Échelles longue et courte | EPFL Graph Search

L'échelle longue et l'échelle courte sont deux systèmes incompatibles de noms des grands nombres, tous deux utilisés dans une grande partie du monde actuel, utilisant pour bases respectivement le million et le millier. L’échelle longue (ou échelle de Chuquet) est le système dans lequel un billion représente un million de millions, ou mille milliards (10), et l’échelle courte est le système dans lequel un billion représente un millier de millions (10), ou un milliard. Dans l'échelle courte, la terminaison est toujours ion (à l'exception de mille), tandis que l'échelle longue alterne entre -ion et -iard. Pour éviter la confusion qui résulte de la coexistence des deux échelles dans certaines langues, le Système international d'unités (SI) recommande l'utilisation de ses préfixes, qui conservent la même signification quels que soient le pays et la langue. Les échelles longue et courte restent utilisées de facto pour compter la monnaie. Dans ses traductions, l'Union européenne utilise

Finite element modeling of dynamic frictional rupture with rate and state friction

Fabian Barras, Michael Ludovic Brun, Jean-François Molinari, Roozbeh Rezakhani

Numerous laboratory experiments have demonstrated the dependence of the friction coefficient on the interfacial slip rate and the contact history, a behavior generically called rate and state friction. Although numerical models have been widely used for analyzing rate and state friction, in general they consider infinite elastic domains surrounding the sliding interface and rely on boundary integral formulations. Much less work has been dedicated to modeling finite size systems to account for interactions with boundaries. This paper investigates rate and state frictional interfaces in the context of finite size systems with the finite element method in explicit dynamics. It is shown that due to the highly non-linear nature of rate and state friction and its sensitivity to numerical noise, the time integration step to achieve an accurate steady state solution is orders of magnitude smaller compared to the stable time step required in boundary integral formulations. We provide evidence that the noise, which is source of instability in the finite element solution, originates from internal discretization nodes. We then investigate the long term behavior of the sliding interface for two different friction laws: a velocity weakening law, for which the friction monotonously decreases with increasing sliding velocity, and a velocity weakening-strengthening law, for which the friction coefficient first decreases but then increases above a critical velocity. We show that for both friction laws at finite times, that is before wave reflections from the boundaries come back to the sliding interface, a temporary steady state sliding is reached, with a well-defined stress drop at the interface. This stress drop gives rise to a stress concentration and leads to an analogy between friction and fracture. However, at longer times, that is after multiple wave reflections, the stress drop is essentially zero, resulting in losing the analogy with fracture mechanics. Finally, the simulations with applied constant traction boundary conditions reveal that velocity weakening is unstable at long time scales, as it results in an acceleration of the sliding blocks. On the other hand, velocity weakening-strengthening reaches a steady state sliding configuration. (C) 2020 Elsevier Ltd. All rights reserved.

PERGAMON-ELSEVIER SCIENCE LTD2020

Optical Coherence Correlation Spectroscopy

Stéphane Broillet

Questions such as biomolecular interactions, kinetics of enzymes, DNA conformational changes, cellular structures properties (among others) are addressed by characterizing the biological function of molecules. This function depends on their structure and their dynamic properties, and are usually studied with optical labels. A widely used technique for that purpose is fluorescence correlation spectroscopy (FCS) that adopts fluorophores as reporters of dynamic processes. However, photobleaching limits the observation time on the one hand, and saturation at high excitation intensities imposes constraints for the study of fast molecular processes on the other hand. Gold nanoparticles (NPs) are labels of particular interest to overcome these drawbacks due to their photostability, low cytotoxicity and their availability with biocompatible surface coatings. In addition, NPs have found widespread application in life sciences and medicine, such as labels for optical imaging, carriers for drug and gene delivery, targets for cancer cell imaging and phototherapy, and contrast agent for magnetic resonance imaging (MRI). These applications all require methods to characterize their behaviour in a biological environment. Medical use of NPs usually requires intravenous injection. Once NPs are introduced into the blood stream they become exposed to biomolecules in the plasma that form a so-called protein corona. Obviously, knowledge about this interaction is needed for a safe medical application of NPs. The uptake of NPs by cells depends mainly on this protein corona. It is thus very important to understand the structural and dynamic properties of the protein corona at the molecular level to judge the fate of NPs in the human body prior to clinical studies. We introduce Optical Coherence Correlation Spectroscopy (OCCS) which exploits the backscattered light of NPs illuminated by a broadband light source. Due to the measurement of a scattering signal, OCCS gives access to long time scales that are hardly accessible with FCS experiments. The signal acquisition is similar to Fourier-domain optical coherence microscopy (FDOCM) with a dark-field contrast. We present the theory of OCCS based on auto-correlation analysis. Numerical simulations were used to estimate the performance of our new spectroscopy method and to build an analytical model for the auto-correlation function for measuring the diffusion coefficient and concentration of NPs in solution. An application to the study of the protein corona on NPs is presented. The hydrodynamic radius of superparamagnetic iron oxide nanoparticles (SPIONs) with adsorbed bovine serum albumin (BSA) is measured under physiological conditions using OCCS.We also aimed at improving the detection of these NPs in highly scattering environments, for instance inside a cell. Photothermal optical lock-in OCCS (poli-OCCS) is proposed, which exploits the absorption properties of gold NPs to generate a specific signal due to the photothermal effect. Poli-OCCS is introduced and first proof-of-principle measurements with gold NPs are presented.

EPFL2014

Continuous attractor working memory and provenance of channel models

Alexander Kevin Seeholzer

The brain is a complex biological system composed of a multitude of microscopic processes, which together give rise to computational abilities observed in everyday behavior. Neuronal modeling, consisting of models of single neurons and neuronal networks at varying levels of biological detail, can synthesize the gaps currently hard to constrain in experiments and provide mechanistic explanations of how these computations might arise. In this thesis, I present two parallel lines of research on neuronal modeling, situated at varying levels of biological detail. First, I assess the provenance of voltage-gated ion channel models in an integrative meta-analysis that investigates a backlog of nearly 50 years of published research. To cope with the ever-increasing volume of research produced in the field of neuroscience, we need to develop methods for the systematic assessment and comparison of published work. As we demonstrate, neuronal models offer the intriguing possibility of performing automated quantitative analyses across studies, by standardized simulated experiments. We developed protocols for the quantitative comparison of voltage-gated ion channels, and applied them to a large body of published models, allowing us to assess the variety and temporal development of different models for the same ion channels over the time scale of years of research. Beyond a systematic classification of the existing body of research made available in an online platform, we show that our approach extends to large-scale comparisons of ion channel models to experimental data, thereby facilitating field-wide standardization of experimentally-constrained modeling. Second, I investigate neuronal models of working memory (WM). How can cortical networks bridge the short time scales of their microscopic components, which operate on the order of milliseconds, to the behaviorally relevant time scales of seconds observed in WM experiments? I consider here a candidate model: continuous attractor networks. These can implement WM for a continuum of possible spatial locations over several seconds and have been proposed for the organization of prefrontal cortical networks. I first present a novel method for the efficient prediction of the network-wide steady states from the underlying microscopic network properties. The method can be applied to predict and tune the "bump" shapes of continuous attractors implemented in networks of spiking neuron models connected by nonlinear synapses, which we demonstrate for saturating synapses involving NMDA receptors. In a second part, I investigate the computational role of short-term synaptic plasticity as a synaptic nonlinearity. Continuous attractor models are sensitive to the inevitable variability of biological neurons: variable neuronal firing and heterogeneous networks decrease the time that memories are accurately retained, eventually leading to a loss of memory functionality on behaviorally relevant time scales. In theory and simulations, I show that short-term plasticity can control the time scale of memory retention, with facilitation and depression playing antagonistic roles in controlling the drift and diffusion of locations in memory. Finally, we place quantitative constraints on the combination of synaptic and network parameters under which continuous attractors networks can implement reliable WM in cortical settings.

EPFL2017