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 $\tau$. 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.

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 $f$ 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