Generalized flows, intrinsic stochasticity, and turbulent transport

The study of passive scalar transport in a turbulent velocity field leads naturally to the notion of generalized flows, which are families of probability distributions on the space of solutions to the associated ordinary differential equations which no longer satisfy the uniqueness theorem for ordinary differential equations. Two most natural regularizations of this problem, namely the regularization via adding small molecular diffusion and the regularization via smoothing out the velocity field, are considered. White-in-time random velocity fields are used as an example to examine the variety of phenomena that take place when the velocity field is not spatially regular. Three different regimes, characterized by their degrees of compressibility, are isolated in the parameter space. In the regime of intermediate compressibility, the two different regularizations give rise to two different scaling behaviors for the structure functions of the passive scalar. Physically, this means that the scaling depends on Prandtl number. In the other two regimes, the two different regularizations give rise to the same generalized flows even though the sense of convergence can be very different. The “one force, one solution” principle is established for the scalar field in the weakly compressible regime, and for the difference of the scalar in the strongly compressible regime, which is the regime of inverse cascade. Existence and uniqueness of an invariant measure are also proved in these regimes when the transport equation is suitably forced. Finally incomplete self similarity in the sense of Barenblatt and Chorin is established.

A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems

We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

Broken symmetry and critical transport properties of random metals

Recent experimental data on the conductivity σ+(T), T → 0, on the metallic side of the metal–insulator transition in ideally random (neutron transmutation-doped) 70Ge:Ga have shown that σ+(0) ∝ (N − Nc)μ with μ = ½, confirming earlier ultra-low-temperature results for Si:P. This value is inconsistent with theoretical predictions based on diffusive classical scaling models, but it can be understood by a quantum-directed percolative filamentary amplitude model in which electronic basis states exist which have a well-defined momentum parallel but not normal to the applied electric field. The model, which is based on a new kind of broken symmetry, also explains the anomalous sign reversal of the derivative of the temperature dependence in the critical regime.

Role of intrinsic synaptic circuitry in collicular sensorimotor integration

The superficial gray layer of the superior colliculus contains a map that represents the visual field, whereas the underlying intermediate gray layer contains a vector map of the saccades that shift the direction of gaze. These two maps are aligned so that a particular region of the visual field is represented directly above the neurons that orient the highest acuity area of the retina toward that region. Although it has been proposed that the transmission of information from the visuosensory to the motor map plays an important role in the generation of visually guided saccades, experiments have failed to demonstrate any functional linkage between the two layers. We examined synaptic transmission between these layers in vitro by stimulating the superficial layer while using whole-cell patch-clamp methods to measure the responses of intermediate layer neurons. Stimulation of superficial layer neurons evoked excitatory postsynaptic currents in premotor cells. This synaptic input was columnar in organization, indicating that the connections between the layers link corresponding regions of the visuosensory and motor maps. Excitatory postsynaptic currents were large enough to evoke action potentials and often occurred in clusters similar in duration to the bursts of action potentials that premotor cells use to command saccades. Our results indicate the presence of functional connections between the superficial and intermediate layers and show that such connections could play a significant role in the generation of visually guided saccades.

Energy-based de novo protein folding by conformational space annealing and an off-lattice united-residue force field: Application to the 10-55 fragment of staphylococcal protein A and to apo calbindin D9K

The conformational space annealing (CSA) method for global optimization has been applied to the 10-55 fragment of the B-domain of staphylococcal protein A (protein A) and to a 75-residue protein, apo calbindin D9K (PDB ID code 1CLB), by using the UNRES off-lattice united-residue force field. Although the potential was not calibrated with these two proteins, the native-like structures were found among the low-energy conformations, without the use of threading or secondary-structure predictions. This is because the CSA method can find many distinct families of low-energy conformations. Starting from random conformations, the CSA method found that there are two families of low-energy conformations for each of the two proteins, the native-like fold and its mirror image. The CSA method converged to the same low-energy folds in all cases studied, as opposed to other optimization methods. It appears that the CSA method with the UNRES force field, which is based on the thermodynamic hypothesis, can be used in prediction of protein structures in real time.

Molecular dynamics of a grid-mounted molecular dipolar rotor in a rotating electric field

Classical molecular dynamics is applied to the rotation of a dipolar molecular rotor mounted on a square grid and driven by rotating electric field E(ν) at T ≃ 150 K. The rotor is a complex of Re with two substituted o-phenanthrolines, one positively and one negatively charged, attached to an axial position of Rh\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}{\mathrm{_{2}^{4+}}}\end{equation*}\end{document} in a [2]staffanedicarboxylate grid through 2-(3-cyanobicyclo[1.1.1]pent-1-yl)malonic dialdehyde. Four regimes are characterized by a, the average lag per turn: (i) synchronous (a < 1/e) at E(ν) = |E(ν)| > Ec(ν) [Ec(ν) is the critical field strength], (ii) asynchronous (1/e < a < 1) at Ec(ν) > E(ν) > Ebo(ν) > kT/μ, [Ebo(ν) is the break-off field strength], (iii) random driven (a ≃ 1) at Ebo(ν) > E(ν) > kT/μ, and (iv) random thermal (a ≃ 1) at kT/μ > E(ν). A fifth regime, (v) strongly hindered, W > kT, Eμ, (W is the rotational barrier), has not been examined. We find Ebo(ν)/kVcm−1 ≃ (kT/μ)/kVcm−1 + 0.13(ν/GHz)1.9 and Ec(ν)/kVcm−1 ≃ (2.3kT/μ)/kVcm−1 + 0.87(ν/GHz)1.6. For ν > 40 GHz, the rotor behaves as a macroscopic body with a friction constant proportional to frequency, η/eVps ≃ 1.14 ν/THz, and for ν < 20 GHz, it exhibits a uniquely molecular behavior.

Galaxy formation

It is argued that within the standard Big Bang cosmological model the bulk of the mass of the luminous parts of the large galaxies likely had been assembled by redshift z ∼ 10. Galaxy assembly this early would be difficult to fit in the widely discussed adiabatic cold dark matter model for structure formation, but it could agree with an isocurvature version in which the cold dark matter is the remnant of a massive scalar field frozen (or squeezed) from quantum fluctuations during inflation. The squeezed field fluctuations would be Gaussian with zero mean, and the distribution of the field mass therefore would be the square of a random Gaussian process. This offers a possibly interesting new direction for the numerical exploration of models for cosmic structure formation.

Subthreshold facilitation and suppression in primary visual cortex revealed by intrinsic signal imaging.

Neurons in primary visual cortex (area 17) respond vigorously to oriented stimuli within their receptive fields; however, stimuli presented outside the suprathreshold receptive field can also influence their responses. Here we describe a fundamental feature of the spatial interaction between suprathreshold center and subthreshold surround. By optical imaging of intrinsic signals in area 17 in response to a stimulus border, we show that a given stimulus generates activity primarily in iso-orientation domains, which extend for several millimeters across the cortical surface in a manner consistent with the architecture of long-range horizontal connections in area 17. By mapping the receptive fields of single neurons and imaging responses from the same cortex to stimuli that include or exclude the aggregate suprathreshold receptive field, we show that intrinsic signals strongly reveal the subthreshold surround contribution. Optical imaging and single-unit recording both demonstrate that the relative contrast of center and surround stimuli regulates whether surround interactions are facilitative or suppressive: the same surround stimulus facilitates responses when center contrast is low, but suppresses responses when center contrast is high. Such spatial interactions in area 17 are ideally suited to contribute to phenomena commonly regarded as part of "higher-level" visual processing, such as perceptual "popout" and "filling-in."

Motor learning by field approximation.

We investigated how human subjects adapt to forces perturbing the motion of their ams. We found that this kind of learning is based on the capacity of the central nervous system (CNS) to predict and therefore to cancel externally applied perturbing forces. Our experimental results indicate: (i) that the ability of the CNS to compensate for the perturbing forces is restricted to those spatial locations where the perturbations have been experienced by the moving arm. The subjects also are able to compensate for forces experienced at neighboring workspace locations. However, adaptation decays smoothly and quickly with distance from the locations where disturbances had been sensed by the moving limb. (ii) Our experiments also how that the CNS builds an internal model of the external perturbing forces in intrinsic (muscles and / or joints) coordinates.