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In this paper, we consider the spread of an epidemic on a changing network, specifically focusing on two phenomena. The first part of the paper investigates a possible mechanism of disease outbreaks on college campuses. We present a toy model, dividing students into extroverts (high-degree nodes with a large number of contacts) and introverts (low-degree nodes with a small number of contacts). In our model, the average degree of extroverts is evolving with time, and its dynamics is coupled with the current epidemic situation: extroverts tend to increase their number of contacts for low level of epidemic, but as more and more students get infected, they start decreasing their average degree. Another phenomenon analyzed in the paper is vaccination: how should the vaccine be allocated to best benefit the population? We consider two possible vaccination strategies: (1) vaccinating people starting from high risk groups (older people with a higher risk of mortality) or (2) prioritizing vaccination of people with a higher number of contacts (such as college students) to decrease the epidemic outbreak. Both phenomena show the importance of diversity in the number of contacts. [ABSTRACT FROM AUTHOR]

The importance of a strict quarantine has been widely debated during the COVID-19 epidemic even from the purely epidemiological point of view. One argument against strict lockdown measures is that once the strict quarantine is lifted, the epidemic comes back, and so the cumulative number of infected individuals during the entire epidemic will stay the same. We consider an SIR model on a network and follow the disease dynamics, modeling the phases of quarantine by changing the node degree distribution. We show that the system reaches different steady states based on the history: the outcome of the epidemic is path-dependent despite the same final node degree distribution. The results indicate that the two-phase route to the final node degree distribution (a strict phase followed by a soft phase) is always better than one phase (the same soft one) unless all the individuals have the same number of connections at the end (the same degree); in the latter case, the overall number of infected is indeed history-independent. The modeling also suggests that the optimal procedure of lifting the quarantine consists of releasing nodes in the order of their degree - highest first. [ABSTRACT FROM AUTHOR]

The effect of chemotaxis on migration of adhesive and proliferative cells on a substrate is analyzed by employing two approaches: by solving a stochastic discrete lattice model for cell dynamics and by deriving and solving a continuum macroscopic equation for cell density. The phenomenon of front propagation is investigated in the framework of the two approaches both for positive and negative chemotaxis. A good agreement between the results of the lattice model and of the continuum model is observed both for front velocities and front profiles. The theoretical model is also able to match recent experimental observations on glioma cell migration. [ABSTRACT FROM AUTHOR]

The position of a reaction front, propagating into a metastable state, fluctuates because of the shot noise of reactions and diffusion. A recent theory (Meerson et al 2011 Phys. Rev. E 84 011147) gave a closed analytic expression for the front diffusion coefficient in the weak noise limit. Here we test this theory in stochastic simulations involving reacting and diffusing particles on a one-dimensional lattice. We also investigate a noise-induced systematic shift of the front velocity compared to the prediction from the spatially continuous deterministic reaction--diffusion equation. [ABSTRACT FROM AUTHOR]

We consider population dynamics on a network of patches, having the same local dynamics, with different population scales (carrying capacities). It is reasonable to assume that if the patches are coupled by very fast migration the whole system will look like an individual patch with a large effective carrying capacity. This is called a "well-mixed" system. We show that, in general, it is not true that the total population has the same dynamics as each local patch when the migration is fast. Different global dynamics can emerge, and usually must be figured out for each individual case. We give a general condition which must be satisfied for the total population to have the same dynamics as the constituent patches. [ABSTRACT FROM AUTHOR]

We investigate the migration of glioma cells as a front propagation phenomenon both theoretically (by using both discrete lattice modeling and a continuum approach) and experimentally. For small effective strength of cell-cell adhesion q, the front velocity does not depend on q. When q exceeds a critical threshold, a fingeringlike front propagation is observed due to cluster formation in the invasive zone. We show that the experiments correspond to the transient regime, before the regime of front propagation is established. We performed an additional experiment on cell migration. A detailed comparison with experimental observations showed that the theory correctly predicts the maximal migration distance but underestimates the migration of the main mass of cells. [ABSTRACT FROM AUTHOR]

We investigate the long-standing puzzle of phase separation in a granular monolayer vibrated from below. Although this system is three dimensional, an interesting dynamics occurs mostly in the horizontal plane, perpendicular to the direction of vibration. Experiments [Olafsen and Urbach, Phys. Rev. Lett. 81, 4369 (1998)] demonstrated that for a high amplitude of vibration the system is in the gaslike phase, but when the amplitude becomes smaller than a certain threshold, a phase separation occurs: A solidlike dense condensate of particles forms in the center of the system, surrounded by particles in the gaslike phase. We explain theoretically the experimentally observed coexistence of dilute and dense phases, employing Navier-Stokes granular hydrodynamics. We show that the phase separation is associated with a negative compressibility of granular gas. [ABSTRACT FROM AUTHOR]

We consider emergent collective behavior of a multicellular biological system. Specifically, we investigate the role of hypoxia (lack of oxygen) in migration of brain tumor cells. We performed two series of cell migration experiments. In the first set of experiments, cell migration away from a tumor spheroid was investigated. The second set of experiments was performed in a typical wound-healing geometry: Cells were placed on a substrate, a scratch was made, and cell migration into the gap was investigated. Experiments show a surprising result: Cells under normal and hypoxic conditions have migrated the same distance in the "spheroid" experiment, while in the "scratch" experiment cells under normal conditions migrated much faster than under hypoxic conditions. To explain this paradox, we formulate a discrete stochastic model for cell dynamics. The theoretical model explains our experimental observations and suggests that hypoxia decreases both the motility of cells and the strength of cell-cell adhesion. The theoretical predictions were further verified in independent experiments. [ABSTRACT FROM AUTHOR]

The granular Leidenfrost state consists of a dense granular cluster levitating above a hot granular gas. The density of particles inside the cluster can be very high and even close to the density of crystalline packing. To describe this state theoretically, one needs to know the density dependence of constitutive relations (pressure, heat losses, thermal conductivity) at these very high densities. However, the accurate expression for the coefficient of thermal conductivity is lacking. In this work, the constitutive relations were measured at high densities in molecular dynamics simulations in three different settings: a uniform freely cooling dense granulate (to measure heat losses), a uniform ensemble of elastically colliding particles (to measure pressure), and a dense granular medium between two thermal walls under gravity (to measure thermal conductivity). Next, the hydrodynamic equations with the resulting expressions were solved to describe the levitating cluster state in various parameter regimes. Separate molecular dynamics simulations were performed to test the theoretical predictions and measure the density and temperature profiles of the granular Leidenfrost state, and a good agreement with theoretical results was observed. [ABSTRACT FROM AUTHOR]

The granular Leidenfrost effect [B. Meerson, et al., Phys. Rev. Lett. 91, 024301 (2003); P. Eshuis et al., Phys. Rev. Lett. 95, 258001 (2005)] is the levitation of a mass of granular matter when a wall below the grains is vibrated, giving rise to a hot granular gas below the cluster. We find by simulation that for a range of parameters the system is bistable: the levitated cluster can occasionally break and give rise to two clusters and a hot granular gas above and below. We use techniques from the theory of rare events to compute the mean transition time for breaking to occur. This requires the introduction of a two-component reaction coordinate. [ABSTRACT FROM AUTHOR]

We consider clustering of particles in the lattice gas model above the critical point. We find the probability for large density fluctuations over scales much larger than the correlation length. This fundamental problem is of interest in various biological contexts such as quorum sensing and clustering of motile, adhesive, cancer cells. In the latter case, it may give a clue to the problem of growth of recurrent tumors. We develop a formalism for the analysis of this rare event employing a phenomenological master equation and measuring the transition rates in numerical simulations. The spontaneous clustering is treated in the framework of the eikonal approximation to the master equation. [ABSTRACT FROM AUTHOR]

Many populations in nature are fragmented: they consist of local populations occupying separate patches. A local population is prone to extinction due to the shot noise of birth and death processes. A migrating population from another patch can dramatically delay the extinction. What is the optimal migration rate that minimizes the extinction risk of the whole population? Here, we answer this question for a connected network of model habitat patches with different carrying capacities. [ABSTRACT FROM AUTHOR]