611 research outputs found
Link Prediction Based on Local Random Walk
The problem of missing link prediction in complex networks has attracted much
attention recently. Two difficulties in link prediction are the sparsity and
huge size of the target networks. Therefore, the design of an efficient and
effective method is of both theoretical interests and practical significance.
In this Letter, we proposed a method based on local random walk, which can give
competitively good prediction or even better prediction than other
random-walk-based methods while has a lower computational complexity.Comment: 6 pages, 2 figure
A point process framework for modeling electrical stimulation of the auditory nerve
Model-based studies of auditory nerve responses to electrical stimulation can
provide insight into the functioning of cochlear implants. Ideally, these
studies can identify limitations in sound processing strategies and lead to
improved methods for providing sound information to cochlear implant users. To
accomplish this, models must accurately describe auditory nerve spiking while
avoiding excessive complexity that would preclude large-scale simulations of
populations of auditory nerve fibers and obscure insight into the mechanisms
that influence neural encoding of sound information. In this spirit, we develop
a point process model of the auditory nerve that provides a compact and
accurate description of neural responses to electric stimulation. Inspired by
the framework of generalized linear models, the proposed model consists of a
cascade of linear and nonlinear stages. We show how each of these stages can be
associated with biophysical mechanisms and related to models of neuronal
dynamics. Moreover, we derive a semi-analytical procedure that uniquely
determines each parameter in the model on the basis of fundamental statistics
from recordings of single fiber responses to electric stimulation, including
threshold, relative spread, jitter, and chronaxie. The model also accounts for
refractory and summation effects that influence the responses of auditory nerve
fibers to high pulse rate stimulation. Throughout, we compare model predictions
to published physiological data and explain differences in auditory nerve
responses to high and low pulse rate stimulation. We close by performing an
ideal observer analysis of simulated spike trains in response to sinusoidally
amplitude modulated stimuli and find that carrier pulse rate does not affect
modulation detection thresholds.Comment: 1 title page, 27 manuscript pages, 14 figures, 1 table, 1 appendi
Path-integral analysis of fluctuation theorems for general Langevin processes
We examine classical, transient fluctuation theorems within the unifying
framework of Langevin dynamics. We explicitly distinguish between the effects
of non-conservative forces that violate detailed balance, and non-autonomous
dynamics arising from the variation of an external parameter. When both these
sources of nonequilibrium behavior are present, there naturally arise two
distinct fluctuation theorems.Comment: 24 pages, one figur
Constituting monetary conservatives via the 'savings habit': New Labour and the British housing market bubble
The ongoing world credit crunch might well kill off the most recent bubble dynamics in the British housing market by driving prices systematically downwards from their 2007 peak. Nonetheless, the experience of that bubble still warrants analytical attention. The Labour Government might not have been responsible for consciously creating it, but it has certainly grasped the opportunities the bubble has provided in an attempt to enforce a process of agential change at the heart of the British economy. The key issue in this respect is the way in which the Government has challenged the legitimacy of passive welfare receipts in favour of establishing a welfare system based on incorporating the individual into an active asset-holding society. The housing market has taken on new political significance as a means for individuals first to acquire assets and then to accumulate wealth on the back of asset ownership. The ensuing integration of the housing market into an increasingly reconfigured welfare system has permeated into the politics of everyday life. It has been consistent with individuals remaking their political subjectivities in line with preferences for the type of conservative monetary policies that typically keep house price bubbles inflated
Distribution-based bisimulation for labelled Markov processes
In this paper we propose a (sub)distribution-based bisimulation for labelled
Markov processes and compare it with earlier definitions of state and event
bisimulation, which both only compare states. In contrast to those state-based
bisimulations, our distribution bisimulation is weaker, but corresponds more
closely to linear properties. We construct a logic and a metric to describe our
distribution bisimulation and discuss linearity, continuity and compositional
properties.Comment: Accepted by FORMATS 201
The Complexity of Computing Minimal Unidirectional Covering Sets
Given a binary dominance relation on a set of alternatives, a common thread
in the social sciences is to identify subsets of alternatives that satisfy
certain notions of stability. Examples can be found in areas as diverse as
voting theory, game theory, and argumentation theory. Brandt and Fischer [BF08]
proved that it is NP-hard to decide whether an alternative is contained in some
inclusion-minimal upward or downward covering set. For both problems, we raise
this lower bound to the Theta_{2}^{p} level of the polynomial hierarchy and
provide a Sigma_{2}^{p} upper bound. Relatedly, we show that a variety of other
natural problems regarding minimal or minimum-size covering sets are hard or
complete for either of NP, coNP, and Theta_{2}^{p}. An important consequence of
our results is that neither minimal upward nor minimal downward covering sets
(even when guaranteed to exist) can be computed in polynomial time unless P=NP.
This sharply contrasts with Brandt and Fischer's result that minimal
bidirectional covering sets (i.e., sets that are both minimal upward and
minimal downward covering sets) are polynomial-time computable.Comment: 27 pages, 7 figure
Evaluation of effective resistances in pseudo-distance-regular resistor networks
In Refs.[1] and [2], calculation of effective resistances on distance-regular
networks was investigated, where in the first paper, the calculation was based
on the stratification of the network and Stieltjes function associated with the
network, whereas in the latter one a recursive formula for effective
resistances was given based on the Christoffel-Darboux identity. In this paper,
evaluation of effective resistances on more general networks called
pseudo-distance-regular networks [21] or QD type networks \cite{obata} is
investigated, where we use the stratification of these networks and show that
the effective resistances between a given node such as and all of the
nodes belonging to the same stratum with respect to
(, belonging to the -th stratum with respect
to the ) are the same. Then, based on the spectral techniques, an
analytical formula for effective resistances such that
(those nodes , of
the network such that the network is symmetric with respect to them) is given
in terms of the first and second orthogonal polynomials associated with the
network, where is the pseudo-inverse of the Laplacian of the network.
From the fact that in distance-regular networks,
is satisfied for all nodes
of the network, the effective resistances
for ( is diameter of the network which
is the same as the number of strata) are calculated directly, by using the
given formula.Comment: 30 pages, 7 figure
Laparoscopic Placement of Hepatic Artery Infusion Pumps: Technical Considerations and Early Results
Laparoscopic hepatic artery infusion pump (LHAIP) placement is a novel treatment option for patients with colorectal liver metastases. This study investigates technical difficulties with regard to variant hepatic arteries and the preliminary outcomes for patients treated with LHAIP placement.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41404/1/10434_2004_Article_589.pd
Networking - A Statistical Physics Perspective
Efficient networking has a substantial economic and societal impact in a
broad range of areas including transportation systems, wired and wireless
communications and a range of Internet applications. As transportation and
communication networks become increasingly more complex, the ever increasing
demand for congestion control, higher traffic capacity, quality of service,
robustness and reduced energy consumption require new tools and methods to meet
these conflicting requirements. The new methodology should serve for gaining
better understanding of the properties of networking systems at the macroscopic
level, as well as for the development of new principled optimization and
management algorithms at the microscopic level. Methods of statistical physics
seem best placed to provide new approaches as they have been developed
specifically to deal with non-linear large scale systems. This paper aims at
presenting an overview of tools and methods that have been developed within the
statistical physics community and that can be readily applied to address the
emerging problems in networking. These include diffusion processes, methods
from disordered systems and polymer physics, probabilistic inference, which
have direct relevance to network routing, file and frequency distribution, the
exploration of network structures and vulnerability, and various other
practical networking applications.Comment: (Review article) 71 pages, 14 figure
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