Numerical investigation of plasma-controlled turbulent jets for mixing enhancement

Plasma-controlled turbulent jets are investigated by means of Implicit Large–Eddy Simulations at a Reynolds number equal to 460,000 (based on the diameter of the jet and the centreline velocity at the nozzle exit). Eight Dielectric Barrier Discharge (DBD) plasma actuators located just before the nozzle exit are used as an active control device with the aim to enhance the mixing of the jet. Four control configurations are presented in this numerical study as well as a reference case with no control and a tripping case where a random forcing is used to destabilize the nozzle boundary layer. Visualisations of the different cases and time-averaged statistics for the different controlled cases are showing strong modifications of the vortex structures downstream of the nozzle exit, with a substantial reduction of the potential core, an increase of the jet radial expansion and an improvement of the mixing properties of the flow

Kinetic energy functional for Fermi vapors in spherical harmonic confinement

Two equations are constructed which reflect, for fermions moving independently in a spherical harmonic potential, a differential virial theorem and a relation between the turning points of kinetic energy and particle densities. These equations are used to derive a differential equation for the particle density and a non-local kinetic energy functional.Comment: 8 pages, 2 figure

IgG anti-apolipoprotein A-1 antibodies in patients with systemic lupus erythematosus are associated with disease activity and corticosteroid therapy: an observational study.

IgG anti-apolipoprotein A-1 (IgG anti-apoA-1) antibodies are present in patients with systemic lupus erythematosus (SLE) and may link inflammatory disease activity and the increased risk of developing atherosclerosis and cardiovascular disease (CVD) in these patients. We carried out a rigorous analysis of the associations between IgG anti-apoA-1 levels and disease activity, drug therapy, serology, damage, mortality and CVD events in a large British SLE cohort

Quantum Separability and Entanglement Detection via Entanglement-Witness Search and Global Optimization

We focus on determining the separability of an unknown bipartite quantum state $\rho$ by invoking a sufficiently large subset of all possible entanglement witnesses given the expected value of each element of a set of mutually orthogonal observables. We review the concept of an entanglement witness from the geometrical point of view and use this geometry to show that the set of separable states is not a polytope and to characterize the class of entanglement witnesses (observables) that detect entangled states on opposite sides of the set of separable states. All this serves to motivate a classical algorithm which, given the expected values of a subset of an orthogonal basis of observables of an otherwise unknown quantum state, searches for an entanglement witness in the span of the subset of observables. The idea of such an algorithm, which is an efficient reduction of the quantum separability problem to a global optimization problem, was introduced in PRA 70 060303(R), where it was shown to be an improvement on the naive approach for the quantum separability problem (exhaustive search for a decomposition of the given state into a convex combination of separable states). The last section of the paper discusses in more generality such algorithms, which, in our case, assume a subroutine that computes the global maximum of a real function of several variables. Despite this, we anticipate that such algorithms will perform sufficiently well on small instances that they will render a feasible test for separability in some cases of interest (e.g. in 3-by-3 dimensional systems)

Comparative assessment of young learners' foreign language competence in three Eastern European countries

This paper concerns teacher practices in, and beliefs about, the assessment of young learners' progress in English in three Eastern European countries (Slovenia, Croatia, and the Czech Republic). The central part of the paper focuses on an international project involving empirical research into assessment of young learners' foreign language competence in Slovenia, Croatia and the Czech Republic. With the help of an adapted questionnaire, we collected data from a non-random sample of primary and foreign language teachers who teach foreign languages at the primary level in these countries. The research shows that English as a foreign language is taught mostly by young teachers either primary specialists or foreign language teachers. These teachers most frequently use oral assessment/interviews or self-developed tests. Other more authentic types of assessment, such as language portfolios, are rarely used. The teachers most frequently assess speaking and listening skills, and they use assessment involving vocabulary the most frequently of all. However, there are significant differences in practice among the three countries

Improved algorithm for quantum separability and entanglement detection

Determining whether a quantum state is separable or entangled is a problem of fundamental importance in quantum information science. It has recently been shown that this problem is NP-hard. There is a highly inefficient `basic algorithm' for solving the quantum separability problem which follows from the definition of a separable state. By exploiting specific properties of the set of separable states, we introduce a new classical algorithm that solves the problem significantly faster than the `basic algorithm', allowing a feasible separability test where none previously existed e.g. in 3-by-3-dimensional systems. Our algorithm also provides a novel tool in the experimental detection of entanglement.Comment: 4 pages, revtex4, no figure

Refining Architectures of Deep Convolutional Neural Networks

© 2016 IEEE. Deep Convolutional Neural Networks (CNNs) have recently evinced immense success for various image recognition tasks [11, 27]. However, a question of paramount importance is somewhat unanswered in deep learning research - is the selected CNN optimal for the dataset in terms of accuracy and model size? In this paper, we intend to answer this question and introduce a novel strategy that alters the architecture of a given CNN for a specified dataset, to potentially enhance the original accuracy while possibly reducing the model size. We use two operations for architecture refinement, viz. stretching and symmetrical splitting. Stretching increases the number of hidden units (nodes) in a given CNN layer, while a symmetrical split of say K between two layers separates the input and output channels into K equal groups, and connects only the corresponding input-output channel groups. Our procedure starts with a pre-trained CNN for a given dataset, and optimally decides the stretch and split factors across the network to refine the architecture. We empirically demonstrate the necessity of the two operations. We evaluate our approach on two natural scenes attributes datasets, SUN Attributes [16] and CAMIT-NSAD [20], with architectures of GoogleNet and VGG-11, that are quite contrasting in their construction. We justify our choice of datasets, and show that they are interestingly distinct from each other, and together pose a challenge to our architectural refinement algorithm. Our results substantiate the usefulness of the proposed method

Inventory of alien marine species of Cyprus (2009)

An updated inventory of alien marine species from coastal and offshore waters of Cyprus is presented. Records were compiled based on the existing scientific and grey literature, including HCMR database of Mediterranean alien species, technical reports, scientific congresses, academic dissertations, and websites, as well as on unpublished/personal observations. The listed species were classified in one of five categories: established, invasive, casual, cryptogenic, and questionable. The mode of introduction and the year of first sighting were also reported for each species. Eight new records based on personal observations of the authors were reported (Chondria coerulescens, Neosiphonia sphaerocarpa, Enchelycore anatina, Lagocephalus spadiceus, Lagocephalus suezensis, Scomberomorus commerson, Sillago sihama, and Sphoeroides pachygaster). Nine species, previously reported as aliens in Cypriot waters, were excluded from the inventory for various reasons. Ten established species were characterized as invasive (Caulerpa racemosa var. cylindracea, Cerithium scabridum, Strombus persicus, Trochus erythraeus, Brachidontes pharaonis, Pinctada radiata, Fistularia commersonii, Lagocephalus sceleratus, Siganus luridus, and Siganus rivulatus) as they have a substantial impact on biodiversity and/or local economy. The impact of alien marine species in Cyprus is expected to grow in the close future, and further effort directed towards recording alien invasions and their impact will be needed