Microfabricated rubber microscope using soft solid immersion lenses

We show here a technique of soft lithography to microfabricate efficient solid immersion lenses (SIL) out of rubber elastomers. The light collection efficiency of a lens system is described by its numerical aperture (NA), and is critical for applications as epifluorescence microscopy [B. Herman, Fluorescence Microscopy (BIOS Scientific, Oxford/Springer, United Kingdom, 1998). While most simple lens systems have numerical apertures less than 1, the lenses described here have NA=1.25. Better performance can be engineered though the use of compound designs; we used this principle to make compound solid immersion lenses (NA=1.32). An important application of these lenses will be as integrated optics for microfluidic devices. We incorporated them into a handheld rubber microscope for microfluidic flow cytometry and imaged single E. Coli cells by fluorescence

Probing dark energy models with extreme pairwise velocities of galaxy clusters from the DEUS-FUR simulations

Observations of colliding galaxy clusters with high relative velocity probe the tail of the halo pairwise velocity distribution with the potential of providing a powerful test of cosmology. As an example it has been argued that the discovery of the Bullet Cluster challenges standard $\Lambda$CDM model predictions. Halo catalogs from N-body simulations have been used to estimate the probability of Bullet-like clusters. However, due to simulation volume effects previous studies had to rely on a Gaussian extrapolation of the pairwise velocity distribution to high velocities. Here, we perform a detail analysis using the halo catalogs from the Dark Energy Universe Simulation Full Universe Runs (DEUS-FUR), which enables us to resolve the high-velocity tail of the distribution and study its dependence on the halo mass definition, redshift and cosmology. Building upon these results we estimate the probability of Bullet-like systems in the framework of Extreme Value Statistics. We show that the tail of extreme pairwise velocities significantly deviates from that of a Gaussian, moreover it carries an imprint of the underlying cosmology. We find the Bullet Cluster probability to be two orders of magnitude larger than previous estimates, thus easing the tension with the $\Lambda$CDM model. Finally, the comparison of the inferred probabilities for the different DEUS-FUR cosmologies suggests that observations of extreme interacting clusters can provide constraints on dark energy models complementary to standard cosmological tests.Comment: Submitted to MNRAS, 15 pages, 12 figures, 3 table

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

A NMR and molecular dynamics study of CO2-bearing basaltic melts and glasses

International audienceThe presence of volatile, especially carbon dioxide (CO2), in silicate liquids is considered as a key parameter to magmatic degassing and eruptive processes. Unfortunately, due to experimental difficulties, our current knowledge on the CO2 effect on silicate melt structure is weak and relies on the observation of ex-situ recovered CO2-bearing glasses.In the present work, we confront the results obtained from NMR spectroscopic observations of glass synthesised at pressure between 0.5 and 3.0 GPa and theoretical investigations from first-principles molecular dynamics (FPMD) simulations conducted at 5.0 and 8.0 GPa on high temperature melt for a simplified basaltic composition.The results obtained on the aluminosilicate framework (molar fraction of silicon species and Al average coordination number) suggest that both ex-situ and in-situ results compare adequately. The results are in agreement with our current knowledge on the change in aluminosilicate melt/glass structure with changing intensive conditions. Increasing pressure from 0.5 to 8.0 GPa induces 1) an increase in the average Al coordination number from 4.1 to almost 5.0 and 2) an increase in the degree of polymerisation with NBO/Si changing from 1.30 to 0.80.The presence of CO2 does not seem to induce a dramatic change on both the average Al coordination number and the NBO/Si. FPMD simulations performed with 0 and 20 wt.% CO2 at 8.0 GPa result in a change from 4.84 to 4.96 for the average Al coordination number and in a change from 0.87 to 0.80 for the NBO/Si value, respectively.On the contrary, there is a lack of consistency in between the CO2 speciation obtained from NMR spectroscopy and from FPMD simulations. Whereas the analysis of glasses does not reveal the presence of CO2mol species, the FPMD simulation results suggests the existence of a small proportion of CO2mol. Further work with in-situ experimental approach is therefore required to explain the observed lack of consistency between the CO2 speciation in glass and in high temperature melt with basaltic composition

pFoF: a highly scalable halo-finder for large cosmological data sets

We present a parallel implementation of the friends-of-friends algorithm and an innovative technique for reducing complex-shaped data to a user-friendly format. This code, named pFoF, contains an optimized post-processing workflow that reduces the input data coming from gravitational codes, arranges them in a user-friendly format and detects groups of particles using percolation and merging methods. The pFoF code also allows for detecting structures in sub- or non-cubic volumes of the comoving box. In addition, the code offers the possibility of performing new halo-findings with a lower percolation factor, useful for more complex analysis. In this paper, we give standard test results and show performance diagnostics to stress the robustness of pFoF. This code has been extensively tested up to 32768 MPI processes and has proved to be highly scalable with an efficiency of more than 75%. It has been used for analysing the Dark Energy Universe Simulation: Full Universe Runs (DEUS-FUR) project, the first cosmological simulations of the entire observable Universe, modelled with more than half a trillion dark matter particles

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

Heritability of cognitive and emotion processing during functional MRI in a twin sample

Despite compelling evidence that brain structure is heritable, the evidence for the heritability of task-evoked brain function is less robust. Findings from previous studies are inconsistent possibly reflecting small samples and methodological variations. In a large national twin sample, we systematically evaluated heritability of task-evoked brain activity derived from functional magnetic resonance imaging. We used established standardised tasks to engage brain regions involved in cognitive and emotional functions. Heritability was evaluated across a conscious and nonconscious Facial Expressions of Emotion Task (FEET), selective attention Oddball Task, N-back task of working memory maintenance, and a Go-NoGo cognitive control task in a sample of Australian adult twins (N ranged from 136 to 226 participants depending on the task and pairs). Two methods for quantifying associations of heritability and brain activity were utilised; a multivariate independent component analysis (ICA) approach and a univariate brain region-of-interest (ROI) approach. Using ICA, we observed that a significant proportion of task-evoked brain activity was heritable, with estimates ranging from 23% to 26% for activity elicited by nonconscious facial emotion stimuli, 27% to 34% for N-back working memory maintenance and sustained attention, and 32% to 33% for selective attention in the Oddball task. Using the ROI approach, we found that activity of regions specifically implicated in emotion processing and selective attention showed significant heritability for three ROIs, including estimates of 33%–34% for the left and right amygdala in the nonconscious processing of sad faces and 29% in the medial superior prefrontal cortex for the Oddball task. Although both approaches show similar levels of heritability for the Nonconscious Faces and Oddball tasks, ICA results displayed a more extensive network of heritable brain function, including additional regions beyond the ROI analysis. Furthermore, multivariate twin modelling of both ICA networks and ROI activation suggested a mix of common genetic and unique environmental factors that contribute to the associations between networks/regions. Together, the results indicate a complex relationship between genetic factors and environmental interactions that ultimately give rise to neural activation underlying cognition and emotion