A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

Compressive failure of finite size unidirectional composite laminates with a region of fibre waviness

The compressive behaviour of finite unidirectional composites with a region of misaligned reinforcement is investigated via finite element analyses. Models with and without fibre bending stiffness are compared, confirming that compressive strength is accurately predicted without modelling fibre bending stiffness for real composite components which typically have waviness defects of several millimetres wavelength. Various defect parameters are investigated. Results confirm the well-known sensitivity of compressive strength to misalignment angle, and also show that compressive strength falls rapidly with the proportion of laminate width covered by the wavy region. A simple empirical equation is proposed to model the effect of a single patch of waviness in finite specimens. Other parameters such as length and position of the wavy region are found to have a smaller effect on compressive strength. The modelling approach is finally adapted to model distributed waviness and thus determine the compressive strength of composites with realistic waviness defects. © 2011 Elsevier Ltd. All rights reserved.

CFD modeling of single-phase flow in a packed bed with MRI validation

Computational fluid dynamics (CFD) simulations are becoming increasingly widespread with the advent of more powerful computers and more sophisticated software. The aim of these developments is to facilitate more accurate reactor design and optimization methods compared to traditional lumped-parameter models. However, in order for CFD to be a trusted method, it must be validated using experimental data acquired at sufficiently high spatial resolution. This article validates an in-house CFD code by comparison with flow-field data obtained using magnetic resonance imaging (MRI) for a packed bed with a particle-to-column diameter ratio of 2. Flows characterized by inlet Reynolds numbers, based on particle diameter, of 27, 55, 111, and 216 are considered. The code used employs preconditioning to directly solve for pressure in low-velocity flow regimes. Excellent agreement was found between the MRI and CFD data with relative error between the experimentally determined and numerically predicted flow-fields being in the range of 3-9%. © 2012 American Institute of Chemical Engineers (AIChE).

A comparison of two models for the vibration response of piled foundations to inertial and underground-railway-induced loadings

The vibration response of piled foundations due to ground-borne vibration produced by an underground railway is a largely-neglected area in the field of structural dynamics. However, this continues to be an important aspect of research as it is expected that the presence of piled foundations can have a significant influence on the propagation and transmission of the wavefield produced by the underground railway. This paper presents a comparison of two methods that can be employed in calculating the vibration response of a piled foundation: an efficient semi-analytical model, and a Boundary Element model. The semi-analytical model uses a column or an Euler beam to model the pile, and the soil is modelled as a linear, elastic continuum that has the geometry of a thick-walled cylinder with an infinite outer radius and an inner radius equal to the radius of the pile. The boundary element model uses a constant-element BEM formulation for the halfspace, and a rectangular discretisation of the circular pile-soil interface. The piles are modelled as Timoshenko beams. Pile-soil-pile interactions are inherently accounted for in the BEM equations, whereas in the semi-analytical model these are quantified using the superposition of interaction factors. Both models use the method of joining subsystems to incorporate the incident wavefield generated by the underground railway into the pile model. Results are computed for a single pile subject to an inertial loading, pile-soil-pile interactions, and a pile group subjected to excitation from an underground railway. The two models are compared in terms of accuracy, computation time, versatility and applicability, and guidelines for future vibration prediction models involving piled foundations are proposed.

An efficient model for the dynamic behaviour of a single pile in viscoelastic soil

This paper presents a novel, three-dimensional, single-pile model, formulated in the wavenumber domain and adapted to account for boundary conditions using the superposition of loading cases. The pile is modelled as a column in axial vibration, and a Euler-Bernoulli beam in lateral vibration. The surrounding soil is treated as a viscoelastic continuum. The response of the pile is presented in terms of the stiffness and damping coefficients, and also the magnitude and phase of the pile-head frequency-response function. Comparison with existing models shows that excellent agreement is observed between this model, a boundary-element formulation, and an elastic-continuum-type formulation. This three-dimensional model has an accuracy equivalent to a 3D boundary-element model, and a runtime similar to a 2D plane-strain analytical model. Analysis of the response of the single pile illustrates a difference in axial and lateral vibration behaviour; the displacement along the pile is relatively invariant under axial loads, but in lateral vibration the pile exhibits localised deformations. This implies that a plane-strain assumption is valid for axial loadings and only at higher frequencies for lateral loadings. © 2013 Elsevier Ltd.

Resonant excitation and imaging of nonequilibrium exciton spins in single core-shell GaAs-AlGaAs nanowires.

Nonequilibrium spin distributions in single GaAs/AlGaAs core-shell nanowires are excited using resonant polarized excitation at 10 K. At all excitation energies, we observe strong photoluminescence polarization due to suppressed radiative recombination of excitons with dipoles aligned perpendicular to the nanowire. Excitation resonances are observed at 1- or 2-LO phonon energies above the exciton ground states. Using rate equation modeling, we show that, at the lowest energies, strongly nonequilibrium spin distributions are present and we estimate their spin relaxation rate.

Dynamic models of piled foundations

The vibration behavior of piled foundations is an important consideration in fields such as earthquake engineering, construction, machine-foundation design, offshore structures, nuclear energy, and road and rail development. This paper presents a review of the past 40 years' literature on modeling the frequency-dependent behavior of pile foundations. Beginning with the earliest model of a single pile, adapted from those for embedded footings, it charts the development of the four pile-modeling techniques: the "dynamic Winkler-foundation" approach that uses springs to represent the effect of the soil; elasticcontinuum-type formulations involving the analytical solutions for displacements due to a subsurface disk, cylinder, or other element; boundary element methods; and dynamic finite-element formulations with special nonreflecting boundaries. The modeling of pile groups involves accounting for pile-soil-pile interactions, and four such methods exist: interaction factors; complete pile models; the equivalent pier method; and periodic structure theory. Approaches for validating pile models are also explored. Copyright © 2013 by ASME.

A single-Stream jet noise prediction model for a family of chevron nozzles

This study develops a single-stream jet noise prediction model for a family of chevron nozzles. An original equation is proposed for the fourth-order space-time cross-correlations. They are expressed in flow parameters such as streamwise circulation and turbulent kinetic energy. The cross-correlations based on a Reynolds Averaged Navier-Stokes (RANS) flowfield showed a good agreement with those based on a Large Eddy Simulation (LES) flowfield. This proves that the proposed equation describes the cross-correlations accurately. With this novel source description, there is an excellent agreement between our model's far-field noise predictions and measurements1 for a wide range of frequencies and radiation angles. Our model captures the spectral shape, amplitude and peak frequency very well. This establishes that our model holds good for a family of chevron nozzles. As our model provides quick and accurate predictions, a parametric study was performed to understand the effects of a chevron nozzle geometry on jet noise and thrust loss. Chevron penetration is the underpinning factor for jet noise reduction. The reduction of jet noise per unit thrust loss decreases linearly with chevron penetration. The number of chevrons also has a considerable effect on jet noise.

Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

Factorial comparison of working memory models.

Three questions have been prominent in the study of visual working memory limitations: (a) What is the nature of mnemonic precision (e.g., quantized or continuous)? (b) How many items are remembered? (c) To what extent do spatial binding errors account for working memory failures? Modeling studies have typically focused on comparing possible answers to a single one of these questions, even though the result of such a comparison might depend on the assumed answers to both others. Here, we consider every possible combination of previously proposed answers to the individual questions. Each model is then a point in a 3-factor model space containing a total of 32 models, of which only 6 have been tested previously. We compare all models on data from 10 delayed-estimation experiments from 6 laboratories (for a total of 164 subjects and 131,452 trials). Consistently across experiments, we find that (a) mnemonic precision is not quantized but continuous and not equal but variable across items and trials; (b) the number of remembered items is likely to be variable across trials, with a mean of 6.4 in the best model (median across subjects); (c) spatial binding errors occur but explain only a small fraction of responses (16.5% at set size 8 in the best model). We find strong evidence against all 6 documented models. Our results demonstrate the value of factorial model comparison in working memory.

Differential equation based length scales to improve DES and RANS simulations

Surprisingly expensive to compute wall distances are still used in a range of key turbulence and peripheral physics models. Potentially economical, accuracy improving differential equation based distance algorithms are considered. These involve elliptic Poisson and hyperbolic natured Eikonal equation approaches. Numerical issues relating to non-orthogonal curvilinear grid solution of the latter are addressed. Eikonal extension to a Hamilton-Jacobi (HJ) equation is discussed. Use of this extension to improve turbulence model accuracy and, along with the Eikonal, enhance Detached Eddy Simulation (DES) techniques is considered. Application of the distance approaches is studied for various geometries. These include a plane channel flow with a wire at the centre, a wing-flap system, a jet with co-flow and a supersonic double-delta configuration. Although less accurate than the Eikonal, Poisson method based flow solutions are extremely close to those using a search procedure. For a moving grid case the Poisson method is found especially efficient. Results show the Eikonal equation can be solved on highly stretched, non-orthogonal, curvilinear grids. A key accuracy aspect is that metrics must be upwinded in the propagating front direction. The HJ equation is found to have qualitative turbulence model improving properties. © 2003 by P. G. Tucker.

Single camera pose estimation using Bayesian filtering and Kinect motion priors

Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not ideal and somewhat inelegant as it results in large processing burdens, and instead attempt to incorporate these constraints through priors obtained directly from training data. A prior distribution covering the probability of a human pose occurring is used to incorporate likely human poses. This distribution is obtained offline, by fitting a Gaussian mixture model to a large dataset of recorded human body poses, tracked using a Kinect sensor. We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework. Our model can be viewed as a mixture of discrete Ornstein-Uhlenbeck processes, in that states behave as random walks, but drift towards a set of typically observed poses. This model is combined with measurements of the human head and hand positions, using recursive Bayesian estimation to incorporate temporal information. Measurements are obtained using face detection and a simple skin colour hand detector, trained using the detected face. The suggested model is designed with analytical tractability in mind and we show that the pose tracking can be Rao-Blackwellised using the mixture Kalman filter, allowing for computational efficiency while still incorporating bio-mechanical properties of the upper body. In addition, the use of the proposed upper body model allows reliable three-dimensional pose estimates to be obtained indirectly for a number of joints that are often difficult to detect using traditional object recognition strategies. Comparisons with Kinect sensor results and the state of the art in 2D pose estimation highlight the efficacy of the proposed approach.

Temperature dependence of photoluminescence from single and ensemble InAs/GaAs quantum dots

We investigate the temperature dependence of photoluminescence from single and ensemble InAs/GaAs quantum dots systematically. As temperature increases, the exciton emission peak for single quantum dot shows broadening and redshift. For ensemble quantum dots, however, the exciton emission peak shows narrowing and fast redshift. We use a simple steady-state rate equation model to simulate the experimental data of photoluminescence spectra. It is confirmed that carrier-phonon scattering gives the broadening of the exciton emission peak in single quantum dots while the effects of carrier thermal escape and retrapping play an important role in the narrowing and fast redshift of the exciton emission peak in ensemble quantum dots.

Photostability of single-photon emission from a single quantum dot in the 650-nm wavelength band at room temperature

The photoluminescence correlation from a single CdSe nanocrystal under pulsed excitation is studied, and a single photon is realized at wavelength 655 nm at room temperature. The single colloidal CdSe quantum dot is prepared on a SiO2/silicon surface by a drop-and-drag technique. The long-term stability of the single-photon source is investigated; it is found that the antibunching effect weakens with excitation time, and the reason for the weakening is attributed to photobleaching. The lifetimes of photoluminescence from a single quantum dot are analyzed at different excitation times. By analyzing the probability distribution of on and off times of photoluminescence, the Auger assisted tunneling and Auger assisted photobleaching models are applied to explain the antibunching phenomenon.

Single-mode condition for silicon rib waveguides with trapezoidal cross-section

Single-mode condition for silicon rib waveguides with trapezoidal cross-section was obtained using a numerical method based on imaginary-distance beam propagation method with non-uniform discretization. Both quasi-transverse-electric and quasi-transverse-magnetic modes were investigated. Simulated single-mode condition is given by a modified equation. Comparison with reported results shows that the Marcatili's method is in a better agreement with our results. (C) 2003 Elsevier B.V. All rights reserved.