632 research outputs found
A new technique using a rubber balloon in emergency second trimester cerclage for fetal membrane prolapse
The definitive version is available at www.blackwell-synergy.comArticleJOURNAL OF OBSTETRICS AND GYNAECOLOGY RESEARCH. 34(6):935-940 (2008)journal articl
Criticality and oscillatory behavior in non-Markovian Contact Process
A Non-Markovian generalization of one-dimensional Contact Process (CP) is
being introduced in which every particle has an age and will be annihilated at
its maximum age . There is an absorbing state phase transition which is
controlled by this parameter. The model can demonstrate oscillatory behavior in
its approach to the stationary state. These oscillations are also present in
the mean-field approximation which is a first-order differential equation with
time-delay. Studying dynamical critical exponents suggests that the model
belongs to the DP universlity class.Comment: 4 pages, 5 figures, to be published in Phys. Rev.
Possibility of an ordered state of spins and holes in single-crystal La2-xSrxCu1-yZnyO4 (x=0.21, y=0 and 0.01) studied by μSR
Fermi-Surface Reconstruction in the Periodic Anderson Model
We study ground state properties of periodic Anderson model in a
two-dimensional square lattice with variational Monte Carlo method. It is shown
that there are two different types of quantum phase transition: a conventional
antiferromagnetic transition and a Fermi-surface reconstruction which
accompanies a change of topology of the Fermi surface. The former is induced by
a simple back-folding of the Fermi surface while the latter is induced by
localization of electrons. The mechanism of these transitions and the
relation to the recent experiments on Fermi surface are discussed in detail.Comment: 8 pages, 7 figures, submitted to Journal of the Physical Society of
Japa
Large Scale Cross-Correlations in Internet Traffic
The Internet is a complex network of interconnected routers and the existence
of collective behavior such as congestion suggests that the correlations
between different connections play a crucial role. It is thus critical to
measure and quantify these correlations. We use methods of random matrix theory
(RMT) to analyze the cross-correlation matrix C of information flow changes of
650 connections between 26 routers of the French scientific network `Renater'.
We find that C has the universal properties of the Gaussian orthogonal ensemble
of random matrices: The distribution of eigenvalues--up to a rescaling which
exhibits a typical correlation time of the order 10 minutes--and the spacing
distribution follow the predictions of RMT. There are some deviations for large
eigenvalues which contain network-specific information and which identify
genuine correlations between connections. The study of the most correlated
connections reveals the existence of `active centers' which are exchanging
information with a large number of routers thereby inducing correlations
between the corresponding connections. These strong correlations could be a
reason for the observed self-similarity in the WWW traffic.Comment: 7 pages, 6 figures, final versio
Finite-size and correlation-induced effects in Mean-field Dynamics
The brain's activity is characterized by the interaction of a very large
number of neurons that are strongly affected by noise. However, signals often
arise at macroscopic scales integrating the effect of many neurons into a
reliable pattern of activity. In order to study such large neuronal assemblies,
one is often led to derive mean-field limits summarizing the effect of the
interaction of a large number of neurons into an effective signal. Classical
mean-field approaches consider the evolution of a deterministic variable, the
mean activity, thus neglecting the stochastic nature of neural behavior. In
this article, we build upon two recent approaches that include correlations and
higher order moments in mean-field equations, and study how these stochastic
effects influence the solutions of the mean-field equations, both in the limit
of an infinite number of neurons and for large yet finite networks. We
introduce a new model, the infinite model, which arises from both equations by
a rescaling of the variables and, which is invertible for finite-size networks,
and hence, provides equivalent equations to those previously derived models.
The study of this model allows us to understand qualitative behavior of such
large-scale networks. We show that, though the solutions of the deterministic
mean-field equation constitute uncorrelated solutions of the new mean-field
equations, the stability properties of limit cycles are modified by the
presence of correlations, and additional non-trivial behaviors including
periodic orbits appear when there were none in the mean field. The origin of
all these behaviors is then explored in finite-size networks where interesting
mesoscopic scale effects appear. This study leads us to show that the
infinite-size system appears as a singular limit of the network equations, and
for any finite network, the system will differ from the infinite system
Vortex State and Field-Angle Resolved Specific Heat Oscillation for H // ab in d-Wave Superconductors
When magnetic field is applied parallel to the ab plane in d_{x^2-y^2}-wave
superconductors, the transition of stable vortex lattice structure, spatial
structure of local density of states, and specific heat oscillation by rotation
of magnetic field orientation are investigated by quantitative calculations
based on the selfconsistent Eilenberger theory. We estimate how the vortex
state changes depending on the relative angle between the node-direction of the
superconducting gap and magnetic field orientation. To reproduce the
sign-change of specific heat oscillation observed in CeCoIn_5, our study is
done by including strong paramagnetic effect. The quantitative theoretical
calculations give decisive information to analyze the experimental data on the
field-angle dependence, and establish the angle-resolved specific heat
experiment as a spectroscopic means to identify the node-position of the
superconducting gap.Comment: 9 pages, 13 figure
Stochastic Network Models in Neuroscience: A Festschrift for Jack Cowan. Introduction to the Special Issue
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