2,714 research outputs found

    Post-shutdown temperature of a buried reactor system for a lunar based power plant

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    Post-shutdown temperature of lithium cooled fast reactor assumed to be buried beneath lunar surfac

    A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

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    The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from undersampled data using a deep cascade of convolutional neural networks to accelerate the data acquisition process. We show that for Cartesian undersampling of 2D cardiac MR images, the proposed method outperforms the state-of-the-art compressed sensing approaches, such as dictionary learning-based MRI (DLMRI) reconstruction, in terms of reconstruction error, perceptual quality and reconstruction speed for both 3-fold and 6-fold undersampling. Compared to DLMRI, the error produced by the method proposed is approximately twice as small, allowing to preserve anatomical structures more faithfully. Using our method, each image can be reconstructed in 23 ms, which is fast enough to enable real-time applications

    IntroducciĂłn

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    El Tratado de Libre Comercio de América del Norte (TLC) tiene como objetivo reducir, y en última instancia eliminar, la mayoría de las barreras al comercio y a la inversión entre Canadá, México y Estados Unidos. Aunque se puede interpretar como la continuación de una tendencia anterior hacia una mayor integración económica entre estos tres países, el TLC simboliza un cambio de mayor envergadura, particularmente en las relaciones económicas entre México y Estados Unidos.

    Nuclear Magnetic Resonance and Hyperfine Structure

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    Contains reports on four research projects

    How well-proportioned are lens and prism spaces?

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    The CMB anisotropies in spherical 3-spaces with a non-trivial topology are analysed with a focus on lens and prism shaped fundamental cells. The conjecture is tested that well proportioned spaces lead to a suppression of large-scale anisotropies according to the observed cosmic microwave background (CMB). The focus is put on lens spaces L(p,q) which are supposed to be oddly proportioned. However, there are inhomogeneous lens spaces whose shape of the Voronoi domain depends on the position of the observer within the manifold. Such manifolds possess no fixed measure of well-proportioned and allow a predestined test of the well-proportioned conjecture. Topologies having the same Voronoi domain are shown to possess distinct CMB statistics which thus provide a counter-example to the well-proportioned conjecture. The CMB properties are analysed in terms of cyclic subgroups Z_p, and new point of view for the superior behaviour of the Poincar\'e dodecahedron is found

    Cosmic Topology of Polyhedral Double-Action Manifolds

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    A special class of non-trivial topologies of the spherical space S^3 is investigated with respect to their cosmic microwave background (CMB) anisotropies. The observed correlations of the anisotropies on the CMB sky possess on large separation angles surprising low amplitudes which might be naturally be explained by models of the Universe having a multiconnected spatial space. We analysed in CQG 29(2012)215005 the CMB properties of prism double-action manifolds that are generated by a binary dihedral group D^*_p and a cyclic group Z_n up to a group order of 180. Here we extend the CMB analysis to polyhedral double-action manifolds which are generated by the three binary polyhedral groups (T^*, O^*, I^*) and a cyclic group Z_n up to a group order of 1000. There are 20 such polyhedral double-action manifolds. Some of them turn out to have even lower CMB correlations on large angles than the Poincare dodecahedron
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