Spatially resolved spectroscopy of alkali metal vapour diffusing inside hollow-core photonic crystal fibres

We present a new type of compact and all-glass based vapour cell integrating hollow-core photonic crystal fibres. The absence of metals, as in a traditional vacuum chamber and the much more compact geometry allows for fast and homogeneous heating. As a consequence we can fill the fibres on much faster timescales, ranging from minutes to hours. Additionally the all-glass design ensures optical access along the fibre. This allows live monitoring of the diffusion of rubidium atoms inside the hollow-core by measuring the frequency-dependent fluorescence from the atoms. The atomic density is numerically retrieved using a 5-level system of Bloch-equations.Comment: 9 pages, 5 figure

Semiclassical Asymptotics for the Maxwell - Dirac System

We study the coupled system of Maxwell and Dirac equations from a semiclassical point of view. A rigorous nonlinear WKB-analysis, locally in time, for solutions of (critical) order $O(\sqrt{\epsilon})$ is performed, where the small semiclassical parameter $\epsilon$ denotes the microscopic/macroscopic scale ratio

Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks

Several fundamental problems in science and engineering consist of global optimization tasks involving unknown high-dimensional (black-box) functions that map a set of controllable variables to the outcomes of an expensive experiment. Bayesian Optimization (BO) techniques are known to be effective in tackling global optimization problems using a relatively small number objective function evaluations, but their performance suffers when dealing with high-dimensional outputs. To overcome the major challenge of dimensionality, here we propose a deep learning framework for BO and sequential decision making based on bootstrapped ensembles of neural architectures with randomized priors. Using appropriate architecture choices, we show that the proposed framework can approximate functional relationships between design variables and quantities of interest, even in cases where the latter take values in high-dimensional vector spaces or even infinite-dimensional function spaces. In the context of BO, we augmented the proposed probabilistic surrogates with re-parameterized Monte Carlo approximations of multiple-point (parallel) acquisition functions, as well as methodological extensions for accommodating black-box constraints and multi-fidelity information sources. We test the proposed framework against state-of-the-art methods for BO and demonstrate superior performance across several challenging tasks with high-dimensional outputs, including a constrained optimization task involving shape optimization of rotor blades in turbo-machinery.Comment: 18 pages, 8 figure

Physiological and morphological responses to water deficit in seedling progeny of four populations of Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco)

The relationships among total water potential (psi), osmotic potential ([pi]), pressure potential (P), and relative water content (R*) were determined during four consecutive soil drying cycles for shoots of Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) seedlings. In each cycle, seedlings were sampled for pressure-volume determinations as soil water was depleted gradually from saturation to pre-dawn plant [psi] of 0.8-1.0 MPa (after 7-9 d) and 2.O-2.4 MPa (after an additional 4-6 d); tissue responses were compared against that of frequently irrigated controls. In non-stressed seedlings, [pi], the relative water content of the apoplasm (R*a), and the weight of symplasm water each exhibit significant decline during the period from 2 June to 16 September; the relative water content at the turgor loss point and the volumetric elastic modulus (e) each exhibit significant increases during this period. The osmotic potential at full turgor of irrigated seedlings was not different from that of non-irrigated seedlings in any of the four drying cycles. However, increases in R*a, and decreases in e are induced in shoots of stressed plants relative to unstressed plants in each of soil drying cycles 2, 3, and 4. Both variables are sensitive to water deficit but return to seasonal baseline values during periods of stress relaxation. Diurnal changes in [psi], [pi], P, R*a, and [epsilon] were measured on two days in both irrigated and non-irrigated seedlings. Osmotic adjustment plays a small, though significant, role in diurnal turgor regulation of non-stressed seedlings; release of water from cell walls and increases in wall elasticity are more important features of turgor regulation. In stressed seedlings, osmotic adjustment and changes in R*a act to maintain positive P in shoot tissue. Phenological and morphological responses to water deficit were compared in progeny of 5-7 trees from each of four populations. Highly significant differences were observed among populations for each of 19 traits. Further, a significant fraction of total variability for each trait was attributable to differences among families within populations. The irrigation X population interaction was non-significant for all traits with the exception of seedling height, average rate of growth, and leaf area : sapwood area ratio. Populations and families within populations each exhibit significant interaction with irrigation in multivariate analyses of variance. A canonical discriminant analysis shows distinct separation of groups when the classification variable is based on the region of origin and level of irrigation and when the quantitative variables include six measures of seedling morphology. Coefficients of the allometric formulae of seedling progeny of both coastal and southwestern Oregon populations are significantly altered by the level of soil moisture

Effect of moderate and high light on photosystem II function in Arabidopsis thaliana depleted in digalactosyl-diacylglycerol

AbstractThe response of the heat-sensitive dgd1-2 and dgd1-3 Arabidopsis mutants depleted in the galactolipid DGDG to photoinhibition of chloroplasts photosystem II was studied to verify if there is a relationship between heat stress vulnerability due to depletion in DGDG and the susceptibility to photoinhibitory damage. Non-photochemical quenching (NPQ) is known to dissipate excessive absorbed light energy as heat to protect plants against photodamage. The main component of NPQ is dependent of the transthylakoid pH gradient and is modulated by zeaxanthin (Zx) synthesis. These processes together with chlorophyll fluorescence induction were used to characterize the response of the genotypes. The mutants were more sensitive to photoinhibition to a small extent but this was more severe for dgd1-3 especially at high light intensity. It was deduced that DGDG was not a main factor to influence photoinhibition but other lipid components could affect PSII sensitivity towards photoinhibition in relation to the physical properties of the thylakoid membrane. This article is part of a Special Issue entitled: Photosynthesis Research for Sustainability: from Natural to Artificial

API design for machine learning software: experiences from the scikit-learn project

Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this paper, we present and discuss our design choices for the application programming interface (API) of the project. In particular, we describe the simple and elegant interface shared by all learning and processing units in the library and then discuss its advantages in terms of composition and reusability. The paper also comments on implementation details specific to the Python ecosystem and analyzes obstacles faced by users and developers of the library

Entreprises et pouvoir économique dans la région Rhône-Alpes (1920-1954)

Ce livre est l'aboutissement d'une longue recherche menée au Centre Pierre Léon par les auteurs à partir d'un financement obtenu en 1997 de l'Agence Rhône-Alpes pour les sciences sociales et humaines (ARASSH). Il constitue une tentative inédite, à l'échelle d'une grande région française, de procéder à une étude exhaustive, pour la première moitié du XXe siècle, des modalités de contrôle de l'ensemble des moyennes et grandes entreprises. À partir du recensement d'un millier d'établissements industriels et commerciaux de plus de 100 salariés, une exploitation systématique du premier registre du commerce (1920-1954) a permis de repérer les éventuels liens économiques et personnels qui les unissent. Au-delà de la simple concentration technique à l'échelle des établissements, quel est, à l'échelle des entreprises et des groupes, le véritable degré de concentration économique dans la région ? En comparaison avec le capitalisme très internationalisé d'aujourd'hui, dans quelle mesure le contrôle des entreprises reste-il plutôt local à l'époque ? Au contraire, les prémices d'une ouverture extérieure apparaissent-elles déjà ? Quelles sont les entreprises qui résistent le mieux aux crises traversées au cours de la période étudiée ? Autant de questions qui peuvent apporter un éclairage historique intéressant aux débats actuels sur les conséquences de la mondialisation pour l'économie d'un territoire régional

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Predicting glucocorticoid resistance in multiple sclerosis relapse via a whole blood transcriptomic analysis.

AIMS Treatment of multiple sclerosis (MS) relapses consists of short-term administration of high-dose glucocorticoids (GCs). However, over 40% of patients show an insufficient response to GC treatment. We aimed to develop a predictive model for such GC resistance. METHODS We performed a receiver operating characteristic (ROC) curve analysis following the transcriptomic assay of whole blood samples from stable, relapsing GC-sensitive and relapsing GC-resistant patients with MS in two different European centers. RESULTS We identified 12 genes being regulated during a relapse and differentially expressed between GC-sensitive and GC-resistant patients with MS. Using these genes, we defined a statistical model to predict GC resistance with an area under the curve (AUC) of the ROC analysis of 0.913. Furthermore, we observed that relapsing GC-resistant patients with MS have decreased GR, DUSP1, and TSC22D3 mRNA levels compared with relapsing GC-sensitive patients with MS. Finally, we showed that the transcriptome of relapsing GC-resistant patients with MS resembles those of stable patients with MS. CONCLUSION Predicting GC resistance would allow patients to benefit from prompt initiation of an alternative relapse treatment leading to increased treatment efficacy. Thus, we think our model could contribute to reducing disability development in people with MS

LifeCLEF Bird Identification Task 2016: The arrival of Deep learning

International audienceThe LifeCLEF bird identification challenge provides a large-scale testbed for the system-oriented evaluation of bird species identification based on audio recordings. One of its main strength is that the data used for the evaluation is collected through Xeno-Canto, the largest network of bird sound recordists in the world. This makes the task closer to the conditions of a real-world application than previous, similar initiatives. The main novelty of the 2016-th edition of the challenge was the inclusion of soundscape recordings in addition to the usual xeno-canto recordings that focus on a single foreground species. This paper reports the methodology of the conducted evaluation, the overview of the systems experimented by the 6 participating research groups and a synthetic analysis of the obtained results