Comportement rhéologique de SBR pur et chargé en noir de carbone : effets de la température et du taux de charge

National audienceNous avons étudié le comportement rhéologique d’un SBR en rhéométrie capillaire dans une gamme de température entre 90°C et 40°C, pur et chargé de 16 à 33 % en masse en noir de carbone. Pour tous les matériaux testés, la courbe d’écoulement peut être divisée en plusieurs zones : à taux de cisaillement faible, nous observons un comportement classique, avec une augmentation régulière de la contrainte avec le taux de cisaillement. Au-dessus d’une certaine contrainte critique, les conditions d’écoulement changent avec l'apparition d'un plateau, lié à la présence de glissement et/ou d’instabilités amont. Cette contrainte critique est indépendante de la température mais augmente linéairement avec le taux de charge. Au-delà du plateau, la contrainte augmente à nouveau, mais avec une pente plus faible. Les courbes d’écoulement obtenues pour les différents mélanges peuvent être superposées à l’aide d’un facteur de glissement dépendant du taux de charges. Nous pouvons en déduire une loi de viscosité générale, basée sur le modèle de Carreau-Yasuda, dans laquelle la viscosité limite et le temps caractéristique dépendent à la fois du taux de charge par une expression de Krieger-Dougherty et de la température par une loi d’Arrhénius

Comportement rhéologique de SBR pur et chargé en noir de carbone

International audienceNous avons utilisé un rhéomètre capillaire pour étudier le comportement en écoulement d'un caoutchouc synthétique SBR (copolymère de styrène et de butadiène). Cette étude est réalisée dans une gamme de température allant de 90°C à 50°C, sur un SBR pur et un SBR chargé de noir de carbone (33% en masse). Différents diamètres de capillaires ont été utilisés (2, 3 et 4 mm) pour des rapports de L/D de 0, 4, 8 et 16. On remarque, pour les deux matériaux, l'existence d'une contrainte critique, au-delà de laquelle le comportement est différent. Cette contrainte ne dépend pas de la température et vaut entre 0,38 et 0,36 MPa pour le SBR pur et entre 0,53 et 0,56 MPa pour le SBR chargé. Au-delà de cette contrainte, il existe un glissement à la paroi que l'on a quantifié pour le SBR chargé

Device re-identification in LoRaWAN through messages linkage

International audienceIn LoRaWAN networks, devices are identified by two identifiers: a globally unique and stable one called DevEUI, and an ephemeral and randomly assigned pseudonym called DevAddr. The association between those identifiers is only known by the network and join servers, and is not available to a passive eavesdropper.In this work, we consider the problem of linking the DevAddr with the corresponding DevAddr based on passive observation of the LoRa traffic transmitted over the air. Leveraging metadata exposed in LoRa frames, we devise a technique to link two messages containing respectively the DevEUI and the DevAddr, thus identifying the link between those identifiers. The approach is based on machine learning algorithms using various pieces of information including timing, signal strength, and fields of the frames. Based on an evaluation using a real-world dataset of 11 million messages, with ground truth available, we show that multiple machine learning models are able to reliably link those identifiers. The best of them achieves an impressive true positive rate of over 0.8 and a false positive rate of 0.001

MPFR: A Multiple-Precision Binary Floating-Point Library With Correct Rounding

This paper presents a multiple-precision binary floating-point library, written in the ISO C language, and based on the GNU MP library. Its particularity is to extend ideas from the IEEE-754 standard to arbitrary precision, by providing correct rounding and exceptions. We demonstrate how these strong semantics are achieved | with no signicant slowdown with respect to other tools | and discuss a few applications where such a library can be useful

Closing a gap in tropical forest biomass estimation : taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees = 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot- level error (in %) from [-23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far- from- negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost

Epithelial atypia in biopsies performed for microcalcifications. Practical considerations about 2,833 serially sectioned surgical biopsies with a long follow-up

This study analyzes the occurrence of epithelial atypia in 2,833 serially sectioned surgical breast biopsies (SB) performed for microcalcifications (median number of blocks per SB:26) and the occurrence of subsequent cancer after an initial diagnosis of epithelial atypia (median follow-up 160 months). Epithelial atypia (flat epithelial atypia, atypical ductal hyperplasia, and lobular neoplasia) were found in 971 SB, with and without a concomitant cancer in 301 (31%) and 670 (69%) SB, respectively. Thus, isolated epithelial atypia were found in 670 out of the 2,833 SB (23%). Concomitant cancers corresponded to ductal carcinomas in situ and micro-invasive (77%), invasive ductal carcinomas not otherwise specified (15%), invasive lobular carcinomas (4%), and tubular carcinomas (4%). Fifteen out of the 443 patients with isolated epithelial atypia developed a subsequent ipsilateral (n = 14) and contralateral (n = 1) invasive cancer. The high slide rating might explain the high percentages of epithelial atypia and concomitant cancers and the low percentage of subsequent cancer after a diagnosis of epithelial atypia as a single lesion. Epithelial atypia could be more a risk marker of concomitant than subsequent cancer

Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees  1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.biogeosciences.net