Fast High Resolution Echelle Spectroscopy Of A Laboratory Plasma

An echelle diffraction grating and a multianode photomultiplier tube are paired to construct a high resolution (R=lambda/delta lambda approximate to 2.5x10(4)) spectrograph with fast time response for use from the UV through the visible. This instrument has analyzed the line shape of C III impurity ion emission at 229.687 nm over the lifetime (approximate to 100 mu s) of the hydrogen plasmas produced at SSX. The ion temperature and line of sight average velocity are inferred from the observed thermal broadening and Doppler shift of the line. The time resolution of these measurements is about 1 mu s, sufficient to observe the fastest magnetohydrodynamic activity

LES of additive and non-additive pulsatile flows in a model arterial stenosis

Transition of additive and non-additive pulsatile flows through a simple 3D model of arterial stenosis is investigated by using a large eddy simulation (LES) technique. We find in both the pulsatile cases that the interaction of the two shear layers, one of which separates from the nose of the stenosis and the another one from its opposite wall, causes recirculation in the flow downstream of the stenosis where the nature of the transient flow becomes turbulent. The strength of this recirculation is found to be quite high from the non-additive pulsations when the flow Reynolds numbers, Re ≥ 1500, for which both the pressure and shearing stresses take on an oscillating form at the post-stenotic region. Potential medical consequences of these results are discussed in the paper. In addition, some comparisons of the non-additive pulsatile results are given with those of both the additive pulsatile and steady flows. The capability of using LES to simulate the pulsatile transitional flow is also assessed, and the present results show that the smaller (subgrid) scales (SGS) contributes about 78% energy dissipation to the flow when the Reynolds number is taken as 2000. The level of SGS dissipation decreases as the Reynolds number is decreased. The numerical results are validated with the experimental data available in literature where a quite good agreement is found

Dynamics of Neural Networks with Continuous Attractors

We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stability facilitates the tracking performance of a CANN, which is believed to have wide applications in brain functions. We develop a perturbative approach that utilizes the dominant movement of the network stationary states in the state space. We quantify the distortions of the bump shape during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable, and the reaction time to catch up an abrupt change in stimulus.Comment: 6 pages, 7 figures with 4 caption

Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy and Mobility

Experimental data have revealed that neuronal connection efficacy exhibits two forms of short-term plasticity, namely, short-term depression (STD) and short-term facilitation (STF). They have time constants residing between fast neural signaling and rapid learning, and may serve as substrates for neural systems manipulating temporal information on relevant time scales. The present study investigates the impact of STD and STF on the dynamics of continuous attractor neural networks (CANNs) and their potential roles in neural information processing. We find that STD endows the network with slow-decaying plateau behaviors-the network that is initially being stimulated to an active state decays to a silent state very slowly on the time scale of STD rather than on the time scale of neural signaling. This provides a mechanism for neural systems to hold sensory memory easily and shut off persistent activities gracefully. With STF, we find that the network can hold a memory trace of external inputs in the facilitated neuronal interactions, which provides a way to stabilize the network response to noisy inputs, leading to improved accuracy in population decoding. Furthermore, we find that STD increases the mobility of the network states. The increased mobility enhances the tracking performance of the network in response to time-varying stimuli, leading to anticipative neural responses. In general, we find that STD and STP tend to have opposite effects on network dynamics and complementary computational advantages, suggesting that the brain may employ a strategy of weighting them differentially depending on the computational purpose.Comment: 40 pages, 17 figure

Two-dimensional Vesicle dynamics under shear flow: effect of confinement

Dynamics of a single vesicle under shear flow between two parallel plates is studied using two-dimensional lattice-Boltzmann simulations. We first present how we adapted the lattice-Boltzmann method to simulate vesicle dynamics, using an approach known from the immersed boundary method. The fluid flow is computed on an Eulerian regular fixed mesh while the location of the vesicle membrane is tracked by a Lagrangian moving mesh. As benchmarking tests, the known vesicle equilibrium shapes in a fluid at rest are found and the dynamical behavior of a vesicle under simple shear flow is being reproduced. Further, we focus on investigating the effect of the confinement on the dynamics, a question that has received little attention so far. In particular, we study how the vesicle steady inclination angle in the tank-treading regime depends on the degree of confinement. The influence of the confinement on the effective viscosity of the composite fluid is also analyzed. At a given reduced volume (the swelling degree) of a vesicle we find that both the inclination angle, and the membrane tank-treading velocity decrease with increasing confinement. At sufficiently large degree of confinement the tank-treading velocity exhibits a non-monotonous dependence on the reduced volume and the effective viscosity shows a nonlinear behavior.Comment: 12 pages, 8 figure

Dynamical regimes and hydrodynamic lift of viscous vesicles under shear

The dynamics of two-dimensional viscous vesicles in shear flow, with different fluid viscosities $\eta_{\rm in}$ and $\eta_{\rm out}$ inside and outside, respectively, is studied using mesoscale simulation techniques. Besides the well-known tank-treading and tumbling motions, an oscillatory swinging motion is observed in the simulations for large shear rate. The existence of this swinging motion requires the excitation of higher-order undulation modes (beyond elliptical deformations) in two dimensions. Keller-Skalak theory is extended to deformable two-dimensional vesicles, such that a dynamical phase diagram can be predicted for the reduced shear rate and the viscosity contrast $\eta_{\rm in}/\eta_{\rm out}$. The simulation results are found to be in good agreement with the theoretical predictions, when thermal fluctuations are incorporated in the theory. Moreover, the hydrodynamic lift force, acting on vesicles under shear close to a wall, is determined from simulations for various viscosity contrasts. For comparison, the lift force is calculated numerically in the absence of thermal fluctuations using the boundary-integral method for equal inside and outside viscosities. Both methods show that the dependence of the lift force on the distance $y_{\rm {cm}}$ of the vesicle center of mass from the wall is well described by an effective power law $y_{\rm {cm}}^{-2}$ for intermediate distances $0.8 R_{\rm p} \lesssim y_{\rm {cm}} \lesssim 3 R_{\rm p}$ with vesicle radius $R_{\rm p}$. The boundary-integral calculation indicates that the lift force decays asymptotically as $1/[y_{\rm {cm}}\ln(y_{\rm {cm}})]$ far from the wall.Comment: 13 pages, 13 figure