Conservatoire national des arts et métiers

About: Conservatoire national des arts et métiers is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Context (language use). The organization has 3573 authors who have published 7127 publications receiving 141430 citations. The organization is also known as: CNAM & Conservatoire des arts et métiers.

Determinants of thyroid volume in healthy French adults participating in the SU.VI.MAX cohort.

Abstract: Summary OBJECTIVE To study the relative importance of determinants of thyroid volume. DESIGN Cross-sectional study on a sample of subjects issued from the SU.VI.MAX cohort. SUBJECTS 2987 French subjects (1713 women aged 35‐60 years and 1274 men aged 45‐60 years). None of them had previous or present thyroid disease. MEASUREMENTS Thyroid volume was determined by ultrasound. Serum TSH and free thyroxine (fT4) were measured in duplicate. Urinary iodine and urinary thiocyanate were assayed in random morning urine samples. RESULTS For both sexes, thyroid volume (ml) was positively correlated with weight, height, body mass index and body surface area (Pa 0·0001) and negatively with age for females (Pa 0·0009). When the urinary iodine concentration was adjusted for urinary thiocyanate concentration and their interaction, the thyroid volume was negatively correlated with urinary iodine (males Pa 0·02, females Pa 0·006) and positively correlated with urinary thiocyanate (males Pa 0·0001, females Pa 0·004). Mean thyroid volume was greater among active smokers than non-smokers (males P< 0·0001, females Pa 0·0004) and was greater among former smokers than among non-smokers (males Pa 0·0001, femalesa 0·004). Free T4 and thyroid volume were positively correlated for both sexes (Pa 0·0001). TSH was negatively correlated with thyroid volume for both groups (Pa 0·0001). Female users of oral contraception (aged 35‐45 years) had a smaller thyroid volume than non-users (Pa 0·0009).

A fast least-squares algorithm for linearly constrained adaptive filtering

Abstract: An extension of the field of fast least-squares techniques is presented. It is shown that the adaptation gain, which is updated with a number of operations proportional to the number of transversal filter coefficients, can be used to update the coefficients of a linearly constrained adaptive filter. An algorithm that is robust to round-off errors is derived. It is general and flexible. It can handle multiple constraints and multichannel signals. Its performance is illustrated by simulations and compared with the classical LMS-based Frost (1972) algorithm.

Genomewide Association Study of a Rapid Progression Cohort Identifies New Susceptibility Alleles for AIDS (ANRS Genomewide Association Study 03)

Abstract: BACKGROUND Previous genomewide association studies (GWASs) of AIDS have targeted end points based on the control of viral load and disease nonprogression. The discovery of genetic factors that predispose individuals to rapid progression to AIDS should also reveal new insights into the molecular etiology of the pathology. METHODS We undertook a case-control GWAS of a unique cohort of 85 human immunodeficiency virus type 1 (HIV-1)-infected patients who experienced rapid disease progression, using Illumina HumanHap300 BeadChips. The case group was compared with a control group of 1352 individuals for the 291,119 autosomal single-nucleotide polymorphisms (SNPs) passing the quality control tests, using the false-discovery rate (FDR) statistical method for multitest correction. RESULTS Novel associations with rapid progression (FDR, < or = 25%) were identified for PRMT6 (P = 6.1 x 10(-7); odds ratio [OR], 0.24), SOX5 (P = 1.8 x 10(-6); OR, 0.45), RXRG (P = 3.9 x 10(-6); OR, 3.29), and TGFBRAP1 (P = 7 x 10(-6); OR, 0.34). The haplotype analysis identified exonic and promoter SNPs potentially important for PRMT6 and TGFBRAP1 function. CONCLUSIONS The statistical and biological relevance of these associations and their high ORs underscore the power of extreme phenotypes for GWASs, even with a modest sample size. These genetic results emphasize the role of the transforming growth factor beta pathway in the pathogenesis of HIV-1 disease. Finally, the wealth of information provided by this study should help unravel new diagnostic and therapeutic targets.

Improved Constraints on Models of Glacial Isostatic Adjustment: A Review of the Contribution of Ground-Based Geodetic Observations

Abstract: The provision of accurate models of Glacial Isostatic Adjustment (GIA) is presently a priority need in climate studies, largely due to the potential of the Gravity Recovery and Climate Experiment (GRACE) data to be used to determine accurate and continent-wide assessments of ice mass change and hydrology. However, modelled GIA is uncertain due to insufficient constraints on our knowledge of past glacial changes and to large simplifications in the underlying Earth models. Consequently, we show differences between models that exceed several mm/year in terms of surface displacement for the two major ice sheets: Greenland and Antarctica. Geodetic measurements of surface displacement offer the potential for new constraints to be made on GIA models, especially when they are used to improve structural features of the Earth’s interior as to allow for a more realistic reconstruction of the glaciation history. We present the distribution of presently available campaign and continuous geodetic measurements in Greenland and Antarctica and summarise surface velocities published to date, showing substantial disagreement between techniques and GIA models alike. We review the current state-of-the-art in ground-based geodesy (GPS, VLBI, DORIS, SLR) in determining accurate and precise surface velocities. In particular, we focus on known areas of need in GPS observation level models and the terrestrial reference frame in order to advance geodetic observation precision/accuracy toward 0.1 mm/year and therefore further constrain models of GIA and subsequent present-day ice mass change estimates.

Addressing Failure Prediction by Learning Model Confidence

Abstract: Assessing reliably the confidence of a deep neural network and predicting its failures is of primary importance for the practical deployment of these models. In this paper, we propose a new target criterion for model confidence, corresponding to the True Class Probability (TCP). We show how using the TCP is more suited than relying on the classic Maximum Class Probability (MCP). We provide in addition theoretical guarantees for TCP in the context of failure prediction. Since the true class is by essence unknown at test time, we propose to learn TCP criterion on the training set, introducing a specific learning scheme adapted to this context. Extensive experiments are conducted for validating the relevance of the proposed approach. We study various network architectures, small and large scale datasets for image classification and semantic segmentation. We show that our approach consistently outperforms several strong methods, from MCP to Bayesian uncertainty, as well as recent approaches specifically designed for failure prediction.