33,800 research outputs found
Recommended from our members
Measuring and Monitoring Cognition in the Postoperative Period
It is common for patients of all ages to experience some degree of cognitive disturbance following surgery. In most cases, impairment appears mild and is restricted to the acute post-operative period, resolving steadily and speedily. In a small number of cases, however, deficits may be more pronounced and/or endure for longer periods, significantly delaying recovery and increasing the risk of serious clinical complications. The ability to accurately measure postoperative cognition, and track recovery of function, is an important clinical task. This review explores practical and methodological issues that may confound this process, examining how best to obtain reliable and meaningful measures of cognition before and after surgery. It considers neuropsychological test selection, administration, analysis and interpretation and offers evidence-based practice points for clinicians and researchers
Deterministic Modularity Optimization
We study community structure of networks. We have developed a scheme for
maximizing the modularity Q based on mean field methods. Further, we have
defined a simple family of random networks with community structure; we
understand the behavior of these networks analytically. Using these networks,
we show how the mean field methods display better performance than previously
known deterministic methods for optimization of Q.Comment: 7 pages, 4 figures, minor change
Blocking and Persistence in the Zero-Temperature Dynamics of Homogeneous and Disordered Ising Models
A ``persistence'' exponent theta has been extensively used to describe the
nonequilibrium dynamics of spin systems following a deep quench: for
zero-temperature homogeneous Ising models on the d-dimensional cubic lattice,
the fraction p(t) of spins not flipped by time t decays to zero like
t^[-theta(d)] for low d; for high d, p(t) may decay to p(infinity)>0, because
of ``blocking'' (but perhaps still like a power). What are the effects of
disorder or changes of lattice? We show that these can quite generally lead to
blocking (and convergence to a metastable configuration) even for low d, and
then present two examples --- one disordered and one homogeneous --- where p(t)
decays exponentially to p(infinity).Comment: 8 pages (LaTeX); to appear in Physical Review Letter
Uniqueness of Ground States for Short-Range Spin Glasses in the Half-Plane
We consider the Edwards-Anderson Ising spin glass model on the half-plane with zero external field and a wide range of choices, including
mean zero Gaussian, for the common distribution of the collection J of i.i.d.
nearest neighbor couplings. The infinite-volume joint distribution
of couplings J and ground state pairs with periodic
(respectively, free) boundary conditions in the horizontal (respectively,
vertical) coordinate is shown to exist without need for subsequence limits. Our
main result is that for almost every J, the conditional distribution
is supported on a single ground state pair.Comment: 20 pages, 3 figure
Outlier Edge Detection Using Random Graph Generation Models and Applications
Outliers are samples that are generated by different mechanisms from other
normal data samples. Graphs, in particular social network graphs, may contain
nodes and edges that are made by scammers, malicious programs or mistakenly by
normal users. Detecting outlier nodes and edges is important for data mining
and graph analytics. However, previous research in the field has merely focused
on detecting outlier nodes. In this article, we study the properties of edges
and propose outlier edge detection algorithms using two random graph generation
models. We found that the edge-ego-network, which can be defined as the induced
graph that contains two end nodes of an edge, their neighboring nodes and the
edges that link these nodes, contains critical information to detect outlier
edges. We evaluated the proposed algorithms by injecting outlier edges into
some real-world graph data. Experiment results show that the proposed
algorithms can effectively detect outlier edges. In particular, the algorithm
based on the Preferential Attachment Random Graph Generation model consistently
gives good performance regardless of the test graph data. Further more, the
proposed algorithms are not limited in the area of outlier edge detection. We
demonstrate three different applications that benefit from the proposed
algorithms: 1) a preprocessing tool that improves the performance of graph
clustering algorithms; 2) an outlier node detection algorithm; and 3) a novel
noisy data clustering algorithm. These applications show the great potential of
the proposed outlier edge detection techniques.Comment: 14 pages, 5 figures, journal pape
Interfaces (and Regional Congruence?) in Spin Glasses
We present a general theorem restricting properties of interfaces between
thermodynamic states and apply it to the spin glass excitations observed
numerically by Krzakala-Martin and Palassini-Young in spatial dimensions d=3
and 4. We show that such excitations, with interface dimension smaller than d,
cannot yield regionally congruent thermodynamic states. More generally, zero
density interfaces of translation-covariant excitations cannot be pinned (by
the disorder) in any d but rather must deflect to infinity in the thermodynamic
limit. Additional consequences concerning regional congruence in spin glasses
and other systems are discussed.Comment: 4 pages (ReVTeX); 1 figure; submitted to Physical Review Letter
Clustering and preferential attachment in growing networks
We study empirically the time evolution of scientific collaboration networks
in physics and biology. In these networks, two scientists are considered
connected if they have coauthored one or more papers together. We show that the
probability of scientists collaborating increases with the number of other
collaborators they have in common, and that the probability of a particular
scientist acquiring new collaborators increases with the number of his or her
past collaborators. These results provide experimental evidence in favor of
previously conjectured mechanisms for clustering and power-law degree
distributions in networks.Comment: 13 pages, 2 figure
Citation Networks in High Energy Physics
The citation network constituted by the SPIRES data base is investigated
empirically. The probability that a given paper in the SPIRES data base has
citations is well described by simple power laws, ,
with for less than 50 citations and for 50 or more citations. Two models are presented that both represent the
data well, one which generates power laws and one which generates a stretched
exponential. It is not possible to discriminate between these models on the
present empirical basis. A consideration of citation distribution by subfield
shows that the citation patterns of high energy physics form a remarkably
homogeneous network. Further, we utilize the knowledge of the citation
distributions to demonstrate the extreme improbability that the citation
records of selected individuals and institutions have been obtained by a random
draw on the resulting distribution.Comment: 9 pages, 6 figures, 2 table
Realistic spin glasses below eight dimensions: a highly disordered view
By connecting realistic spin glass models at low temperature to the highly
disordered model at zero temperature, we argue that ordinary Edwards-Anderson
spin glasses below eight dimensions have at most a single pair of physically
relevant pure states at nonzero low temperature. Less likely scenarios that
evade this conclusion are also discussed.Comment: 18 pages (RevTeX; 1 figure; to appear in Physical Review E
- …