Macroscopic Quantum Tunneling of a Domain Wall in a Ferromagnetic Metal

The macroscopic quantum tunneling of a planar domain wall in a ferromagnetic metal is studied based on the Hubbard model. It is found that the ohmic dissipation is present even at zero temperature due to the gapless Stoner excitation, which is the crucial difference from the case of the insulating magnet. The dissipative effect is calculated as a function of width of the wall and is shown to be effective in a thin wall and in a weak ferromagnet. The results are discussed in the light of recent experiments on ferromagnets with strong anisotropy. PACS numbers:75.60.Ch, 03.65.Sq, 75.10.LpComment: 13page

Macroscopic Quantum Coherence in a Magnetic Nanoparticle Above the Surface of a Superconductor

We study macroscopic quantum tunneling of the magnetic moment in a single-domain particle placed above the surface of a superconductor. Such a setup allows one to manipulate the height of the energy barrier, preserving the degeneracy of the ground state. The tunneling amplitude and the effect of the dissipation in the superconductor are computed.Comment: RevTeX, 4 pages, 1 figure. Submitted to Phys. Rev. Let

Preventing respiratory viral transmission in long-term care: Knowledge, attitudes, and practices of healthcare personnel

OBJECTIVETo examine knowledge and attitudes about influenza vaccination and infection prevention practices among healthcare personnel (HCP) in a long-term-care (LTC) setting.DESIGNKnowledge, attitudes, and practices (KAP) survey.SETTINGAn LTC facility in St Louis, Missouri.PARTICIPANTSAll HCP working at the LTC facility were eligible to participate, regardless of department or position. Of 170 full- and part-time HCP working at the facility, 73 completed the survey, a 42.9% response rate.RESULTSMost HCP agreed that respiratory viral infections were serious and that hand hygiene and face mask use were protective. However, only 46% could describe the correct transmission-based precautions for an influenza patient. Correctly answering infection prevention knowledge questions did not vary by years of experience but did vary for HCP with more direct patient contact versus less patient contact. Furthermore, 42% of respondents reported working while sick, and 56% reported that their coworkers did. In addition, 54% reported that facility policies made staying home while ill difficult. Some respondents expressed concerns about the safety (22%) and effectiveness (27%) of the influenza vaccine, and 28% of respondents stated that they would not get the influenza vaccine if it was not required.CONCLUSIONSThis survey of staff in an LTC facility identified several areas for policy improvement, particularly sick leave, as well as potential targets for interventions to improve infection prevention knowledge and to address HCP concerns about influenza vaccination to improve HCP vaccination rates in LTCs.Infect Control Hosp Epidemiol 2017;38:1449–1456</jats:sec

Predictable arguments of knowledge

We initiate a formal investigation on the power of predictability for argument of knowledge systems for NP. Specifically, we consider private-coin argument systems where the answer of the prover can be predicted, given the private randomness of the verifier; we call such protocols Predictable Arguments of Knowledge (PAoK). Our study encompasses a full characterization of PAoK, showing that such arguments can be made extremely laconic, with the prover sending a single bit, and assumed to have only one round (i.e., two messages) of communication without loss of generality. We additionally explore PAoK satisfying additional properties (including zero-knowledge and the possibility of re-using the same challenge across multiple executions with the prover), present several constructions of PAoK relying on different cryptographic tools, and discuss applications to cryptography

Magnetic Field Dependence of Macroscopic Quantum Tunneling and Coherence of Ferromagnetic Particle

We calculate the quantum tunneling rate of a ferromagnetic particle of $\sim 100 \AA$ diameter in a magnetic field of arbitrary angle. We consider the magnetocrystalline anisotropy with the biaxial symmetry and that with the tetragonal symmetry. Using the spin-coherent-state path integral, we obtain approximate analytic formulas of the tunneling rates in the small $\epsilon (=1- H/H_c)$-limit for the magnetic field normal to the easy axis ($\theta_H = \pi/2$), for the field opposite to the initial easy axis ($\theta_H = \pi$), and for the field at an angle between these two orientations ($\pi/2 << \theta_H << \pi$). In addition, we obtain numerically the tunneling rates for the biaxial symmetry in the full range of the angle $\theta_H$ of the magnetic field ($\pi/2 < \theta_H \leq \pi$), for the values of \epsilon =0.01 and 0.001.Comment: 25 pages of text (RevTex) and 4 figures (PostScript files), to be published in Phys. Rev.

Stereo Computation for a Single Mixture Image

This paper proposes an original problem of \emph{stereo computation from a single mixture image}-- a challenging problem that had not been researched before. The goal is to separate (\ie, unmix) a single mixture image into two constitute image layers, such that the two layers form a left-right stereo image pair, from which a valid disparity map can be recovered. This is a severely illposed problem, from one input image one effectively aims to recover three (\ie, left image, right image and a disparity map). In this work we give a novel deep-learning based solution, by jointly solving the two subtasks of image layer separation as well as stereo matching. Training our deep net is a simple task, as it does not need to have disparity maps. Extensive experiments demonstrate the efficacy of our method.Comment: Accepted by European Conference on Computer Vision (ECCV) 201

Tunneling of a large spin via hyperfine interactions

We consider a large spin \bf S in the magnetic field parallel to the uniaxial crystal field, interacting with N >> 1 nuclear spins \bf I_i via Hamiltonian \cal H = -DS_z^2 - H_zS_z+ A{\bf S}\cdot \sum_{i=1}^N {\bf I}_i with A << D, at temperature T. Tunneling splittings and the selection rules for the resonant values of H_z are obtained perturbatively. The quantum coherence exists at T << ASI while at T >= ASI the coherence is destroyed and the relaxation of \bf S is described by a stretched dependence which can be close to log t under certain conditions. Relevance to Mn-12 acetate is discussed.Comment: 5 PR pages, 4 figures, submitted to PR

Macroscopic Quantum Tunneling and Dissipation of Domain Wall in Ferromagnetic Metals

The depinning of a domain wall in ferromagentic metal via macroscopic quantum tunneling is studied based on the Hubbard model. The dynamics of the magnetization verctor is shown to be governed by an effective action of Heisenberg model with a term non-local in time that describes the dissipation due to the conduction electron. Due to the existence of the Fermi surface there exists Ohmic dissipation even at zero temperature, which is crucially different from the case of the insulator. Taking into account the effect of pinning and the external magnetic field the action is rewritten in terms of a collective coordinate, the position of the wall, $Q$. The tunneling rate for $Q$ is calculated by use of the instanton method. It is found that the reduction of the tunneling rate due to the dissipation is very large for a thin domain wall with thickness of a few times the lattice spacing, but is negligible for a thick domain wall. Dissipation due to eddy current is shown to be negligible for a wall of mesoscopic size.Comment: of pages 26, to appear in "Quantum Tunneling of Magnetization, ed. B. Barbara and L. Gunther (Kluwer Academic Pub.), Figures available by FAX (81-48-462-4649

NcPred for accurate nuclear protein prediction using n-mer statistics with various classification algorithms

Prediction of nuclear proteins is one of the major challenges in genome annotation. A method, NcPred is described, for predicting nuclear proteins with higher accuracy exploiting n-mer statistics with different classification algorithms namely Alternating Decision (AD) Tree, Best First (BF) Tree, Random Tree and Adaptive (Ada) Boost. On BaCello dataset [1], NcPred improves about 20% accuracy with Random Tree and about 10% sensitivity with Ada Boost for Animal proteins compared to existing techniques. It also increases the accuracy of Fungal protein prediction by 20% and recall by 4% with AD Tree. In case of Human protein, the accuracy is improved by about 25% and sensitivity about 10% with BF Tree. Performance analysis of NcPred clearly demonstrates its suitability over the contemporary in-silico nuclear protein classification research

Non-Markoffian effects of a simple nonlinear bath

We analyze a model of a nonlinear bath consisting of a single two-level system coupled to a linear bath (a classical noise force in the limit considered here). This allows us to study the effects of a nonlinear, non-Markoffian bath in a particularly simple situation. We analyze the effects of this bath onto the dynamics of a spin by calculating the decay of the equilibrium correlator of the spin's z-component. The exact results are compared with those obtained using three commonly used approximations: a Markoffian master equation for the spin dynamics, a weak-coupling approximation, and the substitution of a linear bath for the original nonlinear bath.Comment: 7 pages, 6 figure