Spontaneous structure formation in a network of chaotic units with variable connection strengths

As a model of temporally evolving networks, we consider a globally coupled logistic map with variable connection weights. The model exhibits self-organization of network structure, reflected by the collective behavior of units. Structural order emerges even without any inter-unit synchronization of dynamics. Within this structure, units spontaneously separate into two groups whose distinguishing feature is that the first group possesses many outwardly-directed connections to the second group, while the second group possesses only few outwardly-directed connections to the first. The relevance of the results to structure formation in neural networks is briefly discussed.Comment: 4 pages, 3 figures, REVTe

African vegetable diversity in the limelight: project activities by ProNIVA.

Poster presented at Botanical Congress. Hamburg (Germany), 3-7 Sep 200

Simple Lattice-Models of Ion Conduction: Counter Ion Model vs. Random Energy Model

The role of Coulomb interaction between the mobile particles in ionic conductors is still under debate. To clarify this aspect we perform Monte Carlo simulations on two simple lattice models (Counter Ion Model and Random Energy Model) which contain Coulomb interaction between the positively charged mobile particles, moving on a static disordered energy landscape. We find that the nature of static disorder plays an important role if one wishes to explore the impact of Coulomb interaction on the microscopic dynamics. This Coulomb type interaction impedes the dynamics in the Random Energy Model, but enhances dynamics in the Counter Ion Model in the relevant parameter range.Comment: To be published in Phys. Rev.

Improved feeding and forages at a crossroads: Farming systems approaches for sustainable livestock development in East Africa

Dairy development provides substantial potential economic opportunities for smallholder farmers in East Africa, but productivity is constrained by the scarcity of quantity and quality feed. Ruminant livestock production is also associated with negative environmental impacts, including greenhouse gas (GHG) emissions, air pollution, high water consumption, land-use change, and loss of biodiversity. Improved livestock feeding and forages have been highlighted as key entry point to sustainable intensification, increasing food security, and decreasing environmental trade-offs including GHG emission intensities. In this perspective article, we argue that farming systems approaches are essential to understand the multiple roles and impacts of forages in smallholder livelihoods. First, we outline the unique position of forages in crop-livestock systems and systemic obstacles to adoption that call for multidisciplinary thinking. Second, we discuss the importance of matching forage technologies with agroecological and socioeconomic contexts and niches, and systems agronomy that is required. Third, we demonstrate the usefulness of farming systems modeling to estimate multidimensional impacts of forages and for reducing agro-environmental trade-offs. We conclude that improved forages in East Africa are at a crossroads: if adopted by farmers at scale, they can be a cornerstone of pathways toward sustainable livestock systems in East Africa.</p

A Survey on Continuous Time Computations

We provide an overview of theories of continuous time computation. These theories allow us to understand both the hardness of questions related to continuous time dynamical systems and the computational power of continuous time analog models. We survey the existing models, summarizing results, and point to relevant references in the literature

Hopping Transport in the Presence of Site Energy Disorder: Temperature and Concentration Scaling of Conductivity Spectra

Recent measurements on ion conducting glasses have revealed that conductivity spectra for various temperatures and ionic concentrations can be superimposed onto a common master curve by an appropriate rescaling of the conductivity and frequency. In order to understand the origin of the observed scaling behavior, we investigate by Monte Carlo simulations the diffusion of particles in a lattice with site energy disorder for a wide range of both temperatures and concentrations. While the model can account for the changes in ionic activation energies upon changing the concentration, it in general yields conductivity spectra that exhibit no scaling behavior. However, for typical concentrations and sufficiently low temperatures, a fairly good data collapse is obtained analogous to that found in experiment.Comment: 6 pages, 4 figure

Turing degrees of limit sets of cellular automata

Cellular automata are discrete dynamical systems and a model of computation. The limit set of a cellular automaton consists of the configurations having an infinite sequence of preimages. It is well known that these always contain a computable point and that any non-trivial property on them is undecidable. We go one step further in this article by giving a full characterization of the sets of Turing degrees of cellular automata: they are the same as the sets of Turing degrees of effectively closed sets containing a computable point