Spectroscopic detection of carbon nanotube interaction with amphiphilic molecules in epoxy resin composites

Incorporation of carbon nanotubes into epoxy resin composites has the effect of increasing electrical conductivity at low percolation levels. An amphiphilic molecule such as palmitic acid has been used to increase the surface contact area and improve the dispersion of the carbon nanotube bundles in the prepolymer. The chemical environment of the dispersed nanotubes has been probed using vibrational Raman spectroscopy. Spectroscopic Raman maps, on sample surfaces (60x60 µm2) with ratios of nanotubes to palmitic acid varying from 1:2 to 2:1 by weight, have been recorded to test the uniformity of the dispersion. Substantial spatial inhomogeneities have been observed in the G-band shift and an additional spectral band at 1450 cm-1. The 1450 cm-1 band has been attributed to the CH3 group of the amphiphilic molecules adsorbed onto the nanotube surface. The maps are correlated with the measured electrical conductivity values. The highest conductivity has been observed for the best dispersed nanotubes and nanotubes with the highest degree of interaction

IFN-gamma mediates the rejection of haematopoietic stem cells in IFN-gammaR1-deficient hosts.

International audienceBACKGROUND: Interferon-gamma receptor 1 (IFN-gammaR1) deficiency is a life-threatening inherited disorder, conferring predisposition to mycobacterial diseases. Haematopoietic stem cell transplantation (HSCT) is the only curative treatment available, but is hampered by a very high rate of graft rejection, even with intra-familial HLA-identical transplants. This high rejection rate is not seen in any other congenital disorders and remains unexplained. We studied the underlying mechanism in a mouse model of HSCT for IFN-gammaR1 deficiency. METHODS AND FINDINGS: We demonstrated that HSCT with cells from a syngenic C57BL/6 Ifngr1+/+ donor engrafted well and restored anti-mycobacterial immunity in naive, non-infected C57BL/6 Ifngr1-/- recipients. However, Ifngr1-/- mice previously infected with Mycobacterium bovis bacillus Calmette-Guérin (BCG) rejected HSCT. Like infected IFN-gammaR1-deficient humans, infected Ifngr1-/- mice displayed very high serum IFN-gamma levels before HSCT. The administration of a recombinant IFN-gamma-expressing AAV vector to Ifngr1-/- naive recipients also resulted in HSCT graft rejection. Transplantation was successful in Ifngr1-/- x Ifng-/- double-mutant mice, even after BCG infection. Finally, efficient antibody-mediated IFN-gamma depletion in infected Ifngr1-/- mice in vivo allowed subsequent engraftment. CONCLUSIONS: High serum IFN-gamma concentration is both necessary and sufficient for graft rejection in IFN-gammaR1-deficient mice, inhibiting the development of heterologous, IFN-gammaR1-expressing, haematopoietic cell lineages. These results confirm that IFN-gamma is an anti-haematopoietic cytokine in vivo. They also pave the way for HSCT management in IFN-gammaR1-deficient patients through IFN-gamma depletion from the blood. They further raise the possibility that depleting IFN-gamma may improve engraftment in other settings, such as HSCT from a haplo-identical or unrelated donor

Reconnaissance et détection robuste d'objets couleur

Dans cet article, nous présentons une nouvelle approche de reconnaissance, d'objets basée sur l'utilisation des moments Zernike appliqués sur des images couleur. La détection d'objets repose sur une approche utilisant une segmentation couleur et l'étiquetage des composantes connexes. Une méthode basée sur les séparateurs à vaste marge est utilisée pour l'étape d'apprentissage et de reconnaissance. Nous illustrons la méthode proposée sur des images couleur incluant quelques objets de la base de données COIL-100

A novel high efficiency, low maintenance, hydroponic system for synchronous growth and flowering of Arabidopsis thaliana

BACKGROUND: Arabidopsis thaliana is now the model organism for genetic and molecular plant studies, but growing conditions may still impair the significance and reproducibility of the experimental strategies developed. Besides the use of phytotronic cabinets, controlling plant nutrition may be critical and could be achieved in hydroponics. The availability of such a system would also greatly facilitate studies dealing with root development. However, because of its small size and rosette growth habit, Arabidopsis is hardly grown in standard hydroponic devices and the systems described in the last years are still difficult to transpose at a large scale. Our aim was to design and optimize an up-scalable device that would be adaptable to any experimental conditions. RESULTS: An hydroponic system was designed for Arabidopsis, which is based on two units: a seed-holder and a 1-L tank with its cover. The original agar-containing seed-holder allows the plants to grow from sowing to seed set, without transplanting step and with minimal waste. The optimum nitrate supply was determined for vegetative growth, and the flowering response to photoperiod and vernalization was characterized to show the feasibility and reproducibility of experiments extending over the whole life cycle. How this equipment allowed to overcome experimental problems is illustrated by the analysis of developmental effects of nitrate reductase deficiency in nia1nia2 mutants. CONCLUSION: The hydroponic device described in this paper allows to drive small and large scale cultures of homogeneously growing Arabidopsis plants. Its major advantages are its flexibility, easy handling, fast maintenance and low cost. It should be suitable for many experimental purposes

Etude comparative de critères d'évaluation de la segmentation

- Nous présentons dans cet article une étude comparative de plusieurs critères d'évaluation de résultats de segmentation d'image dans un contexte non supervisé. Nous avons utilisé une base de cent images synthétiques composées de régions uniformes et texturées. La valeur des sept critères analysés est comparée à la mesure de Vinet (correspondant au taux de classification) sur une base de trois cent résultats de segmentation

An analysis of the extent to which monetary and non-monetary rewards motivate employees within a Chinese Financial-services SME

There have been many controversies related to the importance of monetary and non-monetary rewards on motivating employees. In order to help managers to motivate employees effectively, this research set up to analyze the extent to which monetary and non-monetary rewards motivate employees within a case company that is a Chinese Financial-services SME

Recalage de modèle éléments finis utilisant une fonction coût géométrique pour l'identification de paramètres matériau en dynamique transitoire.

Pour identifier la valeur de paramètres matériaux, on réalise des essais normalisés sur des éprouvettes du matériau considéré. Dans ce travail, nous introduisons une nouvelle méthode numérique pour l'identification de paramètres de matériau hyperélastique dans un cadre de dynamique transitoire. Nous nous intéressons particulièrement aux méthodes d'identification basées sur des mesures de champs sans contact. Dans cette situation, on peut citer une technique très utilisée, la corrélation d'images numériques, qui permet l'obtention de champs de déplacement. En utilisant une procédure basée sur un recalage de modèle par éléments finis (Finite Element Model Updating), on propose ici une nouvelle famille de fonctions coûts basées sur la géométrie uniquement. Notre objectif est d'éviter l'utilisation de la corrélation d'images numériques qui est nécessaire lorsque l'on utilise une fonction coût basée sur le déplacement. Le résultat des mesures expérimentales consiste en une succession d'images. Ainsi, la méthode introduite dans nos travaux ne repose que sur une méthode simple de segmentation d'images au lieu d'une technique de corrélation d'images numériques. Cet avantage est rendu possible par l'utilisation d'une nouvelle fonction coût basée sur des quantités géométriques. Les performances de la méthode proposée pour des problèmes en dynamique transitoire où le flux d'information peut devenir très important, et où il est intéressant de n'extraire que l'information essentielle. Des exemples numériques basés sur des données synthétiques permettent de mesurer la précision et la robustesse de l'approche introduite

ReLeaSER: A Reinforcement Learning Strategy for Optimizing Utilization Of Ephemeral Cloud Resources

International audienceCloud data center capacities are over-provisioned to handle demand peaks and hardware failures which leads to low resources' utilization. One way to improve resource utilization and thus reduce the total cost of ownership is to offer unused resources (referred to as ephemeral resources) at a lower price. However, reselling resources needs to meet the expectations of its customers in terms of Quality of Service. The goal is so to maximize the amount of reclaimed resources while avoiding SLA penalties. To achieve that, cloud providers have to estimate their future utilization to provide availability guarantees. The prediction should consider a safety margin for resources to react to unpredictable workloads. The challenge is to find the safety margin that provides the best trade-off between the amount of resources to reclaim and the risk of SLA violations. Most state-of-the-art solutions consider a fixed safety margin for all types of metrics (e.g., CPU, RAM). However, a unique fixed margin does not consider various workloads variations over time which may lead to SLA violations or/and poor utilization. In order to tackle these challenges, we propose ReLeaSER, a Reinforcement Learning strategy for optimizing the ephemeral resources' utilization in the cloud. ReLeaSER dynamically tunes the safety margin at the host-level for each resource metric. The strategy learns from past prediction errors (that caused SLA violations). Our solution reduces significantly the SLA violation penalties on average by 2.7x and up to 3.4x. It also improves considerably the CPs' potential savings by 27.6% on average and up to 43.6%