Enhanced Cloud Disruption by Magnetic Field Interaction

We present results from the first three-dimensional numerical simulations of moderately supersonic cloud motion through a tenuous, magnetized medium. We show that the interaction of the cloud with a magnetic field perpendicular to its motion has a great dynamical impact on the development of instabilities at the cloud surface. Even for initially spherical clouds, magnetic field lines become trapped in surface deformations and undergo stretching. The consequent field amplification that occurs there and particularly its variation across the cloud face then dramatically enhance the growth rate of Rayleigh-Taylor unstable modes, hastening the cloud disruption.Comment: 4 pages, 2 figures, ApJ (Letter) in press. High resolution postscript figures available at http://www.msi.umn.edu/Projects/twj/mhd3d

Synchronization Behavior in Coupled Chemical Oscillators

Synchronization is a collective phenomenon emerging from the interactions of different dynamical systems. Systems with different characteristics adjust their behavior to a common behavior of the group. This collective behavior is observed in many biological, chemical, and physical systems. Examples from different fields include pacemaker heart cells, synchronization of neurons during epilepsy seizures, arrays of microwave oscillators, and robot manipulators. Studies of coupled oscillators have revealed different mechanisms by which discrete oscillators interact and organize to a uniform synchronized state from an incoherent state. The discovery of a new type of synchronization state, called the chimera state has further broadened the field of synchronization. A chimera state is made up of coexisting subpopulations of oscillators, each with same coupling structure, but with one exhibiting synchronous behavior and the other asynchronous behavior. The phenomena has been the focus of much theoretical and experimental research in the past decade. In this thesis, experimental and simulation studies of chimera states in populations of coupled chemical oscillators will be described and their relation to other synchronization states will be characterized. Experiments were carried out with the photosensitive Belousov-Zhabotinsky (BZ) chemical oscillators and a light feedback scheme. The dimensionless two-variable Zhabotinsky-Buchholtz-Kiyatin-Epstein (ZBKE) model of the BZ chemical system was used in simulations.;A two-group coupling model, which splits the oscillators into two subpopulations, was used in the first part of the study. The subpopulations are globally coupled, both within and between the subpopulations. The coupling of every oscillator with members of the other subpopulation is weaker than the coupling with members of its own subpopulation. In-phase, out-of-phase, and phase-cluster synchronized states, as well as the chimera state, were found in both experiments and simulations. The probability of finding a chimera state decreases with increasing intra-group coupling strength. The study also revealed that heterogeneity in the frequencies of the oscillators in the system decreases the lifetime of a chimera. This was evidenced by the collapse of the chimera state to a synchronized state in both experiments and simulations with heterogeneous oscillators.;Synchronized and mixed-state behaviors are observed in populations of nonlocally coupled chemical oscillators in a ring configuration. With nonlocal coupling, the nearest neighbors are strongly coupled and the coupling strength decreases exponentially with distance. Experimental studies show stable chimera states, phase cluster states and phase waves coexisting with unsychronized groups of oscillators. These are spontaneously formed from quasi-random initial phase distributions in the experiments and random initial phase distributions in simulations. Simulations with homogeneous and heterogeneous oscillators revealed that a finite spread of frequencies increases the probability of initiating a synchronized group, leading to chimera states. The effects of group size and coupling strength on chimera states, phase waves, phase clusters, and traveling waves are discussed. Complex behaviors in coexisting states were analyzed, consisting of periodic phase slips with identical oscillators and periodic switching with nonidentical oscillators. Fourier transform analysis was used to distinguish between states exhibiting high periodicity and chimera states, which show similar average behavior

Pre-impact fall detection: optimal sensor positioning based on a machine learning paradigm

The aim of this study was to identify the best subset of body segments that provides for a rapid and reliable detection of the transition from steady walking to a slipping event. Fifteen healthy young subjects managed unexpected perturbations during walking. Whole-body 3D kinematics was recorded and a machine learning algorithm was developed to detect perturbation events. In particular, the linear acceleration of all the body segments was parsed by Independent Component Analysis and a Neural Network was used to classify walking from unexpected perturbations. The Mean Detection Time (MDT) was 3516123 ms with an Accuracy of 95.4%. The procedure was repeated with data related to different subsets of all body segments whose variability appeared strongly influenced by the perturbation-induced dynamic modifications. Accordingly, feet and hands accounted for most data information and the performance of the algorithm were slightly reduced using their combination. Results support the hypothesis that, in the framework of the proposed approach, the information conveyed by all the body segments is redundant to achieve effective fall detection, and suitable performance can be obtained by simply observing the kinematics of upper and lower distal extremities. Future studies are required to assess the extent to which such results can be reproduced in older adults and in different experimental conditions

Excitable-like chaotic pulses in the bounded-phase regime of an opto-radiofrequency oscillator

We report theoretical and experimental evidence of chaotic pulses with excitable-like properties in an opto-radiofrequency oscillator based on a self-injected dual-frequency laser. The chaotic attractor involved in the dynamics produces pulses that, albeit chaotic, are quite regular: They all have similar amplitudes, and are almost periodic in time. Thanks to these features, the system displays properties that are similar to those of excitable systems. In particular, the pulses exhibit a threshold-like response, of well-defined amplitude, to perturbations, and it appears possible to define a refractory time. At variance with excitability in injected lasers, here the excitable-like pulses are not accompanied by phase slips.Comment: 2nd versio

Hamiltonian approach to slip-stacking dynamics

Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stacking efficiency. The dynamics are applied specifically to the Fermilab Booster-Recycler complex. The dynamics can also be applied to other accelerator complexes.Comment: 10 p

Bipedial Locomotion Up Sandy Slopes: Systematic Experiments Using Zero Moment Point Methods

Bipedal robotic locomotion in granular media presents a unique set of challenges at the intersection of granular physics and robotic locomotion. In this paper, we perform a systematic experimental study in which biped robotic gaits for traversing a sandy slope are empirically designed using Zero Moment Point (ZMP) methods. We are able to implement gaits that allow our 7 degree-of-freedom planar walking robot to ascend slopes with inclines up to 10°. Firstly, we identify a given set of kinematic parameters that meet the ZMP stability criterion for uphill walking at a given angle. We then find that further relating the step lengths and center of mass heights to specific slope angles through an interpolated fit allows for significantly improved success rates when ascending a sandy slope. Our results provide increased insight into the design, sensitivity and robustness of gaits on granular material, and the kinematic changes necessary for stable locomotion on complex media

How collective asperity detachments nucleate slip at frictional interfaces

Sliding at a quasi-statically loaded frictional interface can occur via macroscopic slip events, which nucleate locally before propagating as rupture fronts very similar to fracture. We introduce a novel microscopic model of a frictional interface that includes asperity-level disorder, elastic interaction between local slip events, and inertia. For a perfectly flat and homogeneously loaded interface, we find that slip is nucleated by avalanches of asperity detachments of extension larger than a critical radius $A_c$ governed by a Griffith criterion. We find that after slip, the density of asperities at a local distance to yielding $x_\sigma$ presents a pseudo-gap $P(x_\sigma) \sim (x_\sigma)^\theta$, where $\theta$ is a non-universal exponent that depends on the statistics of the disorder. This result makes a link between friction and the plasticity of amorphous materials where a pseudo-gap is also present. For friction, we find that a consequence is that stick-slip is an extremely slowly decaying finite size effect, while the slip nucleation radius $A_c$ diverges as a $\theta$-dependent power law of the system size. We discuss how these predictions can be tested experimentally

Tuning of the Active Hair Bundle

The organs of the inner ear rely upon a population of several thousand sensory hair cells to amplify and transduce acoustic, seismic, and kinesthetic signals. Each hair cell detects mechanical disturbances by means of its hair bundle, a motile organelle consisting of actin-filled, villous projections (called stereocilia) endowed with assemblies (called adaptation motors) of mechano-sensitive ion channels and myosin molecules that power both spontaneous and evoked movements. Active hair-bundle motility serves two functions: it mechanically amplifies sensory stimuli; and it regulates their transduction into electrical signals that drive the hair-cell synapse. To characterize these two functions, we consider here a model of the mechanical and electrical dynamics of the hair bundle of the bullfrog sacculus. Under simplifying assumptions, we reduce this model of a muscle fiber, and outline a procedure for estimating its parameters from experiment. We delineate the bifurcation structure of this simplified model, and analyse by perturbation methods its behavior in various dynamical regimes, notably in the relaxation-oscillation regime that displays prominently the hair bundle\u27s active process; and in the near-Hopf-bifurcation regime at which auditory hair cells are thought to operate in vivo. We find close similarities between the dynamics of the active hair bundle and those of simplified models of a spiking neuron. In light of this analysis, we offer an account of the biophysical mechanisms underlying the spontaneous oscillations, frequency specificity, nonlinear gain, and self-tuning predicted for auditory hair bundles poised near a Hopf bifurcation