Dynamic system simulation of small satellite projects

NASA Astrophysics Data System (ADS)

Raif, Matthias; Walter, Ulrich; Bouwmeester, Jasper

2010-11-01

A prerequisite to accomplish a system simulation is to have a system model holding all necessary project information in a centralized repository that can be accessed and edited by all parties involved. At the Institute of Astronautics of the Technische Universitaet Muenchen a modular approach for modeling and dynamic simulation of satellite systems has been developed called dynamic system simulation (DySyS). DySyS is based on the platform independent description language SysML to model a small satellite project with respect to the system composition and dynamic behavior. A library of specific building blocks and possible relations between these blocks have been developed. From this library a system model of the satellite of interest can be created. A mapping into a C++ simulation allows the creation of an executable system model with which simulations are performed to observe the dynamic behavior of the satellite. In this paper DySyS is used to model and simulate the dynamic behavior of small satellites, because small satellite projects can act as a precursor to demonstrate the feasibility of a system model since they are less complex compared to a large scale satellite project.

Variable threshold algorithm for division of labor analyzed as a dynamical system.

PubMed

Castillo-Cagigal, Manuel; Matallanas, Eduardo; Navarro, Iñaki; Caamaño-Martín, Estefanía; Monasterio-Huelin, Félix; Gutiérrez, Álvaro

2014-12-01

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

The dynamics of perception and action.

PubMed

Warren, William H

2006-04-01

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are treated as a pair of dynamical systems that are coupled mechanically and informationally. Their interactions give rise to the behavioral dynamics, a vector field with attractors that correspond to stable task solutions, repellers that correspond to avoided states, and bifurcations that correspond to behavioral transitions. The framework is used to develop theories of several tasks in which a human agent interacts with the physical environment, including bouncing a ball on a racquet, balancing an object, braking a vehicle, and guiding locomotion. Stable, adaptive behavior emerges from the dynamics of the interaction between a structured environment and an agent with simple control laws, under physical and informational constraints. ((c) 2006 APA, all rights reserved).

Sustainability through Dynamic Energy Management - Continuum Magazine |

Science.gov Websites

NREL Sustainability through Dynamic Energy Management Sustainability through Dynamic Energy Management Integrating behavior change with advanced building systems is the new model in energy efficiency , it's necessary to integrate dynamic energy management with occupant behavior change. As plans were

Dynamic interaction of monowheel inclined vehicle-vibration platform coupled system with quadratic and cubic nonlinearities

NASA Astrophysics Data System (ADS)

Zhou, Shihua; Song, Guiqiu; Sun, Maojun; Ren, Zhaohui; Wen, Bangchun

2018-01-01

In order to analyze the nonlinear dynamics and stability of a novel design for the monowheel inclined vehicle-vibration platform coupled system (MIV-VPCS) with intermediate nonlinearity support subjected to a harmonic excitation, a multi-degree of freedom lumped parameter dynamic model taking into account the dynamic interaction of the MIV-VPCS with quadratic and cubic nonlinearities is presented. The dynamical equations of the coupled system are derived by applying the displacement relationship, interaction force relationship at the contact position and Lagrange's equation, which are further discretized into a set of nonlinear ordinary differential equations with coupled terms by Galerkin's truncation. Based on the mathematical model, the coupled multi-body nonlinear dynamics of the vibration system is investigated by numerical method, and the parameters influences of excitation amplitude, mass ratio and inclined angle on the dynamic characteristics are precisely analyzed and discussed by bifurcation diagram, Largest Lyapunov exponent and 3-D frequency spectrum. Depending on different ranges of system parameters, the results show that the different motions and jump discontinuity appear, and the coupled system enters into chaotic behavior through different routes (period-doubling bifurcation, inverse period-doubling bifurcation, saddle-node bifurcation and Hopf bifurcation), which are strongly attributed to the dynamic interaction of the MIV-VPCS. The decreasing excitation amplitude and inclined angle could reduce the higher order bifurcations, and effectively control the complicated nonlinear dynamic behaviors under the perturbation of low rotational speed. The first bifurcation and chaotic motion occur at lower value of inclined angle, and the chaotic behavior lasts for larger intervals with higher rotational speed. The investigation results could provide a better understanding of the nonlinear dynamic behaviors for the dynamic interaction of the MIV-VPCS.

A nonlinear dynamical system for combustion instability in a pulse model combustor

NASA Astrophysics Data System (ADS)

Takagi, Kazushi; Gotoda, Hiroshi

2016-11-01

We theoretically and numerically study the bifurcation phenomena of nonlinear dynamical system describing combustion instability in a pulse model combustor on the basis of dynamical system theory and complex network theory. The dynamical behavior of pressure fluctuations undergoes a significant transition from steady-state to deterministic chaos via the period-doubling cascade process known as Feigenbaum scenario with decreasing the characteristic flow time. Recurrence plots and recurrence networks analysis we adopted in this study can quantify the significant changes in dynamic behavior of combustion instability that cannot be captured in the bifurcation diagram.

Emergent phases and critical behavior in a non-Markovian open quantum system

NASA Astrophysics Data System (ADS)

Cheung, H. F. H.; Patil, Y. S.; Vengalattore, M.

2018-05-01

Open quantum systems exhibit a range of novel out-of-equilibrium behavior due to the interplay between coherent quantum dynamics and dissipation. Of particular interest in these systems are driven, dissipative transitions, the emergence of dynamical phases with novel broken symmetries, and critical behavior that lies beyond the conventional paradigm of Landau-Ginzburg phenomenology. Here, we consider a parametrically driven two-mode system in the presence of non-Markovian system-reservoir interactions. We show that the non-Markovian dynamics modifies the phase diagram of this system, resulting in the emergence of a broken symmetry phase in a universality class that has no counterpart in the corresponding Markovian system. This emergent phase is accompanied by enhanced two-mode entanglement that remains robust at finite temperatures. Such reservoir-engineered dynamical phases can potentially shed light on universal aspects of dynamical phase transitions in a wide range of nonequilibrium systems, and aid in the development of techniques for the robust generation of entanglement and quantum correlations at finite temperatures with potential applications to quantum control, state preparation, and metrology.

A novel system for tracking social preference dynamics in mice reveals sex- and strain-specific characteristics.

PubMed

Netser, Shai; Haskal, Shani; Magalnik, Hen; Wagner, Shlomo

2017-01-01

Deciphering the biological mechanisms underlying social behavior in animal models requires standard behavioral paradigms that can be unbiasedly employed in an observer- and laboratory-independent manner. During the past decade, the three-chamber test has become such a standard paradigm used to evaluate social preference (sociability) and social novelty preference in mice. This test suffers from several caveats, including its reliance on spatial navigation skills and negligence of behavioral dynamics. Here, we present a novel experimental apparatus and an automated analysis system which offer an alternative to the three-chamber test while solving the aforementioned caveats. The custom-made apparatus is simple for production, and the analysis system is publically available as an open-source software, enabling its free use. We used this system to compare the dynamics of social behavior during the social preference and social novelty preference tests between male and female C57BL/6J mice. We found that in both tests, male mice keep their preference towards one of the stimuli for longer periods than females. We then employed our system to define several new parameters of social behavioral dynamics in mice and revealed that social preference behavior is segregated in time into two distinct phases. An early exploration phase, characterized by high rate of transitions between stimuli and short bouts of stimulus investigation, is followed by an interaction phase with low transition rate and prolonged interactions, mainly with the preferred stimulus. Finally, we compared the dynamics of social behavior between C57BL/6J and BTBR male mice, the latter of which are considered as asocial strain serving as a model for autism spectrum disorder. We found that BTBR mice ( n  = 8) showed a specific deficit in transition from the exploration phase to the interaction phase in the social preference test, suggesting a reduced tendency towards social interaction. We successfully employed our new experimental system to unravel previously unidentified sex- and strain-specific differences in the dynamics of social behavior in mice. Thus, the system presented here facilitates a more thorough and detailed analysis of social behavior in small rodent models, enabling a better comparison between strains and treatments.

The Behavioral Type of a Top Predator Drives the Short-Term Dynamic of Intraguild Predation.

PubMed

Michalko, Radek; Pekár, Stano

2017-03-01

Variation in behavior among individual top predators (i.e., the behavioral type) can strongly shape pest suppression in intraguild predation (IGP). However, the effect of a top predator's behavioral type-namely, foraging aggressiveness (number of killed divided by prey time) and prey choosiness (preference degree for certain prey type)-on the dynamic of IGP may interact with the relative abundances of top predator, mesopredator, and pest. We investigated the influence of the top predator's behavioral type on the dynamic of IGP in a three-species system with a top predator spider, a mesopredator spider, and a psyllid pest using a simulation model. The model parameters were estimated from laboratory experiments and field observations. The top predator's behavioral type altered the food-web dynamics in a context-dependent manner. The system with an aggressive/nonchoosy top predator, without prey preferences between pest and mesopredator, suppressed the pest more when the top predator to mesopredator abundance ratio was high. In contrast, the system with a timid/choosy top predator that preferred the pest to the mesopredator was more effective when the ratio was low. Our results show that the behavioral types and abundances of interacting species need to be considered together when studying food-web dynamics, because they evidently interact. To improve biocontrol efficiency of predators, research on the alteration of their behavioral types is needed.

Spin dynamics of random Ising chain in coexisting transverse and longitudinal magnetic fields

NASA Astrophysics Data System (ADS)

Liu, Zhong-Qiang; Jiang, Su-Rong; Kong, Xiang-Mu; Xu, Yu-Liang

2017-05-01

The dynamics of the random Ising spin chain in coexisting transverse and longitudinal magnetic fields is studied by the recursion method. Both the spin autocorrelation function and its spectral density are investigated by numerical calculations. It is found that system's dynamical behaviors depend on the deviation σJ of the random exchange coupling between nearest-neighbor spins and the ratio rlt of the longitudinal and the transverse fields: (i) For rlt = 0, the system undergoes two crossovers from N independent spins precessing about the transverse magnetic field to a collective-mode behavior, and then to a central-peak behavior as σJ increases. (ii) For rlt ≠ 0, the system may exhibit a coexistence behavior of a collective-mode one and a central-peak one. When σJ is small (or large enough), system undergoes a crossover from a coexistence behavior (or a disordered behavior) to a central-peak behavior as rlt increases. (iii) Increasing σJ depresses effects of both the transverse and the longitudinal magnetic fields. (iv) Quantum random Ising chain in coexisting magnetic fields may exhibit under-damping and critical-damping characteristics simultaneously. These results indicate that changing the external magnetic fields may control and manipulate the dynamics of the random Ising chain.

Nanopore Current Oscillations: Nonlinear Dynamics on the Nanoscale.

PubMed

Hyland, Brittany; Siwy, Zuzanna S; Martens, Craig C

2015-05-21

In this Letter, we describe theoretical modeling of an experimentally realized nanoscale system that exhibits the general universal behavior of a nonlinear dynamical system. In particular, we consider the description of voltage-induced current fluctuations through a single nanopore from the perspective of nonlinear dynamics. We briefly review the experimental system and its behavior observed and then present a simple phenomenological nonlinear model that reproduces the qualitative behavior of the experimental data. The model consists of a two-dimensional deterministic nonlinear bistable oscillator experiencing both dissipation and random noise. The multidimensionality of the model and the interplay between deterministic and stochastic forces are both required to obtain a qualitatively accurate description of the physical system.

Dynamic Investigation of Static Divergence: Analysis and Testing

NASA Technical Reports Server (NTRS)

Heeg, Jennifer

2000-01-01

The phenomenon known as aeroelastic divergence is the focus of this work. The analyses and experiment presented here show that divergence can occur without a structural dynamic mode losing its oscillatory nature. Aeroelastic divergence occurs when the structural restorative capability or stiffness of a structure is overwhelmed by the static aerodynamic moment. This static aeroelastic coupling does not require the structural dynamic system behavior to cease, however. Aeroelastic changes in the dynamic mode behavior are governed not only by the stiffness, but by damping and inertial properties. The work presented here supports these fundamental assertions by examining a simple system: a typical section airfoil with only a rotational structural degree of freedom. Analytical results identified configurations that exhibit different types of dynamic mode behavior as the system encounters divergence. A wind tunnel model was designed and tested to examine divergence experimentally. The experimental results validate the analytical calculations and explicitly examine the divergence phenomenon where the dynamic mode persists. Three configurations of the wind tunnel model were tested. The experimental results agree very well with the analytical predictions of subcritical characteristics, divergence velocity, and behavior of the noncritical dynamic mode at divergence.

How to analytically characterize the epidemic threshold within the coupled disease-behavior systems?. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Xia, Cheng-Yi; Ding, Shuai; Sun, Shi-Wen; Wang, Li; Gao, Zhong-Ke; Wang, Juan

2015-12-01

As is well known, outbreak of epidemics may drive the human population to take some necessary measures to protect themselves from not being infected by infective ones, these precautions in turn will also keep from the further spreading of infectious diseases among the population. Thus, to fully comprehend the epidemic spreading behavior within real-world systems, the interplay between disease dynamics and human behavioral and social dynamics needs to be considered simultaneously, such that some effective containment-measures can be successfully developed [1-3].

Application of finite-element methods to dynamic analysis of flexible spatial and co-planar linkage systems, part 2

NASA Technical Reports Server (NTRS)

Dubowsky, Steven

1989-01-01

An approach is described to modeling the flexibility effects in spatial mechanisms and manipulator systems. The method is based on finite element representations of the individual links in the system. However, it should be noted that conventional finite element methods and software packages will not handle the highly nonlinear dynamic behavior of these systems which results form their changing geometry. In order to design high-performance lightweight systems and their control systems, good models of their dynamic behavior which include the effects of flexibility are required.

Special Educators as Intervention Specialists: Dynamic Systems and the Complexity of Intensifying Intervention for Students With Emotional and Behavioral Disorders

ERIC Educational Resources Information Center

Farmer, Thomas W.; Sutherland, Kevin S.; Talbott, Elizabeth; Brooks, Debbie S.; Norwalk, Kate; Huneke, Michelle

2016-01-01

We present a dynamic systems perspective for the intensification of interventions for students with emotional and behavioral disorders (EBD). With this framework, we suggest behavior involves the contributions of multiple factors and reflects the interplay between the characteristics of the student and the ecologies in which he or she is embedded.…

Dynamics of Numerics & Spurious Behaviors in CFD Computations. Revised

NASA Technical Reports Server (NTRS)

Yee, Helen C.; Sweby, Peter K.

1997-01-01

The global nonlinear behavior of finite discretizations for constant time steps and fixed or adaptive grid spacings is studied using tools from dynamical systems theory. Detailed analysis of commonly used temporal and spatial discretizations for simple model problems is presented. The role of dynamics in the understanding of long time behavior of numerical integration and the nonlinear stability, convergence, and reliability of using time-marching approaches for obtaining steady-state numerical solutions in computational fluid dynamics (CFD) is explored. The study is complemented with examples of spurious behavior observed in steady and unsteady CFD computations. The CFD examples were chosen to illustrate non-apparent spurious behavior that was difficult to detect without extensive grid and temporal refinement studies and some knowledge from dynamical systems theory. Studies revealed the various possible dangers of misinterpreting numerical simulation of realistic complex flows that are constrained by available computing power. In large scale computations where the physics of the problem under study is not well understood and numerical simulations are the only viable means of solution, extreme care must be taken in both computation and interpretation of the numerical data. The goal of this paper is to explore the important role that dynamical systems theory can play in the understanding of the global nonlinear behavior of numerical algorithms and to aid the identification of the sources of numerical uncertainties in CFD.

Seasonal frost effects on the dynamic behavior of a twenty-story office building

USGS Publications Warehouse

Yang, Z.; Dutta, U.; Xiong, F.; Biswas, N.; Benz, H.

2008-01-01

Studies have shown that seasonal frost can significantly affect the seismic behavior of a bridge foundation system in cold regions. However, little information could be found regarding seasonal frost effects on the dynamic behavior of buildings. Based on the analysis of building vibration data recorded by a permanent strong-motion instrumentation system, the objective of this paper is to show that seasonal frost can impact the building dynamic behavior and the magnitude of impact may be different for different structures. Ambient noise and seismic data recorded on a twenty-story steel-frame building have been analyzed to examine the building dynamic characteristics in relationship to the seasonal frost and other variables including ground shaking intensity. Subsequently, Finite Element modeling of the foundation-soil system and the building superstructure was conducted to verify the seasonal frost effects. The Finite Element modeling was later extended to a reinforced-concrete (RC) type building assumed to exist at a similar site as the steel-frame building. Results show that the seasonal frost has great impact on the foundation stiffness in the horizontal direction and a clear influence on the building dynamic behavior. If other conditions remain the same, the effects of seasonal frost on structural dynamic behavior may be much more prominent for RC-type buildings than for steel-frame buildings. ?? 2007 Elsevier B.V. All rights reserved.

The Feldenkrais Method: A Dynamic Approach to Changing Motor Behavior.

ERIC Educational Resources Information Center

Buchanan, Patricia A.; Ulrich, Beverly D.

2001-01-01

Describes the Feldenkrais Method of somatic education, noting parallels with a dynamic systems theory (DST) approach to motor behavior. Feldenkrais uses movement and perception to foster individualized improvement in function. DST explains that a human-environment system continually adapts to changing conditions and assembles behaviors…

Behavior dynamics: One perspective

PubMed Central

Marr, M. Jackson

1992-01-01

Behavior dynamics is a field devoted to analytic descriptions of behavior change. A principal source of both models and methods for these descriptions is found in physics. This approach is an extension of a long conceptual association between behavior analysis and physics. A theme common to both is the role of molar versus molecular events in description and prediction. Similarities and differences in how these events are treated are discussed. Two examples are presented that illustrate possible correspondence between mechanical and behavioral systems. The first demonstrates the use of a mechanical model to describe the molar properties of behavior under changing reinforcement conditions. The second, dealing with some features of concurrent schedules, focuses on the possible utility of nonlinear dynamical systems to the description of both molar and molecular behavioral events as the outcome of a deterministic, but chaotic, process. PMID:16812655

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.

PubMed

McDowell, J J

2010-05-01

An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail. Copyright (c) 2009 Elsevier B.V. All rights reserved.

A Dynamical Systems Model for Understanding Behavioral Interventions for Weight Loss

NASA Astrophysics Data System (ADS)

Navarro-Barrientos, J.-Emeterio; Rivera, Daniel E.; Collins, Linda M.

We propose a dynamical systems model that captures the daily fluctuations of human weight change, incorporating both physiological and psychological factors. The model consists of an energy balance integrated with a mechanistic behavioral model inspired by the Theory of Planned Behavior (TPB); the latter describes how important variables in a behavioral intervention can influence healthy eating habits and increased physical activity over time. The model can be used to inform behavioral scientists in the design of optimized interventions for weight loss and body composition change.

Dynamics and Collapse in a Power System Model with Voltage Variation: The Damping Effect.

PubMed

Ma, Jinpeng; Sun, Yong; Yuan, Xiaoming; Kurths, Jürgen; Zhan, Meng

2016-01-01

Complex nonlinear phenomena are investigated in a basic power system model of the single-machine-infinite-bus (SMIB) with a synchronous generator modeled by a classical third-order differential equation including both angle dynamics and voltage dynamics, the so-called flux decay equation. In contrast, for the second-order differential equation considering the angle dynamics only, it is the classical swing equation. Similarities and differences of the dynamics generated between the third-order model and the second-order one are studied. We mainly find that, for positive damping, these two models show quite similar behavior, namely, stable fixed point, stable limit cycle, and their coexistence for different parameters. However, for negative damping, the second-order system can only collapse, whereas for the third-order model, more complicated behavior may happen, such as stable fixed point, limit cycle, quasi-periodicity, and chaos. Interesting partial collapse phenomena for angle instability only and not for voltage instability are also found here, including collapse from quasi-periodicity and from chaos etc. These findings not only provide a basic physical picture for power system dynamics in the third-order model incorporating voltage dynamics, but also enable us a deeper understanding of the complex dynamical behavior and even leading to a design of oscillation damping in electric power systems.

Information driven self-organization of complex robotic behaviors.

PubMed

Martius, Georg; Der, Ralf; Ay, Nihat

2013-01-01

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.

A numerical evaluation of the dynamical systems approach to wall layer turbulence

NASA Technical Reports Server (NTRS)

Berkooz, Gal

1990-01-01

This work attempts to test predictions based on the Dynamical Systems approach to Wall Layer Turbulence. We analyze the Dynamical Systems model for the nonlinear interaction mechanisms between the coherent structures and deduce qualitative behavior as expected. We then test for this behavior in data sets from D.N.S. The agreement is good, given the suboptimal conditions for the test. We discuss implications of this test and work to be done to deepen the understanding of control of turbulent boundary layers.

Coupled replicator equations for the dynamics of learning in multiagent systems

NASA Astrophysics Data System (ADS)

Sato, Yuzuru; Crutchfield, James P.

2003-01-01

Starting with a group of reinforcement-learning agents we derive coupled replicator equations that describe the dynamics of collective learning in multiagent systems. We show that, although agents model their environment in a self-interested way without sharing knowledge, a game dynamics emerges naturally through environment-mediated interactions. An application to rock-scissors-paper game interactions shows that the collective learning dynamics exhibits a diversity of competitive and cooperative behaviors. These include quasiperiodicity, stable limit cycles, intermittency, and deterministic chaos—behaviors that should be expected in heterogeneous multiagent systems described by the general replicator equations we derive.

Steady-State Dynamic Behavior of a Flexible Rotor With Auxiliary Support From a Clearance Bearing

NASA Technical Reports Server (NTRS)

Xie, Huajun; Flowers, George T.; Feng, Li; Lawrence, Charles T.

1996-01-01

This paper investigates the steady-state responses of a rotor system supported by auxiliary bearings in which there is a clearance between the rotor and the inner race of the bearing. A simulation model based upon the rotor of a production jet engine is developed and its steady-state behavior is explored over a wide range of operating conditions for various parametric configurations. Specifically, the influence of rotor imbalance, clearance, support stiffness and damping is studied. Bifurcation diagrams are used as a tool to examine the dynamic behavior of this system as a function of the afore mentioned parameters. The harmonic balance method is also employed for synchronous response cases. The observed dynamical responses is discussed and some insights into the behavior of such systems are presented.

Interaction Dynamics Between a Flexible Rotor and an Auxiliary Clearance Bearing

NASA Technical Reports Server (NTRS)

Lawen, James L., Jr.; Flowers, George T.

1996-01-01

This study investigates the application of synchronous interaction dynamics methodology to the design of auxiliary bearing systems. The technique is applied to a flexible rotor system and comparisons are made between the behavior predicted by this analysis method and the observed simulation response characteristics. Of particular interest is the influence of coupled shaft/bearing vibration modes on rotordynamical behavior. Experimental studies are also perFormed to validate the simulation results and provide insight into the expected behavior of such a system.

Archetypes for Organisational Safety

NASA Technical Reports Server (NTRS)

Marais, Karen; Leveson, Nancy G.

2003-01-01

We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.

Alternation of regular and chaotic dynamics in a simple two-degree-of-freedom system with nonlinear inertial coupling.

PubMed

Sigalov, G; Gendelman, O V; AL-Shudeifat, M A; Manevitch, L I; Vakakis, A F; Bergman, L A

2012-03-01

We show that nonlinear inertial coupling between a linear oscillator and an eccentric rotator can lead to very interesting interchanges between regular and chaotic dynamical behavior. Indeed, we show that this model demonstrates rather unusual behavior from the viewpoint of nonlinear dynamics. Specifically, at a discrete set of values of the total energy, the Hamiltonian system exhibits non-conventional nonlinear normal modes, whose shape is determined by phase locking of rotatory and oscillatory motions of the rotator at integer ratios of characteristic frequencies. Considering the weakly damped system, resonance capture of the dynamics into the vicinity of these modes brings about regular motion of the system. For energy levels far from these discrete values, the motion of the system is chaotic. Thus, the succession of resonance captures and escapes by a discrete set of the normal modes causes a sequence of transitions between regular and chaotic behavior, provided that the damping is sufficiently small. We begin from the Hamiltonian system and present a series of Poincaré sections manifesting the complex structure of the phase space of the considered system with inertial nonlinear coupling. Then an approximate analytical description is presented for the non-conventional nonlinear normal modes. We confirm the analytical results by numerical simulation and demonstrate the alternate transitions between regular and chaotic dynamics mentioned above. The origin of the chaotic behavior is also discussed.

Bifurcation and Stability Analysis of the Equilibrium States in Thermodynamic Systems in a Small Vicinity of the Equilibrium Values of Parameters

NASA Astrophysics Data System (ADS)

Barsuk, Alexandr A.; Paladi, Florentin

2018-04-01

The dynamic behavior of thermodynamic system, described by one order parameter and one control parameter, in a small neighborhood of ordinary and bifurcation equilibrium values of the system parameters is studied. Using the general methods of investigating the branching (bifurcations) of solutions for nonlinear equations, we performed an exhaustive analysis of the order parameter dependences on the control parameter in a small vicinity of the equilibrium values of parameters, including the stability analysis of the equilibrium states, and the asymptotic behavior of the order parameter dependences on the control parameter (bifurcation diagrams). The peculiarities of the transition to an unstable state of the system are discussed, and the estimates of the transition time to the unstable state in the neighborhood of ordinary and bifurcation equilibrium values of parameters are given. The influence of an external field on the dynamic behavior of thermodynamic system is analyzed, and the peculiarities of the system dynamic behavior are discussed near the ordinary and bifurcation equilibrium values of parameters in the presence of external field. The dynamic process of magnetization of a ferromagnet is discussed by using the general methods of bifurcation and stability analysis presented in the paper.

Nonlinear electromechanical modelling and dynamical behavior analysis of a satellite reaction wheel

NASA Astrophysics Data System (ADS)

Aghalari, Alireza; Shahravi, Morteza

2017-12-01

The present research addresses the satellite reaction wheel (RW) nonlinear electromechanical coupling dynamics including dynamic eccentricity of brushless dc (BLDC) motor and gyroscopic effects, as well as dry friction of shaft-bearing joints (relative small slip) and bearing friction. In contrast to other studies, the rotational velocity of the flywheel is considered to be controllable, so it is possible to study the reaction wheel dynamical behavior in acceleration stages. The RW is modeled as a three-phases BLDC motor as well as flywheel with unbalances on a rigid shaft and flexible bearings. Improved Lagrangian dynamics for electromechanical systems is used to obtain the mathematical model of the system. The developed model can properly describe electromechanical nonlinear coupled dynamical behavior of the satellite RW. Numerical simulations show the effectiveness of the presented approach.

Nonlinear problems in flight dynamics

NASA Technical Reports Server (NTRS)

Chapman, G. T.; Tobak, M.

1984-01-01

A comprehensive framework is proposed for the description and analysis of nonlinear problems in flight dynamics. Emphasis is placed on the aerodynamic component as the major source of nonlinearities in the flight dynamic system. Four aerodynamic flows are examined to illustrate the richness and regularity of the flow structures and the nature of the flow structures and the nature of the resulting nonlinear aerodynamic forces and moments. A framework to facilitate the study of the aerodynamic system is proposed having parallel observational and mathematical components. The observational component, structure is described in the language of topology. Changes in flow structure are described via bifurcation theory. Chaos or turbulence is related to the analogous chaotic behavior of nonlinear dynamical systems characterized by the existence of strange attractors having fractal dimensionality. Scales of the flow are considered in the light of ideas from group theory. Several one and two degree of freedom dynamical systems with various mathematical models of the nonlinear aerodynamic forces and moments are examined to illustrate the resulting types of dynamical behavior. The mathematical ideas that proved useful in the description of fluid flows are shown to be similarly useful in the description of flight dynamic behavior.

Analytical and experimental study of vibrations in a gear transmission

NASA Technical Reports Server (NTRS)

Choy, F. K.; Ruan, Y. F.; Zakrajsek, J. J.; Oswald, Fred B.; Coy, J. J.

1991-01-01

An analytical simulation of the dynamics of a gear transmission system is presented and compared to experimental results from a gear noise test rig at the NASA Lewis Research Center. The analytical procedure developed couples the dynamic behaviors of the rotor-bearing-gear system with the response of the gearbox structure. The modal synthesis method is used in solving the overall dynamics of the system. Locally each rotor-gear stage is modeled as an individual rotor-bearing system using the matrix transfer technique. The dynamics of each individual rotor are coupled with other rotor stages through the nonlinear gear mesh forces and with the gearbox structure through bearing support systems. The modal characteristics of the gearbox structure are evaluated using the finite element procedure. A variable time steping integration routine is used to calculate the overall time transient behavior of the system in modal coordinates. The global dynamic behavior of the system is expressed in a generalized coordinate system. Transient and steady state vibrations of the gearbox system are presented in the time and frequency domains. The vibration characteristics of a simple single mesh gear noise test rig is modeled. The numerical simulations are compared to experimental data measured under typical operating conditions. The comparison of system natural frequencies, peak vibration amplitudes, and gear mesh frequencies are generally in good agreement.

Characterization of Dynamical Phase Transitions in Quantum Jump Trajectories Beyond the Properties of the Stationary State

NASA Astrophysics Data System (ADS)

Lesanovsky, Igor; van Horssen, Merlijn; Guţă, Mădălin; Garrahan, Juan P.

2013-04-01

We describe how to characterize dynamical phase transitions in open quantum systems from a purely dynamical perspective, namely, through the statistical behavior of quantum jump trajectories. This approach goes beyond considering only properties of the steady state. While in small quantum systems dynamical transitions can only occur trivially at limiting values of the controlling parameters, in many-body systems they arise as collective phenomena and within this perspective they are reminiscent of thermodynamic phase transitions. We illustrate this in open models of increasing complexity: a three-level system, the micromaser, and a dissipative version of the quantum Ising model. In these examples dynamical transitions are accompanied by clear changes in static behavior. This is however not always the case, and, in general, dynamical phases need to be uncovered by observables which are strictly dynamical, e.g., dynamical counting fields. We demonstrate this via the example of a class of models of dissipative quantum glasses, whose dynamics can vary widely despite having identical (and trivial) stationary states.

Characterization of dynamical phase transitions in quantum jump trajectories beyond the properties of the stationary state.

PubMed

Lesanovsky, Igor; van Horssen, Merlijn; Guţă, Mădălin; Garrahan, Juan P

2013-04-12

We describe how to characterize dynamical phase transitions in open quantum systems from a purely dynamical perspective, namely, through the statistical behavior of quantum jump trajectories. This approach goes beyond considering only properties of the steady state. While in small quantum systems dynamical transitions can only occur trivially at limiting values of the controlling parameters, in many-body systems they arise as collective phenomena and within this perspective they are reminiscent of thermodynamic phase transitions. We illustrate this in open models of increasing complexity: a three-level system, the micromaser, and a dissipative version of the quantum Ising model. In these examples dynamical transitions are accompanied by clear changes in static behavior. This is however not always the case, and, in general, dynamical phases need to be uncovered by observables which are strictly dynamical, e.g., dynamical counting fields. We demonstrate this via the example of a class of models of dissipative quantum glasses, whose dynamics can vary widely despite having identical (and trivial) stationary states.

Enhancements for a Dynamic Data Warehousing and Mining System for Large-Scale Human Social Cultural Behavioral (HSBC) Data

DTIC Science & Technology

2016-09-26

Intelligent Automation Incorporated Enhancements for a Dynamic Data Warehousing and Mining ...Enhancements for a Dynamic Data Warehousing and Mining System for N00014-16-P-3014 Large-Scale Human Social Cultural Behavioral (HSBC) Data 5b. GRANT NUMBER...Representative Media Gallery View. We perform Scraawl’s NER algorithm to the text associated with YouTube post, which classifies the named entities into

Dynamic Response of Reinforced Soil Systems. Volume 2. Appendices

DTIC Science & Technology

1993-03-01

by a burster slab. These protection measures are costly, time consuming to construct, and sensitive to multiple strikes. Soil has been used to...load--deflection behavior of the reinforced soi I Dynamic puilout tests were then performed using the same parameters as the static tests. A standard...system was capable cf loading the sample in just a few micro-seconds to simulate a blast load. Dynamic load-deflection behavior was characterized and

Dynamic hysteresis behaviors in the kinetic Ising system on triangular lattice

NASA Astrophysics Data System (ADS)

Kantar, Ersin; Ertaş, Mehmet

2018-04-01

We studied dynamic hysteresis behaviors of the spin-1 Blume-Capel (BC) model in a triangular lattice by means of the effective-field theory (EFT) with correlations and using Glauber-type stochastic dynamics. The effects of the exchange interaction (J), crystal field (D), temperature (T) and oscillating frequency (w) on the hysteresis behaviors of the BC model in a triangular lattice are investigated in detail. Results are compared with some other dynamic studies and quantitatively good agreement is found.

The Dynamics of Perception and Action

ERIC Educational Resources Information Center

Warren, William H.

2006-01-01

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are…

Universality and critical behavior of the dynamical Mott transition in a system with long-range interactions

DOE PAGES

Rademaker, Louk; Vinokur, Valerii M.; Galda, Alexey

2017-03-16

Here, we study numerically the voltage-induced breakdown of a Mott insulating phase in a system of charged classical particles with long-range interactions. At half-filling on a square lattice this system exhibits Mott localization in the form of a checkerboard pattern. We find universal scaling behavior of the current at the dynamic Mott insulator-metal transition and calculate scaling exponents corresponding to the transition. Our results are in agreement, up to a difference in universality class, with recent experimental evidence of a dynamic Mott transition in a system of interacting superconducting vortices.

Universality and critical behavior of the dynamical Mott transition in a system with long-range interactions.

PubMed

Rademaker, Louk; Vinokur, Valerii M; Galda, Alexey

2017-03-16

We study numerically the voltage-induced breakdown of a Mott insulating phase in a system of charged classical particles with long-range interactions. At half-filling on a square lattice this system exhibits Mott localization in the form of a checkerboard pattern. We find universal scaling behavior of the current at the dynamic Mott insulator-metal transition and calculate scaling exponents corresponding to the transition. Our results are in agreement, up to a difference in universality class, with recent experimental evidence of a dynamic Mott transition in a system of interacting superconducting vortices.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Dynamic behavior of a magnetic bearing supported jet engine rotor with auxiliary bearings

NASA Technical Reports Server (NTRS)

Homaifar, Abdollah (Editor); Kelly, John C., Jr. (Editor); Flowers, G. T.; Xie, H.; Sinha, S. C.

1994-01-01

This paper presents a study of the dynamic behavior of a rotor system supported by auxiliary bearings. The steady-state behavior of a simulation model based upon a production jet engine is explored over a wide range of operating conditions for varying rotor imbalance, support stiffness and damping. Interesting dynamical phenomena, such as chaos, subharmonic responses, and double-valued responses, are presented and discussed.

Dynamic behavior of a magnetic bearing supported jet engine rotor with auxiliary bearings

NASA Technical Reports Server (NTRS)

Flowers, George T.; Xie, Huajun; Sinha, S. C.

1995-01-01

This paper presents a study of the dynamic behavior of a rotor system supported by auxiliary bearings. The steady-state behavior of a simulation model based upon a production jet engine is explored over a wide range of operating conditions for varying rotor imbalance, support stiffness, and damping. Interesting dynamical phenomena, such as chaos, subharmonic responses, and double-valued responses, are presented and discussed.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states.

PubMed

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

NASA Astrophysics Data System (ADS)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

2015-12-01

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field is chaotic. We argue that this second type of behavior is "extensive" in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.

Evolutionary game based control for biological systems with applications in drug delivery.

PubMed

Li, Xiaobo; Lenaghan, Scott C; Zhang, Mingjun

2013-06-07

Control engineering and analysis of biological systems have become increasingly important for systems and synthetic biology. Unfortunately, no widely accepted control framework is currently available for these systems, especially at the cell and molecular levels. This is partially due to the lack of appropriate mathematical models to describe the unique dynamics of biological systems, and the lack of implementation techniques, such as ultra-fast and ultra-small devices and corresponding control algorithms. This paper proposes a control framework for biological systems subject to dynamics that exhibit adaptive behavior under evolutionary pressures. The control framework was formulated based on evolutionary game based modeling, which integrates both the internal dynamics and the population dynamics. In the proposed control framework, the adaptive behavior was characterized as an internal dynamic, and the external environment was regarded as an external control input. The proposed open-interface control framework can be integrated with additional control algorithms for control of biological systems. To demonstrate the effectiveness of the proposed framework, an optimal control strategy was developed and validated for drug delivery using the pathogen Giardia lamblia as a test case. In principle, the proposed control framework can be applied to any biological system exhibiting adaptive behavior under evolutionary pressures. Copyright © 2013 Elsevier Ltd. All rights reserved.

Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research.

PubMed

Spruijt-Metz, Donna; Hekler, Eric; Saranummi, Niilo; Intille, Stephen; Korhonen, Ilkka; Nilsen, Wendy; Rivera, Daniel E; Spring, Bonnie; Michie, Susan; Asch, David A; Sanna, Alberto; Salcedo, Vicente Traver; Kukakfa, Rita; Pavel, Misha

2015-09-01

Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.

Physical Invariants of Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A program of research is dedicated to development of a mathematical formalism that could provide, among other things, means by which living systems could be distinguished from non-living ones. A major issue that arises in this research is the following question: What invariants of mathematical models of the physics of systems are (1) characteristic of the behaviors of intelligent living systems and (2) do not depend on specific features of material compositions heretofore considered to be characteristic of life? This research at earlier stages has been reported, albeit from different perspectives, in numerous previous NASA Tech Briefs articles. To recapitulate: One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Mathematical models of motor dynamics are used to simulate the observable physical behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. At the time of reporting the information for this article, the focus of this research was upon the following aspects of the formalism: Intelligence is considered to be a means by which a living system preserves itself and improves its ability to survive and is further considered to manifest itself in feedback from the mental dynamics to the motor dynamics. Because of the feedback from the mental dynamics, the motor dynamics attains quantum-like properties: The trajectory of the physical aspect of the system in the space of dynamical variables splits into a family of different trajectories, and each of those trajectories can be chosen with a probability prescribed by the mental dynamics. From a slightly different perspective, the mechanism of decision-making is feedback from the mental dynamics to the motor dynamics, and this mechanism provides a quantum-like collapse of a random motion into an appropriate deterministic state, such that entropy undergoes a pronounced decrease. The existence of this mechanism is considered to be an invariant of intelligent behavior of living systems, regardless of the origins and material compositions of the systems.

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

From Occasional Choices to Inevitable Musts: A Computational Model of Nicotine Addiction

PubMed Central

Metin, Selin; Sengor, N. Serap

2012-01-01

Although, there are considerable works on the neural mechanisms of reward-based learning and decision making, and most of them mention that addiction can be explained by malfunctioning in these cognitive processes, there are very few computational models. This paper focuses on nicotine addiction, and a computational model for nicotine addiction is proposed based on the neurophysiological basis of addiction. The model compromises different levels ranging from molecular basis to systems level, and it demonstrates three different possible behavioral patterns which are addict, nonaddict, and indecisive. The dynamical behavior of the proposed model is investigated with tools used in analyzing nonlinear dynamical systems, and the relation between the behavioral patterns and the dynamics of the system is discussed. PMID:23251144

A coupled human-water system from a systems dynamics perspective

NASA Astrophysics Data System (ADS)

Kuil, Linda; Blöschl, Günter; Carr, Gemma

2013-04-01

Traditionally, models used in hydrological studies have frequently assumed stationarity. Moreover, human-induced water resources management activities are often included as external forcings in water cycle dynamics. However, considering humans' current impact on the water cycle in terms of a growing population, river basins increasingly being managed and a climate considerably changing, it has recently been questioned whether this is still correct. Furthermore, research directed at the evolution of water resources and society has shown that the components constituting the human-water system are changing interdependently. Goal of this study is therefore to approach water cycle dynamics from an integrated perspective in which humans are considered as endogenous forces to the system. The method used to model a coupled, urban human-water system is system dynamics. In system dynamics, particular emphasis is placed on feedback loops resulting in dynamic behavior. Time delays and non-linearity can relatively easily be included, making the method appropriate for studying complex systems that change over time. The approach of this study is as follows. First, a conceptual model is created incorporating the key components of the urban human-water system. Subsequently, only those components are selected that are both relevant and show causal loop behavior. Lastly, the causal narratives are translated into mathematical relationships. The outcome will be a simple model that shows only those characteristics with which we are able to explore the two-way coupling between the societal behavior and the water system we depend on.

Phase transitions in the first-passage time of scale-invariant correlated processes

PubMed Central

Carretero-Campos, Concepción; Bernaola-Galván, Pedro; Ch. Ivanov, Plamen

2012-01-01

A key quantity describing the dynamics of complex systems is the first-passage time (FPT). The statistical properties of FPT depend on the specifics of the underlying system dynamics. We present a unified approach to account for the diversity of statistical behaviors of FPT observed in real-world systems. We find three distinct regimes, separated by two transition points, with fundamentally different behavior for FPT as a function of increasing strength of the correlations in the system dynamics: stretched exponential, power-law, and saturation regimes. In the saturation regime, the average length of FPT diverges proportionally to the system size, with important implications for understanding electronic delocalization in one-dimensional correlated-disordered systems. PMID:22400544

Dynamical gauge effects in an open quantum network

NASA Astrophysics Data System (ADS)

Zhao, Jianshi; Price, Craig; Liu, Qi; Gemelke, Nathan

2016-05-01

We describe new experimental techniques for simulation of high-energy field theories based on an analogy between open thermodynamic systems and effective dynamical gauge-fields following SU(2) × U(1) Yang-Mills models. By coupling near-resonant laser-modes to atoms moving in a disordered optical environment, we create an open system which exhibits a non-equilibrium phase transition between two steady-state behaviors, exhibiting scale-invariant behavior near the transition. By measuring transport of atoms through the disordered network, we observe two distinct scaling behaviors, corresponding to the classical and quantum limits for the dynamical gauge field. This behavior is loosely analogous to dynamical gauge effects in quantum chromodynamics, and can mapped onto generalized open problems in theoretical understanding of quantized non-Abelian gauge theories. Additional, the scaling behavior can be understood from the geometric structure of the gauge potential and linked to the measure of information in the local disordered potential, reflecting an underlying holographic principle. We acknowledge support from NSF Award No.1068570, and the Charles E. Kaufman Foundation.

Nonlinear Socio-Ecological Dynamics and First Principles ofCollective Choice Behavior of ``Homo Socialis"

NASA Astrophysics Data System (ADS)

Sonis, M.

Socio-ecological dynamics emerged from the field of Mathematical SocialSciences and opened up avenues for re-examination of classical problems of collective behavior in Social and Spatial sciences. The ``engine" of this collective behavior is the subjective mental evaluation of level of utilities in the future, presenting sets of composite socio-economic-temporal-locational advantages. These dynamics present new laws of collective multi-population behavior which are the meso-level counterparts of the utility optimization individual behavior. The central core of the socio-ecological choice dynamics includes the following first principle of the collective choice behavior of ``Homo Socialis" based on the existence of ``collective consciousness": the choice behavior of ``Homo Socialis" is a collective meso-level choice behavior such that the relative changes in choice frequencies depend on the distribution of innovation alternatives between adopters of innovations. The mathematical basis of the Socio-Ecological Dynamics includes two complementary analytical approaches both based on the use of computer modeling as a theoretical and simulation tool. First approach is the ``continuous approach" --- the systems of ordinary and partial differential equations reflecting the continuous time Volterra ecological formalism in a form of antagonistic and/or cooperative collective hyper-games between different sub-sets of choice alternatives. Second approach is the ``discrete approach" --- systems of difference equations presenting a new branch of the non-linear discrete dynamics --- the Discrete Relative m-population/n-innovations Socio-Spatial Dynamics (Dendrinos and Sonis, 1990). The generalization of the Volterra formalism leads further to the meso-level variational principle of collective choice behavior determining the balance between the resulting cumulative social spatio-temporal interactions among the population of adopters susceptible to the choice alternatives and the cumulative equalization of the power of elites supporting different choice alternatives. This balance governs the dynamic innovation choice process and constitutes the dynamic meso-level counterpart of the micro-economic individual utility maximization principle.

New approach to study mobility in the vicinity of dynamical arrest; exact application to a kinetically constrained model

NASA Astrophysics Data System (ADS)

DeGregorio, P.; Lawlor, A.; Dawson, K. A.

2006-04-01

We introduce a new method to describe systems in the vicinity of dynamical arrest. This involves a map that transforms mobile systems at one length scale to mobile systems at a longer length. This map is capable of capturing the singular behavior accrued across very large length scales, and provides a direct route to the dynamical correlation length and other related quantities. The ideas are immediately applicable in two spatial dimensions, and have been applied to a modified Kob-Andersen type model. For such systems the map may be derived in an exact form, and readily solved numerically. We obtain the asymptotic behavior across the whole physical domain of interest in dynamical arrest.

On the adaptive sliding mode controller for a hyperchaotic fractional-order financial system

NASA Astrophysics Data System (ADS)

Hajipour, Ahamad; Hajipour, Mojtaba; Baleanu, Dumitru

2018-05-01

This manuscript mainly focuses on the construction, dynamic analysis and control of a new fractional-order financial system. The basic dynamical behaviors of the proposed system are studied such as the equilibrium points and their stability, Lyapunov exponents, bifurcation diagrams, phase portraits of state variables and the intervals of system parameters. It is shown that the system exhibits hyperchaotic behavior for a number of system parameters and fractional-order values. To stabilize the proposed hyperchaotic fractional system with uncertain dynamics and disturbances, an efficient adaptive sliding mode controller technique is developed. Using the proposed technique, two hyperchaotic fractional-order financial systems are also synchronized. Numerical simulations are presented to verify the successful performance of the designed controllers.

Noise switching at a dynamical critical point in a cavity-conductor hybrid

NASA Astrophysics Data System (ADS)

Armour, Andrew D.; Kubala, Björn; Ankerhold, Joachim

2017-12-01

Coupling a mesoscopic conductor to a microwave cavity can lead to fascinating feedback effects which generate strong correlations between the dynamics of photons and charges. We explore the connection between cavity dynamics and charge transport in a model system consisting of a voltage-biased Josephson junction embedded in a high-Q cavity, focusing on the behavior as the system is tuned through a dynamical critical point. On one side of the critical point the noise is strongly suppressed, signaling the existence of a regime of highly coherent transport, but on the other side it switches abruptly to a much larger value. Using a semiclassical approach we show that this behavior arises because of the strongly nonlinear cavity drive generated by the Cooper pairs. We also uncover an equivalence between charge and photonic current noise in the system which opens up a route to detecting the critical behavior through straightforward microwave measurements.

Effects of gear box vibration and mass imbalance on the dynamics of multi-stage gear transmissions

NASA Technical Reports Server (NTRS)

Choy, Fred K.; Tu, Yu K.; Zakrajsek, James J.; Townsend, Dennis P.

1991-01-01

The dynamic behavior of multistage gear transmission system, with the effects of gear-box-induced vibrations and rotor mass-imbalances is analyzed. The model method, using undamped frequencies and planar mode shapes, is used to reduce the degree-of-freedom of the system. The various rotor-bearing stages as well as lateral and torsional vibrations of each individual stage are coupled through localized gear-mesh-tooth interactions. Gear-box vibrations are coupled to the gear stage dynamics through bearing support forces. Transient and steady state dynamics of lateral and torsional vibrations of the geared system are examined in both time and frequency domain. A typical three-staged geared system is used as an example. Effects of mass-imbalance and gear box vibrations on the system dynamic behavior are presented in terms of modal excitation functions for both lateral and torsional vibrations. Operational characteristics and conclusions are drawn from the results presented.

Effects of gear box vibration and mass imbalance on the dynamics of multistage gear transmission

NASA Technical Reports Server (NTRS)

Choy, F. K.; Tu, Y. K.; Zakrajsek, J. J.; Townsend, D. P.

1991-01-01

The dynamic behavior of multistage gear transmission system, with the effects of gear-box-induced vibrations and rotor mass-imbalances is analyzed. The model method, using undamped frequencies and planar mode shapes, is used to reduce the degree-of-freedom of the system. The various rotor-bearing stages as well as lateral and torsional vibrations of each individual stage are coupled through localized gear-mesh-tooth interactions. Gear-box vibrations are coupled to the gear stage dynamics through bearing support forces. Transient and steady state dynamics of lateral and torsional vibrations of the geared system are examined in both time and frequency domain. A typical three-staged geared system is used as an example. Effects of mass-imbalance and gear box vibrations on the system dynamic behavior are presented in terms of modal excitation functions for both lateral and torsional vibrations. Operational characteristics and conclusions are drawn from the results presented.

Nonlinear modeling and dynamic analysis of a hydro-turbine governing system in the process of sudden load increase transient

NASA Astrophysics Data System (ADS)

Li, Huanhuan; Chen, Diyi; Zhang, Hao; Wang, Feifei; Ba, Duoduo

2016-12-01

In order to study the nonlinear dynamic behaviors of a hydro-turbine governing system in the process of sudden load increase transient, we establish a novel nonlinear dynamic model of the hydro-turbine governing system which considers the elastic water-hammer model of the penstock and the second-order model of the generator. The six nonlinear dynamic transfer coefficients of the hydro-turbine are innovatively proposed by utilizing internal characteristics and analyzing the change laws of the characteristic parameters of the hydro-turbine governing system. Moreover, from the point of view of engineering, the nonlinear dynamic behaviors of the above system are exhaustively investigated based on bifurcation diagrams and time waveforms. More importantly, all of the above analyses supply theoretical basis for allowing a hydropower station to maintain a stable operation in the process of sudden load increase transient.

Overly Regulated Thinking and Autism Revisited.

PubMed

Cashin, Andrew; Yorke, James

2016-08-01

Humans exist within a socially mediated dynamical system. Frequent demands are experienced to respond to change in the environment to adapt and flourish. People with autism have impaired behavioral and thinking flexibility and experience high levels of anxiety, as change and adaptation do not come naturally. The disability inherent in autism is by definition the impaired social and occupational functioning that results from lack of adaptation. The point of the behavioral triad of restricted and repetitive interests, activities, and behaviors has received relatively little attention as compared to the other two points of the triad. A review of the literature related to restricted and repetitive interests and activities and behaviors and autism was conducted to inform this theoretical review. This paper considers the overly regulated thought and behavior inherent in autism spectrum disorders through the lens of dynamical systems, and an explanatory model is generated. The mathematical tools applied to understand dynamical systems may be a fruitful basis of further research to enable the movement from a theoretical concept of overly regulated thinking and behavior in autism to an empirically derived understanding. © 2016 Wiley Periodicals, Inc.

Mapping the functional versatility and fragility of Ras GTPase signaling circuits through in vitro network reconstitution.

PubMed

Coyle, Scott M; Lim, Wendell A

2016-01-14

The Ras-superfamily GTPases are central controllers of cell proliferation and morphology. Ras signaling is mediated by a system of interacting molecules: upstream enzymes (GEF/GAP) regulate Ras's ability to recruit multiple competing downstream effectors. We developed a multiplexed, multi-turnover assay for measuring the dynamic signaling behavior of in vitro reconstituted H-Ras signaling systems. By including both upstream regulators and downstream effectors, we can systematically map how different network configurations shape the dynamic system response. The concentration and identity of both upstream and downstream signaling components strongly impacted the timing, duration, shape, and amplitude of effector outputs. The distorted output of oncogenic alleles of Ras was highly dependent on the balance of positive (GAP) and negative (GEF) regulators in the system. We found that different effectors interpreted the same inputs with distinct output dynamics, enabling a Ras system to encode multiple unique temporal outputs in response to a single input. We also found that different Ras-to-GEF positive feedback mechanisms could reshape output dynamics in distinct ways, such as signal amplification or overshoot minimization. Mapping of the space of output behaviors accessible to Ras provides a design manual for programming Ras circuits, and reveals how these systems are readily adapted to produce an array of dynamic signaling behaviors. Nonetheless, this versatility comes with a trade-off of fragility, as there exist numerous paths to altered signaling behaviors that could cause disease.

Influence of changes in initial conditions for the simulation of dynamic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotyrba, Martin

2015-03-10

Chaos theory is a field of study in mathematics, with applications in several disciplines including meteorology, sociology, physics, engineering, economics, biology, and philosophy. Chaos theory studies the behavior of dynamical systems that are highly sensitive to initial conditions—a paradigm popularly referred to as the butterfly effect. Small differences in initial conditions field widely diverging outcomes for such dynamical systems, rendering long-term prediction impossible in general. This happens even though these systems are deterministic, meaning that their future behavior is fully determined by their initial conditions, with no random elements involved. In this paperinfluence of changes in initial conditions will bemore » presented for the simulation of Lorenz system.« less

A system dynamics approach to analyze laboratory test errors.

PubMed

Guo, Shijing; Roudsari, Abdul; Garcez, Artur d'Avila

2015-01-01

Although many researches have been carried out to analyze laboratory test errors during the last decade, it still lacks a systemic view of study, especially to trace errors during test process and evaluate potential interventions. This study implements system dynamics modeling into laboratory errors to trace the laboratory error flows and to simulate the system behaviors while changing internal variable values. The change of the variables may reflect a change in demand or a proposed intervention. A review of literature on laboratory test errors was given and provided as the main data source for the system dynamics model. Three "what if" scenarios were selected for testing the model. System behaviors were observed and compared under different scenarios over a period of time. The results suggest system dynamics modeling has potential effectiveness of helping to understand laboratory errors, observe model behaviours, and provide a risk-free simulation experiments for possible strategies.

Dynamical transitions in large systems of mean field-coupled Landau-Stuart oscillators: Extensive chaos and cluster states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ku, Wai Lim; Girvan, Michelle; Ott, Edward

In this paper, we study dynamical systems in which a large number N of identical Landau-Stuart oscillators are globally coupled via a mean-field. Previously, it has been observed that this type of system can exhibit a variety of different dynamical behaviors. These behaviors include time periodic cluster states in which each oscillator is in one of a small number of groups for which all oscillators in each group have the same state which is different from group to group, as well as a behavior in which all oscillators have different states and the macroscopic dynamics of the mean field ismore » chaotic. We argue that this second type of behavior is “extensive” in the sense that the chaotic attractor in the full phase space of the system has a fractal dimension that scales linearly with N and that the number of positive Lyapunov exponents of the attractor also scales linearly with N. An important focus of this paper is the transition between cluster states and extensive chaos as the system is subjected to slow adiabatic parameter change. We observe discontinuous transitions between the cluster states (which correspond to low dimensional dynamics) and the extensively chaotic states. Furthermore, examining the cluster state, as the system approaches the discontinuous transition to extensive chaos, we find that the oscillator population distribution between the clusters continually evolves so that the cluster state is always marginally stable. This behavior is used to reveal the mechanism of the discontinuous transition. We also apply the Kaplan-Yorke formula to study the fractal structure of the extensively chaotic attractors.« less

Effect of particle-size dynamics on properties of dense spongy-particle systems: Approach towards equilibrium.

PubMed

Zakhari, Monica E A; Anderson, Patrick D; Hütter, Markus

2017-07-01

Open-porous deformable particles, often envisaged as sponges, are ubiquitous in biological and industrial systems (e.g., casein micelles in dairy products and microgels in cosmetics). The rich behavior of these suspensions is owing to the elasticity of the supporting network of the particle, and the viscosity of permeating solvent. Therefore, the rate-dependent size change of these particles depends on their structure, i.e., the permeability. This work aims at investigating the effect of the particle-size dynamics and the underlying particle structure, i.e., the particle permeability, on the transient and long-time behavior of suspensions of spongy particles in the absence of applied deformation, using the dynamic two-scale model developed by Hütter et al. [Farad. Discuss. 158, 407 (2012)1359-664010.1039/c2fd20025b]. In the high-density limit, the transient behavior is found to be accelerated by the particle-size dynamics, even at average size changes as small as 1%. The accelerated dynamics is evidenced by (i) the higher short-time diffusion coefficient as compared to elastic-particle systems and (ii) the accelerated formation of the stable fcc crystal structure. Furthermore, after long times, the particle-size dynamics of spongy particles is shown to result in lower stationary values of the energy and normal stresses as compared to elastic-particle systems. This dependence of the long-time behavior of these systems on the permeability, that essentially is a transport coefficient and hence must not affect the equilibrium properties, confirms that full equilibration has not been reached.

Effect of particle-size dynamics on properties of dense spongy-particle systems: Approach towards equilibrium

NASA Astrophysics Data System (ADS)

Zakhari, Monica E. A.; Anderson, Patrick D.; Hütter, Markus

2017-07-01

Open-porous deformable particles, often envisaged as sponges, are ubiquitous in biological and industrial systems (e.g., casein micelles in dairy products and microgels in cosmetics). The rich behavior of these suspensions is owing to the elasticity of the supporting network of the particle, and the viscosity of permeating solvent. Therefore, the rate-dependent size change of these particles depends on their structure, i.e., the permeability. This work aims at investigating the effect of the particle-size dynamics and the underlying particle structure, i.e., the particle permeability, on the transient and long-time behavior of suspensions of spongy particles in the absence of applied deformation, using the dynamic two-scale model developed by Hütter et al. [Farad. Discuss. 158, 407 (2012), 10.1039/c2fd20025b]. In the high-density limit, the transient behavior is found to be accelerated by the particle-size dynamics, even at average size changes as small as 1 % . The accelerated dynamics is evidenced by (i) the higher short-time diffusion coefficient as compared to elastic-particle systems and (ii) the accelerated formation of the stable fcc crystal structure. Furthermore, after long times, the particle-size dynamics of spongy particles is shown to result in lower stationary values of the energy and normal stresses as compared to elastic-particle systems. This dependence of the long-time behavior of these systems on the permeability, that essentially is a transport coefficient and hence must not affect the equilibrium properties, confirms that full equilibration has not been reached.

Time Series Analysis of the Bacillus subtilis Sporulation Network Reveals Low Dimensional Chaotic Dynamics.

PubMed

Lecca, Paola; Mura, Ivan; Re, Angela; Barker, Gary C; Ihekwaba, Adaoha E C

2016-01-01

Chaotic behavior refers to a behavior which, albeit irregular, is generated by an underlying deterministic process. Therefore, a chaotic behavior is potentially controllable. This possibility becomes practically amenable especially when chaos is shown to be low-dimensional, i.e., to be attributable to a small fraction of the total systems components. In this case, indeed, including the major drivers of chaos in a system into the modeling approach allows us to improve predictability of the systems dynamics. Here, we analyzed the numerical simulations of an accurate ordinary differential equation model of the gene network regulating sporulation initiation in Bacillus subtilis to explore whether the non-linearity underlying time series data is due to low-dimensional chaos. Low-dimensional chaos is expectedly common in systems with few degrees of freedom, but rare in systems with many degrees of freedom such as the B. subtilis sporulation network. The estimation of a number of indices, which reflect the chaotic nature of a system, indicates that the dynamics of this network is affected by deterministic chaos. The neat separation between the indices obtained from the time series simulated from the model and those obtained from time series generated by Gaussian white and colored noise confirmed that the B. subtilis sporulation network dynamics is affected by low dimensional chaos rather than by noise. Furthermore, our analysis identifies the principal driver of the networks chaotic dynamics to be sporulation initiation phosphotransferase B (Spo0B). We then analyzed the parameters and the phase space of the system to characterize the instability points of the network dynamics, and, in turn, to identify the ranges of values of Spo0B and of the other drivers of the chaotic dynamics, for which the whole system is highly sensitive to minimal perturbation. In summary, we described an unappreciated source of complexity in the B. subtilis sporulation network by gathering evidence for the chaotic behavior of the system, and by suggesting candidate molecules driving chaos in the system. The results of our chaos analysis can increase our understanding of the intricacies of the regulatory network under analysis, and suggest experimental work to refine our behavior of the mechanisms underlying B. subtilis sporulation initiation control.

Terminal Model Of Newtonian Dynamics

NASA Technical Reports Server (NTRS)

Zak, Michail

1994-01-01

Paper presents study of theory of Newtonian dynamics of terminal attractors and repellers, focusing on issues of reversibility vs. irreversibility and deterministic evolution vs. probabilistic or chaotic evolution of dynamic systems. Theory developed called "terminal dynamics" emphasizes difference between it and classical Newtonian dynamics. Also holds promise for explaining irreversibility, unpredictability, probabilistic behavior, and chaos in turbulent flows, in thermodynamic phenomena, and in other dynamic phenomena and systems.

Observation of dynamic equilibrium cluster phase in nanoparticle-polymer system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Sugam, E-mail: sugam@barc.gov.in; Mehan, S.; Aswal, V. K.

2016-05-23

Small-angle neutron scattering (SANS) and dynamic light scattering (DLS) have been used to investigate the existence of a cluster phase in a nanoparticle-polymer system. The nanoparticle-polymer system shows an interesting reentrant phase behavior where the charge stabilized silica nanoparticles undergo particle clustering and back to individual nanoparticles as a function of polymer concentration. This kind of phase behavior is believed to be directed by opposing attractive and repulsive interactions present in the system. The phase behavior shows two narrow regions of polymer concentration immediately before and after the two-phase formation indicating the possibility of the existence of some equilibrium clusters.more » DLS results show a much higher size of particles than individuals in these two regions which remains unchanged even after dilution. The SANS data show the evolution of attraction with increased volume fraction of the particles supporting the dynamic nature of these clusters.« less

Crossover from antipersistent to persistent behavior in time series possessing the generalyzed dynamic scaling law

NASA Astrophysics Data System (ADS)

Balankin, Alexander S.; Morales Matamoros, Oswaldo; Gálvez M., Ernesto; Pérez A., Alfonso

2004-03-01

The behavior of crude oil price volatility is analyzed within a conceptual framework of kinetic roughening of growing interfaces. We find that the persistent long-horizon volatilities satisfy the Family-Viscek dynamic scaling ansatz, whereas the mean-reverting in time short horizon volatilities obey the generalized scaling law with continuously varying scaling exponents. Furthermore we find that the crossover from antipersistent to persistent behavior is accompanied by a change in the type of volatility distribution. These phenomena are attributed to the complex avalanche dynamics of crude oil markets and so a similar behavior may be observed in a wide variety of physical systems governed by avalanche dynamics.

Sleeping of a Complex Brain Networks with Hierarchical Organization

NASA Astrophysics Data System (ADS)

Zhang, Ying-Yue; Yang, Qiu-Ying; Chen, Tian-Lun

2009-01-01

The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

The Nonlinear Magnetosphere: Expressions in MHD and in Kinetic Models

NASA Technical Reports Server (NTRS)

Hesse, Michael; Birn, Joachim

2011-01-01

Like most plasma systems, the magnetosphere of the Earth is governed by nonlinear dynamic evolution equations. The impact of nonlinearities ranges from large scales, where overall dynamics features are exhibiting nonlinear behavior, to small scale, kinetic, processes, where nonlinear behavior governs, among others, energy conversion and dissipation. In this talk we present a select set of examples of such behavior, with a specific emphasis on how nonlinear effects manifest themselves in MHD and in kinetic models of magnetospheric plasma dynamics.

Some aspects of control of a large-scale dynamic system

NASA Technical Reports Server (NTRS)

Aoki, M.

1975-01-01

Techniques of predicting and/or controlling the dynamic behavior of large scale systems are discussed in terms of decentralized decision making. Topics discussed include: (1) control of large scale systems by dynamic team with delayed information sharing; (2) dynamic resource allocation problems by a team (hierarchical structure with a coordinator); and (3) some problems related to the construction of a model of reduced dimension.

Predicting chaos for infinite dimensional dynamical systems: The Kuramoto-Sivashinsky equation, a case study

NASA Technical Reports Server (NTRS)

Smyrlis, Yiorgos S.; Papageorgiou, Demetrios T.

1991-01-01

The results of extensive computations are presented in order to accurately characterize transitions to chaos for the Kuramoto-Sivashinsky equation. In particular, the oscillatory dynamics in a window that supports a complete sequence of period doubling bifurcations preceding chaos is followed. As many as thirteen period doublings are followed and used to compute the Feigenbaum number for the cascade and so enable, for the first time, an accurate numerical evaluation of the theory of universal behavior of nonlinear systems, for an infinite dimensional dynamical system. Furthermore, the dynamics at the threshold of chaos exhibit a fractal behavior which is demonstrated and used to compute a universal scaling factor that enables the self-similar continuation of the solution into a chaotic regime.

Chaos and multi-scroll attractors in RCL-shunted junction coupled Jerk circuit connected by memristor

PubMed Central

Zhou, Ping; Ahmad, Bashir; Ren, Guodong; Wang, Chunni

2018-01-01

In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities. PMID:29342178

Chaos and multi-scroll attractors in RCL-shunted junction coupled Jerk circuit connected by memristor.

PubMed

Ma, Jun; Zhou, Ping; Ahmad, Bashir; Ren, Guodong; Wang, Chunni

2018-01-01

In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities.

Model systems for single molecule polymer dynamics

PubMed Central

Latinwo, Folarin

2012-01-01

Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980

Dynamics of Multistage Gear Transmission with Effects of Gearbox Vibrations

NASA Technical Reports Server (NTRS)

Choy, F. K.; Tu, Y. K.; Zakrajsek, J. J.; Townsend, Dennis P.

1990-01-01

A comprehensive approach is presented in analyzing the dynamic behavior of multistage gear transmission systems with the effects of gearbox induced vibrations and mass imbalances of the rotor. The modal method, with undamped frequencies and planar mode shapes, is used to reduce the degrees of freedom of the gear system for time-transient dynamic analysis. Both the lateral and torsional vibration modes of each rotor-bearing-gear stage as well as the interstage vibrational characteristics are coupled together through localized gear mesh tooth interactions. In addition, gearbox vibrations are also coupled to the rotor-bearing-gear system dynamics through bearing support forces between the rotor and the gearbox. Transient and steady state dynamics of lateral and torsional vibrations of the geared system are examined in both time and frequency domains to develop interpretations of the overall modal dynamic characteristics under various operating conditions. A typical three-stage geared system is used as an example. Effects of mass imbalance and gearbox vibrations on the system dynamic behavior are presented in terms of modal excitation functions for both lateral and torsional vibrations. Operational characteristics and conclusions are drawn from the results presented.

A Formal Investigation of the Organization of Guidance Behavior: Implications for Humans and Autonomous Guidance

NASA Astrophysics Data System (ADS)

Kong, Zhaodan

Guidance behavior generated either by artificial agents or humans has been actively studied in the fields of both robotics and cognitive science. The goals of these two fields are different. The former is the automatic generation of appropriate or even optimal behavior, while the latter is the understanding of the underlying mechanism. Their challenges, though, are closely related, the most important one being the lack of a unified, formal and grounded framework where the guidance behavior can be modeled and studied. This dissertation presents such a framework. In this framework, guidance behavior is analyzed as the closed-loop dynamics of the whole agent-environment system. The resulting dynamics give rise to interaction patterns. The central points of this dissertation are that: first of all, these patterns, which can be explained in terms of symmetries that are inherent to the guidance behavior, provide building blocks for the organization of behavior; second, the existence of these patterns and humans' organization of their guidance behavior based on these patterns are the reasons that humans can generate successful behavior in spite of all the complexities involved in the planning and control. This dissertation first gives an overview of the challenges existing in both scientific endeavors, such as human and animal spatial behavior study, and engineering endeavors, such as autonomous guidance system design. It then lays out the foundation for our formal framework, which states that guidance behavior should be interpreted as the collection of the closed-loop dynamics resulting from the agent's interaction with the environment. The following, illustrated by examples of three different UAVs, shows that the study of the closed-loop dynamics should not be done without the consideration of vehicle dynamics, as is the common practice in some of the studies in both autonomous guidance and human behavior analysis. The framework, the core concepts of which are symmetries and interaction patterns, is then elaborated on with the example of Dubins' vehicle's guidance behavior. The dissertation then describes the details of the agile human guidance experiments using miniature helicopters, the technique that is developed for the analysis of the experimental data and the analysis results. The results confirm that human guidance behavior indeed exhibits invariance as defined by interaction patterns. Subsequently, the behavior in each interaction pattern is investigated using piecewise affine model identification. Combined, the results provide a natural and formal decomposition of the behavior that can be unified under a hierarchical hidden Markov model. By employing the languages of dynamical system and control and by adopting algorithms from system identification and machine learning, the framework presented in this dissertation provides a fertile ground where these different disciplines can meet. It also promises multiple potential directions where future research can be headed.

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

Kim, Jason Z; Soffer, Jonathan M; Kahn, Ari E; Vettel, Jean M; Pasqualetti, Fabio; Bassett, Danielle S

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Dynamical principles in neuroscience

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.

2006-10-01

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?

Dynamical principles in neuroscience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.

Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only amore » few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?.« less

Oscillon in Einstein-scalar system with double well potential and its properties.

NASA Astrophysics Data System (ADS)

Ikeda, Taishi; Yoo, Chul-Moon; Cardoso, Vitor

2018-01-01

The dynamical evolution of self-interacting scalar field has many nontrivial behaviors, which tell us many lessons in a nonlinear dynamics. On Minkowski spacetime, the scalar field with double well potential has localized, non-singular, time-dependent, long-lived solutions, which are called oscillons. The lifetime of the oscillon depends on the initial conditions. Furthermore, when the initial parameter is fine-tuned, oscillons can be infinitely, and type I critical behavior is observed. Here, we investigate the Einstein-scalar system with double well potential. We show that oscillons exist in this system, and discuss the behavior when the initial parameter is fine-tuned. Our results suggests that a new type of critical behavior appears in this theory.

Modeling Dynamic Regulatory Processes in Stroke.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

2012-10-11

The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to developmore » dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.« less

Nonlinear analysis of dynamic signature

NASA Astrophysics Data System (ADS)

Rashidi, S.; Fallah, A.; Towhidkhah, F.

2013-12-01

Signature is a long trained motor skill resulting in well combination of segments like strokes and loops. It is a physical manifestation of complex motor processes. The problem, generally stated, is that how relative simplicity in behavior emerges from considerable complexity of perception-action system that produces behavior within an infinitely variable biomechanical and environmental context. To solve this problem, we present evidences which indicate that motor control dynamic in signing process is a chaotic process. This chaotic dynamic may explain a richer array of time series behavior in motor skill of signature. Nonlinear analysis is a powerful approach and suitable tool which seeks for characterizing dynamical systems through concepts such as fractal dimension and Lyapunov exponent. As a result, they can be analyzed in both horizontal and vertical for time series of position and velocity. We observed from the results that noninteger values for the correlation dimension indicates low dimensional deterministic dynamics. This result could be confirmed by using surrogate data tests. We have also used time series to calculate the largest Lyapunov exponent and obtain a positive value. These results constitute significant evidence that signature data are outcome of chaos in a nonlinear dynamical system of motor control.

Mapping the functional versatility and fragility of Ras GTPase signaling circuits through in vitro network reconstitution

PubMed Central

Coyle, Scott M; Lim, Wendell A

2016-01-01

The Ras-superfamily GTPases are central controllers of cell proliferation and morphology. Ras signaling is mediated by a system of interacting molecules: upstream enzymes (GEF/GAP) regulate Ras’s ability to recruit multiple competing downstream effectors. We developed a multiplexed, multi-turnover assay for measuring the dynamic signaling behavior of in vitro reconstituted H-Ras signaling systems. By including both upstream regulators and downstream effectors, we can systematically map how different network configurations shape the dynamic system response. The concentration and identity of both upstream and downstream signaling components strongly impacted the timing, duration, shape, and amplitude of effector outputs. The distorted output of oncogenic alleles of Ras was highly dependent on the balance of positive (GAP) and negative (GEF) regulators in the system. We found that different effectors interpreted the same inputs with distinct output dynamics, enabling a Ras system to encode multiple unique temporal outputs in response to a single input. We also found that different Ras-to-GEF positive feedback mechanisms could reshape output dynamics in distinct ways, such as signal amplification or overshoot minimization. Mapping of the space of output behaviors accessible to Ras provides a design manual for programming Ras circuits, and reveals how these systems are readily adapted to produce an array of dynamic signaling behaviors. Nonetheless, this versatility comes with a trade-off of fragility, as there exist numerous paths to altered signaling behaviors that could cause disease. DOI: http://dx.doi.org/10.7554/eLife.12435.001 PMID:26765565

THE DYNAMIC RESPONSE OF THERMOMETER-WELL ASSEMBLIES.

DTIC Science & Technology

parameter models of the thermometric system were constructed and gave acceptable agreement with the experimental results. These models can be used to predict the dynamic behavior of any similar thermometer system. (Author)

Fractal and chaotic laws on seismic dissipated energy in an energy system of engineering structures

NASA Astrophysics Data System (ADS)

Cui, Yu-Hong; Nie, Yong-An; Yan, Zong-Da; Wu, Guo-You

1998-09-01

Fractal and chaotic laws of engineering structures are discussed in this paper, it means that the intrinsic essences and laws on dynamic systems which are made from seismic dissipated energy intensity E d and intensity of seismic dissipated energy moment I e are analyzed. Based on the intrinsic characters of chaotic and fractal dynamic system of E d and I e, three kinds of approximate dynamic models are rebuilt one by one: index autoregressive model, threshold autoregressive model and local-approximate autoregressive model. The innate laws, essences and systematic error of evolutional behavior I e are explained over all, the short-term behavior predictability and long-term behavior probability of which are analyzed in the end. That may be valuable for earthquake-resistant theory and analysis method in practical engineering structures.

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

Understanding ecohydrological connectivity in savannas: A system dynamics modeling approach

USDA-ARS?s Scientific Manuscript database

Ecohydrological connectivity is a system-level property that results from the linkages in the networks of water transport through ecosystems, by which feedback effects and other emergent system behaviors may be generated. We created a systems dynamic model that represents primary ecohydrological net...

Novel tunable dynamic tweezers using dark-bright soliton collision control in an optical add/drop filter.

PubMed

Teeka, Chat; Jalil, Muhammad Arif; Yupapin, Preecha P; Ali, Jalil

2010-12-01

We propose a novel system of the dynamic optical tweezers generated by a dark soliton in the fiber optic loop. A dark soliton known as an optical tweezer is amplified and tuned within the microring resonator system. The required tunable tweezers with different widths and powers can be controlled. The analysis of dark-bright soliton conversion using a dark soliton pulse propagating within a microring resonator system is analyzed. The dynamic behaviors of soliton conversion in add/drop filter is also analyzed. The control dark soliton is input into the system via the add port of the add/drop filter. The dynamic behavior of the dark-bright soliton conversion is observed. The required stable signal is obtained via a drop and throughput ports of the add/drop filter with some suitable parameters. In application, the trapped light/atom and transportation can be realized by using the proposed system.

Simulating the Interactions Among Land Use, Transportation ...

EPA Pesticide Factsheets

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic and non-linear interactions among transportation, land use, and socioeconomic systems. System dynamics (SD) provides a common framework for modeling the complex interactions among transportation and other related systems. This study uses a SD model to simulate the cascading impacts of a proposed light rail transit (LRT) system in central North Carolina, USA. The Durham-Orange Light Rail Project (D-O LRP) SD model incorporates relationships among the land use, transportation, and economy sectors to simulate the complex feedbacks that give rise to the travel behavior changes forecasted by the region’s transportation model. This paper demonstrates the sensitivity of changes in travel behavior to the proposed LRT system and the assumptions that went into the transportation modeling, and compares those results to the impacts of an alternative fare-free transit system. SD models such as the D-O LRP SD model can complement transportation studies by providing valuable insight into the interdependent community systems that collectively contribute to travel behavior changes. Presented at the 35th International Conference of the System Dynamics Society in Cambridge, MA, July 18th, 2017

Active polar two-fluid macroscopic dynamics.

PubMed

Pleiner, H; Svenšek, D; Brand, H R

2013-11-01

We study the dynamics of systems with a polar dynamic preferred direction. Examples include the pattern-forming growth of bacteria as well as shoals of fish, flocks of birds and migrating insects. Due to the fact that the preferred direction only exists dynamically, but not statically, the macroscopic variable of choice is the macroscopic velocity associated with the motion of the active units, which are typically biological in nature. We derive the macroscopic equations for such a system and discuss novel static, reversible and irreversible cross-couplings connected to a second velocity as a variable. We analyze in detail how the macroscopic behavior of an active system with a polar dynamic preferred direction compares to other systems with two velocities including immiscible liquids and electrically neutral quantum liquids such as superfluid (4)He and (3)He . We critically discuss changes in the normal mode spectrum when comparing uncharged superfluids, immiscible liquids and active system with a polar dynamic preferred direction. We investigate the influence of a macroscopic hand (collective effects of chirality) on the macroscopic behavior of such active media.

Human Guidance Behavior Decomposition and Modeling

NASA Astrophysics Data System (ADS)

Feit, Andrew James

Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

Nonequilibrium magnetic properties in a two-dimensional kinetic mixed Ising system within the effective-field theory and Glauber-type stochastic dynamics approach.

PubMed

Ertaş, Mehmet; Deviren, Bayram; Keskin, Mustafa

2012-11-01

Nonequilibrium magnetic properties in a two-dimensional kinetic mixed spin-2 and spin-5/2 Ising system in the presence of a time-varying (sinusoidal) magnetic field are studied within the effective-field theory (EFT) with correlations. The time evolution of the system is described by using Glauber-type stochastic dynamics. The dynamic EFT equations are derived by employing the Glauber transition rates for two interpenetrating square lattices. We investigate the time dependence of the magnetizations for different interaction parameter values in order to find the phases in the system. We also study the thermal behavior of the dynamic magnetizations, the hysteresis loop area, and dynamic correlation. The dynamic phase diagrams are presented in the reduced magnetic field amplitude and reduced temperature plane and we observe that the system exhibits dynamic tricritical and reentrant behaviors. Moreover, the system also displays a double critical end point (B), a zero-temperature critical point (Z), a critical end point (E), and a triple point (TP). We also performed a comparison with the mean-field prediction in order to point out the effects of correlations and found that some of the dynamic first-order phase lines, which are artifacts of the mean-field approach, disappeared.

Modal identification of dynamic mechanical systems

NASA Astrophysics Data System (ADS)

Srivastava, R. K.; Kundra, T. K.

1992-07-01

This paper reviews modal identification techniques which are now helping designers all over the world to improve the dynamic behavior of vibrating engineering systems. In this context the need to develop more accurate and faster parameter identification is ever increasing. A new dynamic stiffness matrix based identification method which is highly accurate, fast and system-dynamic-modification compatible is presented. The technique is applicable to all those multidegree-of-freedom systems where full receptance matrix can be experimentally measured.

Dynamics analysis of the fast-slow hydro-turbine governing system with different time-scale coupling

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Wu, Changzhi; Wang, Xiangyu

2018-01-01

Multi-time scales modeling of hydro-turbine governing system is crucial in precise modeling of hydropower plant and provides support for the stability analysis of the system. Considering the inertia and response time of the hydraulic servo system, the hydro-turbine governing system is transformed into the fast-slow hydro-turbine governing system. The effects of the time-scale on the dynamical behavior of the system are analyzed and the fast-slow dynamical behaviors of the system are investigated with different time-scale. Furthermore, the theoretical analysis of the stable regions is presented. The influences of the time-scale on the stable region are analyzed by simulation. The simulation results prove the correctness of the theoretical analysis. More importantly, the methods and results of this paper provide a perspective to multi-time scales modeling of hydro-turbine governing system and contribute to the optimization analysis and control of the system.

Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches

NASA Astrophysics Data System (ADS)

Moosavi, S. Amin; Montakhab, Afshin

2015-11-01

Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014), 10.1103/PhysRevE.89.052139] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise. We investigate the role of high-average connectivity, random long-range connections, as well as synaptic noise in achieving mean-field behavior. We employ finite-size scaling in order to extract critical exponents with good accuracy. We conclude that relevant structural mechanisms responsible for mean-field behavior cannot be justified in realistic models of the cortex. However, strong dynamical noise, which can have realistic justifications, always leads to mean-field behavior regardless of the underlying structure. Our work provides a different (dynamical) origin than the conventionally accepted (structural) mechanisms for mean-field behavior in neuronal avalanches.

Application of largest Lyapunov exponent analysis on the studies of dynamics under external forces

NASA Astrophysics Data System (ADS)

Odavić, Jovan; Mali, Petar; Tekić, Jasmina; Pantić, Milan; Pavkov-Hrvojević, Milica

2017-06-01

Dynamics of driven dissipative Frenkel-Kontorova model is examined by using largest Lyapunov exponent computational technique. Obtained results show that besides the usual way where behavior of the system in the presence of external forces is studied by analyzing its dynamical response function, the largest Lyapunov exponent analysis can represent a very convenient tool to examine system dynamics. In the dc driven systems, the critical depinning force for particular structure could be estimated by computing the largest Lyapunov exponent. In the dc+ac driven systems, if the substrate potential is the standard sinusoidal one, calculation of the largest Lyapunov exponent offers a more sensitive way to detect the presence of Shapiro steps. When the amplitude of the ac force is varied the behavior of the largest Lyapunov exponent in the pinned regime completely reflects the behavior of Shapiro steps and the critical depinning force, in particular, it represents the mirror image of the amplitude dependence of critical depinning force. This points out an advantage of this technique since by calculating the largest Lyapunov exponent in the pinned regime we can get an insight into the dynamics of the system when driving forces are applied. Additionally, the system is shown to be not chaotic even in the case of incommensurate structures and large amplitudes of external force, which is a consequence of overdampness of the model and the Middleton's no passing rule.

Continuous monitoring the vehicle dynamics and driver behavior using navigation systems

NASA Astrophysics Data System (ADS)

Ene, George

2017-10-01

In all fields cost is very important and the increasing amount of data that are needed for active safety systems, like ADAS, lead to implementation of some complex and powerful unit for processing raw data. In this manner is necessary a cost-effective method to estimate the maximum available tire road friction during acceleration and braking by continuous monitoring the vehicle dynamics and driver behavior. The method is based on the hypothesis that short acceleration and braking periods can indicate vehicle dynamics, and thus the available tire road friction coefficient, and also human behavior and his limits. Support for this hypothesis is found in the literature and is supported by the result of experiments conducted under different conditions and seasons.

Social Ecology of Asthma: Engaging Stakeholders in Integrating Health Behavior Theories and Practice-Based Evidence through Systems Mapping

ERIC Educational Resources Information Center

Gillen, Emily M.; Hassmiller Lich, Kristen; Yeatts, Karin B.; Hernandez, Michelle L.; Smith, Timothy W.; Lewis, Megan A.

2014-01-01

This article describes a process for integrating health behavior and social science theories with practice-based insights using participatory systems thinking and diagramming methods largely inspired by system dynamics methods. This integration can help close the gap between research and practice in health education and health behavior by offering…

Algorithm for Stabilizing a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

Double dynamic scaling in human communication dynamics

NASA Astrophysics Data System (ADS)

Wang, Shengfeng; Feng, Xin; Wu, Ye; Xiao, Jinhua

2017-05-01

In the last decades, human behavior has been deeply understanding owing to the huge quantities data of human behavior available for study. The main finding in human dynamics shows that temporal processes consist of high-activity bursty intervals alternating with long low-activity periods. A model, assuming the initiator of bursty follow a Poisson process, is widely used in the modeling of human behavior. Here, we provide further evidence for the hypothesis that different bursty intervals are independent. Furthermore, we introduce a special threshold to quantitatively distinguish the time scales of complex dynamics based on the hypothesis. Our results suggest that human communication behavior is a composite process of double dynamics with midrange memory length. The method for calculating memory length would enhance the performance of many sequence-dependent systems, such as server operation and topic identification.

Dynamic behavior of tripolar hip endoprostheses under physiological conditions and their effect on stability.

PubMed

Fabry, Christian; Kaehler, Michael; Herrmann, Sven; Woernle, Christoph; Bader, Rainer

2014-01-01

Tripolar systems have been implanted to reduce the risk of recurrent dislocation. However, there is little known about the dynamic behavior of tripolar hip endoprostheses under daily life conditions and achieved joint stability. Hence, the objective of this biomechanical study was to examine the in vivo dynamics and dislocation behavior of two types of tripolar systems compared to a standard total hip replacement (THR) with the same outer head diameter. Several load cases of daily life activities were applied to an eccentric and a concentric tripolar system by an industrial robot. During testing, the motion of the intermediate component was measured using a stereo camera system. Additionally, their behavior under different dislocation scenarios was investigated in comparison to a standard THR. For the eccentric tripolar system, the intermediate component demonstrated the shifting into moderate valgus-positions, regardless of the type of movement. This implant showed the highest resisting torque against dislocation in combination with a large range of motion. In contrast, the concentric tripolar system tended to remain in varus-positions and was primarily moved after stem contact. According to the results, eccentric tripolar systems can work well under in vivo conditions and increase hip joint stability in comparison to standard THRs. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Design tools for complex dynamic security systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson

2007-01-01

The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systemsmore » are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.« less

From quantum mechanics to finance: Microfoundations for jumps, spikes and high volatility phases in diffusion price processes

NASA Astrophysics Data System (ADS)

Henkel, Christof

2017-03-01

We present an agent behavior based microscopic model that induces jumps, spikes and high volatility phases in the price process of a traded asset. We transfer dynamics of thermally activated jumps of an unexcited/excited two state system discussed in the context of quantum mechanics to agent socio-economic behavior and provide microfoundations. After we link the endogenous agent behavior to price dynamics we establish the circumstances under which the dynamics converge to an Itô-diffusion price processes in the large market limit.

Dynamic behavior of microscale particles controlled by standing bulk acoustic waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenhall, J.; Raeymaekers, B., E-mail: bart.raeymaekers@utah.edu; Guevara Vasquez, F.

2014-10-06

We analyze the dynamic behavior of a spherical microparticle submerged in a fluid medium, driven to the node of a standing bulk acoustic wave created by two opposing transducers. We derive the dynamics of the fluid-particle system taking into account the acoustic radiation force and the time-dependent and time-independent drag force acting on the particle. Using this dynamic model, we characterize the transient and steady-state behavior of the fluid-particle system as a function of the particle and fluid properties and the transducer operating parameters. The results show that the settling time and percent overshoot of the particle trajectory are dependentmore » on the ratio of the acoustic radiation force and time-independent damping force. In addition, we show that the particle oscillates around the node of the standing wave with an amplitude that depends on the ratio of the time-dependent drag forces and the particle inertia.« less

Computational Models of Protein Kinematics and Dynamics: Beyond Simulation

PubMed Central

Gipson, Bryant; Hsu, David; Kavraki, Lydia E.; Latombe, Jean-Claude

2016-01-01

Physics-based simulation represents a powerful method for investigating the time-varying behavior of dynamic protein systems at high spatial and temporal resolution. Such simulations, however, can be prohibitively difficult or lengthy for large proteins or when probing the lower-resolution, long-timescale behaviors of proteins generally. Importantly, not all questions about a protein system require full space and time resolution to produce an informative answer. For instance, by avoiding the simulation of uncorrelated, high-frequency atomic movements, a larger, domain-level picture of protein dynamics can be revealed. The purpose of this review is to highlight the growing body of complementary work that goes beyond simulation. In particular, this review focuses on methods that address kinematics and dynamics, as well as those that address larger organizational questions and can quickly yield useful information about the long-timescale behavior of a protein. PMID:22524225

Making Sense of Dynamic Systems: How Our Understanding of Stocks and Flows Depends on a Global Perspective

ERIC Educational Resources Information Center

Fischer, Helen; Gonzalez, Cleotilde

2016-01-01

Stocks and flows (SF) are building blocks of dynamic systems: Stocks change through inflows and outflows, such as our bank balance changing with withdrawals and deposits, or atmospheric CO[subscript 2] with absorptions and emissions. However, people make systematic errors when trying to infer the behavior of dynamic systems, termed SF failure,…

Deterministic chaos and fractal complexity in the dynamics of cardiovascular behavior: perspectives on a new frontier.

PubMed

Sharma, Vijay

2009-09-10

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts.

Deterministic Chaos and Fractal Complexity in the Dynamics of Cardiovascular Behavior: Perspectives on a New Frontier

PubMed Central

Sharma, Vijay

2009-01-01

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts. PMID:19812706

Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks

NASA Astrophysics Data System (ADS)

Liu, Quan-Hui; Wang, Wei; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-02-01

Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

Experimental Determination of Dynamical Lee-Yang Zeros

NASA Astrophysics Data System (ADS)

Brandner, Kay; Maisi, Ville F.; Pekola, Jukka P.; Garrahan, Juan P.; Flindt, Christian

2017-05-01

Statistical physics provides the concepts and methods to explain the phase behavior of interacting many-body systems. Investigations of Lee-Yang zeros—complex singularities of the free energy in systems of finite size—have led to a unified understanding of equilibrium phase transitions. The ideas of Lee and Yang, however, are not restricted to equilibrium phenomena. Recently, Lee-Yang zeros have been used to characterize nonequilibrium processes such as dynamical phase transitions in quantum systems after a quench or dynamic order-disorder transitions in glasses. Here, we experimentally realize a scheme for determining Lee-Yang zeros in such nonequilibrium settings. We extract the dynamical Lee-Yang zeros of a stochastic process involving Andreev tunneling between a normal-state island and two superconducting leads from measurements of the dynamical activity along a trajectory. From the short-time behavior of the Lee-Yang zeros, we predict the large-deviation statistics of the activity which is typically difficult to measure. Our method paves the way for further experiments on the statistical mechanics of many-body systems out of equilibrium.

Nonlinear dynamics and damage induced properties of soft matter with application in oncology

NASA Astrophysics Data System (ADS)

Naimark, O.

2017-09-01

Molecular-morphological signs of oncogenesis could be linked to multiscale collective effects in molecular, cell and tissue related to defects (damage) dynamics. It was shown that nonlinear behavior of biological systems can be linked to the existence of characteristic collective open state modes providing the coherent expression dynamics. New type of criticality in nonequilibrium systems with defects—structural-scaling transition allows the definition of the `driving force' for a biological soft matter related to consolidated open states. The set of collective open states (breathers, autosolitons and blow-up modes) in the molecular ensembles provides the collective expression dynamics to attract the entire system (cell, tissue) toward a few preferred global states. The co-existence of three types of collective modes determines the multifractal scenario of biological soft matter dynamics. The appearance of `globally convergent' dynamics corresponding to the coherent behavior of multiscale blow-up open states (blow-up gene expression) leads to anomalous localized softening (blow-up localized damage) and the subjection of the cells (or tissue) to monofractal dynamics. This dynamics can be associated with cancer progression.

Time Reparametrization Group and the Long Time Behavior in Quantum Glassy Systems

NASA Astrophysics Data System (ADS)

Kennett, Malcolm P.; Chamon, Claudio

2001-02-01

We study the long time dynamics of a quantum version of the Sherrington-Kirkpatrick model. Time reparametrizations of the dynamical equations have a parallel with renormalization group transformations; in this language the long time behavior of this model is controlled by a reparametrization group ( RpG) fixed point of the classical dynamics. The irrelevance of quantum terms in the dynamical equations in the aging regime explains the classical nature of the out of equilibrium fluctuation-dissipation relation.

Periodic or chaotic bursting dynamics via delayed pitchfork bifurcation in a slow-varying controlled system

NASA Astrophysics Data System (ADS)

Yu, Yue; Zhang, Zhengdi; Han, Xiujing

2018-03-01

In this work, we aim to demonstrate the novel routes to periodic and chaotic bursting, i.e., the different bursting dynamics via delayed pitchfork bifurcations around stable attractors, in the classical controlled Lü system. First, by computing the corresponding characteristic polynomial, we determine where some critical values about bifurcation behaviors appear in the Lü system. Moreover, the transition mechanism among different stable attractors has been introduced including homoclinic-type connections or chaotic attractors. Secondly, taking advantage of the above analytical results, we carry out a study of the mechanism for bursting dynamics in the Lü system with slowly periodic variation of certain control parameter. A distinct delayed supercritical pitchfork bifurcation behavior can be discussed when the control item passes through bifurcation points periodically. This delayed dynamical behavior may terminate at different parameter areas, which leads to different spiking modes around different stable attractors (equilibriums, limit cycles, or chaotic attractors). In particular, the chaotic attractor may appear by Shilnikov connections or chaos boundary crisis, which leads to the occurrence of impressive chaotic bursting oscillations. Our findings enrich the study of bursting dynamics and deepen the understanding of some similar sorts of delayed bursting phenomena. Finally, some numerical simulations are included to illustrate the validity of our study.

Mathematical Models to Determine Stable Behavior of Complex Systems

NASA Astrophysics Data System (ADS)

Sumin, V. I.; Dushkin, A. V.; Smolentseva, T. E.

2018-05-01

The paper analyzes a possibility to predict functioning of a complex dynamic system with a significant amount of circulating information and a large number of random factors impacting its functioning. Functioning of the complex dynamic system is described as a chaotic state, self-organized criticality and bifurcation. This problem may be resolved by modeling such systems as dynamic ones, without applying stochastic models and taking into account strange attractors.

A hyperjerk memristive system with infinite equilibrium points

NASA Astrophysics Data System (ADS)

Prousalis, Dimitrios A.; Volos, Christos K.; Stouboulos, Ioannis N.; Kyprianidis, Ioannis M.

2017-09-01

A novel 4-D dynamical memristive system is presented in this work. The specificity of the model is that it develops a line of equilibrium points and it has hyperjerk dynamics in a particular range of the parameters space. The behavior of the suggested system is investigated through numerical simulations, by using phase portraits, Lyapunov exponents, bifurcation diagrams. Also, its circuital implementation confirms the memristive system's expected dynamics.

Information model of trainee characteristics with definition of stochastic behavior of dynamic system

NASA Astrophysics Data System (ADS)

Sumin, V. I.; Smolentseva, T. E.; Belokurov, S. V.; Lankin, O. V.

2018-03-01

In the work the process of formation of trainee characteristics with their subsequent change is analyzed and analyzed. Characteristics of trainees were obtained as a result of testing for each section of information on the chosen discipline. The results obtained during testing were input to the dynamic system. The area of control actions consisting of elements of the dynamic system is formed. The limit of deterministic predictability of element trajectories in dynamical systems based on local or global attractors is revealed. The dimension of the phase space of the dynamic system is determined, which allows estimating the parameters of the initial system. On the basis of time series of observations, it is possible to determine the predictability interval of all parameters, which make it possible to determine the behavior of the system discretely in time. Then the measure of predictability will be the sum of Lyapunov’s positive indicators, which are a quantitative measure for all elements of the system. The components for the formation of an algorithm allowing to determine the correlation dimension of the attractor for known initial experimental values of the variables are revealed. The generated algorithm makes it possible to carry out an experimental study of the dynamics of changes in the trainee’s parameters with initial uncertainty.

Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Yang, Lingrun; Li, Jing

2018-07-01

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers' rationality degree, travelers' heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers' behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers' bounded rationality. We use reinforcement-learning model to depict travelers' route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers' expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers' group behavior on the transportation system, and give some insights into the relation between travelers' group behavior and the performance of transportation system.

Systemic Case Formulation, Individualized Process Monitoring, and State Dynamics in a Case of Dissociative Identity Disorder.

PubMed

Schiepek, Günter K; Stöger-Schmidinger, Barbara; Aichhorn, Wolfgang; Schöller, Helmut; Aas, Benjamin

2016-01-01

Objective: The aim of this case report is to demonstrate the feasibility of a systemic procedure (synergetic process management) including modeling of the idiographic psychological system and continuous high-frequency monitoring of change dynamics in a case of dissociative identity disorder. The psychotherapy was realized in a day treatment center with a female client diagnosed with borderline personality disorder (BPD) and dissociative identity disorder. Methods: A three hour long co-creative session at the beginning of the treatment period allowed for modeling the systemic network of the client's dynamics of cognitions, emotions, and behavior. The components (variables) of this idiographic system model (ISM) were used to create items for an individualized process questionnaire for the client. The questionnaire was administered daily through an internet-based monitoring tool (Synergetic Navigation System, SNS), to capture the client's individual change process continuously throughout the therapy and after-care period. The resulting time series were reflected by therapist and client in therapeutic feedback sessions. Results: For the client it was important to see how the personality states dominating her daily life were represented by her idiographic system model and how the transitions between each state could be explained and understood by the activating and inhibiting relations between the cognitive-emotional components of that system. Continuous monitoring of her cognitions, emotions, and behavior via SNS allowed for identification of important triggers, dynamic patterns, and psychological mechanisms behind seemingly erratic state fluctuations. These insights enabled a change in management of the dynamics and an intensified trauma-focused therapy. Conclusion: By making use of the systemic case formulation technique and subsequent daily online monitoring, client and therapist continuously refer to detailed visualizations of the mental and behavioral network and its dynamics (e.g., order transitions). Effects on self-related information processing, on identity development, and toward a more pronounced autonomy in life (instead of feeling helpless against the chaoticity of state dynamics) were evident in the presented case and documented by the monitoring system.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Comparing the Ability of Enhanced Sampling Molecular Dynamics Methods To Reproduce the Behavior of Fluorescent Labels on Proteins.

PubMed

Walczewska-Szewc, Katarzyna; Deplazes, Evelyne; Corry, Ben

2015-07-14

Adequately sampling the large number of conformations accessible to proteins and other macromolecules is one of the central challenges in molecular dynamics (MD) simulations; this activity can be difficult, even for relatively simple systems. An example where this problem arises is in the simulation of dye-labeled proteins, which are now being widely used in the design and interpretation of Förster resonance energy transfer (FRET) experiments. In this study, MD simulations are used to characterize the motion of two commonly used FRET dyes attached to an immobilized chain of polyproline. Even in this simple system, the dyes exhibit complex behavior that is a mixture of fast and slow motions. Consequently, very long MD simulations are required to sufficiently sample the entire range of dye motion. Here, we compare the ability of enhanced sampling methods to reproduce the behavior of fluorescent labels on proteins. In particular, we compared Accelerated Molecular Dynamics (AMD), metadynamics, Replica Exchange Molecular Dynamics (REMD), and High Temperature Molecular Dynamics (HTMD) to equilibrium MD simulations. We find that, in our system, all of these methods improve the sampling of the dye motion, but the most significant improvement is achieved using REMD.

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

Comparison of Dynamical Behaviors Between Monofunctional and Bifunctional Two-Component Signaling Modules

NASA Astrophysics Data System (ADS)

Yang, Xiyan; Wu, Yahao; Yuan, Zhanjiang

2015-06-01

Two-component signaling modules exist extensively in bacteria and microbes. These modules can be, based on their distinct network structures, divided into two types: the monofunctional system (denoted by MFS) where the sensor kinase (SK) modulates only phosphorylation of the response regulator (RR), and the bifunctional system (denoted by BFS) where the SK catalyzes both phosphorylation and dephosphorylation of the RR. Here, we analyze dynamical behaviors of these two systems based on stability theory, focusing on differences between them. The analysis of the deterministic behavior indicates that there is no difference between the two modules, that is, each system has the unique stable steady state. However, there are significant differences in stochastic behavior between them. Specifically, if the mean phosphorylated SK level is kept the same for the two modules, then the variance and the Fano factor for the phosphorylated RR in the BFS are always no less than those in the MFS, indicating that bifunctionality always enhances fluctuations. The correlation between the phosphorylated SK and the phosphorylated RR in the BFS is always positive mainly due to competition between system components, but this correlation in the MFS may be positive, almost zero, or negative, depending on the ratio between two rate constants. Our overall analysis indicates that differences between dynamical behaviors of monofunctional and bifunctional signaling modules are mainly in the stochastic rather than deterministic aspect.

Dynamic mechanical control of local vacancies in NiO thin films

NASA Astrophysics Data System (ADS)

Seol, Daehee; Yang, Sang Mo; Jesse, Stephen; Choi, Minseok; Hwang, Inrok; Choi, Taekjib; Park, Bae Ho; Kalinin, Sergei V.; Kim, Yunseok

2018-07-01

The manipulation of local ionic behavior via external stimuli in oxide systems is of great interest because it can help in directly tuning material properties. Among external stimuli, mechanical force has attracted intriguing attention as novel stimulus for ionic modulation. Even though effectiveness of mechanical force on local ionic modulation has been validated in terms of static effect, its real-time i.e., dynamic, behavior under an application of the force is barely investigated in spite of its crucial impact on device performance such as force or pressure sensors. In this study, we explore dynamic ionic behavior modulated by mechanical force in NiO thin films using electrochemical strain microscopy (ESM). Ionically mediated ESM hysteresis loops were significantly varied under an application of mechanical force. Based on these results, we were able to investigate relative relationship between the force and voltage effects on ionic motion and, further, control effectively ionic behavior through combination of mechanical and electrical stimuli. Our results can provide comprehensive information on the effect of mechanical forces on ionic dynamics in ionic systems.

Disentangling the stochastic behavior of complex time series

NASA Astrophysics Data System (ADS)

Anvari, Mehrnaz; Tabar, M. Reza Rahimi; Peinke, Joachim; Lehnertz, Klaus

2016-10-01

Complex systems involving a large number of degrees of freedom, generally exhibit non-stationary dynamics, which can result in either continuous or discontinuous sample paths of the corresponding time series. The latter sample paths may be caused by discontinuous events - or jumps - with some distributed amplitudes, and disentangling effects caused by such jumps from effects caused by normal diffusion processes is a main problem for a detailed understanding of stochastic dynamics of complex systems. Here we introduce a non-parametric method to address this general problem. By means of a stochastic dynamical jump-diffusion modelling, we separate deterministic drift terms from different stochastic behaviors, namely diffusive and jumpy ones, and show that all of the unknown functions and coefficients of this modelling can be derived directly from measured time series. We demonstrate appli- cability of our method to empirical observations by a data-driven inference of the deterministic drift term and of the diffusive and jumpy behavior in brain dynamics from ten epilepsy patients. Particularly these different stochastic behaviors provide extra information that can be regarded valuable for diagnostic purposes.

Dynamic mechanical control of local vacancies in NiO thin films.

PubMed

Seol, Daehee; Yang, Sang Mo; Jesse, Stephen; Choi, Minseok; Hwang, Inrok; Choi, Taekjib; Park, Bae Ho; Kalinin, Sergei V; Kim, Yunseok

2018-07-06

The manipulation of local ionic behavior via external stimuli in oxide systems is of great interest because it can help in directly tuning material properties. Among external stimuli, mechanical force has attracted intriguing attention as novel stimulus for ionic modulation. Even though effectiveness of mechanical force on local ionic modulation has been validated in terms of static effect, its real-time i.e., dynamic, behavior under an application of the force is barely investigated in spite of its crucial impact on device performance such as force or pressure sensors. In this study, we explore dynamic ionic behavior modulated by mechanical force in NiO thin films using electrochemical strain microscopy (ESM). Ionically mediated ESM hysteresis loops were significantly varied under an application of mechanical force. Based on these results, we were able to investigate relative relationship between the force and voltage effects on ionic motion and, further, control effectively ionic behavior through combination of mechanical and electrical stimuli. Our results can provide comprehensive information on the effect of mechanical forces on ionic dynamics in ionic systems.

A System Dynamics Approach to Understanding Cost and Revenue Interactions in the Community College Financial System.

ERIC Educational Resources Information Center

Howard, James E.

After identifying the components of a community college financial system as enrollment, costs, revenues and tuition, this paper addresses the need for a system dynamics analysis of a California community college district. This systems approach would assess the possible effects of alternative policies on the characteristic behavior modes of the…

A system dynamics optimization framework to achieve population desired of average weight target

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Haji; Zaibidi, Nerda Zura

2017-11-01

Obesity is becoming a serious problem in Malaysia as it has been rated as the highest among Asian countries. The aim of the paper is to propose a system dynamics (SD) optimization framework to achieve population desired weight target based on the changes in physical activity behavior and its association to weight and obesity. The system dynamics approach of stocks and flows diagram was used to quantitatively model the impact of both behavior on the population's weight and obesity trends. This work seems to bring this idea together and highlighting the interdependence of the various aspects of eating and physical activity behavior on the complex of human weight regulation system. The model was used as an experimentation vehicle to investigate the impacts of changes in physical activity on weight and prevalence of obesity implications. This framework paper provides evidence on the usefulness of SD optimization as a strategic decision making approach to assist in decision making related to obesity prevention. SD applied in this research is relatively new in Malaysia and has a high potential to apply to any feedback models that address the behavior cause to obesity.

Dynamic modelling and response characteristics of a magnetic bearing rotor system with auxiliary bearings

NASA Technical Reports Server (NTRS)

Free, April M.; Flowers, George T.; Trent, Victor S.

1995-01-01

Auxiliary bearings are a critical feature of any magnetic bearing system. They protect the soft iron core of the magnetic bearing during an overload or failure. An auxiliary bearing typically consists of a rolling element bearing or bushing with a clearance gap between the rotor and the inner race of the support. The dynamics of such systems can be quite complex. It is desired to develop a rotordynamic model which describes the dynamic behavior of a flexible rotor system with magnetic bearings including auxiliary bearings. The model is based upon an experimental test facility. Some simulation studies are presented to illustrate the behavior of the model. In particular, the effects of introducing sideloading from the magnetic bearing when one coil fails is studied.

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Watching cellular machinery in action, one molecule at a time.

PubMed

Monachino, Enrico; Spenkelink, Lisanne M; van Oijen, Antoine M

2017-01-02

Single-molecule manipulation and imaging techniques have become important elements of the biologist's toolkit to gain mechanistic insights into cellular processes. By removing ensemble averaging, single-molecule methods provide unique access to the dynamic behavior of biomolecules. Recently, the use of these approaches has expanded to the study of complex multiprotein systems and has enabled detailed characterization of the behavior of individual molecules inside living cells. In this review, we provide an overview of the various force- and fluorescence-based single-molecule methods with applications both in vitro and in vivo, highlighting these advances by describing their applications in studies on cytoskeletal motors and DNA replication. We also discuss how single-molecule approaches have increased our understanding of the dynamic behavior of complex multiprotein systems. These methods have shown that the behavior of multicomponent protein complexes is highly stochastic and less linear and deterministic than previously thought. Further development of single-molecule tools will help to elucidate the molecular dynamics of these complex systems both inside the cell and in solutions with purified components. © 2017 Monachino et al.

On the Interplay between Order Parameter Dynamics and System Parameter Dynamics in Human Perceptual-Cognitive-Behavioral Systems.

PubMed

Frank, T D

2015-04-01

Previous research has demonstrated that perceiving, thinking, and acting are human activities that correspond to self-organized patterns. The emergence of such patterns can be completely described in terms of the dynamics of the pattern amplitudes, which are referred to as order parameters. The patterns emerge at bifurcations points when certain system parameters internal and external to a human agent exceed critical values. At issue is how one might study the order parameter dynamics for sequences of consecutive, emergent perceptual, cognitive, or behavioral activities. In particular, these activities may in turn impact the system parameters that have led to the emergence of the activities in the first place. This interplay between order parameter dynamics and system parameter dynamics is discussed in general and formulated in mathematical terms. Previous work that has made use of this two-tiered framework of order parameter and system parameter dynamics are briefly addressed. As an application, a model for perception under functional fixedness is presented. Finally, it is argued that the phenomena that emerge in this framework and can be observed when human agents perceive, think, and act are just as likely to occur in pattern formation systems of the inanimate world. Consequently, these phenomena do not necessarily have a neurophysiological basis but should instead be understood from the perspective of the theory of self-organization.

From strings to coils: Rotational dynamics of DNA-linked colloidal chains

NASA Astrophysics Data System (ADS)

Kuei, Steve; Garza, Burke; Biswal, Sibani Lisa

2017-10-01

We investigate the dynamical behavior of deformable filaments experimentally using a tunable model system consisting of linked paramagnetic colloidal particles, where the persistence length lp, the contour length lc, and the strength and frequency of the external driving force are controlled. We find that upon forcing by an external magnetic field, a variety of structural and conformational regimes exist. Depending on the competition of forces and torques on the chain, we see classic rigid rotator behavior, as well as dynamically rich wagging, coiling, and folding behavior. Through a combination of experiments, computational models, and theoretical calculations, we are able to observe, classify, and predict these dynamics as a function of the dimensionless Mason and magnetoelastic numbers.

Dynamic magnetic hysteresis properties of two-dimensional ferrimagnetic structures containing high-spin (S = 5/2) and low-spin (S = 1/2)

NASA Astrophysics Data System (ADS)

Batı, Mehmet; Ertaş, Mehmet

2017-09-01

The dynamic hysteresis behaviors of a containing high spin-5/2 and low spin-1/2 Ising ferrimagnetic system on a square lattice are studied by using the dynamic mean-field approximation. The influences of the temperature, the single-ion anisotropy and the frequency on dynamic hysteresis behaviors are investigated in detail. Somewhat characteristic behaviors are found, such as the presence of triple hysteresis loop for appropriate values of the crystal field or temperature. Besides, we observed that, hysteresis loop area and phase transition points are very sensitive to changes in frequency and thus have profound importance in device application.

Delayed system response times affect immediate physiology and the dynamics of subsequent button press behavior.

PubMed

Kohrs, Christin; Hrabal, David; Angenstein, Nicole; Brechmann, André

2014-11-01

System response time research is an important issue in human-computer interactions. Experience with technical devices and general rules of human-human interactions determine the user's expectation, and any delay in system response time may lead to immediate physiological, emotional, and behavioral consequences. We investigated such effects on a trial-by-trial basis during a human-computer interaction by measuring changes in skin conductance (SC), heart rate (HR), and the dynamics of button press responses. We found an increase in SC and a deceleration of HR for all three delayed system response times (0.5, 1, 2 s). Moreover, the data on button press dynamics was highly informative since subjects repeated a button press with more force in response to delayed system response times. Furthermore, the button press dynamics could distinguish between correct and incorrect decisions and may thus even be used to infer the uncertainty of a user's decision. Copyright © 2014 Society for Psychophysiological Research.

Nonlinear dynamics in the study of birdsong

NASA Astrophysics Data System (ADS)

Mindlin, Gabriel B.

2017-09-01

Birdsong, a rich and complex behavior, is a stellar model to understand a variety of biological problems, from motor control to learning. It also enables us to study how behavior emerges when a nervous system, a biomechanical device and the environment interact. In this review, I will show that many questions in the field can benefit from the approach of nonlinear dynamics, and how birdsong can inspire new directions for research in dynamics.

Dynamical heterogeneity in a glass-forming ideal gas.

PubMed

Charbonneau, Patrick; Das, Chinmay; Frenkel, Daan

2008-07-01

We conduct a numerical study of the dynamical behavior of a system of three-dimensional "crosses," particles that consist of three mutually perpendicular line segments of length sigma rigidly joined at their midpoints. In an earlier study [W. van Ketel, Phys. Rev. Lett. 94, 135703 (2005)] we showed that this model has the structural properties of an ideal gas, yet the dynamical properties of a strong glass former. In the present paper we report an extensive study of the dynamical heterogeneities that appear in this system in the regime where glassy behavior sets in. On the one hand, we find that the propensity of a particle to diffuse is determined by the structure of its local environment. The local density around mobile particles is significantly less than the average density, but there is little clustering of mobile particles, and the clusters observed tend to be small. On the other hand, dynamical susceptibility results indicate that a large dynamical length scale develops even at moderate densities. This suggests that propensity and other mobility measures are an incomplete measure of the dynamical length scales in this system.

Critical Behaviors in Contagion Dynamics.

PubMed

Böttcher, L; Nagler, J; Herrmann, H J

2017-02-24

We study the critical behavior of a general contagion model where nodes are either active (e.g., with opinion A, or functioning) or inactive (e.g., with opinion B, or damaged). The transitions between these two states are determined by (i) spontaneous transitions independent of the neighborhood, (ii) transitions induced by neighboring nodes, and (iii) spontaneous reverse transitions. The resulting dynamics is extremely rich including limit cycles and random phase switching. We derive a unifying mean-field theory. Specifically, we analytically show that the critical behavior of systems whose dynamics is governed by processes (i)-(iii) can only exhibit three distinct regimes: (a) uncorrelated spontaneous transition dynamics, (b) contact process dynamics, and (c) cusp catastrophes. This ends a long-standing debate on the universality classes of complex contagion dynamics in mean field and substantially deepens its mathematical understanding.

Regulation of behavioral plasticity by systemic temperature signaling in Caenorhabditis elegans.

PubMed

Sugi, Takuma; Nishida, Yukuo; Mori, Ikue

2011-06-26

Animals cope with environmental changes by altering behavioral strategy. Environmental information is generally received by sensory neurons in the neural circuit that generates behavior. However, although environmental temperature inevitably influences an animal's entire body, the mechanism of systemic temperature perception remains largely unknown. We show here that systemic temperature signaling induces a change in a memory-based behavior in C. elegans. During behavioral conditioning, non-neuronal cells as well as neuronal cells respond to cultivation temperature through a heat-shock transcription factor that drives newly identified gene expression dynamics. This systemic temperature signaling regulates thermosensory neurons non-cell-autonomously through the estrogen signaling pathway, producing thermotactic behavior. We provide a link between systemic environmental recognition and behavioral plasticity in the nervous system.

Dynamic analysis of a geared rotor system considering a slant crack on the shaft

NASA Astrophysics Data System (ADS)

Han, Qinkai; Zhao, Jingshan; Chu, Fulei

2012-12-01

The vibration problems associated with geared systems have been the focus of research in recent years. As the torque is mainly transmitted by the geared system, a slant crack is more likely to appear on the gear shaft. Due to the slant crack and its breathing mechanism, the dynamic behavior of cracked geared system would differ distinctly with that of uncracked system. Relatively less work is reported on slant crack in the geared rotor system during the past research. Thus, the dynamic analysis of a geared rotor-bearing system with a breathing slant crack is performed in the paper. The finite element model of a geared rotor with slant crack is presented. Based on fracture mechanics, the flexibility matrix for the slant crack is derived that accounts for the additional stress intensity factors. Three methods for whirling analysis, parametric instability analysis and steady-state response analysis are introduced. Then, by taking a widely used one-stage geared rotor-bearing system as an example, the whirling frequencies of the equivalent time-invariant system, two types of instability regions and steady-state response under the excitations of unbalance forces and tooth transmission errors, are computed numerically. The effects of crack depth, position and type (transverse or slant) on the system dynamic behaviors are considered in the discussion. The comparative study with slant cracked geared rotor is carried out to explore distinctive features in their modal, parametric instability and frequency response behaviors.

Generating self-organizing collective behavior using separation dynamics from experimental data

NASA Astrophysics Data System (ADS)

Dieck Kattas, Graciano; Xu, Xiao-Ke; Small, Michael

2012-09-01

Mathematical models for systems of interacting agents using simple local rules have been proposed and shown to exhibit emergent swarming behavior. Most of these models are constructed by intuition or manual observations of real phenomena, and later tuned or verified to simulate desired dynamics. In contrast to this approach, we propose using a model that attempts to follow an averaged rule of the essential distance-dependent collective behavior of real pigeon flocks, which was abstracted from experimental data. By using a simple model to follow the behavioral tendencies of real data, we show that our model can exhibit a wide range of emergent self-organizing dynamics such as flocking, pattern formation, and counter-rotating vortices.

Generating self-organizing collective behavior using separation dynamics from experimental data.

PubMed

Dieck Kattas, Graciano; Xu, Xiao-Ke; Small, Michael

2012-09-01

Mathematical models for systems of interacting agents using simple local rules have been proposed and shown to exhibit emergent swarming behavior. Most of these models are constructed by intuition or manual observations of real phenomena, and later tuned or verified to simulate desired dynamics. In contrast to this approach, we propose using a model that attempts to follow an averaged rule of the essential distance-dependent collective behavior of real pigeon flocks, which was abstracted from experimental data. By using a simple model to follow the behavioral tendencies of real data, we show that our model can exhibit a wide range of emergent self-organizing dynamics such as flocking, pattern formation, and counter-rotating vortices.

Empirical analysis of individual popularity and activity on an online music service system

NASA Astrophysics Data System (ADS)

Hu, Hai-Bo; Han, Ding-Yi

2008-10-01

Quantitative understanding of human behaviors supplies basic comprehension of the dynamics of many socio-economic systems. Based on the log data of an online music service system, we investigate the statistical characteristics of individual activity and popularity, and find that the distributions of both of them follow a stretched exponential form which interpolates between exponential and power law distribution. We also study the human dynamics on the online system and find that the distribution of interevent time between two consecutive listenings of music shows the fat tail feature. Besides, with the reduction of user activity the fat tail becomes more and more irregular, indicating different behavior patterns for users with diverse activities. The research results may shed some light on the in-depth understanding of collective behaviors in socio-economic systems.

Undecidability and Irreducibility Conditions for Open-Ended Evolution and Emergence.

PubMed

Hernández-Orozco, Santiago; Hernández-Quiroz, Francisco; Zenil, Hector

2018-01-01

Is undecidability a requirement for open-ended evolution (OEE)? Using methods derived from algorithmic complexity theory, we propose robust computational definitions of open-ended evolution and the adaptability of computable dynamical systems. Within this framework, we show that decidability imposes absolute limits on the stable growth of complexity in computable dynamical systems. Conversely, systems that exhibit (strong) open-ended evolution must be undecidable, establishing undecidability as a requirement for such systems. Complexity is assessed in terms of three measures: sophistication, coarse sophistication, and busy beaver logical depth. These three complexity measures assign low complexity values to random (incompressible) objects. As time grows, the stated complexity measures allow for the existence of complex states during the evolution of a computable dynamical system. We show, however, that finding these states involves undecidable computations. We conjecture that for similar complexity measures that assign low complexity values, decidability imposes comparable limits on the stable growth of complexity, and that such behavior is necessary for nontrivial evolutionary systems. We show that the undecidability of adapted states imposes novel and unpredictable behavior on the individuals or populations being modeled. Such behavior is irreducible. Finally, we offer an example of a system, first proposed by Chaitin, that exhibits strong OEE.

Dynamical aspects of behavior generation under constraints

PubMed Central

Harter, Derek; Achunala, Srinivas

2007-01-01

Dynamic adaptation is a key feature of brains helping to maintain the quality of their performance in the face of increasingly difficult constraints. How to achieve high-quality performance under demanding real-time conditions is an important question in the study of cognitive behaviors. Animals and humans are embedded in and constrained by their environments. Our goal is to improve the understanding of the dynamics of the interacting brain–environment system by studying human behaviors when completing constrained tasks and by modeling the observed behavior. In this article we present results of experiments with humans performing tasks on the computer under variable time and resource constraints. We compare various models of behavior generation in order to describe the observed human performance. Finally we speculate on mechanisms how chaotic neurodynamics can contribute to the generation of flexible human behaviors under constraints. PMID:19003514

Coupled disease-behavior dynamics on complex networks: A review

NASA Astrophysics Data System (ADS)

Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

The Next Generation of High-Speed Dynamic Stability Wind Tunnel Testing (Invited)

NASA Technical Reports Server (NTRS)

Tomek, Deborah M.; Sewall, William G.; Mason, Stan E.; Szchur, Bill W. A.

2006-01-01

Throughout industry, accurate measurement and modeling of dynamic derivative data at high-speed conditions has been an ongoing challenge. The expansion of flight envelopes and non-conventional vehicle design has greatly increased the demand for accurate prediction and modeling of vehicle dynamic behavior. With these issues in mind, NASA Langley Research Center (LaRC) embarked on the development and shakedown of a high-speed dynamic stability test technique that addresses the longstanding problem of accurately measuring dynamic derivatives outside the low-speed regime. The new test technique was built upon legacy technology, replacing an antiquated forced oscillation system, and greatly expanding the capabilities beyond classic forced oscillation testing at both low and high speeds. The modern system is capable of providing a snapshot of dynamic behavior over a periodic cycle for varying frequencies, not just a damping derivative term at a single frequency.

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Snowflakes, Living Systems, and the Mystery of Giftedness

ERIC Educational Resources Information Center

Dai, David Yun; Renzulli, Joseph S.

2008-01-01

The main argument of this article is that human living systems are open, dynamic, intentional systems and, therefore, are capable of building ever more complex behaviors through self-organization and self-direction. This principle underlying general human development is also applicable to the development of gifted and talented behaviors. These…

Assessing sustainability in real urban systems: the Greater Cincinnati Metropolitan Area in Ohio, Kentucky, and Indiana.

PubMed

Gonzalez-Mejía, Alejandra M; Eason, Tarsha N; Cabezas, Heriberto; Suidan, Makram T

2012-09-04

Urban systems have a number of factors (i.e., economic, social, and environmental) that can potentially impact growth, change, and transition. As such, assessing and managing these systems is a complex challenge. While, tracking trends of key variables may provide some insight, identifying the critical characteristics that truly impact the dynamic behavior of these systems is difficult. As an integrated approach to evaluate real urban systems, this work contributes to the research on scientific techniques for assessing sustainability. Specifically, it proposes a practical methodology based on the estimation of dynamic order, for identifying stable and unstable periods of sustainable or unsustainable trends with Fisher Information (FI) metric. As a test case, the dynamic behavior of the City, Suburbs, and Metropolitan Statistical Area (MSA) of Cincinnati was evaluated by using 29 social and 11 economic variables to characterize each system from 1970 to 2009. Air quality variables were also selected to describe the MSA's environmental component (1980-2009). Results indicate systems dynamic started to change from about 1995 for the social variables and about 2000 for the economic and environmental characteristics.

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

Trivial dynamics in discrete-time systems: carrying simplex and translation arcs

NASA Astrophysics Data System (ADS)

Niu, Lei; Ruiz-Herrera, Alfonso

2018-06-01

In this paper we show that the dynamical behavior in (first octant) of the classical Kolmogorov systems of competitive type admitting a carrying simplex can be sometimes determined completely by the number of fixed points on the boundary and the local behavior around them. Roughly speaking, T has trivial dynamics (i.e. the omega limit set of any orbit is a connected set contained in the set of fixed points) provided T has exactly four hyperbolic nontrivial fixed points in with local attractors on the carrying simplex and local repellers on the carrying simplex; and there exists a unique hyperbolic fixed point in Int. Our results are applied to some classical models including the Leslie–Gower models, Atkinson-Allen systems and Ricker maps.

Computational Methods for Nonlinear Dynamic Problems in Solid and Structural Mechanics: Progress in the Theory and Modeling of Friction and in the Control of Dynamical Systems with Frictional Forces

DTIC Science & Technology

1989-03-31

present several numerical studies designed to reveal the effect that some of the governing parameters have on the behavior of the system and, whenever...Friction and in the Control of Dynamical Systems with Frictional Forces FINAL TECHNICAL REPORT March 31, 1989 _ -- I -.7: .-.- - : AFOSR Contract F49620...SOLID AND STRUCTURAL MECHANICS: Progress in the Theory and Modeling of Friction and in the Control of Dynamical Systems with Frictional Forces I I * FINAL

Joint action syntax in Japanese martial arts.

PubMed

Yamamoto, Yuji; Yokoyama, Keiko; Okumura, Motoki; Kijima, Akifumi; Kadota, Koji; Gohara, Kazutoshi

2013-01-01

Participation in interpersonal competitions, such as fencing or Japanese martial arts, requires players to make instantaneous decisions and execute appropriate motor behaviors in response to various situations. Such actions can be understood as complex phenomena emerging from simple principles. We examined the intentional switching dynamics associated with continuous movement during interpersonal competition in terms of their emergence from a simple syntax. Linear functions on return maps identified two attractors as well as the transitions between them. The effects of skill differences were evident in the second- and third-order state-transition diagrams for these two attractors. Our results suggest that abrupt switching between attractors is related to the diverse continuous movements resulting from quick responses to sudden changes in the environment. This abrupt-switching-quick-response behavior is characterized by a joint action syntax. The resulting hybrid dynamical system is composed of a higher module with discrete dynamics and a lower module with continuous dynamics. Our results suggest that intelligent human behavior and robust autonomy in real-life scenarios are based on this hybrid dynamical system, which connects interpersonal coordination and competition.

Relevance of deterministic chaos theory to studies in functioning of dynamical systems

NASA Astrophysics Data System (ADS)

Glagolev, S. N.; Bukhonova, S. M.; Chikina, E. D.

2018-03-01

The paper considers chaotic behavior of dynamical systems typical for social and economic processes. Approaches to analysis and evaluation of system development processes are studies from the point of view of controllability and determinateness. Explanations are given for necessity to apply non-standard mathematical tools to explain states of dynamical social and economic systems on the basis of fractal theory. Features of fractal structures, such as non-regularity, self-similarity, dimensionality and fractionality are considered.

Nonlinear Dynamics of a Multistage Gear Transmission System with Multi-Clearance

NASA Astrophysics Data System (ADS)

Xiang, Ling; Zhang, Yue; Gao, Nan; Hu, Aijun; Xing, Jingtang

The nonlinear torsional model of a multistage gear transmission system which consists of a planetary gear and two parallel gear stages is established with time-varying meshing stiffness, comprehensive gear error and multi-clearance. The nonlinear dynamic responses are analyzed by applying the reference of backlash bifurcation parameters. The motions of the system on the change of backlash are identified through global bifurcation diagram, largest Lyapunov exponent (LLE), FFT spectra, Poincaré maps, the phase diagrams and time series. The numerical results demonstrate that the system exhibits rich features of nonlinear dynamics such as the periodic motion, nonperiodic states and chaotic states. It is found that the sun-planet backlash has more complex effect on the system than the ring-planet backlash. The motions of the system with backlash of parallel gear are diverse including some different multi-periodic motions. Furthermore, the state of the system can change from chaos into quasi-periodic behavior, which means that the dynamic behavior of the system is composed of more stable components with the increase of the backlash. Correspondingly, the parameters of the system should be designed properly and controlled timely for better operation and enhancing the life of the system.

Glasslike dynamical behavior of the plastocyanin hydration water

NASA Astrophysics Data System (ADS)

Bizzarri, Anna Rita; Paciaroni, Alessandro; Cannistraro, Salvatore

2000-09-01

The dynamical behavior of water around plastocyanin has been investigated in a wide temperature range by molecular dynamics simulation. The mean square displacements of water oxygen atoms show, at long times, a tα trend for all temperatures. Below 150 K, α is constant and equal to 1; at higher temperatures it drops to a value significantly smaller than 1, and thereafter decreases with increasing temperature. The occurrence of such an anomalous diffusion matches the onset of the dynamical transition observed in the protein. The intermediate scattering function of water is characterized, at high temperature, by a stretched exponential decay evolving, at low temperature, toward a two step relaxation behavior, which becomes more evident on increasing the exchanged wave vector q. Both the mean square displacements and the intermediate scattering functions show, beyond the ballistic regime, a plateau, which progressively extends for longer times as long as the temperature is lowered, such behavior reflecting trapping of water molecules within a cage formed by the nearest neighbors. At low temperature, a low frequency broad inelastic peak is observed in the dynamical structure factor of hydration water; such an excess of vibrational modes being reminiscent of the boson peak, characteristic of disordered, amorphous systems. All these features, which are typical of complex systems, can be traced back to the glassy character of the hydration water and suggest a dynamical coupling occurring at the macromolecule-solvent interface.

Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors.

PubMed

Perez-Carrasco, Ruben; Barnes, Chris P; Schaerli, Yolanda; Isalan, Mark; Briscoe, James; Page, Karen M

2018-04-25

Although the structure of a genetically encoded regulatory circuit is an important determinant of its function, the relationship between circuit topology and the dynamical behaviors it can exhibit is not well understood. Here, we explore the range of behaviors available to the AC-DC circuit. This circuit consists of three genes connected as a combination of a toggle switch and a repressilator. Using dynamical systems theory, we show that the AC-DC circuit exhibits both oscillations and bistability within the same region of parameter space; this generates emergent behaviors not available to either the toggle switch or the repressilator alone. The AC-DC circuit can switch on oscillations via two distinct mechanisms, one of which induces coherence into ensembles of oscillators. In addition, we show that in the presence of noise, the AC-DC circuit can behave as an excitable system capable of spatial signal propagation or coherence resonance. Together, these results demonstrate how combinations of simple motifs can exhibit multiple complex behaviors. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

A nonlinear dynamics of trunk kinematics during manual lifting tasks.

PubMed

Khalaf, Tamer; Karwowski, Waldemar; Sapkota, Nabin

2015-01-01

Human responses at work may exhibit nonlinear properties where small changes in the initial task conditions can lead to large changes in system behavior. Therefore, it is important to study such nonlinearity to gain a better understanding of human performance under a variety of physical, perceptual, and cognitive tasks conditions. The main objective of this study was to investigate whether the human trunk kinematics data during a manual lifting task exhibits nonlinear behavior in terms of determinist chaos. Data related to kinematics of the trunk with respect to the pelvis were collected using Industrial Lumbar Motion Monitor (ILMM), and analyzed applying the nonlinear dynamical systems methodology. Nonlinear dynamics quantifiers of Lyapunov exponents and Kaplan-Yorke dimensions were calculated and analyzed under different task conditions. The study showed that human trunk kinematics during manual lifting exhibits chaotic behavior in terms of trunk sagittal angular displacement, velocity and acceleration. The findings support the importance of accounting for nonlinear dynamical properties of biomechanical responses to lifting tasks.

The resonant system: Linking brain-body-environment in sport performance☆.

PubMed

Teques, Pedro; Araújo, Duarte; Seifert, Ludovic; Del Campo, Vicente L; Davids, Keith

2017-01-01

The ecological dynamics approach offers new insights to understand how athlete nervous systems are embedded within the body-environment system in sport. Cognitive neuroscience focuses on the neural bases of athlete behaviors in terms of perceptual, cognitive, and motor functions defined within specific brain structures. Here, we discuss some limitations of this traditional perspective, addressing how athletes functionally adapt perception and action to the dynamics of complex performance environments by continuously perceiving information to regulate goal-directed actions. We examine how recent neurophysiological evidence of functioning in diverse cortical and subcortical regions appears more compatible with an ecological dynamics perspective, than traditional views in cognitive neuroscience. We propose how athlete behaviors in sports may be related to the tuning of resonant mechanisms indicating that perception is a dynamic process involving the whole body of the athlete. We emphasize the important role of metastable dynamics in the brain-body-environment system facilitating continuous interactions with a landscape of affordances (opportunities for action) in a performance environment. We discuss implications of these ideas for performance preparation and practice design in sport. © 2017 Elsevier B.V. All rights reserved.

A New Real - Time Fault Detection Methodology for Systems Under Test. Phase 1

NASA Technical Reports Server (NTRS)

Johnson, Roger W.; Jayaram, Sanjay; Hull, Richard A.

1998-01-01

The purpose of this research is focussed on the identification/demonstration of critical technology innovations that will be applied to various applications viz. Detection of automated machine Health Monitoring (BM, real-time data analysis and control of Systems Under Test (SUT). This new innovation using a High Fidelity Dynamic Model-based Simulation (BFDMS) approach will be used to implement a real-time monitoring, Test and Evaluation (T&E) methodology including the transient behavior of the system under test. The unique element of this process control technique is the use of high fidelity, computer generated dynamic models to replicate the behavior of actual Systems Under Test (SUT). It will provide a dynamic simulation capability that becomes the reference truth model, from which comparisons are made with the actual raw/conditioned data from the test elements.

Adaptive functional systems: learning with chaos.

PubMed

Komarov, M A; Osipov, G V; Burtsev, M S

2010-12-01

We propose a new model of adaptive behavior that combines a winnerless competition principle and chaos to learn new functional systems. The model consists of a complex network of nonlinear dynamical elements producing sequences of goal-directed actions. Each element describes dynamics and activity of the functional system which is supposed to be a distributed set of interacting physiological elements such as nerve or muscle that cooperates to obtain certain goal at the level of the whole organism. During "normal" behavior, the dynamics of the system follows heteroclinic channels, but in the novel situation chaotic search is activated and a new channel leading to the target state is gradually created simulating the process of learning. The model was tested in single and multigoal environments and had demonstrated a good potential for generation of new adaptations. © 2010 American Institute of Physics.

Carrier dynamics and recombination mechanisms in staggered-alignment heterostructures

NASA Astrophysics Data System (ADS)

Wilson, Barbara A.

1988-08-01

The experimental and theoretical work on carrier dynamics and recombination mechanisms in semiconductor heterostructures with staggered type II alignments is reviewed. Examples from the literature are discussed for each of the III-V, II-VI, and IV-VI systems, as well as cross-column examples, with a focus on AlGaAs structures. The key optical properties which have benn identified as signatures of staggered-alignment behavior are summarized. A discussion of other epitaxial systems likely to exhibit staggered lineups is presented, and additional experimental and theoretical work is suggested, which could increase understanding of staggered-system behavior.

Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

PubMed Central

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting. PMID:25826692

Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics.

PubMed

Dong, Xianlei; Bollen, Johan

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.

A control systems engineering approach for adaptive behavioral interventions: illustration with a fibromyalgia intervention.

PubMed

Deshpande, Sunil; Rivera, Daniel E; Younger, Jarred W; Nandola, Naresh N

2014-09-01

The term adaptive intervention has been used in behavioral medicine to describe operationalized and individually tailored strategies for prevention and treatment of chronic, relapsing disorders. Control systems engineering offers an attractive means for designing and implementing adaptive behavioral interventions that feature intensive measurement and frequent decision-making over time. This is illustrated in this paper for the case of a low-dose naltrexone treatment intervention for fibromyalgia. System identification methods from engineering are used to estimate dynamical models from daily diary reports completed by participants. These dynamical models then form part of a model predictive control algorithm which systematically decides on treatment dosages based on measurements obtained under real-life conditions involving noise, disturbances, and uncertainty. The effectiveness and implications of this approach for behavioral interventions (in general) and pain treatment (in particular) are demonstrated using informative simulations.

A multi-stakeholder framework for sustainable energy behavior: A multidisciplinary systems study

NASA Astrophysics Data System (ADS)

Khansari, Nasrin

Growth of population and moving towards over-consumption and over-pollution are significant threats to the environment and therefore necessitate moving towards sustainability approaches. CO2 emissions are considered to be the main basis of the incredible increase in the earth's surface temperature in recent years. Most emissions result from human activities. Thus, developing a detailed framework representing the parameters affecting individuals' energy behaviors is required. This dissertation offers an integrated conceptual framework to increase the efficiency of energy systems under complex and uncertainty conditions, facilitate energy consumption problem solving, and support the development of capacities at the individual, social, and technical levels to improve managing energy consumptions in the future. This research presents a conceptual soft systems model to explore the process of individuals' energy behavior change based on socio-structural and techno-structural contexts. In addition, a comprehensive model based on systems dynamics principles is presented to address the issue of CO2 emissions related to the households' energy consumption behavior. The proposed systems dynamics model provides a broad overview of the key agents affecting energy consumption, including government/public sector, households, and power industry. The model is created based on the research in the literature discussing the causal relations between various variables. The proposed systems dynamics model is verified by simulating different scenarios. In this research a survey is designed and conducted to investigate the role of individual, social and technical behaviors in reducing energy consumption, energy costs and carbon footprints based on the energy use profile. In sum, this study investigates the process of energy behavior change based on socio-structural and techno-structural contexts.

Dynamics of a Tapped Granular Column

NASA Astrophysics Data System (ADS)

Rosato, Anthony; Blackmore, Denis; Zuo, Luo; Hao, Wu; Horntrop, David

2015-11-01

We consider the behavior of a column of spheres subjected to a time-dependent vertical taps. Of interest are various dynamical properties, such as the motion of its mass center, its response to taps of different intensities and forms, and the effect of system size and material properties. The interplay between diverse time and length scales are the key contributors to the column's evolving dynamics. Soft sphere discrete element simulations were conducted over a very wide parameter space to obtain a portrait of column behavior as embodied by the collective dynamics of the mass center motion. Results compared favorably with a derived reduced-order paradigm of the mass center motion (surprisingly analogous to that for a single bouncing ball on an oscillating plate) with respect to dynamical regimes and their transitions. A continuum model obtained from a system of Newtonian equations, as a locally averaged limit in the transport mode along trajectories is described, and a numerical solution protocol for a one-dimensional system is outlined. Typical trajectories and density evolution profiles are shown. We conclude with a discussion of our investigations to relate predictions of the continuum and reduced dynamical systems models with discrete simulations.

Dynamical Analysis and Visualization of Tornadoes Time Series

PubMed Central

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns. PMID:25790281

Dynamical analysis and visualization of tornadoes time series.

PubMed

Lopes, António M; Tenreiro Machado, J A

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Dynamical behaviors determined by the Lyapunov function in competitive Lotka-Volterra systems.

PubMed

Tang, Ying; Yuan, Ruoshi; Ma, Yian

2013-01-01

Dynamical behaviors of the competitive Lotka-Volterra system even for 3 species are not fully understood. In this paper, we study this problem from the perspective of the Lyapunov function. We construct explicitly the Lyapunov function using three examples of the competitive Lotka-Volterra system for the whole state space: (1) the general 2-species case, (2) a 3-species model, and (3) the model of May-Leonard. The basins of attraction for these examples are demonstrated, including cases with bistability and cyclical behavior. The first two examples are the generalized gradient system, where the energy dissipation may not follow the gradient of the Lyapunov function. In addition, under a new type of stochastic interpretation, the Lyapunov function also leads to the Boltzmann-Gibbs distribution on the final steady state when multiplicative noise is added.

Dynamical behaviors determined by the Lyapunov function in competitive Lotka-Volterra systems

NASA Astrophysics Data System (ADS)

Tang, Ying; Yuan, Ruoshi; Ma, Yian

2013-01-01

Dynamical behaviors of the competitive Lotka-Volterra system even for 3 species are not fully understood. In this paper, we study this problem from the perspective of the Lyapunov function. We construct explicitly the Lyapunov function using three examples of the competitive Lotka-Volterra system for the whole state space: (1) the general 2-species case, (2) a 3-species model, and (3) the model of May-Leonard. The basins of attraction for these examples are demonstrated, including cases with bistability and cyclical behavior. The first two examples are the generalized gradient system, where the energy dissipation may not follow the gradient of the Lyapunov function. In addition, under a new type of stochastic interpretation, the Lyapunov function also leads to the Boltzmann-Gibbs distribution on the final steady state when multiplicative noise is added.

A Huygens principle for diffusion and anomalous diffusion in spatially extended systems

PubMed Central

Gottwald, Georg A.; Melbourne, Ian

2013-01-01

We present a universal view on diffusive behavior in chaotic spatially extended systems for anisotropic and isotropic media. For anisotropic systems, strong chaos leads to diffusive behavior (Brownian motion with drift) and weak chaos leads to superdiffusive behavior (Lévy processes with drift). For isotropic systems, the drift term vanishes and strong chaos again leads to Brownian motion. We establish the existence of a nonlinear Huygens principle for weakly chaotic systems in isotropic media whereby the dynamics behaves diffusively in even space dimension and exhibits superdiffusive behavior in odd space dimensions. PMID:23653481

Salience network dynamics underlying successful resistance of temptation

PubMed Central

Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q

2017-01-01

Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582

Linking brain, mind and behavior.

PubMed

Makeig, Scott; Gramann, Klaus; Jung, Tzyy-Ping; Sejnowski, Terrence J; Poizner, Howard

2009-08-01

Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.

Detection of Structural Abnormalities Using Neural Nets

NASA Technical Reports Server (NTRS)

Zak, M.; Maccalla, A.; Daggumati, V.; Gulati, S.; Toomarian, N.

1996-01-01

This paper describes a feed-forward neural net approach for detection of abnormal system behavior based upon sensor data analyses. A new dynamical invariant representing structural parameters of the system is introduced in such a way that any structural abnormalities in the system behavior are detected from the corresponding changes to the invariant.

Relaxation mechanisms in glassy dynamics: the Arrhenius and fragile regimes.

PubMed

Hentschel, H George E; Karmakar, Smarajit; Procaccia, Itamar; Zylberg, Jacques

2012-06-01

Generic glass formers exhibit at least two characteristic changes in their relaxation behavior, first to an Arrhenius-type relaxation at some characteristic temperature and then at a lower characteristic temperature to a super-Arrhenius (fragile) behavior. We address these transitions by studying the statistics of free energy barriers for different systems at different temperatures and space dimensions. We present a clear evidence for changes in the dynamical behavior at the transition to Arrhenius and then to a super-Arrhenius behavior. A simple model is presented, based on the idea of competition between single-particle and cooperative dynamics. We argue that Arrhenius behavior can take place as long as there is enough free volume for the completion of a simple T1 relaxation process. Once free volume is absent one needs a cooperative mechanism to "collect" enough free volume. We show that this model captures all the qualitative behavior observed in simulations throughout the considered temperature range.

Automated adaptive inference of phenomenological dynamical models

NASA Astrophysics Data System (ADS)

Daniels, Bryan

Understanding the dynamics of biochemical systems can seem impossibly complicated at the microscopic level: detailed properties of every molecular species, including those that have not yet been discovered, could be important for producing macroscopic behavior. The profusion of data in this area has raised the hope that microscopic dynamics might be recovered in an automated search over possible models, yet the combinatorial growth of this space has limited these techniques to systems that contain only a few interacting species. We take a different approach inspired by coarse-grained, phenomenological models in physics. Akin to a Taylor series producing Hooke's Law, forgoing microscopic accuracy allows us to constrain the search over dynamical models to a single dimension. This makes it feasible to infer dynamics with very limited data, including cases in which important dynamical variables are unobserved. We name our method Sir Isaac after its ability to infer the dynamical structure of the law of gravitation given simulated planetary motion data. Applying the method to output from a microscopically complicated but macroscopically simple biological signaling model, it is able to adapt the level of detail to the amount of available data. Finally, using nematode behavioral time series data, the method discovers an effective switch between behavioral attractors after the application of a painful stimulus.

Coordination dynamics in a socially situated nervous system

PubMed Central

Coey, Charles A.; Varlet, Manuel; Richardson, Michael J.

2012-01-01

Traditional theories of cognitive science have typically accounted for the organization of human behavior by detailing requisite computational/representational functions and identifying neurological mechanisms that might perform these functions. Put simply, such approaches hold that neural activity causes behavior. This same general framework has been extended to accounts of human social behavior via concepts such as “common-coding” and “co-representation” and much recent neurological research has been devoted to brain structures that might execute these social-cognitive functions. Although these neural processes are unquestionably involved in the organization and control of human social interactions, there is good reason to question whether they should be accorded explanatory primacy. Alternatively, we propose that a full appreciation of the role of neural processes in social interactions requires appropriately situating them in their context of embodied-embedded constraints. To this end, we introduce concepts from dynamical systems theory and review research demonstrating that the organization of human behavior, including social behavior, can be accounted for in terms of self-organizing processes and lawful dynamics of animal-environment systems. Ultimately, we hope that these alternative concepts can complement the recent advances in cognitive neuroscience and thereby provide opportunities to develop a complete and coherent account of human social interaction. PMID:22701413

An Agent-Based Model for Analyzing Control Policies and the Dynamic Service-Time Performance of a Capacity-Constrained Air Traffic Management Facility

NASA Technical Reports Server (NTRS)

Conway, Sheila R.

2006-01-01

Simple agent-based models may be useful for investigating air traffic control strategies as a precursory screening for more costly, higher fidelity simulation. Of concern is the ability of the models to capture the essence of the system and provide insight into system behavior in a timely manner and without breaking the bank. The method is put to the test with the development of a model to address situations where capacity is overburdened and potential for propagation of the resultant delay though later flights is possible via flight dependencies. The resultant model includes primitive representations of principal air traffic system attributes, namely system capacity, demand, airline schedules and strategy, and aircraft capability. It affords a venue to explore their interdependence in a time-dependent, dynamic system simulation. The scope of the research question and the carefully-chosen modeling fidelity did allow for the development of an agent-based model in short order. The model predicted non-linear behavior given certain initial conditions and system control strategies. Additionally, a combination of the model and dimensionless techniques borrowed from fluid systems was demonstrated that can predict the system s dynamic behavior across a wide range of parametric settings.

Collective Behavior of Camphor Floats Migrating on the Water Surface

NASA Astrophysics Data System (ADS)

Nishimori, Hiraku; Suematsu, Nobuhiko J.; Nakata, Satoshi

2017-10-01

As simple and easily controllable objects among various self-propelled particles, camphor floats on the water surface have been widely recognized. In this paper, we introduce characteristic behaviors and discuss the background mechanism of camphor floats on water, both in isolated and non-isolated conditions. In particular, we focus on: (i) the transition of dynamical characters through bifurcations exhibited by systems with small number of camphor floats and (ii) the emergence of a rich variety of complex dynamics observed in systems with large number camphor floats, and attempt to elucidate these phenomena through mathematical modeling as well as experimental analysis. Finally, we discuss the connection of the dynamics of camphor floats to that of a wider class of complex and sophisticated dynamics exhibited by various types of self-propelled particles.

Bifurcation and response analysis of a nonlinear flexible rotating disc immersed in bounded compressible fluid

NASA Astrophysics Data System (ADS)

Remigius, W. Dheelibun; Sarkar, Sunetra; Gupta, Sayan

2017-03-01

Use of heavy gases in centrifugal compressors for enhanced oil extraction have made the impellers susceptible to failures through acousto-elastic instabilities. This study focusses on understanding the dynamical behavior of such systems by considering the effects of the bounded fluid housed in a casing on a rotating disc. First, a mathematical model is developed that incorporates the interaction between the rotating impeller - modelled as a flexible disc - and the bounded compressible fluid medium in which it is immersed. The nonlinear effects arising due to large deformations of the disc have been included in the formulation so as to capture the post flutter behavior. A bifurcation analysis is carried out with the disc rotational speed as the bifurcation parameter to investigate the dynamical behavior of the coupled system and estimate the stability boundaries. Parametric studies reveal that the relative strengths of the various dissipation mechanisms in the coupled system play a significant role that affect the bifurcation route and the post flutter behavior in the acousto-elastic system.

Symmetry analysis for hyperbolic equilibria using a TB/dengue fever model

NASA Astrophysics Data System (ADS)

Massoukou, R. Y. M.'Pika; Govinder, K. S.

2016-08-01

We investigate the interplay between Lie symmetry analysis and dynamical systems analysis. As an example, we take a toy model describing the spread of TB and dengue fever. We first undertake a comprehensive dynamical systems analysis including a discussion about local stability. For those regions in which such analyzes cannot be translated to global behavior, we undertake a Lie symmetry analysis. It is shown that the Lie analysis can be useful in providing information for systems where the (local) dynamical systems analysis breaks down.

Vision-based navigation in a dynamic environment for virtual human

NASA Astrophysics Data System (ADS)

Liu, Yan; Sun, Ji-Zhou; Zhang, Jia-Wan; Li, Ming-Chu

2004-06-01

Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.

Modeling Common-Sense Decisions

NASA Astrophysics Data System (ADS)

Zak, Michail

This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

Vehicle dynamic analysis using neuronal network algorithms

NASA Astrophysics Data System (ADS)

Oloeriu, Florin; Mocian, Oana

2014-06-01

Theoretical developments of certain engineering areas, the emergence of new investigation tools, which are better and more precise and their implementation on-board the everyday vehicles, all these represent main influence factors that impact the theoretical and experimental study of vehicle's dynamic behavior. Once the implementation of these new technologies onto the vehicle's construction had been achieved, it had led to more and more complex systems. Some of the most important, such as the electronic control of engine, transmission, suspension, steering, braking and traction had a positive impact onto the vehicle's dynamic behavior. The existence of CPU on-board vehicles allows data acquisition and storage and it leads to a more accurate and better experimental and theoretical study of vehicle dynamics. It uses the information offered directly by the already on-board built-in elements of electronic control systems. The technical literature that studies vehicle dynamics is entirely focused onto parametric analysis. This kind of approach adopts two simplifying assumptions. Functional parameters obey certain distribution laws, which are known in classical statistics theory. The second assumption states that the mathematical models are previously known and have coefficients that are not time-dependent. Both the mentioned assumptions are not confirmed in real situations: the functional parameters do not follow any known statistical repartition laws and the mathematical laws aren't previously known and contain families of parameters and are mostly time-dependent. The purpose of the paper is to present a more accurate analysis methodology that can be applied when studying vehicle's dynamic behavior. A method that provides the setting of non-parametrical mathematical models for vehicle's dynamic behavior is relying on neuronal networks. This method contains coefficients that are time-dependent. Neuronal networks are mostly used in various types' system controls, thus being a non-linear process identification algorithm. The common use of neuronal networks for non-linear processes is justified by the fact that both have the ability to organize by themselves. That is why the neuronal networks best define intelligent systems, thus the word `neuronal' is sending one's mind to the biological neuron cell. The paper presents how to better interpret data fed from the on-board computer and a new way of processing that data to better model the real life dynamic behavior of the vehicle.

A Mathematical Framework for the Complex System Approach to Group Dynamics: The Case of Recovery House Social Integration.

PubMed

Light, John M; Jason, Leonard A; Stevens, Edward B; Callahan, Sarah; Stone, Ariel

2016-03-01

The complex system conception of group social dynamics often involves not only changing individual characteristics, but also changing within-group relationships. Recent advances in stochastic dynamic network modeling allow these interdependencies to be modeled from data. This methodology is discussed within a context of other mathematical and statistical approaches that have been or could be applied to study the temporal evolution of relationships and behaviors within small- to medium-sized groups. An example model is presented, based on a pilot study of five Oxford House recovery homes, sober living environments for individuals following release from acute substance abuse treatment. This model demonstrates how dynamic network modeling can be applied to such systems, examines and discusses several options for pooling, and shows how results are interpreted in line with complex system concepts. Results suggest that this approach (a) is a credible modeling framework for studying group dynamics even with limited data, (b) improves upon the most common alternatives, and (c) is especially well-suited to complex system conceptions. Continuing improvements in stochastic models and associated software may finally lead to mainstream use of these techniques for the study of group dynamics, a shift already occurring in related fields of behavioral science.

Dynamics of macroautophagy: Modeling and oscillatory behavior

NASA Astrophysics Data System (ADS)

Han, Kyungreem; Kwon, Hyun Woong; Kang, Hyuk; Kim, Jinwoong; Lee, Myung-Shik; Choi, M. Y.

2012-02-01

We propose a model for macroautophagy and study the resulting dynamics of autophagy in a system isolated from its extra-cellular environment. It is found that the intracellular concentrations of autophagosomes and autolysosomes display oscillations with their own natural frequencies. Such oscillatory behaviors, which are interrelated to the dynamics of intracellular ATP, amino acids, and proteins, are consistent with the very recent biological observations. Implications of this theoretical study of autophagy are discussed, with regard to the possibility of guiding molecular studies of autophagy.

Coupled disease-behavior dynamics on complex networks: A review.

PubMed

Wang, Zhen; Andrews, Michael A; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years. Copyright © 2015 Elsevier B.V. All rights reserved.

Loners, Groupies, and Long-term Eccentricity (and Inclination) Behavior: Insights from Secular Theory

NASA Astrophysics Data System (ADS)

Van Laerhoven, Christa L.

2015-05-01

Considering the secular dynamics of multi-planet systems provides substantial insight into the interactions between planets in those systems. Secular interactions are those that don't involve knowing where a planet is along its orbit, and they dominate when planets are not involved in mean motion resonances. These interactions exchange angular momentum among the planets, evolving their eccentricities and inclinations. To second order in the planets' eccentricities and inclinations, the eccentricity and inclination perturbations are decoupled. Given the right variable choice, the relevant differential equations are linear and thus the eccentricity and inclination behaviors can be described as a sum of eigenmodes. Since the underlying structure of the secular eigenmodes can be calculated using only the planets' masses and semi-major axes, one can elucidate the eccentricity and inclination behavior of planets in exoplanet systems even without knowing the planets' current eccentricities and inclinations. I have calculated both the eccentricity and inclination secular eigenmodes for the population of known multi-planet systems whose planets have well determined masses and periods. Using this catalog of secular character, I will discuss the prevalence of dynamically grouped planets ('groupies') versus dynamically uncoupled planets ('loners') and how this relates to the exoplanets' long-term eccentricity and inclination behavior. I will also touch on the distribution of the secular eigenfreqiencies.

Capturing complexity in work disability research: application of system dynamics modeling methodology.

PubMed

Jetha, Arif; Pransky, Glenn; Hettinger, Lawrence J

2016-01-01

Work disability (WD) is characterized by variable and occasionally undesirable outcomes. The underlying determinants of WD outcomes include patterns of dynamic relationships among health, personal, organizational and regulatory factors that have been challenging to characterize, and inadequately represented by contemporary WD models. System dynamics modeling (SDM) methodology applies a sociotechnical systems thinking lens to view WD systems as comprising a range of influential factors linked by feedback relationships. SDM can potentially overcome limitations in contemporary WD models by uncovering causal feedback relationships, and conceptualizing dynamic system behaviors. It employs a collaborative and stakeholder-based model building methodology to create a visual depiction of the system as a whole. SDM can also enable researchers to run dynamic simulations to provide evidence of anticipated or unanticipated outcomes that could result from policy and programmatic intervention. SDM may advance rehabilitation research by providing greater insights into the structure and dynamics of WD systems while helping to understand inherent complexity. Challenges related to data availability, determining validity, and the extensive time and technical skill requirements for model building may limit SDM's use in the field and should be considered. Contemporary work disability (WD) models provide limited insight into complexity associated with WD processes. System dynamics modeling (SDM) has the potential to capture complexity through a stakeholder-based approach that generates a simulation model consisting of multiple feedback loops. SDM may enable WD researchers and practitioners to understand the structure and behavior of the WD system as a whole, and inform development of improved strategies to manage straightforward and complex WD cases.

A complex systems analysis of stick-slip dynamics of a laboratory fault

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, David M.; Tordesillas, Antoinette, E-mail: atordesi@unimelb.edu.au; Small, Michael

2014-03-15

We study the stick-slip behavior of a granular bed of photoelastic disks sheared by a rough slider pulled along the surface. Time series of a proxy for granular friction are examined using complex systems methods to characterize the observed stick-slip dynamics of this laboratory fault. Nonlinear surrogate time series methods show that the stick-slip behavior appears more complex than a periodic dynamics description. Phase space embedding methods show that the dynamics can be locally captured within a four to six dimensional subspace. These slider time series also provide an experimental test for recent complex network methods. Phase space networks, constructedmore » by connecting nearby phase space points, proved useful in capturing the key features of the dynamics. In particular, network communities could be associated to slip events and the ranking of small network subgraphs exhibited a heretofore unreported ordering.« less

Physics of Life: A Model for Non-Newtonian Properties of Living Systems

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

This innovation proposes the reconciliation of the evolution of life with the second law of thermodynamics via the introduction of the First Principle for modeling behavior of living systems. The structure of the model is quantum-inspired: it acquires the topology of the Madelung equation in which the quantum potential is replaced with the information potential. As a result, the model captures the most fundamental property of life: the progressive evolution; i.e. the ability to evolve from disorder to order without any external interference. The mathematical structure of the model can be obtained from the Newtonian equations of motion (representing the motor dynamics) coupled with the corresponding Liouville equation (representing the mental dynamics) via information forces. All these specific non-Newtonian properties equip the model with the levels of complexity that matches the complexity of life, and that makes the model applicable for description of behaviors of ecological, social, and economical systems. Rather than addressing the six aspects of life (organization, metabolism, growth, adaptation, response to stimuli, and reproduction), this work focuses only on biosignature ; i.e. the mechanical invariants of life, and in particular, the geometry and kinematics of behavior of living things. Living things obey the First Principles of Newtonian mechanics. One main objective of this model is to extend the First Principles of classical physics to include phenomenological behavior on living systems; to develop a new mathematical formalism within the framework of classical dynamics that would allow one to capture the specific properties of natural or artificial living systems such as formation of the collective mind based upon abstract images of the selves and non-selves; exploitation of this collective mind for communications and predictions of future expected characteristics of evolution; and for making decisions and implementing the corresponding corrections if the expected scenario is different from the originally planned one. This approach postulates that even a primitive living species possesses additional, non-Newtonian properties that are not included in the laws of Newtonian or statistical mechanics. These properties follow from a privileged ability of living systems to possess a self-image (a concept introduced in psychology) and to interact with it. The proposed mathematical system is based on the coupling of the classical dynamical system representing the motor dynamics with the corresponding Liouville equation describing the evolution of initial uncertainties in terms of the probability density and representing the mental dynamics. The coupling is implemented by the information-based supervising forces that can be associated with self-awareness. These forces fundamentally change the pattern of the probability evolution, and therefore, lead to a major departure of the behavior of living systems from the patterns of both Newtonian and statistical mechanics. This innovation is meant to capture the signature of life based only on observable behavior, not on any biochemistry. This will not prevent the use of this model for developing artificial living systems, as well as for studying some general properties of behavior of natural, living systems.

Dynamics of sustained use and abandonment of clean cooking systems: study protocol for community-based system dynamics modeling.

PubMed

Kumar, Praveen; Chalise, Nishesh; Yadama, Gautam N

2016-04-26

More than 3 billion of the world's population are affected by household air pollution from relying on unprocessed solid fuels for heating and cooking. Household air pollution is harmful to human health, climate, and environment. Sustained uptake and use of cleaner cooking technologies and fuels are proposed as solutions to this problem. In this paper, we present our study protocol aimed at understanding multiple interacting feedback mechanisms involved in the dynamic behavior between social, ecological, and technological systems driving sustained use or abandonment of cleaner cooking technologies among the rural poor in India. This study uses a comparative case study design to understand the dynamics of sustained use or abandonment of cleaner cooking technologies and fuels in four rural communities of Rajasthan, India. The study adopts a community based system dynamics modeling approach. We describe our approach of using community based system dynamics with rural communities to delineate the feedback mechanisms involved in the uptake and sustainment of clean cooking technologies. We develop a reference mode with communities showing the trend over time of use or abandonment of cleaner cooking technologies and fuels in these communities. Subsequently, the study develops a system dynamics model with communities to understand the complex sub-systems driving the behavior in these communities as reflected in the reference mode. We use group model building techniques to facilitate participation of relevant stakeholders in the four communities and elicit a narrative describing the feedback mechanisms underlying sustained adoption or abandonment of cleaner cooking technologies. In understanding the dynamics of feedback mechanisms in the uptake and exclusive use of cleaner cooking systems, we increase the likelihood of dissemination and implementation of efficacious interventions into everyday settings to improve the health and wellbeing of women and children most affected by household air pollution. The challenge is not confined to developing robust technical solutions to reduce household air pollution and exposure to improve respiratory health, and prevent associated diseases. The bigger challenge is to disseminate and implement cleaner cooking technologies and fuels in the context of various social, behavioral, and economic constraints faced by poor households and communities. The Institutional Review Board of Washington University in St. Louis has exempted community based system dynamics modeling from review.

Selected Problems in Nonlinear Dynamics and Sociophysics

NASA Astrophysics Data System (ADS)

Westley, Alexandra Renee

This Ph.D. dissertation focuses on a collection of problems on the dynamical behavior of nonlinear many-body systems, drawn from two substantially different areas. First, the dynamical behavior seen in strongly nonlinear lattices such as in the Fermi-Pasta-Ulam-Tsingou (FPUT) system (part I) and second, time evolution behavior of interacting living objects which can be broadly considered as sociophysics systems (part II). The studies on FPUT-like systems will comprise of five chapters, dedicated to the properties of solitary and anti-solitary waves in the system, how localized nonlinear excitations decay and spread throughout these lattices, how two colliding solitary waves can precipitate highly localized and stable excitations, a possible alternative way to view these localized excitations through Duffing oscillators, and finally an exploration of parametric resonance in an FPUT-like lattice. Part II consists of two problems in the context of sociophysics. I use molecular dynamics inspired simulations to study the size and the stability of social groups of chimpanzees (such as those seen in central Africa) and compare the results with existing observations on the stability of chimpanzee societies. Secondly, I use an agent-based model to simulate land battles between an intelligent army and an insurgency when both have access to equally powerful weaponry. The study considers genetic algorithm based adaptive strategies to infer the strategies needed for the intelligent army to win the battles.

Molecular driving forces behind the tetrahydrofuran–water miscibility gap

DOE PAGES

Smith, Micholas Dean; Mostofian, Barmak; Petridis, Loukas; ...

2016-01-06

The tetrahydrofuran water binary system exhibits an unusual closed-loop miscibility gap (transitions from a miscible regime to an immiscible regime back to another miscible regime as the temperature increases). Here, using all-atom molecular dynamics simulations, we probe the structural and dynamical behavior of the binary system in the temperature regime of this gap at four different mass ratios, and we compare the behavior of bulk water and tetrahydrofuran. The changes in structure and dynamics observed in the simulations indicate that the temperature region associated with the miscibility gap is distinctive. Within the miscibility-gap temperature region, the self diffusion of watermore » is significantly altered and the second virial coefficients (pair interaction strengths) show parabolic-like behavior. Altogether, the results suggest that the gap is the result of differing trends with temperature of minor structural changes, which produces interaction virials with parabolic temperature dependence near the miscibility gap.« less

Regulating Cortical Neurodynamics for Past, Present and Future

NASA Astrophysics Data System (ADS)

Liljenström, Hans

2002-09-01

Behaving systems, biological as well as artificial, need to respond quickly and accurately to changes in the environment. The response is dependent on stored memories, and novel situations should be learnt for the guidance of future behavior. A highly nonlinear system dynamics is required in order to cope with a complex and changing environment, and this dynamics should be regulated to match the demands of the current situation, and to predict future behavior. In many cases the dynamics should be regulated to minimize processing time. We use computer simulations of cortical structures in order to investigate how the neurodynamics of these systems can be regulated for optimal performance in an unknown and changing environment. In particular, we study how cortical oscillations can serve to amplify weak signals and sustain an input pattern for more accurate information processing, and how chaotic-like behavior could increase the sensitivity in initial, exploratory states. We mimic regulating mechanisms based on neuromodulators, intrinsic noise levels, and various synchronizing effects. We find optimal noise levels where system performance is maximized, and neuromodulatory strategies for an efficient pattern recognition, where the anticipatory state of the system plays an important role.

Detecting and classifying method based on similarity matching of Android malware behavior with profile.

PubMed

Jang, Jae-Wook; Yun, Jaesung; Mohaisen, Aziz; Woo, Jiyoung; Kim, Huy Kang

2016-01-01

Mass-market mobile security threats have increased recently due to the growth of mobile technologies and the popularity of mobile devices. Accordingly, techniques have been introduced for identifying, classifying, and defending against mobile threats utilizing static, dynamic, on-device, and off-device techniques. Static techniques are easy to evade, while dynamic techniques are expensive. On-device techniques are evasion, while off-device techniques need being always online. To address some of those shortcomings, we introduce Andro-profiler, a hybrid behavior based analysis and classification system for mobile malware. Andro-profiler main goals are efficiency, scalability, and accuracy. For that, Andro-profiler classifies malware by exploiting the behavior profiling extracted from the integrated system logs including system calls. Andro-profiler executes a malicious application on an emulator in order to generate the integrated system logs, and creates human-readable behavior profiles by analyzing the integrated system logs. By comparing the behavior profile of malicious application with representative behavior profile for each malware family using a weighted similarity matching technique, Andro-profiler detects and classifies it into malware families. The experiment results demonstrate that Andro-profiler is scalable, performs well in detecting and classifying malware with accuracy greater than 98 %, outperforms the existing state-of-the-art work, and is capable of identifying 0-day mobile malware samples.

Nonequilibrium phase transitions in isotropic Ashkin-Teller model

NASA Astrophysics Data System (ADS)

Akıncı, Ümit

2017-03-01

Dynamic behavior of an isotropic Ashkin-Teller model in the presence of a periodically oscillating magnetic field has been analyzed by means of the mean field approximation. The dynamic equation of motion has been constructed with the help of a Glauber type stochastic process and solved for a square lattice. After defining the possible dynamical phases of the system, phase diagrams have been given and the behavior of the hysteresis loops has been investigated in detail. The hysteresis loop for specific order parameter of isotropic Ashkin-Teller model has been defined and characteristics of this loop in different dynamical phases have been given.

Dynamical Systems in Psychology: Linguistic Approaches

NASA Astrophysics Data System (ADS)

Sulis, William

Major goals for psychoanalysis and psychology are the description, analysis, prediction, and control of behaviour. Natural language has long provided the medium for the formulation of our theoretical understanding of behavior. But with the advent of nonlinear dynamics, a new language has appeared which offers promise to provide a quantitative theory of behaviour. In this paper, some of the limitations of natural and formal languages are discussed. Several approaches to understanding the links between natural and formal languages, as applied to the study of behavior, are discussed. These include symbolic dynamics, Moore's generalized shifts, Crutchfield's ɛ machines, and dynamical automata.

Examples of equilibrium and non-equilibrium behavior in evolutionary systems

NASA Astrophysics Data System (ADS)

Soulier, Arne

With this thesis, we want to shed some light into the darkness of our understanding of simply defined statistical mechanics systems and the surprisingly complex dynamical behavior they exhibit. We will do so by presenting in turn one equilibrium and then one non-equilibrium system with evolutionary dynamics. In part 1, we will present the seceder-model, a newly developed system that cannot equilibrate. We will then study several properties of the system and obtain an idea of the richness of the dynamics of the seceder model, which is particular impressive given the minimal amount of modeling necessary in its setup. In part 2, we will present extensions to the directed polymer in random media problem on a hypercube and its connection to the Eigen model of evolution. Our main interest will be the influence of time-dependent and time-independent changes in the fitness landscape viewed by an evolving population. This part contains the equilibrium dynamics. The stochastic models and the topic of evolution and non-equilibrium in general will allow us to point out similarities to the various lines of thought in game theory.

Managing lifelike behavior in a dynamic self-assembled system

NASA Astrophysics Data System (ADS)

Ropp, Chad; Bachelard, Nicolas; Wang, Yuan; Zhang, Xiang

Self-organization can arise outside of thermodynamic equilibrium in a process of dynamic self-assembly. This is observed in nature, for example in flocking birds, but can also be created artificially with non-living entities. Such dynamic systems often display lifelike properties, including the ability to self-heal and adapt to environmental changes, which arise due to the collective and often complex interactions between the many individual elements. Such interactions are inherently difficult to predict and control, and limit the development of artificial systems. Here, we report a fundamentally new method to manage dynamic self-assembly through the direct external control of collective phenomena. Our system consists of a waveguide filled with mobile scattering particles. These particles spontaneously self-organize when driven by a coherent field, self-heal when mechanically perturbed, and adapt to changes in the drive wavelength. This behavior is governed by particle interactions that are completely mediated by coherent wave scattering. Compared to hydrodynamic interactions which lead to compact ordered structures, our system displays sinusoidal degeneracy and many different steady-state geometries that can be adjusted using the external field.

Scale Invariance in Lateral Head Scans During Spatial Exploration.

PubMed

Yadav, Chetan K; Doreswamy, Yoganarasimha

2017-04-14

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Scale Invariance in Lateral Head Scans During Spatial Exploration

NASA Astrophysics Data System (ADS)

Yadav, Chetan K.; Doreswamy, Yoganarasimha

2017-04-01

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

A Selectionist Perspective on Systemic and Behavioral Change in Organizations

ERIC Educational Resources Information Center

Sandaker, Ingunn

2009-01-01

This article provides a discussion of how different dynamics in production processes and communication structures in the organization serve as different environmental contingencies favoring different behavioral patterns and variability of performance in organizations. Finally, an elaboration on a systems perspective on the selection of corporate…

Dynamical investigation and parameter stability region analysis of a flywheel energy storage system in charging mode

NASA Astrophysics Data System (ADS)

Zhang, Wei-Ya; Li, Yong-Li; Chang, Xiao-Yong; Wang, Nan

2013-09-01

In this paper, the dynamic behavior analysis of the electromechanical coupling characteristics of a flywheel energy storage system (FESS) with a permanent magnet (PM) brushless direct-current (DC) motor (BLDCM) is studied. The Hopf bifurcation theory and nonlinear methods are used to investigate the generation process and mechanism of the coupled dynamic behavior for the average current controlled FESS in the charging mode. First, the universal nonlinear dynamic model of the FESS based on the BLDCM is derived. Then, for a 0.01 kWh/1.6 kW FESS platform in the Key Laboratory of the Smart Grid at Tianjin University, the phase trajectory of the FESS from a stable state towards chaos is presented using numerical and stroboscopic methods, and all dynamic behaviors of the system in this process are captured. The characteristics of the low-frequency oscillation and the mechanism of the Hopf bifurcation are investigated based on the Routh stability criterion and nonlinear dynamic theory. It is shown that the Hopf bifurcation is directly due to the loss of control over the inductor current, which is caused by the system control parameters exceeding certain ranges. This coupling nonlinear process of the FESS affects the stability of the motor running and the efficiency of energy transfer. In this paper, we investigate into the effects of control parameter change on the stability and the stability regions of these parameters based on the averaged-model approach. Furthermore, the effect of the quantization error in the digital control system is considered to modify the stability regions of the control parameters. Finally, these theoretical results are verified through platform experiments.

Behavior generation strategy of artificial behavioral system by self-learning paradigm for autonomous robot tasks

NASA Astrophysics Data System (ADS)

Dağlarli, Evren; Temeltaş, Hakan

2008-04-01

In this study, behavior generation and self-learning paradigms are investigated for the real-time applications of multi-goal mobile robot tasks. The method is capable to generate new behaviors and it combines them in order to achieve multi goal tasks. The proposed method is composed from three layers: Behavior Generating Module, Coordination Level and Emotion -Motivation Level. Last two levels use Hidden Markov models to manage dynamical structure of behaviors. The kinematics and dynamic model of the mobile robot with non-holonomic constraints are considered in the behavior based control architecture. The proposed method is tested on a four-wheel driven and four-wheel steered mobile robot with constraints in simulation environment and results are obtained successfully.

Is a Universal Science of Complexity Conceivable?

NASA Astrophysics Data System (ADS)

West, Geoffrey B.

Over the past quarter of a century, terms like complex adaptive system, the science of complexity, emergent behavior, self-organization, and adaptive dynamics have entered the literature, reflecting the rapid growth in collaborative, trans-disciplinary research on fundamental problems in complex systems ranging across the entire spectrum of science from the origin and dynamics of organisms and ecosystems to financial markets, corporate dynamics, urbanization and the human brain...

Behavioral Dynamics in Swimming: The Appropriate Use of Inertial Measurement Units.

PubMed

Guignard, Brice; Rouard, Annie; Chollet, Didier; Seifert, Ludovic

2017-01-01

Motor control in swimming can be analyzed using low- and high-order parameters of behavior. Low-order parameters generally refer to the superficial aspects of movement (i.e., position, velocity, acceleration), whereas high-order parameters capture the dynamics of movement coordination. To assess human aquatic behavior, both types have usually been investigated with multi-camera systems, as they offer high three-dimensional spatial accuracy. Research in ecological dynamics has shown that movement system variability can be viewed as a functional property of skilled performers, helping them adapt their movements to the surrounding constraints. Yet to determine the variability of swimming behavior, a large number of stroke cycles (i.e., inter-cyclic variability) has to be analyzed, which is impossible with camera-based systems as they simply record behaviors over restricted volumes of water. Inertial measurement units (IMUs) were designed to explore the parameters and variability of coordination dynamics. These light, transportable and easy-to-use devices offer new perspectives for swimming research because they can record low- to high-order behavioral parameters over long periods. We first review how the low-order behavioral parameters (i.e., speed, stroke length, stroke rate) of human aquatic locomotion and their variability can be assessed using IMUs. We then review the way high-order parameters are assessed and the adaptive role of movement and coordination variability in swimming. We give special focus to the circumstances in which determining the variability between stroke cycles provides insight into how behavior oscillates between stable and flexible states to functionally respond to environmental and task constraints. The last section of the review is dedicated to practical recommendations for coaches on using IMUs to monitor swimming performance. We therefore highlight the need for rigor in dealing with these sensors appropriately in water. We explain the fundamental and mandatory steps to follow for accurate results with IMUs, from data acquisition (e.g., waterproofing procedures) to interpretation (e.g., drift correction).

Behavioral Dynamics in Swimming: The Appropriate Use of Inertial Measurement Units

PubMed Central

Guignard, Brice; Rouard, Annie; Chollet, Didier; Seifert, Ludovic

2017-01-01

Motor control in swimming can be analyzed using low- and high-order parameters of behavior. Low-order parameters generally refer to the superficial aspects of movement (i.e., position, velocity, acceleration), whereas high-order parameters capture the dynamics of movement coordination. To assess human aquatic behavior, both types have usually been investigated with multi-camera systems, as they offer high three-dimensional spatial accuracy. Research in ecological dynamics has shown that movement system variability can be viewed as a functional property of skilled performers, helping them adapt their movements to the surrounding constraints. Yet to determine the variability of swimming behavior, a large number of stroke cycles (i.e., inter-cyclic variability) has to be analyzed, which is impossible with camera-based systems as they simply record behaviors over restricted volumes of water. Inertial measurement units (IMUs) were designed to explore the parameters and variability of coordination dynamics. These light, transportable and easy-to-use devices offer new perspectives for swimming research because they can record low- to high-order behavioral parameters over long periods. We first review how the low-order behavioral parameters (i.e., speed, stroke length, stroke rate) of human aquatic locomotion and their variability can be assessed using IMUs. We then review the way high-order parameters are assessed and the adaptive role of movement and coordination variability in swimming. We give special focus to the circumstances in which determining the variability between stroke cycles provides insight into how behavior oscillates between stable and flexible states to functionally respond to environmental and task constraints. The last section of the review is dedicated to practical recommendations for coaches on using IMUs to monitor swimming performance. We therefore highlight the need for rigor in dealing with these sensors appropriately in water. We explain the fundamental and mandatory steps to follow for accurate results with IMUs, from data acquisition (e.g., waterproofing procedures) to interpretation (e.g., drift correction). PMID:28352243

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons.

PubMed

Toutounji, Hazem; Pasemann, Frank

2014-01-01

The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with 18 degrees of freedom, and obstacle-avoidance of a wheel-driven robot.

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons

PubMed Central

Toutounji, Hazem; Pasemann, Frank

2014-01-01

The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with 18 degrees of freedom, and obstacle-avoidance of a wheel-driven robot. PMID:24904403

Application of Tube Dynamics to Non-Statistical Reaction Processes

NASA Astrophysics Data System (ADS)

Gabern, F.; Koon, W. S.; Marsden, J. E.; Ross, S. D.; Yanao, T.

2006-06-01

A technique based on dynamical systems theory is introduced for the computation of lifetime distributions and rates of chemical reactions and scattering phenomena, even in systems that exhibit non-statistical behavior. In particular, we merge invariant manifold tube dynamics with Monte Carlo volume determination for accurate rate calculations. This methodology is applied to a three-degree-of-freedom model problem and some ideas on how it might be extended to higher-degree-of-freedom systems are presented.

Multiscale System for Environmentally-Driven Infectious Disease with Threshold Control Strategy

NASA Astrophysics Data System (ADS)

Sun, Xiaodan; Xiao, Yanni

A multiscale system for environmentally-driven infectious disease is proposed, in which control measures at three different scales are implemented when the number of infected hosts exceeds a certain threshold. Our coupled model successfully describes the feedback mechanisms of between-host dynamics on within-host dynamics by employing one-scale variable guided enhancement of interventions on other scales. The modeling approach provides a novel idea of how to link the large-scale dynamics to small-scale dynamics. The dynamic behaviors of the multiscale system on two time-scales, i.e. fast system and slow system, are investigated. The slow system is further simplified to a two-dimensional Filippov system. For the Filippov system, we study the dynamics of its two subsystems (i.e. free-system and control-system), the sliding mode dynamics, the boundary equilibrium bifurcations, as well as the global behaviors. We prove that both subsystems may undergo backward bifurcations and the sliding domain exists. Meanwhile, it is possible that the pseudo-equilibrium exists and is globally stable, or the pseudo-equilibrium, the disease-free equilibrium and the real equilibrium are tri-stable, or the pseudo-equilibrium and the real equilibrium are bi-stable, or the pseudo-equilibrium and disease-free equilibrium are bi-stable, which depends on the threshold value and other parameter values. The global stability of the pseudo-equilibrium reveals that we may maintain the number of infected hosts at a previously given value. Moreover, the bi-stability and tri-stability indicate that whether the number of infected individuals tends to zero or a previously given value or other positive values depends on the parameter values and the initial states of the system. These results highlight the challenges in the control of environmentally-driven infectious disease.

Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.

PubMed

Collins, Anne G E; Frank, Michael J

2018-03-06

Learning from rewards and punishments is essential to survival and facilitates flexible human behavior. It is widely appreciated that multiple cognitive and reinforcement learning systems contribute to decision-making, but the nature of their interactions is elusive. Here, we leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. Neural dynamics confirmed that increases in neural expectation were predictive of reduced neural surprise in the following feedback period, supporting central tenets of RL models. Within- and cross-trial dynamics revealed a cooperative interplay between systems for learning, in which WM contributes expectations to guide RL, despite competition between systems during choice. Together, these results provide a deeper understanding of how multiple neural systems interact for learning and decision-making and facilitate analysis of their disruption in clinical populations.

The Interplay between Language, Gesture, and Affect during Communicative Transition: A Dynamic Systems Approach

ERIC Educational Resources Information Center

Parlade, Meaghan V.; Iverson, Jana M.

2011-01-01

From a dynamic systems perspective, transition points in development are times of increased instability, during which behavioral patterns are susceptible to temporary decoupling. This study investigated the impact of the vocabulary spurt on existing patterns of communicative coordination. Eighteen typically developing infants were videotaped at…

Cognition as a Dynamic System: Principles from Embodiment

ERIC Educational Resources Information Center

Smith, Linda B.

2005-01-01

Traditional approaches to cognitive development concentrate on the stability of cognition and explain that stability via concepts segregated from perceiving acting. A dynamic systems approach in contrast focuses on the self-organization of behavior in tasks. This article uses recent results concerning the embodiment of cognition to argue for a…

Hybrid Configuration of Darrieus and Savonius Rotors for Stand-alone Power Systems

NASA Astrophysics Data System (ADS)

Wakui, Tetsuya; Tanzawa, Yoshiaki; Hashizume, Takumi; Nagao, Toshio

The suitable hybrid configuration of Darrieus lift-type and Savonius drag-type rotors for stand-alone wind turbine-generator systems is discussed using our dynamic simulation model. Two types of hybrid configurations are taken up: Type-A installs the Savonius rotor inside the Darrieus rotor and Type-B installs the Savonius rotor outside the Darrieus rotor. The computed results of the output characteristics and the dynamic behaviors of the system operated at the maximum power coefficient points show that Type-A, which has fine operating behavior to wind speed changes and can be compactly designed because of a shorter rotational shaft, is an effective way for self-controlled stand-alone small-scale systems.

Engineering entrainment and adaptation in limit cycle systems : From biological inspiration to applications in robotics.

PubMed

Buchli, Jonas; Righetti, Ludovic; Ijspeert, Auke Jan

2006-12-01

Periodic behavior is key to life and is observed in multiple instances and at multiple time scales in our metabolism, our natural environment, and our engineered environment. A natural way of modeling or generating periodic behavior is done by using oscillators, i.e., dynamical systems that exhibit limit cycle behavior. While there is extensive literature on methods to analyze such dynamical systems, much less work has been done on methods to synthesize an oscillator to exhibit some specific desired characteristics. The goal of this article is twofold: (1) to provide a framework for characterizing and designing oscillators and (2) to review how classes of well-known oscillators can be understood and related to this framework. The basis of the framework is to characterize oscillators in terms of their fundamental temporal and spatial behavior and in terms of properties that these two behaviors can be designed to exhibit. This focus on fundamental properties is important because it allows us to systematically compare a large variety of oscillators that might at first sight appear very different from each other. We identify several specifications that are useful for design, such as frequency-locking behavior, phase-locking behavior, and specific output signal shape. We also identify two classes of design methods by which these specifications can be met, namely offline methods and online methods. By relating these specifications to our framework and by presenting several examples of how oscillators have been designed in the literature, this article provides a useful methodology and toolbox for designing oscillators for a wide range of purposes. In particular, the focus on synthesis of limit cycle dynamical systems should be useful both for engineering and for computational modeling of physical or biological phenomena.

Regulation of Dynamic Behavior of Retinal Microglia by CX3CR1 Signaling

PubMed Central

Liang, Katharine J.; Lee, Jung Eun; Wang, Yunqing D.; Ma, Wenxin; Fontainhas, Aurora M.; Fariss, Robert N.; Wong, Wai T.

2009-01-01

PURPOSE Microglia in the central nervous system display a marked structural dynamism in their processes in the resting state. This dynamic behavior, which may play a constitutive surveying role in the uninjured neural parenchyma, is also highly responsive to tissue injury. The role of CX3CR1, a chemokine receptor expressed in microglia, in regulating microglia morphology and dynamic behavior in the resting state and after laser-induced focal injury was examined. METHODS Time-lapse confocal imaging of retinal explants was used to evaluate the dynamic behavior of retinal microglia labeled with green fluorescent protein (GFP). Transgenic mice in which CX3CR1 signaling was ablated (CX3CR1GFP/GFP/CX3CR1−/−) and preserved (CX3CR1+/GFP/CX3CR1+/−) were used. RESULTS Retinal microglial density, distribution, cellular morphology, and overall retinal tissue anatomy were not altered in young CX3CR1−/− animals. In the absence of CX3CR1, retinal microglia continued to exhibit dynamic motility in their processes. However, rates of process movement were significantly decreased, both under resting conditions and in response to tissue injury. In addition, microglia migration occurring in response to focal laser injury was also significantly slowed in microglia lacking CX3CR1. CONCLUSIONS CX3CR1 signaling in retinal microglia, though not absolutely required for the presence of microglial dynamism, plays a role in potentiating the rate of retinal microglial process dynamism and cellular migration. CX3CL1 signaling from retinal neurons and endothelial cells likely modulates dynamic microglia behavior so as to influence the level of microglial surveillance under basal conditions and the rate of dynamic behavior in response to tissue injury. PMID:19443728

Robustness of Oscillatory Behavior in Correlated Networks

PubMed Central

Sasai, Takeyuki; Morino, Kai; Tanaka, Gouhei; Almendral, Juan A.; Aihara, Kazuyuki

2015-01-01

Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity. PMID:25894574

Oculometric Assessment of Dynamic Visual Processing

NASA Technical Reports Server (NTRS)

Liston, Dorion Bryce; Stone, Lee

2014-01-01

Eye movements are the most frequent (3 per second), shortest-latency (150-250 ms), and biomechanically simplest (1 joint, no inertial complexities) voluntary motor behavior in primates, providing a model system to assess sensorimotor disturbances arising from trauma, fatigue, aging, or disease states (e.g., Diefendorf and Dodge, 1908). We developed a 15-minute behavioral tracking protocol consisting of randomized stepramp radial target motion to assess several aspects of the behavioral response to dynamic visual motion, including pursuit initiation, steadystate tracking, direction-tuning, and speed-tuning thresholds. This set of oculomotor metrics provide valid and reliable measures of dynamic visual performance (Stone and Krauzlis, 2003; Krukowski and Stone, 2005; Stone et al, 2009; Liston and Stone, 2014), and may prove to be a useful assessment tool for functional impairments of dynamic visual processing.

Deployment dynamics and control of large-scale flexible solar array system with deployable mast

NASA Astrophysics Data System (ADS)

Li, Hai-Quan; Liu, Xiao-Feng; Guo, Shao-Jing; Cai, Guo-Ping

2016-10-01

In this paper, deployment dynamics and control of large-scale flexible solar array system with deployable mast are investigated. The adopted solar array system is introduced firstly, including system configuration, deployable mast and solar arrays with several mechanisms. Then dynamic equation of the solar array system is established by the Jourdain velocity variation principle and a method for dynamics with topology changes is introduced. In addition, a PD controller with disturbance estimation is designed to eliminate the drift of spacecraft mainbody. Finally the validity of the dynamic model is verified through a comparison with ADAMS software and the deployment process and dynamic behavior of the system are studied in detail. Simulation results indicate that the proposed model is effective to describe the deployment dynamics of the large-scale flexible solar arrays and the proposed controller is practical to eliminate the drift of spacecraft mainbody.

Using Systems Theory to Understand and Respond to Family Influences on Children's Bullying Behavior: Friendly Schools Friendly Families Program

ERIC Educational Resources Information Center

Cross, Donna; Barnes, Amy

2014-01-01

This article addresses Systems Theory as it applies to school-age children's bullying behavior. It focuses on the interrelationships, mutual influences, and dynamics of relationships within the family, and how these may affect children's behavior toward their peers. The theory helps to explain the ways family patterns are reflected in…

A new approach for modular robot system behavioral modeling: Base on Petri net and category theory

NASA Astrophysics Data System (ADS)

Zhang, Yun; Wei, Hongxing; Yang, Bo

2018-04-01

To design modular robot system, Petri nets and category theory are combined and the ability of simulation of Petri net is discussed. According to category theory, the method of describing the category of components in the dynamic characteristics of the system is deduced. Moreover, a modular robot system is analyzed, which provides a verifiable description of the dynamic characteristics of the system.

COED Transactions, Vol. XI, No. 3, March 1979. LSSP: An Educational Aid to the Study of Linear System Dynamics.

ERIC Educational Resources Information Center

Mitchell, Eugene E., Ed.

The study of the dynamics of physical systems is of importance to all engineering students. LSSP, a Linear System Simulation Program, is used to study the behavior of physical phenomena and systems which may be represented to a good degree of approximation by linear models. Emphasis is placed upon the unity resulting from the mathematical…

Tour time in a two-route traffic system controlled by signals

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Naito, Yuichi

2011-11-01

We study the dynamic behavior of vehicular traffic in a two-route system with a series of signals (traffic lights) at low density where the number of signals on route A is different from that on route B. We investigate the dependence of the tour time on the route for some strategies of signal control. The nonlinear dynamic model of a two-route traffic system controlled by signals is presented by nonlinear maps. The vehicular traffic exhibits a very complex behavior, depending on the cycle time, the phase difference, and the irregularity. The dependence of the tour time on the route choice is clarified for the signal strategies.

Some remarks on the compatibility between determinism and unpredictability.

PubMed

Franceschelli, Sara

2012-09-01

Determinism and unpredictability are compatible since deterministic flows can produce, if sensitive to initial conditions, unpredictable behaviors. Within this perspective, the notion of scenario to chaos transition offers a new form of predictability for the behavior of sensitive to initial condition systems under the variation of a control parameter. In this paper I first shed light on the genesis of this notion, based on a dynamical systems approach and on considerations of structural stability. I then suggest a link to the figure of epigenetic landscape, partially inspired by a dynamical systems perspective, and offering a theoretical framework to apprehend developmental noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

Understanding the dynamics of sustainable social-ecological systems: human behavior, institutions, and regulatory feedback networks.

PubMed

Anderies, John M

2015-02-01

I present a general mathematical modeling framework that can provide a foundation for the study of sustainability in social- ecological systems (SESs). Using basic principles from feedback control and a sequence of specific models from bioeconomics and economic growth, I outline several mathematical and empirical challenges associated with the study of sustainability of SESs. These challenges are categorized into three classes: (1) the social choice of performance measures, (2) uncertainty, and (3) collective action. Finally, I present some opportunities for combining stylized dynamical systems models with empirical data on human behavior and biophysical systems to address practical challenges for the design of effective governance regimes (policy feedbacks) for highly uncertain natural resource systems.

Modeling Common-Sense Decisions in Artificial Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Dynamic heterogeneity in crossover spin facilitated model of supercooled liquid and fractional Stokes-Einstein relation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Seo-Woo; Kim, Soree; Jung, YounJoon, E-mail: yjjung@snu.ac.kr

Kinetically constrained models have gained much interest as models that assign the origins of interesting dynamic properties of supercooled liquids to dynamical facilitation mechanisms that have been revealed in many experiments and numerical simulations. In this work, we investigate the dynamic heterogeneity in the fragile-to-strong liquid via Monte Carlo method using the model that linearly interpolates between the strong liquid-like behavior and the fragile liquid-like behavior by an asymmetry parameter b. When the asymmetry parameter is sufficiently small, smooth fragile-to-strong transition is observed both in the relaxation time and the diffusion constant. Using these physical quantities, we investigate fractional Stokes-Einsteinmore » relations observed in this model. When b is fixed, the system shows constant power law exponent under the temperature change, and the exponent has the value between that of the Frederickson-Andersen model and the East model. Furthermore, we investigate the dynamic length scale of our systems and also find the crossover relation between the relaxation time. We ascribe the competition between energetically favored symmetric relaxation mechanism and entropically favored asymmetric relaxation mechanism to the fragile-to-strong crossover behavior.« less

Patterns of Stochastic Behavior in Dynamically Unstable High-Dimensional Biochemical Networks

PubMed Central

Rosenfeld, Simon

2009-01-01

The question of dynamical stability and stochastic behavior of large biochemical networks is discussed. It is argued that stringent conditions of asymptotic stability have very little chance to materialize in a multidimensional system described by the differential equations of chemical kinetics. The reason is that the criteria of asymptotic stability (Routh-Hurwitz, Lyapunov criteria, Feinberg’s Deficiency Zero theorem) would impose the limitations of very high algebraic order on the kinetic rates and stoichiometric coefficients, and there are no natural laws that would guarantee their unconditional validity. Highly nonlinear, dynamically unstable systems, however, are not necessarily doomed to collapse, as a simple Jacobian analysis would suggest. It is possible that their dynamics may assume the form of pseudo-random fluctuations quite similar to a shot noise, and, therefore, their behavior may be described in terms of Langevin and Fokker-Plank equations. We have shown by simulation that the resulting pseudo-stochastic processes obey the heavy-tailed Generalized Pareto Distribution with temporal sequence of pulses forming the set of constituent-specific Poisson processes. Being applied to intracellular dynamics, these properties are naturally associated with burstiness, a well documented phenomenon in the biology of gene expression. PMID:19838330

Representation in dynamical agents.

PubMed

Ward, Ronnie; Ward, Robert

2009-04-01

This paper extends experiments by Beer [Beer, R. D. (1996). Toward the evolution of dynamical neural networks for minimally cognitive behavior. In P. Maes, M. Mataric, J. Meyer, J. Pollack, & S. Wilson (Eds.), From animals to animats 4: Proceedings of the fourth international conference on simulation of adaptive behavior (pp. 421-429). MIT Press; Beer, R. D. (2003). The dynamics of active categorical perception in an evolved model agent (with commentary and response). Adaptive Behavior, 11 (4), 209-243] with an evolved, dynamical agent to further explore the question of representation in cognitive systems. Beer's environmentally-situated visual agent was controlled by a continuous-time recurrent neural network, and evolved to perform a categorical perception task, discriminating circles from diamonds. Despite the agent's high levels of discrimination performance, Beer found no evidence of internal representation in the best-evolved agent's nervous system. Here we examine the generality of this result. We evolved an agent for shape discrimination, and performed extensive behavioral analyses to test for representation. In this case we find that agents developed to discriminate equal-width shapes exhibit what Clark [Clark, A. (1997). The dynamical challenge. Cognitive Science, 21 (4), 461-481] calls "weak-substantive representation". The agent had internal configurations that (1) were understandably related to the object in the environment, and (2) were functionally used in a task relevant way when the target was not visible to the agent.

Dynamic Game Behavior of Retailers Considering the Quality of Substitute Products Based on Delay Decision

NASA Astrophysics Data System (ADS)

Bao, Binshuo; Ma, Junhai

2017-12-01

Motivated by the Silk Road Economic Belt and the 21st-Century Maritime Silk Road project, i.e. the Belt and Road (B&R), more goods will flow around the world. With this trading platform, people can buy products at relatively cheap prices, and it is easier for people to buy various goods. The quality and quantity of products thus attract more and more attention in the supply chains. This paper discusses the quantity decision by considering the product quality in parallel supply chains where two manufacturers produce substitute products and then sell them to their downstream retailers separately. In terms of the changing quantity, as well as the different quality, this paper establishes a dynamic game model to explore the dynamic behavior when the optimal profits of two retailers have been calculated. The dynamic behaviors of the system, such as stable region, bifurcation and chaos, strange attractors and the largest Lyapunov exponents (LLE) are analyzed. The effect of the quantity adjustment parameter on the stability of the supply chain system is investigated through numerical simulations. Furthermore, a dynamic game model is established based on the quality delay decision, to investigate the influence of the quality delay parameter on the dynamic game model and the profits. Finally, the optimal decisions are obtained and analyzed.

Stochastic ice stream dynamics

PubMed Central

Bertagni, Matteo Bernard; Ridolfi, Luca

2016-01-01

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution. PMID:27457960

Chaos as the hub of systems dynamics. The part I-The attitude control of spacecraft by involving in the heteroclinic chaos

NASA Astrophysics Data System (ADS)

Doroshin, Anton V.

2018-06-01

In this work the chaos in dynamical systems is considered as a positive aspect of dynamical behavior which can be applied to change systems dynamical parameters and, moreover, to change systems qualitative properties. From this point of view, the chaos can be characterized as a hub for the system dynamical regimes, because it allows to interconnect separated zones of the phase space of the system, and to fulfill the jump into the desirable phase space zone. The concretized aim of this part of the research is to focus on developing the attitude control method for magnetized gyrostat-satellites, which uses the passage through the intentionally generated heteroclinic chaos. The attitude dynamics of the satellite/spacecraft in this case represents the series of transitions from the initial dynamical regime into the chaotic heteroclinic regime with the subsequent exit to the final target dynamical regime with desirable parameters of the attitude dynamics.

Natural neural projection dynamics underlying social behavior

PubMed Central

Gunaydin, Lisa A.; Grosenick, Logan; Finkelstein, Joel C.; Kauvar, Isaac V.; Fenno, Lief E.; Adhikari, Avishek; Lammel, Stephan; Mirzabekov, Julie J.; Airan, Raag D.; Zalocusky, Kelly A.; Tye, Kay M.; Anikeeva, Polina; Malenka, Robert C.; Deisseroth, Karl

2014-01-01

Social interaction is a complex behavior essential for many species, and is impaired in major neuropsychiatric disorders. Pharmacological studies have implicated certain neurotransmitter systems in social behavior, but circuit-level understanding of endogenous neural activity during social interaction is lacking. We therefore developed and applied a new methodology, termed fiber photometry, to optically record natural neural activity in genetically- and connectivity-defined projections to elucidate the real-time role of specified pathways in mammalian behavior. Fiber photometry revealed that activity dynamics of a ventral tegmental area (VTA)-to-nucleus accumbens (NAc) projection could encode and predict key features of social but not novel-object interaction. Consistent with this observation, optogenetic control of cells specifically contributing to this projection was sufficient to modulate social behavior, which was mediated by type-1 dopamine receptor signaling downstream in the NAc. Direct observation of projection-specific activity in this way captures a fundamental and previously inaccessible dimension of circuit dynamics. PMID:24949967

Mean-field behavior as a result of noisy local dynamics in self-organized criticality: Neuroscience implications

NASA Astrophysics Data System (ADS)

Moosavi, S. Amin; Montakhab, Afshin

2014-05-01

Motivated by recent experiments in neuroscience which indicate that neuronal avalanches exhibit scale invariant behavior similar to self-organized critical systems, we study the role of noisy (nonconservative) local dynamics on the critical behavior of a sandpile model which can be taken to mimic the dynamics of neuronal avalanches. We find that despite the fact that noise breaks the strict local conservation required to attain criticality, our system exhibits true criticality for a wide range of noise in various dimensions, given that conservation is respected on the average. Although the system remains critical, exhibiting finite-size scaling, the value of critical exponents change depending on the intensity of local noise. Interestingly, for a sufficiently strong noise level, the critical exponents approach and saturate at their mean-field values, consistent with empirical measurements of neuronal avalanches. This is confirmed for both two and three dimensional models. However, the addition of noise does not affect the exponents at the upper critical dimension (D =4). In addition to an extensive finite-size scaling analysis of our systems, we also employ a useful time-series analysis method to establish true criticality of noisy systems. Finally, we discuss the implications of our work in neuroscience as well as some implications for the general phenomena of criticality in nonequilibrium systems.

Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks

PubMed Central

Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the “information networks” different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed. PMID:28796797

Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks.

PubMed

Park, Jihoon; Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the "information networks" different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed.

Phase behavior of charged colloids at a fluid interface

NASA Astrophysics Data System (ADS)

Kelleher, Colm P.; Guerra, Rodrigo E.; Hollingsworth, Andrew D.; Chaikin, Paul M.

2017-02-01

We study the phase behavior of a system of charged colloidal particles that are electrostatically bound to an almost flat interface between two fluids. We show that, despite the fact that our experimental system consists of only 103-104 particles, the phase behavior is consistent with the theory of melting due to Kosterlitz, Thouless, Halperin, Nelson, and Young. Using spatial and temporal correlations of the bond-orientational order parameter, we classify our samples into solid, isotropic fluid, and hexatic phases. We demonstrate that the topological defect structure we observe in each phase corresponds to the predictions of Kosterlitz-Thouless-Halperin-Nelson-Young theory. By measuring the dynamic Lindemann parameter γL(τ ) and the non-Gaussian parameter α2(τ ) of the displacements of the particles relative to their neighbors, we show that each of the phases displays distinctive dynamical behavior.

Outline of a general theory of behavior and brain coordination.

PubMed

Kelso, J A Scott; Dumas, Guillaume; Tognoli, Emmanuelle

2013-01-01

Much evidence suggests that dynamic laws of neurobehavioral coordination are sui generis: they deal with collective properties that are repeatable from one system to another and emerge from microscopic dynamics but may not (even in principle) be deducible from them. Nevertheless, it is useful to try to understand the relationship between different levels while all the time respecting the autonomy of each. We report a program of research that uses the theoretical concepts of coordination dynamics and quantitative measurements of simple, well-defined experimental model systems to explicitly relate neural and behavioral levels of description in human beings. Our approach is both top-down and bottom-up and aims at ending up in the same place: top-down to derive behavioral patterns from neural fields, and bottom-up to generate neural field patterns from bidirectional coupling between astrocytes and neurons. Much progress can be made by recognizing that the two approaches--reductionism and emergentism--are complementary. A key to understanding is to couch the coordination of very different things--from molecules to thoughts--in the common language of coordination dynamics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Numerical evidences of universal trap-like aging dynamics

NASA Astrophysics Data System (ADS)

Cammarota, Chiara; Marinari, Enzo

2018-04-01

Trap models have been initially proposed as toy models for dynamical relaxation in extremely simplified rough potential energy landscapes. Their importance has recently grown considerably thanks to the discovery that the trap-like aging mechanism directly controls the out-of-equilibrium relaxation processes of more sophisticated spin models, that are considered as the solvable counterpart of real disordered systems. Further establishing the connection between these spin models, out-of-equilibrium behavior and the trap like aging mechanism could shed new light on the properties, which are still largely mysterious, for the activated out-of-equilibrium dynamics of disordered systems. In this work we discuss numerical evidence based on the computations of the permanence times of an emergent trap-like aging behavior in a variety of very simple disordered models—developed from the trap model paradigm. Our numerical results are backed by analytic derivations and heuristic discussions. Such exploration reveals some of the tricks needed to reveal the trap behavior in spite of the occurrence of secondary processes, of the existence of dynamical correlations and of strong finite system’s size effects.

Outline of a General Theory of Behavior and Brain Coordination

PubMed Central

Kelso, J. A. Scott; Dumas, Guillaume; Tognoli, Emmanuelle

2012-01-01

Much evidence suggests that dynamic laws of neurobehavioral coordination are sui generis: they deal with collective properties that are repeatable from one system to another and emerge from microscopic dynamics but may not (even in principle) be deducible from them. Nevertheless, it is useful to try to understand the relationship between different levels while all the time respecting the autonomy of each. We report a program of research that uses the theoretical concepts of coordination dynamics and quantitative measurements of simple, well-defined experimental model systems to explicitly relate neural and behavioral levels of description in human beings. Our approach is both top-down and bottom-up and aims at ending up in the same place: top-down to derive behavioral patterns from neural fields, and bottom-up to generate neural field patterns from bidirectional coupling between astrocytes and neurons. Much progress can be made by recognizing that the two approaches —reductionism and emergentism— are complementary. A key to understanding is to couch the coordination of very different things —from molecules to thoughts— in the common language of coordination dynamics. PMID:23084845

Fast dynamics in glass-forming polymers revisited

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colmenero, J.; Arbe, A.; Mijangos, C.

1997-12-31

The so called fast-dynamics of glass-forming systems as observed by time of flight (TOF) neutron scattering techniques is revisited. TOF-results corresponding to several glass-forming polymers with different chemical microstructure and glass-transition temperature are presented together with the theoretical framework proposed by the authors to interpret these results. The main conclusion is that the TOF-data can be explained in terms of quasiharmonic vibrations and the particular short time behavior of the segmental dynamics. The segmental dynamics display in the very short time range (t {approx} 2 ps) a crossover from a simple exponential behavior towards a non-exponential regime. The first exponentialmore » decay, which is controlled by C-C rotational barriers, can be understood as a trace of the behavior of the system in absence of the effects (correlations, cooperativity, memory effects {hor_ellipsis}) which characterize the dense supercooled liquid like state against the normal liquid state. The non-exponential regime at t > 2 ps corresponds to what is usually understood as {alpha} and {beta} relaxations. Some implications of these results are also discussed.« less

Cyclic Game Dynamics Driven by Iterated Reasoning

PubMed Central

Frey, Seth; Goldstone, Robert L.

2013-01-01

Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning–what you think I think you think–will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept. These cycles are driven by a “hopping” behavior that is consistent with other accounts of iterated reasoning: agents are constrained to about two steps of iterated reasoning and learn an additional one-half step with each session. If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems. PMID:23441191

Out-of-equilibrium dynamics driven by localized time-dependent perturbations at quantum phase transitions

NASA Astrophysics Data System (ADS)

Pelissetto, Andrea; Rossini, Davide; Vicari, Ettore

2018-03-01

We investigate the quantum dynamics of many-body systems subject to local (i.e., restricted to a limited space region) time-dependent perturbations. If the system crosses a quantum phase transition, an off-equilibrium behavior is observed, even for a very slow driving. We show that, close to the transition, time-dependent quantities obey scaling laws. In first-order transitions, the scaling behavior is universal, and some scaling functions can be computed exactly. For continuous transitions, the scaling laws are controlled by the standard critical exponents and by the renormalization-group dimension of the perturbation at the transition. Our protocol can be implemented in existing relatively small quantum simulators, paving the way for a quantitative probe of the universal off-equilibrium scaling behavior, without the need to manipulate systems close to the thermodynamic limit.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method.

PubMed

Zomorodian, Mehdi; Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method

PubMed Central

Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system. PMID:29216200

A system dynamics approach for modeling construction workers' safety attitudes and behaviors.

PubMed

Shin, Mingyu; Lee, Hyun-Soo; Park, Moonseo; Moon, Myunggi; Han, Sangwon

2014-07-01

Construction accidents are caused by an unsafe act (i.e., a person's behavior or activity that deviates from normal accepted safe procedure) and/or an unsafe condition (i.e., a hazard or an unsafe mechanical or physical environment). While there has been dramatic improvement in creating safer construction environments, relatively little is known regarding the elimination of construction workers' unsafe acts. To address this deficiency, this paper aims to develop a system dynamics (SD)-based model of construction workers' mental processes that can help analyze the feedback mechanisms and the resultant dynamics regarding the workers' safety attitudes and safe behaviors. The developed model is applied to examine the effectiveness of three safety improvement policies: incentives for safe behaviors, and increased levels of communication and immersion in accidents. Application of the model verifies the strong potential of the developed model to provide a better understanding of how to eliminate unsafe acts, and to function as a robust test-bed to assess the effectiveness of safety programs or training sessions before their implementation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Crossing the threshold

NASA Astrophysics Data System (ADS)

Bush, John; Tambasco, Lucas

2017-11-01

First, we summarize the circumstances in which chaotic pilot-wave dynamics gives rise to quantum-like statistical behavior. For ``closed'' systems, in which the droplet is confined to a finite domain either by boundaries or applied forces, quantum-like features arise when the persistence time of the waves exceeds the time required for the droplet to cross its domain. Second, motivated by the similarities between this hydrodynamic system and stochastic electrodynamics, we examine the behavior of a bouncing droplet above the Faraday threshold, where a stochastic element is introduced into the drop dynamics by virtue of its interaction with a background Faraday wave field. With a view to extending the dynamical range of pilot-wave systems to capture more quantum-like features, we consider a generalized theoretical framework for stochastic pilot-wave dynamics in which the relative magnitudes of the drop-generated pilot-wave field and a stochastic background field may be varied continuously. We gratefully acknowledge the financial support of the NSF through their CMMI and DMS divisions.

Collaborative Research Program on Advanced Metals and Ceramics for Armor and Anti-Armor Applications Dynamic Behavior of Non-Crystalline and Crystalline Metallic Systems

DTIC Science & Technology

2006-09-01

compression, including real-time cinematography of failure under dynamic compression, was evaluated. The results (figure 10) clearly show that the failure... art of simulations of dynamic failure and damage mechanisms. An explicit dynamic parallel code has been developed to track damage mechanisms in the

Behavioral Priming 2.0: Enter a Dynamical Systems Perspective

PubMed Central

Krpan, Dario

2017-01-01

On a daily basis, people are exposed to numerous stimuli, ranging from colors and smells to sounds and words, that could potentially activate different cognitive constructs and influence their actions. This type of influence on human behavior is referred to as priming. Roughly two decades ago, behavioral priming was hailed as one of the core forces that shape automatic behavior. However, failures to replicate some of the representative findings in this domain soon followed, which posed the following question: “How robust are behavioral priming effects, and to what extent are they actually important in shaping people's actions?” To shed a new light on this question, I revisit behavioral priming through the prism of a dynamical systems perspective (DSP). The DSP is a scientific paradigm that has been developed through a combined effort of many different academic disciplines, ranging from mathematics and physics to biology, economics, psychology, etc., and it deals with behavior of simple and complex systems over time. In the present paper, I use conceptual and methodological tools stemming from the DSP to propose circumstances under which behavioral priming effects are likely to occur. More precisely, I outline three possible types of the influence of priming on human behavior, to which I refer as emergence, readjustment, and attractor switch, and propose experimental designs to examine them. Finally, I discuss relevant implications for behavioral priming effects and their replications. PMID:28769846

Dynamics of Robertson–Walker spacetimes with diffusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alho, A., E-mail: aalho@math.ist.utl.pt; Calogero, S., E-mail: calogero@chalmers.se; Machado Ramos, M.P., E-mail: mpr@mct.uminho.pt

2015-03-15

We study the dynamics of spatially homogeneous and isotropic spacetimes containing a fluid undergoing microscopic velocity diffusion in a cosmological scalar field. After deriving a few exact solutions of the equations, we continue by analyzing the qualitative behavior of general solutions. To this purpose we recast the equations in the form of a two dimensional dynamical system and perform a global analysis of the flow. Among the admissible behaviors, we find solutions that are asymptotically de-Sitter both in the past and future time directions and which undergo accelerated expansion at all times.

Dynamic behavior of the mechanical systems from the structure of a hybrid automobile

NASA Astrophysics Data System (ADS)

Dinel, Popa; Irina, Tudor; Nicolae-Doru, Stănescu

2017-10-01

In introduction are presented solutions of planetary mechanisms that can be used in the construction of the hybrid automobiles where the thermal and electrical sources must be coupled. The systems have in their composition a planetary mechanism with two degrees of mobility at which are coupled a thermal engine, two revertible electrical machines, a gear transmission with four gears and a differential mechanism which transmits the motion at the driving wheels. For the study of the dynamical behavior, with numerical results, one designs such mechanisms, models the elements with solids in AutoCAD, and obtains the mechanical properties of the elements. Further on, we present and solve the equations of motion of a hybrid automotive for which one knows the dynamical parameters.

A Qualitative Model of Human Interaction with Complex Dynamic Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

A qualitative model of human interaction with complex dynamic systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

An integrated approach to evaluate policies for controlling traffic law violations.

PubMed

Mehmood, Arif

2010-03-01

Modeling dynamics of the driver behavior is a complex problem. In this paper a system approach is introduced to model and to analyze the driver behavior related to traffic law violations in the Emirate of Abu Dhabi. This paper demonstrates how the theoretical relationships between different factors can be expressed formally, and how the resulting model can assist in evaluating potential benefits of various policies to control the traffic law violations Using system approach, an integrated dynamic simulation model is developed, and model is tested to simulate the driver behavior for violating traffic laws during 2002-2007 in the Emirate of Abu Dhabi. The dynamic simulation model attempts to address the questions: (1) "what" interventions should be implemented to reduce and eventually control traffic violations which will lead to improving road safety and (2) "how" to justify those interventions will be effective or ineffective to control the violations in different transportation conditions. The simulation results reveal promising capability of applying system approach in the policy evaluation studies. Copyright 2009 Elsevier Ltd. All rights reserved.

Mode-coupling of interaction quenched ultracold bosons in periodically driven lattices

NASA Astrophysics Data System (ADS)

Mistakidis, Simeon; Schmelcher, Peter

2016-05-01

The out-of-equilibrium dynamics of interaction quenched finite ultracold bosonic ensembles in periodically driven one-dimensional optical lattices is investigated. As a first attempt a brief analysis of the dynamics caused exclusively by the periodically driven lattice is presented and the induced low-lying modes are introduced. It is shown that the periodic driving enforces the bosons in the outer wells to exhibit out-of-phase dipole-like modes, while in the central well the cloud experiences a local-breathing mode. The dynamical behavior of the system is investigated with respect to the driving frequency, revealing a resonant-like behavior of the intra-well dynamics. Subsequently, we drive the system to a highly non-equilibrium state by performing an interaction quench upon the periodically driven lattice. This protocol gives rise to admixtures of excitations in the outer wells, an enhanced breathing in the center and an amplification of the tunneling dynamics. As a result (of the quench) the system experiences multiple resonances between the inter- and intra-well dynamics at different quench amplitudes. Finally, our study reveals that the position of the resonances can be adjusted e.g. via the driving frequency or the atom number manifesting their many-body nature. Deutsche Forschungsgemeinschaft (DFG) in the framework of the SFB 925 ``Light induced dynamics and control of correlated quantum systems''.

Agent-based modeling in ecological economics.

PubMed

Heckbert, Scott; Baynes, Tim; Reeson, Andrew

2010-01-01

Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

Mother-Infant Dyadic State Behaviour: Dynamic Systems in the Context of Risk

ERIC Educational Resources Information Center

Coburn, Shayna S.; Crnic, Keith A.; Ross, Emily K.

2015-01-01

Dynamic systems methods offer invaluable insight into the nuances of the early parent-child relationship. This prospective study aimed to highlight the characteristics of mother-infant dyadic behavior at 12?weeks post-partum using state space grid analysis (total n?=?322). We also examined whether maternal prenatal depressive symptoms and…

Toward a Comprehensive Model of Antisocial Development: A Dynamic Systems Approach

ERIC Educational Resources Information Center

Granic, Isabela; Patterson, Gerald R.

2006-01-01

The purpose of this article is to develop a preliminary comprehensive model of antisocial development based on dynamic systems principles. The model is built on the foundations of behavioral research on coercion theory. First, the authors focus on the principles of multistability, feedback, and nonlinear causality to reconceptualize real-time…

Hybrid computers and simulation languages in the study of dynamics of continuous systems

NASA Technical Reports Server (NTRS)

Acaccia, G. M.; Lucifredi, A. L.

1970-01-01

A comparison is presented of the use of hybrid computers and simulation languages as a means of studying the behavior of dynamic systems. Both procedures are defined and their advantages and disadvantages at the present state of the art are discussed. Some comparison and evaluation criteria are presented.

Triple grouping and period-three oscillations in minority-game dynamics.

PubMed

Dong, Jia-Qi; Huang, Zi-Gang; Huang, Liang; Lai, Ying-Cheng

2014-12-01

Dynamical systems based on the minority game (MG) have been a paradigm for gaining significant insights into a variety of social and biological behaviors. Recently, a grouping phenomenon has been unveiled in MG systems of multiple resources (strategies) in which the strategies spontaneously break into an even number of groups, each exhibiting an identical oscillation pattern in the attendance of game players. Here we report our finding of spontaneous breakup of resources into three groups, each exhibiting period-three oscillations. An analysis is developed to understand the emergence of the striking phenomenon of triple grouping and period-three oscillations. In the presence of random disturbances, the triple-group/period-three state becomes transient, and we obtain explicit formula for the average transient lifetime using two methods of approximation. Our finding indicates that, period-three oscillation, regarded as one of the most fundamental behaviors in smooth nonlinear dynamical systems, can also occur in much more complex, evolutionary-game dynamical systems. Our result also provides a plausible insight for the occurrence of triple grouping observed, for example, in the U.S. housing market.

Complex Dynamical Behavior in Hybrid Systems

DTIC Science & Technology

2012-09-29

stability for a class of hybrid dynamical systems via averaging”, Mathematics of Control , Signals, and Systems , vol. 23, no. 4, pp...no. 7, pp. 1636-1649, 2011. J9. A.R. Teel and L. Marconi, `` Stabilization for a class of minimum phase hybrid systems under an average dwell- time ...functions for L2 and input-to-state stability in a class of quantized control systems ”, 50th IEEE Conference on Decision and Control , Dec.

Nouvelles techniques pratiques pour la modelisation du comportement dynamique des systèmes eau-structure

NASA Astrophysics Data System (ADS)

Miquel, Benjamin

The dynamic or seismic behavior of hydraulic structures is, as for conventional structures, essential to assure protection of human lives. These types of analyses also aim at limiting structural damage caused by an earthquake to prevent rupture or collapse of the structure. The particularity of these hydraulic structures is that not only the internal displacements are caused by the earthquake, but also by the hydrodynamic loads resulting from fluid-structure interaction. This thesis reviews the existing complex and simplified methods to perform such dynamic analysis for hydraulic structures. For the complex existing methods, attention is placed on the difficulties arising from their use. Particularly, interest is given in this work on the use of transmitting boundary conditions to simulate the semi infinity of reservoirs. A procedure has been developed to estimate the error that these boundary conditions can introduce in finite element dynamic analysis. Depending on their formulation and location, we showed that they can considerably affect the response of such fluid-structure systems. For practical engineering applications, simplified procedures are still needed to evaluate the dynamic behavior of structures in contact with water. A review of the existing simplified procedures showed that these methods are based on numerous simplifications that can affect the prediction of the dynamic behavior of such systems. One of the main objectives of this thesis has been to develop new simplified methods that are more accurate than those existing. First, a new spectral analysis method has been proposed. Expressions for the fundamental frequency of fluid-structure systems, key parameter of spectral analysis, have been developed. We show that this new technique can easily be implemented in a spreadsheet or program, and that its calculation time is near instantaneous. When compared to more complex analytical or numerical method, this new procedure yields excellent prediction of the dynamic behavior of fluid-structure systems. Spectral analyses ignore the transient and oscillatory nature of vibrations. When such dynamic analyses show that some areas of the studied structure undergo excessive stresses, time history analyses allow a better estimate of the extent of these zones as well as a time notion of these excessive stresses. Furthermore, the existing spectral analyses methods for fluid-structure systems account only for the static effect of higher modes. Thought this can generally be sufficient for dams, for flexible structures the dynamic effect of these modes should be accounted for. New methods have been developed for fluid-structure systems to account for these observations as well as the flexibility of foundations. A first method was developed to study structures in contact with one or two finite or infinite water domains. This new technique includes flexibility of structures and foundations as well as the dynamic effect of higher vibration modes and variations of the levels of the water domains. Extension of this method was performed to study beam structures in contact with fluids. These new developments have also allowed extending existing analytical formulations of the dynamic properties of a dry beam to a new formulation that includes effect of fluid-structure interaction. The method yields a very good estimate of the dynamic behavior of beam-fluid systems or beam like structures in contact with fluid. Finally, a Modified Accelerogram Method (MAM) has been developed to modify the design earthquake into a new accelerogram that directly accounts for the effect of fluid-structure interaction. This new accelerogram can therefore be applied directly to the dry structure (i.e. without water) in order to calculate the dynamic response of the fluid-structure system. This original technique can include numerous parameters that influence the dynamic response of such systems and allows to treat analytically the fluid-structure interaction while keeping the advantages of finite element modeling.

Dynamics of Variable Mass Systems

NASA Technical Reports Server (NTRS)

Eke, Fidelis O.

1998-01-01

This report presents the results of an investigation of the effects of mass loss on the attitude behavior of spinning bodies in flight. The principal goal is to determine whether there are circumstances under which the motion of variable mass systems can become unstable in the sense that their transverse angular velocities become unbounded. Obviously, results from a study of this kind would find immediate application in the aerospace field. The first part of this study features a complete and mathematically rigorous derivation of a set of equations that govern both the translational and rotational motions of general variable mass systems. The remainder of the study is then devoted to the application of the equations obtained to a systematic investigation of the effect of various mass loss scenarios on the dynamics of increasingly complex models of variable mass systems. It is found that mass loss can have a major impact on the dynamics of mechanical systems, including a possible change in the systems stability picture. Factors such as nozzle geometry, combustion chamber geometry, propellant's initial shape, size and relative mass, and propellant location can all have important influences on the system's dynamic behavior. The relative importance of these parameters on-system motion are quantified in a way that is useful for design purposes.

Inclusion Complexes Behavior at the Air-Water Interface. Molecular Dynamic Simulation Study.

NASA Astrophysics Data System (ADS)

Gargallo, L.; Vargas, D.; Sandoval, C.; Saavedra, M.; Becerra, N.; Leiva, A.; Radić, D.

2008-08-01

The interfacial properties of the inclusion complexes (ICs), obtained from the threading of α-cyclodextrin (α-CD) onto poly(ethylene-oxide)(PEO), poly(ɛ-caprolactone)(PEC) and poly(tetrahydrofuran)(PTHF) and their precursor homopolymers (PHPoly), were studied at the air-water interface. The free surface energy was determined by wettability measurements. The experimental behavior of these systems was described by an atomistic molecular dynamics simulation (MDS).

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Intermittency and dynamical Lee-Yang zeros of open quantum systems.

PubMed

Hickey, James M; Flindt, Christian; Garrahan, Juan P

2014-12-01

We use high-order cumulants to investigate the Lee-Yang zeros of generating functions of dynamical observables in open quantum systems. At long times the generating functions take on a large-deviation form with singularities of the associated cumulant generating functions-or dynamical free energies-signifying phase transitions in the ensemble of dynamical trajectories. We consider a driven three-level system as well as the dissipative Ising model. Both systems exhibit dynamical intermittency in the statistics of quantum jumps. From the short-time behavior of the dynamical Lee-Yang zeros, we identify critical values of the counting field which we attribute to the observed intermittency and dynamical phase coexistence. Furthermore, for the dissipative Ising model we construct a trajectory phase diagram and estimate the value of the transverse field where the stationary state changes from being ferromagnetic (inactive) to paramagnetic (active).

Detection and Learning of Unexpected Behaviors of Systems of Dynamical Systems by Using the Q2 Abstractions

DTIC Science & Technology

2017-11-01

Finite State Machine ............................................... 21 9 Main Ontological Concepts for Representing Structure of a Multi -Agent...19 NetLogo Simulation of persistent surveillance of circular plume by 4 UAVs ........................36 20 Flocking Emergent Behaviors in Multi -UAV...Region) - Undesirable Group Formation ................................................................................... 40 24 Two UAVs Moving in

Modeling and simulation of dust behaviors behind a moving vehicle

NASA Astrophysics Data System (ADS)

Wang, Jingfang

Simulation of physically realistic complex dust behaviors is a difficult and attractive problem in computer graphics. A fast, interactive and visually convincing model of dust behaviors behind moving vehicles is very useful in computer simulation, training, education, art, advertising, and entertainment. In my dissertation, an experimental interactive system has been implemented for the simulation of dust behaviors behind moving vehicles. The system includes physically-based models, particle systems, rendering engines and graphical user interface (GUI). I have employed several vehicle models including tanks, cars, and jeeps to test and simulate in different scenarios and conditions. Calm weather, winding condition, vehicle turning left or right, and vehicle simulation controlled by users from the GUI are all included. I have also tested the factors which play against the physical behaviors and graphics appearances of the dust particles through GUI or off-line scripts. The simulations are done on a Silicon Graphics Octane station. The animation of dust behaviors is achieved by physically-based modeling and simulation. The flow around a moving vehicle is modeled using computational fluid dynamics (CFD) techniques. I implement a primitive variable and pressure-correction approach to solve the three dimensional incompressible Navier Stokes equations in a volume covering the moving vehicle. An alternating- direction implicit (ADI) method is used for the solution of the momentum equations, with a successive-over- relaxation (SOR) method for the solution of the Poisson pressure equation. Boundary conditions are defined and simplified according to their dynamic properties. The dust particle dynamics is modeled using particle systems, statistics, and procedure modeling techniques. Graphics and real-time simulation techniques, such as dynamics synchronization, motion blur, blending, and clipping have been employed in the rendering to achieve realistic appearing dust behaviors. In addition, I introduce a temporal smoothing technique to eliminate the jagged effect caused by large simulation time. Several algorithms are used to speed up the simulation. For example, pre-calculated tables and display lists are created to replace some of the most commonly used functions, scripts and processes. The performance study shows that both time and space costs of the algorithms are linear in the number of particles in the system. On a Silicon Graphics Octane, three vehicles with 20,000 particles run at 6-8 frames per second on average. This speed does not include the extra calculations of convergence of the numerical integration for fluid dynamics which usually takes about 4-5 minutes to achieve steady state.

Organization of excitable dynamics in hierarchical biological networks.

PubMed

Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten

2008-09-26

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

Study of tethered satellite active attitude control

NASA Technical Reports Server (NTRS)

Colombo, G.

1982-01-01

Existing software was adapted for the study of tethered subsatellite rotational dynamics, an analytic solution for a stable configuration of a tethered subsatellite was developed, the analytic and numerical integrator (computer) solutions for this "test case' was compared in a two mass tether model program (DUMBEL), the existing multiple mass tether model (SKYHOOK) was modified to include subsatellite rotational dynamics, the analytic "test case,' was verified, and the use of the SKYHOOK rotational dynamics capability with a computer run showing the effect of a single off axis thruster on the behavior of the subsatellite was demonstrated. Subroutines for specific attitude control systems are developed and applied to the study of the behavior of the tethered subsatellite under realistic on orbit conditions. The effect of all tether "inputs,' including pendular oscillations, air drag, and electrodynamic interactions, on the dynamic behavior of the tether are included.

Effect of Glycerol Water Binary Mixtures on the Structure and Dynamics of Protein Solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghattyvenkatakrishna, Pavan K; Carri, Gustavo A.

We have performed 20ns of fully atomistic molecular dynamics simulations of Hen Egg-White Lysozyme in 0, 10, 20, 30 and 100% by weight of glycerol in water to better understand the microscopic physics behind the bioprotection offered by glycerol to naturally occuring biological systems. The sovlent exposure of protein surface residues changes when glycerol is introduced. The dynamic behavior of the protein, as quantified by the Incoherent Intermediate Scattering Function, shows a non-monotonic dependence on glycerol content. The fluctuations of the protein residues with respect to each other were found to be similar in all water containing solvents; but differentmore » from the pure glycerol case. The increase in the number of protein glycerol hydrogen bonds in glycerol water binary mixtures explains the slowing down of protein dynamics as the glycerol content increases. We also explored the dynamic behavior of the hydration layer. We show that the short-length scale dynamics of this layer are insenstive to glycerol concentration. However, the long-length scale behavior shows a significant dependence on glycerol content. We also provide insights into the behavior of bound and mobile water molecules.« less

Heterogeneity and Self-Organization of Complex Systems Through an Application to Financial Market with Multiagent Systems

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

2017-12-01

Multiagent systems (MAS) provide a useful tool for exploring the complex dynamics and behavior of financial markets and now MAS approach has been widely implemented and documented in the empirical literature. This paper introduces the implementation of an innovative multi-scale mathematical model for a computational agent-based financial market. The paper develops a method to quantify the degree of self-organization which emerges in the system and shows that the capacity of self-organization is maximized when the agent behaviors are heterogeneous. Numerical results are presented and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.

Transition Manifolds of Complex Metastable Systems: Theory and Data-Driven Computation of Effective Dynamics.

PubMed

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-01-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Can a simple dynamical system describe the interplay between drag and buoyancy in terrain-induced canopy flows?

NASA Astrophysics Data System (ADS)

De Roo, Frederik; Banerjee, Tirtha

2017-04-01

Under non-neutral conditions and in the presence of topography the dynamics of turbulent flow within a canopy is not yet completely understood. This has implications for the measurement of surface-atmosphere exchange by means of eddy-covariance. For example the measurement of carbon dioxide fluxes are strongly influenced if drainage flows happen during night, when the flow within the canopy decouples from the flow aloft. In the present work, we investigate the dynamics of terrain-induced turbulent flow within sloped canopies. We concentrate on the presence of oscillatory behavior in the flow variables in terms of switching of flow regimes by conducting linear stability analysis. We revisit and correct the simplified theory that exists in the literature, which is based on the interplay between the drag force and the buoyancy. We find that the simplified description of this dynamical system cannot exhibit the observed richness of the dynamics. To tackle the full spatiotemporal dynamical system theoretically is beyond the scope of this work, although we can make some qualitative arguments. Additionally, we make use of large-eddy simulation of a three-dimensional hill covered by a homogeneous forest and analyze phase synchronization behavior of the major terms in the momentum budget to explore the turbulent dynamics in more detail.

Nonlinear dynamic behaviors of permanent magnet synchronous motors in electric vehicles caused by unbalanced magnetic pull

NASA Astrophysics Data System (ADS)

Xiang, Changle; Liu, Feng; Liu, Hui; Han, Lijin; Zhang, Xun

2016-06-01

Unbalanced magnetic pull (UMP) plays a key role in nonlinear dynamic behaviors of permanent magnet synchronous motors (PMSM) in electric vehicles. Based on Jeffcott rotor model, the stiffness characteristics of the rotor system of the PMSM are analyzed and the nonlinear dynamic behaviors influenced by UMP are investigated. In free vibration study, eigenvalue-based stability analysis for multiple equilibrium points is performed which offers an insight in system stiffness. Amplitude modulation effects are discovered of which the mechanism is explained and the period of modulating signal is carried out by phase analysis and averaging method. The analysis indicates that the effects are caused by the interaction of the initial phases of forward and backward whirling motions. In forced vibration study, considering dynamic eccentricity, frequency characteristics revealing softening type are obtained by harmonic balance method, and the stability of periodic solution is investigated by Routh-Hurwitz criterion. The frequency characteristics analysis indicates that the response amplitude is limited in the range between the amplitudes of the two kinds of equilibrium points. In the vicinity of the continuum of equilibrium points, the system hardly provides resistance to bending, and hence external disturbances easily cause loss of stability. It is useful for the design of the PMSM with high stability and low vibration and acoustic noise.

Towards classification of the bifurcation structure of a spherical cavitation bubble.

PubMed

Behnia, Sohrab; Sojahrood, Amin Jafari; Soltanpoor, Wiria; Sarkhosh, Leila

2009-12-01

We focus on a single cavitation bubble driven by ultrasound, a system which is a specimen of forced nonlinear oscillators and is characterized by its extreme sensitivity to the initial conditions. The driven radial oscillations of the bubble are considered to be implicated by the principles of chaos physics and owing to specific ranges of control parameters, can be periodic or chaotic. Despite the growing number of investigations on its dynamics, there is not yet an inclusive yardstick to sort the dynamical behavior of the bubble into classes; also, the response oscillations are so complex that long term prediction on the behavior becomes difficult to accomplish. In this study, the nonlinear dynamics of a bubble oscillator was treated numerically and the simulations were proceeded with bifurcation diagrams. The calculated bifurcation diagrams were compared in an attempt to classify the bubble dynamic characteristics when varying the control parameters. The comparison reveals distinctive bifurcation patterns as a consequence of driving the systems with unequal ratios of R(0)lambda (where R(0) is the bubble initial radius and lambda is the wavelength of the driving ultrasonic wave). Results indicated that systems having the equal ratio of R(0)lambda, share remarkable similarities in their bifurcating behavior and can be classified under a unit category.

The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

PubMed Central

Srinivasa, Narayan; Stepp, Nigel D.; Cruz-Albrecht, Jose

2015-01-01

Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it. PMID:26648839

Sensory flow shaped by active sensing: sensorimotor strategies in electric fish.

PubMed

Hofmann, Volker; Sanguinetti-Scheck, Juan I; Künzel, Silke; Geurten, Bart; Gómez-Sena, Leonel; Engelmann, Jacob

2013-07-01

Goal-directed behavior in most cases is composed of a sequential order of elementary motor patterns shaped by sensorimotor contingencies. The sensory information acquired thus is structured in both space and time. Here we review the role of motion during the generation of sensory flow focusing on how animals actively shape information by behavioral strategies. We use the well-studied examples of vision in insects and echolocation in bats to describe commonalities of sensory-related behavioral strategies across sensory systems, and evaluate what is currently known about comparable active sensing strategies in electroreception of electric fish. In this sensory system the sensors are dispersed across the animal's body and the carrier source emitting energy used for sensing, the electric organ, is moved while the animal moves. Thus ego-motions strongly influence sensory dynamics. We present, for the first time, data of electric flow during natural probing behavior in Gnathonemus petersii (Mormyridae), which provide evidence for this influence. These data reveal a complex interdependency between the physical input to the receptors and the animal's movements, posture and objects in its environment. Although research on spatiotemporal dynamics in electrolocation is still in its infancy, the emerging field of dynamical sensory systems analysis in electric fish is a promising approach to the study of the link between movement and acquisition of sensory information.

Simulation of noisy dynamical system by Deep Learning

NASA Astrophysics Data System (ADS)

Yeo, Kyongmin

2017-11-01

Deep learning has attracted huge attention due to its powerful representation capability. However, most of the studies on deep learning have been focused on visual analytics or language modeling and the capability of the deep learning in modeling dynamical systems is not well understood. In this study, we use a recurrent neural network to model noisy nonlinear dynamical systems. In particular, we use a long short-term memory (LSTM) network, which constructs internal nonlinear dynamics systems. We propose a cross-entropy loss with spatial ridge regularization to learn a non-stationary conditional probability distribution from a noisy nonlinear dynamical system. A Monte Carlo procedure to perform time-marching simulations by using the LSTM is presented. The behavior of the LSTM is studied by using noisy, forced Van der Pol oscillator and Ikeda equation.

Political Dynamics Affected by Turncoats

NASA Astrophysics Data System (ADS)

Di Salvo, Rosa; Gorgone, Matteo; Oliveri, Francesco

2017-11-01

An operatorial theoretical model based on raising and lowering fermionic operators for the description of the dynamics of a political system consisting of macro-groups affected by turncoat-like behaviors is presented. The analysis of the party system dynamics is carried on by combining the action of a suitable quadratic Hamiltonian operator with specific rules (depending on the variations of the mean values of the observables) able to adjust periodically the conservative model to the political environment.

Comprehensive dynamic analysis of a bladed disk-turborotor-bearing system

NASA Astrophysics Data System (ADS)

Kaushal, Ashok

The dynamic behavior of a bladed disk-turborotor-bearing system is studied employing analytical, numerical, and experimental methods. The system consists of several subsystems such as turbine disk, blades, bearings, support pedestals etc. In order to completely understand the dynamic behavior of the turborotor system an appropriate model for each individual component of the system is first developed. The individual components are modeled to include various design parameters and the effect of these parameters on the vibrational behavior is studied. The vibration studies on the individual components are carried out using Rayleigh-Ritz method boundary characteristic orthogonal polynomials as assumed shape functions. The individual components are then assembled using the finite element technique. The turborotor system is studied from a system point of view and the natural frequencies and mode shapes are obtained for various rotational speeds. The results show that the natural frequencies of the system are different from those obtained by analyzing individual components, suggesting that a system approach must be adopted for proper design of a turborotor system. The amplitude of vibration and stresses due to harmonic and centrifugal loading on the blades and the disk are also obtained. The results indicate that for the turborotor speed of operation, the centrifugal loading is the major factor in determining the critical stresses in comparison to the gas forces on the blade modeled as harmonic loading. Experimental validation of the analytical model is carried out and suggestions for future work are given.

Post-Markovian dynamics of quantum correlations: entanglement versus discord

NASA Astrophysics Data System (ADS)

Mohammadi, Hamidreza

2017-02-01

Dynamics of an open two-qubit system is investigated in the post-Markovian regime, where the environments have a short-term memory. Each qubit is coupled to separate environment which is held in its own temperature. The inter-qubit interaction is modeled by XY-Heisenberg model in the presence of spin-orbit interaction and inhomogeneous magnetic field. The dynamical behavior of entanglement and discord has been considered. The results show that quantum discord is more robust than quantum entanglement, during the evolution. Also the asymmetric feature of quantum discord can be monitored by introducing the asymmetries due to inhomogeneity of magnetic field and temperature difference between the reservoirs. By employing proper parameters of the model, it is possible to maintain nonvanishing quantum correlation at high degree of temperature. The results can provide a useful recipe for studying dynamical behavior of two-qubit systems such as trapped spin electrons in coupled quantum dots.

Nonlinear dynamics of the magnetosphere and space weather

NASA Technical Reports Server (NTRS)

Sharma, A. Surjalal

1996-01-01

The solar wind-magnetosphere system exhibits coherence on the global scale and such behavior can arise from nonlinearity on the dynamics. The observational time series data were used together with phase space reconstruction techniques to analyze the magnetospheric dynamics. Analysis of the solar wind, auroral electrojet and Dst indices showed low dimensionality of the dynamics and accurate prediction can be made with an input/output model. The predictability of the magnetosphere in spite of the apparent complexity arises from its dynamical synchronism with the solar wind. The electrodynamic coupling between different regions of the magnetosphere yields its coherent, low dimensional behavior. The data from multiple satellites and ground stations can be used to develop a spatio-temporal model that identifies the coupling between different regions. These nonlinear dynamical models provide space weather forecasting capabilities.

Applying differential dynamic logic to reconfigurable biological networks.

PubMed

Figueiredo, Daniel; Martins, Manuel A; Chaves, Madalena

2017-09-01

Qualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used. Copyright © 2017 Elsevier Inc. All rights reserved.

Chaos as a psychological construct: historical roots, principal findings, and current growth directions.

PubMed

Guastello, Stephen J

2009-07-01

The landmarks in the use of chaos and related constructs in psychology were entwined with the growing use of other nonlinear dynamical constructs, especially catastrophes and self-organization. The growth in substantive applications of chaos in psychology is partially related to the development of methodologies that work within the constraints of psychological data. The psychological literature includes rigorous theory with testable propositions, lighter-weight metaphorical uses of the construct, and colloquial uses of "chaos" with no particular theoretical intent. The current state of the chaos construct and supporting empirical research in psychological theory is summarized in neuroscience, psychophysics, psychomotor skill and other learning phenomena, clinical and abnormal psychology, and group dynamics and organizational behavior. Trends indicate that human systems do not remain chaotic indefinitely; they eventually self-organize, and the concept of the complex adaptive system has become prominent. Chaotic turbulence is generally higher in healthy systems compared to unhealthy systems, although opposite appears true in mood disorders. Group dynamics research shows trends consistent with the complex adaptive system, whereas organizational behavior lags behind in empirical studies relative to the quantity of its theory. Future directions for research involving the chaos construct and other nonlinear dynamics are outlined.

Nonlinear optimal control for the synchronization of chaotic and hyperchaotic finance systems

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Ademi, S.; Ghosh, T.

2017-11-01

It is possible to make specific finance systems get synchronized to other finance systems exhibiting chaotic and hyperchaotic dynamics, by applying nonlinear optimal (H-infinity) control. This signifies that chaotic behavior can be generated in finance systems by exerting a suitable control input. Actually, a lead financial system is considered which exhibits inherently chaotic dynamics. Moreover, a follower finance system is introduced having parameters in its model that inherently prohibit the appearance of chaotic dynamics. Through the application of a suitable nonlinear optimal (H-infinity) control input it is proven that the follower finance system can replicate the chaotic dynamics of the lead finance system. By applying Lyapunov analysis it is proven that asymptotically the follower finance system gets synchronized with the lead system and that the tracking error between the state variables of the two systems vanishes.

Long-term influence of asteroids on planet longitudes and chaotic dynamics of the solar system

NASA Astrophysics Data System (ADS)

Woillez, E.; Bouchet, F.

2017-11-01

Over timescales much longer than an orbital period, the solar system exhibits large-scale chaotic behavior and can thus be viewed as a stochastic dynamical system. The aim of the present paper is to compare different sources of stochasticity in the solar system. More precisely we studied the importance of the long term influence of asteroids on the chaotic dynamics of the solar system. We show that the effects of asteroids on planets is similar to a white noise process, when those effects are considered on a timescale much larger than the correlation time τϕ ≃ 104 yr of asteroid trajectories. We computed the timescale τe after which the effects of the stochastic evolution of the asteroids lead to a loss of information for the initial conditions of the perturbed Laplace-Lagrange secular dynamics. The order of magnitude of this timescale is precisely determined by theoretical argument, and we find that τe ≃ 104 Myr. Although comparable to the full main-sequence lifetime of the sun, this timescale is considerably longer than the Lyapunov time τI ≃ 10 Myr of the solar system without asteroids. This shows that the external sources of chaos arise as a small perturbation in the stochastic secular behavior of the solar system, rather due to intrinsic chaos.

Local disturbance cycles and the maintenance of heterogeneity across scales in marine metapopulations.

PubMed

Gouhier, Tarik C; Guichard, Frédéric

2007-03-01

In marine systems, the occurrence and implications of disturbance-recovery cycles have been revealed at the landscape level, but only in demographically open or closed systems where landscape-level dynamics are assumed to have no feedback effect on regional dynamics. We present a mussel metapopulation model to elucidate the role of landscape-level disturbance cycles for regional response of mussel populations to onshore productivity and larval transport. Landscape dynamics are generated through spatially explicit rules, and each landscape is connected to its neighbor through unidirectional larval dispersal. The role of landscape disturbance cycles in the regional system behavior is elucidated (1) in demographically open vs. demographically coupled systems, in relation to (2) onshore reproductive output and (3) the temporal scale of landscape disturbance dynamics. By controlling for spatial structure at the landscape and metapopulation levels, we first demonstrate the interaction between landscape and oceanographic connectivity. The temporal scale of disturbance cycles, as controlled by mussel colonization rate, plays a critical role in the regional behavior of the system. Indeed, fast disturbance cycles are responsible for regional synchrony in relation to onshore reproductive output. Slow disturbance cycles, however, lead to increased robustness to changes in productivity and to demographic coupling. These testable predictions indicate that the occurrence and temporal scale of local disturbance-recovery dynamics can drive large-scale variability in demographically open systems, and the response of metapopulations to changes in nearshore productivity.

Toward experimental validation of a model for human sensorimotor learning and control in teleoperation

NASA Astrophysics Data System (ADS)

Roth, Eatai; Howell, Darrin; Beckwith, Cydney; Burden, Samuel A.

2017-05-01

Humans, interacting with cyber-physical systems (CPS), formulate beliefs about the system's dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human-cyber-physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system's dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator's ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.

Analysis Methodologies and Ameliorative Techniques for Mitigation of the Risk in Churches with Drum Domes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zingone, Gaetano; Licata, Vincenzo; Calogero, Cucchiara

2008-07-08

The present work fits into the interesting theme of seismic prevention for protection of the monumental patrimony made up of churches with drum domes. Specifically, with respect to a church in the historic area of Catania, chosen as a monument exemplifying the typology examined, the seismic behavior is analyzed in the linear field using modern dynamic identification techniques. The dynamically identified computational model arrived at made it possible to identify the macro-element most at risk, the dome-drum system. With respect to this system the behavior in the nonlinear field is analyzed through dynamic tests on large-scale models in the presencemore » of various types of improving reinforcement. The results are used to appraise the ameliorative contribution afforded by each of them and to choose the most suitable type of reinforcement, optimizing the stiffness/ductility ratio of the system.« less

Zero-Field Ambient-Pressure Quantum Criticality in the Stoichiometric Non-Fermi Liquid System CeRhBi

NASA Astrophysics Data System (ADS)

Anand, Vivek K.; Adroja, Devashibhai T.; Hillier, Adrian D.; Shigetoh, Keisuke; Takabatake, Toshiro; Park, Je-Geun; McEwen, Keith A.; Pixley, Jedediah H.; Si, Qimiao

2018-06-01

We present the spin dynamics study of a stoichiometric non-Fermi liquid (NFL) system CeRhBi, using low-energy inelastic neutron scattering (INS) and muon spin relaxation (μSR) measurements. It shows evidence for an energy-temperature (E/T) scaling in the INS dynamic response and a time-field (t/Hη) scaling of the μSR asymmetry function indicating a quantum critical behavior in this compound. The E/T scaling reveals a local character of quantum criticality consistent with the power-law divergence of the magnetic susceptibility, logarithmic divergence of the magnetic heat capacity and T-linear resistivity at low temperature. The occurrence of NFL behavior and local criticality over a very wide dynamical range at zero field and ambient pressure without any tuning in this stoichiometric heavy fermion compound is striking, making CeRhBi a model system amenable to in-depth studies for quantum criticality.

Complexity multiscale asynchrony measure and behavior for interacting financial dynamics

NASA Astrophysics Data System (ADS)

Yang, Ge; Wang, Jun; Niu, Hongli

2016-08-01

A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.

Phase Transition of a Dynamical System with a Bi-Directional, Instantaneous Coupling to a Virtual System

NASA Astrophysics Data System (ADS)

Gintautas, Vadas; Hubler, Alfred

2006-03-01

As worldwide computer resources increase in power and decrease in cost, real-time simulations of physical systems are becoming increasingly prevalent, from laboratory models to stock market projections and entire ``virtual worlds'' in computer games. Often, these systems are meticulously designed to match real-world systems as closely as possible. We study the limiting behavior of a virtual horizontally driven pendulum coupled to its real-world counterpart, where the interaction occurs on a time scale that is much shorter than the time scale of the dynamical system. We find that if the physical parameters of the virtual system match those of the real system within a certain tolerance, there is a qualitative change in the behavior of the two-pendulum system as the strength of the coupling is increased. Applications include a new method to measure the physical parameters of a real system and the use of resonance spectroscopy to refine a computer model. As virtual systems better approximate real ones, even very weak interactions may produce unexpected and dramatic behavior. The research is supported by the National Science Foundation Grant No. NSF PHY 01-40179, NSF DMS 03-25939 ITR, and NSF DGE 03-38215.

Many-body dynamics of chemically propelled nanomotors

NASA Astrophysics Data System (ADS)

Colberg, Peter H.; Kapral, Raymond

2017-08-01

The collective behavior of chemically propelled sphere-dimer motors made from linked catalytic and noncatalytic spheres in a quasi-two-dimensional confined geometry is studied using a coarse-grained microscopic dynamical model. Chemical reactions at the catalytic spheres that convert fuel to product generate forces that couple to solvent degrees of freedom as a consequence of momentum conservation in the microscopic dynamics. The collective behavior of the many-body system is influenced by direct intermolecular interactions among the motors, chemotactic effects due to chemical gradients, hydrodynamic coupling, and thermal noise. Segregation into high and low density phases and globally homogeneous states with strong fluctuations are investigated as functions of the motor characteristics. Factors contributing to this behavior are discussed in the context of active Brownian models.

Development and Validation of a Bioreactor System for Dynamic Loading and Mechanical Characterization of Whole Human Intervertebral Discs in Organ Culture

PubMed Central

Walter, BA; Illien-Junger, S; Nasser, P; Hecht, AC; Iatridis, JC

2014-01-01

Intervertebral disc (IVD) degeneration is a common cause of back pain, and attempts to develop therapies are frustrated by lack of model systems that mimic the human condition. Human IVD organ culture models can address this gap, yet current models are limited since vertebral endplates are removed to maintain cell viability, physiological loading is not applied, and mechanical behaviors are not measured. This study aimed to (i) establish a method for isolating human IVDs from autopsy with intact vertebral endplates, and (ii) develop and validate an organ culture loading system for human or bovine IVDs. Human IVDs with intact endplates were isolated from cadavers within 48 hours of death and cultured for up to 21 days. IVDs remained viable with ~80% cell viability in nucleus and annulus regions. A dynamic loading system was designed and built with the capacity to culture 9 bovine or 6 human IVDs simultaneously while applying simulated physiologic loads (maximum force: 4kN) and measuring IVD mechanical behaviors. The loading system accurately applied dynamic loading regimes (RMS error <2.5N and total harmonic distortion <2.45%), and precisely evaluated mechanical behavior of rubber and bovine IVDs. Bovine IVDs maintained their mechanical behavior and retained >85% viable cells throughout the 3 week culture period. This organ culture loading system can closely mimic physiological conditions and be used to investigate response of living human and bovine IVDs to mechanical and chemical challenges and to screen therapeutic repair techniques. PMID:24725441

Complexity analysis of dual-channel game model with different managers' business objectives

NASA Astrophysics Data System (ADS)

Li, Ting; Ma, Junhai

2015-01-01

This paper considers dual-channel game model with bounded rationality, using the theory of bifurcations of dynamical system. The business objectives of retailers are assumed to be different, which is closer to reality than previous studies. We study the local stable region of Nash equilibrium point and find that business objectives can expand the stable region and play an important role in price strategy. One interesting finding is that a fiercer competition tends to stabilize the Nash equilibrium. Simulation shows the complex behavior of two dimensional dynamic system, we find period doubling bifurcation and chaos phenomenon. We measure performances of the model in different period by using the index of average profit. The results show that unstable behavior in economic system is often an unfavorable outcome. So this paper discusses the application of adaptive adjustment mechanism when the model exhibits chaotic behavior and then allows the retailers to eliminate the negative effects.

Coordinated Dynamic Behaviors for Multirobot Systems With Collision Avoidance.

PubMed

Sabattini, Lorenzo; Secchi, Cristian; Fantuzzi, Cesare

2017-12-01

In this paper, we propose a novel methodology for achieving complex dynamic behaviors in multirobot systems. In particular, we consider a multirobot system partitioned into two subgroups: 1) dependent and 2) independent robots. Independent robots are utilized as a control input, and their motion is controlled in such a way that the dependent robots solve a tracking problem, that is following arbitrarily defined setpoint trajectories, in a coordinated manner. The control strategy proposed in this paper explicitly addresses the collision avoidance problem, utilizing a null space-based behavioral approach: this leads to combining, in a non conflicting manner, the tracking control law with a collision avoidance strategy. The combination of these control actions allows the robots to execute their task in a safe way. Avoidance of collisions is formally proven in this paper, and the proposed methodology is validated by means of simulations and experiments on real robots.

Review: mechanical behavior of metal/ceramic interfaces in nanolayered composites—experiments and modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Nan; Liu, Xiang-Yang

In this study, recent experimental and modeling studies in nanolayered metal/ceramic composites are reviewed, with focus on the mechanical behaviors of metal/nitrides interfaces. The experimental and modeling studies of the slip systems in bulk TiN are reviewed first. Then, the experimental studies of interfaces, including co-deformation mechanism by micropillar compression tests, in situ TEM straining tests for the dynamic process of the co-deformation, thickness-dependent fracture behavior, and interrelationship among the interfacial bonding, microstructure, and mechanical response, are reviewed for the specific material systems of Al/TiN and Cu/TiN multilayers at nanoscale. The modeling studies reviewed cover first-principles density functional theory-based modeling,more » atomistic molecular dynamics simulations, and mesoscale modeling of nanolayered composites using discrete dislocation dynamics. The phase transformation between zinc-blende and wurtzite AlN phases in Al/AlN multilayers at nanoscale is also reviewed. Finally, a summary and perspective of possible research directions and challenges are given.« less

Review: mechanical behavior of metal/ceramic interfaces in nanolayered composites—experiments and modeling

DOE PAGES

Li, Nan; Liu, Xiang-Yang

2017-11-03

In this study, recent experimental and modeling studies in nanolayered metal/ceramic composites are reviewed, with focus on the mechanical behaviors of metal/nitrides interfaces. The experimental and modeling studies of the slip systems in bulk TiN are reviewed first. Then, the experimental studies of interfaces, including co-deformation mechanism by micropillar compression tests, in situ TEM straining tests for the dynamic process of the co-deformation, thickness-dependent fracture behavior, and interrelationship among the interfacial bonding, microstructure, and mechanical response, are reviewed for the specific material systems of Al/TiN and Cu/TiN multilayers at nanoscale. The modeling studies reviewed cover first-principles density functional theory-based modeling,more » atomistic molecular dynamics simulations, and mesoscale modeling of nanolayered composites using discrete dislocation dynamics. The phase transformation between zinc-blende and wurtzite AlN phases in Al/AlN multilayers at nanoscale is also reviewed. Finally, a summary and perspective of possible research directions and challenges are given.« less

Modeling, numerical simulation, and nonlinear dynamic behavior analysis of PV microgrid-connected inverter with capacitance catastrophe

NASA Astrophysics Data System (ADS)

Li, Sichen; Liao, Zhixian; Luo, Xiaoshu; Wei, Duqu; Jiang, Pinqun; Jiang, Qinghong

2018-02-01

The value of the output capacitance (C) should be carefully considered when designing a photovoltaic (PV) inverter since it can cause distortion in the working state of the circuit, and the circuit produces nonlinear dynamic behavior. According to Kirchhoff’s laws and the characteristics of an ideal operational amplifier for a strict piecewise linear state equation, a circuit simulation model is constructed to study the system parameters (time, C) for the current passing through an inductor with an inductance of L and the voltage across the capacitor with a capacitance of C. The developed simulation model uses Runge-Kutta methods to solve the state equations. This study focuses on predicting the fault of the circuit from the two aspects of the harmonic distortion and simulation results. Moreover, the presented model is also used to research the working state of the system in the case of a load capacitance catastrophe. The nonlinear dynamic behaviors in the inverter are simulated and verified.

Ultrasensitive dual phosphorylation dephosphorylation cycle kinetics exhibits canonical competition behavior

NASA Astrophysics Data System (ADS)

Huang, Qingdao; Qian, Hong

2009-09-01

We establish a mathematical model for a cellular biochemical signaling module in terms of a planar differential equation system. The signaling process is carried out by two phosphorylation-dephosphorylation reaction steps that share common kinase and phosphatase with saturated enzyme kinetics. The pair of equations is particularly simple in the present mathematical formulation, but they are singular. A complete mathematical analysis is developed based on an elementary perturbation theory. The dynamics exhibits the canonical competition behavior in addition to bistability. Although widely understood in ecological context, we are not aware of a full range of biochemical competition in a simple signaling network. The competition dynamics has broad implications to cellular processes such as cell differentiation and cancer immunoediting. The concepts of homogeneous and heterogeneous multisite phosphorylation are introduced and their corresponding dynamics are compared: there is no bistability in a heterogeneous dual phosphorylation system. A stochastic interpretation is also provided that further gives intuitive understanding of the bistable behavior inside the cells.

Dynamic evolution characteristics of a fractional order hydropower station system

NASA Astrophysics Data System (ADS)

Gao, Xiang; Chen, Diyi; Yan, Donglin; Xu, Beibei; Wang, Xiangyu

2018-01-01

This paper investigates the dynamic evolution characteristics of the hydropower station by introducing the fractional order damping forces. A careful analysis of the dynamic characteristics of the generator shaft system is carried out under different values of fractional order. It turns out the vibration state of the axis coordinates has a certain evolution law with the increase of the fractional order. Significantly, the obtained law exists in the horizontal evolution and vertical evolution of the dynamical behaviors. Meanwhile, some interesting dynamical phenomena were found in this process. The outcomes of this study enrich the nonlinear dynamic theory from the engineering practice of hydropower stations.

Architecture Analysis of Evolving Complex Systems of Systems: Technical Presentation [and Executive Status Report

NASA Technical Reports Server (NTRS)

Lindvall, Mikael; Godfrey, Sally; Ackermann, Chris; Ray, Arnab; Yonkwa, Lyly; Ganesan, Dharma; Stratton, William C.; Sibol, Deane E.

2008-01-01

Analyze, Visualize, and Evaluate structure and behavior using static and dynamic information, individual systems as well as systems of systems. Next steps: Refine software tool support; Apply to other systems; and Apply earlier in system life cycle.

Physical Processes and Real-Time Chemical Measurement of the Insect Olfactory Environment

PubMed Central

Abrell, Leif; Hildebrand, John G.

2009-01-01

Odor-mediated insect navigation in airborne chemical plumes is vital to many ecological interactions, including mate finding, flower nectaring, and host locating (where disease transmission or herbivory may begin). After emission, volatile chemicals become rapidly mixed and diluted through physical processes that create a dynamic olfactory environment. This review examines those physical processes and some of the analytical technologies available to characterize those behavior-inducing chemical signals at temporal scales equivalent to the olfactory processing in insects. In particular, we focus on two areas of research that together may further our understanding of olfactory signal dynamics and its processing and perception by insects. First, measurement of physical atmospheric processes in the field can provide insight into the spatiotemporal dynamics of the odor signal available to insects. Field measurements in turn permit aspects of the physical environment to be simulated in the laboratory, thereby allowing careful investigation into the links between odor signal dynamics and insect behavior. Second, emerging analytical technologies with high recording frequencies and field-friendly inlet systems may offer new opportunities to characterize natural odors at spatiotemporal scales relevant to insect perception and behavior. Characterization of the chemical signal environment allows the determination of when and where olfactory-mediated behaviors may control ecological interactions. Finally, we argue that coupling of these two research areas will foster increased understanding of the physicochemical environment and enable researchers to determine how olfactory environments shape insect behaviors and sensory systems. PMID:18548311

Development of a helicopter rotor/propulsion system dynamics analysis

NASA Technical Reports Server (NTRS)

Warmbrodt, W.; Hull, R.

1982-01-01

A time-domain analysis of coupled engine/drive train/rotor dynamics of a twin-engine, single main rotor helicopter model has been performed. The analysis incorporates an existing helicopter model with nonlinear simulations of a helicopter turboshaft engine and its fuel controller. System dynamic behavior is studied using the resulting simulation which included representations for the two engines and their fuel controllers, drive system, main rotor, tail rotor, and aircraft rigid body motions. Time histories of engine and rotor RPM response to pilot control inputs are studied for a baseline rotor and propulsion system model. Sensitivity of rotor RPM droop to fuel controller gain changes and collective input feed-forward gain changes are studied. Torque-load-sharing between the two engines is investigated by making changes in the fuel controller feedback paths. A linear engine model is derived from the nonlinear engine simulation and used in the coupled system analysis. This four-state linear engine model is then reduced to a three-state model. The effect of this simplification on coupled system behavior is shown.

Initial condition-dependent dynamics and transient period in memristor-based hypogenetic jerk system with four line equilibria

NASA Astrophysics Data System (ADS)

Bao, Han; Wang, Ning; Bao, Bocheng; Chen, Mo; Jin, Peipei; Wang, Guangyi

2018-04-01

Memristor-based nonlinear dynamical system easily presents the initial condition-dependent dynamical phenomenon of extreme multistability, i.e., coexisting infinitely many attractors, which has been received much attention in recent years. By introducing an ideal and active flux-controlled memristor into an existing hypogenetic chaotic jerk system, an interesting memristor-based chaotic system with hypogenetic jerk equation and circuit forms is proposed. The most striking feature is that this system has four line equilibria and exhibits the extreme multistability phenomenon of coexisting infinitely many attractors. Stability of these line equilibria are analyzed, and coexisting infinitely many attractors' behaviors with the variations of the initial conditions are investigated by bifurcation diagrams, Lyapunov exponent spectra, attraction basins, and phased portraits, upon which the forming mechanism of extreme multistablity in the memristor-based hypogenetic jerk system is explored. Specially, unusual transition behavior of long term transient period with steady chaos, completely different from the phenomenon of transient chaos, can be also found for some initial conditions. Moreover, a hardware circuit is design and fabricated and its experimental results effectively verify the truth of extreme multistablity.

Fractional Order and Dynamic Simulation of a System Involving an Elastic Wide Plate

NASA Astrophysics Data System (ADS)

David, S. A.; Balthazar, J. M.; Julio, B. H. S.; Oliveira, C.

2011-09-01

Numerous researchers have studied about nonlinear dynamics in several areas of science and engineering. However, in most cases, these concepts have been explored mainly from the standpoint of analytical and computational methods involving integer order calculus (IOC). In this paper we have examined the dynamic behavior of an elastic wide plate induced by two electromagnets of a point of view of the fractional order calculus (FOC). The primary focus of this study is on to help gain a better understanding of nonlinear dynamic in fractional order systems.

Scaling behavior in the dynamics of citations to scientific journals

NASA Astrophysics Data System (ADS)

Picoli, S., Jr.; Mendes, R. S.; Malacarne, L. C.; Lenzi, E. K.

2006-08-01

We analyze a database comprising the impact factor (citations per recent items published) of scientific journals for a 13-year period (1992 2004). We find that i) the distribution of impact factors follows asymptotic power law behavior, ii) the distribution of annual logarithmic growth rates has an exponential form, and iii) the width of this distribution decays with the impact factor as a power law with exponent β simeq 0.22. The results ii) and iii) are surprising similar to those observed in the growth dynamics of organizations with complex internal structure suggesting the existence of common mechanisms underlying the dynamics of these systems. We propose a general model for such systems, an extension of the simplest model for firm growth, and compare their predictions with our empirical results.

The developmental dynamics of behavioral growth processes in rodent egocentric and allocentric space.

PubMed

Golani, Ilan

2012-06-01

In this review I focus on how three methodological principles advocated by Philip Teitelbaum influenced my work to this day: that similar principles of organization should be looked for in ontogeny and recovery of function; that the order of emergence of behavioral components provides a view on the organization of that behavior; and that the components of behavior should be exhibited by the animal itself in relatively pure form. I start by showing how these principles influenced our common work on the developmental dynamics of rodent egocentric space, and then proceed to describe how these principles affected my work with Yoav Benjamini and others on the developmental dynamics of rodent allocentric space. We analyze issues traditionally addressed by physiological psychologists with methods borrowed from ethology, EW (Eshkol-Wachman) movement notation, dynamical systems and exploratory data analysis. Then we show how the natural origins of axes embodied by the behavior of the organism itself, are used by us as the origins of axes for the measurement of the developmental moment-by-moment dynamics of behavior. Using this methodology we expose similar principles of organization across situations, species and preparations, provide a developmental view on the organization of behavior, expose the natural components of behavior in relatively pure form, and reveal how low level primitives generate higher level constructs. Advances in tracking technology should allow us to study how movements in egocentric and allocentric spaces interlace. Tracking of multi-limb coordination, progress in online recording of neural activity in freely moving animals, and the unprecedented accumulation of genetically engineered mouse preparations makes the behavioral ground plan exposed in this review essential for a systematic study of the brain/behavior interface. Copyright © 2012 Elsevier B.V. All rights reserved.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

PubMed

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

Transition Manifolds of Complex Metastable Systems

NASA Astrophysics Data System (ADS)

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-04-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Visibility graphlet approach to chaotic time series

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mutua, Stephen; Computer Science Department, Masinde Muliro University of Science and Technology, P.O. Box 190-50100, Kakamega; Gu, Changgui, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn

Many novel methods have been proposed for mapping time series into complex networks. Although some dynamical behaviors can be effectively captured by existing approaches, the preservation and tracking of the temporal behaviors of a chaotic system remains an open problem. In this work, we extended the visibility graphlet approach to investigate both discrete and continuous chaotic time series. We applied visibility graphlets to capture the reconstructed local states, so that each is treated as a node and tracked downstream to create a temporal chain link. Our empirical findings show that the approach accurately captures the dynamical properties of chaotic systems.more » Networks constructed from periodic dynamic phases all converge to regular networks and to unique network structures for each model in the chaotic zones. Furthermore, our results show that the characterization of chaotic and non-chaotic zones in the Lorenz system corresponds to the maximal Lyapunov exponent, thus providing a simple and straightforward way to analyze chaotic systems.« less

A Method for Comparing Multivariate Time Series with Different Dimensions

PubMed Central

Tapinos, Avraam; Mendes, Pedro

2013-01-01

In many situations it is desirable to compare dynamical systems based on their behavior. Similarity of behavior often implies similarity of internal mechanisms or dependency on common extrinsic factors. While there are widely used methods for comparing univariate time series, most dynamical systems are characterized by multivariate time series. Yet, comparison of multivariate time series has been limited to cases where they share a common dimensionality. A semi-metric is a distance function that has the properties of non-negativity, symmetry and reflexivity, but not sub-additivity. Here we develop a semi-metric – SMETS – that can be used for comparing groups of time series that may have different dimensions. To demonstrate its utility, the method is applied to dynamic models of biochemical networks and to portfolios of shares. The former is an example of a case where the dependencies between system variables are known, while in the latter the system is treated (and behaves) as a black box. PMID:23393554

Can a simple dynamical system describe the interplay between drag and buoyancy in terrain-induced canopy flows?

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Roo, Frederik; Banerjee, Tirtha

Under non-neutral stratification and in the presence of topography the dynamics of turbulent flow within a canopy is not yet completely understood. This has, among others, serious implications for the measurement of surface – atmosphere exchange by means of eddy-covariance: for example the measurement of carbon dioxide fluxes are strongly influenced if drainage flows occur during night, when the flow within the canopy decouples from the flow aloft. An improved physical understanding of the behavior of scalars under canopy turbulence in complex terrain is urgently needed. In the present work, we investigate the dynamics of turbulent flow within sloped canopies,more » focusing on the slope wind and potential temperature. We concentrate on the presence of oscillatory behavior in the flow variables in terms of switching of flow regimes by conducting linear stability analysis. We revisit and correct the simplified theory that exists in the literature, which is based on the interplay between the drag force and the buoyancy. We find that the simplified description of this dynamical system cannot exhibit the observed richness of the dynamics. To augment the simplified dynamical system’s analysis, we make use of large-eddy simulation of a three-dimensional hill covered by a homogeneous forest and analyze the phase synchronization behavior of the buoyancy and drag forces in the momentum budget to explore the turbulent dynamics in more detail.« less

Can a simple dynamical system describe the interplay between drag and buoyancy in terrain-induced canopy flows?

DOE PAGES

De Roo, Frederik; Banerjee, Tirtha

2018-02-23

Under non-neutral stratification and in the presence of topography the dynamics of turbulent flow within a canopy is not yet completely understood. This has, among others, serious implications for the measurement of surface – atmosphere exchange by means of eddy-covariance: for example the measurement of carbon dioxide fluxes are strongly influenced if drainage flows occur during night, when the flow within the canopy decouples from the flow aloft. An improved physical understanding of the behavior of scalars under canopy turbulence in complex terrain is urgently needed. In the present work, we investigate the dynamics of turbulent flow within sloped canopies,more » focusing on the slope wind and potential temperature. We concentrate on the presence of oscillatory behavior in the flow variables in terms of switching of flow regimes by conducting linear stability analysis. We revisit and correct the simplified theory that exists in the literature, which is based on the interplay between the drag force and the buoyancy. We find that the simplified description of this dynamical system cannot exhibit the observed richness of the dynamics. To augment the simplified dynamical system’s analysis, we make use of large-eddy simulation of a three-dimensional hill covered by a homogeneous forest and analyze the phase synchronization behavior of the buoyancy and drag forces in the momentum budget to explore the turbulent dynamics in more detail.« less

Computation of the spectrum of spatial Lyapunov exponents for the spatially extended beam-plasma systems and electron-wave devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hramov, Alexander E.; Saratov State Technical University, Politechnicheskaja str., 77, Saratov 410054; Koronovskii, Alexey A.

2012-08-15

The spectrum of Lyapunov exponents is powerful tool for the analysis of the complex system dynamics. In the general framework of nonlinear dynamics, a number of the numerical techniques have been developed to obtain the spectrum of Lyapunov exponents for the complex temporal behavior of the systems with a few degree of freedom. Unfortunately, these methods cannot be applied directly to analysis of complex spatio-temporal dynamics of plasma devices which are characterized by the infinite phase space, since they are the spatially extended active media. In the present paper, we propose the method for the calculation of the spectrum ofmore » the spatial Lyapunov exponents (SLEs) for the spatially extended beam-plasma systems. The calculation technique is applied to the analysis of chaotic spatio-temporal oscillations in three different beam-plasma model: (1) simple plasma Pierce diode, (2) coupled Pierce diodes, and (3) electron-wave system with backward electromagnetic wave. We find an excellent agreement between the system dynamics and the behavior of the spectrum of the spatial Lyapunov exponents. Along with the proposed method, the possible problems of SLEs calculation are also discussed. It is shown that for the wide class of the spatially extended systems, the set of quantities included in the system state for SLEs calculation can be reduced using the appropriate feature of the plasma systems.« less

Dynamic Response of Reinforced Soil Systems. Volume 1. Report

DTIC Science & Technology

1993-03-01

include Security Clas~sification) DYNAMIC RWSPC!SE OF REIFý1Cý SOIL SYSTEM~, VCTJI4E I OF II: PREPO~r 󈧐. PERSONAL AUTHOR($) BMW3U, R.C.; FRAWASZY...protected by a burster slab. These protection measures are costly, time consuming to construct, and sensitive to multiple strikes. Soil has been used to...characterize the static load-deflection behavior of the reinforced soil. Dynamic pullout tests were then performed using the same parameters as the static

A cognitive-affective system theory of personality: reconceptualizing situations, dispositions, dynamics, and invariance in personality structure.

PubMed

Mischel, W; Shoda, Y

1995-04-01

A theory was proposed to reconcile paradoxical findings on the invariance of personality and the variability of behavior across situations. For this purpose, individuals were assumed to differ in (a) the accessibility of cognitive-affective mediating units (such as encodings, expectancies and beliefs, affects, and goals) and (b) the organization of relationships through which these units interact with each other and with psychological features of situations. The theory accounts for individual differences in predictable patterns of variability across situations (e.g., if A then she X, but if B then she Y), as well as for overall average levels of behavior, as essential expressions or behavioral signatures of the same underlying personality system. Situations, personality dispositions, dynamics, and structure were reconceptualized from this perspective.

Recurrence plot analyses suggest a novel reference system involved in newborn spontaneous movements.

PubMed

Assmann, Birte; Thiel, Marco; Romano, Maria C; Niemitz, Carsten

2006-08-01

The movements of newborns have been thoroughly studied in terms of reflexes, muscle synergies, leg coordination, and target-directed arm/hand movements. Since these approaches have concentrated mainly on separate accomplishments, there has remained a clear need for more integrated investigations. Here, we report an inquiry in which we explicitly concentrated on taking such a perspective and, additionally, were guided by the methodological concept of home base behavior, which Ilan Golani developed for studies of exploratory behavior in animals. Methods from nonlinear dynamics, such as symbolic dynamics and recurrence plot analyses of kinematic data received from audiovisual newborn recordings, yielded new insights into the spatial and temporal organization of limb movements. In the framework of home base behavior, our approach uncovered a novel reference system of spontaneous newborn movements.

Thermalization dynamics in a quenched many-body state

NASA Astrophysics Data System (ADS)

Kaufman, Adam; Preiss, Philipp; Tai, Eric; Lukin, Alex; Rispoli, Matthew; Schittko, Robert; Greiner, Markus

2016-05-01

Quantum and classical many-body systems appear to have disparate behavior due to the different mechanisms that govern their evolution. The dynamics of a classical many-body system equilibrate to maximally entropic states and quickly re-thermalize when perturbed. The assumptions of ergodicity and unbiased configurations lead to a successful framework of describing classical systems by a sampling of thermal ensembles that are blind to the system's microscopic details. By contrast, an isolated quantum many-body system is governed by unitary evolution: the system retains memory of past dynamics and constant global entropy. However, even with differing characteristics, the long-term behavior for local observables in quenched, non-integrable quantum systems are often well described by the same thermal framework. We explore the onset of this convergence in a many-body system of bosonic atoms in an optical lattice. Our system's finite size allows us to verify full state purity and measure local observables. We observe rapid growth and saturation of the entanglement entropy with constant global purity. The combination of global purity and thermalized local observables agree with the Eigenstate Thermalization Hypothesis in the presence of a near-volume law in the entanglement entropy.

Evolutionary dynamics under interactive diversity

NASA Astrophysics Data System (ADS)

Su, Qi; Li, Aming; Wang, Long

2017-10-01

As evidenced by many cases in human societies, individuals often make different behavior decisions in different interactions, and adaptively adjust their behavior in changeable interactive scenarios. However, up to now, how such diverse interactive behavior affects cooperation dynamics has still remained unknown. Here we develop a general framework of interactive diversity, which models individuals’ separated behavior against distinct opponents and their adaptive adjustment in response to opponents’ strategies, to explore the evolution of cooperation. We find that interactive diversity enables individuals to reciprocate every single opponent, and thus sustains large-scale reciprocal interactions. Our work witnesses an impressive boost of cooperation for a notably extensive range of parameters and for all pairwise games. These results are robust against well-mixed and various networked populations, and against degree-normalized and cumulative payoff patterns. From the perspective of network dynamics, distinguished from individuals competing for nodes in most previous work, in this paper, the system evolves in the form of behavior disseminating along edges. We propose a theoretical method based on evolution of edges, which predicts well both the frequency of cooperation and the compact cooperation clusters. Our thorough investigation clarifies the positive role of interactive diversity in resolving social dilemmas and highlights the significance of understanding evolutionary dynamics from the viewpoint of edge dynamics.

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development

PubMed Central

Cotter, Christopher R.; Schüttler, Heinz-Bernd; Igoshin, Oleg A.; Shimkets, Lawrence J.

2017-01-01

Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell–cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues. PMID:28533367

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sensation during Active Behaviors

PubMed Central

Cardin, Jessica A.; Chiappe, M. Eugenia; Halassa, Michael M.; McGinley, Matthew J.; Yamashita, Takayuki

2017-01-01

A substantial portion of our sensory experience happens during active behaviors such as walking around or paying attention. How do sensory systems work during such behaviors? Neural processing in sensory systems can be shaped by behavior in multiple ways ranging from a modulation of responsiveness or sharpening of tuning to a dynamic change of response properties or functional connectivity. Here, we review recent findings on the modulation of sensory processing during active behaviors in different systems: insect vision, rodent thalamus, and rodent sensory cortices. We discuss the circuit-level mechanisms that might lead to these modulations and their potential role in sensory function. Finally, we highlight the open questions and future perspectives of this exciting new field. PMID:29118211

Dynamical Heterogeneity in Granular Fluids and Structural Glasses

NASA Astrophysics Data System (ADS)

Avila, Karina E.

Our current understanding of the dynamics of supercooled liquids and other similar slowly evolving (glassy) systems is rather limited. One aspect that is particularly poorly understood is the origin and behavior of the strong non trivial fluctuations that appear in the relaxation process toward equilibrium. Glassy systems and granular systems both present regions of particles moving cooperatively and at different rates from other regions. This phenomenon is known as spatially heterogeneous dynamics. A detailed explanation of this phenomenon may lead to a better understanding of the slow relaxation process, and perhaps it could even help to explain the presence of the glass transition. This dissertation concentrates on studying dynamical heterogeneity by analyzing simulation data for models of granular materials and structural glasses. For dissipative granular fluids, the growing behavior of dynamical heterogeneities is studied for different densities and different degrees of inelasticity in the particle collisions. The correlated regions are found to grow rapidly as the system approaches dynamical arrest. Their geometry is conserved even when probing at different cutoff length in the correlation function or when the energy dissipation in the system is increased. For structural glasses, I test a theoretical framework that models dynamical heterogeneity as originated in the presence of Goldstone modes, which emerge from a broken continuous time reparametrization symmetry. This analysis is based on quantifying the size and the spatial correlations of fluctuations in the time variable and of other kinds of fluctuations. The results obtained here agree with the predictions of the hypothesis. In particular, the fluctuations associated to the time reparametrization invariance become stronger for low temperatures, long timescales, and large coarse graining lengths. Overall, this research points to dynamical heterogeneity to be described for granular systems similarly than for other glassy systems and it provides evidence in favor of a particular theory for the origin of dynamical heterogeneity.

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Simulating the dynamic behavior of chain drive systems by advanced CAE programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, J.; Meyer, J.

1996-09-01

Due to the increased requirements for chain drive systems of 4-stroke internal combustion engines CAE-tools are necessary to design the optimum dynamic system. In comparison to models used din the past the advantage of the new model CDD (Chain Drive Dynamics) is the capability of simulating the trajectory of each chain link around the drive system. Each chain link is represented by a mass with two degrees of freedom and is coupled to the next by a spring-damper element. The drive sprocket can be moved with a constant or non-constant speed. As in reality the other sprockets are driven bymore » the running chain and can be excited by torques. Due to these unique model features it is possible to calculate all vibration types of the chain, polygon effects and radial or angular vibrations of the sprockets very accurately. The model includes the detailed simulation of a mechanical or a hydraulic tensioner as well. The method is ready to be coupled to other detailed calculation models (e.g. valve train systems, crankshaft, etc.). The high efficiency of the tool predicting the dynamic and acoustic behavior of a chain drive system will be demonstrated in comparison to measurements.« less

Contact dynamic phenomena in rotating machines: Active/passive considerations

NASA Astrophysics Data System (ADS)

Keogh, Patrick S.

2012-05-01

There are machine operating regimes in which rotor/stator interactions may lead to problematic rotor dynamic behavior. For example, dynamic heat sources arising from seals, bearings and other rubbing stator components may cause rotor thermal bend instability. In active magnetic bearing (AMB) systems, the rotor may experience forward and backward whirl rubs with touchdown bearings (TDBs). In abnormal cases, rotor transient and bounce interactions with such bearings may involve highly localized and short duration contacts. This paper discusses certain contact phenomena that may occur in passive and active systems. For example, the rub induced spiral behavior arises from a combination of unbalance and a thermal input that moves slowly around the rotor, typically in passive rotor-bearing systems. However, the instability can be regarded as if arising from a closed-loop feedback system. Hence it is possible to analyze the phenomenon using techniques that have been developed for active control systems. Rotors levitated by AMBs are truly active, but there are fundamental issues that may arise when contact with TDBs occurs. AMB control and contact interactions are discussed together with the benefits for making the TDB an active element. The reason for this lies in the potential ability to control the contact dynamics and associated mechanical and thermal stresses. A prototype system is described.

Maternal Depressive Symptomatology and Child Behavior: Transactional Relationship with Simultaneous Bidirectional Coupling

PubMed Central

Nicholson, Jody S.; Deboeck, Pascal; Farris, Jaelyn R.; Boker, Steven M.; Borkowski, John G.

2011-01-01

The present study investigated reciprocal relationships between adolescent mothers and their children’s well-being through an analysis of the coupling relationship of mothers’ depressive symptomatology and children’s internalizing and externalizing behaviors. Unlike studies using discrete time analyses, the present study used dynamical systems to model time continuously, which allowed for the study of dynamic, transactional effects between members of each dyad. Findings provided evidence of coupling between maternal depressive symptoms and children’s behaviors. The most robust finding was that as maternal depressive symptoms became more or less severe, children’s behavior problems increased or decreased in a reciprocal manner. Results from this study extended upon theoretical contributions of authors such as Richters (1997) and Granic and Hollenstein (2003), providing empirical validation from a longitudinal study for understanding the ongoing, dynamic relationships between at-risk mothers and their children. PMID:21639624

Self-Organized Behavior Generation for Musculoskeletal Robots.

PubMed

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics.

Self-Organized Behavior Generation for Musculoskeletal Robots

PubMed Central

Der, Ralf; Martius, Georg

2017-01-01

With the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors “waiting” to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics. PMID:28360852

Relationship between local structure and relaxation in out-of-equilibrium glassy systems

DOE PAGES

Schoenholz, Samuel S.; Cubuk, Ekin D.; Kaxiras, Efthimios; ...

2016-12-27

The dynamical glass transition is typically taken to be the temperature at which a glassy liquid is no longer able to equilibrate on experimental timescales. Consequently, the physical properties of these systems just above or below the dynamical glass transition, such as viscosity, can change by many orders of magnitude over long periods of time following external perturbation. During this progress toward equilibrium, glassy systems exhibit a history dependence that has complicated their study. In previous work, we bridged the gap between structure and dynamics in glassy liquids above their dynamical glass transition temperatures by introducing a scalar field calledmore » “softness,” a quantity obtained using machine-learning methods. Softness is designed to capture the hidden patterns in relative particle positions that correlate strongly with dynamical rearrangements of particle positions. Here we show that the out-of-equilibrium behavior of a model glass-forming system can be understood in terms of softness. We first demonstrate that the evolution of behavior following a temperature quench is a primarily structural phenomenon: The structure changes considerably, but the relationship between structure and dynamics remains invariant. We then show that the relaxation time can be robustly computed from structure as quantified by softness, with the same relation holding both in equilibrium and as the system ages. Together, these results show that the history dependence of the relaxation time in glasses requires knowledge only of the softness in addition to the usual state variables.« less

Relationship between local structure and relaxation in out-of-equilibrium glassy systems.

PubMed

Schoenholz, Samuel S; Cubuk, Ekin D; Kaxiras, Efthimios; Liu, Andrea J

2017-01-10

The dynamical glass transition is typically taken to be the temperature at which a glassy liquid is no longer able to equilibrate on experimental timescales. Consequently, the physical properties of these systems just above or below the dynamical glass transition, such as viscosity, can change by many orders of magnitude over long periods of time following external perturbation. During this progress toward equilibrium, glassy systems exhibit a history dependence that has complicated their study. In previous work, we bridged the gap between structure and dynamics in glassy liquids above their dynamical glass transition temperatures by introducing a scalar field called "softness," a quantity obtained using machine-learning methods. Softness is designed to capture the hidden patterns in relative particle positions that correlate strongly with dynamical rearrangements of particle positions. Here we show that the out-of-equilibrium behavior of a model glass-forming system can be understood in terms of softness. To do this we first demonstrate that the evolution of behavior following a temperature quench is a primarily structural phenomenon: The structure changes considerably, but the relationship between structure and dynamics remains invariant. We then show that the relaxation time can be robustly computed from structure as quantified by softness, with the same relation holding both in equilibrium and as the system ages. Together, these results show that the history dependence of the relaxation time in glasses requires knowledge only of the softness in addition to the usual state variables.

The mechanisms of plastic strain accommodation and post critical behavior of heterogeneous reactive composites subject to dynamic loading

NASA Astrophysics Data System (ADS)

Olney, Karl L.

The dynamic behavior of granular/porous and laminate reactive materials is of interest due to their practical applications; reactive structural components, reactive fragments, etc. The mesostructural properties control meso- and macro-scale dynamic behavior of these heterogeneous composites including the behavior during the post-critical stage of deformation. They heavily influence mechanisms of fragment generation and the in situ development of local hot spots, which act as sites of ignition in these materials. This dissertation concentrates on understanding the mechanisms of plastic strain accommodation in two representative reactive material systems with different heterogeneous mesostructrues: Aluminum-Tungsten granular/porous and Nickel-Aluminum laminate composites. The main focus is on the interpretation of results of the following dynamic experiments conducted at different strain and strain rates: drop weight tests, explosively expanded ring experiments, and explosively collapsed thick walled cylinder experiments. Due to the natural limitations in the evaluation of the mesoscale behavior of these materials experimentally and the large variation in the size scales between the mesostructural level and the sample, it is extremely difficult, if not impossible, to examine the mesoscale behavior in situ. Therefore, numerical simulations of the corresponding experiments are used as the main tool to explore material behavior at the mesoscale. Numerical models were developed to elucidate the mechanisms of plastic strain accommodation and post critical behavior in these heterogeneous composites subjected to dynamic loading. These simulations were able to reproduce the qualitative and quantitative features that were observable in the experiments and provided insight into the evolution of the mechanisms of plastic strain accommodation and post critical behavior in these materials with complex mesotructure. Additionally, these simulations provided a framework to examine the influence of various mesoscale properties such as the bonding of interfaces, the role of material properties, and the influence of mesoscale geometry. The results of this research are helpful in the design of material mesotructures conducive to the desirable behavior under dynamic loading.

Emergent dynamic structures and statistical law in spherical lattice gas automata.

PubMed

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Emergent dynamic structures and statistical law in spherical lattice gas automata

NASA Astrophysics Data System (ADS)

Yao, Zhenwei

2017-12-01

Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.

Synchronizability of nonidentical weakly dissipative systems

NASA Astrophysics Data System (ADS)

Sendiña-Nadal, Irene; Letellier, Christophe

2017-10-01

Synchronization is a very generic process commonly observed in a large variety of dynamical systems which, however, has been rarely addressed in systems with low dissipation. Using the Rössler, the Lorenz 84, and the Sprott A systems as paradigmatic examples of strongly, weakly, and non-dissipative chaotic systems, respectively, we show that a parameter or frequency mismatch between two coupled such systems does not affect the synchronizability and the underlying structure of the joint attractor in the same way. By computing the Shannon entropy associated with the corresponding recurrence plots, we were able to characterize how two coupled nonidentical chaotic oscillators organize their dynamics in different dissipation regimes. While for strongly dissipative systems, the resulting dynamics exhibits a Shannon entropy value compatible with the one having an average parameter mismatch, for weak dissipation synchronization dynamics corresponds to a more complex behavior with higher values of the Shannon entropy. In comparison, conservative dynamics leads to a less rich picture, providing either similar chaotic dynamics or oversimplified periodic ones.

Dynamic phase transitions of the Blume-Emery-Griffiths model under an oscillating external magnetic field by the path probability method

NASA Astrophysics Data System (ADS)

Ertaş, Mehmet; Keskin, Mustafa

2015-03-01

By using the path probability method (PPM) with point distribution, we study the dynamic phase transitions (DPTs) in the Blume-Emery-Griffiths (BEG) model under an oscillating external magnetic field. The phases in the model are obtained by solving the dynamic equations for the average order parameters and a disordered phase, ordered phase and four mixed phases are found. We also investigate the thermal behavior of the dynamic order parameters to analyze the nature dynamic transitions as well as to obtain the DPT temperatures. The dynamic phase diagrams are presented in three different planes in which exhibit the dynamic tricritical point, double critical end point, critical end point, quadrupole point, triple point as well as the reentrant behavior, strongly depending on the values of the system parameters. We compare and discuss the dynamic phase diagrams with dynamic phase diagrams that were obtained within the Glauber-type stochastic dynamics based on the mean-field theory.

Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws

PubMed Central

Palva, J. Matias; Zhigalov, Alexander; Hirvonen, Jonni; Korhonen, Onerva; Linkenkaer-Hansen, Klaus; Palva, Satu

2013-01-01

Scale-free fluctuations are ubiquitous in behavioral performance and neuronal activity. In time scales from seconds to hundreds of seconds, psychophysical dynamics and the amplitude fluctuations of neuronal oscillations are governed by power-law-form long-range temporal correlations (LRTCs). In millisecond time scales, neuronal activity comprises cascade-like neuronal avalanches that exhibit power-law size and lifetime distributions. However, it remains unknown whether these neuronal scaling laws are correlated with those characterizing behavioral performance or whether neuronal LRTCs and avalanches are related. Here, we show that the neuronal scaling laws are strongly correlated both with each other and with behavioral scaling laws. We used source reconstructed magneto- and electroencephalographic recordings to characterize the dynamics of ongoing cortical activity. We found robust power-law scaling in neuronal LRTCs and avalanches in resting-state data and during the performance of audiovisual threshold stimulus detection tasks. The LRTC scaling exponents of the behavioral performance fluctuations were correlated with those of concurrent neuronal avalanches and LRTCs in anatomically identified brain systems. The behavioral exponents also were correlated with neuronal scaling laws derived from a resting-state condition and with a similar anatomical topography. Finally, despite the difference in time scales, the scaling exponents of neuronal LRTCs and avalanches were strongly correlated during both rest and task performance. Thus, long and short time-scale neuronal dynamics are related and functionally significant at the behavioral level. These data suggest that the temporal structures of human cognitive fluctuations and behavioral variability stem from the scaling laws of individual and intrinsic brain dynamics. PMID:23401536

Creating virtual humans for simulation-based training and planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stansfield, S.; Sobel, A.

1998-05-12

Sandia National Laboratories has developed a distributed, high fidelity simulation system for training and planning small team Operations. The system provides an immersive environment populated by virtual objects and humans capable of displaying complex behaviors. The work has focused on developing the behaviors required to carry out complex tasks and decision making under stress. Central to this work are techniques for creating behaviors for virtual humans and for dynamically assigning behaviors to CGF to allow scenarios without fixed outcomes. Two prototype systems have been developed that illustrate these capabilities: MediSim, a trainer for battlefield medics and VRaptor, a system formore » planning, rehearsing and training assault operations.« less

Phase Shadows: An Enhanced Representation of Nonlinear Dynamic Systems

NASA Astrophysics Data System (ADS)

Luque, Amalia; Barbancho, Julio; Cañete, Javier Fernández; Córdoba, Antonio

2017-12-01

Many nonlinear dynamic systems have a rotating behavior where an angle defining its state may extend to more than 360∘. In these cases the use of the phase portrait does not properly depict the system’s evolution. Normalized phase portraits or cylindrical phase portraits have been extensively used to overcome the original phase portrait’s disadvantages. In this research a new graphic representation is introduced: the phase shadow. Its use clearly reveals the system behavior while overcoming the drawback of the existing plots. Through the paper the method to obtain the graphic is stated. Additionally, to show the phase shadow’s expressiveness, a rotating pendulum is considered. The work exposes that the new graph is an enhanced representational tool for systems having equilibrium points, limit cycles, chaotic attractors and/or bifurcations.

Rotordynamic Modelling and Response Characteristics of an Active Magnetic Bearing Rotor System

NASA Technical Reports Server (NTRS)

Free, April M.; Flowers, George T.; Trent, Victor S.

1996-01-01

Auxiliary bearings are a critical feature of any magnetic bearing system. They protect the soft iron core of the magnetic bearing during an overload or failure. An auxiliary bearing typically consists of a rolling element bearing or bushing with a clearance gap between the rotor and the inner race of the support. The dynamics of such systems can be quite complex. It is desired to develop a rotordynamic model which describes the dynamic behavior of a flexible rotor system with magnetic bearings including auxiliary bearings. The model is based upon an experimental test facility. Some simulation studies are presented to illustrate the behavior of the model. In particular, the effects of introducing sideloading from the magnetic bearing when one coil fails is studied. These results are presented and discussed.

Nonequilibrium optical control of dynamical states in superconducting nanowire circuits.

PubMed

Madan, Ivan; Buh, Jože; Baranov, Vladimir V; Kabanov, Viktor V; Mrzel, Aleš; Mihailovic, Dragan

2018-03-01

Optical control of states exhibiting macroscopic phase coherence in condensed matter systems opens intriguing possibilities for materials and device engineering, including optically controlled qubits and photoinduced superconductivity. Metastable states, which in bulk materials are often associated with the formation of topological defects, are of more practical interest. Scaling to nanosize leads to reduced dimensionality, fundamentally changing the system's properties. In one-dimensional superconducting nanowires, vortices that are present in three-dimensional systems are replaced by fluctuating topological defects of the phase. These drastically change the dynamical behavior of the superconductor and introduce dynamical periodic long-range ordered states when the current is driven through the wire. We report the control and manipulation of transitions between different dynamically stable states in superconducting δ 3 -MoN nanowire circuits by ultrashort laser pulses. Not only can the transitions between different dynamically stable states be precisely controlled by light, but we also discovered new photoinduced hidden states that cannot be reached under near-equilibrium conditions, created while laser photoexcited quasi-particles are outside the equilibrium condition. The observed switching behavior can be understood in terms of dynamical stabilization of various spatiotemporal periodic trajectories of the order parameter in the superconductor nanowire, providing means for the optical control of the superconducting phase with subpicosecond control of timing.

Chaotic behavior in Malaysian stock market: A study with recurrence quantification analysis

NASA Astrophysics Data System (ADS)

Niu, Betty Voon Wan; Noorani, Mohd Salmi Md; Jaaman, Saiful Hafizah

2016-11-01

The dynamics of stock market has been questioned for decades. Its behavior appeared random yet some found it behaves as chaos. Up to 5000 daily adjusted closing data of FTSE Bursa Malaysia Kuala Lumpur Composite Index (KLSE) was investigated through recurrence plot and recurrence quantification analysis. Results were compared between stochastic system, chaotic system and deterministic system. Results show that KLSE daily adjusted closing data behaves chaotically.

Evidence for deterministic chaos in aperiodic oscillations of acute lymphoblastic leukemia cells in long-term culture

NASA Astrophysics Data System (ADS)

Lambrou, George I.; Chatziioannou, Aristotelis; Vlahopoulos, Spiros; Moschovi, Maria; Chrousos, George P.

Biological systems are dynamic and possess properties that depend on two key elements: initial conditions and the response of the system over time. Conceptualizing this on tumor models will influence conclusions drawn with regard to disease initiation and progression. Alterations in initial conditions dynamically reshape the properties of proliferating tumor cells. The present work aims to test the hypothesis of Wolfrom et al., that proliferation shows evidence for deterministic chaos in a manner such that subtle differences in the initial conditions give rise to non-linear response behavior of the system. Their hypothesis, tested on adherent Fao rat hepatoma cells, provides evidence that these cells manifest aperiodic oscillations in their proliferation rate. We have tested this hypothesis with some modifications to the proposed experimental setup. We have used the acute lymphoblastic leukemia cell line CCRF-CEM, as it provides an excellent substrate for modeling proliferation dynamics. Measurements were taken at time points varying from 24h to 48h, extending the assayed populations beyond that of previous published reports that dealt with the complex dynamic behavior of animal cell populations. We conducted flow cytometry studies to examine the apoptotic and necrotic rate of the system, as well as DNA content changes of the cells over time. The cells exhibited a proliferation rate of nonlinear nature, as this rate presented oscillatory behavior. The obtained data have been fit in known models of growth, such as logistic and Gompertzian growth.

Non-Markovian continuous-time quantum walks on lattices with dynamical noise

NASA Astrophysics Data System (ADS)

Benedetti, Claudia; Buscemi, Fabrizio; Bordone, Paolo; Paris, Matteo G. A.

2016-04-01

We address the dynamics of continuous-time quantum walks on one-dimensional disordered lattices inducing dynamical noise in the system. Noise is described as time-dependent fluctuations of the tunneling amplitudes between adjacent sites, and attention is focused on non-Gaussian telegraph noise, going beyond the usual assumption of fast Gaussian noise. We observe the emergence of two different dynamical behaviors for the walker, corresponding to two opposite noise regimes: slow noise (i.e., strong coupling with the environment) confines the walker into few lattice nodes, while fast noise (weak coupling) induces a transition between quantum and classical diffusion over the lattice. A phase transition between the two dynamical regimes may be observed by tuning the ratio between the autocorrelation time of the noise and the coupling between the walker and the external environment generating the noise. We also address the non-Markovianity of the quantum map by assessing its memory effects, as well as evaluating the information backflow to the system. Our results suggest that the non-Markovian character of the evolution is linked to the dynamical behavior in the slow noise regime, and that fast noise induces a Markovian dynamics for the walker.

Selective predation and productivity jointly drive complex behavior in host-parasite systems.

PubMed

Hall, Spencer R; Duffy, Meghan A; Cáceres, Carla E

2005-01-01

Successful invasion of a parasite into a host population and resulting host-parasite dynamics can depend crucially on other members of a host's community such as predators. We do not fully understand how predation intensity and selectivity shape host-parasite dynamics because the interplay between predator density, predator foraging behavior, and ecosystem productivity remains incompletely explored. By modifying a standard susceptible-infected model, we show how productivity can modulate complex behavior induced by saturating and selective foraging behavior of predators in an otherwise stable host-parasite system. When predators strongly prefer parasitized hosts, the host-parasite system can oscillate, but predators can also create alternative stable states, Allee effects, and catastrophic extinction of parasites. In the latter three cases, parasites have difficulty invading and/or persisting in ecosystems. When predators are intermediately selective, these more complex behaviors become less important, but the host-parasite system can switch from stable to oscillating and then back to stable states along a gradient of predator control. Surprisingly, at higher productivity, predators that neutrally select or avoid parasitized hosts can catalyze extinction of both hosts and parasites. Thus, synergy between two enemies can end disastrously for the host. Such diverse outcomes underscore the crucial importance of the community and ecosystem context in which host-parasite interactions occur.

Continuous variable quantum optical simulation for time evolution of quantum harmonic oscillators

PubMed Central

Deng, Xiaowei; Hao, Shuhong; Guo, Hong; Xie, Changde; Su, Xiaolong

2016-01-01

Quantum simulation enables one to mimic the evolution of other quantum systems using a controllable quantum system. Quantum harmonic oscillator (QHO) is one of the most important model systems in quantum physics. To observe the transient dynamics of a QHO with high oscillation frequency directly is difficult. We experimentally simulate the transient behaviors of QHO in an open system during time evolution with an optical mode and a logical operation system of continuous variable quantum computation. The time evolution of an atomic ensemble in the collective spontaneous emission is analytically simulated by mapping the atomic ensemble onto a QHO. The measured fidelity, which is used for quantifying the quality of the simulation, is higher than its classical limit. The presented simulation scheme provides a new tool for studying the dynamic behaviors of QHO. PMID:26961962

Dissipative gravitational bouncer on a vibrating surface

NASA Astrophysics Data System (ADS)

Espinoza Ortiz, J. S.; Lagos, R. E.

2017-12-01

We study the dynamical behavior of a particle flying under the influence of a gravitational field, with dissipation constant λ (Stokes-like), colliding successive times against a rigid surface vibrating harmonically with restitution coefficient α. We define re-scaled dimensionless dynamical variables, such as the relative particle velocity Ω with respect to the surface’s velocity; and the real parameter τ accounting for the temporal evolution of the system. At the particle-surface contact point and for the k‧th collision, we construct the mapping described by (τk ; Ω k ) in order to analyze the system’s nonlinear dynamical behavior. From the dynamical mapping, the fixed point trajectory is computed and its stability is analyzed. We find the dynamical behavior of the fixed point trajectory to be stable or unstable, depending on the values of the re-scaled vibrating surface amplitude Γ, the restitution coefficient α and the damping constant λ. Other important dynamical aspects such as the phase space volume and the one cycle vibrating surface (decomposed into absorbing and transmitting regions) are also discussed. Furthermore, the model rescues well known results in the limit λ = 0.

Dynamic Light Scattering Study of Pig Vitreous Body

NASA Astrophysics Data System (ADS)

Matsuura, Toyoaki; Idota, Naokazu; Hara, Yoshiaki; Annaka, Masahiko

The phase behaviors and dynamical properties of pig vitreous body were studied by macroscopic observation of swelling behavior and dynamic light scattering under various conditions. From the observations of the dynamics of light scattered by the pig vitreous body under physiological condition, intensity autocorrelation functions that revealed two diffusion coefficients, D fast and D slow were obtained. We developed the theory for describing the density fluctuation of the entities in the vitreous gel system with sodium hyaluronate filled in the meshes of collagen fiber network. The dynamics of collagen and sodium hyaluronate explains two relaxation modes of the fluctuation. The diffusion coefficient of collagen obtained from D fast and D slow is very close to that in aqueous solution, which suggests the vitreous body is in the swollen state. Divergent behavior in the measured total scattered light intensities and diffusion coefficients upon varying the concentration of salt (NaCl and CaCl2) was observed. Namely, a slowing down of the dynamic modes accompanied by increased “static” scattered intensities was observed. This is indicative of the occurrence of a phase transition upon salt concentration.

Backward bifurcations, turning points and rich dynamics in simple disease models.

PubMed

Zhang, Wenjing; Wahl, Lindi M; Yu, Pei

2016-10-01

In this paper, dynamical systems theory and bifurcation theory are applied to investigate the rich dynamical behaviours observed in three simple disease models. The 2- and 3-dimensional models we investigate have arisen in previous investigations of epidemiology, in-host disease, and autoimmunity. These closely related models display interesting dynamical behaviors including bistability, recurrence, and regular oscillations, each of which has possible clinical or public health implications. In this contribution we elucidate the key role of backward bifurcations in the parameter regimes leading to the behaviors of interest. We demonstrate that backward bifurcations with varied positions of turning points facilitate the appearance of Hopf bifurcations, and the varied dynamical behaviors are then determined by the properties of the Hopf bifurcation(s), including their location and direction. A Maple program developed earlier is implemented to determine the stability of limit cycles bifurcating from the Hopf bifurcation. Numerical simulations are presented to illustrate phenomena of interest such as bistability, recurrence and oscillation. We also discuss the physical motivations for the models and the clinical implications of the resulting dynamics.

Critical dynamics in population vaccinating behavior.

PubMed

Pananos, A Demetri; Bury, Thomas M; Wang, Clara; Schonfeld, Justin; Mohanty, Sharada P; Nyhan, Brendan; Salathé, Marcel; Bauch, Chris T

2017-12-26

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena-special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles-mumps-rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014-2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior-disease systems, the population responds to the outbreak by moving away from the tipping point, causing "critical speeding up" whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal. Copyright © 2017 the Author(s). Published by PNAS.

Dynamic self-organization of side-propelling colloidal rods: experiments and simulations.

PubMed

Vutukuri, Hanumantha Rao; Preisler, Zdeněk; Besseling, Thijs H; van Blaaderen, Alfons; Dijkstra, Marjolein; Huck, Wilhelm T S

2016-12-06

In recent years, there is a growing interest in designing artificial analogues of living systems, fueled not only by potential applications as 'smart micro-machines', but also by the demand for simple models that can be used to study the behavior of their more complex natural counterparts. Here, we present a facile, internally driven, experimental system comprised of fluorescently labeled colloidal silica rods of which the self-propulsion is powered by the decomposition of H 2 O 2 catalyzed by a length-wise half Pt coating of the particles in order to study how shape anisotropy and swimming direction affect the collective behavior. We investigated the emerging structures and their time evolution for various particle concentrations in (quasi-)two dimensional systems for three aspect ratios of the rods on a single particle level using a combination of experiments and simulations. We found that the dynamic self-organization relied on a competition between self-propulsion and phoretic attractions induced by phoresis of the rods. We observed that the particle clustering behavior depends on the concentration as well as the aspect ratio of the rods. Our findings provide a more detailed understanding of dynamic self-organization of anisotropic particles and the role the propulsion direction plays in internally driven systems.

Web-based experiments for the study of collective social dynamics in cultural markets.

PubMed

Salganik, Matthew J; Watts, Duncan J

2009-07-01

Social scientists are often interested in understanding how the dynamics of social systems are driven by the behavior of individuals that make up those systems. However, this process is hindered by the difficulty of experimentally studying how individual behavioral tendencies lead to collective social dynamics in large groups of people interacting over time. In this study, we investigate the role of social influence, a process well studied at the individual level, on the puzzling nature of success for cultural products such as books, movies, and music. Using a "multiple-worlds" experimental design, we are able to isolate the causal effect of an individual-level mechanism on collective social outcomes. We employ this design in a Web-based experiment in which 2,930 participants listened to, rated, and downloaded 48 songs by up-and-coming bands. Surprisingly, despite relatively large differences in the demographics, behavior, and preferences of participants, the experimental results at both the individual and collective levels were similar to those found in Salganik, Dodds, and Watts (2006). Further, by comparing results from two distinct pools of participants, we are able to gain new insights into the role of individual behavior on collective outcomes. We conclude with a discussion of the strengths and weaknesses of Web-based experiments to address questions of collective social dynamics. Copyright © 2009 Cognitive Science Society, Inc.

Web-based experiments for the study of collective social dynamics in cultural markets

PubMed Central

Salganik, Matthew J.; Watts, Duncan J.

2013-01-01

Social scientists are often interested in understanding how the dynamics of social systems are driven by the behavior of individuals that make up those systems. However, this process is hindered by the difficulty of experimentally studying how individual behavioral tendencies lead to collective social dynamics in large groups of people interacting over time. In this paper we investigate the role of social influence, a process well studied at the individual level, on the puzzling nature of success for cultural products such as books, movies, and music. Using a “multiple-worlds” experimental design we are able to isolate the causal effect of an individual level mechanism on collective social outcomes. We employ this design in a web-based experiment in which 2,930 participants listened to, rated, and download 48 songs by up-and-coming bands. Surprisingly, despite relatively large differences in the demographics, behavior, and preferences of participants, the experimental results at both the individual and collective level were similar to those found in Salganik, Dodds, and Watts (2006). Further, by comparing results from two distinct pools of participants we are able to gain new insights into the role of individual behavior on collective outcomes. We conclude with a discussion of the strengths and weaknesses of web-based experiments to address questions of collective social dynamics. PMID:25164996

CELFE: Coupled Eulerian-Lagrangian Finite Element program for high velocity impact. Part 1: Theory and formulation. [hydroelasto-viscoplastic model

NASA Technical Reports Server (NTRS)

Lee, C. H.

1978-01-01

A 3-D finite element program capable of simulating the dynamic behavior in the vicinity of the impact point, together with predicting the dynamic response in the remaining part of the structural component subjected to high velocity impact is discussed. The finite algorithm is formulated in a general moving coordinate system. In the vicinity of the impact point contained by a moving failure front, the relative velocity of the coordinate system will approach the material particle velocity. The dynamic behavior inside the region is described by Eulerian formulation based on a hydroelasto-viscoplastic model. The failure front which can be regarded as the boundary of the impact zone is described by a transition layer. The layer changes the representation from the Eulerian mode to the Lagrangian mode outside the failure front by varying the relative velocity of the coordinate system to zero. The dynamic response in the remaining part of the structure described by the Lagrangian formulation is treated using advanced structural analysis. An interfacing algorithm for coupling CELFE with NASTRAN is constructed to provide computational capabilities for large structures.

Multi-source micro-friction identification for a class of cable-driven robots with passive backbone

NASA Astrophysics Data System (ADS)

Tjahjowidodo, Tegoeh; Zhu, Ke; Dailey, Wayne; Burdet, Etienne; Campolo, Domenico

2016-12-01

This paper analyses the dynamics of cable-driven robots with a passive backbone and develops techniques for their dynamic identification, which are tested on the H-Man, a planar cabled differential transmission robot for haptic interaction. The mechanism is optimized for human-robot interaction by accounting for the cost-benefit-ratio of the system, specifically by eliminating the necessity of an external force sensor to reduce the overall cost. As a consequence, this requires an effective dynamic model for accurate force feedback applications which include friction behavior in the system. We first consider the significance of friction in both the actuator and backbone spaces. Subsequently, we study the required complexity of the stiction model for the application. Different models representing different levels of complexity are investigated, ranging from the conventional approach of Coulomb to an advanced model which includes hysteresis. The results demonstrate each model's ability to capture the dynamic behavior of the system. In general, it is concluded that there is a trade-off between model accuracy and the model cost.

Quasi-Steady-State Analysis based on Structural Modules and Timed Petri Net Predict System's Dynamics: The Life Cycle of the Insulin Receptor.

PubMed

Scheidel, Jennifer; Lindauer, Klaus; Ackermann, Jörg; Koch, Ina

2015-12-17

The insulin-dependent activation and recycling of the insulin receptor play an essential role in the regulation of the energy metabolism, leading to a special interest for pharmaceutical applications. Thus, the recycling of the insulin receptor has been intensively investigated, experimentally as well as theoretically. We developed a time-resolved, discrete model to describe stochastic dynamics and study the approximation of non-linear dynamics in the context of timed Petri nets. Additionally, using a graph-theoretical approach, we analyzed the structure of the regulatory system and demonstrated the close interrelation of structural network properties with the kinetic behavior. The transition invariants decomposed the model into overlapping subnetworks of various sizes, which represent basic functional modules. Moreover, we computed the quasi-steady states of these subnetworks and demonstrated that they are fundamental to understand the dynamic behavior of the system. The Petri net approach confirms the experimental results of insulin-stimulated degradation of the insulin receptor, which represents a common feature of insulin-resistant, hyperinsulinaemic states.

Moving Word Learning to a Novel Space: A Dynamic Systems View of Referent Selection and Retention

ERIC Educational Resources Information Center

Samuelson, Larissa K.; Kucker, Sarah C.; Spencer, John P.

2017-01-01

Theories of cognitive development must address both the issue of how children bring their knowledge to bear on behavior in-the-moment, and how knowledge changes over time. We argue that seeking answers to these questions requires an appreciation of the dynamic nature of the developing system in its full, reciprocal complexity. We illustrate this…

Simulation of Long-Term Landscape-Level Fuel Treatment Effects on Large Wildfires

Treesearch

Mark A. Finney; Rob C. Seli; Charles W. McHugh; Alan A. Ager; Berni Bahro; James K. Agee

2006-01-01

A simulation system was developed to explore how fuel treatments placed in random and optimal spatial patterns affect the growth and behavior of large fires when implemented at different rates over the course of five decades. The system consists of a forest/fuel dynamics simulation module (FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel...

MODEL-Based Methodology for System of Systems Architecture Development with Application to the Recapitalization of the Future Towing and Salvage Platform

DTIC Science & Technology

2008-09-01

SEP) is a comprehensive , iterative and recursive problem solving process, applied sequentially top-down by integrated teams. It transforms needs...central integrated design repository. It includes a comprehensive behavior modeling notation to understand the dynamics of a design. CORE is a MBSE...37 F. DYNAMIC POSITIONING..........................................................................38 G. FIREFIGHTING

Quench dynamics of a dissipative Rydberg gas in the classical and quantum regimes

NASA Astrophysics Data System (ADS)

Gribben, Dominic; Lesanovsky, Igor; Gutiérrez, Ricardo

2018-01-01

Understanding the nonequilibrium behavior of quantum systems is a major goal of contemporary physics. Much research is currently focused on the dynamics of many-body systems in low-dimensional lattices following a quench, i.e., a sudden change of parameters. Already such a simple setting poses substantial theoretical challenges for the investigation of the real-time postquench quantum dynamics. In classical many-body systems, the Kolmogorov-Mehl-Johnson-Avrami model describes the phase transformation kinetics of a system that is quenched across a first-order phase transition. Here, we show that a similar approach can be applied for shedding light on the quench dynamics of an interacting gas of Rydberg atoms, which has become an important experimental platform for the investigation of quantum nonequilibrium effects. We are able to gain an analytical understanding of the time evolution following a sudden quench from an initial state devoid of Rydberg atoms and identify strikingly different behaviors of the excitation growth in the classical and quantum regimes. Our approach allows us to describe quenches near a nonequilibrium phase transition and provides an approximate analytical solution deep in the quantum domain.

Analysis of dynamic cantilever behavior in tapping mode atomic force microscopy.

PubMed

Deng, Wenqi; Zhang, Guang-Ming; Murphy, Mark F; Lilley, Francis; Harvey, David M; Burton, David R

2015-10-01

Tapping mode atomic force microscopy (AFM) provides phase images in addition to height and amplitude images. Although the behavior of tapping mode AFM has been investigated using mathematical modeling, comprehensive understanding of the behavior of tapping mode AFM still poses a significant challenge to the AFM community, involving issues such as the correct interpretation of the phase images. In this paper, the cantilever's dynamic behavior in tapping mode AFM is studied through a three dimensional finite element method. The cantilever's dynamic displacement responses are firstly obtained via simulation under different tip-sample separations, and for different tip-sample interaction forces, such as elastic force, adhesion force, viscosity force, and the van der Waals force, which correspond to the cantilever's action upon various different representative computer-generated test samples. Simulated results show that the dynamic cantilever displacement response can be divided into three zones: a free vibration zone, a transition zone, and a contact vibration zone. Phase trajectory, phase shift, transition time, pseudo stable amplitude, and frequency changes are then analyzed from the dynamic displacement responses that are obtained. Finally, experiments are carried out on a real AFM system to support the findings of the simulations. © 2015 Wiley Periodicals, Inc.

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Fractional Relativistic Yamaleev Oscillator Model and Its Dynamical Behaviors

NASA Astrophysics Data System (ADS)

Luo, Shao-Kai; He, Jin-Man; Xu, Yan-Li; Zhang, Xiao-Tian

2016-07-01

In the paper we construct a new kind of fractional dynamical model, i.e. the fractional relativistic Yamaleev oscillator model, and explore its dynamical behaviors. We will find that the fractional relativistic Yamaleev oscillator model possesses Lie algebraic structure and satisfies generalized Poisson conservation law. We will also give the Poisson conserved quantities of the model. Further, the relation between conserved quantities and integral invariants of the model is studied and it is proved that, by using the Poisson conserved quantities, we can construct integral invariants of the model. Finally, the stability of the manifold of equilibrium states of the fractional relativistic Yamaleev oscillator model is studied. The paper provides a general method, i.e. fractional generalized Hamiltonian method, for constructing a family of fractional dynamical models of an actual dynamical system.

Dynamics of polymerization induced phase separation in reactive polymer blends

NASA Astrophysics Data System (ADS)

Lee, Jaehyung

Mechanisms and dynamics of phase decomposition following polymerization induced phase separation (PIPS) of reactive polymer blends have been investigated experimentally and theoretically. The phenomenon of PIPS is a non-equilibrium and non-linear dynamic process. The mechanism of PIPS has been thought to be a nucleation and growth (NG) type originally, however, newer results indicate spinodal decomposition (SD). In PIPS, the coexistence curve generally passes through the reaction temperature at off-critical compositions, thus phase separation has to be initiated first in the metastable region where nucleation occurs. When the system farther drifts from the metastable to unstable region, the NG structure transforms to the SD bicontinuous morphology. The crossover behavior of PIPS may be called nucleation initiated spinodal decomposition (NISD). The formation of newer domains between the existing ones is responsible for the early stage of PIPS. Since PIPS is non- equilibrium kinetic process, it would not be surprising to discern either or both structures. The phase separation dynamics of DGEBA/CTBN mixtures having various kinds of curing agents from low reactivity to high reactivity and various amount of curing agents were examined at various reaction temperatures. The phase separation behavior was monitored by a quantity of scattered light intensity experimentally and by a quantity of collective structure factor numerically. Prior to the study of phase separation dynamics, a preliminary investigation on the isothermal cure behavior of the mixtures were executed in order to determine reaction kinetics parameters. The cure behavior followed the overall second order reaction kinetics. Next, based on the knowledge obtained from the phase separation dynamics study of DGEBA/CTBN mixtures, the phase separation dynamics of various composition of DGEBA/R45EPI mixtures having MDA as a curing agent were investigated. The phase separation behavior was quite dependent upon the composition variation. R45EPI itself can react with itself or with DGEBA without curing, therefore three-component system was considered in this mixture. For the numerical studies of this three- component mixture, a system that is composed of a reactive component-1 that is miscible with its growing molecules and another reactive component-2 that is not miscible with its growing molecules was considered with crosslinking reaction kinetics of the each component.

The dynamics of a harvested predator-prey system with Holling type IV functional response.

PubMed

Liu, Xinxin; Huang, Qingdao

2018-05-31

The paper aims to investigate the dynamical behavior of a predator-prey system with Holling type IV functional response in which both the species are subject to capturing. We mainly consider how the harvesting affects equilibria, stability, limit cycles and bifurcations in this system. We adopt the method of qualitative and quantitative analysis, which is based on the dynamical theory, bifurcation theory and numerical simulation. The boundedness of solutions, the existence and stability of equilibrium points of the system are further studied. Based on the Sotomayor's theorem, the existence of transcritical bifurcation and saddle-node bifurcation are derived. We use the normal form theorem to analyze the Hopf bifurcation. Simulation results show that the first Lyapunov coefficient is negative and a stable limit cycle may bifurcate. Numerical simulations are performed to make analytical studies more complete. This work illustrates that using the harvesting effort as control parameter can change the behaviors of the system, which may be useful for the biological management. Copyright © 2018 Elsevier B.V. All rights reserved.

Human Adaptive Behavior in Common Pool Resource Systems

PubMed Central

Brandt, Gunnar; Merico, Agostino; Vollan, Björn; Schlüter, Achim

2012-01-01

Overexploitation of common-pool resources, resulting from uncooperative harvest behavior, is a major problem in many social-ecological systems. Feedbacks between user behavior and resource productivity induce non-linear dynamics in the harvest and the resource stock that complicate the understanding and the prediction of the co-evolutionary system. With an adaptive model constrained by data from a behavioral economic experiment, we show that users’ expectations of future pay-offs vary as a result of the previous harvest experience, the time-horizon, and the ability to communicate. In our model, harvest behavior is a trait that adjusts to continuously changing potential returns according to a trade-off between the users’ current harvest and the discounted future productivity of the resource. Given a maximum discount factor, which quantifies the users’ perception of future pay-offs, the temporal dynamics of harvest behavior and ecological resource can be predicted. Our results reveal a non-linear relation between the previous harvest and current discount rates, which is most sensitive around a reference harvest level. While higher than expected returns resulting from cooperative harvesting in the past increase the importance of future resource productivity and foster sustainability, harvests below the reference level lead to a downward spiral of increasing overexploitation and disappointing returns. PMID:23285180

Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

DOE PAGES

Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

2015-04-01

The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu 40Zr 51Al 9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T x ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T m ~ 900K),more » and the crossover temperature is roughly twice of the glass-transition temperature (T g). Below T x, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T x and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

Access Control for Cooperation Systems Based on Group Situation

NASA Astrophysics Data System (ADS)

Kim, Minsoo; Joshi, James B. D.; Kim, Minkoo

Cooperation systems characterize many emerging environments such as ubiquitous and pervasive systems. Agent based cooperation systems have been proposed in the literature to address challenges of such emerging application environments. A key aspect of such agent based cooperation system is the group situation that changes dynamically and governs the requirements of the cooperation. While individual agent context is important, the overall cooperation behavior is more driven by the group context because of relationships and interactions between agents. Dynamic access control based on group situation is a crucial challenge in such cooperation systems. In this paper we propose a dynamic role based access control model for cooperation systems based on group situation. The model emphasizes capability based agent to role mapping and group situation based permission assignment to allow capturing dynamic access policies that evolve continuously.

True orbit simulation of piecewise linear and linear fractional maps of arbitrary dimension using algebraic numbers

NASA Astrophysics Data System (ADS)

Saito, Asaki; Yasutomi, Shin-ichi; Tamura, Jun-ichi; Ito, Shunji

2015-06-01

We introduce a true orbit generation method enabling exact simulations of dynamical systems defined by arbitrary-dimensional piecewise linear fractional maps, including piecewise linear maps, with rational coefficients. This method can generate sufficiently long true orbits which reproduce typical behaviors (inherent behaviors) of these systems, by properly selecting algebraic numbers in accordance with the dimension of the target system, and involving only integer arithmetic. By applying our method to three dynamical systems—that is, the baker's transformation, the map associated with a modified Jacobi-Perron algorithm, and an open flow system—we demonstrate that it can reproduce their typical behaviors that have been very difficult to reproduce with conventional simulation methods. In particular, for the first two maps, we show that we can generate true orbits displaying the same statistical properties as typical orbits, by estimating the marginal densities of their invariant measures. For the open flow system, we show that an obtained true orbit correctly converges to the stable period-1 orbit, which is inherently possessed by the system.

A methodology for the efficient integration of transient constraints in the design of aircraft dynamic systems

NASA Astrophysics Data System (ADS)

Phan, Leon L.

The motivation behind this thesis mainly stems from previous work performed at Hispano-Suiza (Safran Group) in the context of the European research project "Power Optimised Aircraft". Extensive testing on the COPPER Bird RTM, a test rig designed to characterize aircraft electrical networks, demonstrated the relevance of transient regimes in the design and development of dynamic systems. Transient regimes experienced by dynamic systems may have severe impacts on the operation of the aircraft. For example, the switching on of a high electrical load might cause a network voltage drop inducing a loss of power available to critical aircraft systems. These transient behaviors are thus often regulated by dynamic constraints, requiring the dynamic signals to remain within bounds whose values vary with time. The verification of these peculiar types of constraints, which generally requires high-fidelity time-domain simulation, intervenes late in the system development process, thus potentially causing costly design iterations. The research objective of this thesis is to develop a methodology that integrates the verification of dynamic constraints in the early specification of dynamic systems. In order to circumvent the inefficiencies of time-domain simulation, multivariate dynamic surrogate models of the original time-domain simulation models are generated, building on a nonlinear system identification technique using wavelet neural networks (or wavenets), which allow the multiscale nature of transient signals to be captured. However, training multivariate wavenets can become computationally prohibitive as the number of design variables increases. Therefore, an alternate approach is formulated, in which dynamic surrogate models using sigmoid-based neural networks are used to emulate the transient behavior of the envelopes of the time-domain response. Thus, in order to train the neural network, the envelopes are extracted by first separating the scales of the dynamic response, using a multiresolution analysis (MRA) based on the discrete wavelet transform. The MRA separates the dynamic response into a trend and a noise signal (ripple). The envelope of the noise is then computed with a windowing method, and recombined with the trend in order to reconstruct the global envelope of the dynamic response. The run-time efficiency of the resulting dynamic surrogate models enable the implementation of a data farming approach, in which a Monte-Carlo simulation generates time-domain behaviors of transient responses for a vast set of design and operation scenarios spanning the design and operation space. An interactive visualization environment, enabling what-if analyses, will be developed; the user can thereby instantaneously comprehend the transient response of the system (or its envelope) and its sensitivities to design and operation variables, as well as filter the design space to have it exhibit only the design scenarios verifying the dynamic constraints. The proposed methodology, along with its foundational hypotheses, are tested on the design and optimization of a 350VDC network, where a generator and its control system are concurrently designed in order to minimize the electrical losses, while ensuring that the transient undervoltage induced by peak demands in the consumption of a motor does not violate transient power quality constraints.

Hybrid particle-continuum simulations coupling Brownian dynamics and local dynamic density functional theory.

PubMed

Qi, Shuanhu; Schmid, Friederike

2017-11-08

We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense such that particles can switch their level of resolution on the fly. The switching of resolution is controlled by a tuning function which can be chosen at will according to the geometry of the system. As an application, the hybrid scheme is used to study the kinetics of interfacial broadening of a polymer blend, and is validated by comparing the results to the predictions from pure Brownian dynamics and pure local dynamics calculations.

Dynamic Models of the U.S. Automobile Fleet

DOT National Transportation Integrated Search

1977-08-01

The report examines some of the dynamic properties of the automobile fleet. The focus is not on new-car demand, but rather on the overall behavior of the system. Relationships derived from previous studies have been incorporated and integrated in a s...

Dynamical singularities for complex initial conditions and the motion at a real separatrix.

PubMed

Shnerb, Tamar; Kay, K G

2006-04-01

This work investigates singularities occurring at finite real times in the classical dynamics of one-dimensional double-well systems with complex initial conditions. The objective is to understand the relationship between these singularities and the behavior of the systems for real initial conditions. An analytical treatment establishes that the dynamics of a quartic double well system possesses a doubly infinite sequence of singularities. These are associated with initial conditions that converge to those for the real separatrix as the singularity time becomes infinite. This confluence of singularities is shown to lead to the unstable behavior that characterizes the real motion at the separatrix. Numerical calculations confirm the existence of a large number of singularities converging to the separatrix for this and two additional double-well systems. The approach of singularities to the real axis is of particular interest since such behavior has been related to the formation of chaos in nonintegrable systems. The properties of the singular trajectories which cause this convergence to the separatrix are identified. The hyperbolic fixed point corresponding to the potential energy maximum, responsible for the characteristic motion at a separatrix, also plays a critical role in the formation of the complex singularities by delaying trajectories and then deflecting them into asymptotic regions of space from where they are directly repelled to infinity in a finite time.

Investigation of the nonlinear seismic behavior of knee braced frames using the incremental dynamic analysis method

NASA Astrophysics Data System (ADS)

Sheidaii, Mohammad Reza; TahamouliRoudsari, Mehrzad; Gordini, Mehrdad

2016-06-01

In knee braced frames, the braces are attached to the knee element rather than the intersection of beams and columns. This bracing system is widely used and preferred over the other commonly used systems for reasons such as having lateral stiffness while having adequate ductility, damage concentration on the second degree convenience of repairing and replacing of these elements after Earthquake. The lateral stiffness of this system is supplied by the bracing member and the ductility of the frame attached to the knee length is supplied through the bending or shear yield of the knee member. In this paper, the nonlinear seismic behavior of knee braced frame systems has been investigated using incremental dynamic analysis (IDA) and the effects of the number of stories in a building, length and the moment of inertia of the knee member on the seismic behavior, elastic stiffness, ductility and the probability of failure of these systems has been determined. In the incremental dynamic analysis, after plotting the IDA diagrams of the accelerograms, the collapse diagrams in the limit states are determined. These diagrams yield that for a constant knee length with reduced moment of inertia, the probability of collapse in limit states heightens and also for a constant knee moment of inertia with increasing length, the probability of collapse in limit states increases.

Self-organization of complex networks as a dynamical system

NASA Astrophysics Data System (ADS)

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Self-organization of complex networks as a dynamical system.

PubMed

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

From synthetic modeling of social interaction to dynamic theories of brain-body-environment-body-brain systems.

PubMed

Froese, Tom; Iizuka, Hiroyuki; Ikegami, Takashi

2013-08-01

Synthetic approaches to social interaction support the development of a second-person neuroscience. Agent-based models and psychological experiments can be related in a mutually informing manner. Models have the advantage of making the nonlinear brain-body-environment-body-brain system as a whole accessible to analysis by dynamical systems theory. We highlight some general principles of how social interaction can partially constitute an individual's behavior.

Dynamics of a modified Hindmarsh-Rose neural model with random perturbations: Moment analysis and firing activities

NASA Astrophysics Data System (ADS)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

In this paper, an attempt has been made to understand the activity of mean membrane voltage and subsidiary system variables with moment equations (i.e., mean, variance and covariance's) under noisy environment. We consider a biophysically plausible modified Hindmarsh-Rose (H-R) neural system injected by an applied current exhibiting spiking-bursting phenomenon. The effects of predominant parameters on the dynamical behavior of a modified H-R system are investigated. Numerically, it exhibits period-doubling, period halving bifurcation and chaos phenomena. Further, a nonlinear system has been analyzed for the first and second order moments with additive stochastic perturbations. It has been solved using fourth order Runge-Kutta method and noisy systems by Euler's scheme. It has been demonstrated that the firing properties of neurons to evoke an action potential in a certain parameter space of the large exact systems can be estimated using an approximated model. Strong stimulation can cause a change in increase or decrease of the firing patterns. Corresponding to a fixed set of parameter values, the firing behavior and dynamical differences of the collective variables of a large, exact and approximated systems are investigated.

Dynamic analysis and electronic circuit implementation of a novel 3D autonomous system without linear terms

NASA Astrophysics Data System (ADS)

Kengne, J.; Jafari, S.; Njitacke, Z. T.; Yousefi Azar Khanian, M.; Cheukem, A.

2017-11-01

Mathematical models (ODEs) describing the dynamics of almost all continuous time chaotic nonlinear systems (e.g. Lorenz, Rossler, Chua, or Chen system) involve at least a nonlinear term in addition to linear terms. In this contribution, a novel (and singular) 3D autonomous chaotic system without linear terms is introduced. This system has an especial feature of having two twin strange attractors: one ordinary and one symmetric strange attractor when the time is reversed. The complex behavior of the model is investigated in terms of equilibria and stability, bifurcation diagrams, Lyapunov exponent plots, time series and Poincaré sections. Some interesting phenomena are found including for instance, period-doubling bifurcation, antimonotonicity (i.e. the concurrent creation and annihilation of periodic orbits) and chaos while monitoring the system parameters. Compared to the (unique) case previously reported by Xu and Wang (2014) [31], the system considered in this work displays a more 'elegant' mathematical expression and experiences richer dynamical behaviors. A suitable electronic circuit (i.e. the analog simulator) is designed and used for the investigations. Pspice based simulation results show a very good agreement with the theoretical analysis.

Long-term aging behaviors in a model soft colloidal system.

PubMed

Li, Qi; Peng, Xiaoguang; McKenna, Gregory B

2017-02-15

Colloidal and molecular systems share similar behaviors near to the glass transition volume fraction or temperature. Here, aging behaviors after volume fraction up-jump (induced by performing temperature down-jumps) conditions for a PS-PNIPAM/AA soft colloidal system were investigated using light scattering (diffusing wave spectroscopy, DWS). Both aging responses and equilibrium dynamics were investigated. For the aging responses, long-term experiments (100 000 s) were performed, and both equilibrium and non-equilibrium behaviors of the system were obtained. In the equilibrium state, as effective volume fraction increases (or temperature decreases), the colloidal dispersion displays a transition from the liquid to a glassy state. The equilibrium α-relaxation dynamics strongly depend on both the effective volume fraction and the initial mass concentration for the studied colloidal systems. Compared with prior results from our lab [X. Di, X. Peng and G. B. McKenna, J. Chem. Phys., 2014, 140, 054903], the effective volume fractions investigated spanned a wider range, to deeper into the glassy domain. The results show that the α-relaxation time τ α of the samples aged into equilibrium deviate from the classical Vogel-Fulcher-Tammann (VFT)-type expectations and the super-Arrhenius signature disappears above the glass transition volume fraction. The non-equilibrium aging response shows that the time for the structural evolution into equilibrium and the α-relaxation time are decoupled. The DWS investigation of the aging behavior after different volume fraction jumps reveals a different non-equilibrium or aging behavior for the considered colloidal systems compared with either molecular glasses or the macroscopic rheology of a similar colloidal dispersions.

Bütschli dynamic droplet system.

PubMed

Armstrong, Rachel; Hanczyc, Martin

2013-01-01

Dynamical oil-water systems such as droplets display lifelike properties and may lend themselves to chemical programming to perform useful work, specifically with respect to the built environment. We present Bütschli water-in-oil droplets as a model for further investigation into the development of a technology with living properties. Otto Bütschli first described the system in 1898, when he used alkaline water droplets in olive oil to initiate a saponification reaction. This simple recipe produced structures that moved and exhibited characteristics that resembled, at least superficially, the amoeba. We reconstructed the Bütschli system and observed its life span under a light microscope, observing chemical patterns and droplet behaviors in nearly three hundred replicate experiments. Self-organizing patterns were observed, and during this dynamic, embodied phase the droplets provided a means of introducing temporal and spatial order in the system with the potential for chemical programmability. The authors propose that the discrete formation of dynamic droplets, characterized by their lifelike behavior patterns, during a variable window of time (from 30 s to 30 min after the addition of alkaline water to the oil phase), qualify this system as an example of living technology. The analysis of the Bütschli droplets suggests that a set of conditions may precede the emergence of lifelike characteristics and exemplifies the richness of this rudimentary chemical system, not only for artificial life investigations but also for possible real-world applications in architectural practice.

Parity-time symmetry-breaking mechanism of dynamic Mott transitions in dissipative systems

DOE PAGES

Tripathi, Vikram; Galda, Alexey; Barman, Himadri; ...

2016-07-05

Here, we describe the critical behavior of the electric field-driven (dynamic) Mott insulator-to-metal transitions in dissipative Fermi and Bose systems in terms of non-Hermitian Hamiltonians invariant under simultaneous parity (P) and time-reversal (T) operations. The dynamic Mott transition is identified as a PT symmetry-breaking phase transition, with the Mott insulating state corresponding to the regime of unbroken PT symmetry with a real energy spectrum. We also established that the imaginary part of the Hamiltonian arises from the combined effects of the driving field and inherent dissipation. We derive the renormalization and collapse of the Mott gap at the dielectric breakdownmore » and describe the resulting critical behavior of transport characteristics. The critical exponent we obtained is in an excellent agreement with experimental findings.« less

Nonlinear dynamic failure process of tunnel-fault system in response to strong seismic event

NASA Astrophysics Data System (ADS)

Yang, Zhihua; Lan, Hengxing; Zhang, Yongshuang; Gao, Xing; Li, Langping

2013-03-01

Strong earthquakes and faults have significant effect on the stability capability of underground tunnel structures. This study used a 3-Dimensional Discrete Element model and the real records of ground motion in the Wenchuan earthquake to investigate the dynamic response of tunnel-fault system. The typical tunnel-fault system was composed of one planned railway tunnel and one seismically active fault. The discrete numerical model was prudentially calibrated by means of the comparison between the field survey and numerical results of ground motion. It was then used to examine the detailed quantitative information on the dynamic response characteristics of tunnel-fault system, including stress distribution, strain, vibration velocity and tunnel failure process. The intensive tunnel-fault interaction during seismic loading induces the dramatic stress redistribution and stress concentration in the intersection of tunnel and fault. The tunnel-fault system behavior is characterized by the complicated nonlinear dynamic failure process in response to a real strong seismic event. It can be qualitatively divided into 5 main stages in terms of its stress, strain and rupturing behaviors: (1) strain localization, (2) rupture initiation, (3) rupture acceleration, (4) spontaneous rupture growth and (5) stabilization. This study provides the insight into the further stability estimation of underground tunnel structures under the combined effect of strong earthquakes and faults.

Research in Structures and Dynamics, 1984

NASA Technical Reports Server (NTRS)

Hayduk, R. J. (Compiler); Noor, A. K. (Compiler)

1984-01-01

A symposium on advanced and trends in structures and dynamics was held to communicate new insights into physical behavior and to identify trends in the solution procedures for structures and dynamics problems. Pertinent areas of concern were (1) multiprocessors, parallel computation, and database management systems, (2) advances in finite element technology, (3) interactive computing and optimization, (4) mechanics of materials, (5) structural stability, (6) dynamic response of structures, and (7) advanced computer applications.

Goal Translation: How To Create a Results-Focused Organizational Culture.

ERIC Educational Resources Information Center

Mourier, Pierre

2000-01-01

Presents a model for changing human and organizational behavior. Highlights include behavioral dynamics; expectations; alignment; organizational structure; organizational culture; individual skills and training; leadership; management systems; developing corporate-level goals; communicating goals to the organization; and developing employee goals.…

Dynamic stability analysis for a self-mixing interferometry system.

PubMed

Fan, Yuanlong; Yu, Yanguang; Xi, Jiangtao; Guo, Qinghua

2014-11-17

A self-mixing interferometry (SMI) system is a laser diode (LD) with an external cavity formed by a moving external target. The behavior of an SMI system is governed by the injection current J to the LD and the parameters associated with the external cavity mainly including optical feedback factor C, the initial external cavity length (L₀) and the light phase (ϕ₀) which is mapped to the movement of the target. In this paper, we investigate the dynamic behavior of an SMI system by using the Lang-Kobayashi model. The stability boundary of such system is presented in the plane of (C, ϕ₀), from which a critical C (denoted as C(critical)) is derived. Both simulations and experiments show that the stability can be enhanced by increasing either L₀ or J. Furthermore, three regions on the plane of (C, ϕ₀) are proposed to characterize the behavior of an SMI system, including stable, semi-stable and unstable regions. We found that the existing SMI model is only valid for the stable region, and the semi-stable region has potential applications on sensing and measurement but needs re-modeling the system by considering the bandwidth of the detection components.

[Homeostasis and Disorder of Musculoskeletal System.Cellular dynamics in musculoskeletal system visualized by intravital imaging techniques.

PubMed

Kikuta, Junichi; Ishii, Masaru

Bone is continually remodeled by bone-resorbing osteoclasts and bone-forming osteoblasts. Although it has long been believed that bone homeostasis is tightly regulated by communication between osteoclasts and osteoblasts, the fundamental process and dynamics have remained elusive. We originally established an advanced imaging system to visualize living bone tissues using intravital two-photon microscopy. By means of this system, we revealed the in vivo behavior of bone-resorbing osteoclasts and bone-forming osteoblasts in bone tissues. This approach facilitates investigation of cellular dynamics in the pathogenesis of musculoskeletal disorders, and would thus be useful for evaluating the efficacy of novel therapeutic agents.

Intrinsic information carriers in combinatorial dynamical systems

NASA Astrophysics Data System (ADS)

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features—"sites" for short—characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations—unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are self-consistent descriptors of system dynamics in that their time-evolution is governed by a closed system of kinetic equations. Taken together, fragments are endogenous distinctions that matter for the dynamics of a system, which warrants viewing them as the carriers of information. Although fragments can be thought of as multisets of molecular species (an extensional view), their self-consistency suggests treating them as autonomous aspects cut off from their microscopic realization (an intensional view). Fragmentation is a seeded process that depends on the choice of observables whose dynamics one insists to describe. Different observables can cause distinct fragmentations, in effect altering the set of information carriers that govern the behavior of a system, even though nothing has changed in its microscopic constitution. In this contribution, we present a mathematical specification of fragments, but not an algorithmic implementation. We have described the latter elsewhere in rather technical terms that, although effective, were lacking an embedding into a more general conceptual framework, which we here provide.

Intrinsic information carriers in combinatorial dynamical systems.

PubMed

Harmer, Russ; Danos, Vincent; Feret, Jérôme; Krivine, Jean; Fontana, Walter

2010-09-01

Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations-unless the complexity is radically trimmed. Yet, if combinatorial complexity is key to the system's behavior, eliminating it will prevent, not facilitate, understanding. A more adequate representation of a combinatorial system is provided by a graph-based framework of rewrite rules where each rule specifies only the information that an interaction mechanism depends on. Unlike reactions, which deal with molecular species, rules deal with patterns, i.e., multisets of molecular species. Although the stochastic dynamics induced by a collection of rules on a mixture of molecules can be simulated, it appears useful to capture the system's average or deterministic behavior by means of differential equations. However, expansion of the rules into kinetic equations at the level of molecular species is not only impractical, but conceptually indefensible. If rules describe bona fide patterns of interaction, molecular species are unlikely to constitute appropriate units of dynamics. Rather, we must seek aggregate variables reflective of the causal structure laid down by the rules. We call these variables "fragments" and the process of identifying them "fragmentation." Ideally, fragments are aspects of the system's microscopic population that the set of rules can actually distinguish on average; in practice, it may only be feasible to identify an approximation to this. Most importantly, fragments are self-consistent descriptors of system dynamics in that their time-evolution is governed by a closed system of kinetic equations. Taken together, fragments are endogenous distinctions that matter for the dynamics of a system, which warrants viewing them as the carriers of information. Although fragments can be thought of as multisets of molecular species (an extensional view), their self-consistency suggests treating them as autonomous aspects cut off from their microscopic realization (an intensional view). Fragmentation is a seeded process that depends on the choice of observables whose dynamics one insists to describe. Different observables can cause distinct fragmentations, in effect altering the set of information carriers that govern the behavior of a system, even though nothing has changed in its microscopic constitution. In this contribution, we present a mathematical specification of fragments, but not an algorithmic implementation. We have described the latter elsewhere in rather technical terms that, although effective, were lacking an embedding into a more general conceptual framework, which we here provide.

Fluid dynamic and thermodynamic analysis of a model pertaining to cryogenic fluid management in low gravity environments for a system with dynamically induced settling

NASA Technical Reports Server (NTRS)

Rios, J.

1982-01-01

The settling behavior of the liquid and gaseous phases of a fluid in a propellant and in a zero-g environment, when such settling is induced through the use of a dynamic device, in this particular case, a helical screw was studied. Particular emphasis was given to: (1) the description of a fluid mechanics model which seems applicable to the system under consideration, (2) a First Law of Thermodynamics analysis of the system, and (3) a discussion of applicable scaling rules.

Differential equation models for sharp threshold dynamics.

PubMed

Schramm, Harrison C; Dimitrov, Nedialko B

2014-01-01

We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. Published by Elsevier Inc.

Complexity and dynamics of topological and community structure in complex networks

NASA Astrophysics Data System (ADS)

Berec, Vesna

2017-07-01

Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.

Spontaneous mode switching in coupled oscillators competing for constant amounts of resources

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Aono, Masashi; Hara, Masahiko; Aihara, Kazuyuki

2010-03-01

We propose a widely applicable scheme of coupling that models competitions among dynamical systems for fixed amounts of resources. Two oscillators coupled in this way synchronize in antiphase. Three oscillators coupled circularly show a number of oscillation modes such as rotation and partially in-phase synchronization. Intriguingly, simple oscillators in the model also produce complex behavior such as spontaneous switching among different modes. The dynamics reproduces well the spatiotemporal oscillatory behavior of a true slime mold Physarum, which is capable of computational optimization.

Universal scaling in the aging of the strong glass former SiO{sub 2}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vollmayr-Lee, Katharina, E-mail: kvollmay@bucknell.edu; Gorman, Christopher H.; Castillo, Horacio E.

We show that the aging dynamics of a strong glass former displays a strikingly simple scaling behavior, connecting the average dynamics with its fluctuations, namely, the dynamical heterogeneities. We perform molecular dynamics simulations of SiO{sub 2} with van Beest-Kramer-van Santen interactions, quenching the system from high to low temperature, and study the evolution of the system as a function of the waiting time t{sub w} measured from the instant of the quench. We find that both the aging behavior of the dynamic susceptibility χ{sub 4} and the aging behavior of the probability distribution P(f{sub s,r}) of the local incoherent intermediatemore » scattering function f{sub s,r} can be described by simple scaling forms in terms of the global incoherent intermediate scattering function C. The scaling forms are the same that have been found to describe the aging of several fragile glass formers and that, in the case of P(f{sub s,r}), have been also predicted theoretically. A thorough study of the length scales involved highlights the importance of intermediate length scales. We also analyze directly the scaling dependence on particle type and on wavevector q and find that both the average and the fluctuations of the slow aging dynamics are controlled by a unique aging clock, which is not only independent of the wavevector q, but is also the same for O and Si atoms.« less

The physics of flocking: Correlation as a compass from experiments to theory

NASA Astrophysics Data System (ADS)

Cavagna, Andrea; Giardina, Irene; Grigera, Tomás S.

2018-01-01

Collective behavior in biological systems is a complex topic, to say the least. It runs wildly across scales in both space and time, involving taxonomically vastly different organisms, from bacteria and cell clusters, to insect swarms and up to vertebrate groups. It entails concepts as diverse as coordination, emergence, interaction, information, cooperation, decision-making, and synchronization. Amid this jumble, however, we cannot help noting many similarities between collective behavior in biological systems and collective behavior in statistical physics, even though none of these organisms remotely looks like an Ising spin. Such similarities, though somewhat qualitative, are startling, and regard mostly the emergence of global dynamical patterns qualitatively different from individual behavior, and the development of system-level order from local interactions. It is therefore tempting to describe collective behavior in biology within the conceptual framework of statistical physics, in the hope to extend to this new fascinating field at least part of the great predictive power of theoretical physics. In this review we propose that the conceptual cornerstone of this ambitious program be that of correlation. To illustrate this idea we address the case of collective behavior in bird flocks. Two key threads emerge, as two sides of one single story: the presence of scale-free correlations and the dynamical mechanism of information transfer. We discuss first static correlations in starling flocks, in particular the experimental finding of their scale-free nature, the formulation of models that account for this fact using maximum entropy, and the relation of scale-free correlations to information transfer. This is followed by a dynamic treatment of information propagation (propagation of turns across a flock), starting with a discussion of experimental results and following with possible theoretical explanations of those, which require the addition of behavioral inertia to existing theories of flocking. We finish with the definition and analysis of space-time correlations and their relevance to the detection of inertial behavior in the absence of external perturbations.

Frequency and phase synchronization in large groups: Low dimensional description of synchronized clapping, firefly flashing, and cricket chirping

NASA Astrophysics Data System (ADS)

Ott, Edward; Antonsen, Thomas M.

2017-05-01

A common observation is that large groups of oscillatory biological units often have the ability to synchronize. A paradigmatic model of such behavior is provided by the Kuramoto model, which achieves synchronization through coupling of the phase dynamics of individual oscillators, while each oscillator maintains a different constant inherent natural frequency. Here we consider the biologically likely possibility that the oscillatory units may be capable of enhancing their synchronization ability by adaptive frequency dynamics. We propose a simple augmentation of the Kuramoto model which does this. We also show that, by the use of a previously developed technique [Ott and Antonsen, Chaos 18, 037113 (2008)], it is possible to reduce the resulting dynamics to a lower dimensional system for the macroscopic evolution of the oscillator ensemble. By employing this reduction, we investigate the dynamics of our system, finding a characteristic hysteretic behavior and enhancement of the quality of the achieved synchronization.

Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain

PubMed Central

Kim, Christina K; Yang, Samuel J; Pichamoorthy, Nandini; Young, Noah P; Kauvar, Isaac; Jennings, Joshua H; Lerner, Talia N; Berndt, Andre; Lee, Soo Yeun; Ramakrishnan, Charu; Davidson, Thomas J; Inoue, Masatoshi; Bito, Haruhiko; Deisseroth, Karl

2017-01-01

Real-time activity measurements from multiple specific cell populations and projections are likely to be important for understanding the brain as a dynamical system. Here we developed frame-projected independent-fiber photometry (FIP), which we used to record fluorescence activity signals from many brain regions simultaneously in freely behaving mice. We explored the versatility of the FIP microscope by quantifying real-time activity relationships among many brain regions during social behavior, simultaneously recording activity along multiple axonal pathways during sensory experience, performing simultaneous two-color activity recording, and applying optical perturbation tuned to elicit dynamics that match naturally occurring patterns observed during behavior. PMID:26878381

Complex Dynamics of the Power Transmission Grid (and other Critical Infrastructures)

NASA Astrophysics Data System (ADS)

Newman, David

2015-03-01

Our modern societies depend crucially on a web of complex critical infrastructures such as power transmission networks, communication systems, transportation networks and many others. These infrastructure systems display a great number of the characteristic properties of complex systems. Important among these characteristics, they exhibit infrequent large cascading failures that often obey a power law distribution in their probability versus size. This power law behavior suggests that conventional risk analysis does not apply to these systems. It is thought that much of this behavior comes from the dynamical evolution of the system as it ages, is repaired, upgraded, and as the operational rules evolve with human decision making playing an important role in the dynamics. In this talk, infrastructure systems as complex dynamical systems will be introduced and some of their properties explored. The majority of the talk will then be focused on the electric power transmission grid though many of the results can be easily applied to other infrastructures. General properties of the grid will be discussed and results from a dynamical complex systems power transmission model will be compared with real world data. Then we will look at a variety of uses of this type of model. As examples, we will discuss the impact of size and network homogeneity on the grid robustness, the change in risk of failure as generation mix (more distributed vs centralized for example) changes, as well as the effect of operational changes such as the changing the operational risk aversion or grid upgrade strategies. One of the important outcomes from this work is the realization that ``improvements'' in the system components and operational efficiency do not always improve the system robustness, and can in fact greatly increase the risk, when measured as a risk of large failure.

A computational framework for prime implicants identification in noncoherent dynamic systems.

PubMed

Di Maio, Francesco; Baronchelli, Samuele; Zio, Enrico

2015-01-01

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time-dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple-valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases. © 2014 Society for Risk Analysis.

Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.

PubMed

Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D; Jeong, Jaeseung

2014-08-01

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.

Spatial nonlinearities: Cascading effects in the earth system

USGS Publications Warehouse

Peters, Debra P.C.; Pielke, R.A.; Bestelmeyer, B.T.; Allen, Craig D.; Munson-McGee, Stuart; Havstad, K. M.; Canadell, Josep G.; Pataki, Diane E.; Pitelka, Louis F.

2006-01-01

Nonlinear behavior is prevalent in all aspects of the Earth System, including ecological responses to global change (Gallagher and Appenzeller 1999; Steffen et al. 2004). Nonlinear behavior refers to a large, discontinuous change in response to a small change in a driving variable (Rial et al. 2004). In contrast to linear systems where responses are smooth, well-behaved, continuous functions, nonlinear systems often undergo sharp or discontinuous transitions resulting from the crossing of thresholds. These nonlinear responses can result in surprising behavior that makes forecasting difficult (Kaplan and Glass 1995). Given that many system dynamics are nonlinear, it is imperative that conceptual and quantitative tools be developed to increase our understanding of the processes leading to nonlinear behavior in order to determine if forecasting can be improved under future environmental changes (Clark et al. 2001).

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

NASA Astrophysics Data System (ADS)

Ullrich, Paul A.; Jablonowski, Christiane; Kent, James; Lauritzen, Peter H.; Nair, Ramachandran; Reed, Kevin A.; Zarzycki, Colin M.; Hall, David M.; Dazlich, Don; Heikes, Ross; Konor, Celal; Randall, David; Dubos, Thomas; Meurdesoif, Yann; Chen, Xi; Harris, Lucas; Kühnlein, Christian; Lee, Vivian; Qaddouri, Abdessamad; Girard, Claude; Giorgetta, Marco; Reinert, Daniel; Klemp, Joseph; Park, Sang-Hun; Skamarock, William; Miura, Hiroaki; Ohno, Tomoki; Yoshida, Ryuji; Walko, Robert; Reinecke, Alex; Viner, Kevin

2017-12-01

Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

From dissipative dynamics to studies of heat transfer at the nanoscale: analysis of the spin-boson model.

PubMed

Boudjada, Nazim; Segal, Dvira

2014-11-26

We study in a unified manner the dissipative dynamics and the transfer of heat in the two-bath spin-boson model. We use the Bloch-Redfield (BR) formalism, valid in the very weak system-bath coupling limit, the noninteracting-blip approximation (NIBA), applicable in the nonadiabatic limit, and iterative, numerically exact path integral tools. These methodologies were originally developed for the description of the dissipative dynamics of a quantum system, and here they are applied to explore the problem of quantum energy transport in a nonequilibrium setting. Specifically, we study the weak-to-intermediate system-bath coupling regime at high temperatures kBT/ħ > ε, with ε as the characteristic frequency of the two-state system. The BR formalism and NIBA can lead to close results for the dynamics of the reduced density matrix (RDM) in a certain range of parameters. However, relatively small deviations in the RDM dynamics propagate into significant qualitative discrepancies in the transport behavior. Similarly, beyond the strict nonadiabatic limit NIBA's prediction for the heat current is qualitatively incorrect: It fails to capture the turnover behavior of the current with tunneling energy and temperature. Thus, techniques that proved meaningful for describing the RDM dynamics, to some extent even beyond their rigorous range of validity, should be used with great caution in heat transfer calculations, because qualitative-serious failures develop once parameters are mildly stretched beyond the techniques' working assumptions.

Impact compaction of a granular material

DOE PAGES

Fenton, Gregg; Asay, Blaine; Dalton, Devon

2015-05-19

The dynamic behavior of granular materials has importance to a variety of engineering applications. Structural seismic coupling, planetary science, and earth penetration mechanics, are just a few of the application areas. Although the mechanical behavior of granular materials of various types have been studied extensively for several decades, the dynamic behavior of such materials remains poorly understood. High-quality experimental data are needed to improve our general understanding of granular material compaction physics. This study will describe how an instrumented plunger impact system can be used to measure pressure-density relationships for model materials at high and controlled strain rates and subsequentlymore » used for computational modeling.« less

Analysis and Ground Testing for Validation of the Inflatable Sunshield in Space (ISIS) Experiment

NASA Technical Reports Server (NTRS)

Lienard, Sebastien; Johnston, John; Adams, Mike; Stanley, Diane; Alfano, Jean-Pierre; Romanacci, Paolo

2000-01-01

The Next Generation Space Telescope (NGST) design requires a large sunshield to protect the large aperture mirror and instrument module from constant solar exposure at its L2 orbit. The structural dynamics of the sunshield must be modeled in order to predict disturbances to the observatory attitude control system and gauge effects on the line of site jitter. Models of large, non-linear membrane systems are not well understood and have not been successfully demonstrated. To answer questions about sunshield dynamic behavior and demonstrate controlled deployment, the NGST project is flying a Pathfinder experiment, the Inflatable Sunshield in Space (ISIS). This paper discusses in detail the modeling and ground-testing efforts performed at the Goddard Space Flight Center to: validate analytical tools for characterizing the dynamic behavior of the deployed sunshield, qualify the experiment for the Space Shuttle, and verify the functionality of the system. Included in the discussion will be test parameters, test setups, problems encountered, and test results.

Emergent behaviors of the Schrödinger-Lohe model on cooperative-competitive networks

NASA Astrophysics Data System (ADS)

Huh, Hyungjin; Ha, Seung-Yeal; Kim, Dohyun

2017-12-01

We present several sufficient frameworks leading to the emergent behaviors of the coupled Schrödinger-Lohe (S-L) model under the same one-body external potential on cooperative-competitive networks. The S-L model was first introduced as a possible phenomenological model exhibiting quantum synchronization and its emergent dynamics on all-to-all cooperative networks has been treated via two distinct approaches, Lyapunov functional approach and the finite-dimensional reduction based on pairwise correlations. In this paper, we further generalize the finite-dimensional dynamical systems approach for pairwise correlation functions on cooperative-competitive networks and provide several sufficient frameworks leading to the collective exponential synchronization. For small systems consisting of three and four quantum subsystem, we also show that the system for pairwise correlations can be reduced to the Lotka-Volterra model with cooperative and competitive interactions, in which lots of interesting dynamical patterns appear, e.g., existence of closed orbits and limit-cycles.

A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

Hysteresis compensation for piezoelectric actuators in single-point diamond turning

NASA Astrophysics Data System (ADS)

Wang, Haifeng; Hu, Dejin; Wan, Daping; Liu, Hongbin

2006-02-01

In recent years, interests have been growing for fast tool servo (FTS) systems to increase the capability of existing single-point diamond turning machines. Although piezoelectric actuator is the most universal base of FTS system due to its high stiffness, accuracy and bandwidth, nonlinearity in piezoceramics limits both the static and dynamic performance of piezoelectric-actuated control systems evidently. To compensate the nonlinear hysteresis behavior of piezoelectric actuators, a hybrid model coupled with Preisach model and feedforward neural network (FNN) has been described. Since the training of FNN does not require a special calibration sequence, it is possible for on-line identification and real-time implementation with general operating data of a specific piezoelectric actuator. To describe the rate dependent behavior of piezoelectric actuators, a hybrid dynamic model was developed to predict the response of piezoelectric actuators in a wider range of input frequency. Experimental results show that a maximal error of less than 3% was accomplished by this dynamic model.

Dynamic behavior of ion acoustic waves in electron-positron-ion magnetoplasmas with superthermal electrons and positrons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saha, Asit, E-mail: asit-saha123@rediffmail.com, E-mail: prasantachatterjee1@rediffmail.com; Department of Mathematics, Siksha Bhavana, Visva Bharati University, Santiniketan-731235; Pal, Nikhil

The dynamic behavior of ion acoustic waves in electron-positron-ion magnetoplasmas with superthermal electrons and positrons has been investigated in the framework of perturbed and non-perturbed Kadomtsev-Petviashili (KP) equations. Applying the reductive perturbation technique, we have derived the KP equation in electron-positron-ion magnetoplasma with kappa distributed electrons and positrons. Bifurcations of ion acoustic traveling waves of the KP equation are presented. Using the bifurcation theory of planar dynamical systems, the existence of the solitary wave solutions and the periodic traveling wave solutions has been established. Two exact solutions of these waves have been derived depending on the system parameters. Then, usingmore » the Hirota's direct method, we have obtained two-soliton and three-soliton solutions of the KP equation. The effect of the spectral index κ on propagations of the two-soliton and the three-soliton has been shown. Considering an external periodic perturbation, we have presented the quasi periodic behavior of ion acoustic waves in electron-positron-ion magnetoplasmas.« less

A discrete mechanics framework for real time virtual surgical simulations with application to virtual laparoscopic nephrectomy.

PubMed

Zhou, Xiangmin; Zhang, Nan; Sha, Desong; Shen, Yunhe; Tamma, Kumar K; Sweet, Robert

2009-01-01

The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.

Specialized data analysis for the Space Shuttle Main Engine and diagnostic evaluation of advanced propulsion system components

NASA Technical Reports Server (NTRS)

1993-01-01

The Marshall Space Flight Center is responsible for the development and management of advanced launch vehicle propulsion systems, including the Space Shuttle Main Engine (SSME), which is presently operational, and the Space Transportation Main Engine (STME) under development. The SSME's provide high performance within stringent constraints on size, weight, and reliability. Based on operational experience, continuous design improvement is in progress to enhance system durability and reliability. Specialized data analysis and interpretation is required in support of SSME and advanced propulsion system diagnostic evaluations. Comprehensive evaluation of the dynamic measurements obtained from test and flight operations is necessary to provide timely assessment of the vibrational characteristics indicating the operational status of turbomachinery and other critical engine components. Efficient performance of this effort is critical due to the significant impact of dynamic evaluation results on ground test and launch schedules, and requires direct familiarity with SSME and derivative systems, test data acquisition, and diagnostic software. Detailed analysis and evaluation of dynamic measurements obtained during SSME and advanced system ground test and flight operations was performed including analytical/statistical assessment of component dynamic behavior, and the development and implementation of analytical/statistical models to efficiently define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational condition. In addition, the SSME and J-2 data will be applied to develop vibroacoustic environments for advanced propulsion system components, as required. This study will provide timely assessment of engine component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. This contract will be performed through accomplishment of negotiated task orders.

Modeling workplace bullying using catastrophe theory.

PubMed

Escartin, J; Ceja, L; Navarro, J; Zapf, D

2013-10-01

Workplace bullying is defined as negative behaviors directed at organizational members or their work context that occur regularly and repeatedly over a period of time. Employees' perceptions of psychosocial safety climate, workplace bullying victimization, and workplace bullying perpetration were assessed within a sample of nearly 5,000 workers. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes in workplace bullying. More specifically, the present study examines whether a nonlinear dynamical systems model (i.e., a cusp catastrophe model) is superior to the linear combination of variables for predicting the effect of psychosocial safety climate and workplace bullying victimization on workplace bullying perpetration. According to the AICc, and BIC indices, the linear regression model fits the data better than the cusp catastrophe model. The study concludes that some phenomena, especially unhealthy behaviors at work (like workplace bullying), may be better studied using linear approaches as opposed to nonlinear dynamical systems models. This can be explained through the healthy variability hypothesis, which argues that positive organizational behavior is likely to present nonlinear behavior, while a decrease in such variability may indicate the occurrence of negative behaviors at work.

Behavioral Assembly Required: Particularly for Quantitative Courses

ERIC Educational Resources Information Center

Mazen, Abdelmagid

2008-01-01

This article integrates behavioral approaches into the teaching and learning of quantitative subjects with application to statistics. Focusing on the emotional component of learning, the article presents a system dynamic model that provides descriptive and prescriptive accounts of learners' anxiety. Metaphors and the metaphorizing process are…

Can Multilayer Networks Advance Animal Behavior Research?

PubMed

Silk, Matthew J; Finn, Kelly R; Porter, Mason A; Pinter-Wollman, Noa

2018-06-01

Interactions among individual animals - and between these individuals and their environment - yield complex, multifaceted systems. The development of multilayer network analysis offers a promising new approach for studying animal social behavior and its relation to eco-evolutionary dynamics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of mixing in threshold models of social behavior

NASA Astrophysics Data System (ADS)

Akhmetzhanov, Andrei R.; Worden, Lee; Dushoff, Jonathan

2013-07-01

We consider the dynamics of an extension of the influential Granovetter model of social behavior, where individuals are affected by their personal preferences and observation of the neighbors’ behavior. Individuals are arranged in a network (usually the square lattice), and each has a state and a fixed threshold for behavior changes. We simulate the system asynchronously by picking a random individual and we either update its state or exchange it with another randomly chosen individual (mixing). We describe the dynamics analytically in the fast-mixing limit by using the mean-field approximation and investigate it mainly numerically in the case of finite mixing. We show that the dynamics converge to a manifold in state space, which determines the possible equilibria, and show how to estimate the projection of this manifold by using simulated trajectories, emitted from different initial points. We show that the effects of considering the network can be decomposed into finite-neighborhood effects, and finite-mixing-rate effects, which have qualitatively similar effects. Both of these effects increase the tendency of the system to move from a less-desired equilibrium to the “ground state.” Our findings can be used to probe shifts in behavioral norms and have implications for the role of information flow in determining when social norms that have become unpopular in particular communities (such as foot binding or female genital cutting) persist or vanish.

Drosophila learn efficient paths to a food source.

PubMed

Navawongse, Rapeechai; Choudhury, Deepak; Raczkowska, Marlena; Stewart, James Charles; Lim, Terrence; Rahman, Mashiur; Toh, Alicia Guek Geok; Wang, Zhiping; Claridge-Chang, Adam

2016-05-01

Elucidating the genetic, and neuronal bases for learned behavior is a central problem in neuroscience. A leading system for neurogenetic discovery is the vinegar fly Drosophila melanogaster; fly memory research has identified genes and circuits that mediate aversive and appetitive learning. However, methods to study adaptive food-seeking behavior in this animal have lagged decades behind rodent feeding analysis, largely due to the challenges presented by their small scale. There is currently no method to dynamically control flies' access to food. In rodents, protocols that use dynamic food delivery are a central element of experimental paradigms that date back to the influential work of Skinner. This method is still commonly used in the analysis of learning, memory, addiction, feeding, and many other subjects in experimental psychology. The difficulty of microscale food delivery means this is not a technique used in fly behavior. In the present manuscript we describe a microfluidic chip integrated with machine vision and automation to dynamically control defined liquid food presentations and sensory stimuli. Strikingly, repeated presentations of food at a fixed location produced improvements in path efficiency during food approach. This shows that improved path choice is a learned behavior. Active control of food availability using this microfluidic system is a valuable addition to the methods currently available for the analysis of learned feeding behavior in flies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

On effective temperature in network models of collective behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porfiri, Maurizio, E-mail: mporfiri@nyu.edu; Ariel, Gil, E-mail: arielg@math.biu.ac.il

Collective behavior of self-propelled units is studied analytically within the Vectorial Network Model (VNM), a mean-field approximation of the well-known Vicsek model. We propose a dynamical systems framework to study the stochastic dynamics of the VNM in the presence of general additive noise. We establish that a single parameter, which is a linear function of the circular mean of the noise, controls the macroscopic phase of the system—ordered or disordered. By establishing a fluctuation–dissipation relation, we posit that this parameter can be regarded as an effective temperature of collective behavior. The exact critical temperature is obtained analytically for systems withmore » small connectivity, equivalent to low-density ensembles of self-propelled units. Numerical simulations are conducted to demonstrate the applicability of this new notion of effective temperature to the Vicsek model. The identification of an effective temperature of collective behavior is an important step toward understanding order–disorder phase transitions, informing consistent coarse-graining techniques and explaining the physics underlying the emergence of collective phenomena.« less

Nonlinear dynamic response of a uni-directional model for the tile/pad space shuttle thermal protection system

NASA Technical Reports Server (NTRS)

Housner, J. M.; Edighoffer, H. H.; Park, K. C.

1980-01-01

A unidirectional analysis of the nonlinear dynamic behavior of the space shuttle tile/pad thermal protection system is developed and examined for imposed sinusoidal and random motions of the shuttle skin and/or applied tile pressure. The analysis accounts for the highly nonlinear stiffening hysteresis and viscous behavior of the pad which joins the tile to the shuttle skin. Where available, experimental data are used to confirm the validity of the analysis. Both analytical and experimental studies reveal that the system resonant frequency is very high for low amplitude oscillations but decreases rapidly to a minimum value with increasing amplitude. Analytical studies indicate that with still higher amplitude the resonant frequency increases slowly. The nonlinear pad is also responsible for the analytically and experimentally observed distorted response wave shapes having high sharp peaks when the system is subject to sinusoidal loads. Furthermore, energy dissipation in the pad is studied analytically and it is found that the energy dissipated is sufficiently high to cause rapid decay of dynamic transients. Nevertheless, the sharp peaked nonlinear responses of the system lead to higher magnification factors than would be expected in such a highly damped linear system.

Probabilistic assessment of dynamic system performance. Part 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belhadj, Mohamed

1993-01-01

Accurate prediction of dynamic system failure behavior can be important for the reliability and risk analyses of nuclear power plants, as well as for their backfitting to satisfy given constraints on overall system reliability, or optimization of system performance. Global analysis of dynamic systems through investigating the variations in the structure of the attractors of the system and the domains of attraction of these attractors as a function of the system parameters is also important for nuclear technology in order to understand the fault-tolerance as well as the safety margins of the system under consideration and to insure a safemore » operation of nuclear reactors. Such a global analysis would be particularly relevant to future reactors with inherent or passive safety features that are expected to rely on natural phenomena rather than active components to achieve and maintain safe shutdown. Conventionally, failure and global analysis of dynamic systems necessitate the utilization of different methodologies which have computational limitations on the system size that can be handled. Using a Chapman-Kolmogorov interpretation of system dynamics, a theoretical basis is developed that unifies these methodologies as special cases and which can be used for a comprehensive safety and reliability analysis of dynamic systems.« less

A nonlinear delayed model for the immune response in the presence of viral mutation

NASA Astrophysics Data System (ADS)

Messias, D.; Gleria, Iram; Albuquerque, S. S.; Canabarro, Askery; Stanley, H. E.

2018-02-01

We consider a delayed nonlinear model of the dynamics of the immune system against a viral infection that contains a wild-type virus and a mutant. We consider the finite response time of the immune system and find sustained oscillatory behavior as well as chaotic behavior triggered by the presence of delays. We present a numeric analysis and some analytical results.

UAV Swarm Mission Planning Development Using Evolutionary Algorithms - Part I

DTIC Science & Technology

2008-05-01

desired behaviors in autonomous vehicles is a difficult problem at best and in general prob- ably impossible to completely resolve in complex dynamic...associated behaviors. Various techniques inspired by biological self-organized systems as found in forging insects and flocking birds, revolve around...swarms of heterogeneous vehicles in a distributed simulation system with animated graphics. Statistical measurements and observations indicate that bio

Long-Term Dynamics of Autonomous Fractional Differential Equations

NASA Astrophysics Data System (ADS)

Liu, Tao; Xu, Wei; Xu, Yong; Han, Qun

This paper aims to investigate long-term dynamic behaviors of autonomous fractional differential equations with effective numerical method. The long-term dynamic behaviors predict where systems are heading after long-term evolution. We make some modification and transplant cell mapping methods to autonomous fractional differential equations. The mapping time duration of cell mapping is enlarged to deal with the long memory effect. Three illustrative examples, i.e. fractional Lotka-Volterra equation, fractional van der Pol oscillator and fractional Duffing equation, are studied with our revised generalized cell mapping method. We obtain long-term dynamics, such as attractors, basins of attraction, and saddles. Compared with some existing stability and numerical results, the validity of our method is verified. Furthermore, we find that the fractional order has its effect on the long-term dynamics of autonomous fractional differential equations.

Static and dynamic stability of pneumatic vibration isolators and systems of isolators

NASA Astrophysics Data System (ADS)

Ryaboy, Vyacheslav M.

2014-01-01

Pneumatic vibration isolation is the most widespread effective method for creating vibration-free environments that are vital for precise experiments and manufacturing operations in optoelectronics, life sciences, microelectronics, nanotechnology and other areas. The modeling and design principles of a dual-chamber pneumatic vibration isolator, basically established a few decades ago, continue to attract attention of researchers. On the other hand, behavior of systems of such isolators was never explained in the literature in sufficient detail. This paper covers a range of questions essential for understanding the mechanics of pneumatic isolation systems from both design and application perspectives. The theory and a model of a single standalone isolator are presented in concise form necessary for subsequent analysis. Then the dynamics of a system of isolators supporting a payload is considered with main attention directed to two aspects of their behavior: first, the static stability of payloads with high positions of the center of gravity; second, dynamic stability of the feedback system formed by mechanical leveling valves. The direct method of calculating the maximum stable position of the center of gravity is presented and illustrated by three-dimensional stability domains; analytic formulas are given that delineate these domains. A numerical method for feedback stability analysis of self-leveling valve systems is given, and the results are compared with the analytical estimates for a single isolator. The relation between the static and dynamic phenomena is discussed.

Nonlinear dynamic modeling of a simple flexible rotor system subjected to time-variable base motions

NASA Astrophysics Data System (ADS)

Chen, Liqiang; Wang, Jianjun; Han, Qinkai; Chu, Fulei

2017-09-01

Rotor systems carried in transportation system or under seismic excitations are considered to have a moving base. To study the dynamic behavior of flexible rotor systems subjected to time-variable base motions, a general model is developed based on finite element method and Lagrange's equation. Two groups of Euler angles are defined to describe the rotation of the rotor with respect to the base and that of the base with respect to the ground. It is found that the base rotations would cause nonlinearities in the model. To verify the proposed model, a novel test rig which could simulate the base angular-movement is designed. Dynamic experiments on a flexible rotor-bearing system with base angular motions are carried out. Based upon these, numerical simulations are conducted to further study the dynamic response of the flexible rotor under harmonic angular base motions. The effects of base angular amplitude, rotating speed and base frequency on response behaviors are discussed by means of FFT, waterfall, frequency response curve and orbits of the rotor. The FFT and waterfall plots of the disk horizontal and vertical vibrations are marked with multiplications of the base frequency and sum and difference tones of the rotating frequency and the base frequency. Their amplitudes will increase remarkably when they meet the whirling frequencies of the rotor system.

Holographic control of information and dynamical topology change for composite open quantum systems

NASA Astrophysics Data System (ADS)

Aref'eva, I. Ya.; Volovich, I. V.; Inozemcev, O. V.

2017-12-01

We analyze how the compositeness of a system affects the characteristic time of equilibration. We study the dynamics of open composite quantum systems strongly coupled to the environment after a quantum perturbation accompanied by nonequilibrium heating. We use a holographic description of the evolution of entanglement entropy. The nonsmooth character of the evolution with holographic entanglement is a general feature of composite systems, which demonstrate a dynamical change of topology in the bulk space and a jumplike velocity change of entanglement entropy propagation. Moreover, the number of jumps depends on the system configuration and especially on the number of composite parts. The evolution of the mutual information of two composite systems inherits these jumps. We present a detailed study of the mutual information for two subsystems with one of them being bipartite. We find five qualitatively different types of behavior of the mutual information dynamics and indicate the corresponding regions of the system parameters.

Benford's law and the FSD distribution of economic behavioral micro data

NASA Astrophysics Data System (ADS)

Villas-Boas, Sofia B.; Fu, Qiuzi; Judge, George

2017-11-01

In this paper, we focus on the first significant digit (FSD) distribution of European micro income data and use information theoretic-entropy based methods to investigate the degree to which Benford's FSD law is consistent with the nature of these economic behavioral systems. We demonstrate that Benford's law is not an empirical phenomenon that occurs only in important distributions in physical statistics, but that it also arises in self-organizing dynamic economic behavioral systems. The empirical likelihood member of the minimum divergence-entropy family, is used to recover country based income FSD probability density functions and to demonstrate the implications of using a Benford prior reference distribution in economic behavioral system information recovery.

Sustainable Water Systems for the City of Tomorrow—A Conceptual Framework

EPA Science Inventory

Urban water systems are an example of complex, dynamic human-environment coupled systems, which exhibit emergent behaviors that transcends individual scientific disciplines. While previous siloed approaches to water services (i.e., water resources, drinking water, wastewater, and...

Dynamic model including piping acoustics of a centrifugal compression system

NASA Astrophysics Data System (ADS)

van Helvoirt, Jan; de Jager, Bram

2007-04-01

This paper deals with low-frequency pulsation phenomena in full-scale centrifugal compression systems associated with compressor surge. The Greitzer lumped parameter model is applied to describe the dynamic behavior of an industrial compressor test rig and experimental evidence is provided for the presence of acoustic pulsations in the compression system under study. It is argued that these acoustic phenomena are common for full-scale compression systems where pipe system dynamics have a significant influence on the overall system behavior. The main objective of this paper is to extend the basic compressor model in order to include the relevant pipe system dynamics. For this purpose a pipeline model is proposed, based on previous developments for fluid transmission lines. The connection of this model to the lumped parameter model is accomplished via the selection of appropriate boundary conditions. Validation results will be presented, showing a good agreement between simulation and measurement data. The results indicate that the damping of piping transients depends on the nominal, time-varying pressure and flow velocity. Therefore, model parameters are made dependent on the momentary pressure and a switching nonlinearity is introduced into the model to vary the acoustic damping as a function of flow velocity. These modifications have limited success and the results indicate that a more sophisticated model is required to fully describe all (nonlinear) acoustic effects. However, the very good qualitative results show that the model adequately combines compressor and pipe system dynamics. Therefore, the proposed model forms a step forward in the analysis and modeling of surge in full-scale centrifugal compression systems and opens the path for further developments in this field.

Aspects of jamming in two-dimensional athermal frictionless systems.

PubMed

Reichhardt, C; Reichhardt, C J Olson

2014-05-07

In this work we provide an overview of jamming transitions in two dimensional systems focusing on the limit of frictionless particle interactions in the absence of thermal fluctuations. We first discuss jamming in systems with short range repulsive interactions, where the onset of jamming occurs at a critical packing density and where certain quantities show a divergence indicative of critical behavior. We describe how aspects of the dynamics change as the jamming density is approached and how these dynamics can be explored using externally driven probes. Different particle shapes can produce jamming densities much lower than those observed for disk-shaped particles, and we show how jamming exhibits fragility for some shapes while for other shapes this is absent. Next we describe the effects of long range interactions and jamming behavior in systems such as charged colloids, vortices in type-II superconductors, and dislocations. We consider the effect of adding obstacles to frictionless jamming systems and discuss connections between this type of jamming and systems that exhibit depinning transitions. Finally, we discuss open questions such as whether the jamming transition in all these different systems can be described by the same or a small subset of universal behaviors, as well as future directions for studies of jamming transitions in two dimensional systems, such as jamming in self-driven or active matter systems.

The fractal geometry of Hartree-Fock

NASA Astrophysics Data System (ADS)

Theel, Friethjof; Karamatskou, Antonia; Santra, Robin

2017-12-01

The Hartree-Fock method is an important approximation for the ground-state electronic wave function of atoms and molecules so that its usage is widespread in computational chemistry and physics. The Hartree-Fock method is an iterative procedure in which the electronic wave functions of the occupied orbitals are determined. The set of functions found in one step builds the basis for the next iteration step. In this work, we interpret the Hartree-Fock method as a dynamical system since dynamical systems are iterations where iteration steps represent the time development of the system, as encountered in the theory of fractals. The focus is put on the convergence behavior of the dynamical system as a function of a suitable control parameter. In our case, a complex parameter λ controls the strength of the electron-electron interaction. An investigation of the convergence behavior depending on the parameter λ is performed for helium, neon, and argon. We observe fractal structures in the complex λ-plane, which resemble the well-known Mandelbrot set, determine their fractal dimension, and find that with increasing nuclear charge, the fragmentation increases as well.

Image reconstruction of dynamic infrared single-pixel imaging system

NASA Astrophysics Data System (ADS)

Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

2018-03-01

Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

The Shock and Vibration Bulletin. Part 2. Model Test and Analysis, Testing Techniques, Machinery Dynamics, Isolation and Damping, Structural Dynamics

DTIC Science & Technology

1986-08-01

each subsystem wist include more than a set of rigid body and normal modes to properly represent the dynamics of the entire system. Various types of...MCM 1 AUGMENTATION HETNO-MrifaOII FIELD TflACKER »f Tl BASIC EXPERIMENT Figure 3. Dynamics augmentation experiment. i i mnc...Villeurbanne - France Today the dynamic behavior of rotors must be predicted with the greatest care. This work deals with the influence of disc flexi

Quench dynamics of the interacting Bose gas in one dimension.

PubMed

Iyer, Deepak; Andrei, Natan

2012-09-14

We obtain an exact expression for the time evolution of the interacting Bose gas following a quench from a generic initial state using the Yudson representation for integrable systems. We study the time evolution of the density and noise correlation for a small number of bosons and their asymptotic behavior for any number. We show that for any value of the coupling, as long as it is repulsive, the system asymptotes towards a strongly repulsive gas, while for any value of an attractive coupling the long time behavior is dominated by the maximal bound state. This occurs independently of the initial state and can be viewed as an emerging "dynamic universality."

Using nonlinear methods to quantify changes in infant limb movements and vocalizations.

PubMed

Abney, Drew H; Warlaumont, Anne S; Haussman, Anna; Ross, Jessica M; Wallot, Sebastian

2014-01-01

The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Accordingly, this longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant's vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant's limbs and an audio recorder was worn on the child's chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant's behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior.

Using nonlinear methods to quantify changes in infant limb movements and vocalizations

PubMed Central

Abney, Drew H.; Warlaumont, Anne S.; Haussman, Anna; Ross, Jessica M.; Wallot, Sebastian

2014-01-01

The pairing of dynamical systems theory and complexity science brings novel concepts and methods to the study of infant motor development. Accordingly, this longitudinal case study presents a new approach to characterizing the dynamics of infant limb and vocalization behaviors. A single infant's vocalizations and limb movements were recorded from 51-days to 305-days of age. On each recording day, accelerometers were placed on all four of the infant's limbs and an audio recorder was worn on the child's chest. Using nonlinear time series analysis methods, such as recurrence quantification analysis and Allan factor, we quantified changes in the stability and multiscale properties of the infant's behaviors across age as well as how these dynamics relate across modalities and effectors. We observed that particular changes in these dynamics preceded or coincided with the onset of various developmental milestones. For example, the largest changes in vocalization dynamics preceded the onset of canonical babbling. The results show that nonlinear analyses can help to understand the functional co-development of different aspects of infant behavior. PMID:25161629

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

PubMed

Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

2017-01-01

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Transient behavior of redox flow battery connected to circuit based on global phase structure

NASA Astrophysics Data System (ADS)

Mannari, Toko; Hikihara, Takashi

A Redox Flow Battery (RFB) is one of the promising energy storage systems in power grid. An RFB has many advantages such as a quick response, a large capacity, and a scalability. Due to these advantages, an RFB can operate in mixed time scale. Actually, it has been demonstrated that an RFB can be used for load leveling, compensating sag, and smoothing the output of the renewable sources. An analysis on transient behaviors of an RFB is a key issue for these applications. An RFB is governed by electrical, chemical, and fluid dynamics. The hybrid structure makes the analysis difficult. To analyze transient behaviors of an RFB, the exact model is necessary. In this paper, we focus on a change in a concentration of ions in the electrolyte, and simulate the change with a model which is mainly based on chemical kinetics. The simulation results introduces transient behaviors of an RFB in a response to a load variation. There are found three kinds of typical transient behaviors including oscillations. As results, it is clarified that the complex transient behaviors, due to slow and fast dynamics in the system, arise by the quick response to load.

Steady-state kinetic modeling constrains cellular resting states and dynamic behavior.

PubMed

Purvis, Jeremy E; Radhakrishnan, Ravi; Diamond, Scott L

2009-03-01

A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions. Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components. Here, we show how combining small, well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors. By requiring each kinetic module to be homeostatic (at steady state under resting conditions), the method proceeds by (i) computing steady-state solutions to a system of ordinary differential equations for each module, (ii) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network, and (iii) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation. Importantly, this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model. These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture. To demonstrate application of the method, we show how small kinetic perturbations in a modular model of platelet P2Y(1) signaling can cause widespread compensatory effects on cellular resting states.

Investigations Into Internal and External Aspects of Dynamic Agent-Environment Couplings

NASA Astrophysics Data System (ADS)

Dautenhahn, Kerstin

This paper originates from my work on `social agents'. An issue which I consider important to this kind of research is the dynamic coupling of an agent with its social and non-social environment. I hypothesize `internal dynamics' inside an agent as a basic step towards understanding. The paper therefore focuses on the internal and external dynamics which couple an agent to its environment. The issue of embodiment in animals and artifacts and its relation to `social dynamics' is discussed first. I argue that embodiment is linked to a concept of a body and is not necessarily given when running a control program on robot hardware. I stress the individual characteristics of an embodied cognitive system, as well as its social embeddedness. I outline the framework of a physical-psychological state space which changes dynamically in a self-modifying way as a holistic approach towards embodied human and artificial cognition. This framework is meant to discuss internal and external dynamics of an embodied, natural or artificial agent. In order to stress the importance of a dynamic memory I introduce the concept of an `autobiographical agent'. The second part of the paper gives an example of the implementation of a physical agent, a robot, which is dynamically coupled to its environment by balancing on a seesaw. For the control of the robot a behavior-oriented approach using the dynamical systems metaphor is used. The problem is studied through building a complete and co-adapted robot-environment system. A seesaw which varies its orientation with one or two degrees of freedom is used as the artificial `habitat'. The problem of stabilizing the body axis by active motion on a seesaw is solved by using two inclination sensors and a parallel, behavior-oriented control architecture. Some experiments are described which demonstrate the exploitation of the dynamics of the robot-environment system.

Numerical simulation of magmatic hydrothermal systems

USGS Publications Warehouse

Ingebritsen, S.E.; Geiger, S.; Hurwitz, S.; Driesner, T.

2010-01-01

The dynamic behavior of magmatic hydrothermal systems entails coupled and nonlinear multiphase flow, heat and solute transport, and deformation in highly heterogeneous media. Thus, quantitative analysis of these systems depends mainly on numerical solution of coupled partial differential equations and complementary equations of state (EOS). The past 2 decades have seen steady growth of computational power and the development of numerical models that have eliminated or minimized the need for various simplifying assumptions. Considerable heuristic insight has been gained from process-oriented numerical modeling. Recent modeling efforts employing relatively complete EOS and accurate transport calculations have revealed dynamic behavior that was damped by linearized, less accurate models, including fluid property control of hydrothermal plume temperatures and three-dimensional geometries. Other recent modeling results have further elucidated the controlling role of permeability structure and revealed the potential for significant hydrothermally driven deformation. Key areas for future reSearch include incorporation of accurate EOS for the complete H2O-NaCl-CO2 system, more realistic treatment of material heterogeneity in space and time, realistic description of large-scale relative permeability behavior, and intercode benchmarking comparisons. Copyright 2010 by the American Geophysical Union.

A Novel Type of Chaotic Attractor for Quadratic Systems Without Equilibriums

NASA Astrophysics Data System (ADS)

Dantsev, Danylo

In this paper, a new chaotic dynamic system without equilibriums is presented. A conducted research of the qualitative properties of the discovered system reveals a noncompliance between the bifurcation behavior of the system and the Feigenbaum-Sharkovskii-Magnitsky theory. Additional research of known systems confirms the discrepancy.

Emergence of the self-similar property in gene expression dynamics

NASA Astrophysics Data System (ADS)

Ochiai, T.; Nacher, J. C.; Akutsu, T.

2007-08-01

Many theoretical models have recently been proposed to understand the structure of cellular systems composed of various types of elements (e.g., proteins, metabolites and genes) and their interactions. However, the cell is a highly dynamic system with thousands of functional elements fluctuating across temporal states. Therefore, structural analysis alone is not sufficient to reproduce the cell's observed behavior. In this article, we analyze the gene expression dynamics (i.e., how the amount of mRNA molecules in cell fluctuate in time) by using a new constructive approach, which reveals a symmetry embedded in gene expression fluctuations and characterizes the dynamical equation of gene expression (i.e., a specific stochastic differential equation). First, by using experimental data of human and yeast gene expression time series, we found a symmetry in short-time transition probability from time t to time t+1. We call it self-similarity symmetry (i.e., the gene expression short-time fluctuations contain a repeating pattern of smaller and smaller parts that are like the whole, but different in size). Secondly, we reconstruct the global behavior of the observed distribution of gene expression (i.e., scaling-law) and the local behavior of the power-law tail of this distribution. This approach may represent a step forward toward an integrated image of the basic elements of the whole cell.

Dynamic Task Performance, Cohesion, and Communications in Human Groups.

PubMed

Giraldo, Luis Felipe; Passino, Kevin M

2016-10-01

In the study of the behavior of human groups, it has been observed that there is a strong interaction between the cohesiveness of the group, its performance when the group has to solve a task, and the patterns of communication between the members of the group. Developing mathematical and computational tools for the analysis and design of task-solving groups that are not only cohesive but also perform well is of importance in social sciences, organizational management, and engineering. In this paper, we model a human group as a dynamical system whose behavior is driven by a task optimization process and the interaction between subsystems that represent the members of the group interconnected according to a given communication network. These interactions are described as attractions and repulsions among members. We show that the dynamics characterized by the proposed mathematical model are qualitatively consistent with those observed in real-human groups, where the key aspect is that the attraction patterns in the group and the commitment to solve the task are not static but change over time. Through a theoretical analysis of the system we provide conditions on the parameters that allow the group to have cohesive behaviors, and Monte Carlo simulations are used to study group dynamics for different sets of parameters, communication topologies, and tasks to solve.

Recasting a model atomistic glassformer as a system of icosahedra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinney, Rhiannon; Bristol Centre for Complexity Science, University of Bristol, Bristol BS8 1TS; Liverpool, Tanniemola B.

2015-12-28

We consider a binary Lennard-Jones glassformer whose super-Arrhenius dynamics are correlated with the formation of icosahedral structures. Upon cooling, these icosahedra organize into mesoclusters. We recast this glassformer as an effective system of icosahedra which we describe with a population dynamics model. This model we parameterize with data from the temperature regime accessible to molecular dynamics simulations. We then use the model to determine the population of icosahedra in mesoclusters at arbitrary temperature. Using simulation data to incorporate dynamics into the model, we predict relaxation behavior at temperatures inaccessible to conventional approaches. Our model predicts super-Arrhenius dynamics whose relaxation timemore » remains finite for non-zero temperature.« less

Wetware, Hardware, or Software Incapacitation: Observational Methods to Determine When Autonomy Should Assume Control

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2014-01-01

Control-theoretic modeling of human operator's dynamic behavior in manual control tasks has a long, rich history. There has been significant work on techniques used to identify the pilot model of a given structure. This research attempts to go beyond pilot identification based on experimental data to develop a predictor of pilot behavior. Two methods for pre-dicting pilot stick input during changing aircraft dynamics and deducing changes in pilot behavior are presented This approach may also have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot. With this ability to detect changes in piloting behavior, the possibility now exists to mediate human adverse behaviors, hardware failures, and software anomalies with autono-my that may ameliorate these undesirable effects. However, appropriate timing of when au-tonomy should assume control is dependent on criticality of actions to safety, sensitivity of methods to accurately detect these adverse changes, and effects of changes in levels of auto-mation of the system as a whole.

Floquet-Magnus theory and generic transient dynamics in periodically driven many-body quantum systems

NASA Astrophysics Data System (ADS)

Kuwahara, Tomotaka; Mori, Takashi; Saito, Keiji

2016-04-01

This work explores a fundamental dynamical structure for a wide range of many-body quantum systems under periodic driving. Generically, in the thermodynamic limit, such systems are known to heat up to infinite temperature states in the long-time limit irrespective of dynamical details, which kills all the specific properties of the system. In the present study, instead of considering infinitely long-time scale, we aim to provide a general framework to understand the long but finite time behavior, namely the transient dynamics. In our analysis, we focus on the Floquet-Magnus (FM) expansion that gives a formal expression of the effective Hamiltonian on the system. Although in general the full series expansion is not convergent in the thermodynamics limit, we give a clear relationship between the FM expansion and the transient dynamics. More precisely, we rigorously show that a truncated version of the FM expansion accurately describes the exact dynamics for a certain time-scale. Our theory reveals an experimental time-scale for which non-trivial dynamical phenomena can be reliably observed. We discuss several dynamical phenomena, such as the effect of small integrability breaking, efficient numerical simulation of periodically driven systems, dynamical localization and thermalization. Especially on thermalization, we discuss a generic scenario on the prethermalization phenomenon in periodically driven systems.

Dynamic modelling and response characteristics of a magnetic bearing rotor system including auxiliary bearings

NASA Technical Reports Server (NTRS)

Free, April M.; Flowers, George T.; Trent, Victor S.

1993-01-01

Auxiliary bearings are a critical feature of any magnetic bearing system. They protect the soft iron core of the magnetic bearing during an overload or failure. An auxiliary bearing typically consists of a rolling element bearing or bushing with a clearance gap between the rotor and the inner race of the support. The dynamics of such systems can be quite complex. It is desired to develop a rotor-dynamic model and assess the dynamic behavior of a magnetic bearing rotor system which includes the effects of auxiliary bearings. Of particular interest is the effects of introducing sideloading into such a system during failure of the magnetic bearing. A model is developed from an experimental test facility and a number of simulation studies are performed. These results are presented and discussed.

Application of uniform design to improve dental implant system.

PubMed

Cheng, Yung-Chang; Lin, Deng-Huei; Jiang, Cho-Pei

2015-01-01

This paper introduces the application of uniform experimental design to improve dental implant systems subjected to dynamic loads. The dynamic micromotion of the Zimmer dental implant system is calculated and illustrated by explicit dynamic finite element analysis. Endogenous and exogenous factors influence the success rate of dental implant systems. Endogenous factors include: bone density, cortical bone thickness and osseointegration. Exogenous factors include: thread pitch, thread depth, diameter of implant neck and body size. A dental implant system with a crest module was selected to simulate micromotion distribution and stress behavior under dynamic loads using conventional and proposed methods. Finally, the design which caused minimum micromotion was chosen as the optimal design model. The micromotion of the improved model is 36.42 μm, with an improvement is 15.34% as compared to the original model.

Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

PubMed

Li, Jianwei; Nowak, Piotr; Otto, Sijbren

2013-06-26

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

Understanding and Modeling Teams As Dynamical Systems

PubMed Central

Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

2017-01-01

By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

Emotional First Aid: Crisis Development and Systems of Intervention.

ERIC Educational Resources Information Center

Rosenbluh, Edward S.; And Others

This instructional manual takes a developmental approach toward understanding the psychological, social and behavioral dynamics of human crisis. The manual describes the behavior patterns characterizing various psychological and physical crises, and provides background information and methods of crisis intervention with which to manage each. In…

Crack stability in a representative piping system under combined inertial and seismic/dynamic displacement-controlled stresses. Subtask 1.3 final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, P.; Olson, R.; Wilkowski, O.G.

1997-06-01

This report presents the results from Subtask 1.3 of the International Piping Integrity Research Group (IPIRG) program. The objective of Subtask 1.3 is to develop data to assess analysis methodologies for characterizing the fracture behavior of circumferentially cracked pipe in a representative piping system under combined inertial and displacement-controlled stresses. A unique experimental facility was designed and constructed. The piping system evaluated is an expansion loop with over 30 meters of 16-inch diameter Schedule 100 pipe. The experimental facility is equipped with special hardware to ensure system boundary conditions could be appropriately modeled. The test matrix involved one uncracked andmore » five cracked dynamic pipe-system experiments. The uncracked experiment was conducted to evaluate piping system damping and natural frequency characteristics. The cracked-pipe experiments evaluated the fracture behavior, pipe system response, and stability characteristics of five different materials. All cracked-pipe experiments were conducted at PWR conditions. Material characterization efforts provided tensile and fracture toughness properties of the different pipe materials at various strain rates and temperatures. Results from all pipe-system experiments and material characterization efforts are presented. Results of fracture mechanics analyses, dynamic finite element stress analyses, and stability analyses are presented and compared with experimental results.« less

Substrate clamping effects on irreversible domain wall dynamics in lead zirconate titanate thin films.

PubMed

Griggio, F; Jesse, S; Kumar, A; Ovchinnikov, O; Kim, H; Jackson, T N; Damjanovic, D; Kalinin, S V; Trolier-McKinstry, S

2012-04-13

The role of long-range strain interactions on domain wall dynamics is explored through macroscopic and local measurements of nonlinear behavior in mechanically clamped and released polycrystalline lead zirconate-titanate (PZT) films. Released films show a dramatic change in the global dielectric nonlinearity and its frequency dependence as a function of mechanical clamping. Furthermore, we observe a transition from strong clustering of the nonlinear response for the clamped case to almost uniform nonlinearity for the released film. This behavior is ascribed to increased mobility of domain walls. These results suggest the dominant role of collective strain interactions mediated by the local and global mechanical boundary conditions on the domain wall dynamics. The work presented in this Letter demonstrates that measurements on clamped films may considerably underestimate the piezoelectric coefficients and coupling constants of released structures used in microelectromechanical systems, energy harvesting systems, and microrobots.

From electromyographic activity to frequency modulation in zebra finch song.

PubMed

Döppler, Juan F; Bush, Alan; Goller, Franz; Mindlin, Gabriel B

2018-02-01

Behavior emerges from the interaction between the nervous system and peripheral devices. In the case of birdsong production, a delicate and fast control of several muscles is required to control the configuration of the syrinx (the avian vocal organ) and the respiratory system. In particular, the syringealis ventralis muscle is involved in the control of the tension of the vibrating labia and thus affects the frequency modulation of the sound. Nevertheless, the translation of the instructions (which are electrical in nature) into acoustical features is complex and involves nonlinear, dynamical processes. In this work, we present a model of the dynamics of the syringealis ventralis muscle and the labia, which allows calculating the frequency of the generated sound, using as input the electrical activity recorded in the muscle. In addition, the model provides a framework to interpret inter-syllabic activity and hints at the importance of the biomechanical dynamics in determining behavior.

Priority in Process Algebras

NASA Technical Reports Server (NTRS)

Cleaveland, Rance; Luettgen, Gerald; Natarajan, V.

1999-01-01

This paper surveys the semantic ramifications of extending traditional process algebras with notions of priority that allow for some transitions to be given precedence over others. These enriched formalisms allow one to model system features such as interrupts, prioritized choice, or real-time behavior. Approaches to priority in process algebras can be classified according to whether the induced notion of preemption on transitions is global or local and whether priorities are static or dynamic. Early work in the area concentrated on global pre-emption and static priorities and led to formalisms for modeling interrupts and aspects of real-time, such as maximal progress, in centralized computing environments. More recent research has investigated localized notions of pre-emption in which the distribution of systems is taken into account, as well as dynamic priority approaches, i.e., those where priority values may change as systems evolve. The latter allows one to model behavioral phenomena such as scheduling algorithms and also enables the efficient encoding of real-time semantics. Technically, this paper studies the different models of priorities by presenting extensions of Milner's Calculus of Communicating Systems (CCS) with static and dynamic priority as well as with notions of global and local pre- emption. In each case the operational semantics of CCS is modified appropriately, behavioral theories based on strong and weak bisimulation are given, and related approaches for different process-algebraic settings are discussed.

Dynamics of early planetary gear trains

NASA Technical Reports Server (NTRS)

August, R.; Kasuba, R.; Frater, J. L.; Pintz, A.

1984-01-01

A method to analyze the static and dynamic loads in a planetary gear train was developed. A variable-variable mesh stiffness (VVMS) model was used to simulate the external and internal spur gear mesh behavior, and an equivalent conventional gear train concept was adapted for the dynamic studies. The analysis can be applied either involute or noninvolute spur gearing. By utilizing the equivalent gear train concept, the developed method may be extended for use for all types of epicyclic gearing. The method is incorporated into a computer program so that the static and dynamic behavior of individual components can be examined. Items considered in the analysis are: (1) static and dynamic load sharing among the planets; (2) floating or fixed Sun gear; (3) actual tooth geometry, including errors and modifications; (4) positioning errors of the planet gears; (5) torque variations due to noninvolute gear action. A mathematical model comprised of power source, load, and planetary transmission is used to determine the instantaneous loads to which the components are subjected. It considers fluctuating output torque, elastic behavior in the system, and loss of contact between gear teeth. The dynamic model has nine degrees of freedom resulting in a set of simultaneous second order differential equations with time varying coefficients, which are solved numerically. The computer program was used to determine the effect of manufacturing errors, damping and component stiffness, and transmitted load on dynamic behavior. It is indicated that this methodology offers the designer/analyst a comprehensive tool with which planetary drives may be quickly and effectively evaluated.

Nonlinear identification of the total baroreflex arc.

PubMed

Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru; Mukkamala, Ramakrishna

2015-12-15

The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This "Uryson" model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure. Copyright © 2015 the American Physiological Society.

Nonlinear identification of the total baroreflex arc

PubMed Central

Moslehpour, Mohsen; Kawada, Toru; Sunagawa, Kenji; Sugimachi, Masaru

2015-01-01

The total baroreflex arc [the open-loop system relating carotid sinus pressure (CSP) to arterial pressure (AP)] is known to exhibit nonlinear behaviors. However, few studies have quantitatively characterized its nonlinear dynamics. The aim of this study was to develop a nonlinear model of the sympathetically mediated total arc without assuming any model form. Normal rats were studied under anesthesia. The vagal and aortic depressor nerves were sectioned, the carotid sinus regions were isolated and attached to a servo-controlled piston pump, and the AP and sympathetic nerve activity (SNA) were measured. CSP was perturbed using a Gaussian white noise signal. A second-order Volterra model was developed by applying nonparametric identification to the measurements. The second-order kernel was mainly diagonal, but the diagonal differed in shape from the first-order kernel. Hence, a reduced second-order model was similarly developed comprising a linear dynamic system in parallel with a squaring system in cascade with a slower linear dynamic system. This “Uryson” model predicted AP changes 12% better (P < 0.01) than a linear model in response to new Gaussian white noise CSP. The model also predicted nonlinear behaviors, including thresholding and mean responses to CSP changes about the mean. Models of the neural arc (the system relating CSP to SNA) and peripheral arc (the system relating SNA to AP) were likewise developed and tested. However, these models of subsystems of the total arc showed approximately linear behaviors. In conclusion, the validated nonlinear model of the total arc revealed that the system takes on an Uryson structure. PMID:26354845

Generation of 2N + 1-scroll existence in new three-dimensional chaos systems.

PubMed

Liu, Yue; Guan, Jian; Ma, Chunyang; Guo, Shuxu

2016-08-01

We propose a systematic methodology for creating 2N + 1-scroll chaotic attractors from a simple three-dimensional system, which is named as the translation chaotic system. It satisfies the condition a12a21 = 0, while the Chua system satisfies a12a21 > 0. In this paper, we also propose a successful (an effective) design and an analytical approach for constructing 2N + 1-scrolls, the translation transformation principle. Also, the dynamics properties of the system are studied in detail. MATLAB simulation results show very sophisticated dynamical behaviors and unique chaotic behaviors of the system. It provides a new approach for 2N + 1-scroll attractors. Finally, to explore the potential use in technological applications, a novel block circuit diagram is also designed for the hardware implementation of 1-, 3-, 5-, and 7-scroll attractors via switching the switches. Translation chaotic system has the merit of convenience and high sensitivity to initial values, emerging potentials in future engineering chaos design.

Modelling chaotic vibrations using NASTRAN

NASA Technical Reports Server (NTRS)

Sheerer, T. J.

1993-01-01

Due to the unavailability and, later, prohibitive cost of the computational power required, many phenomena in nonlinear dynamic systems have in the past been addressed in terms of linear systems. Linear systems respond to periodic inputs with periodic outputs, and may be characterized in the time domain or in the frequency domain as convenient. Reduction to the frequency domain is frequently desireable to reduce the amount of computation required for solution. Nonlinear systems are only soluble in the time domain, and may exhibit a time history which is extremely sensitive to initial conditions. Such systems are termed chaotic. Dynamic buckling, aeroelasticity, fatigue analysis, control systems and electromechanical actuators are among the areas where chaotic vibrations have been observed. Direct transient analysis over a long time period presents a ready means of simulating the behavior of self-excited or externally excited nonlinear systems for a range of experimental parameters, either to characterize chaotic behavior for development of load spectra, or to define its envelope and preclude its occurrence.

Investigation of Seasonal and Latitudinal Effects on the Expression of Clock Genes in Drosophila

NASA Astrophysics Data System (ADS)

Hosseini, Seyede Sanaz; Nazarimehr, Fahimeh; Jafari, Sajad

The primary goal in this work is to develop a dynamical model capturing the influence of seasonal and latitudinal variations on the expression of Drosophila clock genes. To this end, we study a specific dynamical system with strange attractors that exhibit changes of Drosophila activity in a range of latitudes and across different seasons. Bifurcations of this system are analyzed to peruse the effect of season and latitude on the behavior of clock genes. Existing experimental data collected from the activity of Drosophila melanogaster corroborate the dynamical model.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

A Symbolic and Graphical Computer Representation of Dynamical Systems

NASA Astrophysics Data System (ADS)

Gould, Laurence I.

2005-04-01

AUTONO is a Macsyma/Maxima program, designed at the University of Hartford, for solving autonomous systems of differential equations as well as for relating Lagrangians and Hamiltonians to their associated dynamical equations. AUTONO can be used in a number of fields to decipher a variety of complex dynamical systems with ease, producing their Lagrangian and Hamiltonian equations in seconds. These equations can then be incorporated into VisSim, a modeling and simulation program, which yields graphical representations of motion in a given system through easily chosen input parameters. The program, along with the VisSim differential-equations graphical package, allows for resolution and easy understanding of complex problems in a relatively short time; thus enabling quicker and more advanced computing of dynamical systems on any number of platforms---from a network of sensors on a space probe, to the behavior of neural networks, to the effects of an electromagnetic field on components in a dynamical system. A flowchart of AUTONO, along with some simple applications and VisSim output, will be shown.

A dual systems account of visual perception: Predicting candy consumption from distance estimates.

PubMed

Krpan, Dario; Schnall, Simone

2017-04-01

A substantial amount of evidence shows that visual perception is influenced by forces that control human actions, ranging from motivation to physiological potential. However, studies have not yet provided convincing evidence that perception itself is directly involved in everyday behaviors such as eating. We suggest that this issue can be resolved by employing the dual systems account of human behavior. We tested the link between perceived distance to candies and their consumption for participants who were tired or depleted (impulsive system), versus those who were not (reflective system). Perception predicted eating only when participants were tired (Experiment 1) or depleted (Experiments 2 and 3). In contrast, a rational determinant of behavior-eating restraint towards candies-predicted eating for non-depleted individuals (Experiment 2). Finally, Experiment 3 established that perceived distance was correlated with participants' self-reported motivation to consume candies. Overall, these findings suggest that the dynamics between perception and behavior depend on the interplay of the two behavioral systems. Copyright © 2017 Elsevier B.V. All rights reserved.