Elasto-plastic response of reversibly crosslinked biopolymer bundles

We study the response of F-actin bundles to driving forces through a simple analytical model. We consider two filaments connected by reversibly bound crosslinks and driven by an external force. Two failure modes under load can be defined. \textit{Brittle failure} is observed when crosslinks suddenly and collectively unbind, leading to catastrophic loss of bundle integrity. During \textit{ductile failure}, on the other hand, bundle integrity is maintained, however at the cost of crosslink reorganization and defect formation. We present phase diagrams for the onset of failure, highlighting the importance of the crosslink stiffness for these processes. Crossing the phase boundaries, force-deflection curves display (frequency-dependent) hysteresis loops, reflecting the first-order character of the failure processes. We evidence how the introduction of defects can lead to complex elasto-plastic relaxation processes, once the force is switched off. Depending on, both, the time-scale for defect motion as well as the crosslink stiffness, bundles can remain in a quasi-permanent plastically deformed state for a very long time.Comment: 9 pages, 15 figure

BRAHMS: Novel middleware for integrated systems computation

Biological computational modellers are becoming increasingly interested in building large, eclectic models, including components on many different computational substrates, both biological and non-biological. At the same time, the rise of the philosophy of embodied modelling is generating a need to deploy biological models as controllers for robots in real-world environments. Finally, robotics engineers are beginning to find value in seconding biomimetic control strategies for use on practical robots. Together with the ubiquitous desire to make good on past software development effort, these trends are throwing up new challenges of intellectual and technological integration (for example across scales, across disciplines, and even across time) - challenges that are unmet by existing software frameworks. Here, we outline these challenges in detail, and go on to describe a newly developed software framework, BRAHMS. that meets them. BRAHMS is a tool for integrating computational process modules into a viable, computable system: its generality and flexibility facilitate integration across barriers, such as those described above, in a coherent and effective way. We go on to describe several cases where BRAHMS has been successfully deployed in practical situations. We also show excellent performance in comparison with a monolithic development approach. Additional benefits of developing in the framework include source code self-documentation, automatic coarse-grained parallelisation, cross-language integration, data logging, performance monitoring, and will include dynamic load-balancing and 'pause and continue' execution. BRAHMS is built on the nascent, and similarly general purpose, model markup language, SystemML. This will, in future, also facilitate repeatability and accountability (same answers ten years from now), transparent automatic software distribution, and interfacing with other SystemML tools. (C) 2009 Elsevier Ltd. All rights reserved

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

KInNeSS: A Modular Framework for Computational Neuroscience

Making use of very detailed neurophysiological, anatomical, and behavioral data to build biological-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalabiltiy, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multu-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions of ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further developement of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effecitively collaborate using a modern neural simulation platform.Center for Excellence for Learning Education, Science, and Technology (SBE-0354378); Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

Simulating Astro-H Observations of Sloshing Gas Motions in the Cores of Galaxy Clusters

Astro-H will be the first X-ray observatory to employ a high-resolution microcalorimeter, capable of measuring the shift and width of individual spectral lines to the precision necessary for estimating the velocity of the diffuse plasma in galaxy clusters. This new capability is expected to bring significant progress in understanding the dynamics, and therefore the physics, of the intracluster medium. However, because this plasma is optically thin, projection effects will be an important complicating factor in interpreting future Astro-H measurements. To study these effects in detail, we performed an analysis of the velocity field from simulations of a galaxy cluster experiencing gas sloshing, and generated synthetic X-ray spectra, convolved with model Astro-H Soft X-ray Spectrometer (SXS) responses. We find that the sloshing motions produce velocity signatures that will be observable by Astro-H in nearby clusters: the shifting of the line centroid produced by the fast-moving cold gas underneath the front surface, and line broadening produced by the smooth variation of this motion along the line of sight. The line shapes arising from inviscid or strongly viscous simulations are very similar, indicating that placing constraints on the gas viscosity from these measurements will be difficult. Our spectroscopic analysis demonstrates that, for adequate exposures, Astro-H will be able to recover the first two moments of the velocity distribution of these motions accurately, and in some cases multiple velocity components may be discerned. The simulations also confirm the importance of accurate treatment of PSF scattering in the interpretation of Astro-H/SXS spectra of cluster plasmas.Comment: 27 pages, 20 figures, submitted to the Astrophysical Journa

Galacticus: A Semi-Analytic Model of Galaxy Formation

We describe a new, free and open source semi-analytic model of galaxy formation, Galacticus. The Galacticus model was designed to be highly modular to facilitate expansion and the exploration of alternative descriptions of key physical ingredients. We detail the Galacticus engine for evolving galaxies through a merging hierarchy of dark matter halos and give details of the specific implementations of physics currently available in Galacticus. Finally, we show results from an example model that is in reasonably good agreement with several observational datasets. We use this model to explore numerical convergence and to demonstrate the types of information which can be extracted from Galacticus.Comment: 35 pages, submitted to New Astronom