130 research outputs found
A Position-Space Renormalization-Group Approach for Driven Diffusive Systems Applied to the Asymmetric Exclusion Model
This paper introduces a position-space renormalization-group approach for
nonequilibrium systems and applies the method to a driven stochastic
one-dimensional gas with open boundaries. The dynamics are characterized by
three parameters: the probability that a particle will flow into the
chain to the leftmost site, the probability that a particle will flow
out from the rightmost site, and the probability that a particle will jump
to the right if the site to the right is empty. The renormalization-group
procedure is conducted within the space of these transition probabilities,
which are relevant to the system's dynamics. The method yields a critical point
at ,in agreement with the exact values, and the critical
exponent , as compared with the exact value .Comment: 14 pages, 4 figure
Breakdown of thermodynamic equilibrium for DNA hybridization in microarrays
Test experiments of hybridization in DNA microarrays show systematic
deviations from the equilibrium isotherms. We argue that these deviations are
due to the presence of a partially hybridized long-lived state, which we
include in a kinetic model. Experiments confirm the model predictions for the
intensity vs. free energy behavior. The existence of slow relaxation phenomena
has important consequences for the specificity of microarrays as devices for
the detection of a target sequence from a complex mixture of nucleic acids.Comment: 4 pages, 4 figure
Thermodynamics of histories for the one-dimensional contact process
The dynamical activity K(t) of a stochastic process is the number of times it
changes configuration up to time t. It was recently argued that (spin) glasses
are at a first order dynamical transition where histories of low and high
activity coexist. We study this transition in the one-dimensional contact
process by weighting its histories by exp(sK(t)). We determine the phase
diagram and the critical exponents of this model using a recently developed
approach to the thermodynamics of histories that is based on the density matrix
renormalisation group. We find that for every value of the infection rate,
there is a phase transition at a critical value of s. Near the absorbing state
phase transition of the contact process, the generating function of the
activity shows a scaling behavior similar to that of the free energy in an
equilibrium system near criticality.Comment: 16 pages, 7 figure
Real-space renormalisation group approach to driven diffusive systems
We introduce a real-space renormalisation group procedure for driven
diffusive systems which predicts both steady state and dynamic properties. We
apply the method to the boundary driven asymmetric simple exclusion process and
recover exact results for the steady state phase diagram, as well as the
crossovers in the relaxation dynamics for each phase.Comment: 10 pages, 5 figure
Nonequilibrium effects in DNA microarrays: a multiplatform study
It has recently been shown that in some DNA microarrays the time needed to
reach thermal equilibrium may largely exceed the typical experimental time,
which is about 15h in standard protocols (Hooyberghs et al. Phys. Rev. E 81,
012901 (2010)). In this paper we discuss how this breakdown of thermodynamic
equilibrium could be detected in microarray experiments without resorting to
real time hybridization data, which are difficult to implement in standard
experimental conditions. The method is based on the analysis of the
distribution of fluorescence intensities I from different spots for probes
carrying base mismatches. In thermal equilibrium and at sufficiently low
concentrations, log I is expected to be linearly related to the hybridization
free energy with a slope equal to , where is
the experimental temperature and R is the gas constant. The breakdown of
equilibrium results in the deviation from this law. A model for hybridization
kinetics explaining the observed experimental behavior is discussed, the
so-called 3-state model. It predicts that deviations from equilibrium yield a
proportionality of to . Here, is an
effective temperature, higher than the experimental one. This behavior is
indeed observed in some experiments on Agilent arrays. We analyze experimental
data from two other microarray platforms and discuss, on the basis of the
results, the attainment of equilibrium in these cases. Interestingly, the same
3-state model predicts a (dynamical) saturation of the signal at values below
the expected one at equilibrium.Comment: 27 pages, 9 figures, 1 tabl
Finite size scaling of current fluctuations in the totally asymmetric exclusion process
We study the fluctuations of the current J(t) of the totally asymmetric
exclusion process with open boundaries. Using a density matrix renormalization
group approach, we calculate the cumulant generating function of the current.
This function can be interpreted as a free energy for an ensemble in which
histories are weighted by exp(-sJ(t)). We show that in this ensemble the model
has a first order space-time phase transition at s=0. We numerically determine
the finite size scaling of the cumulant generating function near this phase
transition, both in the non-equilibrium steady state and for large times.Comment: 18 pages, 11 figure
Bovine tuberculosis surveillance alternatives in Belgium
<p>Belgium obtained the bovine tuberculosis (bTB) officially free status in 2003 (EC Decision 2003/467/EC). This study was carried out to evaluate the components of the current bTB surveillance program in Belgium and to determine the sensitivity of this program. Secondly, alternatives to optimize the bTB surveillance in accordance with European legislation (Council Directive 64/432/EEC) were evaluated. Separate scenario trees were designed for each active surveillance component of the bTB surveillance program. Data from 2005 to 2009 regarding cattle population, movement and surveillance were collected to feed the stochastic scenario tree simulation model. A total of 7,403,826 cattle movement history records were obtained for the 2,678,020 cattle from 36,059 cattle herds still active in 2009. The current surveillance program sensitivity as well as the impact of alternative surveillance protocols was simulated in a stochastic model using 10,000 iterations per simulation. The median (50% percentile) of the component sensitivities across 10,000 iterations was 0.83, 0.85, 0.99, 0.99, respectively, for (i) testing the cattle only during the winter screening, (ii) testing only imported cattle, (iii) testing only purchased cattle and (iv) testing only all slaughtered cattle. The sensitivity analysis showed that the most influential input parameter explaining the variability around the output came from the uncertainty distribution around the sensitivity of the diagnostic tests used within the bTB surveillance. Providing all animals are inspected and post mortem inspection is highly sensitive, slaughterhouse surveillance was the most effective surveillance component. If these conditions were not met, the uncertainty around the mean sensitivity of this component was important. Using an antibody ELISA at purchase and an interferon gamma test during winter screening and at import would increase greatly the sensitivity and the confidence level of Belgium's freedom from bTB infection status.</p></p
Low-density series expansions for directed percolation IV. Temporal disorder
We introduce a model for temporally disordered directed percolation in which
the probability of spreading from a vertex , where is the time and
is the spatial coordinate, is independent of but depends on . Using
a very efficient algorithm we calculate low-density series for bond percolation
on the directed square lattice. Analysis of the series yields estimates for the
critical point and various critical exponents which are consistent with a
continuous change of the critical parameters as the strength of the disorder is
increased.Comment: 11 pages, 3 figure
The effects of mismatches on hybridization in DNA microarrays: determination of nearest neighbor parameters
Quantifying interactions in DNA microarrays is of central importance for a
better understanding of their functioning. Hybridization thermodynamics for
nucleic acid strands in aqueous solution can be described by the so-called
nearest-neighbor model, which estimates the hybridization free energy of a
given sequence as a sum of dinucleotide terms. Compared with its solution
counterparts, hybridization in DNA microarrays may be hindered due to the
presence of a solid surface and of a high density of DNA strands. We present
here a study aimed at the determination of hybridization free energies in DNA
microarrays. Experiments are performed on custom Agilent slides. The solution
contains a single oligonucleotide. The microarray contains spots with a perfect
matching complementary sequence and other spots with one or two mismatches: in
total 1006 different probe spots, each replicated 15 times per microarray. The
free energy parameters are directly fitted from microarray data. The
experiments demonstrate a clear correlation between hybridization free energies
in the microarray and in solution. The experiments are fully consistent with
the Langmuir model at low intensities, but show a clear deviation at
intermediate (non-saturating) intensities. These results provide new
interesting insights for the quantification of molecular interactions in DNA
microarrays.Comment: 31 pages, 5 figure
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