Foraging at the Edge of Chaos: Internal Clock versus External Forcing

Activity rhythms in animal groups arise both from external changes in the environment, as well as from internal group dynamics. These cycles are reminiscent of physical and chemical systems with quasiperiodic and even chaotic behavior resulting from “autocatalytic” mechanisms. We use nonlinear differential equations to model how the coupling between the self-excitatory interactions of individuals and external forcing can produce four different types of activity rhythms: quasiperiodic, chaotic, phase locked, and displaying over or under shooting. At the transition between quasiperiodic and chaotic regimes, activity cycles are asymmetrical, with rapid activity increases and slower decreases and a phase shift between external forcing and activity. We find similar activity patterns in ant colonies in response to varying temperature during the day. Thus foraging ants operate in a region of quasiperiodicity close to a cascade of transitions leading to chaos. The model suggests that a wide range of temporal structures and irregularities seen in the activity of animal and human groups might be accounted for by the coupling between collectively generated internal clocks and external forcings.

A fuzzified systematic adjustment of the robotic Darwinian PSO

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization using natural selection to enhance the ability to escape from sub-optimal solutions. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots, hence decreasing the amount of required information exchange among robots. This paper further extends the previously proposed algorithm adapting the behavior of robots based on a set of context-based evaluation metrics. Those metrics are then used as inputs of a fuzzy system so as to systematically adjust the RDPSO parameters (i.e., outputs of the fuzzy system), thus improving its convergence rate, susceptibility to obstacles and communication constraints. The adapted RDPSO is evaluated in groups of physical robots, being further explored using larger populations of simulated mobile robots within a larger scenario.

Rapid Evolution of the Sequences and Gene Repertoires

Proteins secreted to the extracellular environment or to the periphery of the cell envelope, the secretome, play essential roles in foraging, antagonistic and mutualistic interactions. We hypothesize that arms races, genetic conflicts and varying selective pressures should lead to the rapid change of sequences and gene repertoires of the secretome. The analysis of 42 bacterial pan-genomes shows that secreted, and especially extracellular proteins, are predominantly encoded in the accessory genome, i.e. among genes not ubiquitous within the clade. Genes encoding outer membrane proteins might engage more frequently in intra-chromosomal gene conversion because they are more often in multi-genic families. The gene sequences encoding the secretome evolve faster than the rest of the genome and in particular at non-synonymous positions. Cell wall proteins in Firmicutes evolve particularly fast when compared with outer membrane proteins of Proteobacteria. Virulence factors are over-represented in the secretome, notably in outer membrane proteins, but cell localization explains more of the variance in substitution rates and gene repertoires than sequence homology to known virulence factors. Accordingly, the repertoires and sequences of the genes encoding the secretome change fast in the clades of obligatory and facultative pathogens and also in the clades of mutualists and free-living bacteria. Our study shows that cell localization shapes genome evolution. In agreement with our hypothesis, the repertoires and the sequences of genes encoding secreted proteins evolve fast. The particularly rapid change of extracellular proteins suggests that these public goods are key players in bacterial adaptation.