Nuclear Magnetic Resonance in High Magnetic Field: Application to Condensed Matter Physics

In this review, we describe the potentialities offered by the nuclear magnetic resonance (NMR) technique to explore at a microscopic level new quantum states of condensed matter induced by high magnetic fields. We focus on experiments realised in resistive (up to 34~T) or hybrid (up to 45~T) magnets, which open a large access to these quantum phase transitions. After an introduction on NMR observable, we consider several topics: quantum spin systems (spin-Peierls transition, spin ladders, spin nematic phases, magnetisation plateaus and Bose-Einstein condensation of triplet excitations), the field-induced charge density wave (CDW) in high $T_c$~superconductors, and exotic superconductivity including the Fulde-Ferrel-Larkin-Ovchinnikov superconducting state and the field-induced superconductivity due to the Jaccarino-Peter mechanism.Comment: 19 pages, 6 figure

New taxa and new records of Oemini Lacordaire, 1868 and Ectenessini Martins, 1998 from French Guiana (Coleoptera, Cerambycidae, Cerambycinae)

Four new species and one new genus of Cerambycinae are described from French Guiana: Sphagoeme premarginata sp. nov. and Atenizus apicalis sp. nov. (Oemini); Paraniophis signatipes gen. nov., sp. nov., and Niophis brusteli sp. nov. (Ectenessini). Three new country records for French Guiana are provided: Sphagoeme paraensis Martins, 1977, Atenizus simplex Bates, 1884, and Macroeme vittipennis (Melzer, 1934). All taxa are illustrated

A new Pseudosparna Mermudes & Monné, 2009 from Mitaraka mountains, French Guiana (Coleoptera, Cerambycidae)

Pseudosparna ubirajara sp. nov. is described from southern French Guiana and illustrated. It is compared with other Pseudosparna and the key to species is updated

New taxa and new records of Oemini Lacordaire, 1868 and Ectenessini Martins, 1998 from French Guiana (Coleoptera, Cerambycidae, Cerambycinae)

Four new species and one new genus of Cerambycinae are described from French Guiana: Sphagoeme premarginata sp. nov. and Atenizus apicalis sp. nov. (Oemini); Paraniophis signatipes gen. nov., sp. nov., and Niophis brusteli sp. nov. (Ectenessini). Three new country records for French Guiana are provided: Sphagoeme paraensis Martins, 1977, Atenizus simplex Bates, 1884, and Macroeme vittipennis (Melzer, 1934). All taxa are illustrated

A maximum entropy principle explains quasi-stationary states in systems with long-range interactions: the example of the Hamiltonian Mean Field model

A generic feature of systems with long-range interactions is the presence of {\it quasi-stationary} states with non-Gaussian single particle velocity distributions. For the case of the Hamiltonian Mean Field (HMF) model, we demonstrate that a maximum entropy principle applied to the associated Vlasov equation explains known features of such states for a wide range of initial conditions. We are able to reproduce velocity distribution functions with an analytical expression which is derived from the theory with no adjustable parameters. A normal diffusion of angles is detected and a new dynamical effect, two oscillating clusters surrounded by a halo, is also found and theoretically justified.Comment: 4 pages, 3 figs, submitted to Phys. Rev. Let

Computing the expected makespan of task graphs in the presence of silent errors

International audienceApplications structured as Directed Acyclic Graphs (DAGs) of tasks correspond to a general model of parallel computation that occurs in many domains, including popular scientific workflows. DAG scheduling has received an enormous amount of attention, and several list-scheduling heuristics have been proposed and shown to be effective in practice. Many of these heuristics make scheduling decisions based on path lengths in the DAG. At large scale, however, compute platforms and thus tasks are subject to various types of failures with no longer negligible probabilities of occurrence. Failures that have recently received increasing attention are " silent errors, " which cause a task to produce incorrect results even though it ran to completion. Tolerating silent errors is done by checking the validity of the results and re-executing the task from scratch in case of an invalid result. The execution time of a task then becomes a random variable, and so are path lengths. Unfortunately, computing the expected makespan of a DAG (and equivalently computing expected path lengths in a DAG) is a computationally difficult problem. Consequently, designing effective scheduling heuristics is preconditioned on computing accurate approximations of the expected makespan. In this work we propose an algorithm that computes a first order approximation of the expected makespan of a DAG when tasks are subject to silent errors. We compare our proposed approximation to previously proposed such approximations for three classes of application graphs from the field of numerical linear algebra. Our evaluations quantify approximation error with respect to a ground truth computed via a brute-force Monte Carlo method. We find that our proposed approximation outperforms previously proposed approaches, leading to large reductions in approximation error for low (and realistic) failure rates, while executing much faster

Differential ultrafast all-optical switching of the resonances of a micropillar cavity

We perform frequency- and time-resolved all-optical switching of a GaAs-AlAs micropillar cavity using an ultrafast pump-probe setup. The switching is achieved by two-photon excitation of free carriers. We track the cavity resonances in time with a high frequency resolution. The pillar modes exhibit simultaneous frequency shifts, albeit with markedly different maximum switching amplitudes and relaxation dynamics. These differences stem from the non-uniformity of the free carrier density in the micropillar, and are well understood by taking into account the spatial distribution of injected free carriers, their spatial diffusion and surface recombination at micropillar sidewalls.Comment: 4 pages, 3 figure

In vitro screening of probiotic lactic acid bacteria and prebiotic glucooligosaccharides to select effective synbiotics

Probiotics and prebiotics have been demonstrated to positively modulate the intestinal microflora and could promote host health. Although some studies have been performed on combinations of probiotics and prebiotics, constituting synbiotics, results on the synergistic effects tend to be discordant in the published works. The first aim of our study was to screen some lactic acid bacteria on the basis of probiotic characteristics (resistance to intestinal conditions, inhibition of pathogenic strains). Bifidobacterium was the most resistant genus whereas Lactobacillus farciminis was strongly inhibited. The inhibitory effect on pathogen growth was strain dependent but lactobacilli were the most effective, especially L. farciminis. The second aim of the work was to select glucooligosaccharides for their ability to support the growth of the probiotics tested. We demonstrated the selective fermentability of oligodextran and oligoalternan by probiotic bacteria, especially the bifidobacteria, for shorter degrees of polymerisation and absence of metabolism by pathogenic bacteria. Thus, the observed characteristics confer potential prebiotic properties on these glucooligosaccharides, to be further confirmed in vivo, and suggest some possible applications in synbiotic combinations with the selected probiotics. Furthermore, the distinctive patterns of the different genera suggest a combination of lactobacilli and bifidobacteria with complementary probiotic effects in addition to the prebiotic ones. These associations should be further evaluated for their synbiotic effects through in vitro and in vivo models

Interactive visual exploration of association rules with rule-focusing methodology

International audienceOn account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a difficult stage in an association rule discovery process. In order to find relevant knowledge for decision making, the user (a decision maker specialized in the data studied) needs to rummage through the rules. To assist him/her in this task, we here propose the rule-focusing methodology, an interactive methodology for the visual post-processing of association rules. It allows the user to explore large sets of rules freely by focusing his/her attention on limited subsets. This new approach relies on rule interestingness measures, on a visual representation, and on interactive navigation among the rules. We have implemented the rule-focusing methodology in a prototype system called ARVis. It exploits the user's focus to guide the generation of the rules by means of a specific constraint-based rule-mining algorithm