Effects on semiflexible polymer dynamics

The influence of hydrodynamic screening near a surface on the dynamics of a single semiflexible polymer is studied by means of Brownian dynamics simulations and hydrodynamicmean field theory. The polymer motion is characterized in terms of the mean squared displacements of the end-monomers, the end-to-end vector, and the scalar end-to-end distance. In order to control hydrodynamic screening effects, the polymer is confined to a plane at a fixed separation from the wall. When gradually decreasing this separation, a crossover from Zimm-type towards Rouse (free-draining) polymerdynamics is induced. However, this crossover is rather slow and the free-draining limit is not completely reached—substantial deviations from Rouse-like dynamics are registered in both simulations and theory—even at distances of the polymer from the wall on the order of the monomer size. Remarkably, the effect of surface-induced screening of hydrodynamic interactions sensitively depends on the type of dynamic observable considered. For vectorial quantities such as the end-to-end vector, hydrodynamic interactions are important and therefore surface screening effects are sizeable. For a scalar quantity such as the end- to-end distance, on the other hand, hydrodynamic interactions are less important, but a pronounced dependence of dynamic scaling exponents on the persistence length to contour length ratio becomes noticeable. Our findings are discussed against the background of single-molecule experiments on f-actin [L. Le Goff et al., Phys. Rev. Lett.89, 258101 (2002)]10.1103/PhysRevLett.89.258101

Anomalous Anisotropic Diffusion Dynamics of Hydration Water at Lipid Membranes

The diffusional water dynamics in the hydration layer of a dipalmitoylphosphatidylcholine bilayer is studied using molecular dynamics simulations. By mapping the perpendicular water motion on the ordinary diffusion equation, we disentangle free energetic and friction effects and show that perpendicular diffusion is strongly reduced. The lateral water motion exhibits anomalous diffusion up to several nanoseconds and is characterized by even further decreased diffusion coefficients, which by comparison with coarse grained simulations are explained by the transient corrugated effective free energy landscape imposed by the lipids. This is in contrast to homogenous surfaces, where boundary hydrodynamic theory quantitatively predicts the anisotropy of water diffusion

Modélisation numérique du laminage à pas de pèlerin de tubes ODS en vu de limiter les risques d'endommagement

National audiencePour les Réacteurs à Neutrons Rapides au sodium, les matériaux de gainage de référence pour les très forts taux de combustion sont les nuances ferritiques/martensitiques ODS. Ces matériaux présentent en effet des bonnes propriétés en fluage, en résilience et en résistance à l'oxydation. Toutefois la présence des oxydes ODS font de ces nuances des matériaux très difficiles à mettre en forme. Classiquement le tube de gainage est mis en forme à froid à partir d'une ébauche tubulaire par une succession de passes de laminage à pas de pèlerin et de traitements thermiques. Dans le cadre de cette étude la modélisation numérique du procédé de laminage dans une configuration de type HPTR a été entreprise. Le modèle prend en compte toute la complexité des phénomènes physiques, mécaniques ainsi que le modèle de comportement du matériau pour simuler les déformations élastoplastiques cycliques qui apparaissent au cours de la mise forme des tubes minces. La modélisation de la cinématique du procédé a déjà été réalisée. L'utilisation de capteurs numériques pour suivre le chemin de déformation de la matière lors du procédé permet d'estimer la nature et l'amplitude des déformations cycliques subies

DNA-Protein Binding Rates: Bending Fluctuation and Hydrodynamic Coupling Effects

We investigate diffusion-limited reactions between a diffusing particle and a target site on a semiflexible polymer, a key factor determining the kinetics of DNA-protein binding and polymerization of cytoskeletal filaments. Our theory focuses on two competing effects: polymer shape fluctuations, which speed up association, and the hydrodynamic coupling between the diffusing particle and the chain, which slows down association. Polymer bending fluctuations are described using a mean field dynamical theory, while the hydrodynamic coupling between polymer and particle is incorporated through a simple heuristic approximation. Both of these we validate through comparison with Brownian dynamics simulations. Neither of the effects has been fully considered before in the biophysical context, and we show they are necessary to form accurate estimates of reaction processes. The association rate depends on the stiffness of the polymer and the particle size, exhibiting a maximum for intermediate persistence length and a minimum for intermediate particle radius. In the parameter range relevant to DNA-protein binding, the rate increase is up to 100% compared to the Smoluchowski result for simple center-of-mass motion. The quantitative predictions made by the theory can be tested experimentally.Comment: 21 pages, 11 figures, 1 tabl

Auto- and cross-power spectral analysis of dual trap optical tweezer experiments using Bayesian inference

The thermal fluctuations of micron-sized beads in dual trap optical tweezer experiments contain complete dynamic information about the viscoelastic properties of the embedding medium and—if present—macromolecular constructs connecting the two beads. To quantitatively interpret the spectral properties of the measured signals, a detailed understanding of the instrumental characteristics is required. To this end, we present a theoretical description of the signal processing in a typical dual trap optical tweezer experiment accounting for polarization crosstalk and instrumental noise and discuss the effect of finite statistics. To infer the unknown parameters from experimental data, a maximum likelihood method based on the statistical properties of the stochastic signals is derived. In a first step, the method can be used for calibration purposes: We propose a scheme involving three consecutive measurements (both traps empty, first one occupied and second empty, and vice versa), by which all instrumental and physical parameters of the setup are determined. We test our approach for a simple model system, namely a pair of unconnected, but hydrodynamically interacting spheres. The comparison to theoretical predictions based on instantaneous as well as retarded hydrodynamics emphasizes the importance of hydrodynamic retardation effects due to vorticity diffusion in the fluid. For more complex experimental scenarios, where macromolecular constructs are tethered between the two beads, the same maximum likelihood method in conjunction with dynamic deconvolution theory will in a second step allow one to determine the viscoelastic properties of the tethered element connecting the two beads

Finite element simulation of cold pilgering of ODS tubes

International audienceThe oxide dispersion strengthened (ODS) ferritic and martensitic steels are candidate cladding materials for the new fast-neutron sodium-cooled Generation IV reactors. Typically the cladding is cold formed by a sequence of cold pilger rolling passes with intermediate heat treatments. Cracking risk prediction in pilgering is linked to the choice of an appropriate constitutive model for modeling the process. Consequently, this work aims to assess the impact of the constitutive laws on cracking risk development in pilgering conditions

Symbiont identity matters: carbon and phosphorus fluxes between Medicago truncatula and different arbuscular mycorrhizal fungi

Many studies have scrutinized the nutritional benefits of arbuscular mycorrhizal associations to their host plants, while the carbon (C) balance of the symbiosis has often been neglected. Here, we present quantification of both the C costs and the phosphorus (P) uptake benefits of mycorrhizal association between barrel medic (Medicago truncatula) and three arbuscular mycorrhizal fungal species, namely Glomus intraradices, Glomus claroideum, and Gigaspora margarita. Plant growth, P uptake and C allocation were assessed 7weeks after sowing by comparing inoculated plants with their non-mycorrhizal counterparts, supplemented with different amounts of P. Isotope tracing (33P and 13C) was used to quantify both the mycorrhizal benefits and the costs, respectively. G. intraradices supported greatest plant P acquisition and incurred high C costs, which lead to similar plant growth benefits as inoculation with G. claroideum, which was less efficient in supporting plant P acquisition, but also required less C. G. margarita imposed large C requirement on the host plant and provided negligible P uptake benefits. However, it did not significantly reduce plant growth due to sink strength stimulation of plant photosynthesis. A simple experimental system such as the one established here should allow quantification of mycorrhizal costs and benefits routinely on a large number of experimental units. This is necessary for rapid progress in assessment of C fluxes between the plants and different mycorrhizal fungi or fungal communities, and for understanding the dynamics between mutualism and parasitism in mycorrhizal symbiose

Size dependence of efficiency of PbS quantum dots in NiO-based dye sensitised solar cells and mechanistic charge transfer investigation

Quantum dots (QDs) are very attractive materials for solar cells due to their high absorption coefficients, size dependence and easy tunability of their optical and electronic properties due to quantum confinement. Particularly interesting are the PbS QDs owing to their broad spectral absorption until the long wavelengths, their easy processability and low cost. Here, we used control of the PbS QDs size to understand charge transfer processes at the interfaces of NiO semiconductor and explain the optimal QDs size in photovoltaic devices. Towards this goal, we have synthesized a series of PbS QDs with different diameters (2.8 A until 4A) and investigated charge transfer dynamics by time resolved spectroscopy and their ability to act as sensitizers in nanocrystalline NiO based solar cells using the cobalt tris(4,4'-diterbutyl-2,2'-bipyridine) complex as redox mediator. We found that PbS QDs with average diameter of 3.0 nm are optimal size in terms of efficient charge transfers and light harvesting efficiency for photovoltaic performances. Our study showed that an hole injection from PbS QDs to NiO valence band (VB) is an efficient process even with low injection driving force (0.3 eV) and occurs in 6-10 ns. Furthermore we found that the direct electrolyte reduction (photoinduced electron transfer to the cobalt redox mediator) also occurs in parallel to the hole injection with rate constant of similar magnitude (10-20 ns). In spite of its large driving force, the rate constant of the oxidative quenching of PbS by Co(III) diminishes more steeply than hole injection on NiO when the diameter of PbS increases. This is understood as the consequence of increasing the trap states that limit electron shift. We believe that our detailed findings will advance the future design of QD sensitized photocathodes. © 2017, Royal Society of Chemistry. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at / https://doi.org/10.1039/C7NR03698

EmoNets: Multimodal deep learning approaches for emotion recognition in video

The task of the emotion recognition in the wild (EmotiW) Challenge is to assign one of seven emotions to short video clips extracted from Hollywood style movies. The videos depict acted-out emotions under realistic conditions with a large degree of variation in attributes such as pose and illumination, making it worthwhile to explore approaches which consider combinations of features from multiple modalities for label assignment. In this paper we present our approach to learning several specialist models using deep learning techniques, each focusing on one modality. Among these are a convolutional neural network, focusing on capturing visual information in detected faces, a deep belief net focusing on the representation of the audio stream, a K-Means based "bag-of-mouths" model, which extracts visual features around the mouth region and a relational autoencoder, which addresses spatio-temporal aspects of videos. We explore multiple methods for the combination of cues from these modalities into one common classifier. This achieves a considerably greater accuracy than predictions from our strongest single-modality classifier. Our method was the winning submission in the 2013 EmotiW challenge and achieved a test set accuracy of 47.67% on the 2014 dataset