Boundary conditions in local electrostatics algorithms

We study the simulation of charged systems in the presence of general boundary conditions in a local Monte Carlo algorithm based on a constrained electric field. We firstly show how to implement constant-potential, Dirichlet, boundary conditions by introducing extra Monte Carlo moves to the algorithm. Secondly, we show the interest of the algorithm for studying systems which require anisotropic electrostatic boundary conditions for simulating planar geometries such as membranes.Comment: 8 pages, 6 figures, accepted in JC

Simulating nanoscale dielectric response

We introduce a constrained energy functional to describe dielectric response. We demonstrate that the local functional is a generalization of the long ranged Marcus energy. Our re-formulation is used to implement a cluster Monte Carlo algorithm for the simulation of dielectric media. The algorithm avoids solving the Poisson equation and remains efficient in the presence of spatial heterogeneity, nonlinearity and scale dependent dielectric properties.Comment: 4 pages, 2 figures. Revtex

Anisotropic elasticity in confocal studies of colloidal crystals

We consider the theory of fluctuations of a colloidal solid observed in a confocal slice. For a cubic crystal we study the evolution of the projected elastic properties as a function of the anisotropy of the crystal using numerical methods based on the fast Fourier transform. In certain situations of high symmetry we find exact analytic results for the projected fluctuations.Comment: 6 pages, 7 figure

Local Simulation Algorithms for Coulombic Interactions

We consider dynamically constrained Monte-Carlo dynamics and show that this leads to the generation of long ranged effective interactions. This allows us to construct a local algorithm for the simulation of charged systems without ever having to evaluate pair potentials or solve the Poisson equation. We discuss a simple implementation of a charged lattice gas as well as more elaborate off-lattice versions of the algorithm. There are analogies between our formulation of electrostatics and the bosonic Hubbard model in the phase approximation. Cluster methods developed for this model further improve the efficiency of the electrostatics algorithm.Comment: Proceedings Statphys22 10 page

Academic team formation as evolving hypergraphs

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions

Molecular Tools for Monitoring the Ecological Sustainability of a Stone Bio-Consolidation Treatment at the Royal Chapel, Granada

Background: Biomineralization processes have recently been applied in situ to protect and consolidate decayed ornamental stone of the Royal Chapel in Granada (Spain). While this promising method has demonstrated its efficacy regarding strengthening of the stone, little is known about its ecological sustainability.Methodology/Principal Findings: Here, we report molecular monitoring of the stone-autochthonous microbiota before and at 5, 12 and 30 months after the bio-consolidation treatment (medium/long-term monitoring), employing the well-known molecular strategy of DGGE analyses. Before the bio-consolidation treatment, the bacterial diversity showed the exclusive dominance of Actinobacteria (100%), which decreased in the community (44.2%) after 5 months, and Gamma-proteobacteria (30.24%) and Chloroflexi (25.56%) appeared. After 12 months, Gamma-proteobacteria vanished from the community and Cyanobacteria (22.1%) appeared and remained dominant after thirty months, when the microbiota consisted of Actinobacteria (42.2%) and Cyanobacteria (57.8%) only. Fungal diversity showed that the Ascomycota phylum was dominant before treatment (100%), while, after five months, Basidiomycota (6.38%) appeared on the stone, and vanished again after twelve months. Thirty months after the treatment, the fungal population started to stabilize and Ascomycota dominated on the stone (83.33%) once again. Members of green algae (Chlorophyta, Viridiplantae) appeared on the stone at 5, 12 and 30 months after the treatment and accounted for 4.25%, 84.77% and 16.77%, respectively.Conclusions: The results clearly show that, although a temporary shift in the bacterial and fungal diversity was observed during the first five months, most probably promoted by the application of the bio-consolidation treatment, the microbiota tends to regain its initial stability in a few months. Thus, the treatment does not seem to have any negative side effects on the stone-autochthonous microbiota over that time. The molecular strategy employed here is suggested as an efficient monitoring tool to assess the impact on the stone-autochthonous microbiota of the application of biomineralization processes as a restoration/conservation procedure.This work was supported by the European Regional Development Fund (ERDF), Junta de Andalucía (Spain) and the “Fortalecimiento de la I+D+i” program from the University of Granada, co-financed by grant RNM-3493 and Research Group BIO-103 from Junta de Andalucía, as well as by the Spanish Government through “José Castillejo” program from the “Ministerio de Educación, Cultura y Deporte” (I+D+i 2008-2011), and by the Austrian Science Fund (FWF) under Grant “Elise-Richter V194-B20”