Hamatum osteoblastoma

SummaryWe report the case of an osteoblastoma of the hamate bone that was successfully treated by curettage. This tumor is very rare in a carpal bone and only nine cases have been reported in the literature. Pathological examination is mandatory before treatment due to the lack of distinctive clinical and radiological features. Osteoblastomas are benign, but potentially aggressive bone tumors. Treatment of the lesion may either be a conservative “intralesional resection” or radical “wide en bloc resection”. The latter option, which has non-negligible functional consequences in the wrist, should be reserved for recurrence after curettage but may also be considered a primary immediate alternative for aggressive forms

Performance des égaliseurs à complexité réduite et application à la norme EDGE

Nous analysons les performances des récepteurs, réduisant la mémoire du canal de communication, par la borne du filtre adapté (BFA) qui est une borne supérieure (et souvent une bonne approximation) de la détection de séquence basée sur le critère de maximum de vraisemblance (DSMV). Nous démontrons que les performances varient entre celles d'un égaliseur linéaire ou avec retour de décisions et celles de la DSMV avec le canal non raccourci

Splitting Arabic Texts into Elementary Discourse Units

International audienceIn this article, we propose the first work that investigates the feasibility of Arabic discourse segmentation into elementary discourse units within the segmented discourse representation theory framework. We first describe our annotation scheme that defines a set of principles to guide the segmentation process. Two corpora have been annotated according to this scheme: elementary school textbooks and newspaper documents extracted from the syntactically annotated Arabic Treebank. Then, we propose a multiclass supervised learning approach that predicts nested units. Our approach uses a combination of punctuation, morphological, lexical, and shallow syntactic features. We investigate how each feature contributes to the learning process. We show that an extensive morphological analysis is crucial to achieve good results in both corpora. In addition, we show that adding chunks does not boost the performance of our system

Modelling prognostic factors in advanced pancreatic cancer

Pancreatic cancer is the fifth most common cause of cancer death. Identification of defined patient groups based on a prognostic index may improve the prediction of survival and selection of therapy. Many prognostic factors have been identified often based on retrospective, underpowered studies with unclear analyses. Data from 653 patients were analysed. Continuous variables are often simplified assuming a linear relationship with log hazard or introducing a step function (dichotomising). Misspecification may lead to inappropriate conclusions but has not been previously investigated in pancreatic cancer studies. Models based on standard assumptions were compared with a novel approach using nonlinear fractional polynomial (FP) transformations. The model based on FP-transformed covariates was most appropriate and confirmed five previously reported prognostic factors: albumin, CA19-9, alkaline phosphatase, LDH and metastases, and identified three additional factors not previously reported: WBC, AST and BUN. The effects of CA19-9, alkaline phosphatase, AST and BUN may go unrecognised due to simplistic assumptions made in statistical modelling. We advocate a multivariable approach that uses information contained within continuous variables appropriately. The functional form of the relationship between continuous covariates and survival should always be assessed. Our model should aid individual patient risk stratification and the design and analysis of future trials in pancreatic cancer