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At least 289 records · Page 16Linked to original sources
PubMed2006

Stress and large-scale spatial structures in dense, driven granular flows.

We study the appearance of large-scale dynamical heterogeneities in a simplified model of a driven, dissipative granular system. Simulations of steady-state gravity-driven flows of inelastically colliding hard disks show the formation of large-scale linear structures of particles with a high collision frequency. These chains can be shown to carry much of the collisional stress in the system due to a dynamical correlation that develops between the momentum transfer and time between collisions in these frequently colliding particles. The lifetime of these dynamical stress heterogeneities is seen to grow as the flow velocity decreases toward jamming, leading to slowly decaying stress correlations reminiscent of the slow dynamics observed in supercooled liquids.

Journal Article↗
PubMed2006

Ordered spatial structures of dust grains in the thermal plasma.

The thermal complex plasma of atmospheric pressure, containing the grains of condensed phase, has been studied. It has been demonstrated that the existence of the space charge areas around the dust grains leads to the inhomogeneous ionization of the plasma and the occurrence of the fluxes of nonequilibrium charge carriers. These fluxes change the pressure of the gas on the grain surfaces and define the forces that force the grains to move towards the zone of maximum ionization perturbation of the plasma. It has been shown that the combined operation of the electrical forces and the forces of the interface pressure leads to the formation of the ordered structures, corresponding to the balance of forces. The results of computer simulation, corresponding to the experimental data, are given.

Journal Article↗
PubMed2003

Spatial structure of a vortex in low density neutron matter.

We study in a fully self-consistent approach the structure of a vortex in low density superfluid neutron matter. We determine that the matter density profile of a vortex shows a significant depletion in the region of the core, a feature never reported for a vortex state in a Fermi superfluid.

Journal Article↗
PubMed2004

Spatial structures and dynamics of kinetically constrained models of glasses.

Kob and Andersen's simple lattice models for the dynamics of structural glasses are analyzed. Although the particles have only hard core interactions, the imposed constraint that they cannot move if surrounded by too many others causes slow dynamics. On Bethe lattices, a dynamical transition to a partially frozen phase occurs. In finite dimensions there exist rare mobile elements that destroy the transition. At low vacancy density v, the spacing Xi between mobile elements diverges exponentially or faster in 1/v. Within the mobile elements, the dynamics is intrinsically cooperative, and the characteristic time scale diverges faster than any power of 1/v (although slower than Xi). The tagged-particle diffusion coefficient vanishes roughly as Xi(-d).

Journal Article↗
PubMed2001

Unsupervised statistical learning of higher-order spatial structures from visual scenes.

Three experiments investigated the ability of human observers to extract the joint and conditional probabilities of shape co-occurrences during passive viewing of complex visual scenes. Results indicated that statistical learning of shape conjunctions was both rapid and automatic, as subjects were not instructed to attend to any particularfeatures of the displays. Moreover, in addition to single-shape frequency, subjects acquired in parallel several different higher-order aspects of the statistical structure of the displays, including absolute shape-position relations in an array, shape-pair arrangements independent of position, and conditional probabilities of shape co-occurrences. Unsupervised learning of these higher-order statistics provides support for Barlow's theory of visual recognition, which posits that detecting "suspicious coincidences" of elements during recognition is a necessary prerequisite for efficient learning of new visual features.

Adult↗
PubMed2004

The evolution of phenotypic plasticity in spatially structured environments: implications of intraspecific competition, plasticity costs and environmental characteristics.

We model the evolution of reaction norms focusing on three aspects: frequency-dependent selection arising from resource competition, maintenance and production costs of phenotypic plasticity, and three characteristics of environmental heterogeneity (frequency of environments, their intrinsic carrying capacity and the sensitivity to phenotypic maladaptation in these environments). We show that (i) reaction norms evolve so as to trade adaptation for acquiring resources against cost avoidance; (ii) maintenance costs cause reaction norms to better adapt to frequent rather than to infrequent environments, whereas production costs do not; and (iii) evolved reaction norms confer better adaptation to environments with low rather than with high intrinsic carrying capacity. The two previous findings contradict earlier theoretical results and originate from two previously unexplored features that are included in our model. First, production costs of phenotypic plasticity are only incurred when a given phenotype is actually produced. Therefore, they are proportional to the frequency of environments, and these frequencies thus affect the selection pressure to avoid costs just as much as the selection pressure to improve adaptation. This prevents the frequency of environments from affecting the evolving reaction norm. Secondly, our model describes the evolution of plasticity for a phenotype determining an individual's capability to acquire resources, and thus its realized carrying capacity. When individuals are distributed randomly across environments, they cannot avoid experiencing environments with intrinsically low carrying capacity. As selection pressures arising from the need to improve adaptation are stronger under such extreme conditions than under mild ones, better adaptation to environments with low rather than with high intrinsic carrying capacity results.

Adaptation, Physiological↗
PubMed2004

Sources of stochasticity in models of sex allocation in spatially structured populations.

There are many ways to include stochastic effects in models of sex allocation evolution. These include variability in the number of mating partners and fecundity in a rich literature that goes back 20 years. The effects of variance in the fecundity and number of mating partners have typically been considered separately from the stochastic effects of mortality. However, I show that these processes produce mathematically equivalent models with subtly different biological details. These scenarios differ in the way that information becomes available to individuals because the parents often have information on mating partners while they are making sex allocation decisions, but must make these decisions before brood mortality takes place. This makes it possible to test which mechanism, stochastic mortality or variation in mating partners, is responsible for observed sex ratios. Alternatively, asymmetric variance between sexual functions can cause skewed sex allocation, even in the absence of local mate competition. This allows the evolution of either female- or male-biased sex ratios depending on which sexual function is more variable.

Animals↗
PubMed1995

Computer-aided studies on the spatial structure of the small hepatitis B surface protein.

Hepatitis B surface proteins play a central role in the assembly of the virus and in the infection of the host cells. Whereas some functional aspects of the proteins have been studied in detail, little is known about their structure. Since X-ray analysis of these proteins appear unlikely in the near future, we chose to use a variety of computer-aided methods to improve the model for the major surface protein (SHBs). We here describe the model, discuss it in light of current results in the literature and discuss new functional implications of SHBs.

Computer Simulation↗
PubMed2005

A phenomenological theory of spatially structured local synaptic connectivity.

The structure of local synaptic circuits is the key to understanding cortical function and how neuronal functional modules such as cortical columns are formed. The central problem in deciphering cortical microcircuits is the quantification of synaptic connectivity between neuron pairs. I present a theoretical model that accounts for the axon and dendrite morphologies of pre- and postsynaptic cells and provides the average number of synaptic contacts formed between them as a function of their relative locations in three-dimensional space. An important aspect of the current approach is the representation of a complex structure of an axonal/dendritic arbor as a superposition of basic structures-synaptic clouds. Each cloud has three structural parameters that can be directly estimated from two-dimensional drawings of the underlying arbor. Using empirical data available in literature, I applied this theory to three morphologically different types of cell pairs. I found that, within a wide range of cell separations, the theory is in very good agreement with empirical data on (i) axonal-dendritic contacts of pyramidal cells and (ii) somatic synapses formed by the axons of inhibitory interneurons. Since for many types of neurons plane arborization drawings are available from literature, this theory can provide a practical means for quantitatively deriving local synaptic circuits based on the actual observed densities of specific types of neurons and their morphologies. It can also have significant implications for computational models of cortical networks by making it possible to wire up simulated neural networks in a realistic fashion.

Journal Article↗