No abstract

We introduce a new class of models in which a large number of "agents" organize under the influence of an externally imposed coherent noise. The model shows reorganization events whose size distribution closely follows a power-law over many decades, even in the case where the agents do not interact with each other. In addition the system displays "aftershock" events in which large disturbances are followed by a string of others at times which are distributed according to a t −1 law. We also find that the lifetimes of the agents in the system possess a power-law distribution. We explain all of these results using an approximate analytic treatment of the dynamics and discuss a number of variations on the basic model relevant to the study of particular physical systems.

Bacteria form colonies and secrete extracellular polymeric substances that surround the individual cells. These spatial structures are often associated with collaboration and quorum sensing between the bacteria. Here we investigate the mutual protection provided by spherical growth of a monoclonal colony during exposure to phages that proliferate on its surface. As a proof of concept we exposed growing colonies of to a virulent mutant of phage P1. When the colony consists of less than [Formula: see text]50,000 members it is eliminated, while larger initial colonies allow long-term survival of both phage-resistant mutants and, importantly, colonies of mostly phage-sensitive members. A mathematical model predicts that colonies formed solely by phage-sensitive bacteria can survive because the growth of bacteria throughout the colony exceeds the killing of bacteria on the surface and pinpoints how the critical colony size depends on key parameters in the phage infection cycle.

We investigate extremal dynamics on random networks. In the quenched case, after a transient time the dynamics is localized in the largest cluster. The activity in the largest cluster is nonergodic, with hot spots of activity typically centered around nodes with a high coordination number. The nonergodicity of the activity opens for models of evolving networks, which can self-organize into fractal geometries.[S0031-9007(98)

Boolean networks may be viewed as idealizations of biological genetic networks, where each node is represented by an on-off switch which is a function of the binary output from some other nodes. We evolve connectivity in a single Boolean network, and demonstrate how the sole requirement of sequential matching of attractors may open for an evolution that exhibits punctuated equilibrium.PACS numbers: 87.10.+e, 02.70.Lq, 05.40.+jPublished as Phys. Rev. Lett. 81, 236 (1998).

We present a statistical mechanics treatment of the stability of globular proteins which takes explicitly into account the coupling between the protein and water degrees of freedom. This allows us to describe both the cold and the warm unfolding, thus qualitatively reproducing the known thermodynamics of proteins. Classification: BiophysicsThe folded conformation of globular proteins is a state of matter peculiar in more than one respect. The density is that of a condensed phase (solid or liquid), and the relative position of the atoms is, on average, fixed; these are the characteristics of the solid state. However, solids are either crystalline or amorphous, and proteins are neither: the folded structure, while ordered in the sense that each molecule of a given species is folded in the same way, lacks the translational symmetry of a crystal. In Schrödinger's words, proteins are "aperiodic crystals". Unlike any other known solids, globular proteins are not really rigid, being able to perform large conformational motions while retaining locally the same folded structure. Finally, these are mesoscopic systems, consisting of a few thousand atoms.Quantitatively, the peculiarities of this state of matter are perhaps best appreciated from the thermodynamics. Delicate calorimetric measurements [1-3] on the folding transition of globular proteins reveals the following picture: first the transition is first order, at least in the case of single domain proteins. Secondly, the stability of the folded state, i.e. the difference in Gibbs potential ∆G between the unfolded and the folded state is at most a fraction of kT room per aminoacid. Following Privalov [3], we will refer to this property as "cooperativity". The Gibbs potential difference ∆G, as a function of temperature, is non monotonic: it has a maximum around room temperature (where ∆G > 0 and so the folded form is stable), then crosses zero and becomes negative both for higher and lower temperatures. Correspondingly, the protein unfolds not only at high, but also at low temperatures. This phenomenon of "cold unfolding", which is observed experimentally, is most peculiar: solids usually do not melt upon cooling! For temperatures around the cold unfolding transition and below, the enthalpy difference ∆H between the unfolded and the folded state is negative; this means that cold unfolding proceeds with a release of heat (a negative latent heat), as is also observed experimentally; at the higher unfolding transition, on the contrary, ∆H > 0 which corresponds to the usual situation of a positive latent heat. Fig.1 shows Privalovs measurements of the specific heat of myoglobin [3]. There are two peaks in the specific heat, corresponding to the two unfolding transitions, and a large gap ∆C in the specific heat between the unfolded and the folded state. This gap is again peculiar to proteins: usually, for a melting transition ∆C ≈ 0 (e.g. for ice at 0 C C = 1.01 cal/gK while for water at 0 C C = 1.00 cal/gK). The existence of this gap ∆C is related to the phenomenon of cold...

Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity.

We study the scaling relations of the Manna ͓J. Phys. A 24, L363 ͑1992͔͒ model. We found that the avalanche exponent depends crucially on whether one drives the system in the bulk or at the boundary while the cutoff scaling exponent is invariant. Scaling relations relating these exponents are derived for various modes of driving. It is shown numerically that the one dimensional Manna model and a recently introduced ricepile model have the same exponents. Finally, a class of nonconserved self-organized critical models is introduced, and a classification scheme for sandpile models is proposed.