rheumatoid arthritis: the reporting and handling of missing data in composite outcomes.

BACKGROUND: Most reported outcome measures in rheumatoid arthritis (RA) trials are composite, whose components comprise single measures that are combined into one outcome. The aims of this review were to assess the range of missing data rates in primary composite outcomes and to document the current practice for handling and reporting missing data in published RA trials compared to the Consolidated Standards of Reporting Trials (CONSORT) recommendations. METHODS: A systematic search for randomised controlled trials was conducted for RA trials published between 2008 and 2013 in four rheumatology and four high impact general medical journals. RESULTS: A total of 51 trials with a composite primary outcome were identified, of which 38 (75 %) used the binary American College of Rheumatology responder index and 13 (25 %) used the Disease Activity Score for 28 joints (DAS28). Forty-four trials (86 %) reported on an intention-to-treat analysis population, while 7 trials (14 %) analysed according to a modified intention-to-treat population. Missing data rates for the primary composite outcome ranged from 2-53 % and were above 30 % in 9 trials, 20-30 % in 11 trials, 10-20 % in 18 trials and below 10 % in 13 trials. Thirty-eight trials (75 %) used non-responder imputation and 10 (20 %) used last observation carried forward to impute missing composite outcome data at the primary time point. The rate of dropout was on average 61 % times higher in the placebo group compared to the treatment group in the 34 placebo controlled trials (relative rate 1.61, 95 % CI: 1.29, 2.02). Thirty-seven trials (73 %) did not report the use of sensitivity analyses to assess the handling of missing data in the primary analysis as recommended by CONSORT guidelines. CONCLUSIONS: This review highlights an improvement in rheumatology trial practice since the revision of CONSORT guidelines, in terms of power calculation and participant's flow diagram. However, there is a need to improve the handling and reporting of missing composite outcome data and their components in RA trials. In particular, sensitivity analyses need to be more widely used in RA trials because imputation is widespread and generally uses single imputation methods, and in this area the missing data rates are commonly differentially higher in the placebo group

Information fusion and adaptation for on-line text recognition

In this paper, we present a new writer independent system dedicated to the automatic recognition of on-line hand-printed texts. This system uses a very large French lexicon (200000 words), which covers numerous fields of application. The recognition process is based on the activation-verification model proposed in perceptive psychology. A set of experts encodes the input signal and extracts probabilistic information at several levels of abstraction (geometrical and morphological). A neural expert generates a tree of segmentation hypotheses. It is explored by a probabilistic fusion expert that uses all the available information (geometrical, morphological and lexical) in order to provide the best transcription of the input signal. We experiment several strategies of self-supervised writer-adaptation on this system. The best one, called “dynamic self-supervised adaptation”, modifies the recognizer parameters continuously. It gets recognition results close to supervised methods. These results are evaluated on a database of 90 texts (5400 words) written by 38 different writers and are very encouraging as they reach a recognition rate of 90%.Dans cet article nous présentons un nouveau système de reconnaissance de textes manuscrits scripts en mode omni-scripteur. Ce système utilise un lexique français de très grande taille (200 000 mots), qui couvre de nombreux champs d'application. Le processus de reconnaissance repose sur le modèle d'activationvérification proposé en psychologie perceptive. Un ensemble d'experts code le signal d'entrée et extrait des informations probabilistes à différents niveaux d'abstraction (géométrique, morphologique). Un expert de segmentation neuronal génère un treillis d’hypothèses qui est exploré par un expert de fusion probabiliste qui utilise toute l’information disponible (géométrique, morphologique et lexicale) afin de fournir la meilleure retranscription du signal d’entrée. Nous avons expérimenté plusieurs stratégies d'adaptation non supervisée au scripteur. La meilleure, appelée « adaptation non-supervisée dynamique» agit en continu sur les paramètres du système. Elle permet d'atteindre des performances proches de l’une adaptation supervisée. Les performances, évaluées sur une base de données comportant 90 textes (5 400 mots) écrits par 38 utilisateurs différents, sont très encourageantes car elles atteignent un taux de reconnaissance de 90%

Nurses\u27 Alumnae Association Bulletin, May 1960

Accreditation of Programs in Nursing Alumnae Meetings, 1959 Committee Reports Greetings from the President Highlights from first issue of Alumnae Bulletin Living in the new nurses residence Lost Members Marriages Necrology New Arrivals Notices Personal Items of Interest Report of the School of Nursing and Nursing Services Staff Nurses Association Student Activities Year of tremendous growth and expansio

Combinaison de classifieurs pour la localisation de visage

Dans cette communication, nous présentons une méthode de localisation de visages dans des images couleurs combinant trois détecteurs respectivement anthropomorphique (détecteur basé sur un modèle d'apparence neuronal), géométrique (détecteur d'ellipse utilisant une Transformée de Hough Généralisée sur l'image des orientations de gradient) et colorimétrique (détecteur de teinte chair utilisant un seuillage dans l'espace CbCr). La combinaison linéaire de ces trois détecteurs produit une carte de probabilités. La localisation du visage dans l'image correspond au maximum absolu de cette carte. Nous montrons l'apport de la combinaison sur le taux de localisation des détecteurs pris isolément

Détection de visages sur des images fixes par combinaison de classifieurs discriminants et de modèles

- Cette communication présente une technique de détection de visages sur des images fixes couleur quelconques applicable à l'indexation de séquences vidéos ou à des bases d'images. Les méthodes exposées sont sans segmentation (globale) combinant une étape par modélisation (fusionnant deux classifieurs) et une étape discriminante exploitant la modélisation. On observe une très bonne capacité à détecter des visages d'orientation variée sur un fond quelconque, même avec des résolutions faibles