Influence of niobium solutes on the mechanical behavior of nickel during hot working

International audienceAn experimental program was performed to determine the rheology and influence of niobium additions to high-purity nickel on dynamic-recrystallization behavior during hot working. Various high-purity alloys were prepared (pure Ni and Ni-0.01, 0.1, 1, 2, 5 and 10 wt% Nb) and deformed to high strains by hot torsion to characterize the mechanical behavior within the temperature range from 800 to 1000 degrees C at (von Mises equivalent) strain rates of 0.03, 0.1 and 03 s(-1). A simple analytical method was proposed for predicting the strain-hardening and dynamic-recovery parameters in the classical Yoshie-Laasraoui-Jonas equation. By the means, the effect of niobium solutes on plastic flow was determined, thus enabling a reasonable fit for the flow curves for the entire range of solid solution Ni-Nb alloys. (C) 2013 Elsevier B.V. All rights reserved

Synergistic interactions between antimicrobial peptides derived from plectasin and lipid nanocapsules containing monolaurin as a cosurfactant against Staphylococcus aureus

Anita Umerska,1 Viviane Cassisa,2 Guillaume Bastiat,1 Nada Matougui,1 Hassan Nehme,1 Florence Manero,3 Matthieu Eveillard,4 Patrick Saulnier1 1MINT, UNIV Angers, INSERM 1066, CNRS 6021, Université Bretagne Loire, Angers, Cedex, France; 2Laboratoire de bactériologie, CHU Angers, France; 3SCIAM (Service Commun d’Imagerie et d’Analyses Microscopiques), Angers, France; 4Equipe ATIP AVENIR, CRCINA, Inserm, Université de Nantes, Université d’Angers, Angers, France Abstract: Development of effective antibacterial agents for the treatment of infections caused by Gram-positive bacteria resistant to existing antibiotics, such as methicillin-resistant Staphylococcus aureus (MRSA), is an area of intensive research. In this work, the antibacterial efficacy of two antimicrobial peptides derived from plectasin, AP114 and AP138, used alone and in combination with monolaurin-lipid nanocapsules (ML-LNCs) was evaluated. Several interesting findings emerged from the present study. First, ML-LNCs and both plectasin derivatives showed potent activity against all 14 tested strains of S. aureus, independent of their resistance phenotype. Both peptides displayed a considerable adsorption (33%–62%) onto ML-LNCs without having an important impact on the particle properties such as size. The combinations of peptide with ML-LNC displayed synergistic effect against S. aureus, as confirmed by two methods: checkerboard and time-kill assays. This synergistic interaction enables a dose reduction and consequently decreases the risk of toxicity and has the potential of minimizing the development of resistance. Together, these results suggest that ML-LNCs loaded with a plectasin derivative may be a very promising drug delivery system for further development as a novel antibacterial agent against S. aureus, including MRSA. Keywords: nanoparticles, antimicrobial peptides, glycerol monolaurate, synergy, antibiotic resistance, MRSA, methicillin-resistant Staphylococcus aureu

A Formal Method for Modeling Deployment Architectures Based on Bigraphs

International audienceSoftware deployment is executed according a deployment architecture which describes the allocation of software components to its hardware hosts. In this paper, we tackle the issue of constructing correct deployment architectures for large distributed systems. Actually, such architectures should satisfy various constraints related to the software components and the target environment such as the hierarchical description of components , their connections and the resource constraints. We present a formal method for constructing deployment architectures using a formal language called BRS (Bigraphical Reactive System). This method provides a correct by design approach based on multi-scale modeling ensuring the correctness of the obtained deployment architectures. Following our approach, the designer starts by modeling the first scale architecture which is refined automatically by successively adding smaller scale components until obtaining the last scale deployment architecture