Impedance control balances stability with metabolically costly muscle activation.

Humans are able to stabilize their movements in environments with unstable dynamics by selectively modifying arm impedance independently of force and torque. We further investigated adaptation to unstable dynamics to determine whether the CNS maintains a constant overall level of stability as the instability of the environmental dynamics is varied. Subjects performed reaching movements in unstable force fields of varying strength, generated by a robotic manipulator. Although the force fields disrupted the initial movements, subjects were able to adapt to the novel dynamics and learned to produce straight trajectories. After adaptation, the endpoint stiffness of the arm was measured at the midpoint of the movement. The stiffness had been selectively modified in the direction of the instability. The stiffness in the stable direction was relatively unchanged from that measured during movements in a null force field prior to exposure to the unstable force field. This impedance modification was achieved without changes in force and torque. The overall stiffness of the arm and environment in the direction of instability was adapted to the force field strength such that it remained equivalent to that of the null force field. This suggests that the CNS attempts both to maintain a minimum level of stability and minimize energy expenditure.

Impedance control and internal model use during the initial stage of adaptation to novel dynamics in humans.

This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.

QM/MM simulation of liquid water with an adaptive quantum region.

The simulation of complex chemical systems often requires a multi-level description, in which a region of special interest is treated using a computationally expensive quantum mechanical (QM) model while its environment is described by a faster, simpler molecular mechanical (MM) model. Furthermore, studying dynamic effects in solvated systems or bio-molecules requires a variable definition of the two regions, so that atoms or molecules can be dynamically re-assigned between the QM and MM descriptions during the course of the simulation. Such reassignments pose a problem for traditional QM/MM schemes by exacerbating the errors that stem from switching the model at the boundary. Here we show that stable, long adaptive simulations can be carried out using density functional theory with the BLYP exchange-correlation functional for the QM model and a flexible TIP3P force field for the MM model without requiring adjustments of either. Using a primary benchmark system of pure water, we investigate the convergence of the liquid structure with the size of the QM region, and demonstrate that by using a sufficiently large QM region (with radius 6 Å) it is possible to obtain radial and angular distributions that, in the QM region, match the results of fully quantum mechanical calculations with periodic boundary conditions, and, after a smooth transition, also agree with fully MM calculations in the MM region. The key ingredient is the accurate evaluation of forces in the QM subsystem which we achieve by including an extended buffer region in the QM calculations. We also show that our buffered-force QM/MM scheme is transferable by simulating the solvated Cl(-) ion.

Immersed Boundary Method for generalised finite volume and finite difference Navier-Stokes solvers

In Immersed Boundary Methods (IBM) the effect of complex geometries is introduced through the forces added in the Navier-Stokes solver at the grid points in the vicinity of the immersed boundaries. Most of the methods in the literature have been used with Cartesian grids. Moreover many of the methods developed in the literature do not satisfy some basic conservation properties (the conservation of torque, for instance) on non-uniform meshes. In this paper we will follow the RKPM method originated by Liu et al. [1] to build locally regularized functions that verify a number of integral conditions. These local approximants will be used both for interpolating the velocity field and for spreading the singular force field in the framework of a pressure correction scheme for the incompressible Navier-Stokes equations. We will also demonstrate the robustness and effectiveness of the scheme through various examples. Copyright © 2010 by ASME.

Measuring stiffness during arm movements in various dynamic environments

The technique presented in this paper enables a simple, accurate and unbiased measurement of hand stiffness during human arm movements. Using a computer-controlled mechanical interface, the hand is shifted relative to a prediction of the undisturbed trajectory. Stiffness is then computed as the restoring force divided by the position amplitude of the perturbation. A precise prediction algorithm insures the measurement quality. We used this technique to measure stiffness in free movements and after adaptation to a linear velocity dependent force field. The subjects compensated for the external force by co-contracting muscles selectively. The stiffness geometry changed with learning and stiffness tended to increase in the direction of the external force.

Visuomotor feedback gains upregulate during the learning of novel dynamics.

At an early stage of learning novel dynamics, changes in muscle activity are mainly due to corrective feedback responses. These feedback contributions to the overall motor command are gradually reduced as feedforward control is learned. The temporary increased use of feedback could arise simply from the large errors in early learning with either unaltered gains or even slightly downregulated gains, or from an upregulation of the feedback gains when feedforward prediction is insufficient. We therefore investigated whether the sensorimotor control system alters feedback gains during adaptation to a novel force field generated by a robotic manipulandum. To probe the feedback gains throughout learning, we measured the magnitude of involuntary rapid visuomotor responses to rapid shifts in the visual location of the hand during reaching movements. We found large increases in the magnitude of the rapid visuomotor response whenever the dynamics changed: both when the force field was first presented, and when it was removed. We confirmed that these changes in feedback gain are not simply a byproduct of the change in background load, by demonstrating that this rapid visuomotor response is not load sensitive. Our results suggest that when the sensorimotor control system experiences errors, it increases the gain of the visuomotor feedback pathways to deal with the unexpected disturbances until the feedforward controller learns the appropriate dynamics. We suggest that these feedback gains are upregulated with increased uncertainty in the knowledge of the dynamics to counteract any errors or disturbances and ensure accurate and skillful movements.

Gone in 0.6 seconds: the encoding of motor memories depends on recent sensorimotor states.

Real-world tasks often require movements that depend on a previous action or on changes in the state of the world. Here we investigate whether motor memories encode the current action in a manner that depends on previous sensorimotor states. Human subjects performed trials in which they made movements in a randomly selected clockwise or counterclockwise velocity-dependent curl force field. Movements during this adaptation phase were preceded by a contextual phase that determined which of the two fields would be experienced on any given trial. As expected from previous research, when static visual cues were presented in the contextual phase, strong interference (resulting in an inability to learn either field) was observed. In contrast, when the contextual phase involved subjects making a movement that was continuous with the adaptation-phase movement, a substantial reduction in interference was seen. As the time between the contextual and adaptation movement increased, so did the interference, reaching a level similar to that seen for static visual cues for delays >600 ms. This contextual effect generalized to purely visual motion, active movement without vision, passive movement, and isometric force generation. Our results show that sensorimotor states that differ in their recent temporal history can engage distinct representations in motor memory, but this effect decays progressively over time and is abolished by ∼600 ms. This suggests that motor memories are encoded not simply as a mapping from current state to motor command but are encoded in terms of the recent history of sensorimotor states.

Topologically invariant reaction coordinates for simulating multistate chemical reactions.

Evaluating free energy profiles of chemical reactions in complex environments such as solvents and enzymes requires extensive sampling, which is usually performed by potential of mean force (PMF) techniques. The reliability of the sampling depends not only on the applied PMF method but also the reaction coordinate space within the dynamics is biased. In contrast to simple geometrical collective variables that depend only on the positions of the atomic coordinates of the reactants, the E(gap) reaction coordinate (the energy difference obtained by evaluating a suitable force field using reactant and product state topologies) has the unique property that it is able to take environmental effects into account leading to better convergence, a more faithful description of the transition state ensemble and therefore more accurate free energy profiles. However, E(gap) requires predefined topologies and is therefore inapplicable for multistate reactions, in which the barrier between the chemically equivalent topologies is comparable to the reaction activation barrier, because undesired "side reactions" occur. In this article, we introduce a new energy-based collective variable by generalizing the E(gap) reaction coordinate such that it becomes invariant to equivalent topologies and show that it yields more well behaved free energy profiles than simpler geometrical reaction coordinates.

Context-dependent decay of motor memories during skill acquisition.

Current models of motor learning posit that skill acquisition involves both the formation and decay of multiple motor memories that can be engaged in different contexts. Memory formation is assumed to be context dependent, so that errors most strongly update motor memories associated with the current context. In contrast, memory decay is assumed to be context independent, so that movement in any context leads to uniform decay across all contexts. We demonstrate that for both object manipulation and force-field adaptation, contrary to previous models, memory decay is highly context dependent. We show that the decay of memory associated with a given context is greatest for movements made in that context, with more distant contexts showing markedly reduced decay. Thus, both memory formation and decay are strongest for the current context. We propose that this apparently paradoxical organization provides a mechanism for optimizing performance. While memory decay tends to reduce force output, memory formation can correct for any errors that arise, allowing the motor system to regulate force output so as to both minimize errors and avoid unnecessary energy expenditure. The motor commands for any given context thus result from a balance between memory formation and decay, while memories for other contexts are preserved.

Conceptual transformation framework for servitization

This paper presents a Conceptual Transformation Framework for Servitization. The challenges experienced by manufacturers on their journey to servitization are investigated in order to develop our understanding of the transformation that traditional manufacturers undergo to become servitized manufacturers. Three change theories are applied to develop the Framework: Lewin's force field analysis, Senge's system thinking and Pettigrew and Whipp's framework of strategic change. The Framework includes the dimensions of the change that takes place and the elements of change when transforming towards Product-Service Systems.

Motor effort alters changes of mind in sensorimotor decision making.

After committing to an action, a decision-maker can change their mind to revise the action. Such changes of mind can even occur when the stream of information that led to the action is curtailed at movement onset. This is explained by the time delays in sensory processing and motor planning which lead to a component at the end of the sensory stream that can only be processed after initiation. Such post-initiation processing can explain the pattern of changes of mind by asserting an accumulation of additional evidence to a criterion level, termed change-of-mind bound. Here we test the hypothesis that physical effort associated with the movement required to change one's mind affects the level of the change-of-mind bound and the time for post-initiation deliberation. We varied the effort required to change from one choice target to another in a reaching movement by varying the geometry of the choice targets or by applying a force field between the targets. We show that there is a reduction in the frequency of change of mind when the separation of the choice targets would require a larger excursion of the hand from the initial to the opposite choice. The reduction is best explained by an increase in the evidence required for changes of mind and a reduced time period of integration after the initial decision. Thus the criteria to revise an initial choice is sensitive to energetic costs.

Rashba spin splitting of the minibands of coupled InAs/GaAs pyramid quantum dots

The Rashba spin splitting of the minibands of coupled InAs/GaAs pyramid quantum dots is investigated using the k center dot p method and valence force field model. The Rashba splitting of the two dimensional miniband in the lateral directions is found due to the structure inversion asymmetry in the vertical direction while the miniband in the vertical direction has no Rashba spin splitting. As the space between dots increases, the Rashba coefficients decrease and the conduction-band effective mass increases. This Rashba spin splitting of the minibands will significantly affect the spin transport properties between quantum dots. (C) 2008 American Institute of Physics.

Electronic structure and optical gain of truncated InAs1-xNx/GaAs quantum dots

The shape of truncated square-based pyramid quantum dots (QDs) is similar to that of real QDs in experiments. The electronic band structures and optical gain of InAs1-xNx/GaAs QDs are calculated by using the 10-band k.p model, and the strain is calculated by the valence force field (VFF) method. When the top part of the QD is truncated, greater truncation corresponds to a flatter shape of the QD. The truncation changes the strain distribution and the confinement in the z direction. A flatter QD has a greater C1-HH1 transition energy, greater transition matrix element, less detrimental effect of higher excited transition, and higher saturation gain and differential gain. The trade-off between these properties must be considered. From our results, a truncated QD with half of its top part removed has better overall performance. This can provide guidance to growing QDs in experiments in which the proper growing conditions can be controlled to achieve required properties. (C) 2009 Elsevier Ltd. All rights reserved.

Electronic structure and optical gain saturation of InAs1-xNx/GaAs quantum dots

The electronic band structures and optical gains of InAs1-xNx/GaAs pyramid quantum dots (QDs) are calculated using the ten-band k . p model and the valence force field method. The optical gains are calculated using the zero-dimensional optical gain formula with taking into consideration of both homogeneous and inhomogeneous broadenings due to the size fluctuation of quantum dots which follows a normal distribution. With the variation of QD sizes and nitrogen composition, it can be shown that the nitrogen composition and the strains can significantly affect the energy levels especially the conduction band which has repulsion interaction with nitrogen resonant state due to the band anticrossing interaction. It facilitates to achieve emission of longer wavelength (1.33 or 1.55 mu m) lasers for optical fiber communication system. For QD with higher nitrogen composition, it has longer emission wavelength and less detrimental effect of higher excited state transition, but nitrogen composition can affect the maximum gain depending on the factors of transition matrix element and the Fermi-Dirac distributions for electrons in the conduction bands and holes in the valence bands respectively. For larger QD, its maximum optical gain is greater at lower carrier density, but it is slowly surpassed by smaller QD as carrier concentration increases. Larger QD can reach its saturation gain faster, but this saturation gain is smaller than that of smaller QD. So the trade-off between longer wavelength, maximum optical, saturation gain, and differential gain must be considered to select the appropriate QD size according to the specific application requirement. (C) 2009 American Institute of Physics. [DOI 10.1063/1.3143025]

Strain relaxation and band-gap tunability in ternary InxGa1-xN nanowires

The alloy formation enthalpy and band structure of InGaN nanowires were studied by a combined approach of the valence-force field model, Monte Carlo simulation, and density-functional theory (DFT). For both random and ground-state structures of the coherent InGaN alloy, the nanowire configuration was found to be more favorable for the strain relaxation than the bulk alloy. We proposed an analytical formula for computing the band gap of any InGaN nanowires based on the results from the screened exchange hybrid DFT calculations, which in turn reveals a better band-gap tunability in ternary InGaN nanowires than the bulk alloy.