Kinetic Ising System in an Oscillating External Field: Stochastic Resonance and Residence-Time Distributions

Experimental, analytical, and numerical results suggest that the mechanism by which a uniaxial single-domain ferromagnet switches after sudden field reversal depends on the field magnitude and the system size. Here we report new results on how these distinct decay mechanisms influence hysteresis in a two-dimensional nearest-neighbor kinetic Ising model. We present theoretical predictions supported by numerical simulations for the frequency dependence of the probability distributions for the hysteresis-loop area and the period-averaged magnetization, and for the residence-time distributions. The latter suggest evidence of stochastic resonance for small systems in moderately weak oscillating fields.Comment: Includes updated results for Fig.2 and minor text revisions to the abstract and text for clarit

Linear Invariant Systems Theory for Signal Enhancement

This paper discusses a linear time invariant (LTI) systems approach to signal enhancement via projective subspace techniques. It provides closed form expressions for the frequency response of data adaptive finite impulse response eigenfilters. An illustrative example using speech enhancement is also presented.Este artigo apresenta a aplicação da teoria de sistemas lineares invariantes no tempo (LTI) na análise de técnicas de sub-espaço. A resposta em frequência dos filtros resultantes da decomposição em valores singulares é obtida aplicando as propriedades dos sistemas LTI

Simultaneous targeting of Eph receptors in glioblastoma

Eph tyrosine kinase receptors are frequently overexpressed and functional in many cancers, and they are attractive candidates for targeted therapy. Here, we analyzed the expression of Eph receptor A3, one of the most up-regulated factors in glioblastoma cells cultured under tumorsphere-forming conditions, together with EphA2 and EphB2 receptors. EphA3 was overexpressed in up to 60% of glioblastoma tumors tested, but not in normal brain. EphA3 was localized in scattered areas of the tumor, the invasive ring, and niches near tumor vessels. EphA3 co-localized with macrophage/leukocyte markers, suggesting EphA3 expression on tumor-infiltrating cells of bone marrow origin. We took advantage of the fact that ephrinA5 (eA5) is a ligand that binds EphA3, EphA2 and EphB2 receptors, and used it to construct a novel targeted anti-glioblastoma cytotoxin. The eA5-based cytotoxin potently and specifically killed glioblastoma cells with an IC(50) of at least 10(−11) M. This and similar cytotoxins will simultaneously target different compartments of glioblastoma tumors while mitigating tumor heterogeneity

A new physarum learner for network structure learning from biomedical data

A novel structure learning algorithm for Bayesian Networks based on a Physarum Learner is presented. The length of the connections within an initially fully connected Physarum-Maze is taken as the inverse Pearson correlation coefficient between the connected nodes. The Physarum Learner then estimates the shortest indirect paths between each pair of nodes. In each iteration, a score of the surviving edges is incremented. Finally, the highest scored connections are combined to form a Bayesian Network. The novel Physarum Learner method is evaluated with different configurations and compared to the LAGD Hill Climber showing comparable performance with respect to quality of training results and increased time efficiency for large data sets

Boundary layers in pressure-driven flow in smectic A liquid crystals

This article examines the steady flow of a smectic A liquid crystal sample that is initially aligned in a classical "bookshelf" geometry confined between parallel plates and is then subjected to a lateral pressure gradient which is perpendicular to the initial local smectic layer arrangement. The nonlinear dynamic equations are derived. These equations can be linearized and solved exactly to reveal two characteristic length scales that can be identified in terms of the material parameters and reflect the boundary layer behavior of the velocity and the director and smectic layer normal orientations. The asymptotic properties of the nonlinear equations are then investigated to find that these length scales apparently manifest themselves in various aspects of the solutions to the nonlinear steady state equations, especially in the separation between the orientations of the director and smectic layer normal. Non-Newtonian plug-like flow occurs and the solutions for the director profile and smectic layer normal share features identified elsewhere in static liquid crystal configurations. Comparisons with numerical solutions of the nonlinear equations are also made

Chaotic hysteresis in an adiabatically oscillating double well

We consider the motion of a damped particle in a potential oscillating slowly between a simple and a double well. The system displays hysteresis effects which can be of periodic or chaotic type. We explain this behaviour by computing an analytic expression of a Poincar'e map.Comment: 4 pages RevTeX, 3 PS figs, uses psfig.sty. Submitted to Phys. Rev. Letters. PS file also available at http://dpwww.epfl.ch/instituts/ipt/berglund.htm

A Constrained ICA-EMD Model for Group Level fMRI Analysis

Independent component analysis (ICA), being a data-driven method, has been shown to be a powerful tool for functional magnetic resonance imaging (fMRI) data analysis. One drawback of this multivariate approach is that it is not, in general, compatible with the analysis of group data. Various techniques have been proposed to overcome this limitation of ICA. In this paper, a novel ICA-based workflow for extracting resting-state networks from fMRI group studies is proposed. An empirical mode decomposition (EMD) is used, in a data-driven manner, to generate reference signals that can be incorporated into a constrained version of ICA (cICA), thereby eliminating the inherent ambiguities of ICA. The results of the proposed workflow are then compared to those obtained by a widely used group ICA approach for fMRI analysis. In this study, we demonstrate that intrinsic modes, extracted by EMD, are suitable to serve as references for cICA. This approach yields typical resting-state patterns that are consistent over subjects. By introducing these reference signals into the ICA, our processing pipeline yields comparable activity patterns across subjects in a mathematically transparent manner. Our approach provides a user-friendly tool to adjust the trade-off between a high similarity across subjects and preserving individual subject features of the independent components

Numerical solution of the Ericksen-Leslie model for liquid crystalline polymers free surface flows

In this paper we present a finite difference method on a staggered grid for solving two-dimensional free surface flows of liquid crystalline polymers governed by the Ericksen–Leslie dynamic equations. The numerical technique is based on a projection method and employs Cartesian coordinates. The technique solves the governing equations using primitive variables for velocity, pressure, extra-stress tensor and the director. These equations are nonlinear partial differential equations consisting of the mass conservation equation and the balance laws of linear and angular momentum. Code verification and convergence estimates are effected by solving a flow problem on 5 different meshes. Two free surface problems are tackled: A jet impinging on a flat surface and injection molding. In the first case the buckling phenomenon is examined and shown to be highly dependent on the elasticity of the fluid. In the second case, injection molding of two differently shaped containers is carried out and the director is shown to be strongly dependent on its orientation at the boundaries