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In multi-modular process architectures with independent but interacting subsystems, identification may not be the first choice at hand for closed loop control. A robust relay-based PID autotuning strategy is presented and validated on a quadruple tank system with non-minimum phase dynamics. The controller ensures a specified closed loop robustness, which is of great benefit to the overall performance. The experimental results suggest that the proposed method fulfils the robustness requirement and performs well in various operating conditions of the testbench.

A method for estimating the characteristics of the delayed coupling between the oscillatory systems, which is based on the empirical simulation of the phase dynamics with allowance for the phase-noise correlatedness, is proposed. The method efficiency is illustrated FOR the standard stochastic and chaotic oscillators in numerical experiments. Using this method for analyzing climatic time series, we confirm the presence of the delayed influence of the El Nino Southern oscillation on the North Atlantic Oscillation.

Tomography is a non-invasive, non-intrusive imaging technique allowing the visualization of phase dynamics in industrial and biological processes. This article reviews progress in Electrical Capacitance Volume Tomography (ECVT). ECVT is a direct 3D visualizing technique, unlike three-dimensional imaging, which is based on stacking 2D images to obtain an interpolated 3D image. ECVT has recently matured for real time, non-invasive 3-D monitoring of processes involving materials with strong contrast in dielectric permittivity. In this article, ECVT sensor design, optimization and performance of various sensors seen in literature are summarized. Qualitative Analysis of ECVT image reconstruction techniques has also been presented.

We examine the impact of small parity-time () symmetric perturbations on nonlinear optical honeycomb lattices in the tight-binding limit. We show for strained lattices that complex dispersion relationships do not form under perturbation, and we find a variety of nonlinear wave equations which describe the effective dynamics in this regime. The existence of semilocalized gap solitons in this case is also shown, though we numerically demonstrate these solitons are likely unstable. We show for unstrained lattices under the effect of a restricted class of perturbations, which prevent complex dispersion relationships from appearing, that nontrivial phase dynamics emerge as a result of the perturbation. This phase can be understood as momentum imparted to optical beams by the lattice, thus showing perturbations offer potentially novel means for the control of light in honeycomb lattices.

Phase identification is an arduous task during high-throughput processing experiments, which can be exacerbated by the need to reconcile results from multiple measurement techniques to form a holistic understanding of phase dynamics. Here, we demonstrate AutoPhase, a machine learning algorithm, which can identify the presence of the different phases in spectral and diffraction data. The algorithm uses training data to determine the characteristic features of each phase present and then uses these features to evaluate new spectral and diffraction data. AutoPhase was used to identify oxide phase growth during a high-throughput oxidation study of NiAl bond coats that used x-ray diffraction, Raman, and fluorescence spectroscopic techniques. The algorithm had a minimum overall accuracy of 88.9% for unprocessed data and 98.4% for postprocessed data. Although the features selected by AutoPhase for phase attribution were distinct from those of topical experts, these results show that AutoPhase can substantially increase the throughput high-throughput data analysis.

Although the phase shifts in ongoing oscillations seen in electroencephalograms (EEGs) and magnetoencephalograms are an important factor in discussions of phase dynamics, such as synchrony and reset, few studies have focused specifically on the phase shift. Here we investigate the relationship between phase shifts in alpha-frequency rhythms and reaction times during a visual simple reaction task by applying our previously described method (Naruse et al., 2013), which enables detection of phase shifts from a single EEG trial. In the left, parietal, and occipital areas, the reaction times in the trials in which phase shifts were detected before the button press were significantly longer than in those in which phase shifts were not so detected. These results indicate that phase shifts in the alpha and mu rhythms relate to variability in reaction times.

Rider models are employed to gain insight into bicycle rider steering behaviour and to improve characteristic properties of bicycles. In this paper, stability properties as well as basic dynamic characteristics of the passive (uncontrolled) bicycle-rider system and consequences on the rider control modelling are addressed. In particular, the unstable motion of the system at low velocities and bandwidth limitations caused by non-minimum phase dynamics are emphasized. To analyse the effectiveness of the steering torque and the lean torque as possible rider's inputs to control the dynamics of the bicycle, a controllability analysis of the bicycle-rider system has been performed. It turns out that lean torque input, in contrast to steering torque input, has marginal impact on the dynamics of the system. Finally, a bicycle rider control model considering human rider properties is presented, and its capabilities are demonstrated by performing a curve entering manoeuvre.

In this work, we consider a ring of coupled electronic (Wien-bridge) oscillators from a perspective combining modeling, simulation, and experimental observation. Following up on earlier work characterizing the pairwise interaction of Wien-bridge oscillators by Kuramoto-Sakaguchi phase dynamics, we develop a lattice model for a chain thereof, featuring an exponentially decaying spatial kernel. We find that for certain values of the Sakaguchi parameter α, states of traveling phase-domain fronts involving the coexistence of two clearly separated regions of distinct dynamical behavior, can establish themselves in the ring lattice. Experiments and simulations show that stationary coexistence domains of synchronization only manifest themselves with the introduction of a local impurity; here an incoherent cluster of oscillators can arise reminiscent of the chimera states in a range of systems with homogeneous oscillators and suitable nonlocal interactions between them.

Synchronization occurs in many natural and technological systems, from cardiac pacemaker cells to coupled lasers. In the synchronized state, the individual cells or lasers coordinate the timing of their oscillations, but they do not move through space. A complementary form of self-organization occurs among swarming insects, flocking birds, or schooling fish; now the individuals move through space, but without conspicuously altering their internal states. Here we explore systems in which both synchronization and swarming occur together. Specifically, we consider oscillators whose phase dynamics and spatial dynamics are coupled. We call them swarmalators, to highlight their dual character. A case study of a generalized Kuramoto model predicts five collective states as possible long-term modes of organization. These states may be observable in groups of sperm, Japanese tree frogs, colloidal suspensions of magnetic particles, and other biological and physical systems in which self-assembly and synchronization interact., Collective self-organized behavior can be observed in a variety of systems such as colloids and microswimmers. Here O’Keeffe et al. propose a model of oscillators which move in space and tend to synchronize with neighboring oscillators and outline five types of collective self-organized states.

Already several years ago [3], it was suggested that a laser with optical injection can respond to external perturbations by emitting spikes if the perturbation overcomes a certain threshold, all the spikes being identical to each other, in complete analogy with the behaviour of the simple theta-model neuron [1]. The underlying explanation of this phenomenon lies in the isomorphism between a model of neuron [1] and that of an over-damped oscillator with periodic forcing (often called the Adler equation [2]). The control of these spikes was only achieved recently [5], while their observation goes back to [4]. Although there is an excellent agreement between these observations and the predictions of the reduction to pure phase dynamics of a laser model [3], it was soon noticed that whenever the pure phase dynamics reduction ceases to be valid, more complex dynamical phenomena can take place, leading to multipulse excitability [6]. This has led to the investigation of the behaviour of a semiconductor laser locked to an external forcing in response to external perturbations beyond the simple case of the Adler-like mode. We observe resonator features of the neuron-like system and multi-spike responses. Beyond improving the understanding of the neuron-like excitable dynamics of the laser with injected signal, our aim is to leverage the multipulse excitability and the resonator features of the optical neuron analogue for optical data processing and to provide possible insight about complex solitons interactions in forced oscillatory media [7, 8].

The phase dynamics of two parallel connected stacks of intrinsic Josephson junctions (JJs) in high temperature superconductors is numerically investigated. The calculations are based on the system of nonlinear differential equations obtained within the CCJJ + DC model, which allows one to determine the general current-voltage characteristic of the system, as well as each individual stack. The processes with increasing and decreasing base currents are studied. The features in the behavior of the current in each stack of the system due to the switching between the states with rotating and oscillating phases are analyzed.

A two-dimensional D-shaped cylinder and heaving foil were mounted in tandem and used to simulate the main body and tail, respectively, of a natural swimmer. Thrust/drag measurements of the force on the foil and particle image velocimetry measurements of the flow downstream of the swimming system were conducted at a Reynolds number of about $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}10^4$ in a water channel with a constant free stream current speed. Two main sets of measurements were conducted: one set with the swimming system locked at a fixed streamwise location in the water channel as the heave frequency of the foil was varied; the other set with the system freely swimming to a desired set-point position from different upstream and downstream locations. When the freely swimming system reached and maintained its set-point position, so that its swimming speed matched that of the current, the oscillation frequency of the heaving foil corresponded to a Strouhal number of 0.36. Phase portraits of the measured thrust/drag forces reveal limit cycle oscillations for all swimming cases studied, which suggests that self-regulation drives the selection of this Strouhal number. No coupling was observed between the vortices shed by the D-shaped cylinder and the self-selected frequency of the heaving foil during free swimming. An examination of the ratio of the phase-locking indices for the input heaving motion of the foil and the coupled fluidic thrust/drag response reveals that it approaches a value of 0.5 over time when the freely swimming system is released from rest and allowed to achieve steady-state cruising. The jet produced by the freely swimming foil was inclined at an angle of approximately $4^\circ $ with respect to the direction of the mean flow.

This paper aims at doing research on the variation of volume fraction of precipitation. And Avrami empirical equation characterizing the relationship between transformation ratios and ageing time is established. This research was carried out by measuring the electric conductivity of Cu-Ni-Be wedge copper alloy after ageing treatment, and analyzing the relationship between electric conductivity and volume fraction of precipitations. Consequently, the equation between electric conductivity and the ageing time is fixed. Then S-curves of the dynamics of phase dynamics of phase transformation and C-curves of isothermal transformation for the Cu-Ni-Be wedge copper alloy are derived.

We formulate a theory for the collective phase description of globally coupled noisy limit-cycle oscillators exhibiting macroscopic rhythms. Collective phase equations describing such macroscopic rhythms are derived by means of a two-step phase reduction. The collective phase sensitivity and collective phase coupling functions, which quantitatively characterize the macroscopic rhythms, are illustrated using three representative models of limit-cycle oscillators. As an important result of the theory, we demonstrate noise-induced anti-phase synchronization between macroscopic rhythms by direct numerical simulations of the three models., Comment: 19 pages, 11 figures

A minimal model of nonlinear phase dynamics in drift waves is shown to support phase bore solutions. Coupled nonlinear equations for amplitude, phase, and zonal flow are derived for the Hasegawa-Mima system and specialized to the case of spatiotemporally constant amplitude. In that limit, phase curvature (finite second derivative of the phase with respect to the radius) alone generates propagating shear flows. The phase field evolves nonlinearly by a competition between phase steepening and dispersion. The analytical solution of the model reveals that the phase bore solutions so obtained realize the concept of a phase slip in a concrete dynamical model of drift wave dynamics. The implications for phase turbulence are discussed.

Neural oscillatory dynamics are a candidate mechanism to steer perception of time and temporal rate change. While oscillator models of time perception are strongly supported by behavioral evidence, a direct link to neural oscillations and oscillatory entrainment has not yet been provided. In addition, it has thus far remained unaddressed how context-induced illusory percepts of time are coded for in oscillator models of time perception. To investigate these questions, we used magnetoencephalography and examined the neural oscillatory dynamics that underpin pitch-induced illusory percepts of temporal rate change. Human participants listened to frequency-modulated sounds that varied over time in both modulation rate and pitch, and judged the direction of rate change (decrease vs increase). Our results demonstrate distinct neural mechanisms of rate perception: Modulation rate changes directly affected listeners' rate percept as well as the exact frequency of the neural oscillation. However, pitch-induced illusory rate changes were unrelated to the exact frequency of the neural responses. The rate change illusion was instead linked to changes in neural phase patterns, which allowed for single-trial decoding of percepts. That is, illusory underestimations or overestimations of perceived rate change were tightly coupled to increased intertrial phase coherence and changes in cerebro-acoustic phase lag. The results provide insight on how illusory percepts of time are coded for by neural oscillatory dynamics.

A Ginzburg–Landau theory for multi-band mesoscopic Josephson junctions has been developed. The theory, obtained by generalizing the de Gennes matching-matrix method for the interface order parameters, allows the study of the phase dynamics of various types of mesoscopic Josephson junctions. As a relevant application, we studied mesoscopic double-band junctions also in the presence of a superconducting nanobridge interstitial layer. The results are in agreement with a microscopic treatment of the same system. Furthermore, thermal stability of the nanobridge junction is discussed in connection with recent experiments on iron-based grain-boundary junctions.

We consider networks of coupled phase oscillators of different complexity: Kuramoto–Daido-type networks, generalized Winfree networks, and hypernetworks with triple interactions. For these setups an inverse problem of reconstruction of the network connections and of the coupling function from the observations of the phase dynamics is addressed. We show how a reconstruction based on the minimization of the squared error can be implemented in all these cases. Examples include random networks with full disorder both in the connections and in the coupling functions, as well as networks where the coupling functions are taken from experimental data of electrochemical oscillators. The method can be directly applied to asynchronous dynamics of units, while in the case of synchrony, additional phase resettings are necessary for reconstruction.

Light is the primary signal that calibrates circadian neural circuits and thus coordinates daily physiological and behavioral rhythms with solar entrainment cues. Drosophila and mammalian circadian circuits consist of diverse populations of cellular oscillators that exhibit a wide range of dynamic light responses, periods, phases, and degrees of synchrony. How heterogeneous circadian circuits can generate robust physiological rhythms while remaining flexible enough to respond to synchronizing stimuli has long remained enigmatic. Cryptochrome is a short-wavelength photoreceptor that is endogenously expressed in approximately half of Drosophila circadian neurons. In a previous study, physiological light response was measured using real-time bioluminescence recordings in Drosophila whole-brain explants, which remain intrinsically light-sensitive. Here we apply analysis of real-time bioluminescence experimental data to show detailed dynamic ensemble representations of whole circadian circuit light entrainment at single neuron resolution. Organotypic whole-brain explants were either maintained in constant darkness (DD) for 6 days or exposed to a phase-advancing light pulse on the second day. We find that stronger circadian oscillators support robust overall circuit rhythmicity in DD, whereas weaker oscillators can be pushed toward transient desynchrony and damped amplitude to facilitate a new state of phase-shifted network synchrony. Additionally, we use mathematical modeling to examine how a network composed of distinct oscillator types can give rise to complex dynamic signatures in DD conditions and in response to simulated light pulses. Simulations suggest that complementary coupling mechanisms and a combination of strong and weak oscillators may enable a robust yet flexible circadian network that promotes both synchrony and entrainment. A more complete understanding of how the properties of oscillators and their signaling mechanisms facilitate their distinct roles in light entrainment may allow us to direct and augment the circadian system to speed recovery from jet lag, shift work, and seasonal affective disorder.

Phase plays a crucial role in many quantum effects including interference. Here we lay the foundations for the study of phase in probabilistic theories more generally. Phase is normally defined in terms of complex numbers that appear when representing quantum states as complex vectors. Here we give an operational definition whereby phase is instead defined in terms of measurement statistics. Our definition is phrased in terms of the operational framework known as generalized probabilistic theories or the convex framework. The definition makes it possible to ask whether other theories in this framework can also have phase. We apply our definition to investigate phase and interference in several example theories: classical probability theory, a version of Spekkens' toy model, quantum theory and box-world. We find that phase is ubiquitous; any non-classical theory can be said to have non-trivial phase dynamics. © IOP Publishing and Deutsche Physikalische Gesellschaft.

Synchronization phenomena in a fluid dynamical analogue of atmospheric circulation is studied experimentally by investigating the dynamics of a pair of thermally coupled, rotating baroclinic annulus systems. The coupling between the systems is in the well-known master-slave configuration in both periodic and chaotic regimes. Synchronization tools such as phase dynamics analysis are used to study the dynamics of the coupled system and demonstrate phase synchronization and imperfect phase synchronization, depending upon the coupling strength and parameter mismatch.

Characterizing the complicated flow behaviors arising from high water cut and low velocity oil-water flows is an important problem of significant challenge. We design a high-speed cycle motivation conductance sensor and carry out experiments for measuring the local flow information from different oil-in-water flow patterns. We first use multivariate time-frequency analysis to probe the typical features of three flow patterns from the perspective of energy and frequency. Then we infer complex networks from multi-channel measurements in terms of phase lag index, aiming to uncovering the phase dynamics governing the transition and evolution of different oil-in-water flow patterns. In particular, we employ spectral radius and weighted clustering coefficient entropy to characterize the derived unweighted and weighted networks and the results indicate that our approach yields quantitative insights into the phase dynamics underlying the high water cut and low velocity oil-water flows.

Alpha oscillations are modulated in response to visual temporal and spatial cues, However, the neural response to alerting cues is less explored, as is how this response is affected by healthy aging. Using scalp EEG, we examined how visual cortical alpha activity relates to working memory performance. Younger (20-30 years) and older (60-70 years) participants were presented with a visual alerting cue uninformative of the position or size of a lateralized working memory array. Older adults showed longer response times overall, and reduced accuracy when memory load was high. Older adults had less consistent cue-evoked phase resetting than younger adults, which predicted worse performance. Alpha phase prior to memory array presentation predicted response time, but the relationship between phase and response time was weaker in older adults. These results suggest that changes in alpha phase dynamics, especially prior to presentation of task-relevant stimuli, potentially contribute to age-related cognitive decline.

Phase dynamics of disordered Josephson junction ladders (JJLs) driven by external currents which are spatially and temporally modulated is studied using a numerical simulation based on a random field XY model. This model is considered theoretically as an effective model of JJLs with structural disorder in a magnetic field. The spatiotemporal modulation of external currents causes peculiar dynamical effects of phases in the system under certain conditions, such as the directed motion of phases and the mode-locking in the absence of dc currents. We clarify the details of effects of the spatiotemporal modulation on the phase dynamics.

By applying the ‘theory of synchronization’ from the science of complexity to studying the regional regularity of ore formation within the Nanling region of South China, a characteristic target-pattern regional ore zonality has been discovered. During the early and late Yanshanian epoch (corresponding respectively to the Jurassic and Cretaceous periods), two centers of ore formation emerged successively in the Nanling region; the former is mainly for rare metals (W, Sn, Mo, Bi, Nb) and one rare-earth element (La) and was generated in the Jurassic period; whereas the latter is mainly for base metals (Cu, Pb, Zn, Sb, Hg), noble metals (Au, Ag), and one radioactive element (U) and was generated in the Cretaceous period. Centers of ore formation were brought about by interface dynamics respectively at the Qitianling and Jiuyishan districts in southern Hunan Province. The characteristic giant nonlinear target-pattern regional ore zonality was generated respectively from the two centers of ore formation by the spatio-temporal synchronization process of the Nanling complex metallogenic system. It induced the collective dynamics and cooperative behavior of the system and displayed the configuration of the regional ore zonality. Then dynamical clustering transformed the configuration into rudimentary ordered coherent structures. Phase dynamics eventually defined the spatio-temporal structures of the target-pattern regional ore zonality and determined their localization and distribution. The integral successive processes of synchronization-dynamical clustering-phase dynamics accomplished the regional ore zonality by way of “multiple field dynamics” of spatio-temporal superposition of multiple coupled pulsatory solitary wave trains of the zonal sequences of different ores. A new methodology for revealing regional ore zonality is developed, which will encourage further investigation of the formation of deep-seated ore resources and the onset of large-scale mineralization.

[EN] The microstructure of rubber-modified polystyrene after thermal ageing at 90 °C and multiple extrusion was analyzed by time-domain nuclear magnetic resonance (TD-NMR) in a non-destructive manner. The transverse magnetization decay behaviour observed in TD-NMR was related to the total rubber fraction and its cross-linking density. The data reveal different mechanisms of long-term rubber degradation in high-impact polystyrene (HIPS) during thermo-oxidation and multiple processing: Multiple processing causes a slight increase in the cross-linking density of the rubber phase, without appreciably altering the total amount of rubber fraction. Thermo-oxidation is accompanied by a significant overall decrease of the rubber fraction, an increase of the cross-linking density, and a pronounced increase of the non-crosslinked fraction (chain ends and fragmented segments). The NMR results correlate well with spectroscopic observations and moderately with macroscopic mechanical properties. © 2011 Elsevier Ltd. All rights reserved., The lab support for the NMR studies by Jens Schober and Cornelia Willax is gratefully acknowledged. FV thanks the economical support of the Spanish Ministry of Science and Innovation through the FPU doctoral program.

The need to estimate the delay times between elements of coupled oscillatory ensembles is frequently encountered in the analysis of systems of various natures, for which only separate records (time series) of the observed oscillations are available. The possibility of obtaining these estimates in the case of relatively short time series recorded in the presence of noise is considered. Using the well-known point estimator based on a model of the phase dynamics, an interval estimator is proposed, a correction that eliminates a bias of the point estimate is introduced, and a formula for the confidence interval is derived based on the maximum likelihood formalism. Possibilities of the proposed approach are illustrated by the results of numerical experiments in systems of coupled oscillators.

This paper proposes distributed control laws for formations of swimming robotic fish generating antiphase sinusoidal body waves. The control laws are inspired by the mathematical model for the hydrodynamics of schools of cruising fish, which reveals that fish swimming in diamond-shape formations with synchronized antiphase body waves can benefit greatly from energy saving. The phase dynamics of the body waves of the robotic fish are modeled by coupled Kuramoto oscillators and the stability analysis for the phase dynamics are carried out for coupling topologies corresponding to diamond-shape formations. It is proven that the body waves can be synchronized in specific antiphase patterns. Simulations and experiments further validate the effectiveness of the proposed control laws.

We develop a systematic method for deriving the phase dynamics of perturbed periodic solutions. The method is to regard periodic solutions as slowly modulated traveling solutions on the circle. There, problems are reduced to the perturbed problems from stationary solutions on the circle. This makes the treatment of periodic solutions far easier and systematic. We also give the rigorous proofs for this method.

Introduction: Sighs (deep inspirations) are thought to have an importantrole in restoring lung volume, resetting the mechanical propertiesof lung tissue and in changing neurorespiratory control. Especially, inquiet or non-rapid eye movement sleep, sighs may be followed bycentral apnea. Sighs reduce in frequency with maturation over the fi rstyear of life. We speculated that strength of cardiorespiratory synchronization(CS) and direction of cardiorespiratory coupling (DC), as ameasure of neurorespiratory control, would differ before and after sigh,and between sighs with and without central apnea, and that there wouldbe a maturational effect.Methodology: CS and DC were assessed by a phase dynamics methodpreceding and following sigh (with and without central apnea) in 15healthy infants at 2 weeks, 3 months and 6 months of age. The CSindex varied from 0 (unsynchronized) to 1 (perfectly synchronized).The DC index varies from −1 (if the direction of coupling is from respirationto heart rate) to 1 (in the opposite directional coupling fromheart rate to respiration), and −1 < DC index < 1 indicates bidirectionalcoupling.Results and discussion: Our results show a signifi cant decrease in CSand respiratory modulation on heart rate (RMH) (interpreted by “negative”DC index) prior to sighs with central apnea compared to sighsalone. Prior to a sigh, CS index was lower with sigh followed by centralapnea (0.58, 0.66, 0.64 at 2 weeks, 3 months and 6 months of age,respectively) than with sigh alone (0.63, 0.71, 0.76, respectively). Onthe other hand, prior to a sigh, DC index was higher with sigh followedby central apnea (−0.45, −0.67, −0.77 at 2 weeks, 3 months and6 months of age, respectively) than with sigh alone from (−0.50, −0.79,−0.80, respectively). We found that RMH increased after a sigh (withor without central apnea), suggesting the involvement of sighs in regulationand resetting of the neurorespiratory controller. Using neonataldata as a reference, CS and RMH increased at 3 months and furtherincreased at 6 months of age. The greatest change was observed between2 weeks and 3 months of age.Conclusion: CS in infants changes with maturation and is differentbefore a sigh with and without central apnea as well as changes beforeand after a sigh, suggesting a neuroregulatory role of sigh.

The detailed investigation of the phase dynamics and the I–V curves in the system of coupled Josephson junctions have been carried out. The superconducting, quasiparticle, diffusion, and displacement currents have been calculated as functions of the total current through the system. The role of the diffusion current in the formation of the I–V curves has been studied and the influence of this quantity on the I–V curve branching and the magnitude of the return current has been revealed. The calculation results agree qualitatively with the experimental data.

Based on the model system undergoing phase separation and chemical reactions, we investigate the dynamics of propagating dissipative waves under external forcing which is periodic both in space and time. A phase diagram for the entrained and non-entrained states under the external forcing is obtained numerically. Theoretical analysis in terms of phase description of the traveling waves is carried out to show that the transition between the entrained and the non-entrained states by changing the external frequency occurs either through a saddle-node bifurcation or through a Hopf bifurcation and that these two bifurcation lines are connected at a Bogdanov-Takens bifurcation point.

Previous studies have shown only modest effects of supramammillary nucleus (SuM) dysfunction on theta frequency and learning in the water maze (WM), with larger effects in other tasks. However, theta recorded from SuM, and used to trigger the production of theta-like oscillations in the hippocampus, produced reversal of the deficit in WM learning produced by theta blocking. We explored this apparent inconsistency by analyzing the relationship between SuM and hippocampal theta in the control group of this theta-blocking experiment using coherence, phase analysis, and the directed transfer function. We found little evidence of an influence of SuM on the hippocampus in the bulk of WM learning-with some possibility of SuM becoming involved briefly later in learning. A learning-related increase in coherence was observed in conjunction with gradual phase reorganization of hippocampal theta in relation to SuM theta. This change in phase dynamics between the two structures was also correlated with a relative increase of the estimated direction of theta propagation from the SuM to the hippocampus. These results are consistent with the previous weak effects of SuM lesions and suggest that the use of SuM as a source to trigger hippocampal theta and recover function is likely to be due to coherence between SuM and some other structure that normally controls hippocampal theta during WM learning.

This article is available open access through the publisher’s website at the link below. Copyright @ The Author 2010. Bimanual coordination requires the functional integration of the activity in various cortical, subcortical, spinal, and peripheral neural structures. We challenged this functional integration by destabilizing bimanual 5:8 tapping through an increase in movement tempo, while measuring brain and muscle activity using magnetoencephalography and electromyography. Movement instabilities were characterized by a drop in frequency locking. Time–frequency analysis revealed movement-related beta amplitude modulation in bilateral motor areas as well as movement-related corticospinal entrainment. Both of these synchronization patterns depended on movement tempo suggesting that the timescale needed for the upregulation and downregulation of beta synchrony in rhythmic tapping poses constraints on motor performance. Bilateral phase locking over movement cycles appeared to be mediated by beta-frequency oscillations and constrained by its phase dynamics. The timescale of beta synchrony thus seems to play a key role in achieving timed phase synchrony in the motor cortex and along the neural axis. Once event-related desynchronization–synchronization cycles cannot be build up properly, inhibition may become inadequate, resulting in a reduction of the stability of performance, which may eventually become unstable. Netherlands Organisation for Scientific Research

Single-track vehicles such as motorcycles or bicycles provide an agile mobile platform. Control of motorcycles is challenging due to its underactuation and non-minimum phase dynamics properties. In this paper, we present a maneuver regulation control design for autonomous motorcycles. The maneuver regulation control guides the vehicle to follow a desired path and automatically tunes the desired velocity. We extend the motorcycle dynamics by including the coupled longitudinal/lateral tire/road interaction. We then design a velocity field for regulating vehicle maneuvers. The velocity field-based maneuver regulation design is integrated with the previously established trajectory tracking controller for motorcycle systems. Simulation results are presented to illustrate the maneuver regulation design.

The relations between the processes occurring in the equatorial latitudes of the Pacific and Atlantic oceans were studied on the basis of the Granger causality analysis and a simulation of phase dynamics using the indices of the El Nino-Southern Oscillation (ENSO) and the equatorial Atlantic mode (EAM). Data on the monthly means of the sea-surface temperature over the period 1870–2006 for the Nino 3 (5° S-5° N, 150° W-90° W) and Nino 3.4 (5° S-5° N, 170° W-120° W) regions in the Pacific and the Atlantic 3 region (20° W-0, 3° S-3° N) in the Atlantic Ocean were used as the ENSO and EAM indices. The statistically significant influence of the EAM on the ENSO is noted. The lag time of this influence is estimated at two months. No significant reverse effect is revealed. An increase in the EAM’s influence on the ENSO was observed in the second half of the 20th century.

A quantitative summary of computer models in diving applications is presented, underscoring dual phase dynamics and quantifying metrics in tissue and blood. Algorithms covered include the multitissue, diffusion, split phase gradient, linear-exponential, asymmetric tissue, thermodynamic, varying permeability, reduced gradient bubble, tissue bubble diffusion, and linear-exponential phase models. Defining relationships are listed, and diver staging regimens are underscored. Implementations, diving sectors, and correlations are indicated for models with a history of widespread acceptance, utilization, and safe application across recreational, scientific, military, research, and technical communities. Presently, all models are incomplete, but many (included above) are useful, having resulted in diving tables, underwater meters, and dive planning software. Those herein employ varying degrees of calibration and data tuning. We discuss bubble metrics in tissue and blood as a backdrop against computer models. The past 15 years, or so, have witnessed changes and additions to diving protocols and table procedures, such as shorter nonstop time limits, slower ascent rates, shallow safety stops, ascending repetitive profiles, deep decompression stops, helium based breathing mixtures, permissible reverse profiles, multilevel techniques, both faster and slower controlling repetitive tissue halftimes, smaller critical tensions, longer flying-after-diving surface intervals, and others. Stimulated by Doppler and imaging technology, table and decompression meter development, theory, statistics, chamber and animal testing, or safer diving consensus, these modifications affect a gamut of activity, spanning bounce to decompression, single to multiday, and air to mixed gas diving. As it turns out, there is growing support for many protocols on operational, experimental, and theoretical grounds, with bubble models addressing many concerns on plausible bases, but with further testing or profile data analyses requisite.

Spiral turbulence observed in Couette-Taylor system has been characterized using the phase diffusion equation suggested by Hegseth et al. [Phys. Rev. Lett. 62, 257 (1989)]. From space-time diagrams, we have measured the diffusion coefficient, the diffusion velocity, and the turbulent spiral pitch.

A piezoelectric tube is shown to have linear, but non-minimum phase dynamics. The main impediment to the actuation of this piezoelectric tube is the presence of a low-frequency resonant mode which causes mechanical vibrations. A physical-model-based control method is extended to non-minimum phase systems in general and successfully applied to damp the resonant mode; leading to a vibration-free actuation of the piezoelectric tube.

We explore identical R\"ossler systems organized into two equally-sized groups, among which differing positive and negative in- and out-coupling strengths are allowed. Patterns of distinctly synchronized phase dynamics are observed, which coexist with chaotically evolving amplitudes. In particular, we report the emergence of traveling phase waves, i.e. states in which the oscillators settle on a new rhythm different from their own. We further elucidate our findings through phase-coupled R\"ossler systems, establishing a connection with the Kuramoto model. Together with the study of noise effects, our results suggest a promising new avenue towards the coexistence of chaotic, noisy and regular collective dynamics., Comment: 5 pages, 4 figures and Supplemental Material

Multi-electrode recordings of local field potentials (LFPs) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFPs allow studying the coordination of neural oscillations in time and space and to tie it to cognitive processing. Given the computational roles of LFP phases, it is important to know how they relate to the phases of the underlying current source densities (CSDs) that generate them. Although CSDs and LFPs are distinct physical quantities, they are often (implicitly) identified when interpreting experimental observations. That this identification is problematic is clear from the fact that LFP phases change when switching to different electrode montages, while the underlying CSD phases remain unchanged. In this study we use a volume-conductor model to characterize discrepancies between LFP and CSD phase-patterns, to identify the contributing factors, and to assess the effect of different electrode montages. Although we focus on cortical LFPs recorded with two-dimensional (Utah) arrays, our findings are also relevant for other electrode configurations. We found that the main factors that determine the discrepancy between CSD and LFP phase-patterns are the frequency of the neural oscillations and the extent to which the laminar CSD profile is balanced. Furthermore, the presence of laminar phase-differences in cortical oscillations, as commonly observed in experiments, precludes identifying LFP phases with those of the CSD oscillations at a given cortical depth. This observation potentially complicates the interpretation of spike-LFP coherence and spike-triggered LFP averages. With respect to reference strategies, we found that the average-reference montage leads to larger discrepancies between LFP and CSD phases as compared with the referential montage, while the Laplacian montage reduces these discrepancies. We therefore advice to conduct analysis of two-dimensional LFP recordings using the Laplacian montage. RH and GD were funded by the European Research Council (Advanced Grant DYSTRUCTURE No. 295129), the Spanish Research Project PSI2013-42091-P, the CONSOLIDER-INGENIO 2010 Program CSD2007-00012, and the FP7-ICT Brainscales (269921). XA and PV are supported by the European Research Council's CDAC project: “The Role of Consciousness in Adaptive Behavior: A Combined Empirical, Computational and Robot based Approach” (ERC-2013- ADG 341196).

We experimentally analyze extreme events in a fast (nanosecond) spatially extended oscillatory medium with coherent forcing. We focus on individual events and their emergence in the (spatio-temporally resolved) optical phase dynamics.

We perform experiments and phase model simulations with a ring network of oscillatory electrochemical reactions to explore the effect of random connections and non-isochronocity of the interactions on the pattern formation. A few additional links facilitate the emergence of the fully synchronized state. With larger non-isochronicity, complex rotating waves or persistent irregular phase dynamics can derail the convergence to global synchronization. The observed long transients of irregular phase dynamics exemplify the possibility of a sudden onset of hyper synchronous behavior without any external stimulus or network reorganization., Comment: 4 pages main text and 4 pages supplemental material