Quantum tunneling of magnetization in dipolar spin-1 condensates under external fields

We study the macroscopic quantum tunneling of magnetization of the F=1 spinor condensate interacting through dipole-dipole interaction with an external magnetic field applied along the longitudinal or transverse direction. We show that the ground state energy and the effective magnetic moment of the system exhibit an interesting macroscopic quantum oscillation phenomenon originating from the oscillating dependence of thermodynamic properties of the system on the vacuum angle. Tunneling between two degenerate minima are analyzed by means of an effective potential method and the periodic instanton method.Comment: 2 figures, accepted PR

A Numerical Study of the Effects of Wave-Induced Fluid Flow in Porous Media: Linear Solver

In this paper, we present a computational method to simulate wave propagation in porous rocks saturated with Newtonian fluids over a range of frequencies of interest. The method can use a digital representation of a rock sample where distinct material phase and properties at each volume cell are identified and model the dynamic response of the rock to an acoustic excitation mathematically with a coupled equation system: elastic wave equation in solid matrix and viscous wave equation in fluid. The coupled wave equations are solved numerically with a rotated-staggered-grid finite difference scheme. We simulate P-wave propagation through an idealized porous medium of periodically alternating solid and fluid layers where an analytical solution is available and obtain excellent agreements between numerical and analytical solutions. The method models the effect of pore fluid motion on the rock dynamic response more accurately with a linearized Navier-Stokes equation than with the viscoelastic model of the generalized Maxwell body, a low frequency approximation commonly used to overcome the difficulty of modeling frequency-dependent fluid shear modulus in time domain.Schlumberger Doll ResearchMassachusetts Institute of Technology. Earth Resources Laborator

Effects of Low Intensity Focused Ultrasound on Liposomes Containing Channel proteins.

The ability to reversibly and non-invasively modulate region-specific brain activity in vivo suggests Low Intensity Focused Ultrasound (LIFU) as potential therapeutics for neurological dysfunctions such as epilepsy and Parkinson's disease. While in vivo studies provide evidence of the bioeffects of LIFU on neuronal activity, they merely hint at potential mechanisms but do not fully explain how this technology achieves these effects. One potential hypothesis is that LIFU produces local membrane depolarization by mechanically perturbing the neuronal cell membrane, or activating channels or other proteins embedded in the membrane. Proteins that sense mechanical perturbations of the membrane, such as those gated by membrane tension, are prime candidates for activating in response to LIFU and thus leading to the neurological responses that have been measured. Here we use the bacterial mechanosensitive channel MscL, which has been purified and reconstituted in liposomes, to determine how LIFU may affect the activation of this membrane-tension gated channel. Two bacterial voltage-gated channels, KvAP and NaK2K F92A channels were also studied. Surprisingly, the results suggest that ultrasound modulation and membrane perturbation does not induce channel gating, but rather induces pore formation at the membrane protein-lipid interface. However, in vesicles with high MscL mechanosensitive channel concentrations, apparent decreases in pore formation are observed, suggesting that this membrane-tension-sensitive protein may serve to increase the elasticity of the membrane, presumably because of expansion of the channel in the plane of the membrane independent of channel gating

Object-based 3D binary reconstruction from sparse projections in cone beam CT: Comparison of three projection operators

International audienceWe present herein a level set approach to the X-ray tomography problem with sparse projection data and study the impact of the projection operator on the binary reconstruction accuracy and computation time. The comparison is carried out on three projectors: the Separable Footprint (Trapeze-Trapeze, SF-TT) [3], a classical Raydriven (RD) and a Simplified version of the Distance-Driven (SDD) projector respectively. The performance, are evaluated for each operator, on a binary 3D Shepp-Logan phantom by varying the number of projections from 5 to 13, and considering noise free and noisy cone beam projection data

On-nanowire spatial band gap design for white light emission.

This is the accepted manuscript. The final version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/nl203529h.We demonstrated a substrate-moving vapor-liquid-solid (VLS) route for growing composition gradient ZnCdSSe alloy nanowires. Relying on temperature-selected composition deposition along their lengths, single tricolor ZnCdSSe alloy nanowires with engineerable band gap covering the entire visible range were obtained. The photometric property of these tricolor nanowires, which was determined by blue-, green-, and red-color emission intensities, can be in turn controlled by their corresponding emission lengths. More particularly, under carefully selected growth conditions, on-nanowire white light emission has been achieved. Band-gap-engineered semiconductor alloy nanowires demonstrated here may find applications in broad band light absorption and emission devices

Artifact Suppressed Dictionary Learning for Low-Dose CT Image Processing

International audience–Low-dose CT (LDCT) images are often severely degraded by amplified mottle noise and streak artifacts. These artifacts are often hard to suppress without introducing tissue blurring effects. In this paper, we propose to process LDCT images using a novel image-domain algorithm called "artifact suppressed dictionary learning (ASDL)". In this ASDL method, orientation and scale information on artifacts is exploited to train artifact atoms, which are then combined with tissue feature atoms to build three discriminative dictionaries. The streak artifacts are cancelled via a discriminative sparse representation (DSR) operation based on these dictionaries. Then, a general dictionary learning (DL) processing is applied to further reduce the noise and residual artifacts. Qualitative and quantitative evaluations on a large set of abdominal and mediastinum CT images are carried out and the results show that the proposed method can be efficiently applied in most current CT systems. Index Terms—Low-dose CT (LDCT), dictionary learning, noise, artifact suppression, artifact suppressed dictionary learning algorithm (ASDL