104 research outputs found

### Intrusion and extrusion of water in hydrophobic mesopores

We present experimental and theoretical results on intrusion-extrusion cycles
of water in hydrophobic mesoporous materials, characterized by independent
cylindrical pores. The intrusion, which takes place above the bulk saturation
pressure, can be well described using a macroscopic capillary model. Once the
material is saturated with water, extrusion takes place upon reduction of the
externally applied pressure; Our results for the extrusion pressure can only be
understood by assuming that the limiting extrusion mechanism is the nucleation
of a vapour bubble inside the pores. A comparison of calculated and
experimental nucleation pressures shows that a proper inclusion of line tension
effects is necessary to account for the observed values of nucleation barriers.
Negative line tensions of order $10^{-11} \mathrm{J.m}^{-1}$ are found for our
system, in reasonable agreement with other experimental estimates of this
quantity

### TreeKnit: Inferring ancestral reassortment graphs of influenza viruses

When two influenza viruses co-infect the same cell, they can exchange genome segments in a process known as reassortment. Reassortment is an important source of genetic diversity and is known to have been involved in the emergence of most pandemic influenza strains. However, because of the difficulty in identifying reassortment events from viral sequence data, little is known about their role in the evolution of the seasonal influenza viruses. Here we introduce TreeKnit, a method that infers ancestral reassortment graphs (ARG) from two segment trees. It is based on topological differences between trees, and proceeds in a greedy fashion by finding regions that are compatible in the two trees. Using simulated genealogies with reassortments, we show that TreeKnit performs well in a wide range of settings and that it is as accurate as a more principled bayesian method, while being orders of magnitude faster. Finally, we show that it is possible to use the inferred ARG to better resolve segment trees and to construct more informative visualizations of reassortments

### Propagation dynamics on networks featuring complex topologies

Analytical description of propagation phenomena on random networks has
flourished in recent years, yet more complex systems have mainly been studied
through numerical means. In this paper, a mean-field description is used to
coherently couple the dynamics of the network elements (nodes, vertices,
individuals...) on the one hand and their recurrent topological patterns
(subgraphs, groups...) on the other hand. In a SIS model of epidemic spread on
social networks with community structure, this approach yields a set of ODEs
for the time evolution of the system, as well as analytical solutions for the
epidemic threshold and equilibria. The results obtained are in good agreement
with numerical simulations and reproduce random networks behavior in the
appropriate limits which highlights the influence of topology on the processes.
Finally, it is demonstrated that our model predicts higher epidemic thresholds
for clustered structures than for equivalent random topologies in the case of
networks with zero degree correlation.Comment: 10 pages, 5 figures, 1 Appendix. Published in Phys. Rev. E (mistakes
in the PRE version are corrected here

### Limited Predictability of Amino Acid Substitutions in Seasonal Influenza Viruses

Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. Although the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as traveling fitness waves

### Propagation on networks: an exact alternative perspective

By generating the specifics of a network structure only when needed
(on-the-fly), we derive a simple stochastic process that exactly models the
time evolution of susceptible-infectious dynamics on finite-size networks. The
small number of dynamical variables of this birth-death Markov process greatly
simplifies analytical calculations. We show how a dual analytical description,
treating large scale epidemics with a Gaussian approximations and small
outbreaks with a branching process, provides an accurate approximation of the
distribution even for rather small networks. The approach also offers important
computational advantages and generalizes to a vast class of systems.Comment: 8 pages, 4 figure

### Localization of thermal packets and metastable states in Sinai model

We consider the Sinai model describing a particle diffusing in a 1D random
force field. As shown by Golosov, this model exhibits a strong localization
phenomenon for the thermal packet: the disorder average of the thermal
distribution of the relative distance y=x-m(t), with respect to the
(disorder-dependent) most probable position m(t), converges in the limit of
infinite time towards a distribution P(y). In this paper, we revisit this
question of the localization of the thermal packet. We first generalize the
result of Golosov by computing explicitly the joint asymptotic distribution of
relative position y=x(t)-m(t) and relative energy u=U(x(t))-U(m(t)) for the
thermal packet. Next, we compute in the infinite-time limit the localization
parameters Y_k, representing the disorder-averaged probabilities that k
particles of the thermal packet are at the same place, and the correlation
function C(l) representing the disorder-averaged probability that two particles
of the thermal packet are at a distance l from each other. We moreover prove
that our results for Y_k and C(l) exactly coincide with the thermodynamic limit
of the analog quantities computed for independent particles at equilibrium in a
finite sample of length L. Finally, we discuss the properties of the
finite-time metastable states that are responsible for the localization
phenomenon and compare with the general theory of metastable states in glassy
systems, in particular as a test of the Edwards conjecture.Comment: 17 page

### Fast diffusion of a Lennard-Jones cluster on a crystalline surface

We present a Molecular Dynamics study of large Lennard-Jones clusters
evolving on a crystalline surface. The static and the dynamic properties of the
cluster are described. We find that large clusters can diffuse rapidly, as
experimentally observed. The role of the mismatch between the lattice
parameters of the cluster and the substrate is emphasized to explain the
diffusion of the cluster. This diffusion can be described as a Brownian motion
induced by the vibrationnal coupling to the substrate, a mechanism that has not
been previously considered for cluster diffusion.Comment: latex, 5 pages with figure

### Glassy behaviour in disordered systems with non-relaxational dynamics

We show that a family of disordered systems with non-relaxational dynamics
may exhibit ``glassy'' behavior at nonzero temperature, although such a
behavior appears to be ruled out by a face-value application of mean-field
theory. Nevertheless, the roots of this behavior can be understood within
mean-field theory itself, properly interpreted. Finite systems belonging to
this family have a dynamical regime with a self-similar pattern of alternating
periods of fast motion and trapping.Comment: 4 pages, 4 figure

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