High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition

This paper presents a novel adaptive-sparse polynomial dimensional decomposition (PDD) method for stochastic design optimization of complex systems. The method entails an adaptive-sparse PDD approximation of a high-dimensional stochastic response for statistical moment and reliability analyses; a novel integration of the adaptive-sparse PDD approximation and score functions for estimating the first-order design sensitivities of the statistical moments and failure probability; and standard gradient-based optimization algorithms. New analytical formulae are presented for the design sensitivities that are simultaneously determined along with the moments or the failure probability. Numerical results stemming from mathematical functions indicate that the new method provides more computationally efficient design solutions than the existing methods. Finally, stochastic shape optimization of a jet engine bracket with 79 variables was performed, demonstrating the power of the new method to tackle practical engineering problems.Comment: 18 pages, 2 figures, to appear in Sparse Grids and Applications--Stuttgart 2014, Lecture Notes in Computational Science and Engineering 109, edited by J. Garcke and D. Pfl\"{u}ger, Springer International Publishing, 201

Anisotropic Superconductivity in the Induced Pairing Model

The model of local electron pairs and itinerant fermions coupled via charge exchange mechanism, which mutually induces superconductivity in both subsystems is studied for anisotropic pairing symmetry. The phase diagram is presented and the phase fluctuations effects are analyzed within the Kosterlitz-Thouless scenario.Comment: 4 pages, 2 figures. Physica B (in press), Proceedings of the International Conference on Strongly Correlated Electron Systems, Ann Arbor, Michigan, August 6-10, 200

The {\alpha}-Decay Chains of the 287,288115^{287, 288}115 Isotopes using Relativistic Mean Field Theory

We study the binding energy, root-mean-square radius and quadrupole deformation parameter for the synthesized superheavy element Z = 115, within the formalism of relativistic mean field theory. The calculation is dones for various isotopes of Z = 115 element, starting from A = 272 to A = 292. A systematic comparison between the binding energies and experimental data is made.The calculated binding energies are in good agreement with experimental result. The results show the prolate deformation for the ground state of these nuclei. The most stable isotope is found to be 282115 nucleus (N = 167) in the isotopic chain. We have also studied Q{\alpha} and T{\alpha} for the {\alpha}-decay chains of $^{287, 288}$115.Comment: 12 Pages 6 Figures 3 Table

Entropy Driven Dimerization in a One-Dimensional Spin-Orbital Model

We study a new version of the one-dimensional spin-orbital model with spins S=1 relevant to cubic vanadates. At small Hund's coupling J_H we discover dimerization in a pure electronic system solely due to a dynamical spin-orbital coupling. Above a critical value J_H, a uniform ferromagnetic state is stabilized at zero temperature. More surprisingly, we observe a temperature driven dimerization of the ferrochain, which occurs due to a large entropy released by dimer states. This dynamical dimerization seems to be the mechanism driving the peculiar intermediate phase of YVO_3.Comment: 5 pages, 4 figure

UOLO - automatic object detection and segmentation in biomedical images

We propose UOLO, a novel framework for the simultaneous detection and segmentation of structures of interest in medical images. UOLO consists of an object segmentation module which intermediate abstract representations are processed and used as input for object detection. The resulting system is optimized simultaneously for detecting a class of objects and segmenting an optionally different class of structures. UOLO is trained on a set of bounding boxes enclosing the objects to detect, as well as pixel-wise segmentation information, when available. A new loss function is devised, taking into account whether a reference segmentation is accessible for each training image, in order to suitably backpropagate the error. We validate UOLO on the task of simultaneous optic disc (OD) detection, fovea detection, and OD segmentation from retinal images, achieving state-of-the-art performance on public datasets.Comment: Publised on DLMIA 2018. Licensed under the Creative Commons CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0

Neutrino spin oscillations in gravitational fields

We study neutrino spin oscillations in black hole backgrounds. In the case of a charged black hole, the maximum frequency of oscillations is a monotonically increasing function of the charge. For a rotating black hole, the maximum frequency decreases with increasing the angular momentum. In both cases, the frequency of spin oscillations decreases as the distance from the black hole grows. As a phenomenological application of our results, we study simple bipolar neutrino system which is an interesting example of collective neutrino oscillations. We show that the precession frequency of the flavor pendulum as a function of the neutrino number density will be higher for a charged/non-rotating black hole compared with a neutral/rotating black hole respectively.Comment: Replaced with the version accepted for publication in Gravitation and Cosmology, Springer. 10 pages. 4 figure