1,223 research outputs found
Magnetoresistance of Three-Constituent Composites: Percolation Near a Critical Line
Scaling theory, duality symmetry, and numerical simulations of a random
network model are used to study the magnetoresistance of a
metal/insulator/perfect conductor composite with a disordered columnar
microstructure. The phase diagram is found to have a critical line which
separates regions of saturating and non-saturating magnetoresistance. The
percolation problem which describes this line is a generalization of
anisotropic percolation. We locate the percolation threshold and determine the
t = s = 1.30 +- 0.02, nu = 4/3 +- 0.02, which are the same as in
two-constituent 2D isotropic percolation. We also determine the exponents which
characterize the critical dependence on magnetic field, and confirm numerically
that nu is independent of anisotropy. We propose and test a complete scaling
description of the magnetoresistance in the vicinity of the critical line.Comment: Substantially revised version; description of behavior in finite
magnetic fields added. 7 pages, 7 figures, submitted to PR
Corrections to scaling for percolative conduction: anomalous behavior at small L
Recently Grassberger has shown that the correction to scaling for the
conductance of a bond percolation network on a square lattice is a nonmonotonic
function of the linear lattice dimension with a minimum at , while this
anomalous behavior is not present in the site percolation networks. We perform
a high precision numerical study of the bond percolation random resistor
networks on the square, triangular and honeycomb lattices to further examine
this result. We use the arithmetic, geometric and harmonic means to obtain the
conductance and find that the qualitative behavior does not change: it is not
related to the shape of the conductance distribution for small system sizes. We
show that the anomaly at small L is absent on the triangular and honeycomb
networks. We suggest that the nonmonotonic behavior is an artifact of
approximating the continuous system for which the theory is formulated by a
discrete one which can be simulated on a computer. We show that by slightly
changing the definition of the linear lattice size we can eliminate the minimum
at small L without significantly affecting the large L limit.Comment: 3 pages, 4 figures;slightly expanded, 2 figures added. Accepted for
publishing in Phys. Rev.
On the rate of convergence of the Hamiltonian particle-mesh method
The Hamiltonian Particle-Mesh (HPM) method is a particle-in-cell method for compressible fluid flow with Hamiltonian structure. We present a numer- ical short-time study of the rate of convergence of HPM in terms of its three main governing parameters. We find that the rate of convergence is much better than the best available theoretical estimates. Our results indicate that HPM performs best when the number of particles is on the order of the number of grid cells, the HPM global smoothing kernel has fast decay in Fourier space, and the HPM local interpolation kernel is a cubic spline
Low density expansion for Lyapunov exponents
In some quasi-one-dimensional weakly disordered media, impurities are large
and rare rather than small and dense. For an Anderson model with a low density
of strong impurities, a perturbation theory in the impurity density is
developed for the Lyapunov exponent and the density of states. The Lyapunov
exponent grows linearly with the density. Anomalies of the Kappus-Wegner type
appear for all rational quasi-momenta even in lowest order perturbation theory
The role of smoking in social networks on smoking cessation and relapse among adults: A longitudinal study
Understanding the spread of smoking cessation and relapse within social networks may offer new approaches to further curb the smoking epidemic. Whether smoking behavior among social network members determines smoking cessation and relapse of adults however, is less known. For this study, longitudinal data of 4623 adults participating in the Dutch Longitudinal Internet Studies for the Social sciences (LISS) panel were collected in March 2013 with a follow-up in 2014. Logistic regression was used to examine the association between the proportion of smokers in social networks, and (1) smoking cessation (n = 762) and (2) smoking relapse (n = 1905). Analyses were adjusted for the size of the network, age, sex, and education. Respondents with the largest proportion of smokers in their social network were less likely to quit smoking (OR = 0.25; 95% CI = 0.11–0.66) and more likely to experience a relapse (6.08; 3.01–12.00). Smoking cessation and relapse were most strongly associated with the proportion of smokers among household members and friends. The proportion of smokers in family outside the household was not related to smoking cessation and smoking relapse. In conclusion, smoking behavior in social networks, especially among household members and friends, is strongly associated with smoking cessation and relapse. These findings further support the spread of smoking within social networks, and provide evidence for network-based interventions, particularly including household members and friends
Mating barriers between genetically divergent strains of the parasitic nematode Haemonchus contortus suggest incipient speciation
How big is too big? Critical Shocks for Systemic Failure Cascades
External or internal shocks may lead to the collapse of a system consisting
of many agents. If the shock hits only one agent initially and causes it to
fail, this can induce a cascade of failures among neighoring agents. Several
critical constellations determine whether this cascade remains finite or
reaches the size of the system, i.e. leads to systemic risk. We investigate the
critical parameters for such cascades in a simple model, where agents are
characterized by an individual threshold \theta_i determining their capacity to
handle a load \alpha\theta_i with 1-\alpha being their safety margin. If agents
fail, they redistribute their load equally to K neighboring agents in a regular
network. For three different threshold distributions P(\theta), we derive
analytical results for the size of the cascade, X(t), which is regarded as a
measure of systemic risk, and the time when it stops. We focus on two different
regimes, (i) EEE, an external extreme event where the size of the shock is of
the order of the total capacity of the network, and (ii) RIE, a random internal
event where the size of the shock is of the order of the capacity of an agent.
We find that even for large extreme events that exceed the capacity of the
network finite cascades are still possible, if a power-law threshold
distribution is assumed. On the other hand, even small random fluctuations may
lead to full cascades if critical conditions are met. Most importantly, we
demonstrate that the size of the "big" shock is not the problem, as the
systemic risk only varies slightly for changes of 10 to 50 percent of the
external shock. Systemic risk depends much more on ingredients such as the
network topology, the safety margin and the threshold distribution, which gives
hints on how to reduce systemic risk.Comment: 23 pages, 7 Figure
Smallest small-world network
Efficiency in passage times is an important issue in designing networks, such
as transportation or computer networks. The small-world networks have
structures that yield high efficiency, while keeping the network highly
clustered. We show that among all networks with the small-world structure, the
most efficient ones have a single ``center'', from which all shortcuts are
connected to uniformly distributed nodes over the network. The networks with
several centers and a connected subnetwork of shortcuts are shown to be
``almost'' as efficient. Genetic-algorithm simulations further support our
results.Comment: 5 pages, 6 figures, REVTeX
Bias reduction in traceroute sampling: towards a more accurate map of the Internet
Traceroute sampling is an important technique in exploring the internet
router graph and the autonomous system graph. Although it is one of the primary
techniques used in calculating statistics about the internet, it can introduce
bias that corrupts these estimates. This paper reports on a theoretical and
experimental investigation of a new technique to reduce the bias of traceroute
sampling when estimating the degree distribution. We develop a new estimator
for the degree of a node in a traceroute-sampled graph; validate the estimator
theoretically in Erdos-Renyi graphs and, through computer experiments, for a
wider range of graphs; and apply it to produce a new picture of the degree
distribution of the autonomous system graph.Comment: 12 pages, 3 figure
Long-term treatment with the dopamine agonist quinagolide of patients with clinically non-functioning pituitary adenoma
OBJECTIVE: This study was performed to evaluate the effect of prolonged
treatment with the dopamine agonist quinagolide on serum gonadotropin and
alpha-subunit concentrations and tumor volume in patients with clinically
non-functioning pituitary adenomas (CNPA). DESIGN: Ten patients with CNPA
were treated with quinagolide (0.3 mg daily). The median duration of
treatment was 57 months (range 36-93 months). Blood samples for
measurement of serum gonadotropin and alpha-subunit concentrations were
drawn before treatment, after 5 days, and at each outpatient visit.
Computerized tomography or magnetic resonance imaging of the pituitary
region and Goldmann perimetry were done before and at regular intervals
during treatment. RESULTS: A significant decrease of serum FSH, LH or
alpha-subunit concentrations was found in nine patients. The levels
remained low during the entire treatment period. In two out of three
patients with pre-existing visual field defects a slight improvement was
shown during the first months of treatment, but eventually deterioration
occurred in all three patients. A fourth patient developed unilateral
ophthalmoplegia dur
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