1,039 research outputs found
Predicting perceived tranquillity in urban parks and open spaces
A method is described that enables the potential tranquillity of an amenity area, such as a park, green, or square to be assessed. The method involves the assessment of traffic noise levels and the measurement of the percentage of natural and contextual features using photographs of the scenes. Examples are taken from three amenity areas in Bradford, West Yorkshire, UK. Using published noise maps, sampling was taken at points in the three parks where visitors were likely to be found and where noise levels were likely to be highest and lowest. At these locations, predictions of the traffic noise levels were made and then the tranquillity rating and the mean value and distribution of ratings were compared. Recommendations for improving the perceived tranquillity are discussed
Random Networks with given Rich-club Coefficient
In complex networks it is common to model a network or generate a surrogate
network based on the conservation of the network's degree distribution. We
provide an alternative network model based on the conservation of connection
density within a set of nodes. This density is measure by the rich-club
coefficient. We present a method to generate surrogates networks with a given
rich-club coefficient. We show that by choosing a suitable local linking term,
the generated random networks can reproduce the degree distribution and the
mixing pattern of real networks. The method is easy to implement and produces
good models of real networks.Comment: revised version, new figure
Growing Scale-Free Networks with Small World Behavior
In the context of growing networks, we introduce a simple dynamical model
that unifies the generic features of real networks: scale-free distribution of
degree and the small world effect. While the average shortest path length
increases logartihmically as in random networks, the clustering coefficient
assumes a large value independent of system size. We derive expressions for the
clustering coefficient in two limiting cases: random (C ~ (ln N)^2 / N) and
highly clustered (C = 5/6) scale-free networks.Comment: 4 pages, 4 figure
Properties of highly clustered networks
We propose and solve exactly a model of a network that has both a tunable
degree distribution and a tunable clustering coefficient. Among other things,
our results indicate that increased clustering leads to a decrease in the size
of the giant component of the network. We also study SIR-type epidemic
processes within the model and find that clustering decreases the size of
epidemics, but also decreases the epidemic threshold, making it easier for
diseases to spread. In addition, clustering causes epidemics to saturate
sooner, meaning that they infect a near-maximal fraction of the network for
quite low transmission rates.Comment: 7 pages, 2 figures, 1 tabl
The state of tranquility: Subjective perception is shaped by contextual modulation of auditory connectivity
In this study, we investigated brain mechanisms for the generation of subjective experience from objective sensory inputs. Our experimental construct was subjective tranquility. Tranquility is a mental state more likely to occur in the presence of objective sensory inputs that arise from natural features in the environment. We used functional magnetic resonance imaging to examine the neural response to scenes that were visually distinct (beach images vs. freeway images) and experienced as tranquil (beach) or non-tranquil (freeway). Both sets of scenes had the same auditory component because waves breaking on a beach and vehicles moving on a freeway can produce similar auditory spectral and temporal characteristics, perceived as a constant roar. Compared with scenes experienced as non-tranquil, we found that subjectively tranquil scenes were associated with significantly greater effective connectivity between the auditory cortex and medial prefrontal cortex, a region implicated in the evaluation of mental states. Similarly enhanced connectivity was also observed between the auditory cortex and posterior cingulate gyrus, temporoparietal cortex and thalamus. These findings demonstrate that visual context can modulate connectivity of the auditory cortex with regions implicated in the generation of subjective states. Importantly, this effect arises under conditions of identical auditory input. Hence, the same sound may be associated with different percepts reflecting varying connectivity between the auditory cortex and other brain regions. This suggests that subjective experience is more closely linked to the connectivity state of the auditory cortex than to its basic sensory inputs
Onset of Vortices in Thin Superconducting Strips and Wires
Spontaneous nucleation and the consequent penetration of vortices into thin
superconducting films and wires, subjected to a magnetic field, can be
considered as a nonlinear stage of primary instability of the current-carrying
superconducting state. The development of the instability leads to the
formation of a chain of vortices in strips and helicoidal vortex lines in
wires. The boundary of instability was obtained analytically. The nonlinear
stage was investigated by simulations of the time-dependent generalized
Ginzburg-Landau equation.Comment: REVTeX 3.0, 12 pages, 5Postscript figures (uuencoded). Accepted for
Phys. Rev.
An algorithm to discover the k-clique cover in networks
In social network analysis, a k-clique is a relaxed clique, i.e., a k-clique is a quasi-complete sub-graph. A k-clique in a graph is a sub-graph where the distance between any two vertices is no greater than k. The
visualization of a small number of vertices can be easily performed in a graph.
However, when the number of vertices and edges increases the visualization
becomes incomprehensible. In this paper, we propose a new graph mining approach based on k-cliques. The concept of relaxed clique is extended to the whole graph, to achieve a general view, by covering the network with k-cliques.
The sequence of k-clique covers is presented, combining small world concepts
with community structure components. Computational results and examples are
presented
Dynamics of 2D pancake vortices in layered superconductors
The dynamics of 2D pancake vortices in Josephson-coupled
superconducting/normal - metal multilayers is considered within the
time-dependent Ginzburg-Landau theory. For temperatures close to a
viscous drag force acting on a moving 2D vortex is shown to depend strongly on
the conductivity of normal metal layers. For a tilted vortex line consisting of
2D vortices the equation of viscous motion in the presence of a transport
current parallel to the layers is obtained. The specific structure of the
vortex line core leads to a new dynamic behavior and to substantial deviations
from the Bardeen-Stephen theory. The viscosity coefficient is found to depend
essentially on the angle between the magnetic field and the
axis normal to the layers. For field orientations close to the layers
the nonlinear effects in the vortex motion appear even for slowly moving vortex
lines (when the in-plane transport current is much smaller than the
Ginzburg-Landau critical current). In this nonlinear regime the viscosity
coefficient depends logarithmically on the vortex velocity .Comment: 15 pages, revtex, no figure
Introducing Small-World Network Effect to Critical Dynamics
We analytically investigate the kinetic Gaussian model and the
one-dimensional kinetic Ising model on two typical small-world networks (SWN),
the adding-type and the rewiring-type. The general approaches and some basic
equations are systematically formulated. The rigorous investigation of the
Glauber-type kinetic Gaussian model shows the mean-field-like global influence
on the dynamic evolution of the individual spins. Accordingly a simplified
method is presented and tested, and believed to be a good choice for the
mean-field transition widely (in fact, without exception so far) observed on
SWN. It yields the evolving equation of the Kawasaki-type Gaussian model. In
the one-dimensional Ising model, the p-dependence of the critical point is
analytically obtained and the inexistence of such a threshold p_c, for a finite
temperature transition, is confirmed. The static critical exponents, gamma and
beta are in accordance with the results of the recent Monte Carlo simulations,
and also with the mean-field critical behavior of the system. We also prove
that the SWN effect does not change the dynamic critical exponent, z=2, for
this model. The observed influence of the long-range randomness on the critical
point indicates two obviously different hidden mechanisms.Comment: 30 pages, 1 ps figures, REVTEX, accepted for publication in Phys.
Rev.
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