Spin torque ferromagnetic resonance with magnetic field modulation

We demonstrate a technique of broadband spin torque ferromagnetic resonance (ST-FMR) with magnetic field modulation for measurements of spin wave properties in magnetic nanostructures. This technique gives great improvement in sensitivity over the conventional ST-FMR measurements, and application of this technique to nanoscale magnetic tunnel junctions (MTJs) reveals a rich spectrum of standing spin wave eigenmodes. Comparison of the ST-FMR measurements with micromagnetic simulations of the spin wave spectrum allows us to explain the character of low-frequency magnetic excitations in nanoscale MTJs.Comment: Also see: http://faculty.sites.uci.edu/krivorotovgroup

High precision variational Bayesian inference of sparse linear networks

Sparse networks can be found in a wide range of applications, such as biological and communication networks. Inference of such networks from data has been receiving considerable attention lately, mainly driven by the need to understand and control internal working mechanisms. However, while most available methods have been successful at predicting many correct links, they also tend to infer many incorrect links. Precision is the ratio between the number of correctly inferred links and all inferred links, and should ideally be close to 100%. For example, 50% precision means that half of inferred links are incorrect, and there is only a 50% chance of picking a correct one. In contrast, this paper infers links of discrete-time linear networks with very high precision, based on variational Bayesian inference and Gaussian processes. Our method can handle limited datasets, does not require full-state measurements and effectively promotes both system stability and network sparsity. On several of examples, Monte Carlo simulations illustrate that our method consistently has 100% or nearly 100% precision, even in the presence of noise and hidden nodes, outperforming several state-of-the-art methods. The method should be applicable to a wide range of network inference contexts, including biological networks and power systems

No-horizon theorem for vacuum gravity with spacelike G1 isometry groups

We show that (3+1) vacuum spacetimes admitting a global, spacelike, one-parameter Lie group of isometries of translational type cannot contain apparent horizons. The only assumption made is that of the existence of a global spacelike Killing vector field with infinite open orbits; the four-dimensional vacuum spacetime metric is otherwise arbitrary. This result may thus be viewed as a hoop conjecture theorem for vacuum gravity with one spacelike translational Killing symmetry.Comment: 6 pages, revtex4; published in Phys. Rev. D Rapid Com

Flexible force sensors for e-textiles

This paper presents the development of inexpensive, lightweight, flexible polymer-based piezoresistive sensors appropriate for integration in e-textiles. The transducing element used is a volume-conductive carbon impregnated black polypropylene/polyethylene film with commercial names Velostat (from 3M) or Linqstat (from Caplinq). The objective is to investigate on the influence of different sensor constructions, varying film thicknesses, electrode materials and encapsulations on sensor performance. Furthermore, ways of integrating the sensors into textile products, as well as potential applications are also studied. In this paper, the behaviour of the sensors under different cyclic compression loads, applied at different speeds, is presented. Sensors using three different electrode materials are tested. The results show significant influence of sensor construction and electrode material on the static and dynamic performance of the devices.This work is financed by Project “Deus ex Machina”, NORTE-01-0145-FEDER-000026, funded by CCDRN, through Sistema de Apoio à Investigação Cientifica e Tecnológica (Projetos Estruturados I&D&I) of Programa Operacional Regional do Norte, from Portugal 2020. Acknowledgements also to IAPMEI for funding under the program “Startup Voucher” 2017, project MAPS.info:eu-repo/semantics/publishedVersio

The Domination Number of Grids

In this paper, we conclude the calculation of the domination number of all $n\times m$ grid graphs. Indeed, we prove Chang's conjecture saying that for every $16\le n\le m$, $\gamma(G_{n,m})=\lfloor\frac{(n+2)(m+2)}{5}\rfloor -4$.Comment: 12 pages, 4 figure

Common staining techniques for highlighting Acanthamoeba cysts

A 36-year-old woman returning from holiday in Portugal presented with bilateral ocular pain and acute visual loss. Eye examination revealed an inflammation in the anterior segment associated with corneal keratitis. During her trip, she wore contact lenses and rinsed the storage case using tap water. Corneal scrapings, contact lenses and cleaning solution from the case were inoculated onto agar plates supplemented with heat-inactivated bacteria. Bilateral Acanthamoeba keratitis was diagnosed, as microscopic examination of cultures from the last two samples revealed typical, spherical double-walled cystic structures (Fig. 1)

Adsorption of hidrogen peroxide on the surface of silica - titania mixed oxide obtained by the sol-gel processing method

This work describes the sol-gel mixed oxide SiO2/TiO2 property, ST, as prepared, and submitted to heat treatment a 773 K, STC. SEM and EDS images show, within magnification used, a uniform distribution of the TiO2 particles in SiO2/TiO2 matrix. Both, ST and STC adsorb hydrogen peroxide on the surface and through EPR and UV-Vis diffuse reflectance spectra, it was possible to conclude that the species on the surface is the peroxide molecule attached to the Lewis acid site of titanium particle surface, alphaTi(H2O2)+. As the material is very porous, presumably the hydrogen peroxide molecule is confined in the matrix pores on the surface, a reason why the adsorbed species presents an exceptional long lived stability.4145Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Forgetting in Answer Set Programming with Anonymous Cycles

FORGET (PTDC/CCI-INF/32219/2017). NOVA LINCS (UID/CEC/04516/2019).It is now widely accepted that the operation of forgetting in the context of Answer Set Programming [10, 18] is best characterized by the so-called strong persistence, a property that requires that all existing relations between the atoms not to be forgotten be preserved. However, it has been shown that strong persistence cannot always be satisfied. What happens if we must nevertheless forget? One possibility that has been explored before is to consider weaker versions of strong persistence, although not without a cost: some relations between the atoms not to be forgotten are broken in the process. A different alternative is to enhance the logical language so that all such relations can be maintained after the forgetting operation. In this paper, we borrow from the recently introduced notion of fork [1] – a conservative extension of Equilibrium Logic and its monotonic basis, the logic of Here-and-There – which has been shown to be sufficient to overcome the problems related to satisfying strong persistence. We map this notion into the language of logic programs, enhancing it with so-called anonymous cycles, and we introduce a concrete syntactical forgetting operator over this enhanced language that we show to always obey strong persistence.publishe

Magnetic phase transitions in Ta/CoFeB/MgO multilayers

We study thin films and magnetic tunnel junction nanopillars based on Ta/Co$_{20}$Fe$_{60}$B$_{20}$/MgO multilayers by electrical transport and magnetometry measurements. These measurements suggest that an ultrathin magnetic oxide layer forms at the Co$_{20}$Fe$_{60}$B$_{20}$/MgO interface. At approximately 160 K, the oxide undergoes a phase transition from an insulating antiferromagnet at low temperatures to a conductive weak ferromagnet at high temperatures. This interfacial magnetic oxide is expected to have significant impact on the magnetic properties of CoFeB-based multilayers used in spin torque memories

Identification of nonlinear sparse networks using sparse Bayesian learning

© 2017 IEEE. This paper considers a parametric approach to infer sparse networks described by nonlinear ARX models, with linear ARX treated as a special case. The proposed method infers both the Boolean structure and the internal dynamics of the network. It considers classes of nonlinear systems that can be written as weighted (unknown) sums of nonlinear functions chosen from a fixed basis dictionary. Due to the sparse topology, coefficients of most groups are zero. Besides, only a few nonlinear terms in nonzero groups contribute to the internal dynamics. Therefore, the identification problem should estimate both group-and element-sparse parameter vectors. The proposed method combines Sparse Bayesian Learning (SBL) and Group Sparse Bayesian Learning (GSBL) to impose both kinds of sparsity. Simulations indicate that our method outperforms SBL and GSBL when these are applied alone. A linear ring structure network also illustrates that the proposed method has improved performance to the kernel approach