Modeling Robot Dynamic Performance for Endpoint Force Control

This research aims to understand the fundamental dynamic behavior of servo-controlled machinery in response to various types of sensory feedback. As an example of such a system, we study robot force control, a scheme which promises to greatly expand the capabilities of industrial robots by allowing manipulators to interact with uncertain and dynamic tasks. Dynamic models are developed which allow the effects of actuator dynamics, structural flexibility, and workpiece interaction to be explored in the frequency and time domains. The models are used first to explain the causes of robot force control instability, and then to find methods of improving this performance.

Modeling Stock Order Flows and Learning Market-Making from Data

Stock markets employ specialized traders, market-makers, designed to provide liquidity and volume to the market by constantly supplying both supply and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that learns profitable market-making strategies when run on this model. The sequence of buys and sells for a particular stock, the order flow, we model as an Input-Output Hidden Markov Model fit to historical data. When combined with the dynamics of the order book, this creates a highly non-linear and difficult dynamic system. Our reinforcement learning algorithm, based on likelihood ratios, is run on this partially-observable environment. We demonstrate learning results for two separate real stocks.

Exact Solution of the Nonlinear Dynamics of Recurrent Neural Mechanisms for Direction Selectivity

Different theoretical models have tried to investigate the feasibility of recurrent neural mechanisms for achieving direction selectivity in the visual cortex. The mathematical analysis of such models has been restricted so far to the case of purely linear networks. We present an exact analytical solution of the nonlinear dynamics of a class of direction selective recurrent neural models with threshold nonlinearity. Our mathematical analysis shows that such networks have form-stable stimulus-locked traveling pulse solutions that are appropriate for modeling the responses of direction selective cortical neurons. Our analysis shows also that the stability of such solutions can break down giving raise to a different class of solutions ("lurching activity waves") that are characterized by a specific spatio-temporal periodicity. These solutions cannot arise in models for direction selectivity with purely linear spatio-temporal filtering.

Application of agent-based modeling to the study of gender stereotypes

Gender stereotypes are sets of characteristics that people believe to be typically true of a man or woman. We report an agent-based model (ABM) that simulates how stereotypes disseminate in a group through associative mechanisms. The model consists of agents that carry one of several different versions of a stereotype, which share part of their conceptual content. When an agent acts according to his/her stereotype, and that stereotype is shared by an observer, then the latter’s stereotype strengthens. Contrarily, if the agent does not act according to his/ her stereotype, then the observer’s stereotype weakens. In successive interactions, agents develop preferences, such that there will be a higher probability of interaction with agents that confirm their stereotypes. Depending on the proportion of shared conceptual content in the stereotype’s different versions, three dynamics emerge: all stereotypes in the population strengthen, all weaken, or a bifurcation occurs, i.e., some strengthen and some weaken. Additionally, we discuss the use of agent-based modeling to study social phenomena and the practical consequences that the model’s results might have on stereotype research and their effects on a community

Dynamics of convectively driven banded jets in the laboratory

The banded organization of clouds and zonal winds in the atmospheres of the outer planets has long fascinated observers. Several recent studies in the theory and idealized modeling of geostrophic turbulence have suggested possible explanations for the emergence of such organized patterns, typically involving highly anisotropic exchanges of kinetic energy and vorticity within the dissipationless inertial ranges of turbulent flows dominated (at least at large scales) by ensembles of propagating Rossby waves. The results from an attempt to reproduce such conditions in the laboratory are presented here. Achievement of a distinct inertial range turns out to require an experiment on the largest feasible scale. Deep, rotating convection on small horizontal scales was induced by gently and continuously spraying dense, salty water onto the free surface of the 13-m-diameter cylindrical tank on the Coriolis platform in Grenoble, France. A “planetary vorticity gradient” or “β effect” was obtained by use of a conically sloping bottom and the whole tank rotated at angular speeds up to 0.15 rad s−1. Over a period of several hours, a highly barotropic, zonally banded large-scale flow pattern was seen to emerge with up to 5–6 narrow, alternating, zonally aligned jets across the tank, indicating the development of an anisotropic field of geostrophic turbulence. Using particle image velocimetry (PIV) techniques, zonal jets are shown to have arisen from nonlinear interactions between barotropic eddies on a scale comparable to either a Rhines or “frictional” wavelength, which scales roughly as (β/Urms)−1/2. This resulted in an anisotropic kinetic energy spectrum with a significantly steeper slope with wavenumber k for the zonal flow than for the nonzonal eddies, which largely follows the classical Kolmogorov k−5/3 inertial range. Potential vorticity fields show evidence of Rossby wave breaking and the presence of a “hyperstaircase” with radius, indicating instantaneous flows that are supercritical with respect to the Rayleigh–Kuo instability criterion and in a state of “barotropic adjustment.” The implications of these results are discussed in light of zonal jets observed in planetary atmospheres and, most recently, in the terrestrial oceans.

Hierarchical modeling of entangled polymers

We demonstrate that it is possible to link multi-chain molecular dynamics simulations with the tube model using a single chain slip-links model as a bridge. This hierarchical approach allows significant speed up of simulations, permitting us to span the time scales relevant for a comparison with the tube theory. Fitting the mean-square displacement of individual monomers in molecular dynamics simulations with the slip-spring model, we show that it is possible to predict the stress relaxation. Then, we analyze the stress relaxation from slip-spring simulations in the framework of the tube theory. In the absence of constraint release, we establish that the relaxation modulus can be decomposed as the sum of contributions from fast and longitudinal Rouse modes, and tube survival. Finally, we discuss some open questions regarding possible future directions that could be profitable in rendering the tube model quantitative, even for mildly entangled polymers

Predicting magnetospheric dynamics with a coupled sun-to-Earth model: challenges and first results

Results from the first Sun-to-Earth coupled numerical model developed at the Center for Integrated Space Weather Modeling are presented. The model simulates physical processes occurring in space spanning from the corona of the Sun to the Earth's ionosphere, and it represents the first step toward creating a physics-based numerical tool for predicting space weather conditions in the near-Earth environment. Two 6- to 7-d intervals, representing different heliospheric conditions in terms of the three-dimensional configuration of the heliospheric current sheet, are chosen for simulations. These conditions lead to drastically different responses of the simulated magnetosphere-ionosphere system, emphasizing, on the one hand, challenges one encounters in building such forecasting tools, and on the other hand, emphasizing successes that can already be achieved even at this initial stage of Sun-to-Earth modeling.

C–H local modes in cyclobutene. II. Laser photoacoustic studies 10 000–17 000 cm−1. Vibrational structure and C–H local mode dynamics

In part I of this study [Baggott, Clase, and Mills, Spectrochim. Acta Part A 42, 319 (1986)] we presented FTIR spectra of gas phase cyclobutene and modeled the v=1–3 stretching states of both olefinic and methylenic C–H bonds in terms of a local mode model. In this paper we present some improvements to our original model and make use of recently derived ‘‘x,K relations’’ to find the equivalent normal mode descriptions. The use of both the local mode and normal mode approaches to modeling the vibrational structure is described in some detail. We present evidence for Fermi resonance interactions between the methylenic C–H stretch overtones and ring C–C stretch vibrations, revealed in laser photoacoustic spectra in the v=4–6 region. An approximate model vibrational Hamiltonian is proposed to explain the observed structure and is used to calculate the dynamics of the C–H stretch local mode decay resulting from interaction with lower frequency ring modes. The implications of our experimental and theoretical studies for mode‐selective photochemistry are discussed briefly.

From a discrete to a continuum model of cell dynamics in one dimension

Multiscale modeling is emerging as one of the key challenges in mathematical biology. However, the recent rapid increase in the number of modeling methodologies being used to describe cell populations has raised a number of interesting questions. For example, at the cellular scale, how can the appropriate discrete cell-level model be identified in a given context? Additionally, how can the many phenomenological assumptions used in the derivation of models at the continuum scale be related to individual cell behavior? In order to begin to address such questions, we consider a discrete one-dimensional cell-based model in which cells are assumed to interact via linear springs. From the discrete equations of motion, the continuous Rouse [P. E. Rouse, J. Chem. Phys. 21, 1272 (1953)] model is obtained. This formalism readily allows the definition of a cell number density for which a nonlinear "fast" diffusion equation is derived. Excellent agreement is demonstrated between the continuum and discrete models. Subsequently, via the incorporation of cell division, we demonstrate that the derived nonlinear diffusion model is robust to the inclusion of more realistic biological detail. In the limit of stiff springs, where cells can be considered to be incompressible, we show that cell velocity can be directly related to cell production. This assumption is frequently made in the literature but our derivation places limits on its validity. Finally, the model is compared with a model of a similar form recently derived for a different discrete cell-based model and it is shown how the different diffusion coefficients can be understood in terms of the underlying assumptions about cell behavior in the respective discrete models.

Molecule modeling of human pentameric alpha(7) neuronal nicotinic acetylcholine receptor and its interaction with its agonist and competitive antagonist

The nicotinic Acetylcholine Receptor (nAChR) is the major class of neurotransmitter receptors that is involved in many neurodegenerative conditions such as schizophrenia, Alzheimer's and Parkinson's diseases. The N-terminal region or Ligand Binding Domain (LBD) of nAChR is located at pre- and post-synaptic nervous system, which mediates synaptic transmission. nAChR acts as the drug target for agonist and competitive antagonist molecules that modulate signal transmission at the nerve terminals. Based on Acetylcholine Binding Protein (AChBP) from Lymnea stagnalis as the structural template, the homology modeling approach was carried out to build three dimensional model of the N-terminal region of human alpha(7)nAChR. This theoretical model is an assembly of five alpha(7) subunits with 5 fold axis symmetry, constituting a channel, with the binding picket present at the interface region of the subunits. alpha-netlrotoxin is a potent nAChR competitive antagonist that readily blocks the channel resulting in paralysis. The molecular interaction of alpha-Bungarotoxin, a long chain alpha-neurotoxin from (Bungarus multicinctus) and human alpha(7)nAChR seas studied. Agonists such as acetylcholine, nicotine, which are used in it diverse array of biological activities, such as enhancements of cognitive performances, were also docked with the theoretical model of human alpha(7)nAChR. These docked complexes were analyzed further for identifying the crucial residues involved in interaction. These results provide the details of interaction of agonists and competitive antagonists with three dimensional model of the N-terminal region of human alpha(7)nAChR and thereby point to the design of novel lead compounds.

Assessing and understanding the impact of stratospheric dynamics and variability on the earth system

Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.

Modeling the patrol behavior of the Diacamma's gamergate

The gamergate (generally called the “queen”) of the Diacamma sp. walks around in the nest and comes into contact with the workers. The gamergate informs the workers of its presence by physical contact. This behavior is called a “patrol.” In previous work, it was reported that the gamergate controls its patrolling time depending on the colony size. How does the gamergate know the colony size, and how does it control the patrolling time? In this article, we propose a simple dynamics to explain this behavior. We assume that the gamergate and the workers have internal states which interact by physical contacts. By numerical simulations, we confirm that the patrol time of the proposed model depends on the size of the colony.

Large-scale dynamics of the mesosphere and lower thermosphere: an analysis using the extended Canadian Middle Atmosphere Model

The extended Canadian Middle Atmosphere Model is used to investigate the large-scale dynamics of the mesosphere and lower thermosphere (MLT). It is shown that the 4-day wave is substantially amplified in southern polar winter in the presence of instabilities arising from strong vertical shears in the MLT zonal mean zonal winds brought about by parameterized nonorographic gravity wave drag. A weaker 4-day wave in northern polar winter is attributed to the weaker wind shears that result from weaker parameterized wave drag. The 2-day wave also exhibits a strong dependence on zonal wind shears, in agreement with previous modeling studies. In the equatorial upper mesosphere, the migrating diurnal tide provides most of the resolved westward wave forcing, which varies semiannually in conjunction with the tide itself; resolved forcing by eastward traveling disturbances is dominated by smaller scales. Nonmigrating tides and other planetary-scale waves play only a minor role in the zonal mean zonal momentum budget in the tropics at these heights. Resolved waves are shown to play a significant role in the zonal mean meridional momentum budget in the MLT, impacting significantly on gradient wind balance. Balance fails at low latitudes as a result of a strong Reynolds stress associated with the migrating diurnal tide, an effect which is most pronounced at equinox when the tide is strongest. Resolved and parameterized waves account for most of the imbalance at higher latitudes in summer. This results in the gradient wind underestimating the actual eastward wind reversal by up to 40%.