2,842 research outputs found
Skeleton and fractal scaling in complex networks
We find that the fractal scaling in a class of scale-free networks originates
from the underlying tree structure called skeleton, a special type of spanning
tree based on the edge betweenness centrality. The fractal skeleton has the
property of the critical branching tree. The original fractal networks are
viewed as a fractal skeleton dressed with local shortcuts. An in-silico model
with both the fractal scaling and the scale-invariance properties is also
constructed. The framework of fractal networks is useful in understanding the
utility and the redundancy in networked systems.Comment: 4 pages, 2 figures, final version published in PR
Invasion Percolation Between two Sites
We investigate the process of invasion percolation between two sites
(injection and extraction sites) separated by a distance r in two-dimensional
lattices of size L. Our results for the non-trapping invasion percolation model
indicate that the statistics of the mass of invaded clusters is significantly
dependent on the local occupation probability (pressure) Pe at the extraction
site. For Pe=0, we show that the mass distribution of invaded clusters P(M)
follows a power-law P(M) ~ M^{-\alpha} for intermediate values of the mass M,
with an exponent \alpha=1.39. When the local pressure is set to Pe=Pc, where Pc
corresponds to the site percolation threshold of the lattice topology, the
distribution P(M) still displays a scaling region, but with an exponent
\alpha=1.02. This last behavior is consistent with previous results for the
cluster statistics in standard percolation. In spite of these discrepancies,
the results of our simulations indicate that the fractal dimension of the
invaded cluster does not depends significantly on the local pressure Pe and it
is consistent with the fractal dimension values reported for standard invasion
percolation. Finally, we perform extensive numerical simulations to determine
the effect of the lattice borders on the statistics of the invaded clusters and
also to characterize the self-organized critical behavior of the invasion
percolation process.Comment: 7 pages, 11 figures, submited for PR
Is subdiffusional transport slower than normal?
We consider anomalous non-Markovian transport of Brownian particles in
viscoelastic fluid-like media with very large but finite macroscopic viscosity
under the influence of a constant force field F. The viscoelastic properties of
the medium are characterized by a power-law viscoelastic memory kernel which
ultra slow decays in time on the time scale \tau of strong viscoelastic
correlations. The subdiffusive transport regime emerges transiently for t<\tau.
However, the transport becomes asymptotically normal for t>>\tau. It is shown
that even though transiently the mean displacement and the variance both scale
sublinearly, i.e. anomalously slow, in time, ~ F t^\alpha,
~ t^\alpha, 0<\alpha<1, the mean displacement at each instant
of time is nevertheless always larger than one obtained for normal transport in
a purely viscous medium with the same macroscopic viscosity obtained in the
Markovian approximation. This can have profound implications for the
subdiffusive transport in biological cells as the notion of "ultra-slowness"
can be misleading in the context of anomalous diffusion-limited transport and
reaction processes occurring on nano- and mesoscales
Optimal box-covering algorithm for fractal dimension of complex networks
The self-similarity of complex networks is typically investigated through
computational algorithms the primary task of which is to cover the structure
with a minimal number of boxes. Here we introduce a box-covering algorithm that
not only outperforms previous ones, but also finds optimal solutions. For the
two benchmark cases tested, namely, the E. Coli and the WWW networks, our
results show that the improvement can be rather substantial, reaching up to 15%
in the case of the WWW network.Comment: 5 pages, 6 figure
Extended microsatellite analysis in microsatellite stable, MSH2 and MLH1 mutation-negative HNPCC patients: Genetic reclassification and correlation with clinical features
Background: Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disorder predisposing to predominantly colorectal cancer (CRC) and endometrial cancer frequently due to germline mutations in DNA mismatch repair (MMR) genes, mainly MLH1, MSH2 and also MSH6 in families seen to demonstrate an excess of endometrial cancer. As a consequence, tumors in HNPCC reveal alterations in the length of simple repetitive genomic sequences like poly-A, poly-T, CA or GT repeats (microsatellites) in at least 90% of the cases. Aim of the Study: The study cohort consisted of 25 HNPCC index patients ( 19 Amsterdam positive, 6 Bethesda positive) who revealed a microsatellite stable (MSS) - or low instable (MSI-L) - tumor phenotype with negative mutation analysis for the MMR genes MLH1 and MSH2. An extended marker panel (BAT40, D10S197, D13S153, D18S58, MYCL1) was analyzed for the tumors of these patients with regard to three aspects. First, to reconfirm the MSI-L phenotype found by the standard panel; second, to find minor MSIs which might point towards an MSH6 mutation, and third, to reconfirm the MSS status of hereditary tumors. The reconfirmation of the MSS status of tumors not caused by mutations in the MMR genes should allow one to define another entity of hereditary CRC. Their clinical features were compared with those of 150 patients with sporadic CRCs. Results: In this way, 17 MSS and 8 MSI-L tumors were reclassified as 5 MSS, 18 MSI-L and even 2 MSI-H ( high instability) tumors, the last being seen to demonstrate at least 4 instable markers out of 10. Among all family members, 87 malignancies were documented. The mean age of onset for CRCs was the lowest in the MSI-H-phenotyped patients with 40.5 +/- 4.9 years (vs. 47.0 +/- 14.6 and 49.8 +/- 11.9 years in MSI-L- and MSS-phenotyped patients, respectively). The percentage of CRC was the highest in families with MSS-phenotyped tumors (88%), followed by MSI-L-phenotyped ( 78%) and then by MSI-H-phenotyped (67%) tumors. MSS tumors were preferentially localized in the distal colon supposing a similar biologic behavior like sporadic CRC. MSH6 mutation analysis for the MSI-L and MSI-H patients revealed one truncating mutation for a patient initially with an MSS tumor, which was reclassified as MSI-L by analyzing the extended marker panel. Conclusion: Extended microsatellite analysis serves to evaluate the sensitivity of the reference panel for HNPCC detection and permits phenotype confirmation or upgrading. Additionally, it confirms the MSS status of hereditary CRCs not caused by the common mutations in the MMR genes and provides hints to another entity of hereditary CRC. Copyright (C) 2004 S. Karger AG, Basel
Emergence of fractal behavior in condensation-driven aggregation
We investigate a model in which an ensemble of chemically identical Brownian
particles are continuously growing by condensation and at the same time undergo
irreversible aggregation whenever two particles come into contact upon
collision. We solved the model exactly by using scaling theory for the case
whereby a particle, say of size , grows by an amount over the
time it takes to collide with another particle of any size. It is shown that
the particle size spectra of such system exhibit transition to dynamic scaling
accompanied by the emergence of fractal of
dimension . One of the remarkable feature of this
model is that it is governed by a non-trivial conservation law, namely, the
moment of is time invariant regardless of the choice of the
initial conditions. The reason why it remains conserved is explained by using a
simple dimensional analysis. We show that the scaling exponents and
are locked with the fractal dimension via a generalized scaling relation
.Comment: 8 pages, 6 figures, to appear in Phys. Rev.
Multifractal Analysis of the Coupling Space of Feed-Forward Neural Networks
Random input patterns induce a partition of the coupling space of
feed-forward neural networks into different cells according to the generated
output sequence. For the perceptron this partition forms a random multifractal
for which the spectrum can be calculated analytically using the
replica trick. Phase transition in the multifractal spectrum correspond to the
crossover from percolating to non-percolating cell sizes. Instabilities of
negative moments are related to the VC-dimension.Comment: 10 pages, Latex, submitted to PR
Critical scaling in standard biased random walks
The spatial coverage produced by a single discrete-time random walk, with
asymmetric jump probability and non-uniform steps, moving on an
infinite one-dimensional lattice is investigated. Analytical calculations are
complemented with Monte Carlo simulations. We show that, for appropriate step
sizes, the model displays a critical phenomenon, at . Its scaling
properties as well as the main features of the fragmented coverage occurring in
the vicinity of the critical point are shown. In particular, in the limit , the distribution of fragment lengths is scale-free, with nontrivial
exponents. Moreover, the spatial distribution of cracks (unvisited sites)
defines a fractal set over the spanned interval. Thus, from the perspective of
the covered territory, a very rich critical phenomenology is revealed in a
simple one-dimensional standard model.Comment: 4 pages, 4 figure
Distinguishing cancerous from non-cancerous cells through analysis of electrical noise
Since 1984, electric cell-substrate impedance sensing (ECIS) has been used to
monitor cell behavior in tissue culture and has proven sensitive to cell
morphological changes and cell motility. We have taken ECIS measurements on
several cultures of non-cancerous (HOSE) and cancerous (SKOV) human ovarian
surface epithelial cells. By analyzing the noise in real and imaginary
electrical impedance, we demonstrate that it is possible to distinguish the two
cell types purely from signatures of their electrical noise. Our measures
include power-spectral exponents, Hurst and detrended fluctuation analysis, and
estimates of correlation time; principal-component analysis combines all the
measures. The noise from both cancerous and non-cancerous cultures shows
correlations on many time scales, but these correlations are stronger for the
non-cancerous cells.Comment: 8 pages, 4 figures; submitted to PR
On the Threshold of Intractability
We study the computational complexity of the graph modification problems
Threshold Editing and Chain Editing, adding and deleting as few edges as
possible to transform the input into a threshold (or chain) graph. In this
article, we show that both problems are NP-complete, resolving a conjecture by
Natanzon, Shamir, and Sharan (Discrete Applied Mathematics, 113(1):109--128,
2001). On the positive side, we show the problem admits a quadratic vertex
kernel. Furthermore, we give a subexponential time parameterized algorithm
solving Threshold Editing in time,
making it one of relatively few natural problems in this complexity class on
general graphs. These results are of broader interest to the field of social
network analysis, where recent work of Brandes (ISAAC, 2014) posits that the
minimum edit distance to a threshold graph gives a good measure of consistency
for node centralities. Finally, we show that all our positive results extend to
the related problem of Chain Editing, as well as the completion and deletion
variants of both problems
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