Science.gov

Sample records for complex langevin dynamics

  1. Localised distributions and criteria for correctness in complex Langevin dynamics

    SciTech Connect

    Aarts, Gert; Giudice, Pietro; Seiler, Erhard

    2013-10-15

    Complex Langevin dynamics can solve the sign problem appearing in numerical simulations of theories with a complex action. In order to justify the procedure, it is important to understand the properties of the real and positive distribution, which is effectively sampled during the stochastic process. In the context of a simple model, we study this distribution by solving the Fokker–Planck equation as well as by brute force and relate the results to the recently derived criteria for correctness. We demonstrate analytically that it is possible that the distribution has support in a strip in the complexified configuration space only, in which case correct results are expected. -- Highlights: •Characterisation of the equilibrium distribution sampled in complex Langevin dynamics. •Connection between criteria for correctness and breakdown. •Solution of the Fokker–Planck equation in the case of real noise. •Analytical determination of support in complexified space.

  2. Self-guided Langevin dynamics via generalized Langevin equation.

    PubMed

    Wu, Xiongwu; Brooks, Bernard R; Vanden-Eijnden, Eric

    2016-03-01

    Self-guided Langevin dynamics (SGLD) is a molecular simulation method that enhances conformational search and sampling via acceleration of the low frequency motions of the system. This acceleration is produced via introduction of a guiding force which breaks down the detailed-balance property of the dynamics, implying that some reweighting is necessary to perform equilibrium sampling. Here, we eliminate the need of reweighing and show that the NVT and NPT ensembles are sampled exactly by a new version of self-guided motion involving a generalized Langevin equation (GLE) in which the random force is modified so as to restore detailed-balance. Through the examples of alanine dipeptide and argon liquid, we show that this SGLD-GLE method has enhanced conformational sampling capabilities compared with regular Langevin dynamics (LD) while being of comparable computational complexity. In particular, SGLD-GLE is fully size extensive and can be used in arbitrarily large systems, making it an appealing alternative to LD. © 2015 Wiley Periodicals, Inc. PMID:26183423

  3. The complex chemical Langevin equation

    SciTech Connect

    Schnoerr, David; Sanguinetti, Guido; Grima, Ramon

    2014-07-14

    The chemical Langevin equation (CLE) is a popular simulation method to probe the stochastic dynamics of chemical systems. The CLE’s main disadvantage is its break down in finite time due to the problem of evaluating square roots of negative quantities whenever the molecule numbers become sufficiently small. We show that this issue is not a numerical integration problem, rather in many systems it is intrinsic to all representations of the CLE. Various methods of correcting the CLE have been proposed which avoid its break down. We show that these methods introduce undesirable artefacts in the CLE’s predictions. In particular, for unimolecular systems, these correction methods lead to CLE predictions for the mean concentrations and variance of fluctuations which disagree with those of the chemical master equation. We show that, by extending the domain of the CLE to complex space, break down is eliminated, and the CLE’s accuracy for unimolecular systems is restored. Although the molecule numbers are generally complex, we show that the “complex CLE” predicts real-valued quantities for the mean concentrations, the moments of intrinsic noise, power spectra, and first passage times, hence admitting a physical interpretation. It is also shown to provide a more accurate approximation of the chemical master equation of simple biochemical circuits involving bimolecular reactions than the various corrected forms of the real-valued CLE, the linear-noise approximation and a commonly used two moment-closure approximation.

  4. Multidimensional Langevin Modeling of Nonoverdamped Dynamics

    NASA Astrophysics Data System (ADS)

    Schaudinnus, Norbert; Bastian, Björn; Hegger, Rainer; Stock, Gerhard

    2015-07-01

    Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.

  5. Langevin Equation for DNA Dynamics

    NASA Astrophysics Data System (ADS)

    Grych, David; Copperman, Jeremy; Guenza, Marina

    Under physiological conditions, DNA oligomers can contain well-ordered helical regions and also flexible single-stranded regions. We describe the site-specific motion of DNA with a modified Rouse-Zimm Langevin equation formalism that describes DNA as a coarse-grained polymeric chain with global structure and local flexibility. The approach has successfully described the protein dynamics in solution and has been extended to nucleic acids. Our approach provides diffusive mode analytical solutions for the dynamics of global rotational diffusion and internal motion. The internal DNA dynamics present a rich energy landscape that accounts for an interior where hydrogen bonds and base-stacking determine structure and experience limited solvent exposure. We have implemented several models incorporating different coarse-grained sites with anisotropic rotation, energy barrier crossing, and local friction coefficients that include a unique internal viscosity and our models reproduce dynamics predicted by atomistic simulations. The models reproduce bond autocorrelation along the sequence as compared to that directly calculated from atomistic molecular dynamics simulations. The Langevin equation approach captures the essence of DNA dynamics without a cumbersome atomistic representation.

  6. Langevin stabilization of molecular dynamics

    NASA Astrophysics Data System (ADS)

    Izaguirre, Jesús A.; Catarello, Daniel P.; Wozniak, Justin M.; Skeel, Robert D.

    2001-02-01

    In this paper we show the possibility of using very mild stochastic damping to stabilize long time step integrators for Newtonian molecular dynamics. More specifically, stable and accurate integrations are obtained for damping coefficients that are only a few percent of the natural decay rate of processes of interest, such as the velocity autocorrelation function. Two new multiple time stepping integrators, Langevin Molly (LM) and Brünger-Brooks-Karplus-Molly (BBK-M), are introduced in this paper. Both use the mollified impulse method for the Newtonian term. LM uses a discretization of the Langevin equation that is exact for the constant force, and BBK-M uses the popular Brünger-Brooks-Karplus integrator (BBK). These integrators, along with an extrapolative method called LN, are evaluated across a wide range of damping coefficient values. When large damping coefficients are used, as one would for the implicit modeling of solvent molecules, the method LN is superior, with LM closely following. However, with mild damping of 0.2 ps-1, LM produces the best results, allowing long time steps of 14 fs in simulations containing explicitly modeled flexible water. With BBK-M and the same damping coefficient, time steps of 12 fs are possible for the same system. Similar results are obtained for a solvated protein-DNA simulation of estrogen receptor ER with estrogen response element ERE. A parallel version of BBK-M runs nearly three times faster than the Verlet-I/r-RESPA (reversible reference system propagator algorithm) when using the largest stable time step on each one, and it also parallelizes well. The computation of diffusion coefficients for flexible water and ER/ERE shows that when mild damping of up to 0.2 ps-1 is used the dynamics are not significantly distorted.

  7. Error Analysis of Modified Langevin Dynamics

    NASA Astrophysics Data System (ADS)

    Redon, Stephane; Stoltz, Gabriel; Trstanova, Zofia

    2016-06-01

    We consider Langevin dynamics associated with a modified kinetic energy vanishing for small momenta. This allows us to freeze slow particles, and hence avoid the re-computation of inter-particle forces, which leads to computational gains. On the other hand, the statistical error may increase since there are a priori more correlations in time. The aim of this work is first to prove the ergodicity of the modified Langevin dynamics (which fails to be hypoelliptic), and next to analyze how the asymptotic variance on ergodic averages depends on the parameters of the modified kinetic energy. Numerical results illustrate the approach, both for low-dimensional systems where we resort to a Galerkin approximation of the generator, and for more realistic systems using Monte Carlo simulations.

  8. Error Analysis of Modified Langevin Dynamics

    NASA Astrophysics Data System (ADS)

    Redon, Stephane; Stoltz, Gabriel; Trstanova, Zofia

    2016-08-01

    We consider Langevin dynamics associated with a modified kinetic energy vanishing for small momenta. This allows us to freeze slow particles, and hence avoid the re-computation of inter-particle forces, which leads to computational gains. On the other hand, the statistical error may increase since there are a priori more correlations in time. The aim of this work is first to prove the ergodicity of the modified Langevin dynamics (which fails to be hypoelliptic), and next to analyze how the asymptotic variance on ergodic averages depends on the parameters of the modified kinetic energy. Numerical results illustrate the approach, both for low-dimensional systems where we resort to a Galerkin approximation of the generator, and for more realistic systems using Monte Carlo simulations.

  9. Langevin dynamics, entropic crowding, and stochastic cloaking.

    PubMed

    Eliazar, Iddo

    2011-12-01

    We consider a pack of independent probes--within a spatially inhomogeneous thermal bath consisting of a vast number of randomly moving particles--which are subjected to an external force. The stochastic dynamics of the probes are governed by Langevin's equation. The probes attain a steady state distribution which, in general, is different than the concentration of the particles in the spatially inhomogeneous thermal bath. In this paper we explore the state of "entropic crowding" in which the probes' distribution and the particles' concentration coincide--thus yielding maximal relative entropies of one with respect to the other. Entropic crowding can be attained by two scenarios which are analyzed in detail: (i) "entropically crowding thermal baths"--in which the particles crowd uniformly around the probes; (ii) "entropically crowding Langevin forces"--in which the probes crowd uniformly amongst the particles. Entropic crowding is equivalent to the optimal stochastic cloaking of the probes within the spatially inhomogeneous thermal bath. PMID:22304065

  10. Langevin dynamics neglecting detailed balance condition.

    PubMed

    Ohzeki, Masayuki; Ichiki, Akihisa

    2015-07-01

    An improved method for driving a system into a desired distribution, for example, the Gibbs-Boltzmann distribution, is proposed, which makes use of an artificial relaxation process. The standard techniques for achieving the Gibbs-Boltzmann distribution involve numerical simulations under the detailed balance condition. In contrast, in the present study we formulate the Langevin dynamics, for which the corresponding Fokker-Planck operator includes an asymmetric component violating the detailed balance condition. This leads to shifts in the eigenvalues and results in the acceleration of the relaxation toward the steady state. The numerical implementation demonstrates faster convergence and shorter correlation time, and the technique of biased event sampling, Nemoto-Sasa theory, further highlights the efficacy of our method. PMID:26274123

  11. New Langevin and gradient thermostats for rigid body dynamics

    NASA Astrophysics Data System (ADS)

    Davidchack, R. L.; Ouldridge, T. E.; Tretyakov, M. V.

    2015-04-01

    We introduce two new thermostats, one of Langevin type and one of gradient (Brownian) type, for rigid body dynamics. We formulate rotation using the quaternion representation of angular coordinates; both thermostats preserve the unit length of quaternions. The Langevin thermostat also ensures that the conjugate angular momenta stay within the tangent space of the quaternion coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have constructed three geometric numerical integrators for the Langevin thermostat and one for the gradient thermostat. The numerical integrators reflect key properties of the thermostats themselves. Namely, they all preserve the unit length of quaternions, automatically, without the need of a projection onto the unit sphere. The Langevin integrators also ensure that the angular momenta remain within the tangent space of the quaternion coordinates. The Langevin integrators are quasi-symplectic and of weak order two. The numerical method for the gradient thermostat is of weak order one. Its construction exploits ideas of Lie-group type integrators for differential equations on manifolds. We numerically compare the discretization errors of the Langevin integrators, as well as the efficiency of the gradient integrator compared to the Langevin ones when used in the simulation of rigid TIP4P water model with smoothly truncated electrostatic interactions. We observe that the gradient integrator is computationally less efficient than the Langevin integrators. We also compare the relative accuracy of the Langevin integrators in evaluating various static quantities and give recommendations as to the choice of an appropriate integrator.

  12. New Langevin and gradient thermostats for rigid body dynamics.

    PubMed

    Davidchack, R L; Ouldridge, T E; Tretyakov, M V

    2015-04-14

    We introduce two new thermostats, one of Langevin type and one of gradient (Brownian) type, for rigid body dynamics. We formulate rotation using the quaternion representation of angular coordinates; both thermostats preserve the unit length of quaternions. The Langevin thermostat also ensures that the conjugate angular momenta stay within the tangent space of the quaternion coordinates, as required by the Hamiltonian dynamics of rigid bodies. We have constructed three geometric numerical integrators for the Langevin thermostat and one for the gradient thermostat. The numerical integrators reflect key properties of the thermostats themselves. Namely, they all preserve the unit length of quaternions, automatically, without the need of a projection onto the unit sphere. The Langevin integrators also ensure that the angular momenta remain within the tangent space of the quaternion coordinates. The Langevin integrators are quasi-symplectic and of weak order two. The numerical method for the gradient thermostat is of weak order one. Its construction exploits ideas of Lie-group type integrators for differential equations on manifolds. We numerically compare the discretization errors of the Langevin integrators, as well as the efficiency of the gradient integrator compared to the Langevin ones when used in the simulation of rigid TIP4P water model with smoothly truncated electrostatic interactions. We observe that the gradient integrator is computationally less efficient than the Langevin integrators. We also compare the relative accuracy of the Langevin integrators in evaluating various static quantities and give recommendations as to the choice of an appropriate integrator. PMID:25877569

  13. Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations

    SciTech Connect

    Gottwald, Fabian; Karsten, Sven; Ivanov, Sergei D. Kühn, Oliver

    2015-06-28

    Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into a few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation, which can be rigorously derived by means of a linear projection technique. Within this framework, a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here, we discuss that this task is more naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importantly, we show that the rigid bond approach leads to a systematic overestimation of relaxation times, unless the system under study consists of a harmonic bath bi-linearly coupled to the relevant degrees of freedom.

  14. Langevin Dynamics Deciphers the Motility Pattern of Swimming Parasites

    NASA Astrophysics Data System (ADS)

    Zaburdaev, Vasily; Uppaluri, Sravanti; Pfohl, Thomas; Engstler, Markus; Friedrich, Rudolf; Stark, Holger

    2011-05-01

    The parasite African trypanosome swims in the bloodstream of mammals and causes the highly dangerous human sleeping sickness. Cell motility is essential for the parasite’s survival within the mammalian host. We present an analysis of the random-walk pattern of a swimming trypanosome. From experimental time-autocorrelation functions for the direction of motion we identify two relaxation times that differ by an order of magnitude. They originate from the rapid deformations of the cell body and a slower rotational diffusion of the average swimming direction. Velocity fluctuations are athermal and increase for faster cells whose trajectories are also straighter. We demonstrate that such a complex dynamics is captured by two decoupled Langevin equations that decipher the complex trajectory pattern by referring it to the microscopic details of cell behavior.

  15. Complex Langevin method: When can it be trusted?

    SciTech Connect

    Aarts, Gert; Seiler, Erhard; Stamatescu, Ion-Olimpiu

    2010-03-01

    We analyze to what extent the complex Langevin method, which is in principle capable of solving the so-called sign problems, can be considered as reliable. We give a formal derivation of the correctness and then point out various mathematical loopholes. The detailed study of some simple examples leads to practical suggestions about the application of the method.

  16. Driven Langevin systems: fluctuation theorems and faithful dynamics

    NASA Astrophysics Data System (ADS)

    Sivak, David; Chodera, John; Crooks, Gavin

    2014-03-01

    Stochastic differential equations of motion (e.g., Langevin dynamics) provide a popular framework for simulating molecular systems. Any computational algorithm must discretize these equations, yet the resulting finite time step integration schemes suffer from several practical shortcomings. We show how any finite time step Langevin integrator can be thought of as a driven, nonequilibrium physical process. Amended by an appropriate work-like quantity (the shadow work), nonequilibrium fluctuation theorems can characterize or correct for the errors introduced by the use of finite time steps. We also quantify, for the first time, the magnitude of deviations between the sampled stationary distribution and the desired equilibrium distribution for equilibrium Langevin simulations of solvated systems of varying size. We further show that the incorporation of a novel time step rescaling in the deterministic updates of position and velocity can correct a number of dynamical defects in these integrators. Finally, we identify a particular splitting that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts.

  17. Protein displacements under external forces: An atomistic Langevin dynamics approach

    NASA Astrophysics Data System (ADS)

    Gnandt, David; Utz, Nadine; Blumen, Alexander; Koslowski, Thorsten

    2009-02-01

    We present a fully atomistic Langevin dynamics approach as a method to simulate biopolymers under external forces. In the harmonic regime, this approach permits the computation of the long-term dynamics using only the eigenvalues and eigenvectors of the Hessian matrix of second derivatives. We apply this scheme to identify polymorphs of model proteins by their mechanical response fingerprint, and we relate the averaged dynamics of proteins to their biological functionality, with the ion channel gramicidin A, a phosphorylase, and neuropeptide Y as examples. In an environment akin to dilute solutions, even small proteins show relaxation times up to 50 ns. Atomically resolved Langevin dynamics computations have been performed for the stretched gramicidin A ion channel.

  18. Accurate Langevin approaches to simulate Markovian channel dynamics

    NASA Astrophysics Data System (ADS)

    Huang, Yandong; Rüdiger, Sten; Shuai, Jianwei

    2015-12-01

    The stochasticity of ion-channels dynamic is significant for physiological processes on neuronal cell membranes. Microscopic simulations of the ion-channel gating with Markov chains can be considered to be an accurate standard. However, such Markovian simulations are computationally demanding for membrane areas of physiologically relevant sizes, which makes the noise-approximating or Langevin equation methods advantageous in many cases. In this review, we discuss the Langevin-like approaches, including the channel-based and simplified subunit-based stochastic differential equations proposed by Fox and Lu, and the effective Langevin approaches in which colored noise is added to deterministic differential equations. In the framework of Fox and Lu’s classical models, several variants of numerical algorithms, which have been recently developed to improve accuracy as well as efficiency, are also discussed. Through the comparison of different simulation algorithms of ion-channel noise with the standard Markovian simulation, we aim to reveal the extent to which the existing Langevin-like methods approximate results using Markovian methods. Open questions for future studies are also discussed.

  19. Langevin Dynamics with Space-Time Periodic Nonequilibrium Forcing

    NASA Astrophysics Data System (ADS)

    Joubaud, R.; Pavliotis, G. A.; Stoltz, G.

    2015-01-01

    We present results on the ballistic and diffusive behavior of the Langevin dynamics in a periodic potential that is driven away from equilibrium by a space-time periodic driving force, extending some of the results obtained by Collet and Martinez in (J Math Biol, 56(6):765-792 2008). In the hyperbolic scaling, a nontrivial average velocity can be observed even if the external forcing vanishes in average. More surprisingly, an average velocity in the direction opposite to the forcing may develop at the linear response level—a phenomenon called negative mobility. The diffusive limit of the non-equilibrium Langevin dynamics is also studied using the general methodology of central limit theorems for additive functionals of Markov processes. To apply this methodology, which is based on the study of appropriate Poisson equations, we extend recent results on pointwise estimates of the resolvent of the generator associated with the Langevin dynamics. Our theoretical results are illustrated by numerical simulations of a two-dimensional system.

  20. Inertial stochastic dynamics. I. Long-time-step methods for Langevin dynamics

    NASA Astrophysics Data System (ADS)

    Beard, Daniel A.; Schlick, Tamar

    2000-05-01

    Two algorithms are presented for integrating the Langevin dynamics equation with long numerical time steps while treating the mass terms as finite. The development of these methods is motivated by the need for accurate methods for simulating slow processes in polymer systems such as two-site intermolecular distances in supercoiled DNA, which evolve over the time scale of milliseconds. Our new approaches refine the common Brownian dynamics (BD) scheme, which approximates the Langevin equation in the highly damped diffusive limit. Our LTID ("long-time-step inertial dynamics") method is based on an eigenmode decomposition of the friction tensor. The less costly integrator IBD ("inertial Brownian dynamics") modifies the usual BD algorithm by the addition of a mass-dependent correction term. To validate the methods, we evaluate the accuracy of LTID and IBD and compare their behavior to that of BD for the simple example of a harmonic oscillator. We find that the LTID method produces the expected correlation structure for Langevin dynamics regardless of the level of damping. In fact, LTID is the only consistent method among the three, with error vanishing as the time step approaches zero. In contrast, BD is accurate only for highly overdamped systems. For cases of moderate overdamping, and for the appropriate choice of time step, IBD is significantly more accurate than BD. IBD is also less computationally expensive than LTID (though both are the same order of complexity as BD), and thus can be applied to simulate systems of size and time scale ranges previously accessible to only the usual BD approach. Such simulations are discussed in our companion paper, for long DNA molecules modeled as wormlike chains.

  1. Bifurcation dynamics of the tempered fractional Langevin equation.

    PubMed

    Zeng, Caibin; Yang, Qigui; Chen, YangQuan

    2016-08-01

    Tempered fractional processes offer a useful extension for turbulence to include low frequencies. In this paper, we investigate the stochastic phenomenological bifurcation, or stochastic P-bifurcation, of the Langevin equation perturbed by tempered fractional Brownian motion. However, most standard tools from the well-studied framework of random dynamical systems cannot be applied to systems driven by non-Markovian noise, so it is desirable to construct possible approaches in a non-Markovian framework. We first derive the spectral density function of the considered system based on the generalized Parseval's formula and the Wiener-Khinchin theorem. Then we show that it enjoys interesting and diverse bifurcation phenomena exchanging between or among explosive-like, unimodal, and bimodal kurtosis. Therefore, our procedures in this paper are not merely comparable in scope to the existing theory of Markovian systems but also provide a possible approach to discern P-bifurcation dynamics in the non-Markovian settings. PMID:27586627

  2. Bifurcation dynamics of the tempered fractional Langevin equation

    NASA Astrophysics Data System (ADS)

    Zeng, Caibin; Yang, Qigui; Chen, YangQuan

    2016-08-01

    Tempered fractional processes offer a useful extension for turbulence to include low frequencies. In this paper, we investigate the stochastic phenomenological bifurcation, or stochastic P-bifurcation, of the Langevin equation perturbed by tempered fractional Brownian motion. However, most standard tools from the well-studied framework of random dynamical systems cannot be applied to systems driven by non-Markovian noise, so it is desirable to construct possible approaches in a non-Markovian framework. We first derive the spectral density function of the considered system based on the generalized Parseval's formula and the Wiener-Khinchin theorem. Then we show that it enjoys interesting and diverse bifurcation phenomena exchanging between or among explosive-like, unimodal, and bimodal kurtosis. Therefore, our procedures in this paper are not merely comparable in scope to the existing theory of Markovian systems but also provide a possible approach to discern P-bifurcation dynamics in the non-Markovian settings.

  3. Recovering hidden dynamical modes from the generalized Langevin equation.

    PubMed

    Kawai, Shinnosuke; Miyazaki, Yusuke

    2016-09-01

    In studying large molecular systems, insights can better be extracted by selecting a limited number of physical quantities for analysis rather than treating every atomic coordinate in detail. Some information may, however, be lost by projecting the total system onto a small number of coordinates. For such problems, the generalized Langevin equation (GLE) is shown to provide a useful framework to examine the interaction between the observed variables and their environment. Starting with the GLE obtained from the time series of the observed quantity, we perform a transformation to introduce a set of variables that describe dynamical modes existing in the environment. The introduced variables are shown to effectively recover the essential information of the total system that appeared to be lost by the projection. PMID:27608984

  4. Sampling the isothermal-isobaric ensemble by Langevin dynamics

    NASA Astrophysics Data System (ADS)

    Gao, Xingyu; Fang, Jun; Wang, Han

    2016-03-01

    We present a new method of conducting fully flexible-cell molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way, in the sense that the stationary configurational distribution is proved to be consistent with that of the isothermal-isobaric ensemble. In order to apply the proposed method in computer simulations, a second order symmetric numerical integration scheme is developed by Trotter's splitting of the single-step propagator. Moreover, a practical guide of choosing working parameters is suggested for user specified thermo- and baro-coupling time scales. The method and software implementation are carefully validated by a numerical example.

  5. A Langevin model for low density pedestrian dynamics

    NASA Astrophysics Data System (ADS)

    Corbetta, Alessandro; Lee, Chung-Min; Benzi, Roberto; Muntean, Adrian; Toschi, Federico

    The dynamics of pedestrian crowds shares deep connections with statistical physics and fluid dynamics. Reaching a quantitative understanding, not only of the average behaviours but also of the statistics of (rare) fluctuations would have major impact, for instance, on the design and safety of civil infrastructures. A key feature of pedestrian dynamics is its strong intrinsic variability, that we can already observe at the single individual level. In this work we aim at a quantitative characterisation of this statistical variability by studying individual fluctuations. We consider experimental observations of low-density pedestrian flows in a corridor within a building at Eindhoven University of Technology. Few hundreds of thousands of pedestrian trajectories with high space and time resolutions have been collected via a Microsoft Kinect 3D-range sensor and automatic head tracking techniques. From these observations we model pedestrians as active Brownian particles by means of a generalised Langevin equation. With this model we can quantitatively reproduce the observed dynamics including the statistics of ordinary pedestrian fluctuations and of rarer U-turn events. Low density, pair-wise interactions between pedestrians are also discussed.

  6. Calibrated Langevin-dynamics simulations of intrinsically disordered proteins

    NASA Astrophysics Data System (ADS)

    Smith, W. Wendell; Ho, Po-Yi; O'Hern, Corey S.

    2014-10-01

    We perform extensive coarse-grained (CG) Langevin dynamics simulations of intrinsically disordered proteins (IDPs), which possess fluctuating conformational statistics between that for excluded volume random walks and collapsed globules. Our CG model includes repulsive steric, attractive hydrophobic, and electrostatic interactions between residues and is calibrated to a large collection of single-molecule fluorescence resonance energy transfer data on the interresidue separations for 36 pairs of residues in five IDPs: α-, β-, and γ-synuclein, the microtubule-associated protein τ, and prothymosin α. We find that our CG model is able to recapitulate the average interresidue separations regardless of the choice of the hydrophobicity scale, which shows that our calibrated model can robustly capture the conformational dynamics of IDPs. We then employ our model to study the scaling of the radius of gyration with chemical distance in 11 known IDPs. We identify a strong correlation between the distance to the dividing line between folded proteins and IDPs in the mean charge and hydrophobicity space and the scaling exponent of the radius of gyration with chemical distance along the protein.

  7. Calibrated Langevin-dynamics simulations of intrinsically disordered proteins.

    PubMed

    Smith, W Wendell; Ho, Po-Yi; O'Hern, Corey S

    2014-10-01

    We perform extensive coarse-grained (CG) Langevin dynamics simulations of intrinsically disordered proteins (IDPs), which possess fluctuating conformational statistics between that for excluded volume random walks and collapsed globules. Our CG model includes repulsive steric, attractive hydrophobic, and electrostatic interactions between residues and is calibrated to a large collection of single-molecule fluorescence resonance energy transfer data on the interresidue separations for 36 pairs of residues in five IDPs: α-, β-, and γ-synuclein, the microtubule-associated protein τ, and prothymosin α. We find that our CG model is able to recapitulate the average interresidue separations regardless of the choice of the hydrophobicity scale, which shows that our calibrated model can robustly capture the conformational dynamics of IDPs. We then employ our model to study the scaling of the radius of gyration with chemical distance in 11 known IDPs. We identify a strong correlation between the distance to the dividing line between folded proteins and IDPs in the mean charge and hydrophobicity space and the scaling exponent of the radius of gyration with chemical distance along the protein. PMID:25375525

  8. Complex Langevin simulation of chiral symmetry restoration at finite baryonic density

    NASA Astrophysics Data System (ADS)

    Ilgenfritz, Ernst-Michael

    1986-12-01

    A recently proposed effective SU(3) spin model with chiral order parameter is studied by means of the complex Langevin equation. A first-order chiral symmetry restoring and deconfining transition is observed at sufficiently low temperature at finite baryonic density. Permanent address: Sektion Physik, Karl-Marx Universität, DDR-7010 Leipzig, German Democratic Republic.

  9. Dynamics of neutron-induced fission of 235U using four-dimensional Langevin equations

    NASA Astrophysics Data System (ADS)

    Pahlavani, M. R.; Mirfathi, S. M.

    2015-08-01

    Background: Langevin equations have been suggested as a key approach to the dynamical analysis of energy dissipation in excited nuclei, formed during heavy-ion fusion-fission reactions. Recently, a few researchers theoretically reported investigations of fission for light nuclei in a low excitation energy using the Langevin approach, without considering the contribution of pre- and post-scission particles and γ -ray emission. Purpose: We study the dynamical evolution of mass distribution of fission fragments, and neutron and γ -ray multiplicity for 236U as compound nuclei that are constructed after fusion of a neutron and 235U. Method: Energy dissipation of the compound nucleus through fission is calculated using the Langevin dynamical approach combined with a Monte Carlo method. Also the shape of the fissioning nucleus is restricted to "funny hills" parametrization. Results: Fission fragment mass distribution, neutron and γ -ray multiplicity, and the average kinetic energy of emitted neutrons and γ rays at a low excitation energy are calculated using a dynamical model, based on the four-dimensional Langevin equations. Conclusions: The theoretical results show reasonable agreement with experimental data and the proposed dynamical model can well explain the energy dissipation in low energy induced fission.

  10. Dynamical simulation of neutron-induced fission of uranium isotopes using four-dimensional Langevin equations

    NASA Astrophysics Data System (ADS)

    Pahlavani, M. R.; Mirfathi, S. M.

    2016-04-01

    Four-dimensional Langevin equations have been suggested for the dynamical simulation of neutron-induced fission at low and medium excitation energies. The mass distribution of the fission fragments, the neutron multiplicity, and the fission cross section for the thermal and fast neutron-induced fission of 233U, 235U, and 238U is studied by considering energy dissipation of the compound nucleus through the fission using four-dimensional Langevin equations combined with a Monte Carlo simulation approach. The calculated results using this approach indicate reasonable agreement with available experimental data.

  11. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.

    PubMed

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-14

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used. PMID:27421393

  12. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat

    NASA Astrophysics Data System (ADS)

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-01

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.

  13. Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism.

    PubMed

    Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G

    2015-04-01

    We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation. PMID:25974436

  14. Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism

    NASA Astrophysics Data System (ADS)

    Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G.

    2015-04-01

    We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation.

  15. A novel Generalized Langevin approach to bridge different timescales of relaxation in Protein Dynamics

    NASA Astrophysics Data System (ADS)

    Caballero Manrique, Esther; Bray, Jenelle; Guenza, Marina

    2006-03-01

    The derivation of a Generalized Langevin Equation (GLE) for the long-time dynamics of biological systems presents several challenges as hydrogen bonding, secondary and tertiary structure, Coulombic interactions, and hydrophobic effects come into play. Here we propose a novel GLE approach where the internal friction is explicitly included in the protein dynamics, allowing the distinction between hydrophobic and hydrophilic effects. The protein is described as a linear chain of beads (centered at the alpha carbons) that are connected by harmonic springs. Input for our theory is short time (ns) molecular dynamics simulations of a single protein (or complex) in solution, in this case the bacterial signal transduction protein CheY. Effective inter-bead potentials and local friction coefficients are obtained from the simulations. A comparison of the bond autocorrelation function predicted from the theory and calculated directly from the simulation affords the test of the theory in the short timescales (ns). In the long timescales (ms), the theory is tested against experimental NMR T1 relaxation values. Our results show a remarkable agreement in both cases, indicating that our GLE correctly bridges from the short- to the long-time scale of protein dynamics.

  16. Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review

    PubMed Central

    Paquet, Eric; Viktor, Herna L.

    2015-01-01

    Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262

  17. Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review.

    PubMed

    Paquet, Eric; Viktor, Herna L

    2015-01-01

    Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262

  18. Dynamic scaling behaviors of linear fractal Langevin-type equation driven by nonconserved and conserved noise

    NASA Astrophysics Data System (ADS)

    Zhang, Zhe; Xun, Zhi-Peng; Wu, Ling; Chen, Yi-Li; Xia, Hui; Hao, Da-Peng; Tang, Gang

    2016-06-01

    In order to study the effects of the microscopic details of fractal substrates on the scaling behavior of the growth model, a generalized linear fractal Langevin-type equation, ∂h / ∂t =(- 1) m + 1 ν∇ mzrw h (zrw is the dynamic exponent of random walk on substrates), driven by nonconserved and conserved noise is proposed and investigated theoretically employing scaling analysis. Corresponding dynamic scaling exponents are obtained.

  19. Dynamical consequences of a constraint on the Langevin thermostat in molecular cluster simulation

    SciTech Connect

    Stinson, Jake L.; Kathmann, Shawn M.; Ford, Ian J.

    2014-11-17

    We investigate some unusual behaviour observed while performing molecular dynamics simulations with the DL_POLY_4.03 code. Under the standard Langevin thermostat, atoms appear to be thermalised to different temperatures, depending on their mass and on the total number of particles in the system. We find that an imposed constraint whereby no thermal noise acts on the centre of mass of the system is the cause of the unexpected behaviour. This is demonstrated by solving the stochastic dynamics for the constrained thermostat and comparing the results with simulation data. The effect of the constraint can be considerable for small systems with disparate masses. By removing the constraint the Langevin thermostat may be restored to its intended behaviour and this has been implemented as an option in DL_POLY_4.05. SMK was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences.

  20. Biomolecular folding rates as understood from single-reaction-coordinate Langevin dynamics and Kramers' theory

    NASA Astrophysics Data System (ADS)

    Kabir, Md Adnan

    Langevin dynamics was used to model the folding and unfolding of simple, hairpin-like biomolecules whose ends are attached to laser-trapped beads, as occurs in optical tweezers experiments. The Langevin process was evolved numerically, using parameters motivated by real experimental systems. Folding trajectories were generated and analyzed to extract the folding rate as a function of the force applied to the beads. The observed rate was compared to the analytical predictions of Kramers' theory. Strong discrepancies were noted. The failure of the Kramers' theory was attributed to the slow dynamical response of the beads, which it does not account for. The results of this work highlight the necessity to include in the modeling the experimental systems that mediate force along the length of the biomolecule.

  1. Langevin model of the temperature and hydration dependence of protein vibrational dynamics.

    PubMed

    Moritsugu, Kei; Smith, Jeremy C

    2005-06-23

    The modification of internal vibrational modes in a protein due to intraprotein anharmonicity and solvation effects is determined by performing molecular dynamics (MD) simulations of myoglobin, analyzing them using a Langevin model of the vibrational dynamics and comparing the Langevin results to a harmonic, normal mode model of the protein in vacuum. The diagonal and off-diagonal Langevin friction matrix elements, which model the roughness of the vibrational potential energy surfaces, are determined together with the vibrational potentials of mean force from the MD trajectories at 120 K and 300 K in vacuum and in solution. The frictional properties are found to be describable using simple phenomenological functions of the mode frequency, the accessible surface area, and the intraprotein interaction (the displacement vector overlap of any given mode with the other modes in the protein). The frictional damping of a vibrational mode in vacuum is found to be directly proportional to the intraprotein interaction of the mode, whereas in solution, the friction is proportional to the accessible surface area of the mode. In vacuum, the MD frequencies are lower than those of the normal modes, indicating intramolecular anharmonic broadening of the associated potential energy surfaces. Solvation has the opposite effect, increasing the large-amplitude vibrational frequencies relative to in vacuum and thus vibrationally confining the protein atoms. Frictional damping of the low-frequency modes is highly frequency dependent. In contrast to the damping effect of the solvent, the vibrational frequency increase due to solvation is relatively temperature independent, indicating that it is primarily a structural effect. The MD-derived vibrational dynamic structure factor and density of states are well reproduced by a model in which the Langevin friction and potential of mean force parameters are applied to the harmonic normal modes. PMID:16852503

  2. Isothermal Langevin dynamics in systems with power-law spatially dependent friction

    NASA Astrophysics Data System (ADS)

    Regev, Shaked; Grønbech-Jensen, Niels; Farago, Oded

    2016-07-01

    We study the dynamics of Brownian particles in a heterogeneous one-dimensional medium with a spatially dependent diffusion coefficient of the form D (x ) ˜|x| c , at constant temperature. The particle's probability distribution function (PDF) is calculated both analytically, by solving Fick's diffusion equation, and from numerical simulations of the underdamped Langevin equation. At long times, the PDFs calculated by both approaches yield identical results, corresponding to subdiffusion for c <0 and superdiffusion for 0 1 , the diffusion equation predicts that the particles accelerate. Here we show that this phenomenon, previously considered in several works as an illustration for the possible dramatic effects of spatially dependent thermal noise, is unphysical. We argue that in an isothermal medium, the motion cannot exceed the ballistic limit (˜t2 ). The ballistic limit is reached when the friction coefficient drops sufficiently fast at large distances from the origin and is correctly captured by Langevin's equation.

  3. Constant pressure and temperature discrete-time Langevin molecular dynamics.

    PubMed

    Grønbech-Jensen, Niels; Farago, Oded

    2014-11-21

    We present a new and improved method for simultaneous control of temperature and pressure in molecular dynamics simulations with periodic boundary conditions. The thermostat-barostat equations are built on our previously developed stochastic thermostat, which has been shown to provide correct statistical configurational sampling for any time step that yields stable trajectories. Here, we extend the method and develop a set of discrete-time equations of motion for both particle dynamics and system volume in order to seek pressure control that is insensitive to the choice of the numerical time step. The resulting method is simple, practical, and efficient. The method is demonstrated through direct numerical simulations of two characteristic model systems-a one-dimensional particle chain for which exact statistical results can be obtained and used as benchmarks, and a three-dimensional system of Lennard-Jones interacting particles simulated in both solid and liquid phases. The results, which are compared against the method of Kolb and Dünweg [J. Chem. Phys. 111, 4453 (1999)], show that the new method behaves according to the objective, namely that acquired statistical averages and fluctuations of configurational measures are accurate and robust against the chosen time step applied to the simulation. PMID:25416875

  4. Constant pressure and temperature discrete-time Langevin molecular dynamics

    SciTech Connect

    Grønbech-Jensen, Niels; Farago, Oded

    2014-11-21

    We present a new and improved method for simultaneous control of temperature and pressure in molecular dynamics simulations with periodic boundary conditions. The thermostat-barostat equations are built on our previously developed stochastic thermostat, which has been shown to provide correct statistical configurational sampling for any time step that yields stable trajectories. Here, we extend the method and develop a set of discrete-time equations of motion for both particle dynamics and system volume in order to seek pressure control that is insensitive to the choice of the numerical time step. The resulting method is simple, practical, and efficient. The method is demonstrated through direct numerical simulations of two characteristic model systems—a one-dimensional particle chain for which exact statistical results can be obtained and used as benchmarks, and a three-dimensional system of Lennard-Jones interacting particles simulated in both solid and liquid phases. The results, which are compared against the method of Kolb and Dünweg [J. Chem. Phys. 111, 4453 (1999)], show that the new method behaves according to the objective, namely that acquired statistical averages and fluctuations of configurational measures are accurate and robust against the chosen time step applied to the simulation.

  5. Nonlinear Langevin model for the early-stage dynamics of electrospinning jets

    NASA Astrophysics Data System (ADS)

    Lauricella, Marco; Pontrelli, Giuseppe; Pisignano, Dario; Succi, Sauro

    2015-09-01

    We present a nonlinear Langevin model to investigate the early-stage dynamics of electrified polymer jets in electrospinning experiments. In particular, we study the effects of air drag force on the uniaxial elongation of the charged jet, right after ejection from the nozzle. Numerical simulations show that the elongation of the jet filament close to the injection point is significantly affected by the nonlinear drag exerted by the surrounding air. These results provide useful insights for the optimal design of current and future electrospinning experiments.

  6. Test for a universal behavior of Dirac eigenvalues in the complex Langevin method

    NASA Astrophysics Data System (ADS)

    Ichihara, Terukazu; Nagata, Keitaro; Kashiwa, Kouji

    2016-05-01

    We apply the complex Langevin (CL) method to a chiral random matrix theory (ChRMT) at nonzero chemical potential and study the nearest neighbor spacing (NNS) distribution of the Dirac eigenvalues. The NNS distribution is extracted using an unfolding procedure for the Dirac eigenvalues obtained in the CL method. For large quark mass, we find that the NNS distribution obeys the Ginibre ensemble as expected. For small quark mass, the NNS distribution follows the Wigner surmise for the correct convergence case, while it follows the Ginibre ensemble for the wrong convergence case. The Wigner surmise is physically reasonable from the chemical potential independence of the ChRMT. The Ginibre ensemble is known to be favored in a phase-quenched QCD at finite chemical potential. Our result suggests a possibility that the originally universal behavior of the NNS distribution is preserved even in the CL method for the correct convergence case.

  7. Boedeker's effective theory: From Langevin dynamics to Dyson-Schwinger equations

    SciTech Connect

    Zahlten, Claus Hernandez, Andres Schmidt, Michael G.

    2009-10-15

    The dynamics of weakly coupled, non-abelian gauge fields at high temperature is non-perturbative if the characteristic momentum scale is of order |k|{approx}g{sup 2}T. Such a situation is typical for the processes of electroweak baryon number violation in the early Universe. Boedeker has derived an effective theory that describes the dynamics of the soft field modes by means of a Langevin equation. This effective theory has been used for lattice calculations so far [G.D. Moore, Nucl. Phys. B568 (2000) 367. Available from: (); G.D. Moore, Phys. Rev. D62 (2000) 085011. Available from: ()]. In this work we provide a complementary, more analytic approach based on Dyson-Schwinger equations. Using methods known from stochastic quantitation, we recast Boedeker's Langevin equation in the form of a field theoretic path integral. We introduce gauge ghosts in order to help control possible gauge artefacts that might appear after truncation, and which leads to a BRST symmetric formulation and to corresponding Ward identities. A second set of Ward identities, reflecting the origin of the theory in a stochastic differential equation, is also obtained. Finally, Dyson-Schwinger equations are derived.

  8. Generalized Langevin dynamics of a nanoparticle using a finite element approach: Thermostating with correlated noise

    NASA Astrophysics Data System (ADS)

    Uma, B.; Swaminathan, T. N.; Ayyaswamy, P. S.; Eckmann, D. M.; Radhakrishnan, R.

    2011-09-01

    A direct numerical simulation (DNS) procedure is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian stationary fluid medium with the generalized Langevin approach. We consider both the Markovian (white noise) and non-Markovian (Ornstein-Uhlenbeck noise and Mittag-Leffler noise) processes. Initial locations of the particle are at various distances from the bounding wall to delineate wall effects. At thermal equilibrium, the numerical results are validated by comparing the calculated translational and rotational temperatures of the particle with those obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation functions and mean square displacements with analytical results. Numerical predictions of wall interactions with the particle in terms of mean square displacements are compared with analytical results. In the non-Markovian Langevin approach, an appropriate choice of colored noise is required to satisfy the power-law decay in the velocity autocorrelation function at long times. The results obtained by using non-Markovian Mittag-Leffler noise simultaneously satisfy the equipartition theorem and the long-time behavior of the hydrodynamic correlations for a range of memory correlation times. The Ornstein-Uhlenbeck process does not provide the appropriate hydrodynamic correlations. Comparing our DNS results to the solution of an one-dimensional generalized Langevin equation, it is observed that where the thermostat adheres to the equipartition theorem, the characteristic memory time in the noise is consistent with the inherent time scale of the memory kernel. The performance of the thermostat with respect to equilibrium and dynamic properties for various noise schemes is discussed.

  9. Isothermal Langevin dynamics in systems with power-law spatially dependent friction.

    PubMed

    Regev, Shaked; Grønbech-Jensen, Niels; Farago, Oded

    2016-07-01

    We study the dynamics of Brownian particles in a heterogeneous one-dimensional medium with a spatially dependent diffusion coefficient of the form D(x)∼|x|^{c}, at constant temperature. The particle's probability distribution function (PDF) is calculated both analytically, by solving Fick's diffusion equation, and from numerical simulations of the underdamped Langevin equation. At long times, the PDFs calculated by both approaches yield identical results, corresponding to subdiffusion for c<0 and superdiffusion for 01, the diffusion equation predicts that the particles accelerate. Here we show that this phenomenon, previously considered in several works as an illustration for the possible dramatic effects of spatially dependent thermal noise, is unphysical. We argue that in an isothermal medium, the motion cannot exceed the ballistic limit (〈x^{2}〉∼t^{2}). The ballistic limit is reached when the friction coefficient drops sufficiently fast at large distances from the origin and is correctly captured by Langevin's equation. PMID:27575086

  10. Heavy quark diffusion with relativistic Langevin dynamics in the quark-gluon fluid

    SciTech Connect

    Akamatsu, Yukinao; Hatsuda, Tetsuo; Hirano, Tetsufumi

    2009-05-15

    The relativistic diffusion process of heavy quarks is formulated on the basis of the relativistic Langevin equation in Ito discretization scheme. The drag force inside the quark-gluon plasma (QGP) is parametrized according to the formula for the strongly coupled plasma obtained by the anti-de-Sitter space/conformal field theory (AdS/CFT) correspondence. The diffusion dynamics of charm and bottom quarks in QGP is described by combining the Langevin simulation under the background matter described by the relativistic hydrodynamics. Theoretical calculations of the nuclear modification factor R{sub AA} and the elliptic flow v{sub 2} for the single electrons from the charm and bottom decays are compared with the experimental data from the relativistic heavy-ion collisions. The R{sub AA} for electrons with large transverse momentum (p{sub T}>3 GeV) indicates that the drag force from the QGP is as strong as the AdS/CFT prediction.

  11. Generalized Langevin models of molecular dynamics simulations with applications to ion channels

    NASA Astrophysics Data System (ADS)

    Gordon, Dan; Krishnamurthy, Vikram; Chung, Shin-Ho

    2009-10-01

    We present a new methodology, which combines molecular dynamics and stochastic dynamics, for modeling the permeation of ions across biological ion channels. Using molecular dynamics, a free energy profile is determined for the ion(s) in the channel, and the distribution of random and frictional forces is measured over discrete segments of the ion channel. The parameters thus determined are used in stochastic dynamics simulations based on the nonlinear generalized Langevin equation. We first provide the theoretical basis of this procedure, which we refer to as "distributional molecular dynamics," and detail the methods for estimating the parameters from molecular dynamics to be used in stochastic dynamics. We test the technique by applying it to study the dynamics of ion permeation across the gramicidin pore. Given the known difficulty in modeling the conduction of ions in gramicidin using classical molecular dynamics, there is a degree of uncertainty regarding the validity of the MD-derived potential of mean force (PMF) for gramicidin. Using our techniques and systematically changing the PMF, we are able to reverse engineer a modified PMF which gives a current-voltage curve closely matching experimental results.

  12. Langevin dynamics of the choline head group in a membrane environment.

    PubMed Central

    Konstant, P H; Pearce, L L; Harvey, S C

    1994-01-01

    Computer simulations of dipalmitoylphosphatidylcholine (DPPC) have been performed using Langevin dynamics and a Marcelja-type mean field. This work has focused on the dynamics of the choline head group to parameterize the empirical constraints against phosphorus-carbon dipolar couplings (Dp-c) as measured by nuclear magnetic resonance (13C-NMR). The results show good agreement with experimental values at constraints equivalent to the choline tilt observed in joint refinement of x-ray diffraction and neutron diffraction scatterings. Quadrupolar splittings for the alpha and beta positions are also calculated and compared with 2H-NMR experiments. The model predicts torsional transition rates around the alpha-beta bonds and for the two C-O-P-O torsions. It also predicts T1 relaxation times for the alpha and beta carbons. PMID:7948684

  13. On Application Of Langevin Dynamics In Logarithmic Potential To Model Ion Channel Gate Activity.

    PubMed

    Wawrzkiewicz-Jałowiecka, Agata; Borys, Przemysław; Grzywna, Zbigniew J

    2015-12-01

    We model the activity of an ion channel gate by Langevin dynamics in a logarithmic potential. This approach enables one to describe the power-law dwell-time distributions of the considered system, and the long-term correlations between the durations of the subsequent channel states, or fractal scaling of statistical characteristics of the gate's movement with time. Activity of an ion channel gate is described as an overdamped motion of the reaction coordinate in a confining logarithmic potential, which ensures great flexibility of the model. Depending on the chosen parameters, it allows one to reproduce many types of gate dynamics within the family of non-Markovian, anomalous conformational diffusion processes. In this study we apply the constructed model to largeconductance voltage and Ca2+-activated potassium channels (BKCa). The interpretation of model assumptions and parameters is provided in terms of this biological system. Our results show good agreement with the experimental data. PMID:26317442

  14. Response of rotation-translation blocked proteins using Langevin dynamics on a locally harmonic landscape.

    PubMed

    Manson, Anthony C; Coalson, Rob D

    2012-10-11

    Langevin dynamics is used to compute the time evolution of the nonequilibrium motion of the atomic coordinates of a protein in response to ligand dissociation. The protein potential energy surface (PES) is approximated by a harmonic basin about the minimum of the unliganded state. Upon ligand dissociation, the protein undergoes relaxation from the bound to the unbound state. A coarse graining scheme based on rotation translation blocks (RTB) is applied to the relaxation of the two domain iron transport protein, ferric binding protein. This scheme provides a natural and efficient way to freeze out the small amplitude, high frequency motions within each rigid fragment, thereby allowing for the number of dynamical degrees of freedom to be reduced. The results obtained from all flexible atom (constraint free) dynamics are compared to those obtained using RTB-Langevin dynamics. To assess the impact of the assumed rigid fragment clustering on the temporal relaxation dynamics of the protein molecule, three distinct rigid block decompositions were generated and their responses compared. Each of the decompositions was a variant of the one-block-per-residue grouping, with their force and friction matrices being derived from their fully flexible counterpart. Monitoring the time evolution of the distance separating a selected pair of amino acids, the response curves of the blocked decompositions were similar in shape to each other and to the control system in which all atomic degrees of freedom are fully independent. The similar shape of the blocked responses showed that the variations in grouping had only a minor impact on the kinematics. Compared with the all atom responses, however, the blocked responses were faster as a result of the instantaneous transmission of force throughout each rigid block. This occurred because rigid blocking does not permit any intrablock deformation that could store or divert energy. It was found, however, that this accelerated response could be

  15. Time Step Rescaling Recovers Continuous-Time Dynamical Properties for Discrete-Time Langevin Integration of Nonequilibrium Systems

    PubMed Central

    2015-01-01

    When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon desirable properties. However, for stochastic equations of motion (e.g., Langevin dynamics), there is still broad disagreement over which integration algorithms are most appropriate. While multiple desiderata have been proposed throughout the literature, consensus on which criteria are important is absent, and no published integration scheme satisfies all desiderata simultaneously. Additional nontrivial complications stem from simulating systems driven out of equilibrium using existing stochastic integration schemes in conjunction with recently developed nonequilibrium fluctuation theorems. Here, we examine a family of discrete time integration schemes for Langevin dynamics, assessing how each member satisfies a variety of desiderata that have been enumerated in prior efforts to construct suitable Langevin integrators. We show that the incorporation of a novel time step rescaling in the deterministic updates of position and velocity can correct a number of dynamical defects in these integrators. Finally, we identify a particular splitting (related to the velocity Verlet discretization) that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts. PMID:24555448

  16. Protein Folding Simulations Combining Self-Guided Langevin Dynamics and Temperature-Based Replica Exchange.

    PubMed

    Lee, Michael S; Olson, Mark A

    2010-08-10

    Computer simulations are increasingly being used to predict thermodynamic observables for folding small proteins. Key to continued progress in this area is the development of algorithms that accelerate conformational sampling. Temperature-based replica exchange (ReX) is a commonly used protocol whereby simulations at several temperatures are simultaneously performed and temperatures are exchanged between simulations via a Metropolis criterion. Another method, self-guided Langevin dynamics (SGLD), expedites conformational sampling by accelerating low-frequency, large-scale motions through the addition of an ad hoc momentum memory term. In this work, we combined these two complementary techniques and compared the results against conventional ReX formulations of molecular dynamics (MD) and Langevin dynamics (LD) simulations for the prediction of thermodynamic folding observables of the Trp-cage mini-protein. All simulations were performed with CHARMM using the PARAM22+CMAP force field and the generalized Born molecular volume implicit solvent model. While SGLD-ReX does not fold up the protein significantly faster than the two conventional ReX approaches, there is some evidence that the method improves sampling convergence by reducing topological folding barriers between energetically similar near-native states. Unlike MD-ReX and LD-ReX, SGLD-ReX predicts melting temperatures, heat capacity curves, and folding free energies that are closer in agreement to the experimental observations. However, this favorable result may be due to distortions of the relative free energies of the folded and unfolded conformational basins caused by the ad hoc force term in the SGLD model. PMID:26613500

  17. Kinetics of formation of bile salt micelles from coarse-grained Langevin dynamics simulations.

    PubMed

    Vila Verde, Ana; Frenkel, Daan

    2016-06-21

    We examine the mechanism of formation of micelles of dihydroxy bile salts using a coarse-grained, implicit solvent model and Langevin dynamics simulations. We find that bile salt micelles primarily form via addition and removal of monomers, similarly to surfactants with typical head-tail molecular structures, and not via a two-stage mechanism - involving formation of oligomers and their subsequent aggregation to form larger micelles - originally proposed for bile salts. The free energy barrier to removal of single bile monomers from micelles is ≈2kBT, much less than what has been observed for head-tail surfactants. Such a low barrier may be biologically relevant: it allows for rapid release of bile monomers into the intestine, possibly enabling the coverage of fat droplets by bile salt monomers and subsequent release of micelles containing fats and bile salts - a mechanism that is not possible for ionic head-tail surfactants of similar critical micellar concentrations. PMID:27199094

  18. Current-induced atomic dynamics, instabilities, and Raman signals: Quasiclassical Langevin equation approach

    NASA Astrophysics Data System (ADS)

    Lü, Jing-Tao; Brandbyge, Mads; Hedegård, Per; Todorov, Tchavdar N.; Dundas, Daniel

    2012-06-01

    We derive and employ a semiclassical Langevin equation obtained from path integrals to describe the ionic dynamics of a molecular junction in the presence of electrical current. The electronic environment serves as an effective nonequilibrium bath. The bath results in random forces describing Joule heating, current-induced forces including the nonconservative wind force, dissipative frictional forces, and an effective Lorentz-type force due to the Berry phase of the nonequilibrium electrons. Using a generic two-level molecular model, we highlight the importance of both current-induced forces and Joule heating for the stability of the system. We compare the impact of the different forces, and the wide-band approximation for the electronic structure on our result. We examine the current-induced instabilities (excitation of runaway “waterwheel” modes) and investigate the signature of these in the Raman signals.

  19. Anomalous polymer dynamics is non-Markovian: memory effects and the generalized Langevin equation formulation

    NASA Astrophysics Data System (ADS)

    Panja, Debabrata

    2010-06-01

    Any first course on polymer physics teaches that the dynamics of a tagged monomer of a polymer is anomalously subdiffusive, i.e., the mean-square displacement of a tagged monomer increases as tα for some α < 1 until the terminal relaxation time τ of the polymer. Beyond time τ the motion of the tagged monomer becomes diffusive. Classical examples of anomalous dynamics in polymer physics are single polymeric systems, such as phantom Rouse, self-avoiding Rouse, self-avoiding Zimm, reptation, translocation through a narrow pore in a membrane, and many-polymeric systems such as polymer melts. In this pedagogical paper I report that all these instances of anomalous dynamics in polymeric systems are robustly characterized by power-law memory kernels within a unified generalized Langevin equation (GLE) scheme, and therefore are non-Markovian. The exponents of the power-law memory kernels are related to the relaxation response of the polymers to local strains, and are derived from the equilibrium statistical physics of polymers. The anomalous dynamics of a tagged monomer of a polymer in these systems is then reproduced from the power-law memory kernels of the GLE via the fluctuation-dissipation theorem (FDT). Using this GLE formulation I further show that the characteristics of the drifts caused by a (weak) applied field on these polymeric systems are also obtained from the corresponding memory kernels.

  20. Masking Resonance Artifacts in Force-Splitting Methods for Biomolecular Simulations by Extrapolative Langevin Dynamics

    NASA Astrophysics Data System (ADS)

    Sandu, Adrian; Schlick, Tamar

    1999-05-01

    Numerical resonance artifacts have become recognized recently as a limiting factor to increasing the timestep in multiple-timestep (MTS) biomolecular dynamics simulations. At certain timesteps correlated to internal motions (e.g., 5 fs, around half the period of the fastest bond stretch, Tmin), visible inaccuracies or instabilities can occur. Impulse-MTS schemes are vulnerable to these resonance errors since large energy pulses are introduced to the governing dynamics equations when the slow forces are evaluated. We recently showed that such resonance artifacts can be masked significantly by applying extrapolative splitting to stochastic dynamics. Theoretical and numerical analyses of force-splitting integrators based on the Verlet discretization are reported here for linear models to explain these observations and to suggest how to construct effective integrators for biomolecular dynamics that balance stability with accuracy. Analyses for Newtonian dynamics demonstrate the severe resonance patterns of the Impulse splitting, with this severity worsening with the outer timestep, Δ t; Constant Extrapolation is generally unstable, but the disturbances do not grow with Δ t. Thus, the stochastic extrapolative combination can counteract generic instabilities and largely alleviate resonances with a sufficiently strong Langevin heat-bath coupling (γ), estimates for which are derived here based on the fastest and slowest motion periods. These resonance results generally hold for nonlinear test systems: a water tetramer and solvated protein. Proposed related approaches such as Extrapolation/Correction and Midpoint Extrapolation work better than Constant Extrapolation only for timesteps less than Tmin/2. An effective extrapolative stochastic approach for biomolecules that balances long-timestep stability with good accuracy for the fast subsystem is then applied to a biomolecule using a three-class partitioning: the medium forces are treated by Midpoint Extrapolationvia

  1. Many-particle Brownian and Langevin Dynamics Simulations with the Brownmove package

    PubMed Central

    2011-01-01

    Background Brownian Dynamics (BD) is a coarse-grained implicit-solvent simulation method that is routinely used to investigate binary protein association dynamics, but due to its efficiency in handling large simulation volumes and particle numbers it is well suited to also describe many-protein scenarios as they often occur in biological cells. Results Here we introduce our "brownmove" simulation package which was designed to handle many-particle problems with varying particle numbers and allows for a very flexible definition of rigid and flexible protein and polymer models. Both a Brownian and a Langevin dynamics (LD) propagation scheme can be used and hydrodynamic interactions are treated efficiently with our recently introduced TEA-HI ansatz [Geyer, Winter, JCP 130 (2009) 114905]. With simulations of constrained polymers and flexible models of spherical proteins we demonstrate that it is crucial to include hydrodynamics when multi-bead models are used in BD or LD simulations. Only then both the translational and the rotational diffusion coefficients and the timescales of the internal dynamics can be reproduced correctly. In the third example project we show how constant density boundary conditions [Geyer et al, JCP 120 (2004) 4573] can be used to set up a non-equilibrium simulation of diffusional transport across an array of fixed obstacles. Finally, we demonstrate how the agglomeration dynamics of multiple particles with attractive patches can be analysed conveniently with the help of a dynamic interaction network. Conclusions Combining BD and LD propagation, fast hydrodynamics, a flexible protein model, and interfaces for "open" simulation settings, our freely available "brownmove" simulation package constitutes a new platform for coarse-grained many-particle simulations of biologically relevant diffusion and transport processes. PMID:21596002

  2. Self-guided Langevin dynamics study of regulatory interactions in NtrC

    PubMed Central

    Damjanović, Ana; García-Moreno E, Bertrand; Brooks, Bernard R.

    2012-01-01

    Multiple self-guided Langevin dynamics (SGLD) simulations were performed to examine structural and dynamical properties of the receiver domain of Nitrogen Regulatory Protein C (NtrCr). SGLD and MD simulations of the phosphorylated active form structure suggest a mostly stable but broad structural ensemble of this protein. The finite difference Poisson-Boltzmann calculations of the pKa values of the active site residues suggest an increase in the pKa of His-84 upon phosphorylation of Asp-54. In SGLD simulations of the phosphorylated active form with charged His-84 the average position of the regulatory helix α4 is found closer to the starting structure than in simulations with the neutral His-84. To model the transition pathway the phosphate group was removed from the simulations. After 7 ns of simulations, the regulatory helix α4 was found approximately halfway between positions in the NMR structures of the active and inactive forms. Removal of the phosphate group stimulated loss of helix α4, suggesting that the pathway of conformational transition may involve partial unfolding mechanism. The study illustrates the potential utility of the SGLD method in studies of the coupling between ligand binding and conformational transitions. PMID:19384996

  3. Perturbative treatment of anharmonic vibrational effects on bond distances: an extended Langevin dynamics method.

    PubMed

    Shen, Tonghao; Su, Neil Qiang; Wu, Anan; Xu, Xin

    2014-03-01

    In this work, we first review the perturbative treatment of an oscillator with cubic anharmonicity. It is shown that there is a quantum-classical correspondence in terms of mean displacement, mean-squared displacement, and the corresponding variance in the first-order perturbation theory, provided that the amplitude of the classical oscillator is fixed at the zeroth-order energy of quantum mechanics EQM (0). This correspondence condition is realized by proposing the extended Langevin dynamics (XLD), where the key is to construct a proper driving force. It is assumed that the driving force adopts a simple harmonic form with its amplitude chosen according to EQM (0), while the driving frequency chosen as the harmonic frequency. The latter can be improved by using the natural frequency of the system in response to the potential if its anharmonicity is strong. By comparing to the accurate numeric results from discrete variable representation calculations for a set of diatomic species, it is shown that the present method is able to capture the large part of anharmonicity, being competitive with the wave function-based vibrational second-order perturbation theory, for the whole frequency range from ∼4400 cm(-1) (H2 ) to ∼160 cm(-1) (Na2 ). XLD shows a substantial improvement over the classical molecular dynamics which ceases to work for hard mode when zero-point energy effects are significant. PMID:24375394

  4. Langevin dynamics simulation of polymer-assisted virus-like assembly

    NASA Astrophysics Data System (ADS)

    Mahalik, J. P.; Muthukumar, M.

    2012-04-01

    Starting from a coarse grained representation of the building units of the minute virus of mice and a flexible polyelectrolyte molecule, we have explored the mechanism of assembly into icosahedral structures with the help of Langevin dynamics simulations and the parallel tempering technique. Regular icosahedra with appropriate symmetry form only in a narrow range of temperature and polymer length. Within this region of parameters where successful assembly would proceed, we have systematically investigated the growth kinetics. The assembly of icosahedra is found to follow the classical nucleation and growth mechanism in the absence of the polymer, with the three regimes of nucleation, linear growth, and slowing down in the later stage. The calculated average nucleation time obeys the laws expected from the classical nucleation theory. The linear growth rate is found to obey the laws of secondary nucleation as in the case of lamellar growth in polymer crystallization. The same mechanism is seen in the simulations of the assembly of icosahedra in the presence of the polymer as well. The polymer reduces the nucleation barrier significantly by enhancing the local concentration of subunits via adsorbing them on their backbone. The details of growth in the presence of the polymer are also found to be consistent with the classical nucleation theory, despite the smallness of the assembled structures.

  5. Langevin Dynamics Simulation of DNA Condensation Induced by Nanoparticles in Confinement

    NASA Astrophysics Data System (ADS)

    Liao, Guo-Jun; Chen, Yeng-Long

    2013-03-01

    We study nanoparticle-induced DNA condensation in a confined suspension of dilute DNA molecules and ideal nanoparticles (NPs) with Langevin dynamics simulation. DNA condensation has been observed in a solution of dilute DNA molecules (persistence length P ~ 50 nm) and high concentration of electrostatically neutral NPs (diameter d ~ 5 to 35 nm) in recent experimental measurements. It is believed that NPs entropically induce an attraction between DNA segments. For NPs much smaller than P, a DNA molecule can be considered as a chain of connected rods, and the NP-induced depletion attraction between DNA segments can be regarded as rod-rod attraction. Thus, the strength of the depletion attraction is proportional to the number of persistence length in a DNA chain, N = L / P , the depletion volume NP2 d , and the NP density ρ, where L is the DNA contour length. In slit confinement, DNA conformation changes are much different from in an unconfined environment. The height of the slit relative to the NPs size (H / d) strongly influences the DNA conformation. For H / d ~ 1 , DNA size decreases monotonically as ρ increases, while non-monotonic dependence happens for H / d ~ 5 , due to the competition between DNA-DNA, DNA-NP, and NP-wall interactions.

  6. Generalized Langevin equation: An efficient approach to nonequilibrium molecular dynamics of open systems

    NASA Astrophysics Data System (ADS)

    Stella, L.; Lorenz, C. D.; Kantorovich, L.

    2014-04-01

    The generalized Langevin equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general nonequilibrium processes. In this approach, a part of the whole system (an open system), which interacts and exchanges energy with its dissipative environment, is studied. Because the GLE is derived by projecting out exactly the harmonic environment, the coupling to it is realistic, while the equations of motion are non-Markovian. Although the GLE formalism has already found promising applications, e.g., in nanotribology and as a powerful thermostat for equilibration in classical molecular dynamics simulations, efficient algorithms to solve the GLE for realistic memory kernels are highly nontrivial, especially if the memory kernels decay nonexponentially. This is due to the fact that one has to generate a colored noise and take account of the memory effects in a consistent manner. In this paper, we present a simple, yet efficient, algorithm for solving the GLE for practical memory kernels and we demonstrate its capability for the exactly solvable case of a harmonic oscillator coupled to a Debye bath.

  7. An electrodynamics-Langevin dynamics (ED-LD) approach to simulate metal nanoparticle interactions and motion.

    PubMed

    Sule, N; Rice, S A; Gray, S K; Scherer, N F

    2015-11-16

    Understanding the formation of electrodynamically interacting assemblies of metal nanoparticles requires accurate computational methods for determining the forces and propagating trajectories. However, since computation of electromagnetic forces occurs on attosecond to femtosecond timescales, simulating the motion of colloidal nanoparticles on milliseconds to seconds timescales is a challenging multi-scale computational problem. Here, we present a computational technique for performing accurate simulations of laser-illuminated metal nanoparticles. In the simulation, we self-consistently combine the finite-difference time-domain method for electrodynamics (ED) with Langevin dynamics (LD) for the particle motions. We demonstrate the ED-LD method by calculating the 3D trajectories of a single 100-nm-diameter Ag nanoparticle and optical trapping and optical binding of two and three 150-nm-diameter Ag nanoparticles in simulated optical tweezers. We show that surface charge on the colloidal metal nanoparticles plays an important role in their optically driven self-organization. In fact, these simulations provide a more complete understanding of the assembly of different structures of two and three Ag nanoparticles that have been observed experimentally, demonstrating that the ED-LD method will be a very useful tool for understanding the self-organization of optical matter. PMID:26698479

  8. Finite-Temperature Non-equilibrium Quasicontinuum Method based on Langevin Dynamics

    SciTech Connect

    Marian, J; Venturini, G; Hansen, B; Knap, J; Ortiz, M; Campbell, G

    2009-05-08

    The concurrent bridging of molecular dynamics and continuum thermodynamics presents a number of challenges, mostly associated with energy transmission and changes in the constitutive description of a material across domain boundaries. In this paper, we propose a framework for simulating coarse dynamic systems in the canonical ensemble using the Quasicontinuum method (QC). The equations of motion are expressed in reduced QC coordinates and are strictly derived from dissipative Lagrangian mechanics. The derivation naturally leads to a classical Langevin implementation where the timescale is governed by vibrations emanating from the finest length scale occurring in the computational cell. The equations of motion are integrated explicitly via Newmark's ({beta} = 0; {gamma} = 1/2) method, leading to a robust numerical behavior and energy conservation. In its current form, the method only allows for wave propagations supported by the less compliant of the two meshes across a heterogeneous boundary, which requires the use of overdamped dynamics to avoid spurious heating due to reflected vibrations. We have applied the method to two independent crystallographic systems characterized by different interatomic potentials (Al and Ta) and have measured thermal expansion in order to quantify the vibrational entropy loss due to homogenization. We rationalize the results in terms of system size, mesh coarseness, and nodal cluster diameter within the framework of the quasiharmonic approximation. For Al, we find that the entropy loss introduced by mesh coarsening varies linearly with the element size, and that volumetric effects are not critical in driving the anharmonic behavior of the simulated systems. In Ta, the anomalies of the interatomic potential employed result in negative and zero thermal expansion at low and high temperatures, respectively.

  9. Critical dynamics of self-gravitating Langevin particles and bacterial populations.

    PubMed

    Sire, Clément; Chavanis, Pierre-Henri

    2008-12-01

    We study the critical dynamics of the generalized Smoluchowski-Poisson system (for self-gravitating Langevin particles) or generalized Keller-Segel model (for the chemotaxis of bacterial populations). These models [P. H. Chavanis and C. Sire, Phys. Rev. E 69, 016116 (2004)] are based on generalized stochastic processes leading to the Tsallis statistics. The equilibrium states correspond to polytropic configurations with index n similar to polytropic stars in astrophysics. At the critical index n_{3}=d(d-2) (where d>or=2 is the dimension of space), there exists a critical temperature Theta_{c} (for a given mass) or a critical mass M_{c} (for a given temperature). For Theta>Theta_{c} or MM_{c} the system collapses and forms, in a finite time, a Dirac peak containing a finite fraction M_{c} of the total mass surrounded by a halo. We study these regimes numerically and, when possible, analytically by looking for self-similar or pseudo-self-similar solutions. This study extends the critical dynamics of the ordinary Smoluchowski-Poisson system and Keller-Segel model in d=2 corresponding to isothermal configurations with n_{3}-->+infinity . We also stress the analogy between the limiting mass of white dwarf stars (Chandrasekhar's limit) and the critical mass of bacterial populations in the generalized Keller-Segel model of chemotaxis. PMID:19256806

  10. Critical dynamics of self-gravitating Langevin particles and bacterial populations

    NASA Astrophysics Data System (ADS)

    Sire, Clément; Chavanis, Pierre-Henri

    2008-12-01

    We study the critical dynamics of the generalized Smoluchowski-Poisson system (for self-gravitating Langevin particles) or generalized Keller-Segel model (for the chemotaxis of bacterial populations). These models [P. H. Chavanis and C. Sire, Phys. Rev. E 69, 016116 (2004)] are based on generalized stochastic processes leading to the Tsallis statistics. The equilibrium states correspond to polytropic configurations with index n similar to polytropic stars in astrophysics. At the critical index n3=d/(d-2) (where d⩾2 is the dimension of space), there exists a critical temperature Θc (for a given mass) or a critical mass Mc (for a given temperature). For Θ>Θc or MMc the system collapses and forms, in a finite time, a Dirac peak containing a finite fraction Mc of the total mass surrounded by a halo. We study these regimes numerically and, when possible, analytically by looking for self-similar or pseudo-self-similar solutions. This study extends the critical dynamics of the ordinary Smoluchowski-Poisson system and Keller-Segel model in d=2 corresponding to isothermal configurations with n3→+∞ . We also stress the analogy between the limiting mass of white dwarf stars (Chandrasekhar’s limit) and the critical mass of bacterial populations in the generalized Keller-Segel model of chemotaxis.

  11. The Langevin Hull: Constant pressure and temperature dynamics for non-periodic systems

    PubMed Central

    Vardeman, Charles F.; Stocker, Kelsey M.; Gezelter, J. Daniel

    2011-01-01

    We have developed a new isobaric-isothermal (NPT) algorithm which applies an external pressure to the facets comprising the convex hull surrounding the system. A Langevin thermostat is also applied to the facets to mimic contact with an external heat bath. This new method, the “Langevin Hull”, can handle heterogeneous mixtures of materials with different compressibilities. These systems are problematic for traditional affine transform methods. The Langevin Hull does not suffer from the edge effects of boundary potential methods, and allows realistic treatment of both external pressure and thermal conductivity due to the presence of an implicit solvent. We apply this method to several different systems including bare metal nanoparticles, nanoparticles in an explicit solvent, as well as clusters of liquid water. The predicted mechanical properties of these systems are in good agreement with experimental data and previous simulation work. PMID:21547015

  12. The Small-Mass Limit for Langevin Dynamics with Unbounded Coefficients and Positive Friction

    NASA Astrophysics Data System (ADS)

    Herzog, David P.; Hottovy, Scott; Volpe, Giovanni

    2016-05-01

    A class of Langevin stochastic differential equations is shown to converge in the small-mass limit under very weak assumptions on the coefficients defining the equation. The convergence result is applied to three physically realizable examples where the coefficients defining the Langevin equation for these examples grow unboundedly either at a boundary, such as a wall, and/or at the point at infinity. This unboundedness violates the assumptions of previous limit theorems in the literature. The main result of this paper proves convergence for such examples.

  13. Two-dimensional Langevin modeling of fission dynamics of the excited compound nuclei 188Pt, 227Pa and 251Es

    NASA Astrophysics Data System (ADS)

    Eslamizadeh, H.

    2016-02-01

    A stochastic approach based on one- and two-dimensional Langevin equations is applied to calculate the pre-scission neutron multiplicity, fission probability, anisotropy of fission fragment angular distribution, fission cross section and the evaporation cross section for the compound nuclei 188Pt, 227Pa and 251Es in an intermediate range of excitation energies. The chaos weighted wall and window friction formula are used in the Langevin equations. The elongation parameter, c, is used as the first dimension and projection of the total spin of the compound nucleus onto the symmetry axis, K, considered as the second dimension in Langevin dynamical calculations. A constant dissipation coefficient of K, γK = 0.077(MeV zs)-1/2, is used in two-dimensional calculations to reproduce the above mentioned experimental data. Comparison of the theoretical results of the pre-scission neutron multiplicity, fission probability, fission cross section and the evaporation cross section with the experimental data shows that the results of two-dimensional calculations are in better agreement with the experimental data. Furthermore, it is shown that the two-dimensional Langevin equations together with a dissipation coefficient of K, γK = 0.077(MeV zs)-1/2, can satisfactorily reproduce the anisotropy of fission fragment angular distribution for the heavy compound nucleus 251Es. However, a larger value of γK = 0.250(MeV zs)-1/2 is needed to reproduce the anisotropy of fission fragment angular distribution for the lighter compound nucleus 227Pa.

  14. Mapping the Monte Carlo scheme to Langevin dynamics: a Fokker-Planck approach.

    PubMed

    Cheng, X Z; Jalil, M B A; Lee, Hwee Kuan; Okabe, Yutaka

    2006-02-17

    We propose a general method of using the Fokker-Planck equation (FPE) to link the Monte Carlo (MC) and the Langevin micromagnetic schemes. We derive the drift and diffusion FPE terms corresponding to the MC method and show that it is analytically equivalent to the stochastic Landau-Lifshitz-Gilbert (LLG) equation of Langevin-based micromagnetics. Subsequent results such as the time-quantification factor for the Metropolis MC method can be rigorously derived from this mapping equivalence. The validity of the mapping is shown by the close numerical convergence between the MC method and the LLG equation for the case of a single magnetic particle as well as interacting arrays of particles. We also find that our Metropolis MC method is accurate for a large range of damping factors alpha, unlike previous time-quantified MC methods which break down at low alpha, where precessional motion dominates. PMID:16606044

  15. Mapping the Monte Carlo Scheme to Langevin Dynamics: A Fokker-Planck Approach

    NASA Astrophysics Data System (ADS)

    Cheng, X. Z.; Jalil, M. B.; Lee, Hwee Kuan; Okabe, Yutaka

    2006-02-01

    We propose a general method of using the Fokker-Planck equation (FPE) to link the Monte Carlo (MC) and the Langevin micromagnetic schemes. We derive the drift and diffusion FPE terms corresponding to the MC method and show that it is analytically equivalent to the stochastic Landau-Lifshitz-Gilbert (LLG) equation of Langevin-based micromagnetics. Subsequent results such as the time-quantification factor for the Metropolis MC method can be rigorously derived from this mapping equivalence. The validity of the mapping is shown by the close numerical convergence between the MC method and the LLG equation for the case of a single magnetic particle as well as interacting arrays of particles. We also find that our Metropolis MC method is accurate for a large range of damping factors α, unlike previous time-quantified MC methods which break down at low α, where precessional motion dominates.

  16. Molecular dynamics and analytical Langevin equation approach for the self-diffusion constant of an anisotropic fluid.

    PubMed

    Colmenares, Pedro J; López, Floralba; Olivares-Rivas, Wilmer

    2009-12-01

    We carried out a molecular-dynamics (MD) study of the self-diffusion tensor of a Lennard-Jones-type fluid, confined in a slit pore with attractive walls. We developed Bayesian equations, which modify the virtual layer sampling method proposed by Liu, Harder, and Berne (LHB) [P. Liu, E. Harder, and B. J. Berne, J. Phys. Chem. B 108, 6595 (2004)]. Additionally, we obtained an analytical solution for the corresponding nonhomogeneous Langevin equation. The expressions found for the mean-squared displacement in the layers contain naturally a modification due to the mean force in the transverse component in terms of the anisotropic diffusion constants and mean exit time. Instead of running a time consuming dual MD-Langevin simulation dynamics, as proposed by LHB, our expression was used to fit the MD data in the entire survival time interval not only for the parallel but also for the perpendicular direction. The only fitting parameter was the diffusion constant in each layer. PMID:20365134

  17. Molecular dynamics and analytical Langevin equation approach for the self-diffusion constant of an anisotropic fluid

    NASA Astrophysics Data System (ADS)

    Colmenares, Pedro J.; López, Floralba; Olivares-Rivas, Wilmer

    2009-12-01

    We carried out a molecular-dynamics (MD) study of the self-diffusion tensor of a Lennard-Jones-type fluid, confined in a slit pore with attractive walls. We developed Bayesian equations, which modify the virtual layer sampling method proposed by Liu, Harder, and Berne (LHB) [P. Liu, E. Harder, and B. J. Berne, J. Phys. Chem. B 108, 6595 (2004)]. Additionally, we obtained an analytical solution for the corresponding nonhomogeneous Langevin equation. The expressions found for the mean-squared displacement in the layers contain naturally a modification due to the mean force in the transverse component in terms of the anisotropic diffusion constants and mean exit time. Instead of running a time consuming dual MD-Langevin simulation dynamics, as proposed by LHB, our expression was used to fit the MD data in the entire survival time interval not only for the parallel but also for the perpendicular direction. The only fitting parameter was the diffusion constant in each layer.

  18. Efficient and Unbiased Sampling of Biomolecular Systems in the Canonical Ensemble: A Review of Self-Guided Langevin Dynamics

    PubMed Central

    Wu, Xiongwu; Damjanovic, Ana; Brooks, Bernard R.

    2013-01-01

    This review provides a comprehensive description of the self-guided Langevin dynamics (SGLD) and the self-guided molecular dynamics (SGMD) methods and their applications. Example systems are included to provide guidance on optimal application of these methods in simulation studies. SGMD/SGLD has enhanced ability to overcome energy barriers and accelerate rare events to affordable time scales. It has been demonstrated that with moderate parameters, SGLD can routinely cross energy barriers of 20 kT at a rate that molecular dynamics (MD) or Langevin dynamics (LD) crosses 10 kT barriers. The core of these methods is the use of local averages of forces and momenta in a direct manner that can preserve the canonical ensemble. The use of such local averages results in methods where low frequency motion “borrows” energy from high frequency degrees of freedom when a barrier is approached and then returns that excess energy after a barrier is crossed. This self-guiding effect also results in an accelerated diffusion to enhance conformational sampling efficiency. The resulting ensemble with SGLD deviates in a small way from the canonical ensemble, and that deviation can be corrected with either an on-the-fly or a post processing reweighting procedure that provides an excellent canonical ensemble for systems with a limited number of accelerated degrees of freedom. Since reweighting procedures are generally not size extensive, a newer method, SGLDfp, uses local averages of both momenta and forces to preserve the ensemble without reweighting. The SGLDfp approach is size extensive and can be used to accelerate low frequency motion in large systems, or in systems with explicit solvent where solvent diffusion is also to be enhanced. Since these methods are direct and straightforward, they can be used in conjunction with many other sampling methods or free energy methods by simply replacing the integration of degrees of freedom that are normally sampled by MD or LD. PMID:23913991

  19. Combined Néel and Brown rotational Langevin dynamics in magnetic particle imaging, sensing, and therapy

    SciTech Connect

    Reeves, Daniel B.; Weaver, John B.

    2015-11-30

    Magnetic nanoparticles have been studied intensely because of their possible uses in biomedical applications. Biosensing using the rotational freedom of particles has been used to detect biomarkers for cancer, hyperthermia therapy has been used to treat tumors, and magnetic particle imaging is a promising new imaging modality that can spatially resolve the concentration of nanoparticles. There are two mechanisms by which the magnetization of a nanoparticle can rotate, a fact that poses a challenge for applications that rely on precisely one mechanism. The challenge is exacerbated by the high sensitivity of the dominant mechanism to applied fields. Here, we demonstrate stochastic Langevin equation simulations for the combined rotation in magnetic nanoparticles exposed to oscillating applied fields typical to these applications to both highlight the existing relevant theory and quantify which mechanism should occur in various parameter ranges.

  20. Force-momentum-based self-guided Langevin dynamics: A rapid sampling method that approaches the canonical ensemble

    NASA Astrophysics Data System (ADS)

    Wu, Xiongwu; Brooks, Bernard R.

    2011-11-01

    The self-guided Langevin dynamics (SGLD) is a method to accelerate conformational searching. This method is unique in the way that it selectively enhances and suppresses molecular motions based on their frequency to accelerate conformational searching without modifying energy surfaces or raising temperatures. It has been applied to studies of many long time scale events, such as protein folding. Recent progress in the understanding of the conformational distribution in SGLD simulations makes SGLD also an accurate method for quantitative studies. The SGLD partition function provides a way to convert the SGLD conformational distribution to the canonical ensemble distribution and to calculate ensemble average properties through reweighting. Based on the SGLD partition function, this work presents a force-momentum-based self-guided Langevin dynamics (SGLDfp) simulation method to directly sample the canonical ensemble. This method includes interaction forces in its guiding force to compensate the perturbation caused by the momentum-based guiding force so that it can approximately sample the canonical ensemble. Using several example systems, we demonstrate that SGLDfp simulations can approximately maintain the canonical ensemble distribution and significantly accelerate conformational searching. With optimal parameters, SGLDfp and SGLD simulations can cross energy barriers of more than 15 kT and 20 kT, respectively, at similar rates for LD simulations to cross energy barriers of 10 kT. The SGLDfp method is size extensive and works well for large systems. For studies where preserving accessible conformational space is critical, such as free energy calculations and protein folding studies, SGLDfp is an efficient approach to search and sample the conformational space.

  1. Dynamics of Lane Formation in Driven Binary Complex Plasmas

    SciTech Connect

    Suetterlin, K. R.; Ivlev, A. V.; Raeth, C.; Thomas, H. M.; Rubin-Zuzic, M.; Morfill, G. E.; Wysocki, A.; Loewen, H.; Goedheer, W. J.; Fortov, V. E.; Lipaev, A. M.; Molotkov, V. I.; Petrov, O. F.

    2009-02-27

    The dynamical onset of lane formation is studied in experiments with binary complex plasmas under microgravity conditions. Small microparticles are driven and penetrate into a cloud of big particles, revealing a strong tendency towards lane formation. The observed time-resolved lane-formation process is in good agreement with computer simulations of a binary Yukawa model with Langevin dynamics. The laning is quantified in terms of the anisotropic scaling index, leading to a universal order parameter for driven systems.

  2. Models for microtubule cargo transport coupling the Langevin equation to stochastic stepping motor dynamics: Caring about fluctuations

    NASA Astrophysics Data System (ADS)

    Bouzat, Sebastián

    2016-01-01

    One-dimensional models coupling a Langevin equation for the cargo position to stochastic stepping dynamics for the motors constitute a relevant framework for analyzing multiple-motor microtubule transport. In this work we explore the consistence of these models focusing on the effects of the thermal noise. We study how to define consistent stepping and detachment rates for the motors as functions of the local forces acting on them in such a way that the cargo velocity and run-time match previously specified functions of the external load, which are set on the base of experimental results. We show that due to the influence of the thermal fluctuations this is not a trivial problem, even for the single-motor case. As a solution, we propose a motor stepping dynamics which considers memory on the motor force. This model leads to better results for single-motor transport than the approaches previously considered in the literature. Moreover, it gives a much better prediction for the stall force of the two-motor case, highly compatible with the experimental findings. We also analyze the fast fluctuations of the cargo position and the influence of the viscosity, comparing the proposed model to the standard one, and we show how the differences on the single-motor dynamics propagate to the multiple motor situations. Finally, we find that the one-dimensional character of the models impede an appropriate description of the fast fluctuations of the cargo position at small loads. We show how this problem can be solved by considering two-dimensional models.

  3. Models for microtubule cargo transport coupling the Langevin equation to stochastic stepping motor dynamics: Caring about fluctuations.

    PubMed

    Bouzat, Sebastián

    2016-01-01

    One-dimensional models coupling a Langevin equation for the cargo position to stochastic stepping dynamics for the motors constitute a relevant framework for analyzing multiple-motor microtubule transport. In this work we explore the consistence of these models focusing on the effects of the thermal noise. We study how to define consistent stepping and detachment rates for the motors as functions of the local forces acting on them in such a way that the cargo velocity and run-time match previously specified functions of the external load, which are set on the base of experimental results. We show that due to the influence of the thermal fluctuations this is not a trivial problem, even for the single-motor case. As a solution, we propose a motor stepping dynamics which considers memory on the motor force. This model leads to better results for single-motor transport than the approaches previously considered in the literature. Moreover, it gives a much better prediction for the stall force of the two-motor case, highly compatible with the experimental findings. We also analyze the fast fluctuations of the cargo position and the influence of the viscosity, comparing the proposed model to the standard one, and we show how the differences on the single-motor dynamics propagate to the multiple motor situations. Finally, we find that the one-dimensional character of the models impede an appropriate description of the fast fluctuations of the cargo position at small loads. We show how this problem can be solved by considering two-dimensional models. PMID:26871095

  4. The generalized Langevin equation revisited: Analytical expressions for the persistence dynamics of a viscous fluid under a time dependent external force

    NASA Astrophysics Data System (ADS)

    Olivares-Rivas, Wilmer; Colmenares, Pedro J.

    2016-09-01

    The non-static generalized Langevin equation and its corresponding Fokker-Planck equation for the position of a viscous fluid particle were solved in closed form for a time dependent external force. Its solution for a constant external force was obtained analytically. The non-Markovian stochastic differential equation, associated to the dynamics of the position under a colored noise, was then applied to the description of the dynamics and persistence time of particles constrained within absorbing barriers. Comparisons with molecular dynamics were very satisfactory.

  5. Expectation-maximization of the potential of mean force and diffusion coefficient in Langevin dynamics from single molecule FRET data photon by photon.

    PubMed

    Haas, Kevin R; Yang, Haw; Chu, Jhih-Wei

    2013-12-12

    The dynamics of a protein along a well-defined coordinate can be formally projected onto the form of an overdamped Lagevin equation. Here, we present a comprehensive statistical-learning framework for simultaneously quantifying the deterministic force (the potential of mean force, PMF) and the stochastic force (characterized by the diffusion coefficient, D) from single-molecule Förster-type resonance energy transfer (smFRET) experiments. The likelihood functional of the Langevin parameters, PMF and D, is expressed by a path integral of the latent smFRET distance that follows Langevin dynamics and realized by the donor and the acceptor photon emissions. The solution is made possible by an eigen decomposition of the time-symmetrized form of the corresponding Fokker-Planck equation coupled with photon statistics. To extract the Langevin parameters from photon arrival time data, we advance the expectation-maximization algorithm in statistical learning, originally developed for and mostly used in discrete-state systems, to a general form in the continuous space that allows for a variational calculus on the continuous PMF function. We also introduce the regularization of the solution space in this Bayesian inference based on a maximum trajectory-entropy principle. We use a highly nontrivial example with realistically simulated smFRET data to illustrate the application of this new method. PMID:23937300

  6. Backbone Relaxation Coupled to the Ionization of Internal Groups in Proteins: A Self-Guided Langevin Dynamics Study

    PubMed Central

    Damjanović, Ana; Wu, Xiongwu; García-Moreno E., Bertrand; Brooks, Bernard R.

    2008-01-01

    Pathways of structural relaxation triggered by ionization of internal groups in staphylococcal nuclease (SNase) were studied through multiple self-guided Langevin dynamics (SGLD) simulations. Circular dichroism, steady-state Trp fluorescence, and nuclear magnetic resonance spectroscopy have shown previously that variants of SNase with internal Glu, Asp, and Lys at positions 66 or 92, and Arg at position 66, exhibit local reorganization or global unfolding when the internal ionizable group is charged. Except for Arg-66, these internal ionizable groups have unusual pKa values and are neutral at physiological pH. The structural trends observed in the simulations are in general agreement with experimental observations. The I92D variant, which unfolds globally upon ionization of Asp-92, in simulations often exhibits extensive hydration of the protein core, and sometimes also significant perturbations of the β-barrel. In the crystal structure of the V66R variant, the β1 strand from the β-barrel is domain-swapped; in the simulations, the β1 strand is sometimes partially released. The V66K variant, which in solutions shows reorganization of six residues at the C-terminus of helix α1 and perturbations in the β-barrel structure, exhibits fraying of three residues of helix α1 in one simulation, and perturbations and partial unfolding of three β-strands in a few other simulations. In sharp contrast, very small structural changes were observed in simulations of the wild-type protein. The simulations indicate that charging of internal groups frequently triggers penetration of water into the protein interior. The pKa values of Asp-92 and Arg-66 calculated with continuum methods on SGLD-relaxed structures reached the normal values in most simulations. Detailed analysis of accuracy and performance of SGLD demonstrates that SGLD outperforms LD in sampling of alternative protein conformations without loss of the accuracy and level of detail characteristic of regular LD. PMID

  7. Langevin spin dynamics based on ab initio calculations: numerical schemes and applications.

    PubMed

    Rózsa, L; Udvardi, L; Szunyogh, L

    2014-05-28

    A method is proposed to study the finite-temperature behaviour of small magnetic clusters based on solving the stochastic Landau-Lifshitz-Gilbert equations, where the effective magnetic field is calculated directly during the solution of the dynamical equations from first principles instead of relying on an effective spin Hamiltonian. Different numerical solvers are discussed in the case of a one-dimensional Heisenberg chain with nearest-neighbour interactions. We performed detailed investigations for a monatomic chain of ten Co atoms on top of a Au(0 0 1) surface. We found a spiral-like ground state of the spins due to Dzyaloshinsky-Moriya interactions, while the finite-temperature magnetic behaviour of the system was well described by a nearest-neighbour Heisenberg model including easy-axis anisotropy. PMID:24806308

  8. Computing Freidlin's Cycles for the Overdamped Langevin Dynamics. Application to the Lennard-Jones-38 Cluster

    NASA Astrophysics Data System (ADS)

    Cameron, M. K.

    2013-08-01

    The large time behavior of a stochastic system with infinitesimally small noise can be described in terms of Freidlin's cycles. We show that if the system is gradient and the potential satisfies certain non-restrictive conditions, the hierarchy of cycles has a structure of a full binary tree, and each cycle is exited via the lowest saddle adjacent to it. Exploiting this property, we propose an algorithm for computing the asymptotic zero-temperature path and building a hierarchy of Freidlin's cycles associated with the transition process between two given local equilibria. This algorithm is suitable for systems with a complex potential energy landscape with numerous minima. We apply it to find the asymptotic zero-temperature path and Freidlin's cycles involved into the transition process between the two lowest minima of the Lennard-Jones cluster of 38 atoms. D. Wales's stochastic network of minima and transition states of this cluster is used as an input.

  9. Molecular Dynamics with the United-Residue Model of Polypeptide Chains. II. Langevin and Berendsen-Bath Dynamics and Tests on Model α-Helical Systems

    PubMed Central

    Khalili, Mey; Liwo, Adam; Jagielska, Anna; Scheraga, Harold A.

    2008-01-01

    The implementation of molecular dynamics (MD) with our physics-based protein united-residue (UNRES) force field, described in the accompanying paper (Khalili et al. J. Phys. Chem. B 2005, 109, 13785), was extended to Langevin dynamics. The equations of motion are integrated by using a simplified stochastic velocity Verlet algorithm. To compare the results to those with all-atom simulations with implicit solvent in which no explicit stochastic and friction forces are present, we alternatively introduced the Berendsen thermostat. Test simulations on the Ala10 polypeptide demonstrated that the average kinetic energy is stable with about a 5 fs time step. To determine the correspondence between the UNRES time step and the time step of all-atom molecular dynamics, all-atom simulations with the AMBER 99 force field and explicit solvent and also with implicit solvent taken into account within the framework of the generalized Born/surface area (GBSA) model were carried out on the unblocked Ala10 polypeptide. We found that the UNRES time scale is 4 times longer than that of all-atom MD simulations because the degrees of freedom corresponding to the fastest motions in UNRES are averaged out. When the reduction of the computational cost for evaluation of the UNRES energy function is also taken into account, UNRES (with hydration included implicitly in the side chain–side chain interaction potential) offers about at least a 4000-fold speed up of computations relative to all-atom simulations with explicit solvent and at least a 65-fold speed up relative to all-atom simulations with implicit solvent. To carry out an initial full-blown test of the UNRES/MD approach, we ran Berendsen-bath and Langevin dynamics simulations of the 46-residue B-domain of staphylococcal protein A. We were able to determine the folding temperature at which all trajectories converged to nativelike structures with both approaches. For comparison, we carried out ab initio folding simulations of this

  10. Gauge cooling for the singular-drift problem in the complex Langevin method — a test in Random Matrix Theory for finite density QCD

    NASA Astrophysics Data System (ADS)

    Nagata, Keitaro; Nishimura, Jun; Shimasaki, Shinji

    2016-07-01

    Recently, the complex Langevin method has been applied successfully to finite density QCD either in the deconfinement phase or in the heavy dense limit with the aid of a new technique called the gauge cooling. In the confinement phase with light quarks, however, convergence to wrong limits occurs due to the singularity in the drift term caused by small eigenvalues of the Dirac operator including the mass term. We propose that this singular-drift problem should also be overcome by the gauge cooling with different criteria for choosing the complexified gauge transformation. The idea is tested in chiral Random Matrix Theory for finite density QCD, where exact results are reproduced at zero temperature with light quarks. It is shown that the gauge cooling indeed changes drastically the eigenvalue distribution of the Dirac operator measured during the Langevin process. Despite its non-holomorphic nature, this eigenvalue distribution has a universal diverging behavior at the origin in the chiral limit due to a generalized Banks-Casher relation as we confirm explicitly.

  11. Heuristic dynamic complexity coding

    NASA Astrophysics Data System (ADS)

    Škorupa, Jozef; Slowack, Jürgen; Mys, Stefaan; Lambert, Peter; Van de Walle, Rik

    2008-04-01

    Distributed video coding is a new video coding paradigm that shifts the computational intensive motion estimation from encoder to decoder. This results in a lightweight encoder and a complex decoder, as opposed to the predictive video coding scheme (e.g., MPEG-X and H.26X) with a complex encoder and a lightweight decoder. Both schemas, however, do not have the ability to adapt to varying complexity constraints imposed by encoder and decoder, which is an essential ability for applications targeting a wide range of devices with different complexity constraints or applications with temporary variable complexity constraints. Moreover, the effect of complexity adaptation on the overall compression performance is of great importance and has not yet been investigated. To address this need, we have developed a video coding system with the possibility to adapt itself to complexity constraints by dynamically sharing the motion estimation computations between both components. On this system we have studied the effect of the complexity distribution on the compression performance. This paper describes how motion estimation can be shared using heuristic dynamic complexity and how distribution of complexity affects the overall compression performance of the system. The results show that the complexity can indeed be shared between encoder and decoder in an efficient way at acceptable rate-distortion performance.

  12. Dynamic and topological complexity

    NASA Astrophysics Data System (ADS)

    Turalska, Malgorzata; Geneston, Elvis; Grigolini, Paolo

    2010-03-01

    Cooperative phenomena in complex networks are expected to display unusual characteristics, associated with the peculiar topology of these systems. In this context we study networks of interacting stochastic two-state units as a model of cooperative decision making. Each unit in isolation generates a Poisson process with rate g. We show that when the cooperation is introduced, the decision-making process becomes intermittent. The decision-time distribution density characterized by inverse power-law behavior is defined as a dynamic complexity. Further, the onset of intermittency, expressed in terms of the coupling parameter K, is used as a measure of dynamic efficiency of investigated topologies. We find that the dynamic complexity emerges from regular and small-world topologies. In contrast, both random and scale-free networks correspond to fast transition into exponential decision-time distribution. This property is accompanied by high dynamic efficiency of the decision-making process. Our results indicate that complex dynamical processes occurring on networks could be related to relatively simple topologies.

  13. Elastic Vibrations in the Photosynthetic Bacterial Reaction Center Coupled to the Primary Charge Separation: Implications from Molecular Dynamics Simulations and Stochastic Langevin Approach.

    PubMed

    Milanovsky, Georgy E; Shuvalov, Vladimir A; Semenov, Alexey Yu; Cherepanov, Dmitry A

    2015-10-29

    Primary electron transfer reactions in the bacterial reaction center are difficult for theoretical explication: the reaction kinetics, almost unalterable over a wide range of temperature and free energy changes, revealed oscillatory features observed initially by Shuvalov and coauthors (1997, 2002). Here the reaction mechanism was studied by molecular dynamics and analyzed within a phenomenological Langevin approach. The spectral function of polarization around the bacteriochlorophyll special pair PLPM and the dielectric response upon the formation of PL(+)PM(-) dipole within the special pair were calculated. The system response was approximated by Langevin oscillators; the respective frequencies, friction, and energy coupling coefficients were determined. The protein dynamics around PL and PM were distinctly asymmetric. The polarization around PL included slow modes with the frequency 30-80 cm(-1) and the total amplitude of 130 mV. Two main low-frequency modes of protein response around PM had frequencies of 95 and 155 cm(-1) and the total amplitude of 30 mV. In addition, a slowly damping mode with the frequency of 118 cm(-1) and the damping time >1.1 ps was coupled to the formation of PL(+)PM(-) dipole. It was attributed to elastic vibrations of α-helices in the vicinity of PLPM. The proposed trapping of P excitation energy in the form of the elastic vibrations can rationalize the observed properties of the primary electron transfer reactions, namely, the unusual temperature and ΔG dependences, the oscillating phenomena in kinetics, and the asymmetry of the charge separation reactions. PMID:26148224

  14. A hybrid formalism combining fluctuating hydrodynamics and generalized Langevin dynamics for the simulation of nanoparticle thermal motion in an incompressible fluid medium

    PubMed Central

    Uma, B.; Eckmann, D.M.; Ayyaswamy, P.S.; Radhakrishnan, R.

    2012-01-01

    A novel hybrid scheme based on Markovian fluctuating hydrodynamics of the fluid and a non-Markovian Langevin dynamics with the Ornstein-Uhlenbeck noise perturbing the translational and rotational equations of motion of the nanoparticle is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian fluid medium. A direct numerical simulation adopting an arbitrary Lagrangian-Eulerian (ALE) based finite element method (FEM) is employed in simulating the thermal motion of a particle suspended in the fluid confined in a cylindrical vessel. The results for thermal equilibrium between the particle and the fluid are validated by comparing the numerically predicted temperature of the nanoparticle with that obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation function (VACF) and mean squared displacement (MSD) with well-known analytical results. For nanoparticle motion in an incompressible fluid, the fluctuating hydrodynamics approach resolves the hydrodynamics correctly but does not impose the correct equipartition of energy based on the nanoparticle mass because of the added mass of the displaced fluid. In contrast, the Langevin approach with an appropriate memory is able to show the correct equipartition of energy, but not the correct short- and long-time hydrodynamic correlations. Using our hybrid approach presented here, we show for the first time, that we can simultaneously satisfy the equipartition theorem and the (short- and long-time) hydrodynamic correlations. In effect, this results in a thermostat that also simultaneously preserves the true hydrodynamic correlations. The significance of this result is that our new algorithm provides a robust computational approach to explore nanoparticle motion in arbitrary geometries and flow fields, while simultaneously enabling us to study carrier adhesion mediated by biological reactions (receptor

  15. Modeling surface motion effects in N2 dissociation on W(110): Ab initio molecular dynamics calculations and generalized Langevin oscillator model

    NASA Astrophysics Data System (ADS)

    Nattino, Francesco; Galparsoro, Oihana; Costanzo, Francesca; Díez Muiño, Ricardo; Alducin, Maite; Kroes, Geert-Jan

    2016-06-01

    Accurately modeling surface temperature and surface motion effects is necessary to study molecule-surface reactions in which the energy dissipation to surface phonons can largely affect the observables of interest. We present here a critical comparison of two methods that allow to model such effects, namely, the ab initio molecular dynamics (AIMD) method and the generalized Langevin oscillator (GLO) model, using the dissociation of N2 on W(110) as a benchmark. AIMD is highly accurate as the surface atoms are explicitly part of the dynamics, but this advantage comes with a large computational cost. The GLO model is much more computationally convenient, but accounts for lattice motion effects in a very approximate way. Results show that, despite its simplicity, the GLO model is able to capture the physics of the system to a large extent, returning dissociation probabilities which are in better agreement with AIMD than static-surface results. Furthermore, the GLO model and the AIMD method predict very similar energy transfer to the lattice degrees of freedom in the non-reactive events, and similar dissociation dynamics.

  16. Simplified simulation of Boltzmann-Langevin equation

    SciTech Connect

    Ayik, S.; Randrup, J.

    1994-06-01

    We briefly recall the Boltzmann-Langevin model of nuclear dynamics. We then summarize recent progress in deriving approximate analytical expressions for the associated transport coefficients and describe a numerical method for simulating the stochastic evolution of the phase-space density.

  17. Emergent complex neural dynamics

    NASA Astrophysics Data System (ADS)

    Chialvo, Dante R.

    2010-10-01

    A large repertoire of spatiotemporal activity patterns in the brain is the basis for adaptive behaviour. Understanding the mechanism by which the brain's hundred billion neurons and hundred trillion synapses manage to produce such a range of cortical configurations in a flexible manner remains a fundamental problem in neuroscience. One plausible solution is the involvement of universal mechanisms of emergent complex phenomena evident in dynamical systems poised near a critical point of a second-order phase transition. We review recent theoretical and empirical results supporting the notion that the brain is naturally poised near criticality, as well as its implications for better understanding of the brain.

  18. Beyond complex Langevin equations: from simple examples to positive representation of Feynman path integrals directly in the Minkowski time

    NASA Astrophysics Data System (ADS)

    Wosiek, Jacek

    2016-04-01

    A positive representation for an arbitrary complex, gaussian weight is derived and used to construct a statistical formulation of gaussian path integrals directly in the Minkowski time. The positivity of Minkowski weights is achieved by doubling the number of real variables. The continuum limit of the new representation exists only if some of the additional couplings tend to infinity and are tuned in a specific way. The construction is then successfully applied to three quantum mechanical examples including a particle in a constant magnetic field — a simplest prototype of a Wilson line. Further generalizations are shortly discussed and an intriguing interpretation of new variables is alluded to.

  19. Probability Density Function Method for Langevin Equations with Colored Noise

    SciTech Connect

    Wang, Peng; Tartakovsky, Alexandre M.; Tartakovsky, Daniel M.

    2013-04-05

    We present a novel method to derive closed-form, computable PDF equations for Langevin systems with colored noise. The derived equations govern the dynamics of joint or marginal probability density functions (PDFs) of state variables, and rely on a so-called Large-Eddy-Diffusivity (LED) closure. We demonstrate the accuracy of the proposed PDF method for linear and nonlinear Langevin equations, describing the classical Brownian displacement and dispersion in porous media.

  20. Managing Complex Dynamical Systems

    ERIC Educational Resources Information Center

    Cox, John C.; Webster, Robert L.; Curry, Jeanie A.; Hammond, Kevin L.

    2011-01-01

    Management commonly engages in a variety of research designed to provide insight into the motivation and relationships of individuals, departments, organizations, etc. This paper demonstrates how the application of concepts associated with the analysis of complex systems applied to such data sets can yield enhanced insights for managerial action.

  1. Variance Reduction Using Nonreversible Langevin Samplers

    NASA Astrophysics Data System (ADS)

    Duncan, A. B.; Lelièvre, T.; Pavliotis, G. A.

    2016-05-01

    A standard approach to computing expectations with respect to a given target measure is to introduce an overdamped Langevin equation which is reversible with respect to the target distribution, and to approximate the expectation by a time-averaging estimator. As has been noted in recent papers [30, 37, 61, 72], introducing an appropriately chosen nonreversible component to the dynamics is beneficial, both in terms of reducing the asymptotic variance and of speeding up convergence to the target distribution. In this paper we present a detailed study of the dependence of the asymptotic variance on the deviation from reversibility. Our theoretical findings are supported by numerical simulations.

  2. Synchronization in complex dynamical networks coupled with complex chaotic system

    NASA Astrophysics Data System (ADS)

    Wei, Qiang; Xie, Cheng-Jun; Wang, Bo

    2015-11-01

    This paper investigates synchronization in complex dynamical networks with time delay and perturbation. The node of complex dynamical networks is composed of complex chaotic system. A complex feedback controller is designed to realize different component of complex state variable synchronize up to different scaling complex function when complex dynamical networks realize synchronization. The synchronization scaling function is changed from real field to complex field. Synchronization in complex dynamical networks with constant delay and time-varying coupling delay are investigated, respectively. Numerical simulations show the effectiveness of the proposed method.

  3. Experimenting with Langevin lattice QCD

    SciTech Connect

    Gavai, R.V.; Potvin, J.; Sanielevici, S.

    1987-05-01

    We report on the status of our investigations of the effects of systematic errors upon the practical merits of Langevin updating in full lattice QCD. We formulate some rules for the safe use of this updating procedure and some observations on problems which may be common to all approximate fermion algorithms.

  4. Modeling Wildfire Incident Complexity Dynamics

    PubMed Central

    Thompson, Matthew P.

    2013-01-01

    Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014

  5. Complex dynamics of text analysis

    NASA Astrophysics Data System (ADS)

    Ke, Xiaohua; Zeng, Yongqiang; Ma, Qinghua; Zhu, Lin

    2014-12-01

    This paper presents a novel method for the analysis of nonlinear text quality in Chinese language. Texts produced by university students in China were represented as scale-free networks (word adjacency model), from which typical network features such as the in/outdegree, clustering coefficient and network dynamics were obtained. The method integrates the classical concepts of network feature representation and text quality series variation. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the network features. The results reveal that complex network features of different text qualities can be clearly revealed and applied to potential applications in other instances of text analysis.

  6. Critical exponent of the fractional Langevin equation.

    PubMed

    Burov, S; Barkai, E

    2008-02-22

    We investigate the dynamical phase diagram of the fractional Langevin equation and show that critical exponents mark dynamical transitions in the behavior of the system. For a free and harmonically bound particle the critical exponent alpha(c)=0.402+/-0.002 marks a transition to a nonmonotonic underdamped phase. The critical exponent alpha(R)=0.441... marks a transition to a resonance phase, when an external oscillating field drives the system. Physically, we explain these behaviors using a cage effect, where the medium induces an elastic type of friction. Phase diagrams describing the underdamped, the overdamped and critical frequencies of the fractional oscillator, recently used to model single protein experiments, show behaviors vastly different from normal. PMID:18352535

  7. Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

    NASA Astrophysics Data System (ADS)

    Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

    2016-03-01

    We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

  8. Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.

    PubMed

    Arampatzis, Georgios; Katsoulakis, Markos A; Rey-Bellet, Luc

    2016-03-14

    We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications. PMID:26979681

  9. Dynamic and interacting complex networks

    NASA Astrophysics Data System (ADS)

    Dickison, Mark E.

    This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

  10. Multidimensional treatment of stochastic solvent dynamics in photoinduced proton-coupled electron transfer processes: sequential, concerted, and complex branching mechanisms.

    PubMed

    Soudackov, Alexander V; Hazra, Anirban; Hammes-Schiffer, Sharon

    2011-10-14

    A theoretical approach for the multidimensional treatment of photoinduced proton-coupled electron transfer (PCET) processes in solution is presented. This methodology is based on the multistate continuum theory with an arbitrary number of diabatic electronic states representing the relevant charge distributions in a general PCET system. The active electrons and transferring proton(s) are treated quantum mechanically, and the electron-proton vibronic free energy surfaces are represented as functions of multiple scalar solvent coordinates corresponding to the single electron and proton transfer reactions involved in the PCET process. A dynamical formulation of the dielectric continuum theory is used to derive a set of coupled generalized Langevin equations of motion describing the time evolution of these collective solvent coordinates. The parameters in the Langevin equations depend on the solvent properties, such as the dielectric constants, relaxation time, and molecular moment of inertia, as well as the solute properties. The dynamics of selected intramolecular nuclear coordinates, such as the proton donor-acceptor distance or a torsional angle within the PCET complex, may also be included in this formulation. A surface hopping method in conjunction with the Langevin equations of motion is used to simulate the nonadiabatic dynamics on the multidimensional electron-proton vibronic free energy surfaces following photoexcitation. This theoretical treatment enables the description of both sequential and concerted mechanisms, as well as more complex processes involving a combination of these mechanisms. The application of this methodology to a series of model systems corresponding to collinear and orthogonal PCET illustrates fundamental aspects of these different mechanisms and elucidates the significance of proton vibrational relaxation and nonequilibrium solvent dynamics. PMID:22010706

  11. Cognitive dynamics: complexity and creativity

    NASA Astrophysics Data System (ADS)

    Tito Arecchi, F.

    2007-05-01

    A scientific problem described within a given code is mapped by a corresponding computational problem. We call (algorithmic) complexity the bit length of the shortest instruction which solves the problem. Deterministic chaos in general affects a dynamical system making the corresponding problem experimentally and computationally heavy, since one must reset the initial conditions at a rate higher than that of information loss (Kolmogorov entropy). One can control chaos by adding to the system new degrees of freedom (information swapping: information lost by chaos is replaced by that arising from the new degrees of freedom). This implies a change of code, or a new augmented model. Within a single code, changing hypotheses is equivalent to fixing different sets of control parameters, each with a different a-priori probability, to be then confirmed and transformed to an a-posteriori probability via Bayes theorem. Sequential application of Bayes rule is nothing else than the Darwinian strategy in evolutionary biology. The sequence is a steepest ascent algorithm, which stops once maximum probability has been reached. At this point the hypothesis exploration stops. By changing code (and hence the set of relevant variables) one can start again to formulate new classes of hypotheses. We call creativity the action of code changing, which is guided by hints not formalized within the previous code, whence not accessible to a computer. We call semantic complexity the number of different scientific codes, or models, that describe a situation. It is however a fuzzy concept, in so far as this number changes due to interaction of the operator with the context. These considerations are illustrated with reference to a cognitive task, starting from synchronization of neuron arrays in a perceptual area and tracing the putative path towards a model building. Since this is a report on work in progress, we skip technicalities in order to stress the gist of the question, and provide

  12. Bistable systems with stochastic noise: virtues and limits of effective one-dimensional Langevin equations

    NASA Astrophysics Data System (ADS)

    Lucarini, V.; Faranda, D.; Willeit, M.

    2012-01-01

    The understanding of the statistical properties and of the dynamics of multistable systems is gaining more and more importance in a vast variety of scientific fields. This is especially relevant for the investigation of the tipping points of complex systems. Sometimes, in order to understand the time series of given observables exhibiting bimodal distributions, simple one-dimensional Langevin models are fitted to reproduce the observed statistical properties, and used to investing-ate the projected dynamics of the observable. This is of great relevance for studying potential catastrophic changes in the properties of the underlying system or resonant behaviours like those related to stochastic resonance-like mechanisms. In this paper, we propose a framework for encasing this kind of studies, using simple box models of the oceanic circulation and choosing as observable the strength of the thermohaline circulation. We study the statistical properties of the transitions between the two modes of operation of the thermohaline circulation under symmetric boundary forcings and test their agreement with simplified one-dimensional phenomenological theories. We extend our analysis to include stochastic resonance-like amplification processes. We conclude that fitted one-dimensional Langevin models, when closely scrutinised, may result to be more ad-hoc than they seem, lacking robustness and/or well-posedness. They should be treated with care, more as an empiric descriptive tool than as methodology with predictive power.

  13. Aging and the complexity of cardiovascular dynamics

    NASA Technical Reports Server (NTRS)

    Kaplan, D. T.; Furman, M. I.; Pincus, S. M.; Ryan, S. M.; Lipsitz, L. A.; Goldberger, A. L.

    1991-01-01

    Biomedical signals often vary in a complex and irregular manner. Analysis of variability in such signals generally does not address directly their complexity, and so may miss potentially useful information. We analyze the complexity of heart rate and beat-to-beat blood pressure using two methods motivated by nonlinear dynamics (chaos theory). A comparison of a group of healthy elderly subjects with healthy young adults indicates that the complexity of cardiovascular dynamics is reduced with aging. This suggests that complexity of variability may be a useful physiological marker.

  14. Aging and the complexity of cardiovascular dynamics.

    PubMed Central

    Kaplan, D T; Furman, M I; Pincus, S M; Ryan, S M; Lipsitz, L A; Goldberger, A L

    1991-01-01

    Biomedical signals often vary in a complex and irregular manner. Analysis of variability in such signals generally does not address directly their complexity, and so may miss potentially useful information. We analyze the complexity of heart rate and beat-to-beat blood pressure using two methods motivated by nonlinear dynamics (chaos theory). A comparison of a group of healthy elderly subjects with healthy young adults indicates that the complexity of cardiovascular dynamics is reduced with aging. This suggests that complexity of variability may be a useful physiological marker. PMID:2065195

  15. Complex dynamics in polymer nanocomposites

    NASA Astrophysics Data System (ADS)

    Srivastava, S.; Kandar, A. K.; Basu, J. K.; Mukhopadhyay, M. K.; Lurio, L. B.; Narayanan, S.; Sinha, S. K.

    2009-02-01

    Polymer nanocomposites offer the potential to create a new type of hybrid material with unique thermal, optical, or electrical properties. Understanding their structure, phase behavior, and dynamics is crucial for realizing such potentials. In this work we provide an experimental insight into the dynamics of such composites in terms of the temperature, wave vector, and volume fraction of nanoparticles, using multispeckle synchrotron x-ray photon correlation spectroscopy measurements on gold nanoparticles embedded in polymethylmethacrylate. Detailed analysis of the intermediate scattering functions reveals possible existence of an intrinsic length scale for dynamic heterogeneity in polymer nanocomposites similar to that seen in other soft materials like colloidal gels and glasses.

  16. Dynamics on Complex Networks and Applications

    NASA Astrophysics Data System (ADS)

    Motter, Adilson E.; Matías, Manuel A.; Kurths, Jürgen; Ott, Edward

    2006-12-01

    At the eight-year anniversary of Watts and Strogatz’s work on the collective dynamics of small-world networks and seven years after Barabási and Albert’s discovery of scale-free networks, the area of dynamical processes on complex networks is at the forefront of the current research on nonlinear dynamics and complex systems. This volume brings together a selection of original contributions in complementary topics of statistical physics, nonlinear dynamics and biological sciences, and is expected to provide the reader with a comprehensive up-to-date representation of this rapidly developing area.

  17. Solvation dynamics in a protein surfactant complex

    NASA Astrophysics Data System (ADS)

    Dutta, Partha; Sen, Pratik; Halder, Arnab; Mukherjee, Saptarshi; Sen, Sobhan; Bhattacharyya, Kankan

    2003-08-01

    Solvation dynamics in the denatured state of a protein, lysozyme (denatured by sodium dodecyl sulfate, SDS) is markedly slower than that in the native state. For coumarin 153 bound to lysozyme, the average solvation time, < τs> is 330 ps. In the lysozyme-SDS complex, the solvation dynamics is markedly slower with < τs>=7250 ps. On addition of dithiothreitol (DTT) to the lysozyme-SDS complex, when the di-sulfide bonds are destroyed, < τs> is found to be 1140 ps. The slow dynamics in the denatured protein is attributed to the polymer chain dynamics and the exchange of bound and free water molecules.

  18. Cascade dynamics of complex propagation

    NASA Astrophysics Data System (ADS)

    Centola, Damon; Eguíluz, Víctor M.; Macy, Michael W.

    2007-01-01

    Random links between otherwise distant nodes can greatly facilitate the propagation of disease or information, provided contagion can be transmitted by a single active node. However, we show that when the propagation requires simultaneous exposure to multiple sources of activation, called complex propagation, the effect of random links can be just the opposite; it can make the propagation more difficult to achieve. We numerically calculate critical points for a threshold model using several classes of complex networks, including an empirical social network. We also provide an estimation of the critical values in terms of vulnerable nodes.

  19. Complex Dynamics of the Cardiac Rhythms

    NASA Astrophysics Data System (ADS)

    Filippi, S.; Cherubini, C.

    Many biological systems which appear complex both in space and time and result still not understood, require new theoretical approaches for their nonlinear dynamics. In particular we focus here on the theoretical analysis of the underlying mechanisms of heart dynamics. This could clarify the (apparently) chaotic behavior of the normal heart-beat and especially the control of the bifurcations of dynamics arising in situ- ations of disease. The principal target is to find a possible clear distinction between normal and pathological regimes. A discussion of Complex Ginzburg-Landau equation can give useful hints to this aim.

  20. A Dynamic Testing Complexity Metric

    NASA Technical Reports Server (NTRS)

    Voas, Jeffrey

    1991-01-01

    This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

  1. Amplitude dynamics favors synchronization in complex networks

    PubMed Central

    Gambuzza, Lucia Valentina; Gómez-Gardeñes, Jesus; Frasca, Mattia

    2016-01-01

    In this paper we study phase synchronization in random complex networks of coupled periodic oscillators. In particular, we show that, when amplitude dynamics is not negligible, phase synchronization may be enhanced. To illustrate this, we compare the behavior of heterogeneous units with both amplitude and phase dynamics and pure (Kuramoto) phase oscillators. We find that in small network motifs the behavior crucially depends on the topology and on the node frequency distribution. Surprisingly, the microscopic structures for which the amplitude dynamics improves synchronization are those that are statistically more abundant in random complex networks. Thus, amplitude dynamics leads to a general lowering of the synchronization threshold in arbitrary random topologies. Finally, we show that this synchronization enhancement is generic of oscillators close to Hopf bifurcations. To this aim we consider coupled FitzHugh-Nagumo units modeling neuron dynamics. PMID:27108847

  2. Competitive dynamics on complex networks.

    PubMed

    Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan

    2014-01-01

    We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition. PMID:25068622

  3. Competitive Dynamics on Complex Networks

    NASA Astrophysics Data System (ADS)

    Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan

    2014-07-01

    We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.

  4. Spreading dynamics in complex networks

    NASA Astrophysics Data System (ADS)

    Pei, Sen; Makse, Hernán A.

    2013-12-01

    Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

  5. Collective dynamics of active filament complexes

    NASA Astrophysics Data System (ADS)

    Nogucci, Hironobu; Ishihara, Shuji

    2016-05-01

    Networks of biofilaments are essential for the formation of cellular structures that support various biological functions. For the most part, previous studies have investigated the collective dynamics of rodlike biofilaments; however, the shapes of the actual subcellular components are often more elaborate. In this study, we considered an active object composed of two active filaments, which represents the progression from rodlike biofilaments to complex-shaped biofilaments. Specifically, we numerically assessed the collective behaviors of these active objects in two dimensions and observed several types of dynamics, depending on the density and the angle of the two filaments as shape parameters of the object. Among the observed collective dynamics, a moving density band that we named a "moving smectic" is introduced here for the first time. By analyzing the trajectories of individual objects and the interactions among them, this study demonstrated how interactions among active biofilaments with complex shapes could produce collective dynamics in a nontrivial manner.

  6. Constructing minimal models for complex system dynamics

    NASA Astrophysics Data System (ADS)

    Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László

    2015-05-01

    One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.

  7. Controlling Complex Systems and Developing Dynamic Technology

    NASA Astrophysics Data System (ADS)

    Avizienis, Audrius Victor

    In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit

  8. Mapping dynamical systems onto complex networks

    NASA Astrophysics Data System (ADS)

    Borges, E. P.; Cajueiro, D. O.; Andrade, R. F. S.

    2007-08-01

    The objective of this study is to design a procedure to characterize chaotic dynamical systems, in which they are mapped onto a complex network. The nodes represent the regions of space visited by the system, while the edges represent the transitions between these regions. Parameters developed to quantify the properties of complex networks, including those related to higher order neighbourhoods, are used in the analysis. The methodology is tested on the logistic map, focusing on the onset of chaos and chaotic regimes. The corresponding networks were found to have distinct features that are associated with the particular type of dynamics that generated them.

  9. Langevin description of gauged scalar fields in a thermal bath

    NASA Astrophysics Data System (ADS)

    Miyamoto, Yuhei; Motohashi, Hayato; Suyama, Teruaki; Yokoyama, Jun'ichi

    2014-04-01

    We study the dynamics of the oscillating gauged scalar field in a thermal bath. A Langevin-type equation of motion of the scalar field, which contains both dissipation and fluctuation terms, is derived by using the real-time finite-temperature effective action approach. The existence of the quantum fluctuation-dissipation relation between the nonlocal dissipation term and the Gaussian stochastic noise terms is verified. We find that the noise variables are anticorrelated at equal time. The dissipation rate for each mode is also studied, which turns out to depend on the wave number.

  10. Better Decision Making in Complex, Dynamic Tasks

    NASA Astrophysics Data System (ADS)

    Qudrat-Ullah, Hassan

    Complex managerial problems abound. For instance, project costs continue to overrun, friendly fire events, where a fighter plane bombs its own troops on ground, appear unavoidable, and overexploitation of renewables continues unabated. In essence, managers and policymakers today face problems that are increasingly complex, and dynamic. Therefore, the need for effective and efficient decisional aids is always on the rise.

  11. Dynamic information routing in complex networks

    PubMed Central

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-01-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

  12. Dynamic information routing in complex networks.

    PubMed

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-01-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function. PMID:27067257

  13. Dynamic information routing in complex networks

    NASA Astrophysics Data System (ADS)

    Kirst, Christoph; Timme, Marc; Battaglia, Demian

    2016-04-01

    Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function.

  14. Language Teacher Cognitions: Complex Dynamic Systems?

    ERIC Educational Resources Information Center

    Feryok, Anne

    2010-01-01

    Language teacher cognition research is a growing field. In recent years several features of language teacher cognitions have been noted: they can be complex, ranging over a number of different subjects; they can be dynamic, changing over time and under different influences; and they can be systems, forming unified and cohesive personal or…

  15. On the environmental modes for the generalized Langevin equation

    NASA Astrophysics Data System (ADS)

    Kawai, Shinnosuke

    2015-09-01

    The generalized Langevin equation (GLE) is used widely in molecular science and time series analysis as it offers a convenient low-dimensional description for large systems. There the dynamical effect of the environment interacting with the low-dimensional system is expressed as friction and random force. The present paper aims to investigate explicit dynamical variables to describe the dynamical modes in the environment that are derived from the GLE and defined solely in terms of the time series of the observed variable. The formulation results in equations of motion without a memory term and hence offers a more intuitive description than the GLE. The framework provided by the present study is expected to elucidate a multi-dimensional dynamics hidden behind the time series of the observed quantity.

  16. Role of the Charge-Transfer State in Reduced Langevin Recombination in Organic Solar Cells: A Theoretical Study

    PubMed Central

    2015-01-01

    Reduced Langevin recombination has been observed in organic solar cells (OSCs) for many years, but its origin is still unclear. A recent work by Burke et al. (Adv. Energy Mater.2015, 5, 1500123-1) was inspired by this reduced Langevin recombination, and they proposed an equilibrium model of charge-transfer (CT) states that correlates the open-circuit voltage of OSCs with experimentally available device parameters. In this work, we extend Burke et al.’s CT model further and for the first time directly correlate the reduced Langevin recombination with the energetic and dynamic behavior of the CT state. Recombination through CT states leads in a straightforward manner to a decrease in the Langevin reduction factor with increasing temperature, without explicit consideration of the temperature dependence of the mobility. To verify the correlation between the CT states and reduced Langevin recombination, we incorporated this CT model and the reduced Langevin model into drift-diffusion simulations of a bilayer OSC. The simulations not only successfully reproduced realistic current–voltage (J–V) characteristics of the bilayer OSC, but also demonstrate that the two models consistently lead to same value of the apparent Langevin reduction factor. PMID:26640611

  17. Design tools for complex dynamic security systems.

    SciTech Connect

    Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson; Laguna, Glenn A.; Robinett, Rush D. III; Groom, Kenneth Neal; Wilson, David Gerald; Bickerstaff, Robert J.; Harrington, John J.

    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 systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.

  18. A theory for protein dynamics: Global anisotropy and a normal mode approach to local complexity

    NASA Astrophysics Data System (ADS)

    Copperman, Jeremy; Romano, Pablo; Guenza, Marina

    2014-03-01

    We propose a novel Langevin equation description for the dynamics of biological macromolecules by projecting the solvent and all atomic degrees of freedom onto a set of coarse-grained sites at the single residue level. We utilize a multi-scale approach where molecular dynamic simulations are performed to obtain equilibrium structural correlations input to a modified Rouse-Zimm description which can be solved analytically. The normal mode solution provides a minimal basis set to account for important properties of biological polymers such as the anisotropic global structure, and internal motion on a complex free-energy surface. This multi-scale modeling method predicts the dynamics of both global rotational diffusion and constrained internal motion from the picosecond to the nanosecond regime, and is quantitative when compared to both simulation trajectory and NMR relaxation times. Utilizing non-equilibrium sampling techniques and an explicit treatment of the free-energy barriers in the mode coordinates, the model is extended to include biologically important fluctuations in the microsecond regime, such as bubble and fork formation in nucleic acids, and protein domain motion. This work supported by the NSF under the Graduate STEM Fellows in K-12 Education (GK-12) program, grant DGE-0742540 and NSF grant DMR-0804145, computational support from XSEDE and ACISS.

  19. Analysis of multifrequency langevin composite ultrasonic transducers.

    PubMed

    Lin, Shuyu

    2009-09-01

    The multimode coupled vibration of Langevin composite ultrasonic transducers with conical metal mass of large cross-section is analyzed. The coupled resonance and anti-resonance frequency equations are derived and the effective electromechanical coupling coefficient is analyzed. The effect of the geometrical dimensions on the resonance frequency, the anti-resonance frequency, and the effective electromechanical coupling coefficient is studied. It is illustrated that when the radial dimension is large compared with the longitudinal dimension, the vibration of the Langevin transducer becomes a multifrequency multimode coupled vibration. Numerical methods are used to simulate the coupled vibration; the simulated results are in good agreement with those from the analytical results. Some Langevin transducers of large cross-section are designed and manufactured and their resonance frequencies are measured. It can be seen that the resonance frequencies obtained from the coupled resonance frequency equations are in good agreement with the measured results. It is expected that by properly choosing the dimensions, multifrequency Langevin transducers can be designed and used in ultrasonic cleaning, ultrasonic sonochemistry, and other applications. PMID:19812002

  20. Molecular dynamics simulations of large macromolecular complexes

    PubMed Central

    Perilla, Juan R.; Goh, Boon Chong; Cassidy, C. Keith; Liu, Bo; Bernardi, Rafael C.; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

    2015-01-01

    Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. PMID:25845770

  1. Structure and dynamics of complex liquid water: Molecular dynamics simulation

    NASA Astrophysics Data System (ADS)

    S, Indrajith V.; Natesan, Baskaran

    2015-06-01

    We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.

  2. Dynamical robustness analysis of weighted complex networks

    NASA Astrophysics Data System (ADS)

    He, Zhiwei; Liu, Shuai; Zhan, Meng

    2013-09-01

    Robustness of weighted complex networks is analyzed from nonlinear dynamical point of view and with focus on different roles of high-degree and low-degree nodes. We find that the phenomenon for the low-degree nodes being the key nodes in the heterogeneous networks only appears in weakly weighted networks and for weak coupling. For all other parameters, the heterogeneous networks are always highly vulnerable to the failure of high-degree nodes; this point is the same as in the structural robustness analysis. We also find that with random inactivation, heterogeneous networks are always more robust than the corresponding homogeneous networks with the same average degree except for one special parameter. Thus our findings give an integrated picture for the dynamical robustness analysis on complex networks.

  3. Stability, complexity and robustness in population dynamics.

    PubMed

    Demongeot, J; Hazgui, H; Ben Amor, H; Waku, J

    2014-09-01

    The problem of stability in population dynamics concerns many domains of application in demography, biology, mechanics and mathematics. The problem is highly generic and independent of the population considered (human, animals, molecules,…). We give in this paper some examples of population dynamics concerning nucleic acids interacting through direct nucleic binding with small or cyclic RNAs acting on mRNAs or tRNAs as translation factors or through protein complexes expressed by genes and linked to DNA as transcription factors. The networks made of these interactions between nucleic acids (considered respectively as edges and nodes of their interaction graph) are complex, but exhibit simple emergent asymptotic behaviours, when time tends to infinity, called attractors. We show that the quantity called attractor entropy plays a crucial role in the study of the stability and robustness of such genetic networks. PMID:25107273

  4. Stability threshold approach for complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Klinshov, Vladimir V.; Nekorkin, Vladimir I.; Kurths, Jürgen

    2016-01-01

    A new measure to characterize the stability of complex dynamical systems against large perturbations is suggested, the stability threshold (ST). It quantifies the magnitude of the weakest perturbation capable of disrupting the system and switch it to an undesired dynamical regime. In the phase space, the ST corresponds to the 'thinnest site' of the attraction basin and therefore indicates the most 'dangerous' direction of perturbations. We introduce a computational algorithm for quantification of the ST and demonstrate that the suggested approach is effective and provides important insights. The generality of the obtained results defines their vast potential for application in such fields as engineering, neuroscience, power grids, Earth science and many others where the robustness of complex systems is studied.

  5. Stability threshold approach for complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Klinshov, Vladimir V.; Nekorkin, Vladimir I.; Kurths, Jürgen

    2016-01-01

    A new measure to characterize the stability of complex dynamical systems against large perturbations is suggested, the stability threshold (ST). It quantifies the magnitude of the weakest perturbation capable of disrupting the system and switch it to an undesired dynamical regime. In the phase space, the ST corresponds to the ‘thinnest site’ of the attraction basin and therefore indicates the most ‘dangerous’ direction of perturbations. We introduce a computational algorithm for quantification of the ST and demonstrate that the suggested approach is effective and provides important insights. The generality of the obtained results defines their vast potential for application in such fields as engineering, neuroscience, power grids, Earth science and many others where the robustness of complex systems is studied.

  6. Species Abundance Patterns in Complex Evolutionary Dynamics

    NASA Astrophysics Data System (ADS)

    Tokita, Kei

    2004-10-01

    An analytic theory of species abundance patterns (SAPs) in biological networks is presented. The theory is based on multispecies replicator dynamics equivalent to the Lotka-Volterra equation, with diverse interspecies interactions. Various SAPs observed in nature are derived from a single parameter. The abundance distribution is formed like a widely observed left-skewed lognormal distribution. As the model has a general form, the result can be applied to similar patterns in other complex biological networks, e.g., gene expression.

  7. Nonlinear dynamics, chaos and complex cardiac arrhythmias

    NASA Technical Reports Server (NTRS)

    Glass, L.; Courtemanche, M.; Shrier, A.; Goldberger, A. L.

    1987-01-01

    Periodic stimulation of a nonlinear cardiac oscillator in vitro gives rise to complex dynamics that is well described by one-dimensional finite difference equations. As stimulation parameters are varied, a large number of different phase-locked and chaotic rhythms is observed. Similar rhythms can be observed in the intact human heart when there is interaction between two pacemaker sites. Simplified models are analyzed, which show some correspondence to clinical observations.

  8. Nonlinear Dynamics, Chaotic and Complex Systems

    NASA Astrophysics Data System (ADS)

    Infeld, E.; Zelazny, R.; Galkowski, A.

    2011-04-01

    Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet

  9. Modular interdependency in complex dynamical systems.

    PubMed

    Watson, Richard A; Pollack, Jordan B

    2005-01-01

    Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability. PMID:16197673

  10. Random complex dynamics and devil's coliseums

    NASA Astrophysics Data System (ADS)

    Sumi, Hiroki

    2015-04-01

    We investigate the random dynamics of polynomial maps on the Riemann sphere \\hat{\\Bbb{C}} and the dynamics of semigroups of polynomial maps on \\hat{\\Bbb{C}} . In particular, the dynamics of a semigroup G of polynomials whose planar postcritical set is bounded and the associated random dynamics are studied. In general, the Julia set of such a G may be disconnected. We show that if G is such a semigroup, then regarding the associated random dynamics, the chaos of the averaged system disappears in the C0 sense, and the function T∞ of probability of tending to ∞ \\in \\hat{\\Bbb{C}} is Hölder continuous on \\hat{\\Bbb{C}} and varies only on the Julia set of G. Moreover, the function T∞ has a kind of monotonicity. It turns out that T∞ is a complex analogue of the devil's staircase, and we call T∞ a ‘devil’s coliseum'. We investigate the details of T∞ when G is generated by two polynomials. In this case, T∞ varies precisely on the Julia set of G, which is a thin fractal set. Moreover, under this condition, we investigate the pointwise Hölder exponents of T∞.

  11. Automated Design of Complex Dynamic Systems

    PubMed Central

    Hermans, Michiel; Schrauwen, Benjamin; Bienstman, Peter; Dambre, Joni

    2014-01-01

    Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems. PMID:24497969

  12. Fractional Langevin equation: overdamped, underdamped, and critical behaviors.

    PubMed

    Burov, S; Barkai, E

    2008-09-01

    The dynamical phase diagram of the fractional Langevin equation is investigated for a harmonically bound particle. It is shown that critical exponents mark dynamical transitions in the behavior of the system. Four different critical exponents are found. (i) alpha_{c}=0.402+/-0.002 marks a transition to a nonmonotonic underdamped phase, (ii) alpha_{R}=0.441... marks a transition to a resonance phase when an external oscillating field drives the system, and (iii) alpha_{chi_{1}}=0.527... and (iv) alpha_{chi_{2}}=0.707... mark transitions to a double-peak phase of the "loss" when such an oscillating field present. As a physical explanation we present a cage effect, where the medium induces an elastic type of friction. Phase diagrams describing over and underdamped regimes, with or without resonances, show behaviors different from normal. PMID:18850998

  13. PREFACE: Complex Dynamics in Spatially Extended Systems

    NASA Astrophysics Data System (ADS)

    Mosekilde, Erik; Bohr, Tomas; Rasmussen, Jens Juul; Leth Christiansen, Peter

    1996-01-01

    Self-organization, or the spontaneous emergence of patterns and structures under far-from-equilibrium conditions, turbulence, and related nonlinear dynamic phenomena in spatially extended systems have developed into one of the most exciting topics of modern science. Phenomena of this type arise in a wide variety of different fields, ranging from the development of chemical and biological patterns in reaction-diffusion systems over vortex formation in connection with chemical, optical, hydrodynamic or magnetohydrodynamic turbulence to technical applications in connection with liquid crystal displays or pulse compression in optical communication systems. Lasers often show interesting patterns produced by self-focusing and other nonlinear phenomena, diffusion limited aggregation is known to generate fractal-like structures, and amazing struc- tures also arise in bacterial growth processes or when a droplet of an oil suspension of finely divided magnetic particles is subject to a magnetic field perpendicular to the surface of the cell in which it is contained. In September 1995 the Niels Bohr Institute in Copenhagen was the venue of an International Conference on Complex Dynamics in Spatially Extended Systems. Organizers of the conference were the three Danish centers for nonlinear dynamics: The Center for Chaos and Turbulence Studies (CATS), located at the Niels Bohr Institute; the Center for Modeling, Nonlinear Dynamics and Irreversible Thermodynamics (MIDIT), located at the Technical University of Denmark, and the Center for Nonlinear Dynamics in Continuum Systems, located at the Risø National Laboratories. In the spirit of the successful NATO Advanced Research Workshops on Spatiotemporal Patterns in Nonequilibrium Systems of which the last was held in Santa Fe, New Mexico in 1993, the conference aimed at stimulating new ideas and providing a forum for the exchange of knowledge between leading practitioners of the field. With its 50 invited speakers and more than

  14. Complex Dynamics in Information Sharing Networks

    NASA Astrophysics Data System (ADS)

    Cronin, Bruce

    This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

  15. Hybrid function projective synchronization in complex dynamical networks

    SciTech Connect

    Wei, Qiang; Wang, Xing-yuan Hu, Xiao-peng

    2014-02-15

    This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

  16. MODELING OF A NANOPARTICLE MOTION IN A NEWTONIAN FLUID: A COMPARISON BETWEEN FLUCTUATING HYDRODYNAMICS AND GENERALIZED LANGEVIN PROCEDURES

    PubMed Central

    Uma, B.; Radhakrishnan, R.; Eckmann, D.M.

    2014-01-01

    A direct numerical simulation adopting an arbitrary Lagrangian-Eulerian based finite element method is employed to simulate the motion of a nanocarrier in a quiescent fluid contained in a cylindrical tube. The nanocarrier is treated as a solid sphere. Thermal fluctuations are implemented using two different approaches: (1) fluctuating hydrodynamics; (2) generalized Langevin dynamics (Mittag-Leffler noise). At thermal equilibrium, the numerical predictions for temperature of the nanoparticle, velocity distribution of the particle, decay of the velocity autocorrelation function, diffusivity of the particle and particle-wall interactions are evaluated and compared with analytical results, where available. For a neutrally buoyant nanoparticle of 200 nm radius, the comparisons between the results obtained from the fluctuating hydrodynamics and the generalized Langevin dynamics approaches are provided. Results for particle diffusivity predicted by the fluctuating hydrodynamics approach compare very well with analytical predictions. Ease of computation of the thermostat is obtained with the Langevin approach although the dynamics gets altered. PMID:25621317

  17. The heterogeneous dynamics of economic complexity.

    PubMed

    Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

    2015-01-01

    What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312

  18. Complex Dynamic Development of Poliovirus Membranous Replication Complexes

    PubMed Central

    Nair, Vinod; Hansen, Bryan T.; Hoyt, Forrest H.; Fischer, Elizabeth R.; Ehrenfeld, Ellie

    2012-01-01

    Replication of all positive-strand RNA viruses is intimately associated with membranes. Here we utilize electron tomography and other methods to investigate the remodeling of membranes in poliovirus-infected cells. We found that the viral replication structures previously described as “vesicles” are in fact convoluted, branching chambers with complex and dynamic morphology. They are likely to originate from cis-Golgi membranes and are represented during the early stages of infection by single-walled connecting and branching tubular compartments. These early viral organelles gradually transform into double-membrane structures by extension of membranous walls and/or collapsing of the luminal cavity of the single-membrane structures. As the double-membrane regions develop, they enclose cytoplasmic material. At this stage, a continuous membranous structure may have double- and single-walled membrane morphology at adjacent cross-sections. In the late stages of the replication cycle, the structures are represented mostly by double-membrane vesicles. Viral replication proteins, double-stranded RNA species, and actively replicating RNA are associated with both double- and single-membrane structures. However, the exponential phase of viral RNA synthesis occurs when single-membrane formations are predominant in the cell. It has been shown previously that replication complexes of some other positive-strand RNA viruses form on membrane invaginations, which result from negative membrane curvature. Our data show that the remodeling of cellular membranes in poliovirus-infected cells produces structures with positive curvature of membranes. Thus, it is likely that there is a fundamental divergence in the requirements for the supporting cellular membrane-shaping machinery among different groups of positive-strand RNA viruses. PMID:22072780

  19. Complex Dynamics in Nonequilibrium Economics and Chemistry

    NASA Astrophysics Data System (ADS)

    Wen, Kehong

    Complex dynamics provides a new approach in dealing with economic complexity. We study interactively the empirical and theoretical aspects of business cycles. The way of exploring complexity is similar to that in the study of an oscillatory chemical system (BZ system)--a model for modeling complex behavior. We contribute in simulating qualitatively the complex periodic patterns observed from the controlled BZ experiments to narrow the gap between modeling and experiment. The gap between theory and reality is much wider in economics, which involves studies of human expectations and decisions, the essential difference from natural sciences. Our empirical and theoretical studies make substantial progress in closing this gap. With the help from the new development in nonequilibrium physics, i.e., the complex spectral theory, we advance our technique in detecting characteristic time scales from empirical economic data. We obtain correlation resonances, which give oscillating modes with decays for correlation decomposition, from different time series including S&P 500, M2, crude oil spot prices, and GNP. The time scales found are strikingly compatible with business experiences and other studies in business cycles. They reveal the non-Markovian nature of coherent markets. The resonances enhance the evidence of economic chaos obtained by using other tests. The evolving multi-humped distributions produced by the moving-time -window technique reveal the nonequilibrium nature of economic behavior. They reproduce the American economic history of booms and busts. The studies seem to provide a way out of the debate on chaos versus noise and unify the cyclical and stochastic approaches in explaining business fluctuations. Based on these findings and new expectation formulation, we construct a business cycle model which gives qualitatively compatible patterns to those found empirically. The soft-bouncing oscillator model provides a better alternative than the harmonic oscillator

  20. Optimal dynamic bandwidth allocation for complex networks

    NASA Astrophysics Data System (ADS)

    Jiang, Zhong-Yuan; Liang, Man-Gui; Li, Qian; Guo, Dong-Chao

    2013-03-01

    Traffic capacity of one network strongly depends on the link’s bandwidth allocation strategy. In previous bandwidth allocation mechanisms, once one link’s bandwidth is allocated, it will be fixed throughout the overall traffic transmission process. However, the traffic load of every link changes from time to time. In this paper, with finite total bandwidth resource of the network, we propose to dynamically allocate the total bandwidth resource in which each link’s bandwidth is proportional to the queue length of the output buffer of the link per time step. With plenty of data packets in the network, the traffic handling ability of all links of the network achieves full utilization. The theoretical analysis and the extensive simulation results on complex networks are consistent. This work is valuable for network service providers to improve network performance or to do reasonable network design efficiently.

  1. [The dynamic complex of the temporomandibular meniscus].

    PubMed

    Couly, G; Hureau, J; Vaillant, J M

    1975-12-01

    The existence of meniscocapsular insertions of the temporal, masseter and external pterygoid muscles complicates the scheme of capsulo-meniscal dynamics. Our findings do indeed agree with those of DUBECQ (Bordeaux); but we think that the insertions of the masseter and the temporal are not only fine tracts. In the embryon, the meniscus is the preglossal mekelian conjunctival blastema, which receives the 3 masticatory muscles on its anterior border. In the adult, menisco-capsulo-muscular relationships are not modified; inspite of considerable functional adaptation of the articulation to varied stimuli, the menisco-capsular apparatus seems to be triply controlled by 3 musculo-masticatory bands, owing to the anterior premeniscal tendinous lamina, in histological continuity with the meniscus and rich in corpuscles of deep sensitivity. The resultant of the tridirectional muscular traction of the masseter, external pterygoid and temporal is a force in the postero-anterior oblique direction, downwards and forwards, which allows the meniscus to stretch, as was shown by Pr Delaire, and thus to have a sub-temporal sliding pathway of 8 to 12 mm. The three muscle bundles external pterygoid, temporal and masseter constitute the dynamic complex of the meniscus. PMID:1063432

  2. Dynamics of swimming bacteria at complex interfaces

    NASA Astrophysics Data System (ADS)

    Lopez, Diego; Lauga, Eric

    2014-07-01

    Flagellated bacteria exploiting helical propulsion are known to swim along circular trajectories near surfaces. Fluid dynamics predicts this circular motion to be clockwise (CW) above a rigid surface (when viewed from inside the fluid) and counter-clockwise (CCW) below a free surface. Recent experimental investigations showed that complex physicochemical processes at the nearby surface could lead to a change in the direction of rotation, both at solid surfaces absorbing slip-inducing polymers and interfaces covered with surfactants. Motivated by these results, we use a far-field hydrodynamic model to predict the kinematics of swimming near three types of interfaces: clean fluid-fluid interface, slipping rigid wall, and a fluid interface covered by incompressible surfactants. Representing the helical swimmer by a superposition of hydrodynamic singularities, we first show that in all cases the surfaces reorient the swimmer parallel to the surface and attract it, both of which are a consequence of the Stokes dipole component of the swimmer flow field. We then show that circular motion is induced by a higher-order singularity, namely, a rotlet dipole, and that its rotation direction (CW vs. CCW) is strongly affected by the boundary conditions at the interface and the bacteria shape. Our results suggest thus that the hydrodynamics of complex interfaces provide a mechanism to selectively stir bacteria.

  3. Langevin power curve analysis for numerical wind energy converter models with new insights on high frequency power performance

    NASA Astrophysics Data System (ADS)

    Mücke, Tanja A.; Wächter, Matthias; Milan, Patrick; Peinke, Joachim

    2015-11-01

    Based on the Langevin equation it has been proposed to obtain power curves for wind turbines from high frequency data of wind speed measurements u(t) and power output P (t). The two parts of the Langevin approach, power curve and drift field, give a comprehensive description of the conversion dynamic over the whole operating range of the wind turbine. The method deals with high frequent data instead of 10 min means. It is therefore possible to gain a reliable power curve already from a small amount of data per wind speed. Furthermore, the method is able to visualize multiple fixed points, which is e.g. characteristic for the transition from partial to full load or in case the conversion process deviates from the standard procedures. In order to gain a deeper knowledge it is essential that the method works not only for measured data but also for numerical wind turbine models and synthetic wind fields. Here, we characterize the dynamics of a detailed numerical wind turbine model and calculate the Langevin power curve for different data samplings. We show, how to get reliable results from synthetic data and verify the applicability of the method for field measurements with ultra-sonic, cup and Lidar measurements. The independence of the fixed points on site specific turbulence effects is also confirmed with the numerical model. Furthermore, we demonstrate the potential of the Langevin approach to detect failures in the conversion process and thus show the potential of the Langevin approach for a condition monitoring system.

  4. Dynamic interactions of proteins in complex networks

    SciTech Connect

    Appella, E.; Anderson, C.

    2009-10-01

    Recent advances in techniques such as NMR and EPR spectroscopy have enabled the elucidation of how proteins undergo structural changes to act in concert in complex networks. The three minireviews in this series highlight current findings and the capabilities of new methodologies for unraveling the dynamic changes controlling diverse cellular functions. They represent a sampling of the cutting-edge research presented at the 17th Meeting of Methods in Protein Structure Analysis, MPSA2008, in Sapporo, Japan, 26-29 August, 2008 (http://www.iapsap.bnl.gov). The first minireview, by Christensen and Klevit, reports on a structure-based yeast two-hybrid method for identifying E2 ubiquitin-conjugating enzymes that interact with the E3 BRCA1/BARD1 heterodimer ligase to generate either mono- or polyubiquitinated products. This method demonstrated for the first time that the BRCA1/BARD1 E3 can interact with 10 different E2 enzymes. Interestingly, the interaction with multiple E2 enzymes displayed unique ubiquitin-transfer properties, a feature expected to be common among other RING and U-box E3s. Further characterization of new E3 ligases and the E2 enzymes that interact with them will greatly enhance our understanding of ubiquitin transfer and facilitate studies of roles of ubiquitin and ubiquitin-like proteins in protein processing and trafficking. Stein et al., in the second minireview, describe recent progress in defining the binding specificity of different peptide-binding domains. The authors clearly point out that transient peptide interactions mediated by both post-translational modifications and disordered regions ensure a high level of specificity. They postulate that a regulatory code may dictate the number of combinations of domains and post-translational modifications needed to achieve the required level of interaction specificity. Moreover, recognition alone is not enough to obtain a stable complex, especially in a complex cellular environment. Increasing

  5. Langevin representation of Coulomb collisions for bi-Maxwellian plasmas

    SciTech Connect

    Hellinger, Petr

    2010-07-20

    Langevin model corresponding to the Fokker-Planck equation for bi-Maxwellian particle distribution functions is developed. Rosenbluth potentials and their derivatives are derived in the form of triple hypergeometric functions. The Langevin model is tested in the case of relaxation of the proton temperature anisotropy and implemented into the hybrid expanding box model. First results of this code are presented and discussed.

  6. Orbital Architectures of Dynamically Complex Exoplanet Systems

    NASA Astrophysics Data System (ADS)

    Nelson, Benjamin E.

    2015-01-01

    The most powerful constraints on planet formation will come from characterizing the dynamical state of complex multi-planet systems. Unfortunately, with that complexity comes a number of factors that make analyzing these systems a computationally challenging endeavor: the sheer number of model parameters, a wonky shaped posterior distribution, and hundreds to thousands of time series measurements. We develop a differential evolution Markov chain Monte Carlo (RUN DMC) to tackle these difficult aspects of data analysis. We apply RUN DMC to two classic multi-planet systems from radial velocity surveys, 55 Cancri and GJ 876. For 55 Cancri, we find the inner-most planet "e" must be coplanar to within 40 degrees of the outer planets, otherwise Kozai-like perturbations will cause the planet's orbit to cross the stellar surface. We find the orbits of planets "b" and "c" are apsidally aligned and librating with low to median amplitude (50±610 degrees), but they are not orbiting in a mean-motion resonance. For GJ 876, we can meaningfully constrain the three-dimensional orbital architecture of all the planets based on the radial velocity data alone. By demanding orbital stability, we find the resonant planets have low mutual inclinations (Φ) so they must be roughly coplanar (Φcb = 1.41±0.620.57 degrees and Φbe = 3.87±1.991.86 degrees). The three-dimensional Laplace argument librates with an amplitude of 50.5±7.910.0 degrees, indicating significant past disk migration and ensuring long-term stability. These empirically derived models will provide new challenges for planet formation models and motivate the need for more sophisticated algorithms to analyze exoplanet data.

  7. Guiding locomotion in complex, dynamic environments.

    PubMed

    Fajen, Brett R

    2013-01-01

    Locomotion in complex, dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects-that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach. PMID:23885238

  8. The Complex Dynamics of Sponsored Search Markets

    NASA Astrophysics Data System (ADS)

    Robu, Valentin; La Poutré, Han; Bohte, Sander

    This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms.

  9. Propagation dynamics on networks featuring complex topologies

    NASA Astrophysics Data System (ADS)

    Hébert-Dufresne, Laurent; Noël, Pierre-André; Marceau, Vincent; Allard, Antoine; Dubé, Louis J.

    2010-09-01

    Analytical description of propagation phenomena on random networks has flourished in recent years, yet more complex systems have mainly been studied through numerical means. In this paper, a mean-field description is used to coherently couple the dynamics of the network elements (such as nodes, vertices, individuals, etc.) on the one hand and their recurrent topological patterns (such as subgraphs, groups, etc.) on the other hand. In a susceptible-infectious-susceptible (SIS) model of epidemic spread on social networks with community structure, this approach yields a set of ordinary differential equations for the time evolution of the system, as well as analytical solutions for the epidemic threshold and equilibria. The results obtained are in good agreement with numerical simulations and reproduce the behavior of random networks in the appropriate limits which highlights the influence of topology on the processes. Finally, it is demonstrated that our model predicts higher epidemic thresholds for clustered structures than for equivalent random topologies in the case of networks with zero degree correlation.

  10. Trajectory approach to the Schrödinger-Langevin equation with linear dissipation for ground states

    NASA Astrophysics Data System (ADS)

    Chou, Chia-Chun

    2015-11-01

    The Schrödinger-Langevin equation with linear dissipation is integrated by propagating an ensemble of Bohmian trajectories for the ground state of quantum systems. Substituting the wave function expressed in terms of the complex action into the Schrödinger-Langevin equation yields the complex quantum Hamilton-Jacobi equation with linear dissipation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation is simultaneously integrated with the trajectory guidance equation. Then, the computational method is applied to the harmonic oscillator, the double well potential, and the ground vibrational state of methyl iodide. The excellent agreement between the computational and the exact results for the ground state energies and wave functions shows that this study provides a synthetic trajectory approach to the ground state of quantum systems.

  11. Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

    PubMed

    Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

    2015-12-15

    Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to

  12. Multiple Cancer Cell Population Dynamics in a Complex Ecology

    NASA Astrophysics Data System (ADS)

    Lin, Ke-Chih; Targa, Gonzalo; Pienta, Kenneth; Sturm, James; Austin, Robert

    We have developed a technology for study of complex ecology cancer population dynamics. The technology includes complex drug gradients, full bright field/dark field/fluorescence imaging of areas of several square millimeters and thin gas-permable membranes which allow single cell extraction and analysis. We will present results of studies of prostate cancer cell dynamics.

  13. Gaussian approximations for stochastic systems with delay: Chemical Langevin equation and application to a Brusselator system

    SciTech Connect

    Brett, Tobias Galla, Tobias

    2014-03-28

    We present a heuristic derivation of Gaussian approximations for stochastic chemical reaction systems with distributed delay. In particular, we derive the corresponding chemical Langevin equation. Due to the non-Markovian character of the underlying dynamics, these equations are integro-differential equations, and the noise in the Gaussian approximation is coloured. Following on from the chemical Langevin equation, a further reduction leads to the linear-noise approximation. We apply the formalism to a delay variant of the celebrated Brusselator model, and show how it can be used to characterise noise-driven quasi-cycles, as well as noise-triggered spiking. We find surprisingly intricate dependence of the typical frequency of quasi-cycles on the delay period.

  14. Hamiltonian dynamics for complex food webs.

    PubMed

    Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

    2016-03-01

    We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity. PMID:27078396

  15. Hamiltonian dynamics for complex food webs

    NASA Astrophysics Data System (ADS)

    Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno

    2016-03-01

    We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity.

  16. A path-integral Langevin equation treatment of low-temperature doped helium clusters

    NASA Astrophysics Data System (ADS)

    Ing, Christopher; Hinsen, Konrad; Yang, Jing; Zeng, Toby; Li, Hui; Roy, Pierre-Nicholas

    2012-06-01

    We present an implementation of path integral molecular dynamics for sampling low temperature properties of doped helium clusters using Langevin dynamics. The robustness of the path integral Langevin equation and white-noise Langevin equation [M. Ceriotti, M. Parrinello, T. E. Markland, and D. E. Manolopoulos, J. Chem. Phys. 133, 124104 (2010)], 10.1063/1.3489925 sampling methods are considered for those weakly bound systems with comparison to path integral Monte Carlo (PIMC) in terms of efficiency and accuracy. Using these techniques, convergence studies are performed to confirm the systematic error reduction introduced by increasing the number of discretization steps of the path integral. We comment on the structural and energetic evolution of HeN-CO2 clusters from N = 1 to 20. To quantify the importance of both rotations and exchange in our simulations, we present a chemical potential and calculated band origin shifts as a function of cluster size utilizing PIMC sampling that includes these effects. This work also serves to showcase the implementation of path integral simulation techniques within the molecular modelling toolkit [K. Hinsen, J. Comp. Chem. 21, 79 (2000)], 10.1002/(SICI)1096-987X(20000130)21:2<79::AID-JCC1>3.0.CO;2-B, an open-source molecular simulation package.

  17. Two dimensional Langevin recombination in regioregular poly(3-hexylthiophene)

    NASA Astrophysics Data System (ADS)

    Juška, Gytis; Genevičius, Kristijonas; Nekrašas, Nerijus; Sliaužys, Gytis; Österbacka, Ronald

    2009-07-01

    In this work, it is shown that recombination in regioregular poly(3-hexylthiophene):[6,6]-phenyl-C61-butyric acid methyl ester (RRP3HT:PCBM) bulk-heterojunction solar cells is caused by the two dimensional (2D) Langevin recombination in the lamellar structures of RRP3HT, which are formed after annealing process. Due to 2D Langevin process, bimolecular recombination coefficient is reduced in comparison with three dimensional Langevin case, and bimolecular recombination coefficient depends on the density of charge carriers n1/2. Data obtained from the different experimental techniques (charge extraction with linearly increasing voltage, integral time of flight, double injection current transients and transient absorption spectroscopy) confirms 2D Langevin recombination in RR3PHT.

  18. Exponential rise of dynamical complexity in quantum computing through projections

    PubMed Central

    Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya

    2014-01-01

    The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once ‘observed’ as outlined above. Conversely, we show that any complex quantum dynamics can be ‘purified’ into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics. PMID:25300692

  19. Boltzmann-Langevin theory of Coulomb drag

    NASA Astrophysics Data System (ADS)

    Chen, W.; Andreev, A. V.; Levchenko, A.

    2015-06-01

    We develop a Boltzmann-Langevin description of the Coulomb drag effect in clean double-layer systems with large interlayer separation d as compared to the average interelectron distance λF. Coulomb drag arises from density fluctuations with spatial scales of order d . At low temperatures, their characteristic frequencies exceed the intralayer equilibration rate of the electron liquid, and Coulomb drag may be treated in the collisionless approximation. As temperature is raised, the electron mean free path becomes short due to electron-electron scattering. This leads to local equilibration of electron liquid, and consequently drag is determined by hydrodynamic density modes. Our theory applies to both the collisionless and the hydrodynamic regimes, and it enables us to describe the crossover between them. We find that drag resistivity exhibits a nonmonotonic temperature dependence with multiple crossovers at distinct energy scales. At the lowest temperatures, Coulomb drag is dominated by the particle-hole continuum, whereas at higher temperatures of the collision-dominated regime it is governed by the plasmon modes. We observe that fast intralayer equilibration mediated by electron-electron collisions ultimately renders a stronger drag effect.

  20. Dynamical complexity changes during two forms of meditation

    NASA Astrophysics Data System (ADS)

    Li, Jin; Hu, Jing; Zhang, Yinhong; Zhang, Xiaofeng

    2011-06-01

    Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.

  1. Dynamical Baryogenesis in Complex Hybrid Inflation

    SciTech Connect

    Delepine, David; Martinez, Carlos; Urena-Lopez, L. Arturo

    2008-07-02

    We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U (1) global symmetry associated to the waterfall field charge. We show that the asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry. The latter strongly depends on the vev of the waterfall field, which is well constrained by diverse cosmological observations.

  2. Langevin processes, agent models and socio-economic systems

    NASA Astrophysics Data System (ADS)

    Richmond, Peter; Sabatelli, Lorenzo

    2004-05-01

    We review some approaches to the understanding of fluctuations of financial asset prices. Our approach builds on the development of a simple Langevin equation that characterises stochastic processes. This provides a unifying approach that allows first a straightforward description of the early approaches of Bachelier. We generalize the approach to stochastic equations that model interacting agents. The agent models recently advocated by Marsilli and Solomon are motivated. Using a simple change of variable, we show that the peer pressure model of Marsilli and the wealth dynamics model of Solomon are essentially equivalent. The methods are further shown to be consistent with a global free energy functional that invokes an entropy term based on the Boltzmann formula. There follows a brief digression on the Heston model that extends the simple model to one that, in the language of physics, exhibits a temperature this is subject to stochastic fluctuations. Mathematically the model corresponds to a Feller process. Dragulescu and Yakovenko have shown how the model yields some of the stylised features of asset prices. A more recent approach by Michael and Johnson maximised a Tsallis entropy function subject to simple constraints. They obtain a distribution function for financial returns that exhibits power law tails and which can describe the distribution of returns not only over low but also high frequencies (minute by minute) data for the Dow Jones index. We show how this approach can be developed from an agent model, where the simple Langevin process is now conditioned by local rather than global noise. Such local noise may of course be the origin of speculative frenzy or herding in the market place. The approach yields a BBGKY type hierarchy of equations for the system correlation functions. Of especial interest is that the results can be obtained from a new free energy functional similar to that mentioned above except that a Tsallis like entropy term replaces the

  3. Complex dynamics of cellular automata rule 119

    NASA Astrophysics Data System (ADS)

    Chen, Fang-Fang; Chen, Fang-Yue

    2009-03-01

    In this paper, the dynamical behaviors of cellular automata rule 119 are studied from the viewpoint of symbolic dynamics in the bi-infinite symbolic sequence space Σ2. It is shown that there exists one Bernoulli-measure global attractor of rule 119, which is also the nonwandering set of the rule. Moreover, it is demonstrated that rule 119 is topologically mixing on the global attractor and possesses the positive topological entropy. Therefore, rule 119 is chaotic in the sense of both Li-Yorke and Devaney on the global attractor. It is interesting that rule 119, a member of Wolfram’s class II which was said to be simple as periodic before, actually possesses a chaotic global attractor in Σ2. Finally, it is noted that the method presented in this work is also applicable to studying the dynamics of other rules, especially the 112 Bernoulli-shift rules therein.

  4. Description of quantum noise by a Langevin equation

    NASA Technical Reports Server (NTRS)

    Metiu, H.; Schon, G.

    1984-01-01

    General features of the quantum noise problem expressed as the equations of motion for a particle coupled to a set of oscillators are investigated analytically. Account is taken of the properties of the companion oscillators by formulating quantum statistical correlation Langevin equations (QSLE). The frequency of the oscillators is then retained as a natural cut-off for the quantum noise. The QSLE is further extended to encompass the particle trajectory and is bounded by initial and final states of the oscillator. The states are expressed as the probability of existence at the moment of particle collision that takes the oscillator into a final state. Two noise sources then exist: a statistical uncertainty of the initial state and the quantum dynamical uncertainty associated with a transition from the initial to final state. Feynman's path-integral formulation is used to characterize the functional of the particle trajectory, which slows the particle. It is shown that the energy loss may be attributed to friction, which satisfies energy conservation laws.

  5. Targeting the dynamics of complex networks

    PubMed Central

    Gutiérrez, Ricardo; Sendiña-Nadal, Irene; Zanin, Massimiliano; Papo, David; Boccaletti, Stefano

    2012-01-01

    We report on a generic procedure to steer (target) a network's dynamics towards a given, desired evolution. The problem is here tackled through a Master Stability Function approach, assessing the stability of the aimed dynamics, and through a selection of nodes to be targeted. We show that the degree of a node is a crucial element in this selection process, and that the targeting mechanism is most effective in heterogeneous scale-free architectures. This makes the proposed approach applicable to the large majority of natural and man-made networked systems. PMID:22563525

  6. Nonlinear Dynamics of the Perceived Pitch of Complex Sounds

    NASA Astrophysics Data System (ADS)

    Cartwright, Julyan H. E.; González, Diego L.; Piro, Oreste

    1999-06-01

    We apply results from nonlinear dynamics to an old problem in acoustical physics: the mechanism of the perception of the pitch of sounds, especially the sounds known as complex tones that are important for music and speech intelligibility.

  7. Dynamical origin of complex motor patterns

    NASA Astrophysics Data System (ADS)

    Alonso, L. M.; Alliende, J. A.; Mindlin, G. B.

    2010-11-01

    Behavior emerges as the nervous system generates motor patterns in charge of driving a peripheral biomechanical device. For several cases in the animal kingdom, it has been identified that the motor patterns used in order to accomplish a diversity of tasks are the different solutions of a simple, low dimensional nonlinear dynamical system. Yet, motor patterns emerge from the interaction of an enormous number of individual dynamical units. In this work, we study the dynamics of the average activity of a large set of coupled excitable units which are periodically forced. We show that low dimensional, yet non trivial dynamics emerges. As a case study, we analyze the air sac pressure patterns used by domestic canaries during song, which consists of a succession of repetitions of different syllable types. We show that the pressure patterns used to generate different syllables can be approximated by the solutions of the investigated model. In this way, we are capable of integrating different description scales of our problem.

  8. Complex dynamics and empirical evidence (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Delli Gatti, Domenico; Gaffeo, Edoardo; Giulioni, Gianfranco; Gallegati, Mauro; Kirman, Alan; Palestrini, Antonio; Russo, Alberto

    2005-05-01

    Standard macroeconomics, based on a reductionist approach centered on the representative agent, is badly equipped to explain the empirical evidence where heterogeneity and industrial dynamics are the rule. In this paper we show that a simple agent-based model of heterogeneous financially fragile agents is able to replicate a large number of scaling type stylized facts with a remarkable degree of statistical precision.

  9. Dynamics of Affective States during Complex Learning

    ERIC Educational Resources Information Center

    D'Mello, Sidney; Graesser, Art

    2012-01-01

    We propose a model to explain the dynamics of affective states that emerge during deep learning activities. The model predicts that learners in a state of engagement/flow will experience cognitive disequilibrium and confusion when they face contradictions, incongruities, anomalies, obstacles to goals, and other impasses. Learners revert into the…

  10. Mapping complex traits as a dynamic system

    NASA Astrophysics Data System (ADS)

    Sun, Lidan; Wu, Rongling

    2015-06-01

    Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a "system" in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states.

  11. Metapopulation dynamics in a complex ecological landscape.

    PubMed

    Colombo, E H; Anteneodo, C

    2015-08-01

    We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction. PMID:26382439

  12. Metapopulation dynamics in a complex ecological landscape

    NASA Astrophysics Data System (ADS)

    Colombo, E. H.; Anteneodo, C.

    2015-08-01

    We propose a general model to study the interplay between spatial dispersal and environment spatiotemporal fluctuations in metapopulation dynamics. An ecological landscape of favorable patches is generated like a Lévy dust, which allows to build a range of patterns, from dispersed to clustered ones. Locally, the dynamics is driven by a canonical model for the time evolution of the population density, consisting of a logistic expression plus multiplicative noises. Spatial coupling is introduced by means of two spreading mechanisms: diffusion and selective dispersal driven by patch suitability. We focus on the long-time population size as a function of habitat configurations, environment fluctuations, and coupling schemes. We obtain the conditions, that the spatial distribution of favorable patches and the coupling mechanisms must fulfill, to grant population survival. The fundamental phenomenon that we observe is the positive feedback between environment fluctuations and spatial spread preventing extinction.

  13. Complex dynamics in supervised work groups

    NASA Astrophysics Data System (ADS)

    Dal Forno, Arianna; Merlone, Ugo

    2013-07-01

    In supervised work groups many factors concur to determine productivity. Some of them may be economical and some psychological. According to the literature, the heterogeneity in terms of individual capacity seems to be one of the principal causes for chaotic dynamics in a work group. May sorting groups of people with same capacity for effort be a solution? In the organizational psychology literature an important factor is the engagement in the task, while expectations are central in the economics literature. Therefore, we propose a dynamical model which takes into account both engagement in the task and expectations. An important lesson emerges. The intolerance deriving from the exposure to inequity may not be only caused by differences in individual capacities, but also by these factors combined. Consequently, solutions have to be found in this new direction.

  14. Understanding the complexity of human gait dynamics

    NASA Astrophysics Data System (ADS)

    Scafetta, Nicola; Marchi, Damiano; West, Bruce J.

    2009-06-01

    Time series of human gait stride intervals exhibit fractal and multifractal properties under several conditions. Records from subjects walking at normal, slow, and fast pace speed are analyzed to determine changes in the fractal scalings as a function of the stress condition of the system. Records from subjects with different age from children to elderly and patients suffering from neurodegenerative disease are analyzed to determine changes in the fractal scalings as a function of the physical maturation or degeneration of the system. A supercentral pattern generator model is presented to simulate the above two properties that are typically found in dynamical network performance: that is, how a dynamical network responds to stress and to evolution.

  15. Dust Cloud Dynamics in Complex Plasma Afterglow

    SciTech Connect

    Layden, B.; Samarian, A. A.; Vladimirov, S. V.; Coueedel, L.

    2008-09-07

    Experimental observations of dust cloud dynamics in a RF discharge afterglow are presented. Image analysis is used to extract information from videos taken of the plasma. Estimations of the mean confining electric field have been made for different experimental conditions using a model for the contraction of the dust cloud. Dust particle trajectories in the late afterglow evidence the co-existence of positively and negatively charged dust particles.

  16. The Heterogeneous Dynamics of Economic Complexity

    PubMed Central

    Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

    2015-01-01

    What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312

  17. Complex dynamics in learning complicated games

    PubMed Central

    Galla, Tobias; Farmer, J. Doyne

    2013-01-01

    Game theory is the standard tool used to model strategic interactions in evolutionary biology and social science. Traditionally, game theory studies the equilibria of simple games. However, is this useful if the game is complicated, and if not, what is? We define a complicated game as one with many possible moves, and therefore many possible payoffs conditional on those moves. We investigate two-person games in which the players learn based on a type of reinforcement learning called experience-weighted attraction (EWA). By generating games at random, we characterize the learning dynamics under EWA and show that there are three clearly separated regimes: (i) convergence to a unique fixed point, (ii) a huge multiplicity of stable fixed points, and (iii) chaotic behavior. In case (iii), the dimension of the chaotic attractors can be very high, implying that the learning dynamics are effectively random. In the chaotic regime, the total payoffs fluctuate intermittently, showing bursts of rapid change punctuated by periods of quiescence, with heavy tails similar to what is observed in fluid turbulence and financial markets. Our results suggest that, at least for some learning algorithms, there is a large parameter regime for which complicated strategic interactions generate inherently unpredictable behavior that is best described in the language of dynamical systems theory. PMID:23297213

  18. Two critical issues in Langevin simulation of gas flows

    NASA Astrophysics Data System (ADS)

    Zhang, Jun; Fan, Jing

    2014-12-01

    A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefied gas flows. Compared with the direct simulation Monte Carlo (DSMC) method, the Langevin method is more efficient in simulating small Knudsen number flows. While it is well-known that the cell sizes and time steps should be smaller than the mean free path and the mean collision time, respectively, in DSMC simulations, the Langevin equation uses a drift term and a diffusion term to describe molecule movements, so no direct molecular collisions have to be modeled. This enables the Langevin simulation to proceed with a much larger time step than that in the DSMC method. Two critical issues in Langevin simulation are addressed in this paper. The first issue is how to reproduce the transport properties as that described by kinetic theory. Transport coefficients predicted by Langevin equation are obtained by using Green-Kubo formulae. The second issue is numerical scheme with boundary conditions. We present two schemes corresponding to small time step and large time step, respectively. For small time step, the scheme is similar to DSMC method as the update of positions and velocities are uncoupled; for large time step, we present an analytical solution of the hitting time, which is the crucial factor for accurate simulation. Velocity-Couette flow, thermal-Couette flow, Rayleigh-Bénard flow and wall-confined problem are simulated by using these two schemes. Our study shows that Langevin simulation is a promising tool to investigate small Knudsen number flows.

  19. Two critical issues in Langevin simulation of gas flows

    SciTech Connect

    Zhang, Jun; Fan, Jing

    2014-12-09

    A stochastic algorithm based on the Langevin equation has been recently proposed to simulate rarefied gas flows. Compared with the direct simulation Monte Carlo (DSMC) method, the Langevin method is more efficient in simulating small Knudsen number flows. While it is well-known that the cell sizes and time steps should be smaller than the mean free path and the mean collision time, respectively, in DSMC simulations, the Langevin equation uses a drift term and a diffusion term to describe molecule movements, so no direct molecular collisions have to be modeled. This enables the Langevin simulation to proceed with a much larger time step than that in the DSMC method. Two critical issues in Langevin simulation are addressed in this paper. The first issue is how to reproduce the transport properties as that described by kinetic theory. Transport coefficients predicted by Langevin equation are obtained by using Green-Kubo formulae. The second issue is numerical scheme with boundary conditions. We present two schemes corresponding to small time step and large time step, respectively. For small time step, the scheme is similar to DSMC method as the update of positions and velocities are uncoupled; for large time step, we present an analytical solution of the hitting time, which is the crucial factor for accurate simulation. Velocity-Couette flow, thermal-Couette flow, Rayleigh-Bénard flow and wall-confined problem are simulated by using these two schemes. Our study shows that Langevin simulation is a promising tool to investigate small Knudsen number flows.

  20. Managing Multiple Tasks in Complex, Dynamic Environments

    NASA Technical Reports Server (NTRS)

    Freed, Michael; Null, Cynthia H. (Technical Monitor)

    1998-01-01

    Sketchy planners are designed to achieve goals in realistically complex, time-pressured, and uncertain task environments. However, the ability to manage multiple, potentially interacting tasks in such environments requires extensions to the functionality these systems typically provide. This paper identifies a number of factors affecting how interacting tasks should be prioritized, interrupted, and resumed, and then describes a sketchy planner called APEX that takes account of these factors when managing multiple tasks.

  1. Understanding Learner Agency as a Complex Dynamic System

    ERIC Educational Resources Information Center

    Mercer, Sarah

    2011-01-01

    This paper attempts to contribute to a fuller understanding of the nature of language learner agency by considering it as a complex dynamic system. The purpose of the study was to explore detailed situated data to examine to what extent it is feasible to view learner agency through the lens of complexity theory. Data were generated through a…

  2. Complex, Dynamic Systems: A New Transdisciplinary Theme for Applied Linguistics?

    ERIC Educational Resources Information Center

    Larsen-Freeman, Diane

    2012-01-01

    In this plenary address, I suggest that Complexity Theory has the potential to contribute a transdisciplinary theme to applied linguistics. Transdisciplinary themes supersede disciplines and spur new kinds of creative activity (Halliday 2001 [1990]). Investigating complex systems requires researchers to pay attention to system dynamics. Since…

  3. Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

    NASA Astrophysics Data System (ADS)

    Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

    2011-09-01

    We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

  4. Path planning for complex terrain navigation via dynamic programming

    SciTech Connect

    Kwok, K.S.; Driessen, B.J.

    1998-12-31

    This work considers the problem of planning optimal paths for a mobile robot traversing complex terrain. In addition to the existing obstacles, locations in the terrain where the slope is too steep for the mobile robot to navigate safely without tipping over become mathematically equivalent to extra obstacles. To solve the optimal path problem, the authors use a dynamic programming approach. The dynamic programming approach utilized herein does not suffer the difficulties associated with spurious local minima that the artificial potential field approaches do. In fact, a globally optimal solution is guaranteed to be found if a feasible solution exists. The method is demonstrated on several complex examples including very complex terrains.

  5. Robust Integrated Neurocontroller for Complex Dynamic Systems

    NASA Technical Reports Server (NTRS)

    Zein-Sabatto, S.; Marpaka, D.; Hwang, W.

    1996-01-01

    The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are: adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as: sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system, (2) Development of a robust neurocontroller system, and 3. Integration of above systems to create a Robust Integrated Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.

  6. Robust integrated neurocontroller for complex dynamic systems

    NASA Technical Reports Server (NTRS)

    Zein-Sabbato, S.; Marpaka, D.; Hwang, W.

    1995-01-01

    The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system; (2) Development of a robust neurocontroller system, and; (3) Integration of above systems to create a robust Integration Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.

  7. Space-time complexity in Hamiltonian dynamics.

    PubMed

    Afraimovich, V; Zaslavsky, G M

    2003-06-01

    New notions of the complexity function C(epsilon;t,s) and entropy function S(epsilon;t,s) are introduced to describe systems with nonzero or zero Lyapunov exponents or systems that exhibit strong intermittent behavior with "flights," trappings, weak mixing, etc. The important part of the new notions is the first appearance of epsilon-separation of initially close trajectories. The complexity function is similar to the propagator p(t(0),x(0);t,x) with a replacement of x by the natural lengths s of trajectories, and its introduction does not assume of the space-time independence in the process of evolution of the system. A special stress is done on the choice of variables and the replacement t-->eta=ln t, s-->xi=ln s makes it possible to consider time-algebraic and space-algebraic complexity and some mixed cases. It is shown that for typical cases the entropy function S(epsilon;xi,eta) possesses invariants (alpha,beta) that describe the fractal dimensions of the space-time structures of trajectories. The invariants (alpha,beta) can be linked to the transport properties of the system, from one side, and to the Riemann invariants for simple waves, from the other side. This analog provides a new meaning for the transport exponent mu that can be considered as the speed of a Riemann wave in the log-phase space of the log-space-time variables. Some other applications of new notions are considered and numerical examples are presented. PMID:12777116

  8. Detecting complex network modularity by dynamical clustering

    NASA Astrophysics Data System (ADS)

    Boccaletti, S.; Ivanchenko, M.; Latora, V.; Pluchino, A.; Rapisarda, A.

    2007-04-01

    Based on cluster desynchronization properties of phase oscillators, we introduce an efficient method for the detection and identification of modules in complex networks. The performance of the algorithm is tested on computer generated and real-world networks whose modular structure is already known or has been studied by means of other methods. The algorithm attains a high level of precision, especially when the modular units are very mixed and hardly detectable by the other methods, with a computational effort O(KN) on a generic graph with N nodes and K links.

  9. Structural and dynamical properties of complex networks

    NASA Astrophysics Data System (ADS)

    Ghoshal, Gourab

    Recent years have witnessed a substantial amount of interest within the physics community in the properties of networks. Techniques from statistical physics coupled with the widespread availability of computing resources have facilitated studies ranging from large scale empirical analysis of the worldwide web, social networks, biological systems, to the development of theoretical models and tools to explore the various properties of these systems. Following these developments, in this dissertation, we present and solve for a diverse set of new problems, investigating the structural and dynamical properties of both model and real world networks. We start by defining a new metric to measure the stability of network structure to disruptions, and then using a combination of theory and simulation study its properties in detail on artificially generated networks; we then compare our results to a selection of networks from the real world and find good agreement in most cases. In the following chapter, we propose a mathematical model that mimics the structure of popular file-sharing websites such as Flickr and CiteULike and demonstrate that many of its properties can solved exactly in the limit of large network size. The remaining part of the dissertation primarily focuses on the dynamical properties of networks. We first formulate a model of a network that evolves under the addition and deletion of vertices and edges, and solve for the equilibrium degree distribution for a variety of cases of interest. We then consider networks whose structure can be manipulated by adjusting the rules by which vertices enter and leave the network. We focus in particular on degree distributions and show that, with some mild constraints, it is possible by a suitable choice of rules to arrange for the network to have any degree distribution we desire. In addition we define a simple local algorithm by which appropriate rules can be implemented in practice. Finally, we conclude our

  10. Collective Dynamics of Complex Plasma Bilayers

    SciTech Connect

    Hartmann, P.; Donko, Z.; Kalman, G. J.; Kyrkos, S.; Golden, K. I.; Rosenberg, M.

    2009-12-11

    A classical dusty plasma experiment was performed using two different dust grain sizes to form a strongly coupled asymmetric bilayer (two closely spaced interacting monolayers) of two species of charged dust particles. The observation and analysis of the thermally excited particle oscillations revealed the collective mode structure and dispersion (wave propagation) in this system; in particular, the existence of the theoretically predicted k=0 energy (frequency) gap was verified. Equilibrium molecular-dynamics simulations were performed to emulate the experiment, assuming Yukawa-type interparticle interaction. The simulations and analytic calculations based both on lattice summation and on the quasilocalized charge approximation approach are in good agreement with the experimental findings and help in identifying and characterizing the observed phenomena.

  11. Extremal dynamics on complex networks: Analytic solutions

    NASA Astrophysics Data System (ADS)

    Masuda, N.; Goh, K.-I.; Kahng, B.

    2005-12-01

    The Bak-Sneppen model displaying punctuated equilibria in biological evolution is studied on random complex networks. By using the rate equation and the random walk approaches, we obtain the analytic solution of the fitness threshold xc to be 1/(⟨k⟩f+1) , where ⟨k⟩f=⟨k2⟩/⟨k⟩ (=⟨k⟩) in the quenched (annealed) updating case, where ⟨kn⟩ is the nth moment of the degree distribution. Thus, the threshold is zero (finite) for the degree exponent γ<3 (γ>3) for the quenched case in the thermodynamic limit. The theoretical value xc fits well to the numerical simulation data in the annealed case only. Avalanche size, defined as the duration of successive mutations below the threshold, exhibits a critical behavior as its distribution follows a power law, Pa(s)˜s-3/2 .

  12. Dynamics of a complex streamer structure

    NASA Astrophysics Data System (ADS)

    Lehtinen, N. G.; Ostgaard, N.; Inan, U.

    2014-12-01

    Streamer corona formation and propagation is an important process in the development of lightning. In order to understand its dynamics, the streamer front velocity is calculated in a 1D model with curvature. We show that streamers may only propagate only the presence of mechanisms such as electron drift, electron diffusion and photoionization. The results indicate, in particular, that: (1) the effect of photoionization on the streamer velocity for both positive and negative streamers is mostly determined by the photoionization length, with a weaker dependence on the amount of photoionization; (2) the electron drift may increase the velocity of the negative streamers but has an opposite effect on the positive streamers; (3) the contributions of photoionization and electron diffusion to the velocity are decreased for positive curvature, i.e., convex fronts, while the contribution of electron drift is independent of curvature. These results are used in a fractal model in which the front propagation velocity is simulated as the cluster growth probability [Niemeyer et al, 1984, doi:10.1103/PhysRevLett.52.1033]. In the case when the photoionization is the main mechanism which determines the streamer propagation, the emerging transverse size of the streamers is of the order of the photoionization length, and at the larger scale the streamer structure is a fractal similar to the one obtained in a diffusion-limited aggregation system.

  13. A path integral approach to the Langevin equation

    NASA Astrophysics Data System (ADS)

    Das, Ashok K.; Panda, Sudhakar; Santos, J. R. L.

    2015-02-01

    We study the Langevin equation with both a white noise and a colored noise. We construct the Lagrangian as well as the Hamiltonian for the generalized Langevin equation which leads naturally to a path integral description from first principles. This derivation clarifies the meaning of the additional fields introduced by Martin, Siggia and Rose in their functional formalism. We show that the transition amplitude, in this case, is the generating functional for correlation functions. We work out explicitly the correlation functions for the Markovian process of the Brownian motion of a free particle as well as for that of the non-Markovian process of the Brownian motion of a harmonic oscillator (Uhlenbeck-Ornstein model). The path integral description also leads to a simple derivation of the Fokker-Planck equation for the generalized Langevin equation.

  14. Membrane associated complexes in calcium dynamics modelling

    NASA Astrophysics Data System (ADS)

    Szopa, Piotr; Dyzma, Michał; Kaźmierczak, Bogdan

    2013-06-01

    Mitochondria not only govern energy production, but are also involved in crucial cellular signalling processes. They are one of the most important organelles determining the Ca2+ regulatory pathway in the cell. Several mathematical models explaining these mechanisms were constructed, but only few of them describe interplay between calcium concentrations in endoplasmic reticulum (ER), cytoplasm and mitochondria. Experiments measuring calcium concentrations in mitochondria and ER suggested the existence of cytosolic microdomains with locally elevated calcium concentration in the nearest vicinity of the outer mitochondrial membrane. These intermediate physical connections between ER and mitochondria are called MAM (mitochondria-associated ER membrane) complexes. We propose a model with a direct calcium flow from ER to mitochondria, which may be justified by the existence of MAMs, and perform detailed numerical analysis of the effect of this flow on the type and shape of calcium oscillations. The model is partially based on the Marhl et al model. We have numerically found that the stable oscillations exist for a considerable set of parameter values. However, for some parameter sets the oscillations disappear and the trajectories of the model tend to a steady state with very high calcium level in mitochondria. This can be interpreted as an early step in an apoptotic pathway.

  15. Langevin equation model of dispersion in the convective boundary layer

    SciTech Connect

    Nasstrom, J S

    1998-08-01

    This dissertation presents the development and evaluation of a Lagrangian stochastic model of vertical dispersion of trace material in the convective boundary layer (CBL). This model is based on a Langevin equation of motion for a fluid particle, and assumes the fluid vertical velocity probability distribution is skewed and spatially homogeneous. This approach can account for the effect of large-scale, long-lived turbulent structures and skewed vertical velocity distributions found in the CBL. The form of the Langevin equation used has a linear (in velocity) deterministic acceleration and a skewed randomacceleration. For the case of homogeneous fluid velocity statistics, this ""linear-skewed" Langevin equation can be integrated explicitly, resulting in a relatively efficient numerical simulation method. It is shown that this approach is more efficient than an alternative using a "nonlinear-Gaussian" Langevin equation (with a nonlinear deterministic acceleration and a Gaussian random acceleration) assuming homogeneous turbulence, and much more efficient than alternative approaches using Langevin equation models assuming inhomogeneous turbulence. "Reflection" boundary conditions for selecting a new velocity for a particle that encounters a boundary at the top or bottom of the CBL were investigated. These include one method using the standard assumption that the magnitudes of the particle incident and reflected velocities are positively correlated, and two alternatives in which the magnitudes of these velocities are negatively correlated and uncorrelated. The constraint that spatial and velocity distributions of a well-mixed tracer must be the same as those of the fluid, was used to develop the Langevin equation models and the reflection boundary conditions. The two Langevin equation models and three reflection methods were successfully tested using cases for which exact, analytic statistical properties of particle velocity and position are known, including well

  16. Genetic Influences on Dynamic Complexity of Brain Oscillations

    PubMed Central

    Anokhin, Andrey P.; Müller, Viktor; Lindenberger, Ulman; Heath, Andrew C.; Myers, Erin

    2007-01-01

    Human electroencephalogram (EEG) consists of complex aperiodic oscillations that are assumed to indicate underlying neural dynamics such as the number and the degree of independence of oscillating neuronal networks. EEG complexity can be estimated using measures derived from non-linear dynamic systems theory. Variations in such measures have been shown to be associated with normal individual differences in cognition and some neuropsychiatric disorders. Despite the increasing use of EEG complexity measures for the study of normal and abnormal brain functioning, little is known about genetic and environmental influences on these measures. Using the pointwise dimension (PD2) algorithm, this study assessed heritability of EEG complexity at rest in a sample of 214 young female twins consisting of 51 monozygotic (MZ) and 56 dizygotic (DZ) pairs. In MZ twins, intrapair correlations were high and statistically significant; in DZ twins, correlations were substantially smaller. Genetic analyses using linear structural equation modeling revealed high and significant heritability of EEG complexity: 62–68 % in the eyes closed condition, and 46–60 % in the eyes open condition. Results suggest that individual differences in the complexity of resting electrocortical dynamics are largely determined by genetic factors. Neurophysiological mechanisms mediating genetic variation in EEG complexity may include the degree of structural connectivity and functional differentiation among cortical neuronal assemblies. PMID:16442730

  17. Diastereomerization Dynamics of a Bistridentate Ru(II) Complex.

    PubMed

    Jarenmark, Martin; Carlström, Göran; Fredin, Lisa A; Hedberg Wallenstein, Joachim; Doverbratt, Isa; Abrahamsson, Maria; Persson, Petter

    2016-03-21

    The unsymmetrical nature of a new tridentate ligand bis(quinolinyl)-1,3-pyrazole (DQPz) is exploited in a bistridentate Ru(II) complex [Ru(DQPz)2](2+) to elucidate an unexpected dynamic diastereomerism. Structural characterization based on a combination of nuclear magnetic resonance spectroscopy and density functional theory calculations reveals the first quantifiable diastereomerization dynamics for Ru complexes with fully conjugated tridentate heteroaromatic ligands. A mechanism that involves a large-scale twisting motion of the ligands is proposed to explain the dynamic interconversion between the observed diastereomers, and the analysis of both experiments and calculations reveals a potential energy landscape with a transition barrier for the diastereomerization of ∼70 kJ mol(-1). The structural flexibility demonstrated around the central transition metal ion has implications for integration of complexes into catalytic and photochemical applications. PMID:26962970

  18. Interplay between collective behavior and spreading dynamics on complex networks

    NASA Astrophysics Data System (ADS)

    Li, Kezan; Ma, Zhongjun; Jia, Zhen; Small, Michael; Fu, Xinchu

    2012-12-01

    There are certain correlations between collective behavior and spreading dynamics on some real complex networks. Based on the dynamical characteristics and traditional physical models, we construct several new bidirectional network models of spreading phenomena. By theoretical and numerical analysis of these models, we find that the collective behavior can inhibit spreading behavior, but, conversely, this spreading behavior can accelerate collective behavior. The spread threshold of spreading network is obtained by using the Lyapunov function method. The results show that an effective spreading control method is to enhance the individual awareness to collective behavior. Many real-world complex networks can be thought of in terms of both collective behavior and spreading dynamics and therefore to better understand and control such complex networks systems, our work may provide a basic framework.

  19. Complex dynamics in the Oregonator model with linear delayed feedback

    NASA Astrophysics Data System (ADS)

    Sriram, K.; Bernard, S.

    2008-06-01

    The Belousov-Zhabotinsky (BZ) reaction can display a rich dynamics when a delayed feedback is applied. We used the Oregonator model of the oscillating BZ reaction to explore the dynamics brought about by a linear delayed feedback. The time-delayed feedback can generate a succession of complex dynamics: period-doubling bifurcation route to chaos; amplitude death; fat, wrinkled, fractal, and broken tori; and mixed-mode oscillations. We observed that this dynamics arises due to a delay-driven transition, or toggling of the system between large and small amplitude oscillations, through a canard bifurcation. We used a combination of numerical bifurcation continuation techniques and other numerical methods to explore the dynamics in the strength of feedback-delay space. We observed that the period-doubling and quasiperiodic route to chaos span a low-dimensional subspace, perhaps due to the trapping of the trajectories in the small amplitude regime near the canard; and the trapped chaotic trajectories get ejected from the small amplitude regime due to a crowding effect to generate chaotic-excitable spikes. We also qualitatively explained the observed dynamics by projecting a three-dimensional phase portrait of the delayed dynamics on the two-dimensional nullclines. This is the first instance in which it is shown that the interaction of delay and canard can bring about complex dynamics.

  20. Complex dynamics in a prey predator system with multiple delays

    NASA Astrophysics Data System (ADS)

    Gakkhar, Sunita; Singh, Anuraj

    2012-02-01

    The complex dynamics is explored in a prey predator system with multiple delays. Holling type-II functional response is assumed for prey dynamics. The predator dynamics is governed by modified Leslie-Gower scheme. The existence of periodic solutions via Hopf-bifurcation with respect to both delays are established. An algorithm is developed for drawing two-parametric bifurcation diagram with respect to two delays. The domain of stability with respect to τ1 and τ2 is thus obtained. The complex dynamical behavior of the system outside the domain of stability is evident from the exhaustive numerical simulation. Direction and stability of periodic solutions are also determined using normal form theory and center manifold argument.

  1. Solution of the inverse Langevin problem for open dissipative systems with anisotropic interparticle interaction

    SciTech Connect

    Lisin, E. A.; Lisina, I. I.; Vaulina, O. S.; Petrov, O. F.

    2015-03-15

    Solution of the inverse Langevin problem is presented for open dissipative systems with anisotropic interparticle interaction. Possibility of applying this solution for experimental determining the anisotropic interaction forces between dust particles in complex plasmas with ion flow is considered. For this purpose, we have tested the method on the results of numerical simulation of chain structures of particles with quasidipole-dipole interaction, similar to the one occurring due to effects of ion focusing in gas discharges. Influence of charge spatial inhomogeneity and fluctuations on the results of recovery is also discussed.

  2. Probability in Theories With Complex Dynamics and Hardy's Fifth Axiom

    NASA Astrophysics Data System (ADS)

    Burić, Nikola

    2010-08-01

    L. Hardy has formulated an axiomatization program of quantum mechanics and generalized probability theories that has been quite influential. In this paper, properties of typical Hamiltonian dynamical systems are used to argue that there are applications of probability in physical theories of systems with dynamical complexity that require continuous spaces of pure states. Hardy’s axiomatization program does not deal with such theories. In particular Hardy’s fifth axiom does not differentiate between such applications of classical probability and quantum probability.

  3. Information processing in neural networks with the complex dynamic thresholds

    NASA Astrophysics Data System (ADS)

    Kirillov, S. Yu.; Nekorkin, V. I.

    2016-06-01

    A control mechanism of the information processing in neural networks is investigated, based on the complex dynamic threshold of the neural excitation. The threshold properties are controlled by the slowly varying synaptic current. The dynamic threshold shows high sensitivity to the rate of the synaptic current variation. It allows both to realize flexible selective tuning of the network elements and to provide nontrivial regimes of neural coding.

  4. 2D pattern evolution constrained by complex network dynamics

    NASA Astrophysics Data System (ADS)

    da Rocha, L. E. C.; Costa, L. da F.

    2007-03-01

    Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling several complex natural and artificial systems. In the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, less attention has been focused on hybrid systems, i.e. involving more than one type of network and/or dynamics. Several real systems present such an organization, e.g. the dynamics of a disease coexisting with the dynamics of the immune system. The current paper investigates a specific system involving diffusive (linear and nonlinear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erdös Rényi (ER) and Barabási Albert (BA) graph models with moveable nodes. More specifically, the complex network is expected to control, and if possible, to extinguish the diffusion of some given unwanted process (e.g. fire, oil spilling, pest dissemination, and virus or bacteria reproduction during an infection). Two types of pattern evolution are considered: Fick and Gray Scott. The nodes of the defensive network then interact with the diffusing patterns and communicate between themselves in order to control the diffusion. The main findings include the identification of higher efficiency for the BA control networks and the presence of relapses in the case of the ER model.

  5. 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. PMID:26211717

  6. 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.

  7. Dynamics of rumor-like information dissemination in complex networks

    NASA Astrophysics Data System (ADS)

    Nekovee, Maziar; Moreno, Yamir; Bianconi, Ginestra

    2005-03-01

    An important dynamic process that takes place in complex networks is the spreading of information via rumor-like mechanisms. In addition to their relevance to propagation of rumors and fads in human society, such mechanism are also the basis of an important class of collective communication protocols in complex computer networks, such as the Internet and the peer-to-peer systems. In this talk we present results of our analytical, numerical and large-scale Monte Carlo simulation studies of this process on several classes of complex networks, including random graphs, scale-free networks, and random and small-world topological graphs. Our studies point out to important differences between the dynamics of rumor spreading and that of virus spreading in such networks, and provide new insights into the complex interplay between the spreading phenomena and network topology.

  8. Experimental Investigation of Complex Dynamics of Plasma Turbulence and Transport

    NASA Astrophysics Data System (ADS)

    Gilmore, M.; Peebles, W. A.; Rhodes, T. L.; Newman, D. E.; Sanchez, R.

    2000-10-01

    Theoretical predictions of complex dynamics, such as self-organized criticality (SOC), have led to new insights into the behavior of a wide range of complex systems, such as sandpiles, evolution/extinction models and earthquake fault zones. Recently, complex dynamics have been invoked as a paradigm for understanding turbulent transport in plasmas. In particular, complex dynamical models of turbulent transport make specific predictions regarding power spectra and long range spatial and temporal correlations. In order to test the models experimentally, detailed studies utilizing probe arrays at many axial and azimuthal positions are under way in the linear Large Plasma Device at UCLA. Preliminary edge fluctuation data show frequency spectra with three distinct regions, scaling approximately as f^0, f-1, and f-4, in low, intermediate, and high frequency intervals respectively. The f-1 frequency interval decreases - eventually to zero - as the plasma is scanned from the edge to the core. These observations are consistent with a recently developed complex dynamics model that includes classical diffusion. *Supported by the National Science Foundation

  9. Nonequilibrium processes from generalized Langevin equations: Realistic nanoscale systems connected to two thermal baths

    NASA Astrophysics Data System (ADS)

    Ness, H.; Genina, A.; Stella, L.; Lorenz, C. D.; Kantorovich, L.

    2016-05-01

    We extend the generalized Langevin equation (GLE) method [L. Stella, C. D. Lorenz, and L. Kantorovich, Phys. Rev. B 89, 134303 (2014), 10.1103/PhysRevB.89.134303] to model a central classical region connected to two realistic thermal baths at two different temperatures. In such nonequilibrium conditions a heat flow is established, via the central system, in between the two baths. The GLE-2B (GLE two baths) scheme permits us to have a realistic description of both the dissipative central system and its surrounding baths. Following the original GLE approach, the extended Langevin dynamics scheme is modified to take into account two sets of auxiliary degrees of freedom corresponding to the mapping of the vibrational properties of each bath. These auxiliary variables are then used to solve the non-Markovian dissipative dynamics of the central region. The resulting algorithm is used to study a model of a short Al nanowire connected to two baths. The results of the simulations using the GLE-2B approach are compared to the results of other simulations that were carried out using standard thermostatting approaches (based on Markovian Langevin and Nosé-Hoover thermostats). We concentrate on the steady-state regime and study the establishment of a local temperature profile within the system. The conditions for obtaining a flat profile or a temperature gradient are examined in detail, in agreement with earlier studies. The results show that the GLE-2B approach is able to treat, within a single scheme, two widely different thermal transport regimes, i.e., ballistic systems, with no temperature gradient, and diffusive systems with a temperature gradient.

  10. Converting PSO dynamics into complex network - Initial study

    NASA Astrophysics Data System (ADS)

    Pluhacek, Michal; Janostik, Jakub; Senkerik, Roman; Zelinka, Ivan

    2016-06-01

    In this paper it is presented the initial study on the possibility of capturing the inner dynamic of Particle Swarm Optimization algorithm into a complex network structure. Inspired in previous works there are two different approaches for creating the complex network presented in this paper. Visualizations of the networks are presented and commented. The possibilities for future applications of the proposed design are given in detail.

  11. Characterizing the Dynamics of Proteasome Complexes by Proteomics Approaches

    PubMed Central

    Kaake, Robyn M.; Kao, Athit; Yu, Clinton

    2014-01-01

    Abstract Significance: The proteasome is the degradation machine of the ubiquitin-proteasome system, which is critical in controlling many essential biological processes. Aberrant regulation of proteasome-dependent protein degradation can lead to various human diseases, and general proteasome inhibitors have shown efficacy for cancer treatments. Though clinically effective, current proteasome inhibitors have detrimental side effects and, thus, better therapeutic strategies targeting proteasomes are needed. Therefore, a comprehensive characterization of proteasome complexes will provide the molecular details that are essential for developing new and improved drugs. Recent Advances: New mass spectrometry (MS)-based proteomics approaches have been developed to study protein interaction networks and structural topologies of proteasome complexes. The results have helped define the dynamic proteomes of proteasome complexes, thus providing new insights into the mechanisms underlying proteasome function and regulation. Critical Issues: The proteasome exists as heterogeneous populations in tissues/cells, and its proteome is highly dynamic and complex. In addition, proteasome complexes are regulated by various mechanisms under different physiological conditions. Consequently, complete proteomic profiling of proteasome complexes remains a major challenge for the field. Future Directions: We expect that proteomic methodologies enabling full characterization of proteasome complexes will continue to evolve. Further advances in MS instrumentation and protein separation techniques will be needed to facilitate the detailed proteomic analysis of low-abundance components and subpopulations of proteasome complexes. The results will help us understand proteasome biology as well as provide new therapeutic targets for disease diagnostics and treatment. Antioxid. Redox Signal. 21, 2444–2456. PMID:24423446

  12. Complexity and dynamism from an urban health perspective: a rationale for a system dynamics approach.

    PubMed

    Tozan, Yesim; Ompad, Danielle C

    2015-06-01

    In a variety of urban health frameworks, cities are conceptualized as complex and dynamic yet commonly used epidemiological methods have failed to address this complexity and dynamism head on due to their narrow problem definitions and linear analytical representations. Scholars from a variety of disciplines have also long conceptualized cities as systems, but few have modeled urban health issues as problems within a system. Systems thinking in general and system dynamics in particular are relatively new approaches in public health, but ones that hold immense promise as methodologies to model and analyze the complexity underlying urban processes to effectively inform policy actions in dynamic environments. This conceptual essay reviews the utility of applying the concepts, principles, and methods of systems thinking to the study of complex urban health phenomena as a complementary approach to standard epidemiological methods using specific examples and provides recommendations on how to better incorporate systems thinking methods in urban health research and practice. PMID:25952137

  13. Langevin Theory of Anomalous Brownian Motion Made Simple

    ERIC Educational Resources Information Center

    Tothova, Jana; Vasziova, Gabriela; Glod, Lukas; Lisy, Vladimir

    2011-01-01

    During the century from the publication of the work by Einstein (1905 "Ann. Phys." 17 549) Brownian motion has become an important paradigm in many fields of modern science. An essential impulse for the development of Brownian motion theory was given by the work of Langevin (1908 "C. R. Acad. Sci.", Paris 146 530), in which he proposed an…

  14. Langevin equation approach to granular flow in a narrow pipe

    SciTech Connect

    Riethmueller, T.; Schimansky-Geier, L.; Rosenkranz, D.; Poeschel, T.

    1997-01-01

    The gravity-driven flow of granular material through a rough, narrow vertical pipe is described using the Langevin equation formalism. Above a critical particle density the homogeneous flow becomes unstable with respect to short-wave length perturbations. In correspondence with experimental observations, we find clogging and density waves in the flowing material.

  15. Applications of dynamical complexity theory in traditional Chinese medicine.

    PubMed

    Ma, Yan; Sun, Shuchen; Peng, Chung-Kang

    2014-09-01

    Traditional Chinese medicine (TCM) has been gradually accepted by the world. Despite its widespread use in clinical settings, a major challenge in TCM is to study it scientifically. This difficulty arises from the fact that TCM views human body as a complex dynamical system, and focuses on the balance of the human body, both internally and with its external environment. As a result, conventional tools that are based on reductionist approach are not adequate. Methods that can quantify the dynamics of complex integrative systems may bring new insights and utilities about the clinical practice and evaluation of efficacy of TCM. The dynamical complexity theory recently proposed and its computational algorithm, Multiscale Entropy (MSE) analysis, are consistent with TCM concepts. This new system level analysis has been successfully applied to many health and disease related topics in medicine. We believe that there could be many promising applications of this dynamical complexity concept in TCM. In this article, we propose some promising applications and research areas that TCM practitioners and researchers can pursue. PMID:25204292

  16. Crossover behavior of multiscale fluctuations in Big Data: Langevin model and substorm time-scales in Earth's magnetosphere

    NASA Astrophysics Data System (ADS)

    Sharma, A. S.; Setty, V. A.

    2015-12-01

    Multiscale fluctuations in large and complex data are usually characterized by a power law with a scaling exponent but many systems require more than one exponent and thus exhibit crossover behavior. The scaling exponents, such as Hurst exponents, represent the nature of correlation in the system and the crossover shows the presence of more than one type of correlation. An accurate characterization of the crossover behavior is thus needed for a better understanding of the inherent correlations in the system, and is an important method of Big Data analysis. A multi-step process is developed for accurate computation of the crossover behavior. First the detrended fluctuation analysis is used to remove the trends in the data and the scaling exponents are computed. The crossover point is then computed by a Hyperbolic regression technique, with no prior assumptions. The time series data of the magnetic field variations during substorms in the Earth's magnetosphere is analyzed with these techniques and yields a crossover behavior with a time scale of ~4 hrs. A Langevin model derived from the data provides an excellent fit to the crossover in the scaling exponents and a good model of magnetospheric dynamics. The combination of fluctuation analysis and mathematical modeling thus yields a comprehensive approach in the analysis of Big Data.

  17. Dynamics and Control in Complex Transition Metal Oxides

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Averitt, R. D.

    2014-07-01

    Advances in the synthesis, growth, and characterization of complex transition metal oxides coupled with new experimental techniques in ultrafast optical spectroscopy have ushered in an exciting era of dynamics and control in these materials. Experiments utilizing femtosecond optical pulses can initiate and probe dynamics of the spin, lattice, orbital, and charge degrees of freedom. Major goals include (a) determining how interaction and competition between the relevant degrees of freedom determine macroscopic functionality in transition metal oxides (TMOs) and (b) searching for hidden phases in TMOs by controlling dynamic trajectories in a complex and pliable energy landscape. Advances in creating intense pulses from the far-IR spectrum through the visible spectrum enable mode-selective excitation to facilitate exploration of these possibilities. This review covers recent developments in this emerging field and presents examples that include the cuprates, manganites, and vanadates.

  18. Complex systems dynamics in aging: new evidence, continuing questions.

    PubMed

    Cohen, Alan A

    2016-02-01

    There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity. PMID:25991473

  19. Nonlinear Dynamics of Complex Coevolutionary Systems in Historical Times

    NASA Astrophysics Data System (ADS)

    Perdigão, Rui A. P.

    2016-04-01

    A new theoretical paradigm for statistical-dynamical modeling of complex coevolutionary systems is introduced, with the aim to provide historical geoscientists with a practical tool to analyse historical data and its underlying phenomenology. Historical data is assumed to represent the history of dynamical processes of physical and socio-economic nature. If processes and their governing laws are well understood, they are often treated with traditional dynamical equations: deterministic approach. If the governing laws are unknown or impracticable, the process is often treated as if being random (even if it is not): statistical approach. Although single eventful details - such as the exact spatiotemporal structure of a particular hydro-meteorological incident - may often be elusive to a detailed analysis, the overall dynamics exhibit group properties summarized by a simple set of categories or dynamical regimes at multiple scales - from local short-lived convection patterns to large-scale hydro-climatic regimes. The overwhelming microscale complexity is thus conveniently wrapped into a manageable group entity, such as a statistical distribution. In a stationary setting whereby the distribution is assumed to be invariant, alternating regimes are approachable as dynamical intermittence. For instance, in the context of bimodal climatic oscillations such as NAO and ENSO, each mode corresponds to a dynamical regime or phase. However, given external forcings or longer-term internal variability and multiscale coevolution, the structural properties of the system may change. These changes in the dynamical structure bring about a new distribution and associated regimes. The modes of yesteryear may no longer exist as such in the new structural order of the system. In this context, aside from regime intermittence, the system exhibits structural regime change. New oscillations may emerge whilst others fade into the annals of history, e.g. particular climate fluctuations during

  20. Molecular dynamics studies of U1A-RNA complexes.

    PubMed Central

    Reyes, C M; Kollman, P A

    1999-01-01

    The U1A protein binds to a hairpin RNA and an internal-loop RNA with picomolar affinities. To probe the molecular basis of U1A binding, we performed state-of-the-art nanosecond molecular dynamics simulations on both complexes. The good agreement with experimental structures supports the protocols used in the simulations. We compare the dynamics, hydrogen-bonding occupancies, and interfacial flexibility of both complexes and also describe a rigid-body motion in the U1A-internal loop complex that is not observed in the U1A-hairpin simulation. We relate these observations to experimental mutational studies and highlight their significance in U1A binding affinity and specificity. PMID:10024175

  1. Polyacrylic acids-bovine serum albumin complexation: Structure and dynamics.

    PubMed

    Othman, Mohamed; Aschi, Adel; Gharbi, Abdelhafidh

    2016-01-01

    The study of the mixture of BSA with polyacrylic acids at different masses versus pH allowed highlighting the existence of two regimes of weak and strong complexation. These complexes were studied in diluted regime concentration, by turbidimetry, dynamic light scattering (DLS), zeta-potential measurements and nuclear magnetic resonance (NMR). We have followed the pH effect on the structure and properties of the complex. This allowed refining the interpretation of the phase diagram and understanding the observed phenomena. The NMR measurements allowed probing the dynamics of the constituents versus the pH. The computational method was used to precisely determine the electrostatic potential of BSA and how the polyelectrolyte binds to it at different pH. PMID:26478316

  2. Complexity analysis and parameter estimation of dynamic metabolic systems.

    PubMed

    Tian, Li-Ping; Shi, Zhong-Ke; Wu, Fang-Xiang

    2013-01-01

    A metabolic system consists of a number of reactions transforming molecules of one kind into another to provide the energy that living cells need. Based on the biochemical reaction principles, dynamic metabolic systems can be modeled by a group of coupled differential equations which consists of parameters, states (concentration of molecules involved), and reaction rates. Reaction rates are typically either polynomials or rational functions in states and constant parameters. As a result, dynamic metabolic systems are a group of differential equations nonlinear and coupled in both parameters and states. Therefore, it is challenging to estimate parameters in complex dynamic metabolic systems. In this paper, we propose a method to analyze the complexity of dynamic metabolic systems for parameter estimation. As a result, the estimation of parameters in dynamic metabolic systems is reduced to the estimation of parameters in a group of decoupled rational functions plus polynomials (which we call improper rational functions) or in polynomials. Furthermore, by taking its special structure of improper rational functions, we develop an efficient algorithm to estimate parameters in improper rational functions. The proposed method is applied to the estimation of parameters in a dynamic metabolic system. The simulation results show the superior performance of the proposed method. PMID:24233242

  3. Generalized Langevin equation with colored noise description of the stochastic oscillations of accretion disks

    NASA Astrophysics Data System (ADS)

    Harko, Tiberiu; Leung, Chun Sing; Mocanu, Gabriela

    2014-05-01

    We consider a description of the stochastic oscillations of the general relativistic accretion disks around compact astrophysical objects interacting with their external medium based on a generalized Langevin equation with colored noise and on the fluctuation-dissipation theorems. The former accounts for the general memory and retarded effects of the frictional force. The presence of the memory effects influences the response of the disk to external random interactions, and it modifies the dynamical behavior of the disk, as well as the energy dissipation processes. The generalized Langevin equation of the motion of the disk in the vertical direction is studied numerically, and the vertical displacements, velocities, and luminosities of the stochastically perturbed disks are explicitly obtained for both the Schwarzschild and the Kerr cases. The power spectral distribution of the disk luminosity is also obtained. As a possible astrophysical application of the formalism we investigate the possibility that the intra-day variability of the active galactic nuclei may be due to the stochastic disk instabilities. The perturbations due to colored/nontrivially correlated noise induce a complicated disk dynamics, which could explain some astrophysical observational features related to disk variability.

  4. Scattering studies of molecular dynamics of complex fluids

    NASA Astrophysics Data System (ADS)

    Liao, Ciya

    The dynamics of complex fluids is studied by modeling the spectrum of density fluctuation: dynamic structure factor. The theoretic models are compared with experimental measurements by X-ray and molecular dynamics simulation results. In time scale, the dynamics of supercooled water can be well separated into short time and long time dynamics. While the long time dynamics is modeled well by a stretch exponential and explained as cage relaxations by mode coupling theory, the short time dynamics is under study in this thesis. We introduce two models for the short time dynamics. One model assumes that the short time movement of particles inside a cage is in a harmonic potential well with a vibrational frequency distribution function having a two-peak structure. The relationship of density of state with the single particle dynamic structure factor is employed to formulate the model. The other model treats the in-cage rattlings as collisions between hard sphere particles which can be modeled by a kinetic theory. A modification of the kinetic theory has to be used to account for the cage effect on the short time dynamics. The idea that the short time dynamics can be considered separately from long time dynamics is verified by the potential landscape view. The inherent structure which is defined as a local minimum in the potential function varies from time to time as the result of the crossing- basin of system in the potential landscape. The within basin movement regarded as short time rattlings can be eliminated by calculating the intermediate scattering function of the inherent structure, which shows an almost identical behavior as the long time part of original intermediate scattering function. A recent development of high resolution inelastic X-ray scattering technique brings a challenge on how to deal with the form factors of different atoms in the explanation of the measured dynamic structure factor. A generalized dynamic structure factor is defined to include the

  5. Laser altimetry reveals complex pattern of Greenland Ice Sheet dynamics.

    PubMed

    Csatho, Beata M; Schenk, Anton F; van der Veen, Cornelis J; Babonis, Gregory; Duncan, Kyle; Rezvanbehbahani, Soroush; van den Broeke, Michiel R; Simonsen, Sebastian B; Nagarajan, Sudhagar; van Angelen, Jan H

    2014-12-30

    We present a new record of ice thickness change, reconstructed at nearly 100,000 sites on the Greenland Ice Sheet (GrIS) from laser altimetry measurements spanning the period 1993-2012, partitioned into changes due to surface mass balance (SMB) and ice dynamics. We estimate a mean annual GrIS mass loss of 243 ± 18 Gt ⋅ y(-1), equivalent to 0.68 mm ⋅ y(-1) sea level rise (SLR) for 2003-2009. Dynamic thinning contributed 48%, with the largest rates occurring in 2004-2006, followed by a gradual decrease balanced by accelerating SMB loss. The spatial pattern of dynamic mass loss changed over this time as dynamic thinning rapidly decreased in southeast Greenland but slowly increased in the southwest, north, and northeast regions. Most outlet glaciers have been thinning during the last two decades, interrupted by episodes of decreasing thinning or even thickening. Dynamics of the major outlet glaciers dominated the mass loss from larger drainage basins, and simultaneous changes over distances up to 500 km are detected, indicating climate control. However, the intricate spatiotemporal pattern of dynamic thickness change suggests that, regardless of the forcing responsible for initial glacier acceleration and thinning, the response of individual glaciers is modulated by local conditions. Recent projections of dynamic contributions from the entire GrIS to SLR have been based on the extrapolation of four major outlet glaciers. Considering the observed complexity, we question how well these four glaciers represent all of Greenland's outlet glaciers. PMID:25512537

  6. How vegetation patterning affects sediment dynamics in complex landscapes

    NASA Astrophysics Data System (ADS)

    Baartman, Jantiene; Temme, Arnaud; Saco, Patricia

    2016-04-01

    Semi-arid ecosystems are often spatially self-organized in typical patterns of vegetation bands with high plant cover interspersed with bare soil areas, also known as 'tigerbush'. Tigerbush dynamics have been studied using model simulations on flat synthetic landscapes, although in some cases straight slopes were used. The feedbacks between vegetation and more realistic and complex landscapes have not been studied yet, even though these landscapes are much more prevalent. Hence, our objective was to determine the effect of landform variation on vegetation patterning and sediment dynamics. We linked two existing models that simulate (a) plant growth, death and dispersal of vegetation, and (b) erosion and sedimentation. The model was calibrated on a straight planar hillslope and then applied to (i) a set of synthetic but more complex topographies and (ii) three real-world landscapes. Furthermore, sediment dynamics were evaluated by comparing simulated sediment output with and without vegetation dynamics. Results show banded vegetation patterning on all synthetic topographies, always perpendicular to the slope gradient. For real topographies, banded vegetation was simulated in the relatively flat, rolling landscape and in the dissected landscape when slopes were gentle. In the steep dissected landscape and the alluvial fan, vegetation was simulated to grow in local depressions where moisture is present whereas hilltops were bare. Including vegetation dynamics resulted in significantly less simulated erosion and relatively more deposition compared to simulations with uniformly distributed vegetation.

  7. Control of complex networks requires both structure and dynamics.

    PubMed

    Gates, Alexander J; Rocha, Luis M

    2016-01-01

    The study of network structure has uncovered signatures of the organization of complex systems. However, there is also a need to understand how to control them; for example, identifying strategies to revert a diseased cell to a healthy state, or a mature cell to a pluripotent state. Two recent methodologies suggest that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics: structural controllability and minimum dominating sets. We demonstrate that such structure-only methods fail to characterize controllability when dynamics are introduced. We study Boolean network ensembles of network motifs as well as three models of biochemical regulation: the segment polarity network in Drosophila melanogaster, the cell cycle of budding yeast Saccharomyces cerevisiae, and the floral organ arrangement in Arabidopsis thaliana. We demonstrate that structure-only methods both undershoot and overshoot the number and which sets of critical variables best control the dynamics of these models, highlighting the importance of the actual system dynamics in determining control. Our analysis further shows that the logic of automata transition functions, namely how canalizing they are, plays an important role in the extent to which structure predicts dynamics. PMID:27087469

  8. Control of complex networks requires both structure and dynamics

    PubMed Central

    Gates, Alexander J.; Rocha, Luis M.

    2016-01-01

    The study of network structure has uncovered signatures of the organization of complex systems. However, there is also a need to understand how to control them; for example, identifying strategies to revert a diseased cell to a healthy state, or a mature cell to a pluripotent state. Two recent methodologies suggest that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics: structural controllability and minimum dominating sets. We demonstrate that such structure-only methods fail to characterize controllability when dynamics are introduced. We study Boolean network ensembles of network motifs as well as three models of biochemical regulation: the segment polarity network in Drosophila melanogaster, the cell cycle of budding yeast Saccharomyces cerevisiae, and the floral organ arrangement in Arabidopsis thaliana. We demonstrate that structure-only methods both undershoot and overshoot the number and which sets of critical variables best control the dynamics of these models, highlighting the importance of the actual system dynamics in determining control. Our analysis further shows that the logic of automata transition functions, namely how canalizing they are, plays an important role in the extent to which structure predicts dynamics. PMID:27087469

  9. Molecular dynamics simulation of complex plasmas: interaction of nonlinear waves

    NASA Astrophysics Data System (ADS)

    Durniak, Celine; Samsonov, Dmitry

    2008-11-01

    Complex plasmas consist of micron sized microspheres immersed into ordinary ion-electron plasmas. They exist in solid, liquid, gaseous states and exhibit a range of dynamic phenomena such as waves, solitons, phase transitions, heat transfer. These phenomena can be modelled in complex plasmas at the microscopic or ``molecular'' scale, which is almost impossible in ordinary solids and liquids. We simulate a monolayer complex plasma consisting of 3000 negatively-charged particles (or grains) with the help of molecular dynamics computer simulations. The equations of grain motion are solved using a 5^th order Runge Kutta method taking into account interaction of every grain with each other via a Yukawa potential. The grains are confined more strongly in the vertical direction than in the horizontal. After seeding the grains randomly the code is run until the equilibrium is reached as the grain kinetics energy reduces due to damping force equal to the neutral friction in the experiments and a monolayer crystal lattice is formed. Then we investigate interactions between nonlinear waves in a monolayer strongly coupled complex plasma moving in three dimensions. Different excitations are applied during a short time symmetrically on both sides of the lattice. Structural properties and nonlinear waves characteristics are examined as the pulses propagate across the complex plasma in opposite directions.

  10. Practical synchronization on complex dynamical networks via optimal pinning control.

    PubMed

    Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

    2015-07-01

    We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications. PMID:26274112

  11. Dynamic subcellular localization of a respiratory complex controls bacterial respiration

    PubMed Central

    Alberge, François; Espinosa, Leon; Seduk, Farida; Sylvi, Léa; Toci, René; Walburger, Anne; Magalon, Axel

    2015-01-01

    Respiration, an essential process for most organisms, has to optimally respond to changes in the metabolic demand or the environmental conditions. The branched character of their respiratory chains allows bacteria to do so by providing a great metabolic and regulatory flexibility. Here, we show that the native localization of the nitrate reductase, a major respiratory complex under anaerobiosis in Escherichia coli, is submitted to tight spatiotemporal regulation in response to metabolic conditions via a mechanism using the transmembrane proton gradient as a cue for polar localization. These dynamics are critical for controlling the activity of nitrate reductase, as the formation of polar assemblies potentiates the electron flux through the complex. Thus, dynamic subcellular localization emerges as a critical factor in the control of respiration in bacteria. DOI: http://dx.doi.org/10.7554/eLife.05357.001 PMID:26077726

  12. Critical dynamic approach to stationary states in complex systems

    NASA Astrophysics Data System (ADS)

    Rozenfeld, A. F.; Laneri, K.; Albano, E. V.

    2007-04-01

    A dynamic scaling Ansatz for the approach to stationary states in complex systems is proposed and tested by means of extensive simulations applied to both the Bak-Sneppen (BS) model, which exhibits robust Self-Organised Critical (SOC) behaviour, and the Game of Life (GOL) of J. Conway, whose critical behaviour is under debate. Considering the dynamic scaling behaviour of the density of sites (ρ(t)), it is shown that i) by starting the dynamic measurements with configurations such that ρ(t=0) →0, one observes an initial increase of the density with exponents θ= 0.12(2) and θ= 0.11(2) for the BS and GOL models, respectively; ii) by using initial configurations with ρ(t=0) →1, the density decays with exponents δ= 0.47(2) and δ= 0.28(2) for the BS and GOL models, respectively. It is also shown that the temporal autocorrelation decays with exponents Ca = 0.35(2) (Ca = 0.35(5)) for the BS (GOL) model. By using these dynamically determined critical exponents and suitable scaling relationships, we also obtain the dynamic exponents z = 2.10(5) (z = 2.10(5)) for the BS (GOL) model. Based on this evidence we conclude that the dynamic approach to stationary states of the investigated models can be described by suitable power-law functions of time with well-defined exponents.

  13. Structure and dynamics of small van der Waals complexes

    SciTech Connect

    Loreau, J.

    2014-10-06

    We illustrate computational aspects of the calculation of the potential energy surfaces of small (up to five atoms) van der Waals complexes with high-level quantum chemistry techniques such as the CCSD(T) method with extended basis sets. We discuss the compromise between the required accuracy and the computational time. Further, we show how these potential energy surfaces can be fitted and used in dynamical calculations such as non-reactive inelastic scattering.

  14. E-Index for Differentiating Complex Dynamic Traits

    PubMed Central

    Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

    2016-01-01

    While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292

  15. Topics in Complexity: Dynamical Patterns in the Cyberworld

    NASA Astrophysics Data System (ADS)

    Qi, Hong

    Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

  16. Quantifying spatiotemporal complexity of cardiac dynamics using ordinal patterns.

    PubMed

    Schlemmer, Alexander; Berg, Sebastian; Shajahan, T K; Luther, Stefan; Parlitz, Ulrich

    2015-08-01

    Analyzing the dynamics of complex excitation wave patterns in cardiac tissue plays a key role for understanding the origin of life-threatening arrhythmias and for devising novel approaches to control them. The quantification of spatiotemporal complexity, however, remains a challenging task. This holds in particular for the analysis of data from fluorescence imaging (optical mapping), which allows for the measurement of membrane potential and intracellular calcium at high spatial and temporal resolution. Hitherto methods, like dominant frequency maps and the analysis of phase singularities, address important aspects of cardiac dynamics, but they consider very specific properties of excitable media, only. This article focuses on the benchmark of spatial complexity measures over time in the context of cardiac cell cultures. Standard Shannon Entropy and Spatial Permutation Entropy, an adaption of [1], have been implemented and applied to optical mapping data from embryonic chicken cell culture experiments. We introduce spatial separation of samples when generating ordinal patterns and show its importance for Spatial Permutation Entropy. Results suggest that Spatial Permutation Entropies provide a robust and interpretable measure for detecting qualitative changes in the dynamics of this excitable medium. PMID:26737183

  17. Human opinion dynamics: An inspiration to solve complex optimization problems

    NASA Astrophysics Data System (ADS)

    Kaur, Rishemjit; Kumar, Ritesh; Bhondekar, Amol P.; Kapur, Pawan

    2013-10-01

    Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making.

  18. Human opinion dynamics: An inspiration to solve complex optimization problems

    PubMed Central

    Kaur, Rishemjit; Kumar, Ritesh; Bhondekar, Amol P.; Kapur, Pawan

    2013-01-01

    Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making. PMID:24141795

  19. Stochastic modeling of driver behavior by Langevin equations

    NASA Astrophysics Data System (ADS)

    Langner, Michael; Peinke, Joachim

    2015-06-01

    A procedure based on stochastic Langevin equations is presented and shows how a stochastic model of driver behavior can be estimated directly from given data. The Langevin analysis allows the separation of a given data-set into a stochastic diffusion- and a deterministic drift field. Form the drift field a potential can be derived. In particular the method is here applied on driving data from a simulator. We overcome typical problems like varying sampling rates, low noise levels, low data amounts, inefficient coordinate systems, and non-stationary situations. From the estimation of the drift- and diffusion vector-fields derived from the data, we show different ways how to set up Monte-Carlo simulations for the driver behavior.

  20. SELF-CONSISTENT LANGEVIN SIMULATION OF COULOMB COLLISIONS IN CHARGED-PARTICLE BEAMS

    SciTech Connect

    J. QIANG; R. RYNE; S. HABIB

    2000-05-01

    In many plasma physics and charged-particle beam dynamics problems, Coulomb collisions are modeled by a Fokker-Planck equation. In order to incorporate these collisions, we present a three-dimensional parallel Langevin simulation method using a Particle-In-Cell (PIC) approach implemented on high-performance parallel computers. We perform, for the first time, a fully self-consistent simulation, in which the friction and diffusion coefficients are computed from first principles. We employ a two-dimensional domain decomposition approach within a message passing programming paradigm along with dynamic load balancing. Object oriented programming is used to encapsulate details of the communication syntax as well as to enhance reusability and extensibility. Performance tests on the SGI Origin 2000 and the Cray T3E-900 have demonstrated good scalability. Work is in progress to apply our technique to intrabeam scattering in accelerators.

  1. Complex elaboration: making sense of meiotic cohesin dynamics

    PubMed Central

    Rankin, Susannah

    2015-01-01

    In mitotically dividing cells, the cohesin complex tethers sister chromatids, the products of DNA replication, together from the time they are generated during S phase until anaphase. Cohesion between sister chromatids ensures accurate chromosome segregation, and promotes normal gene regulation and certain kinds of DNA repair. In somatic cells, the core cohesin complex is composed of four subunits: Smc1, Smc3, Rad21 and an SA subunit. During meiotic cell divisions meiosis-specific isoforms of several of the cohesin subunits are also expressed and incorporated into distinct meiotic cohesin complexes. The relative contributions of these meiosis-specific forms of cohesin to chromosome dynamics during meiotic progression have not been fully worked out. However, the localization of these proteins during chromosome pairing and synapsis, and their unique loss-of-function phenotypes, suggest non-overlapping roles in controlling meiotic chromosome behavior. Many of the proteins that regulate cohesin function during mitosis also appear to regulate cohesin during meiosis. Here we review how cohesin contributes to meiotic chromosome dynamics, and explore similarities and differences between cohesin regulation during the mitotic cell cycle and meiotic progression. A deeper understanding of the regulation and function of cohesin in meiosis will provide important new insights into how the cohesin complex is able to promote distinct kinds of chromosome interactions under diverse conditions. PMID:25895170

  2. Intranuclear dynamics of the Nup107-160 complex

    PubMed Central

    Morchoisne-Bolhy, Stéphanie; Geoffroy, Marie-Claude; Bouhlel, Imène B.; Alves, Annabelle; Audugé, Nicolas; Baudin, Xavier; Van Bortle, Kevin; Powers, Maureen A.; Doye, Valérie

    2015-01-01

    Nup98 is a glycine-leucine-phenylalanine-glycine (GLFG) repeat–containing nucleoporin that, in addition to nuclear transport, contributes to multiple aspects of gene regulation. Previous studies revealed its dynamic localization within intranuclear structures known as GLFG bodies. Here we show that the mammalian Nup107-160 complex (Y-complex), a major scaffold module of the nuclear pore, together with its partner Elys, colocalizes with Nup98 in GLFG bodies. The frequency and size of GLFG bodies vary among HeLa sublines, and we find that an increased level of Nup98 is associated with the presence of bodies. Recruitment of the Y-complex and Elys into GLFG bodies requires the C-terminal domain of Nup98. During cell division, Y-Nup–containing GLFG bodies are disassembled in mitotic prophase, significantly ahead of nuclear pore disassembly. FRAP studies revealed that, unlike at nuclear pores, the Y-complex shuttles into and out of GLFG bodies. Finally, we show that within the nucleoplasm, a fraction of Nup107, a key component of the Y-complex, displays reduced mobility, suggesting interaction with other nuclear components. Together our data uncover a previously neglected intranuclear pool of the Y-complex that may underscore a yet-uncharacterized function of these nucleoporins inside the nucleus, even in cells that contain no detectable GLFG bodies. PMID:25904327

  3. Complexity and network dynamics in physiological adaptation: an integrated view.

    PubMed

    Baffy, György; Loscalzo, Joseph

    2014-05-28

    Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. PMID:24751342

  4. Universality of flux-fluctuation law in complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Zhou, Zhao; Huang, Zi-Gang; Huang, Liang; Lai, Ying-Cheng; Yang, Lei; Xue, De-Sheng

    2013-01-01

    Recent work has revealed a law governing flux fluctuation and the average flux in complex dynamical systems. We establish the universality of this flux-fluctuation law through the following steps: (i) We derive the law in a more general setting, showing that it depends on a single parameter characterizing the external driving; (ii) we conduct extensive numerical computations using distinct external driving, different network topologies, and multiple traffic routing strategies; and (iii) we analyze data from an actual vehicle traffic system in a major city in China to lend more credence to the universality of the flux-fluctuation law. Additional factors considered include flux fluctuation on links, window size effect, and hidden topological structures such as nodal degree correlation. Besides its fundamental importance in complex systems, the flux-fluctuation law can be used to infer certain intrinsic property of the system for potential applications such as control of complex systems for improved performance.

  5. Langevin equation approach to reactor noise analysis: stochastic transport equation

    SciTech Connect

    Akcasu, A.Z. ); Stolle, A.M. )

    1993-01-01

    The application of the Langevin equation method to the study of fluctuations in the space- and velocity-dependent neutron density as well as in the detector outputs in nuclear reactors is presented. In this case, the Langevin equation is the stochastic linear neutron transport equation with a space- and velocity-dependent random neutron source, often referred to as the noise equivalent source (NES). The power spectral densities (PSDs) of the NESs in the transport equation, as well as in the accompanying detection rate equations, are obtained, and the cross- and auto-power spectral densities of the outputs of pairs of detectors are explicitly calculated. The transport-level expression for the R([omega]) ratio measured in the [sup 252]Cf source-driven noise analysis method is also derived. Finally, the implementation of the Langevin equation approach at different levels of approximation is discussed, and the stochastic one-speed transport and one-group P[sub 1] equations are derived by first integrating the stochastic transport equation over speed and then eliminating the angular dependence by a spherical harmonics expansion. By taking the large transport rate limit in the P[sub 1] description, the stochastic diffusion equation is obtained as well as the PSD of the NES in it. This procedure also leads directly to the stochastic Fick's law.

  6. Dynamically reconfigurable complex emulsions via tunable interfacial tensions

    PubMed Central

    Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.

    2015-01-01

    Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including multiple emulsions and Janus droplets which contain hemispheres of differing material, are of increasing importance1 in pharmaceuticals and medical diagnostics2, in the fabrication of microparticles and capsules3–5 for food6, in chemical separations7, in cosmetics8, and in dynamic optics9. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets’ physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes10, to small-volume but more precise microfluidic methods11,12. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have greatly increased utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of

  7. Dynamically reconfigurable complex emulsions via tunable interfacial tensions

    NASA Astrophysics Data System (ADS)

    Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.

    2015-02-01

    Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including Janus droplets (that is, droplets with faces of differing chemistries) and multiple emulsions, are of increasing importance in pharmaceuticals and medical diagnostics, in the fabrication of microparticles and capsules for food, in chemical separations, in cosmetics, and in dynamic optics. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets' physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes, to small-volume but more precise microfluidic methods. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have great utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with

  8. Langevin Simulation of Microstructure in Martensitic Transformations

    NASA Astrophysics Data System (ADS)

    Wu, Y.; Lookman, T.; Shenoy, S. R.; Saxena, A.; Bishop, A. R.

    1996-03-01

    We present a dynamical model to simulate microstructure in martensitic transformations within the context of shape memory alloys. The Hamiltonian of the system includes a triple-well potential (φ^6 model) in local shear strain, (2) strain gradient terms up to second order in strain and fourth order in gradient, and (3) all symmetry allowed compositional fluctuation induced strain gradient terms. We show the formation of twinned martensite below the transformation temperature and tweed precursors above the transformation temperature, as well as indications of hierarchical structures near the habit plane. These phases result from a competition between short range attraction and long range elastic repulsive forces. The long range interaction is incorporated via Fourier spectral methods as discussed by C. Roland and R.C.Desai [Phys. Rev. B 42, 6658 (1990)].

  9. Evolution of complex dynamics in spatially structured populations

    PubMed Central

    Johst, K.; Doebeli, M.; Brandl, R.

    1999-01-01

    Dynamics of populations depend on demographic parameters which may change during evolution. In simple ecological models given by one-dimensional difference equations, the evolution of demographic parameters generally leads to equilibrium population dynamics. Here we show that this is not true in spatially structured ecological models. Using a multi-patch metapopulation model, we study the evolutionary dynamics of phenotypes that differ both in their response to local crowding, i.e. in their competitive behaviour within a habitat, and in their rate of dispersal between habitats. Our simulation results show that evolution can favour phenotypes that have the intrinsic potential for very complex dynamics provided that the environment is spatially structured and temporally variable. These phenotypes owe their evolutionary persistence to their large dispersal rates. They typically coexist with phenotypes that have low dispersal rates and that exhibit equilibrium dynamics when alone. This coexistence is brought about through the phenomenon of evolutionary branching, during which an initially uniform population splits into the two phenotypic classes.

  10. The Complexity of Dynamics in Small Neural Circuits.

    PubMed

    Fasoli, Diego; Cattani, Anna; Panzeri, Stefano

    2016-08-01

    Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

  11. The Complexity of Dynamics in Small Neural Circuits

    PubMed Central

    Panzeri, Stefano

    2016-01-01

    Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

  12. Modularity and the spread of perturbations in complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Kolchinsky, Artemy; Gates, Alexander J.; Rocha, Luis M.

    2015-12-01

    We propose a method to decompose dynamical systems based on the idea that modules constrain the spread of perturbations. We find partitions of system variables that maximize "perturbation modularity," defined as the autocovariance of coarse-grained perturbed trajectories. The measure effectively separates the fast intramodular from the slow intermodular dynamics of perturbation spreading (in this respect, it is a generalization of the "Markov stability" method of network community detection). Our approach captures variation of modular organization across different system states, time scales, and in response to different kinds of perturbations: aspects of modularity which are all relevant to real-world dynamical systems. It offers a principled alternative to detecting communities in networks of statistical dependencies between system variables (e.g., "relevance networks" or "functional networks"). Using coupled logistic maps, we demonstrate that the method uncovers hierarchical modular organization planted in a system's coupling matrix. Additionally, in homogeneously coupled map lattices, it identifies the presence of self-organized modularity that depends on the initial state, dynamical parameters, and type of perturbations. Our approach offers a powerful tool for exploring the modular organization of complex dynamical systems.

  13. Inferring Dynamic Signatures of Microbes in Complex Host Ecosystems

    PubMed Central

    Gerber, Georg K.; Onderdonk, Andrew B.; Bry, Lynn

    2012-01-01

    The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe

  14. Outlier-resilient complexity analysis of heartbeat dynamics

    PubMed Central

    Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

    2015-01-01

    Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings. PMID:25744292

  15. Outlier-resilient complexity analysis of heartbeat dynamics

    NASA Astrophysics Data System (ADS)

    Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

    2015-03-01

    Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.

  16. Outlier-resilient complexity analysis of heartbeat dynamics.

    PubMed

    Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

    2015-01-01

    Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings. PMID:25744292

  17. The Dynamics of Coalition Formation on Complex Networks

    NASA Astrophysics Data System (ADS)

    Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

    2015-08-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

  18. Young Children's Knowledge About the Moon: A Complex Dynamic System

    NASA Astrophysics Data System (ADS)

    Venville, Grady J.; Louisell, Robert D.; Wilhelm, Jennifer A.

    2012-08-01

    The purpose of this research was to use a multidimensional theoretical framework to examine young children's knowledge about the Moon. The research was conducted in the interpretive paradigm and the design was a multiple case study of ten children between the ages of three and eight from the USA and Australia. A detailed, semi-structured interview was conducted with each child. In addition, each child's parents were interviewed to determine possible social and cultural influences on the child's knowledge. We sought evidence about how the social and cultural experiences of the children might have influenced the development of their ideas. From a cognitive perspective we were interested in whether the children's ideas were constructed in a theory like form or whether the knowledge was the result of gradual accumulation of fragments of isolated cultural information. Findings reflected the strong and complex relationship between individual children, their social and cultural milieu, and the way they construct ideas about the Moon and astronomy. Findings are presented around four themes including ontology, creatures and artefacts, animism, and permanence. The findings support a complex dynamic system view of students' knowledge that integrates the framework theory perspective and the knowledge in fragments perspective. An initial model of a complex dynamic system of young children's knowledge about the Moon is presented.

  19. The Dynamics of Coalition Formation on Complex Networks

    PubMed Central

    Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

    2015-01-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects. PMID:26303622

  20. The Dynamics of Coalition Formation on Complex Networks.

    PubMed

    Auer, S; Heitzig, J; Kornek, U; Schöll, E; Kurths, J

    2015-01-01

    Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation ("coalitions") on an acquaintance network. We include both the network's influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects. PMID:26303622

  1. Ultrafast excited-state dynamics of copper(I) complexes.

    PubMed

    Iwamura, Munetaka; Takeuchi, Satoshi; Tahara, Tahei

    2015-03-17

    Bis-diimine Cu(I) complexes exhibit strong absorption in the visible region owing to the metal-to-ligand charge transfer (MLCT) transitions, and the triplet MLCT ((3)MLCT) states have long lifetimes. Because these characteristics are highly suitable for photosensitizers and photocatalysts, bis-diimine Cu(I) complexes have been attracting much interest. An intriguing feature of the Cu(I) complexes is the photoinduced structural change called "flattening". Bis-diimine Cu(I) complexes usually have tetrahedron-like D2d structures in the ground (S0) state, in which two ligands are perpendicularly attached to the Cu(I) ion. With MLCT excitation, the central Cu(I) ion is formally oxidized to Cu(II), which induces the structural change to the "flattened" square-planar-like structure that is seen for usual Cu(II) complexes. In this Account, we review our recent studies on ultrafast excited-state dynamics of bis-diimine Cu(I) complexes carried out using femtosecond time-resolved optical spectroscopy. Focusing on three prototypical bis-diimine Cu(I) complexes that have 1,10-phenanthroline ligands with different substituents at the 2,9-positions, i.e., [Cu(phen)2](+) (phen = 1,10-phenanthroline), [Cu(dmphen)2](+) (dmphen = 2,9-dimethyl-1,10-phenanthroline), and [Cu(dpphen)2](+) (dpphen = 2,9-diphenyl-1,10-phenanthroline), we examined their excited-state dynamics by time-resolved emission and absorption spectroscopies with 200 fs time resolution, observed the excited-state coherent nuclear motion with 30 fs time resolution and performed complementary theoretical calculations. This combined approach vividly visualizes excited-state processes in the MLCT state of bis-diimine Cu(I) complexes. It was demonstrated that flattening distortion, internal conversion, and intersystem crossing occur on the femtosecond-early picosecond time scale, and their dynamics is clearly identified separately. The flattening distortion predominantly occurs in the S1 state on the subpicosecond time

  2. Coarse-graining complex dynamics: Continuous Time Random Walks vs. Record Dynamics

    NASA Astrophysics Data System (ADS)

    Sibani, Paolo

    2013-02-01

    Continuous Time Random Walks (CTRW) are widely used to coarse-grain the evolution of systems jumping from a metastable sub-set of their configuration space, or trap, to another via rare intermittent events. The multi-scaled behavior typical of complex dynamics is provided by a fat-tailed distribution of the waiting time between consecutive jumps. We first argue that CTRW are inadequate to describe macroscopic relaxation processes for three reasons: macroscopic variables are not self-averaging, memory effects require an all-knowing observer, and different mechanisms whereby the jumps affect macroscopic variables all produce identical long-time relaxation behaviors. Hence, CTRW shed no light on the link between microscopic and macroscopic dynamics. We then highlight how a more recent approach, Record Dynamics (RD), provides a viable alternative, based on a very different set of physical ideas: while CTRW make use of a renewal process involving identical traps of infinite size, RD embodies a dynamical entrenchment into a hierarchy of traps which are finite in size and possess different degrees of meta-stability. We show in particular how RD produces the stretched exponential, power-law and logarithmic relaxation behaviors ubiquitous in complex dynamics, together with the sub-diffusive time dependence of the Mean Square Displacement characteristic of single particles moving in a complex environment.

  3. Bifurcation Phenomena of Opinion Dynamics in Complex Networks

    NASA Astrophysics Data System (ADS)

    Guo, Long; Cai, Xu

    In this paper, we study the opinion dynamics of Improved Deffuant model (IDM), where the convergence parameter μ is a function of the opposite’s degree K according to the celebrity effect, in small-world network (SWN) and scale-free network (SFN). Generically, the system undergoes a phase transition from the plurality state to the polarization state and to the consensus state as the confidence parameter ɛ increasing. Furthermore, the evolution of the steady opinion s * as a function of ɛ, and the relation between the minority steady opinion s_{*}^{min} and the individual connectivity k also have been analyzed. Our present work shows the crucial role of the confidence parameter and the complex system topology in the opinion dynamics of IDM.

  4. Ultrafast internal dynamics of flexible hydrogen-bonded supramolecular complexes.

    PubMed

    Olschewski, Martin; Knop, Stephan; Seehusen, Jaane; Lindner, Jörg; Vöhringer, Peter

    2011-02-24

    Supramolecular chemistry is intimately linked to the dynamical interplay between intermolecular forces and intramolecular flexibility. Here, we studied the ultrafast equilibrium dynamics of a supramolecular hydrogen-bonded receptor-substrate complex, 18-crown-6 monohydrate, using Fourier transform infrared (FTIR) and two-dimensional infrared (2DIR) spectroscopy in combination with numerical simulations based on molecular mechanics, density functional theory, and transition state theory. The theoretical calculations suggest that the flexibility of the macrocyclic crown ether receptor is related to an ultrafast crankshaft isomerization occurring on a time scale of several picoseconds and that the OH stretching vibrations of the substrate can serve as internal probes for the receptor's flexibility. The importance of population transfer among the vibrational modes of a given binding motif and of chemical exchange between spectroscopically distinguishable binding motifs for shaping the two-dimensional infrared spectrum and its temporal evolution is discussed. PMID:21271721

  5. WATERWAVES: wave particles dynamics on a complex triatomic potential

    NASA Astrophysics Data System (ADS)

    Taioli, Simone; Tennyson, Jonathan

    2006-07-01

    The WATERWAVES program suite performs complex scattering calculations by propagating a wave packet in a complex, full-dimensional potential for non-rotating ( J=0) but vibrating triatomic molecules. Potential energy and decay probability surfaces must be provided. Expectation values of geometric quantities can be calculated, which are useful for following the wave packet motion. The programs use a local complex potential approximation (LCP) for the Hamiltonian and Jacobi coordinates. The bottleneck of the calculation is the application of each term of the Hamiltonian to the wave packet. To solve this problem the programs use a different representation for each term: normalized associated Legendre polynomials PjK(x) as a functional basis for the angular kinetic term and an evenly spaced grid for the radial kinetic term yielding a fully point-wise representation of the wave functions. The potential term is treated using an efficient Discrete Variable Representation (DVR) being diagonal in the coordinate representation. The radial kinetic term uses a fast Fourier transform (FFT) to obtain an operator which is diagonal in the momentum space. To avoid artificial reflection at the boundaries of the grid a complex absorbing potential is included for calculating continuum quantities. Asymptotic analysis is performed to obtain scattering observables such as cross sections and other dynamical properties. Program summaryProgram title: WATERWAVES Catalogue identifier:ADXT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXT_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: Freely available from CPC Programming language: Fortran 77 Computer(s) for which the program has been designed: PC Operating system(s) for which the program has been designed: Linux RAM required to execute with typical data: case dependent: test run requires 976 024 kB No. of bytes in distributed program, including test data, etc.:11

  6. Is the Langevin phase equation an efficient model for oscillating neurons?

    NASA Astrophysics Data System (ADS)

    Ota, Keisuke; Tsunoda, Takamasa; Omori, Toshiaki; Watanabe, Shigeo; Miyakawa, Hiroyoshi; Okada, Masato; Aonishi, Toru

    2009-12-01

    The Langevin phase model is an important canonical model for capturing coherent oscillations of neural populations. However, little attention has been given to verifying its applicability. In this paper, we demonstrate that the Langevin phase equation is an efficient model for neural oscillators by using the machine learning method in two steps: (a) Learning of the Langevin phase model. We estimated the parameters of the Langevin phase equation, i.e., a phase response curve and the intensity of white noise from physiological data measured in the hippocampal CA1 pyramidal neurons. (b) Test of the estimated model. We verified whether a Fokker-Planck equation derived from the Langevin phase equation with the estimated parameters could capture the stochastic oscillatory behavior of the same neurons disturbed by periodic perturbations. The estimated model could predict the neural behavior, so we can say that the Langevin phase equation is an efficient model for oscillating neurons.

  7. A Simple Model for Complex Dynamical Transitions in Epidemics

    NASA Astrophysics Data System (ADS)

    Earn, David J. D.; Rohani, Pejman; Bolker, Benjamin M.; Grenfell, Bryan T.

    2000-01-01

    Dramatic changes in patterns of epidemics have been observed throughout this century. For childhood infectious diseases such as measles, the major transitions are between regular cycles and irregular, possibly chaotic epidemics, and from regionally synchronized oscillations to complex, spatially incoherent epidemics. A simple model can explain both kinds of transitions as the consequences of changes in birth and vaccination rates. Measles is a natural ecological system that exhibits different dynamical transitions at different times and places, yet all of these transitions can be predicted as bifurcations of a single nonlinear model.

  8. Nonlinear complex dynamics and Keynesian rigidity: A short introduction

    NASA Astrophysics Data System (ADS)

    Jovero, Edgardo

    2005-09-01

    The topic of this paper is to show that the greater acceptance and intense use of complex nonlinear dynamics in macroeconomics makes sense only within the neoKeynesian tradition. An example is presented regarding the behavior of an open-economy two-sector growth model endowed with Keynesian rigidity. The Keynesian view that structural instability globally exists in the aggregate economy is put forward, and therefore the need arises for policy to alleviate this instability in the form of dampened fluctuations is presented as an alternative view for macroeconomic theorizing.

  9. Epidemic dynamics and endemic states in complex networks

    SciTech Connect

    Pastor-Satorras, Romualdo; Vespignani, Alessandro

    2001-06-01

    We study by analytical methods and large scale simulations a dynamical model for the spreading of epidemics in complex networks. In networks with exponentially bounded connectivity we recover the usual epidemic behavior with a threshold defining a critical point below that the infection prevalence is null. On the contrary, on a wide range of scale-free networks we observe the absence of an epidemic threshold and its associated critical behavior. This implies that scale-free networks are prone to the spreading and the persistence of infections whatever spreading rate the epidemic agents might possess. These results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks.

  10. Vibrational dynamics of the CH4·F- complex.

    PubMed

    Wodraszka, Robert; Palma, Juliana; Manthe, Uwe

    2012-11-26

    Motivated by recent photodetachment experiments studying resonance structures in the transition-state region of the F + CH(4) → HF + CH(3) reaction, the vibrational dynamics of the precursor complex CH(4)·F(-) is investigated. Delocalized vibrational eigenstates of CH(4)·F(-) are computed in full dimensionality employing the multiconfigurational time-dependent Hartree (MCTDH) approach and a recently developed iterative diagonalization approach for general multiwell systems. Different types of stereographic coordinates are used, and a corresponding general N-body kinetic energy operator is given. The calculated tunneling splittings of the ground and the lower vibrational excited states of the CH(4)·F(-) complex do not significantly exceed 1 cm(-1). Comparing the converged MCTDH results for localized vibrational excitations with existing results obtained by normal-mode-based (truncated) vibrational configuration interaction calculations, significantly lower frequencies are found for excitations in the intermolecular modes. PMID:22731911

  11. Control of complex dynamics and chaos in distributed parameter systems

    SciTech Connect

    Chakravarti, S.; Marek, M.; Ray, W.H.

    1995-12-31

    This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in the complex quasi-periodic or chaotic spatiotemporal patterns.

  12. Multiparametric cytometry for exploration of complex cellular dynamics.

    PubMed

    Gondois-Rey, Françoise; Granjeaud, Samuel; Kieu, Suong Le Thi; Herrera, Diana; Hirsch, Ivan; Olive, Daniel

    2012-04-01

    The development of polychromatic cytometry has contributed to significant progress in the field of human immunology. Although numerous functional studies of rare cell populations have been performed using this technology, here we used polychromatic cytometry to explore the dynamics of complex cellular systems implicated in innate immunity. We used PBMC stimulated with live influenza virus as an experimental model. We studied the time course of activation of PBMC, which contain DC, monocytes, and NK cells, all of which are, in addition to their innate immune properties, susceptible to Flu infection. We developed 12 color panels to investigate intracellular expression of IFN-α, TNF-α, IL-12, IL-6, IFN-γ, CD107, and influenza virus nucleoprotein simultaneously in these cell populations. These panels allowed reproducible determination of activation markers induced in DC after their direct exposure to various stimulations or in NK cells by indirect DC-mediated activation within the complex cellular environment. The ability to use a low number of cells and reduced quantities of reagents permitted us to perform kinetic experiments. The power of polychromatic cytometry associated with bioinformatic tools allowed us to analyze the multiple functional data generated as dynamic clustering maps. These maps present a readily understandable view of activation events induced in different populations of PBMC. In addition, it reveals new information on the coordination of the complex pathways induced and on the cellular interactions that sustained indirect DC-mediated NK cell activation. Our work shows that polychromatic cytometry is a tool for discoveries in unexplored complex cell systems, at the crossroads of immunology and virology. © 2012 International Society for Advancement of Cytometry. PMID:22278900

  13. Computational complexity of ecological and evolutionary spatial dynamics

    PubMed Central

    Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

    2015-01-01

    There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

  14. Dynamic analysis of the human brain with complex cerebral sulci.

    PubMed

    Tseng, Jung-Ge; Huang, Bo-Wun; Ou, Yi-Wen; Yen, Ke-Tien; Wu, Yi-Te

    2016-07-01

    The brain is one of the most vulnerable organs inside the human body. Head accidents often appear in daily life and are easy to cause different level of brain damage inside the skull. Once the brain suffered intense locomotive impact, external injuries, falls, or other accidents, it will result in different degrees of concussion. This study employs finite element analysis to compare the dynamic characteristics between the geometric models of an assumed simple brain tissue and a brain tissue with complex cerebral sulci. It is aimed to understand the free vibration of the internal brain tissue and then to protect the brain from injury caused by external influences. Reverse engineering method is used for a Classic 5-Part Brain (C18) model produced by 3B Scientific Corporation. 3D optical scanner is employed to scan the human brain structure model with complex cerebral sulci and imported into 3D graphics software to construct a solid brain model to simulate the real complex brain tissue. Obtaining the normal mode analysis by inputting the material properties of the true human brain into finite element analysis software, and then to compare the simplified and the complex of brain models. PMID:27459595

  15. Computational complexity of ecological and evolutionary spatial dynamics.

    PubMed

    Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A

    2015-12-22

    There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

  16. Molecular dynamics simulations of DNA-polycation complexes

    NASA Astrophysics Data System (ADS)

    Ziebarth, Jesse; Wang, Yongmei

    2008-03-01

    A necessary step in the preparation of DNA for use in gene therapy is the packaging of DNA with a vector that can condense DNA and provide protection from degrading enzymes. Because of the immunoresponses caused by viral vectors, there has been interest in developing synthetic gene therapy vectors, with polycations emerging as promising candidates. Molecular dynamics simulations of the DNA duplex CGCGAATTCGCG in the presence of 20 monomer long sequences of the polycations, poly-L-lysine (PLL) and polyethyleneimine (PEI), with explicit counterions and TIP3P water, are performed to provide insight into the structure and formation of DNA polyplexes. After an initial separation of approximately 50 å, the DNA and polycation come together and form a stable complex within 10 ns. The DNA does not undergo any major structural changes upon complexation and remains in the B-form. In the formed complex, the charged amine groups of the polycation mainly interact with DNA phosphate groups, and rarely occupy electronegative sites in either the major or minor grooves. Differences between complexation with PEI and PLL will be discussed.

  17. Reconstruction of the modified discrete Langevin equation from persistent time series.

    PubMed

    Czechowski, Zbigniew

    2016-05-01

    The discrete Langevin-type equation, which can describe persistent processes, was introduced. The procedure of reconstruction of the equation from time series was proposed and tested on synthetic data, with short and long-tail distributions, generated by different Langevin equations. Corrections due to the finite sampling rates were derived. For an exemplary meteorological time series, an appropriate Langevin equation, which constitutes a stochastic macroscopic model of the phenomenon, was reconstructed. PMID:27249949

  18. Time-local Heisenberg-Langevin equations and the driven qubit

    NASA Astrophysics Data System (ADS)

    Whalen, S. J.; Carmichael, H. J.

    2016-06-01

    The time-local master equation for a driven boson system interacting with a boson environment is derived by way of a time-local Heisenberg-Langevin equation. Extension to the driven qubit fails—except for weak excitation—due to the lost linearity of the system-environment interaction. We show that a reported time-local master equation for the driven qubit is incorrect. As a corollary to our demonstration, we also uncover odd asymptotic behavior in the "repackaged" time-local dynamics of a system driven to a far-from-equilibrium steady state: the density operator becomes steady while time-dependent coefficients oscillate (with periodic singularities) forever.

  19. Variational superposed Gaussian approximation for time-dependent solutions of Langevin equations

    NASA Astrophysics Data System (ADS)

    Hasegawa, Yoshihiko

    2015-04-01

    We propose a variational superposed Gaussian approximation (VSGA) for dynamical solutions of Langevin equations subject to applied signals, determining time-dependent parameters of superposed Gaussian distributions by the variational principle. We apply the proposed VSGA to systems driven by a chaotic signal, where the conventional Fourier method cannot be adopted, and calculate the time evolution of probability density functions (PDFs) and moments. Both white and colored Gaussian noises terms are included to describe fluctuations. Our calculations show that time-dependent PDFs obtained by VSGA agree excellently with those obtained by Monte Carlo simulations. The correlation between the chaotic input signal and the mean response are also calculated as a function of the noise intensity, which confirms the occurrence of aperiodic stochastic resonance with both white and colored noises.

  20. Composite generalized Langevin equation for Brownian motion in different hydrodynamic and adhesion regimes.

    PubMed

    Yu, Hsiu-Yu; Eckmann, David M; Ayyaswamy, Portonovo S; Radhakrishnan, Ravi

    2015-05-01

    We present a composite generalized Langevin equation as a unified framework for bridging the hydrodynamic, Brownian, and adhesive spring forces associated with a nanoparticle at different positions from a wall, namely, a bulklike regime, a near-wall regime, and a lubrication regime. The particle velocity autocorrelation function dictates the dynamical interplay between the aforementioned forces, and our proposed methodology successfully captures the well-known hydrodynamic long-time tail with context-dependent scaling exponents and oscillatory behavior due to the binding interaction. Employing the reactive flux formalism, we analyze the effect of hydrodynamic variables on the particle trajectory and characterize the transient kinetics of a particle crossing a predefined milestone. The results suggest that both wall-hydrodynamic interactions and adhesion strength impact the particle kinetics. PMID:26066173

  1. Dynamic of astrophysical jets in the complex octonion space

    NASA Astrophysics Data System (ADS)

    Weng, Zi-Hua

    2015-06-01

    The paper aims to consider the strength gradient force as the dynamic of astrophysical jets, explaining the movement phenomena of astrophysical jets. J. C. Maxwell applied the quaternion analysis to describe the electromagnetic theory. This encourages others to adopt the complex quaternion and octonion to depict the electromagnetic and gravitational theories. In the complex octonion space, it is capable of deducing the field potential, field strength, field source, angular momentum, torque, force and so forth. As one component of the force, the strength gradient force relates to the gradient of the norm of field strength only, and is independent of not only the direction of field strength but also the mass and electric charge for the test particle. When the strength gradient force is considered as the thrust of the astrophysical jets, one can deduce some movement features of astrophysical jets, including the bipolarity, matter ingredient, precession, symmetric distribution, emitting, collimation, stability, continuing acceleration and so forth. The above results reveal that the strength gradient force is able to be applied to explain the main mechanical features of astrophysical jets, and is the competitive candidate of the dynamic of astrophysical jets.

  2. Reproductive dynamics shapes genomotype composition in an allopolyploid complex.

    PubMed

    Morgado-Santos, M; Carona, S; Magalhães, M F; Vicente, L; Collares-Pereira, M J

    2016-05-25

    Hybrid complexes are composed of organisms with multiple combinations of parental genomes (genomotypes) that interconnect through nets of crosses. Although several such complexes are well established without speciation or extinction, mechanisms shaping their dynamics remain poorly understood. In this study, we quantified the reproductive success of the allopolyploid Iberian fish Squalius alburnoides in experimental free-access and directional crosses involving the most common genomotypes. Specifically, we analysed the paternity of the offspring produced when females had free access to male genomotypes and quantified variations in egg allocation, fertilization rate, and offspring survival among crosses involving each male genomotype. The composition of the offspring produced from free-access crosses varied significantly from that expected from random mating, suggesting that offspring production and viability are not independent of parental male genomotype. Moreover, directional crosses producing the genomotype most commonly found in wild populations appeared to be the most successful, with females laying more eggs, and fertilization rate and offspring survival being the highest. These results suggest that reproductive dynamics plays a relevant role in structuring the genomotype composition of populations and opens a path to future research on the ecology and evolutionary biology of allopolyploids and their multiplicity of possible evolutionary pathways. PMID:27226473

  3. GPU-enabled molecular dynamics simulations of ankyrin kinase complex

    NASA Astrophysics Data System (ADS)

    Gautam, Vertika; Chong, Wei Lim; Wisitponchai, Tanchanok; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.; Tayapiwatana, Chatchai; Lee, Vannajan Sanghiran

    2014-10-01

    The ankyrin repeat (AR) protein can be used as a versatile scaffold for protein-protein interactions. It has been found that the heterotrimeric complex between integrin-linked kinase (ILK), PINCH, and parvin is an essential signaling platform, serving as a convergence point for integrin and growth-factor signaling and regulating cell adhesion, spreading, and migration. Using ILK-AR with high affinity for the PINCH1 as our model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. In this study, the long time scale dynamics simulations with GPU accelerated molecular dynamics (MD) simulations in AMBER12 have been performed to locate the hot spots of protein-protein interaction by the analysis of the Molecular Mechanics-Poisson-Boltzmann Surface Area/Generalized Born Solvent Area (MM-PBSA/GBSA) of the MD trajectories. Our calculations suggest good binding affinity of the complex and also the residues critical in the binding.

  4. Complex Dynamic Behavior in Simple Gene Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Santillán Zerón, Moisés

    2007-02-01

    Knowing the complete genome of a given species is just a piece of the puzzle. To fully unveil the systems behavior of an organism, an organ, or even a single cell, we need to understand the underlying gene regulatory dynamics. Given the complexity of the whole system, the ultimate goal is unattainable for the moment. But perhaps, by analyzing the most simple genetic systems, we may be able to develop the mathematical techniques and procedures required to tackle more complex genetic networks in the near future. In the present work, the techniques for developing mathematical models of simple bacterial gene networks, like the tryptophan and lactose operons are introduced. Despite all of the underlying assumptions, such models can provide valuable information regarding gene regulation dynamics. Here, we pay special attention to robustness as an emergent property. These notes are organized as follows. In the first section, the long historical relation between mathematics, physics, and biology is briefly reviewed. Recently, the multidisciplinary work in biology has received great attention in the form of systems biology. The main concepts of this novel science are discussed in the second section. A very slim introduction to the essential concepts of molecular biology is given in the third section. In the fourth section, a brief introduction to chemical kinetics is presented. Finally, in the fifth section, a mathematical model for the lactose operon is developed and analyzed..

  5. Complex processes from dynamical architectures with time-scale hierarchy.

    PubMed

    Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor

    2011-01-01

    The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes. PMID:21347363

  6. Quantum Non-Markovian Langevin Equations and Transport Coefficients

    SciTech Connect

    Sargsyan, V.V.; Antonenko, N.V.; Kanokov, Z.; Adamian, G.G.

    2005-12-01

    Quantum diffusion equations featuring explicitly time-dependent transport coefficients are derived from generalized non-Markovian Langevin equations. Generalized fluctuation-dissipation relations and analytic expressions for calculating the friction and diffusion coefficients in nuclear processes are obtained. The asymptotic behavior of the transport coefficients and correlation functions for a damped harmonic oscillator that is linearly coupled in momentum to a heat bath is studied. The coupling to a heat bath in momentum is responsible for the appearance of the diffusion coefficient in coordinate. The problem of regression of correlations in quantum dissipative systems is analyzed.

  7. Solving the generalized Langevin equation with the algebraically correlated noise

    NASA Astrophysics Data System (ADS)

    Srokowski, T.; Płoszajczak, M.

    1998-04-01

    We solve the Langevin equation with the memory kernel. The stochastic force possesses algebraic correlations, proportional to 1/t. The velocity autocorrelation function and related quantities characterizing transport properties are calculated with the assumption that the system is in thermal equilibrium. Stochastic trajectories are simulated numerically, using the kangaroo process as a noise generator. Results of this simulation resemble Lévy walks with divergent moments of the velocity distribution. We consider motion of a Brownian particle, both without any external potential and in the harmonic oscillator field, in particular the escape from a potential well. The results are compared with memory-free calculations for the Brownian particle.

  8. Complex dynamics in systems with many degrees of freedom

    SciTech Connect

    Bourzutschky, M.S.

    1993-01-01

    Complex dynamics in systems with many degrees of freedom are investigated with two classes of computational models. The models in the first class are motivated by the experimental observation of spatiotemporal chaos in strongly driven convection cells, and are designed to display chaotic evolution in discrete space and time. A local conservation law is incorporated into the equations of motion, and its importance is discussed. The central limit theorem is applied to characterize fluctuations over large uncorrelated regions, and a simple theory predicting the wavelength properties of the models is developed and verified numerically. The applicability of the fluctuation-dissipation theorem and the maximum entropy principle to nonequilibrium systems is tested extensively. A possible application to an experimental situation is outlined. The models in the second class are motivated by the concept of self-organized criticality, which predicts that driven dynamical systems naturally evolve to a statistically stationary state displaying scale invariance. Several scenarios of how scaling behavior can occur in dynamical systems are discussed, using ideas from dimensional analysis. A simple mean field theory for a large class of cellular automata models is developed. Extensive numerical simulations are described which test the validity of scaling forms and demonstrate possible errors resulting from finite size effects.

  9. Functional Loop Dynamics of the Streptavidin-Biotin Complex

    PubMed Central

    Song, Jianing; Li, Yongle; Ji, Changge; Zhang, John Z. H.

    2015-01-01

    Accelerated molecular dynamics (aMD) simulation is employed to study the functional dynamics of the flexible loop3-4 in the strong-binding streptavidin-biotin complex system. Conventional molecular (cMD) simulation is also performed for comparison. The present study reveals the following important properties of the loop dynamics: (1) The transition of loop3-4 from open to closed state is observed in 200 ns aMD simulation. (2) In the absence of biotin binding, the open-state streptavidin is more stable, which is consistent with experimental evidences. The free energy (ΔG) difference is about 5 kcal/mol between two states. But with biotin binding, the closed state is more stable due to electrostatic and hydrophobic interactions between the loop3-4 and biotin. (3) The closure of loop3-4 is concerted to the stable binding of biotin to streptavidin. When the loop3-4 is in its open-state, biotin moves out of the binding pocket, indicating that the interactions between the loop3-4 and biotin are essential in trapping biotin in the binding pocket. (4) In the tetrameric streptavidin system, the conformational change of the loop3-4 in each monomer is independent of each other. That is, there is no cooperative binding for biotin bound to the four subunits of the tetramer. PMID:25601277

  10. Functional Loop Dynamics of the Streptavidin-Biotin Complex

    NASA Astrophysics Data System (ADS)

    Song, Jianing; Li, Yongle; Ji, Changge; Zhang, John Z. H.

    2015-01-01

    Accelerated molecular dynamics (aMD) simulation is employed to study the functional dynamics of the flexible loop3-4 in the strong-binding streptavidin-biotin complex system. Conventional molecular (cMD) simulation is also performed for comparison. The present study reveals the following important properties of the loop dynamics: (1) The transition of loop3-4 from open to closed state is observed in 200 ns aMD simulation. (2) In the absence of biotin binding, the open-state streptavidin is more stable, which is consistent with experimental evidences. The free energy (ΔG) difference is about 5 kcal/mol between two states. But with biotin binding, the closed state is more stable due to electrostatic and hydrophobic interactions between the loop3-4 and biotin. (3) The closure of loop3-4 is concerted to the stable binding of biotin to streptavidin. When the loop3-4 is in its open-state, biotin moves out of the binding pocket, indicating that the interactions between the loop3-4 and biotin are essential in trapping biotin in the binding pocket. (4) In the tetrameric streptavidin system, the conformational change of the loop3-4 in each monomer is independent of each other. That is, there is no cooperative binding for biotin bound to the four subunits of the tetramer.

  11. Dynamical complexity of the Brans-Dicke cosmology

    SciTech Connect

    Hrycyna, Orest; Szydłowski, Marek E-mail: marek.szydlowski@uj.edu.pl

    2013-12-01

    The dynamics of the Brans-Dicke theory with a quadratic scalar field potential function and barotropic matter is investigated. The dynamical system methods are used to reveal complexity of dynamical evolution in homogeneous and isotropic cosmological models. The structure of phase space crucially depends on the parameter of the theory ω{sub BD} as well as barotropic matter index w{sub m}. In our analysis these parameters are treated as bifurcation parameters. We found sets of values of these parameters which lead to generic evolutional scenarios. We show that in isotropic and homogeneous models in the Brans-Dicke theory with a quadratic potential function the de Sitter state appears naturally. Stability conditions of this state are fully investigated. It is shown that these models can explain accelerated expansion of the Universe without the assumption of the substantial form of dark matter and dark energy. The Poincare construction of compactified phase space with a circle at infinity is used to show that phase space trajectories in a physical region can be equipped with a structure of a vector field on nontrivial topological closed space. For ω{sub BD} < −3/2 we show new types of early and late time evolution leading from the anti-de Sitter to the de Sitter state through an asymmetric bounce. In the theory without a ghost we find bouncing solutions and the coexistence of the bounces and the singularity. Following the Peixoto theorem some conclusions about structural stability are drawn.

  12. Modeling the complex dynamics of enzyme-pathway coevolution.

    PubMed

    Schütte, Moritz; Skupin, Alexander; Segrè, Daniel; Ebenhöh, Oliver

    2010-12-01

    Metabolic pathways must have coevolved with the corresponding enzyme gene sequences. However, the evolutionary dynamics ensuing from the interplay between metabolic networks and genomes is still poorly understood. Here, we present a computational model that generates putative evolutionary walks on the metabolic network using a parallel evolution of metabolic reactions and their catalyzing enzymes. Starting from an initial set of compounds and enzymes, we expand the metabolic network iteratively by adding new enzymes with a probability that depends on their sequence-based similarity to already present enzymes. Thus, we obtain simulated time courses of chemical evolution in which we can monitor the appearance of new metabolites, enzyme sequences, or even entire organisms. We observe that new enzymes do not appear gradually but rather in clusters which correspond to enzyme classes. A comparison with Brownian motion dynamics indicates that our system displays biased random walks similar to diffusion on the metabolic network with long-range correlations. This suggests that a quantitative molecular principle may underlie the appearance of punctuated equilibrium dynamics, whereby enzymes occur in bursts rather than by phyletic gradualism. Moreover, the simulated time courses lead to a putative time-order of enzyme and organism appearance. Among the patterns we detect in these evolutionary trends is a significant correlation between the time of appearance and their enzyme repertoire size. Hence, our approach to metabolic evolution may help understand the rise in complexity at the biochemical and genomic levels. PMID:21198127

  13. Dynamical complexity of the Brans-Dicke cosmology

    NASA Astrophysics Data System (ADS)

    Hrycyna, Orest; Szydłowski, Marek

    2013-12-01

    The dynamics of the Brans-Dicke theory with a quadratic scalar field potential function and barotropic matter is investigated. The dynamical system methods are used to reveal complexity of dynamical evolution in homogeneous and isotropic cosmological models. The structure of phase space crucially depends on the parameter of the theory ωBD as well as barotropic matter index wm. In our analysis these parameters are treated as bifurcation parameters. We found sets of values of these parameters which lead to generic evolutional scenarios. We show that in isotropic and homogeneous models in the Brans-Dicke theory with a quadratic potential function the de Sitter state appears naturally. Stability conditions of this state are fully investigated. It is shown that these models can explain accelerated expansion of the Universe without the assumption of the substantial form of dark matter and dark energy. The Poincare construction of compactified phase space with a circle at infinity is used to show that phase space trajectories in a physical region can be equipped with a structure of a vector field on nontrivial topological closed space. For ωBD < -3/2 we show new types of early and late time evolution leading from the anti-de Sitter to the de Sitter state through an asymmetric bounce. In the theory without a ghost we find bouncing solutions and the coexistence of the bounces and the singularity. Following the Peixoto theorem some conclusions about structural stability are drawn.

  14. Modeling the complex dynamics of enzyme-pathway coevolution

    NASA Astrophysics Data System (ADS)

    Schütte, Moritz; Skupin, Alexander; Segrè, Daniel; Ebenhöh, Oliver

    2010-12-01

    Metabolic pathways must have coevolved with the corresponding enzyme gene sequences. However, the evolutionary dynamics ensuing from the interplay between metabolic networks and genomes is still poorly understood. Here, we present a computational model that generates putative evolutionary walks on the metabolic network using a parallel evolution of metabolic reactions and their catalyzing enzymes. Starting from an initial set of compounds and enzymes, we expand the metabolic network iteratively by adding new enzymes with a probability that depends on their sequence-based similarity to already present enzymes. Thus, we obtain simulated time courses of chemical evolution in which we can monitor the appearance of new metabolites, enzyme sequences, or even entire organisms. We observe that new enzymes do not appear gradually but rather in clusters which correspond to enzyme classes. A comparison with Brownian motion dynamics indicates that our system displays biased random walks similar to diffusion on the metabolic network with long-range correlations. This suggests that a quantitative molecular principle may underlie the appearance of punctuated equilibrium dynamics, whereby enzymes occur in bursts rather than by phyletic gradualism. Moreover, the simulated time courses lead to a putative time-order of enzyme and organism appearance. Among the patterns we detect in these evolutionary trends is a significant correlation between the time of appearance and their enzyme repertoire size. Hence, our approach to metabolic evolution may help understand the rise in complexity at the biochemical and genomic levels.

  15. Dislocation dynamics during plastic deformations of complex plasma crystals.

    PubMed

    Durniak, C; Samsonov, D; Ralph, J F; Zhdanov, S; Morfill, G

    2013-11-01

    The internal structures of most periodic crystalline solids contain defects. This affects various important mechanical and thermal properties of crystals. Since it is very difficult and expensive to track the motion of individual atoms in real solids, macroscopic model systems, such as complex plasmas, are often used. Complex plasmas consist of micrometer-sized grains immersed into an ion-electron plasma. They exist in solidlike, liquidlike, and gaseouslike states and exhibit a range of nonlinear and dynamic effects, most of which have direct analogies in solids and liquids. Slabs of a monolayer hexagonal complex plasma were subjected to a cycle of uniaxial compression and decompression of large amplitudes to achieve plastic deformations, both in experiments and simulations. During the cycle, the internal structure of the lattice exhibited significant rearrangements. Dislocations (point defects) were generated and displaced in the stressed lattice. They tended to glide parallel to their Burgers vectors under load. It was found that the deformation cycle was macroscopically reversible but irreversible at the particle scale. PMID:24329366

  16. Dislocation dynamics during plastic deformations of complex plasma crystals

    NASA Astrophysics Data System (ADS)

    Durniak, C.; Samsonov, D.; Ralph, J. F.; Zhdanov, S.; Morfill, G.

    2013-11-01

    The internal structures of most periodic crystalline solids contain defects. This affects various important mechanical and thermal properties of crystals. Since it is very difficult and expensive to track the motion of individual atoms in real solids, macroscopic model systems, such as complex plasmas, are often used. Complex plasmas consist of micrometer-sized grains immersed into an ion-electron plasma. They exist in solidlike, liquidlike, and gaseouslike states and exhibit a range of nonlinear and dynamic effects, most of which have direct analogies in solids and liquids. Slabs of a monolayer hexagonal complex plasma were subjected to a cycle of uniaxial compression and decompression of large amplitudes to achieve plastic deformations, both in experiments and simulations. During the cycle, the internal structure of the lattice exhibited significant rearrangements. Dislocations (point defects) were generated and displaced in the stressed lattice. They tended to glide parallel to their Burgers vectors under load. It was found that the deformation cycle was macroscopically reversible but irreversible at the particle scale.

  17. PREFACE: Complex dynamics of fluids in disordered and crowded environments Complex dynamics of fluids in disordered and crowded environments

    NASA Astrophysics Data System (ADS)

    Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

    2011-06-01

    Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized

  18. Electronic Spectroscopy and Dynamics of the Acetylene - Complex

    NASA Astrophysics Data System (ADS)

    Ju, Shan-Shan

    The structures, intermolecular forces and excited state dynamics of acetylene(A) cdot Ar complex are investigated by combination of laser induced fluorescence spectroscopy pairwise potential model calculations. Acetylene is linear in the X state while trans-bent in the (A) state. Although only one structure has been known to exist for the acetylene(X) cdot Ar complex, two isomeric structures are determined for the acetylene(A) cdot Ar complex from the rotational band shape analysis of the fluorescence excitation spectra. One of the isomers has the argon sitting in the molecular plane of C _2H_2 (A), 3.77 A away from the center-of-mass of acetylene, the other has the argon 3.71 A above the plane on the C_2 axis. Formulas useful for calculating axis switching angles in non-planar molecules have been derived and applied to the two isomeric structures. It was found that despite the acetylene geometry change from the (X) to the (A) state, the axis switching effect is negligible for the complex spectral calculation. A pair potential model with parameters directly extracted from the ones calculated for ethene (X) cdot Ar is able to produce the two structures. Based on the structures and the calculated potential surface, three of the vdW frequencies are assigned to be: upsilon_{rm stretch } = 28 cm^{-1} for the out-of-plane isomer, upsilon_ {rm bend1} = 11 cm^ {-1} (the in-plane bend) and upsilon_{rm bend2} = 8.5 cm^{-1} (the out -of-plane bend) for the in-plane isomer. The existence of the two isomers allowed the study of the orientation dependence in intersystem crossing (ISC) of acetylene(S _1) induced by interaction with argon. Similar ISC lifetimes (~100 ns) were observed for the two isomers, suggesting that the pi and pi^* orbitals are equally susceptible to spin-changing interactions with Ar.

  19. Effective Interaction Potentials and Physical Properties of Complex Plasmas

    SciTech Connect

    Ramazanov, T. S.; Dzhumagulova, K. N.; Gabdullin, M. T.; Omarbakiyeva, Y. A.

    2009-11-10

    Microscopic, thermodynamic and transport properties of complex plasmas are investigated on the basis of effective potentials of interparticle interaction. These potentials take into account correlation effects and quantum-mechanical diffraction. Plasma composition, thermodynamic functions of hydrogen and helium plasmas are obtained for a wide region of coupling parameter. Collision processes in partially ionized plasma are considered; some kinetic characteristics such as phase shift, scattering cross section, bremsstrahlung cross section and absorption coefficient are investigated. Dynamic and transport properties of dusty plasma are studied by computer simulation method of the Langevin dynamics.

  20. Collaborative Research. Damage and Burst Dynamics in Failure of Complex Geomaterials. A Statistical Physics Approach to Understanding the Complex Emergent Dynamics in Near Mean-Field Geological Materials

    SciTech Connect

    Rundle, John B.; Klein, William

    2015-09-29

    We have carried out research to determine the dynamics of failure in complex geomaterials, specifically focusing on the role of defects, damage and asperities in the catastrophic failure processes (now popularly termed “Black Swan events”). We have examined fracture branching and flow processes using models for invasion percolation, focusing particularly on the dynamics of bursts in the branching process. We have achieved a fundamental understanding of the dynamics of nucleation in complex geomaterials, specifically in the presence of inhomogeneous structures.

  1. Information processing using a single dynamical node as complex system

    PubMed Central

    Appeltant, L.; Soriano, M.C.; Van der Sande, G.; Danckaert, J.; Massar, S.; Dambre, J.; Schrauwen, B.; Mirasso, C.R.; Fischer, I.

    2011-01-01

    Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing. PMID:21915110

  2. Dynamic workflow model for complex activity in intensive care unit.

    PubMed

    Bricon-Souf, N; Renard, J M; Beuscart, R

    1998-01-01

    Cooperation is very important in Medical care, especially in the Intensive Care Unit (ICU) where the difficulties increase which is due to the urgency of the work. Workflow systems are considered as well adapted to modelize productive work in business process. We aim at introducing this approach in the Health Care domain. We have proposed a conversation-based Workflow in order to modelize the therapeutics plan in the ICU [1]. But in such a complex field, the flexibility of the workflow system is essential for the system to be usable. In this paper, we focus on the main points used to increase the dynamicity. We report on affecting roles, highlighting information, and controlling the system We propose some solutions and describe our prototype in the ICU. PMID:10384452

  3. Photobleaching Methods to Study Golgi Complex Dynamics in Living Cells

    PubMed Central

    Snapp, Erik Lee

    2014-01-01

    The Golgi complex (GC) is a highly dynamic organelle that constantly receives and exports proteins and lipids from both the endoplasmic reticulum and the plasma membrane. While protein trafficking can be monitored with traditional biochemical methods, these approaches average the behaviors of millions of cells, provide modest temporal information and no spatial information. Photobleaching methods enable investigators to monitor protein trafficking in single cells or even single GC stacks with subsecond precision. Furthermore, photobleaching can be exploited to monitor the behaviors of resident GC proteins to provide insight into mechanisms of retention and trafficking. In this chapter, general photobleaching approaches with laser scanning confocal microscopes are described. Importantly, the problems associated with many fluorescent proteins (FPs) and their uses in the secretory pathway are discussed and appropriate choices are suggested. For example, Enhanced Green Fluorescent Protein (EGFP) and most red FPs are extremely problematic. Finally, options for data analyses are described. PMID:24295308

  4. Precision of collective oscillations in complex dynamical systems with noise

    NASA Astrophysics Data System (ADS)

    Mori, Fumito; Mikhailov, Alexander S.

    2016-06-01

    Two kinds of oscillation precision are investigated for complex oscillatory dynamical systems under action of noise. The many-cycle precision determined by the variance of the times needed for a large number of cycles is closely related to diffusion of the global oscillation phase and provides an invariant property of a system. The single-cycle precision given by the variance in durations of single cycles is sensitive to the choice of an output variable and output checkpoint; it can be improved by an appropriate selection of them. A general analysis of the precision properties based on the Floquet perturbation theory is performed and analytical predictions are verified in numerical simulations of a model oscillatory genetic network.

  5. Complex Dynamic Flows in Solar Flare Sheet Structures

    NASA Technical Reports Server (NTRS)

    McKenzie, David E.; Reeves, Katharine K.; Savage, Sabrina

    2012-01-01

    Observations of high-energy emission from solar flares often reveal the presence of large sheet-like structures, sometimes extending over a space comparable to the Sun's radius. Given that these structures are found between a departing coronal mass ejection and the post-eruption flare arcade, it is natural to associate the structure with a current sheet; though the relationship is unclear. Moreover, recent high-resolution observations have begun to reveal that the motions in this region are highly complex, including reconnection outflows, oscillations, and apparent wakes and eddies. We present a detailed first look at the complicated dynamics within this supra-arcade plasma, and consider implications for the interrelationship between the plasma and its embedded magnetic field.

  6. Complex flow dynamics around 3D microbot prototypes.

    PubMed

    Martínez-Aranda, Sergio; Galindo-Rosales, Francisco J; Campo-Deaño, Laura

    2016-02-28

    A new experimental setup for the study of the complex flow dynamics around 3D microbot prototypes in a straight microchannel has been developed and assessed. The ultimate aim of this work is focused on the analysis of the morphology of different microbot prototypes to get a better insight into their efficiency when they swim through the main conduits of the human circulatory system. The setup consists of a fused silica straight microchannel with a 3D microbot prototype fastened in the center of the channel cross-section by an extremely thin support. Four different prototypes were considered: a cube, a sphere and two ellipsoids with aspect ratios of 1 : 2 and 1 : 4, respectively. Flow visualization and micro-particle image velocimetry (μPIV) measurements were performed using Newtonian and viscoelastic blood analogue fluids. An efficiency parameter, ℑ, to discriminate the prototypes in terms of flow disturbance has been proposed. PMID:26790959

  7. PREFACE: Complex dynamics of fluids in disordered and crowded environments Complex dynamics of fluids in disordered and crowded environments

    NASA Astrophysics Data System (ADS)

    Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

    2011-06-01

    Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized

  8. Dynamic workflow model for complex activity in intensive care unit.

    PubMed

    Bricon-Souf, N; Renard, J M; Beuscart, R

    1999-01-01

    Co-operation is very important in Medical care, especially in the Intensive Care Unit (ICU) where the difficulties increase which is due to the urgency of the work. Workflow systems are considered as well adapted to modelize productive work in business process. We aim at introducing this approach in the Health Care domain. We have proposed a conversation-based workflow in order to modelize the therapeutics plan in the ICU [1]. But in such a complex field, the flexibility of the workflow system is essential for the system to be usable. We have concentrated on three main points usually proposed in the workflow models, suffering from a lack of dynamicity: static links between roles and actors, global notification of information changes, lack of human control on the system. In this paper, we focus on the main points used to increase the dynamicity. We report on affecting roles, highlighting information, and controlling the system. We propose some solutions and describe our prototype in the ICU. PMID:10193884

  9. 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.

  10. 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.

  11. The geometry of chaotic dynamics — a complex network perspective

    NASA Astrophysics Data System (ADS)

    Donner, R. V.; Heitzig, J.; Donges, J. F.; Zou, Y.; Marwan, N.; Kurths, J.

    2011-12-01

    Recently, several complex network approaches to time series analysis have been developed and applied to study a wide range of model systems as well as real-world data, e.g., geophysical or financial time series. Among these techniques, recurrence-based concepts and prominently ɛ-recurrence networks, most faithfully represent the geometrical fine structure of the attractors underlying chaotic (and less interestingly non-chaotic) time series. In this paper we demonstrate that the well known graph theoretical properties local clustering coefficient and global (network) transitivity can meaningfully be exploited to define two new local and two new global measures of dimension in phase space: local upper and lower clustering dimension as well as global upper and lower transitivity dimension. Rigorous analytical as well as numerical results for self-similar sets and simple chaotic model systems suggest that these measures are well-behaved in most non-pathological situations and that they can be estimated reasonably well using ɛ-recurrence networks constructed from relatively short time series. Moreover, we study the relationship between clustering and transitivity dimensions on the one hand, and traditional measures like pointwise dimension or local Lyapunov dimension on the other hand. We also provide further evidence that the local clustering coefficients, or equivalently the local clustering dimensions, are useful for identifying unstable periodic orbits and other dynamically invariant objects from time series. Our results demonstrate that ɛ-recurrence networks exhibit an important link between dynamical systems and graph theory.

  12. Complex dynamics of semantic memory access in reading.

    PubMed

    Baggio, Giosué; Fonseca, André

    2012-02-01

    Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as 'cold' in 'In July it is very cold outside'. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing. PMID:21715401

  13. Reprint of : The Boltzmann--Langevin approach: A simple quantum-mechanical derivation

    NASA Astrophysics Data System (ADS)

    Nagaev, K. E.

    2016-08-01

    We present a simple quantum-mechanical derivation of correlation function of Langevin sources in the semiclassical Boltzmann-Langevin equation. The specific case of electron-phonon scattering is considered. It is shown that the assumption of weak scattering leads to the Poisson nature of the scattering fluxes.

  14. The Boltzmann-Langevin approach: A simple quantum-mechanical derivation

    NASA Astrophysics Data System (ADS)

    Nagaev, K. E.

    2015-11-01

    We present a simple quantum-mechanical derivation of correlation function of Langevin sources in the semiclassical Boltzmann-Langevin equation. The specific case of electron-phonon scattering is considered. It is shown that the assumption of weak scattering leads to the Poisson nature of the scattering fluxes.

  15. Proceedings of "Optical Probes of Dynamics in Complex Environments"

    SciTech Connect

    Sension, R; Tokmakoff, A

    2008-04-01

    This document contains the proceedings from the symposium on Optical Probes of Dynamics in Complex Environments, which organized as part of the 235th National Meeting of the American Chemical Society in New Orleans, LA from April 6 to 10, 2008. The study of molecular dynamics in chemical reaction and biological processes using time ƒresolved spectroscopy plays an important role in our understanding of energy conversion, storage, and utilization problems. Fundamental studies of chemical reactivity, molecular rearrangements, and charge transport are broadly supported by the DOE Office of Science because of their role in the development of alternative energy sources, the understanding of biological energy conversion processes, the efficient utilization of existing energy resources, and the mitigation of reactive intermediates in radiation chemistry. In addition, time resolved spectroscopy is central to all of DOEs grand challenges for fundamental energy science. This symposium brought together leaders in the field of ultrafast spectroscopy, including experimentalists, theoretical chemists, and simulators, to discuss the most recent scientific and technological advances. DOE support for this conference was used to help young US and international scientists travel to the meeting. The latest technology in ultrafast infrared, optical, and xray spectroscopy and the scientific advances that these methods enable were covered. Particular emphasis was placed on new experimental methods used to probe molecular dynamics in liquids, solids, interfaces, nanostructured materials, and biomolecules.

  16. Dynamics of Crowd Behaviors: From Complex Plane to Quantum Random Fields

    NASA Astrophysics Data System (ADS)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    2015-11-01

    The following sections are included: * Complex Plane Dynamics of Crowds and Groups * Introduction * Complex-Valued Dynamics of Crowd and Group Behaviors * Kähler Geometry of Crowd and Group Dynamics * Computer Simulations of Crowds and Croups Dynamics * Braids of Agents' Behaviors in the Complex Plane * Hilbert-Space Control of Crowds and Groups Dynamics * Quantum Random Fields: A Unique Framework for Simulation, Optimization, Control and Learning * Introduction * Adaptive Quantum Oscillator * Optimization and Learning on Banach and Hilbert Spaces * Appendix * Complex-Valued Image Processing * Linear Integral Equations * Riemann-Liouville Fractional Calculus * Rigorous Geometric Quantization * Supervised Machine-Learning Methods * First-Order Logic and Quantum Random Fields

  17. Measurement and Information Extraction in Complex Dynamics Quantum Computation

    NASA Astrophysics Data System (ADS)

    Casati, Giulio; Montangero, Simone

    Quantum Information processing has several di.erent applications: some of them can be performed controlling only few qubits simultaneously (e.g. quantum teleportation or quantum cryptography) [1]. Usually, the transmission of large amount of information is performed repeating several times the scheme implemented for few qubits. However, to exploit the advantages of quantum computation, the simultaneous control of many qubits is unavoidable [2]. This situation increases the experimental di.culties of quantum computing: maintaining quantum coherence in a large quantum system is a di.cult task. Indeed a quantum computer is a many-body complex system and decoherence, due to the interaction with the external world, will eventually corrupt any quantum computation. Moreover, internal static imperfections can lead to quantum chaos in the quantum register thus destroying computer operability [3]. Indeed, as it has been shown in [4], a critical imperfection strength exists above which the quantum register thermalizes and quantum computation becomes impossible. We showed such e.ects on a quantum computer performing an e.cient algorithm to simulate complex quantum dynamics [5,6].

  18. The application of dynamic light scattering to complex plasmas

    NASA Astrophysics Data System (ADS)

    Aschinger, Andreas; Winter, Jörg

    2012-09-01

    The dynamic light scattering (DLS) technique is applied to the dust component of a complex (dusty) plasma, revealing a Gaussian intensity autocorrelation function for scattering angles between 4° and 175°. The Gaussian decay form represents free (ballistic) particle motion and allows determination of the one-dimensional squared particle velocity \\left \\langle v_x^2\\right \\rangle . At scattering angles below 1°, the intensity autocorrelation function is shown to be a combination of a Gaussian and an exponential function. This allows determination of the particle velocity and the diffusion constants at the same time. The dust system is fully described by the two components of motion in the horizontal and vertical directions. The two components are simultaneously measured on two scattering paths using only a single incident laser beam. In contrast to standard imaging techniques, the DLS method can be applied even to the disordered phase state where the dust particles have very high kinetic energies. In the ordered phase state, the assumptions of the DLS approach were verified by the independent Charge Coupled Device technique on the fundamental kinetic level. Furthermore, a careful discussion of the standard deviation of the DLS method proves that it can be used to study phase transitions of complex plasmas in detail.

  19. Development of metal-bonded Langevin transducer using LiNbO3

    NASA Astrophysics Data System (ADS)

    Ito, Hiroshi; Jimbo, Hikaru; Shiotani, Koichi; Sakai, Nagahide

    2016-07-01

    We newly developed a metal-bonded Langevin transducer using LiNbO3 in order to realize a practical high-power LiNbO3 Langevin transducer. It utilizes metal bonding with a lead-free solder as an assembly method for a Langevin transducer, instead of a bolt as used in a conventional bolt-clamped Langevin transducer. The newly developed metal-bonded LiNbO3 Langevin transducer achieved a high vibration velocity of over 1.5 m/s and stable operation. Because of rigid metal bonding, it does not show nonlinear phenomena such as a jump phenomenon and/or a resonant frequency shift.

  20. Estimation of Instantaneous Complex Dynamics through Lyapunov Exponents: A Study on Heartbeat Dynamics

    PubMed Central

    Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

    2014-01-01

    Measures of nonlinearity and complexity, and in particular the study of Lyapunov exponents, have been increasingly used to characterize dynamical properties of a wide range of biological nonlinear systems, including cardiovascular control. In this work, we present a novel methodology able to effectively estimate the Lyapunov spectrum of a series of stochastic events in an instantaneous fashion. The paradigm relies on a novel point-process high-order nonlinear model of the event series dynamics. The long-term information is taken into account by expanding the linear, quadratic, and cubic Wiener-Volterra kernels with the orthonormal Laguerre basis functions. Applications to synthetic data such as the Hénon map and Rössler attractor, as well as two experimental heartbeat interval datasets (i.e., healthy subjects undergoing postural changes and patients with severe cardiac heart failure), focus on estimation and tracking of the Instantaneous Dominant Lyapunov Exponent (IDLE). The novel cardiovascular assessment demonstrates that our method is able to effectively and instantaneously track the nonlinear autonomic control dynamics, allowing for complexity variability estimations. PMID:25170911

  1. Incorporating geometrically complex vegetation in a computational fluid dynamic framework

    NASA Astrophysics Data System (ADS)

    Boothroyd, Richard; Hardy, Richard; Warburton, Jeff; Rosser, Nick

    2015-04-01

    Vegetation is known to have a significant influence on the hydraulic, geomorphological, and ecological functioning of river systems. Vegetation acts as a blockage to flow, thereby causing additional flow resistance and influencing flow dynamics, in particular flow conveyance. These processes need to be incorporated into flood models to improve predictions used in river management. However, the current practice in representing vegetation in hydraulic models is either through roughness parameterisation or process understanding derived experimentally from flow through highly simplified configurations of fixed, rigid cylinders. It is suggested that such simplifications inadequately describe the geometric complexity that characterises vegetation, and therefore the modelled flow dynamics may be oversimplified. This paper addresses this issue by using an approach combining field and numerical modelling techniques. Terrestrial Laser Scanning (TLS) with waveform processing has been applied to collect a sub-mm, 3-dimensional representation of Prunus laurocerasus, an invasive species to the UK that has been increasingly recorded in riparian zones. Multiple scan perspectives produce a highly detailed point cloud (>5,000,000 individual data points) which is reduced in post processing using an octree-based voxelisation technique. The method retains the geometric complexity of the vegetation by subdividing the point cloud into 0.01 m3 cubic voxels. The voxelised representation is subsequently read into a computational fluid dynamic (CFD) model using a Mass Flux Scaling Algorithm, allowing the vegetation to be directly represented in the modelling framework. Results demonstrate the development of a complex flow field around the vegetation. The downstream velocity profile is characterised by two distinct inflection points. A high velocity zone in the near-bed (plant-stem) region is apparent due to the lack of significant near-bed foliage. Above this, a zone of reduced velocity is

  2. Quantum Dynamical Behaviour in Complex Systems - A Semiclassical Approach

    SciTech Connect

    Ananth, Nandini

    2008-01-01

    One of the biggest challenges in Chemical Dynamics is describing the behavior of complex systems accurately. Classical MD simulations have evolved to a point where calculations involving thousands of atoms are routinely carried out. Capturing coherence, tunneling and other such quantum effects for these systems, however, has proven considerably harder. Semiclassical methods such as the Initial Value Representation (SC-IVR) provide a practical way to include quantum effects while still utilizing only classical trajectory information. For smaller systems, this method has been proven to be most effective, encouraging the hope that it can be extended to deal with a large number of degrees of freedom. Several variations upon the original idea of the SCIVR have been developed to help make these larger calculations more tractable; these range from the simplest, classical limit form, the Linearized IVR (LSC-IVR) to the quantum limit form, the Exact Forward-Backward version (EFB-IVR). In this thesis a method to tune between these limits is described which allows us to choose exactly which degrees of freedom we wish to treat in a more quantum mechanical fashion and to what extent. This formulation is called the Tuning IVR (TIVR). We further describe methodology being developed to evaluate the prefactor term that appears in the IVR formalism. The regular prefactor is composed of the Monodromy matrices (jacobians of the transformation from initial to finial coordinates and momenta) which are time evolved using the Hessian. Standard MD simulations require the potential surfaces and their gradients, but very rarely is there any information on the second derivative. We would like to be able to carry out the SC-IVR calculation without this information too. With this in mind a finite difference scheme to obtain the Hessian on-the-fly is proposed. Wealso apply the IVR formalism to a few problems of current interest. A method to obtain energy eigenvalues accurately for complex

  3. Complexity and Dynamic Heterogeneity of the Process of Cancer Metastasis

    NASA Astrophysics Data System (ADS)

    Chambers, Ann

    2010-03-01

    Cancer metastasis -- the spread of cancer from a primary tumor to distant parts of the body -- is responsible for most cancer deaths. If cancer is detected early, before it has spread, it can often be treated with local therapies like surgery and radiation. If cancer is detected after it has already spread, it is much harder to treat successfully. Cancer cells may be distributed to many organs, may be present as tiny micrometastases that are hard to detect, and cancer cells can be in a dormant state that may be resistant to treatment that is directed against actively dividing cells. A better understanding of the process of metastasis thus is needed in order to improve survival from cancer. Cancer is not a static disease, but one that can undergo stepwise evolution and progression from early, treatable cancer to aggressive cancer that is harder to treat. Furthermore, cancers are made up of many cells, and there is considerable heterogeneity among the cells in a tumor. Thus, cancer is ``plastic,'' with heterogeneity among cancer cells and changes over time. Understanding this ``dynamic heterogeneity'' has proven to be difficult. Input from physical sciences disciplines may help to shed light on this complex aspect of cancer biology. Here the process of cancer metastasis will be discussed, and experimental models for imaging the process described. The concept of ``dynamic heterogeneity'' of the metastatic process will be discussed, and some of the questions that need to be addressed for better understanding of metastasis will be outlined. An evolving dialogue between cancer biologists and physical scientists may lead to new ways of studying and understanding this lethal aspect of cancer.

  4. The generalized Schrödinger–Langevin equation

    SciTech Connect

    Bargueño, Pedro; Miret-Artés, Salvador

    2014-07-15

    In this work, for a Brownian particle interacting with a heat bath, we derive a generalization of the so-called Schrödinger–Langevin or Kostin equation. This generalization is based on a nonlinear interaction model providing a state-dependent dissipation process exhibiting multiplicative noise. Two straightforward applications to the measurement process are then analyzed, continuous and weak measurements in terms of the quantum Bohmian trajectory formalism. Finally, it is also shown that the generalized uncertainty principle, which appears in some approaches to quantum gravity, can be expressed in terms of this generalized equation. -- Highlights: •We generalize the Kostin equation for arbitrary system–bath coupling. •This generalization is developed both in the Schrödinger and Bohmian formalisms. •We write the generalized Kostin equation for two measurement problems. •We reformulate the generalized uncertainty principle in terms of this equation.

  5. Fluctuation analysis of time-averaged mean-square displacement for the Langevin equation with time-dependent and fluctuating diffusivity

    NASA Astrophysics Data System (ADS)

    Uneyama, Takashi; Miyaguchi, Tomoshige; Akimoto, Takuma

    2015-09-01

    The mean-square displacement (MSD) is widely utilized to study the dynamical properties of stochastic processes. The time-averaged MSD (TAMSD) provides some information on the dynamics which cannot be extracted from the ensemble-averaged MSD. In particular, the relative standard deviation (RSD) of the TAMSD can be utilized to study the long-time relaxation behavior. In this work, we consider a class of Langevin equations which are multiplicatively coupled to time-dependent and fluctuating diffusivities. Various interesting dynamics models such as entangled polymers and supercooled liquids can be interpreted as the Langevin equations with time-dependent and fluctuating diffusivities. We derive a general formula for the RSD of the TAMSD for the Langevin equation with the time-dependent and fluctuating diffusivity. We show that the RSD can be expressed in terms of the correlation function of the diffusivity. The RSD exhibits the crossover at the long time region. The crossover time is related to a weighted average relaxation time for the diffusivity. Thus the crossover time gives some information on the relaxation time of fluctuating diffusivity which cannot be extracted from the ensemble-averaged MSD. We discuss the universality and possible applications of the formula via some simple examples.

  6. Harmonically bound Brownian motion in fluids under shear: Fokker-Planck and generalized Langevin descriptions.

    PubMed

    Híjar, Humberto

    2015-02-01

    We study the Brownian motion of a particle bound by a harmonic potential and immersed in a fluid with a uniform shear flow. We describe this problem first in terms of a linear Fokker-Planck equation which is solved to obtain the probability distribution function for finding the particle in a volume element of its associated phase space. We find the explicit form of this distribution in the stationary limit and use this result to show that both the equipartition law and the equation of state of the trapped particle are modified from their equilibrium form by terms increasing as the square of the imposed shear rate. Subsequently, we propose an alternative description of this problem in terms of a generalized Langevin equation that takes into account the effects of hydrodynamic correlations and sound propagation on the dynamics of the trapped particle. We show that these effects produce significant changes, manifested as long-time tails and resonant peaks, in the equilibrium and nonequilibrium correlation functions for the velocity of the Brownian particle. We implement numerical simulations based on molecular dynamics and multiparticle collision dynamics, and observe a very good quantitative agreement between the predictions of the model and the numerical results, thus suggesting that this kind of numerical simulations could be used as complement of current experimental techniques. PMID:25768490

  7. Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

    PubMed Central

    Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

    2015-01-01

    The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

  8. Molecular Dynamics of Mouse Acetylcholinesterase Complexed with Huperzine A

    SciTech Connect

    Tara, Sylvia; Helms, Volkhard H.; Straatsma, TP; Mccammon, J Andrew A.

    1999-03-16

    Two molecular dynamics simulations were performed for a modeled complex of mouse acetylcholinesterase liganded with huperzine A (HupA). Analysis of these simulations shows that HupA shifts in the active site toward Tyr 337 and Phe 338, and that several residues in the active site area reach out to make hydrogen bonds with the inhibitor. Rapid fluctuations of the gorge width are observed, ranging from widths that allow substrate access to the active site, to pinched structures that do not allow access of molecules as small as water. Additional openings or channels to the active site are found. One opening is formed in the side wall of the active site gorge by residues Val 73, Asp 74, Thr 83, Glu 84, and Asn 87. Another opening is formed at the base of the gorge by residues Trp 86, Val 132, Glu 202, Gly 448, and Ile 451. Both of these openings have been observed separately in the Torpedo californica form of the enzyme. These channels could allow transport of waters and ions to and from the bulk solution.

  9. Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

    PubMed

    Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

    2015-01-01

    The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

  10. Statistical characterization of complex object structure by dynamic tomography

    NASA Astrophysics Data System (ADS)

    Tillack, Gerd-Rüdiger; Goebbels, Jürgen; Illerhaus, Bernhard; Artemiev, Valentin; Naumov, Alexander

    2002-05-01

    Considering modern materials like reinforced plastics or metal foams the mechanical properties of the component are not determined by every single structural element like a single fiber in a composite. Moreover the ensemble mean and correlation properties of all structural elements form the mechanical properties of the component. Accordingly a statistical description of material properties on a macroscopic scale allow to characterize its mechanical behavior or aging. State of the art tomographic techniques assign a measure of material properties to a volume element. The discretization, i.e., the volume or size of a single element, is limited mainly by the physical mechanisms and the equipment used for the data acquisition. In any case the result of reconstruction yields a statistical average within the considered volume element. To evaluate the integrity of the component the determined measures have to be correlated with the mechanical properties of the component. Special reconstruction algorithms are investigated that allow the statistical description of complex object structures including its dynamics. The algorithm is based on the Kalman filter using statistical prior. The prior includes knowledge about the covariance matrix as well as a prior assumption about the probability density distribution function. The resulting algorithm is recursive yielding a quasi-optimal solution at every reconstruction step. The applicability of the developed algorithm is discussed for the investigation of a specimen made from aluminum foam.

  11. Notes on the Langevin model for turbulent diffusion of ``marked`` particles

    SciTech Connect

    Rodean, H.C.

    1994-01-26

    Three models for scalar diffusion in turbulent flow (eddy diffusivity, random displacement, and on the Langevin equation) are briefly described. These models random velocity increment based Fokker-Planck equation is introduced as are then examined in more detail in the reverse order. The Fokker-Planck equation is the Eulerian equivalent of the Lagrangian Langevin equation, and the derivation of e outlined. The procedure for obtaining the deterministic and stochastic components of the Langevin equation from Kolmogorov`s 1941 inertial range theory and the Fokker-Planck equation is described. it is noted that a unique form of the Langevin equation can be determined for diffusion in one dimension but not in two or three. The Langevin equation for vertical diffusion in the non-Gaussian convective boundary layer is presented and successively simplified for Gaussian inhomogeneous turbulence and Gaussian homogeneous turbulence in turn. The Langevin equation for Gaussian inhomogeneous turbulence is mathematically transformed into the random displacement model. It is shown how the Fokker-Planck equation for the random displacement model is identical in form to the partial differential equation for the eddy diffusivity model. It is noted that the Langevin model is applicable in two cases in which the other two are not valid: (1) very close in time and distance to the point of scalar release and (2) the non-Gaussian convective boundary layer. The two- and three-dimensional cases are considered in Part III.

  12. Self-consistent generalized Langevin-equation theory for liquids of nonspherically interacting particles.

    PubMed

    Elizondo-Aguilera, L F; Zubieta Rico, P F; Ruiz-Estrada, H; Alarcón-Waess, O

    2014-11-01

    A self-consistent generalized Langevin-equation theory is proposed to describe the self- and collective dynamics of a liquid of linear Brownian particles. The equations of motion for the spherical harmonics projections of the collective and self-intermediate-scattering functions, F_{lm,lm}(k,t) and F_{lm,lm}^{S}(k,t), are derived as a contraction of the description involving the stochastic equations of the corresponding tensorial one-particle density n_{lm}(k,t) and the translational (α=T) and rotational (α=R) current densities j_{lm}^{α}(k,t). Similar to the spherical case, these dynamic equations require as an external input the equilibrium structural properties of the system contained in the projections of the static structure factor, denoted by S_{lm,lm}(k). Complementing these exact equations with simple (Vineyard-like) approximate relations for the collective and the self-memory functions we propose a closed self-consistent set of equations for the dynamic properties involved. In the long-time asymptotic limit, these equations become the so-called bifurcation equations, whose solutions (the nonergodicity parameters) can be written, extending the spherical case, in terms of one translational and one orientational scalar dynamic order parameter, γ_{T} and γ_{R}, which characterize the possible dynamical arrest transitions of the system. As a concrete illustrative application of this theory we determine the dynamic arrest diagram of the dipolar hard-sphere fluid. In qualitative agreement with mode coupling theory, the present self-consistent equations also predict three different regions in the state space spanned by the macroscopic control parameters η (volume fraction) and T* (scaled temperature): a region of fully ergodic states, a region of mixed states, in which the translational degrees of freedom become arrested while the orientational degrees of freedom remain ergodic, and a region of fully nonergodic states. PMID:25493790

  13. Stochastic thermodynamics of Langevin systems under time-delayed feedback control: Second-law-like inequalities.

    PubMed

    Rosinberg, M L; Munakata, T; Tarjus, G

    2015-04-01

    Response lags are generic to almost any physical system and often play a crucial role in the feedback loops present in artificial nanodevices and biological molecular machines. In this paper, we perform a comprehensive study of small stochastic systems governed by an underdamped Langevin equation and driven out of equilibrium by a time-delayed continuous feedback control. In their normal operating regime, these systems settle in a nonequilibrium steady state in which work is permanently extracted from the surrounding heat bath. By using the Fokker-Planck representation of the dynamics, we derive a set of second-law-like inequalities that provide bounds to the rate of extracted work. These inequalities involve additional contributions characterizing the reduction of entropy production due to the continuous measurement process. We also show that the non-Markovian nature of the dynamics requires a modification of the basic relation linking dissipation to the breaking of time-reversal symmetry at the level of trajectories. The modified relation includes a contribution arising from the acausal character of the reverse process. This, in turn, leads to another second-law-like inequality. We illustrate the general formalism with a detailed analytical and numerical study of a harmonic oscillator driven by a linear feedback, which describes actual experimental setups. PMID:25974446

  14. Stochastic thermodynamics of Langevin systems under time-delayed feedback control: Second-law-like inequalities

    NASA Astrophysics Data System (ADS)

    Rosinberg, M. L.; Munakata, T.; Tarjus, G.

    2015-04-01

    Response lags are generic to almost any physical system and often play a crucial role in the feedback loops present in artificial nanodevices and biological molecular machines. In this paper, we perform a comprehensive study of small stochastic systems governed by an underdamped Langevin equation and driven out of equilibrium by a time-delayed continuous feedback control. In their normal operating regime, these systems settle in a nonequilibrium steady state in which work is permanently extracted from the surrounding heat bath. By using the Fokker-Planck representation of the dynamics, we derive a set of second-law-like inequalities that provide bounds to the rate of extracted work. These inequalities involve additional contributions characterizing the reduction of entropy production due to the continuous measurement process. We also show that the non-Markovian nature of the dynamics requires a modification of the basic relation linking dissipation to the breaking of time-reversal symmetry at the level of trajectories. The modified relation includes a contribution arising from the acausal character of the reverse process. This, in turn, leads to another second-law-like inequality. We illustrate the general formalism with a detailed analytical and numerical study of a harmonic oscillator driven by a linear feedback, which describes actual experimental setups.

  15. Energetic modeling and single-molecule verification of dynamic regulation on receptor complexes by actin corrals and lipid raft domains

    NASA Astrophysics Data System (ADS)

    Lin, Chien Y.; Huang, Jung Y.; Lo, Leu-Wei

    2014-12-01

    We developed an energetic model by integrating the generalized Langevin equation with the Cahn-Hilliard equation to simulate the diffusive behaviors of receptor proteins in the plasma membrane of a living cell. Simulation results are presented to elaborate the confinement effects from actin corrals and protein-induced lipid domains. Single-molecule tracking data of epidermal growth factor receptors (EGFR) acquired on live HeLa cells agree with the simulation results and the mechanism that controls the diffusion of single-molecule receptors is clarified. We discovered that after ligand binding, EGFR molecules move into lipid nanodomains. The transition rates between different diffusion states of liganded EGFR molecules are regulated by the lipid domains. Our method successfully captures dynamic interactions of receptors at the single-molecule level and provides insight into the functional architecture of both the diffusing EGFR molecules and their local cellular environment.

  16. Classification of time series patterns from complex dynamic systems

    SciTech Connect

    Schryver, J.C.; Rao, N.

    1998-07-01

    An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately, the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.

  17. Sinks without borders: Snowshoe hare dynamics in a complex landscape

    USGS Publications Warehouse

    Griffin, P.C.; Scott, Mills L.

    2009-01-01

    A full understanding of population dynamics of wide-ranging animals should account for the effects that movement and habitat use have on individual contributions to population growth or decline. Quantifying the per-capita, habitat-specific contribution to population growth can clarify the value of different patch types, and help to differentiate population sources from population sinks. Snowshoe hares, Lepus americanus, routinely use various habitat types in the landscapes they inhabit in the contiguous US, where managing forests for high snowshoe hare density is a priority for conservation of Canada lynx, Lynx canadensis. We estimated density and demographic rates via mark-recapture live trapping and radio-telemetry within four forest stand structure (FSS) types at three study areas within heterogeneous managed forests in western Montana. We found support for known fate survival models with time-varying individual covariates representing the proportion of locations in each of the FSS types, with survival rates decreasing as use of open young and open mature FSS types increased. The per-capita contribution to overall population growth increased with use of the dense mature or dense young FSS types and decreased with use of the open young or open mature FSS types, and relatively high levels of immigration appear to be necessary to sustain hares in the open FSS types. Our results support a conceptual model for snowshoe hares in the southern range in which sink habitats (open areas) prevent the buildup of high hare densities. More broadly, we use this system to develop a novel approach to quantify demographic sources and sinks for animals making routine movements through complex fragmented landscapes. ?? 2009 Oikos.

  18. Dynamics of Complexity and Accuracy: A Longitudinal Case Study of Advanced Untutored Development

    ERIC Educational Resources Information Center

    Polat, Brittany; Kim, Youjin

    2014-01-01

    This longitudinal case study follows a dynamic systems approach to investigate an under-studied research area in second language acquisition, the development of complexity and accuracy for an advanced untutored learner of English. Using the analytical tools of dynamic systems theory (Verspoor et al. 2011) within the framework of complexity,…

  19. Theoretical Studies on Docking Dynamics and Electronic Structure in Metalloprotein Complexes

    NASA Astrophysics Data System (ADS)

    Sugiyama, Ayumu; Nishikawa, Keigo; Yamamoto, Tetsunori; Purqon, Acep; Nishikawa, Kiyoshi; Nagao, Hidemi

    2007-12-01

    An investigating of docking structure and dynamics between metalloprotein is interested from the viewpoint of searching the function of protein. We investigate the cytochrome c551 and azurin complexes by three computational methods, quantum mechanical calculation, docking searching algorism and molecular dynamics simulation. At first we present the docking structure of the cytochrome c551-azurin complexes expected by ZDOCK searching algorism. Quantum chemical calculation is tools to estimate the charge distrubution around the active site for each protein and force field parameters. From these parameters, we reproduce the protein docking dynamics by molecular dynamics simulation. We analyze some physical properties of complex system such as binding free energy, dynamical cross correlation map, and so on. We discuss the docking stability and dynamical effect of the cytochrome c551-azurin complexes.

  20. Inclusion of trial functions in the Langevin equation path integral ground state method: Application to parahydrogen clusters and their isotopologues

    NASA Astrophysics Data System (ADS)

    Schmidt, Matthew; Constable, Steve; Ing, Christopher; Roy, Pierre-Nicholas

    2014-06-01

    We developed and studied the implementation of trial wavefunctions in the newly proposed Langevin equation Path Integral Ground State (LePIGS) method [S. Constable, M. Schmidt, C. Ing, T. Zeng, and P.-N. Roy, J. Phys. Chem. A 117, 7461 (2013)]. The LePIGS method is based on the Path Integral Ground State (PIGS) formalism combined with Path Integral Molecular Dynamics sampling using a Langevin equation based sampling of the canonical distribution. This LePIGS method originally incorporated a trivial trial wavefunction, ψT, equal to unity. The present paper assesses the effectiveness of three different trial wavefunctions on three isotopes of hydrogen for cluster sizes N = 4, 8, and 13. The trial wavefunctions of interest are the unity trial wavefunction used in the original LePIGS work, a Jastrow trial wavefunction that includes correlations due to hard-core repulsions, and a normal mode trial wavefunction that includes information on the equilibrium geometry. Based on this analysis, we opt for the Jastrow wavefunction to calculate energetic and structural properties for parahydrogen, orthodeuterium, and paratritium clusters of size N = 4 - 19, 33. Energetic and structural properties are obtained and compared to earlier work based on Monte Carlo PIGS simulations to study the accuracy of the proposed approach. The new results for paratritium clusters will serve as benchmark for future studies. This paper provides a detailed, yet general method for optimizing the necessary parameters required for the study of the ground state of a large variety of systems.

  1. Inclusion of trial functions in the Langevin equation path integral ground state method: Application to parahydrogen clusters and their isotopologues

    SciTech Connect

    Schmidt, Matthew; Constable, Steve; Ing, Christopher; Roy, Pierre-Nicholas

    2014-06-21

    We developed and studied the implementation of trial wavefunctions in the newly proposed Langevin equation Path Integral Ground State (LePIGS) method [S. Constable, M. Schmidt, C. Ing, T. Zeng, and P.-N. Roy, J. Phys. Chem. A 117, 7461 (2013)]. The LePIGS method is based on the Path Integral Ground State (PIGS) formalism combined with Path Integral Molecular Dynamics sampling using a Langevin equation based sampling of the canonical distribution. This LePIGS method originally incorporated a trivial trial wavefunction, ψ{sub T}, equal to unity. The present paper assesses the effectiveness of three different trial wavefunctions on three isotopes of hydrogen for cluster sizes N = 4, 8, and 13. The trial wavefunctions of interest are the unity trial wavefunction used in the original LePIGS work, a Jastrow trial wavefunction that includes correlations due to hard-core repulsions, and a normal mode trial wavefunction that includes information on the equilibrium geometry. Based on this analysis, we opt for the Jastrow wavefunction to calculate energetic and structural properties for parahydrogen, orthodeuterium, and paratritium clusters of size N = 4 − 19, 33. Energetic and structural properties are obtained and compared to earlier work based on Monte Carlo PIGS simulations to study the accuracy of the proposed approach. The new results for paratritium clusters will serve as benchmark for future studies. This paper provides a detailed, yet general method for optimizing the necessary parameters required for the study of the ground state of a large variety of systems.

  2. Evaluation of minor hysteresis loops using Langevin transforms in modified inverse Jiles-Atherton model

    NASA Astrophysics Data System (ADS)

    Hamimid, M.; Mimoune, S. M.; Feliachi, M.

    2013-11-01

    In this paper, we present a Langevin transforms model which evaluates accurately minor hysteresis loops for the modified inverse Jiles-Atherton model by using appropriate expressions in order to improve minor hysteresis loops characteristics. The parameters of minor hysteresis loops are then related to the parameters of the major hysteresis loop according to each level of maximal induction by using Langevin transforms expressions. The stochastic optimization method “simulated annealing” is used for the determination of the Langevin transforms coefficients. This model needs only two experimental tests to generate all hysteresis loops. The validity of the Langevin transforms model is justified by comparison of calculated minor hysteresis loops to measured ones and good agreements are obtained with better results than the exponential transforms model (Hamimid et al., 2011 [4]).

  3. The complex interplay between mitochondrial dynamics and cardiac metabolism.

    PubMed

    Parra, Valentina; Verdejo, Hugo; del Campo, Andrea; Pennanen, Christian; Kuzmicic, Jovan; Iglewski, Myriam; Hill, Joseph A; Rothermel, Beverly A; Lavandero, Sergio

    2011-02-01

    Mitochondria are highly dynamic organelles, capable of undergoing constant fission and fusion events, forming networks. These dynamic events allow the transmission of chemical and physical messengers and the exchange of metabolites within the cell. In this article we review the signaling mechanisms controlling mitochondrial fission and fusion, and its relationship with cell bioenergetics, especially in the heart. Furthermore we also discuss how defects in mitochondrial dynamics might be involved in the pathogenesis of metabolic cardiac diseases. PMID:21258852

  4. The complex interplay between mitochondrial dynamics and cardiac metabolism

    PubMed Central

    Parra, Valentina; Verdejo, Hugo; del Campo, Andrea; Pennanen, Christian; Kuzmicic, Jovan; Iglewski, Myriam; Hill, Joseph A.; Rothermel, Beverly A.

    2012-01-01

    Mitochondria are highly dynamic organelles, capable of undergoing constant fission and fusion events, forming networks. These dynamic events allow the transmission of chemical and physical messengers and the exchange of metabolites within the cell. In this article we review the signaling mechanisms controlling mitochondrial fission and fusion, and its relationship with cell bioenergetics, especially in the heart. Furthermore we also discuss how defects in mitochondrial dynamics might be involved in the pathogenesis of metabolic cardiac diseases. PMID:21258852

  5. Stochastic Cascade Dynamical Downscaling of Precipitation over Complex Terrain

    NASA Astrophysics Data System (ADS)

    Posadas, A.; Duffaut, L. E.; Jones, C.; Carvalho, L. V.; Carbajal, M.; Heidinger, H.; Quiroz, R.

    2013-12-01

    spatial and temporal variability of rainfall between the rainfall fields obtained from the rain gauge network and those generated by the simulation model. The potential advantages of this methodology are discussed.Stochastic Cascade Dynamical Downscaling of Precipitation over Complex Terrain

  6. Irreversible Langevin samplers and variance reduction: a large deviations approach

    NASA Astrophysics Data System (ADS)

    Rey-Bellet, Luc; Spiliopoulos, Konstantinos

    2015-07-01

    In order to sample from a given target distribution (often of Gibbs type), the Monte Carlo Markov chain method consists of constructing an ergodic Markov process whose invariant measure is the target distribution. By sampling the Markov process one can then compute, approximately, expectations of observables with respect to the target distribution. Often the Markov processes used in practice are time-reversible (i.e. they satisfy detailed balance), but our main goal here is to assess and quantify how the addition of a non-reversible part to the process can be used to improve the sampling properties. We focus on the diffusion setting (overdamped Langevin equations) where the drift consists of a gradient vector field as well as another drift which breaks the reversibility of the process but is chosen to preserve the Gibbs measure. In this paper we use the large deviation rate function for the empirical measure as a tool to analyze the speed of convergence to the invariant measure. We show that the addition of an irreversible drift leads to a larger rate function and it strictly improves the speed of convergence of ergodic average for (generic smooth) observables. We also deduce from this result that the asymptotic variance decreases under the addition of the irreversible drift and we give an explicit characterization of the observables whose variance is not reduced reduced, in terms of a nonlinear Poisson equation. Our theoretical results are illustrated and supplemented by numerical simulations.

  7. Complexities of Organization Dynamics and Development: Leaders and Managers

    ERIC Educational Resources Information Center

    Nderu-Boddington, Eulalee

    2008-01-01

    This article shows the theoretical framework for understanding organizational dynamics and development - the change theory and subordinate relationships within contemporary organizations. The emphasis is on power strategies and the relationship to organizational dynamics and development. The integrative process broadens the understanding of…

  8. Overview of nonlinear dynamical systems and complexity theory

    SciTech Connect

    Herbert, D.E.

    1996-06-01

    A brief overview is presented of the principal elements of {open_quote}{open_quote}nonlinear dynamics{close_quote}{close_quote}: catastrophes, fractals, chaos, solitary waves, and coherent and dissipative structures. The text is followed by a set of 10 portraits of the strange and violent world of nonlinear dynamics. {copyright} {ital 1996 American Institute of Physics.}

  9. 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.

  10. Complexity, Chaos, and Nonlinear Dynamics: A New Perspective on Career Development Theory

    ERIC Educational Resources Information Center

    Bloch, Deborah P.

    2005-01-01

    The author presents a theory of career development drawing on nonlinear dynamics and chaos and complexity theories. Career is presented as a complex adaptive entity, a fractal of the human entity. Characteristics of complex adaptive entities, including (a) autopiesis, or self-regeneration; (b) open exchange; (c) participation in networks; (d)…

  11. A smart pinless ejection mechanism using dual-resonance excitation Langevin piezoelectric transducers

    NASA Astrophysics Data System (ADS)

    Wang, Yu-Jen; Fu, Kuo-Chieh; Wang, Chun-Chieh

    2016-01-01

    This study investigated a smart pinless ejection mechanism comprising two dual-resonance excitation Langevin piezoelectric transducers (DRELPTs) for keeping the injection parts intact and protecting their top and bottom surfaces from scarring during plastic injection molding. The dimensions of each DRELPT were determined using longitudinal vibration models, and an optimization method was used to set the frequency ratio of the first to the second longitudinal mode to 1:2. This concept enables the driving of DRELPT in its two longitudinal modes consistent with the ejection direction in resonant-type smooth impact drive mechanisms. During the ejection process, DRELPT provides an ejection force, which is applied on the sidewalls of the injection parts to protect their top and bottom surfaces from scarring. Considering individual differences in the resonance frequencies of DRELPTs, a resonance frequency tracking circuit based on a phase-locked loop was designed to keep DRELPT actuating in resonance. The ejection velocity of the injection part was estimated using the kinetic models derived from the dynamic behavior of the mold cavity and injection parameters. A characteristic number S was defined to evaluate the average velocity of the injection part during ejection. Proof-of-concept experimental results of the pinless ejection mechanism are presented. The ejection time, that is, the time from triggering the composite wave to the full departure of the injection part from the mold cavity, was 72 ms.

  12. Langevin Bimolecular Recombination Kinetics of a Layered Exciton-Trion Gas

    NASA Astrophysics Data System (ADS)

    Crowne, Frank; Birdwell, Anthony

    The use of rate equations to describe various many-body kinetic processes in highly photoexcited layered semiconductors is discussed. In these systems, pairs of electrons and holes generated by photons from an external laser combine to form a multicomponent plasma whose time evolution is governed by gas dynamics and various recombination processes. At high levels of illumination this leads to a variety of secondary components in addition to neutral excitons, notably the so-called trions, which consist of exciton-electron and exciton-hole bound states. Although the recombination is modeled as bimolecular for all pairs of carrier species, the structure of the rate terms is sensitive to the dimensionality of the system due to the Langevin nature of encounters between carriers. It is demonstrated that charge neutrality does not apply to individual carrier species, e.g., electron and hole densities need not be equal in the presence of trions. In order to track the full time evolution from laser initiation to steady state, the system of rate equations is simulated numerically.

  13. Non-Gaussian statistics, classical field theory, and realizable Langevin models

    SciTech Connect

    Krommes, J.A.

    1995-11-01

    The direct-interaction approximation (DIA) to the fourth-order statistic Z {approximately}{l_angle}{lambda}{psi}{sup 2}){sup 2}{r_angle}, where {lambda} is a specified operator and {psi} is a random field, is discussed from several points of view distinct from that of Chen et al. [Phys. Fluids A 1, 1844 (1989)]. It is shown that the formula for Z{sub DIA} already appeared in the seminal work of Martin, Siggia, and Rose (Phys. Rev. A 8, 423 (1973)] on the functional approach to classical statistical dynamics. It does not follow from the original generalized Langevin equation (GLE) of Leith [J. Atmos. Sd. 28, 145 (1971)] and Kraichnan [J. Fluid Mech. 41, 189 (1970)] (frequently described as an amplitude representation for the DIA), in which the random forcing is realized by a particular superposition of products of random variables. The relationship of that GLE to renormalized field theories with non-Gaussian corrections (``spurious vertices``) is described. It is shown how to derive an improved representation, that realizes cumulants through O({psi}{sup 4}), by adding to the GLE a particular non-Gaussian correction. A Markovian approximation Z{sub DIA}{sup M} to Z{sub DIA} is derived. Both Z{sub DIA} and Z{sub DIA}{sup M} incorrectly predict a Gaussian kurtosis for the steady state of a solvable three-mode example.

  14. The Spatial Chemical Langevin and Reaction Diffusion Master Equations: Moments and Qualitative Solutions

    NASA Astrophysics Data System (ADS)

    Ghosh, Atiyo; Leier, Andre; Marquez-Lago, Tatiana

    2014-03-01

    Spatial stochastic effects are prevalent in many biological systems spanning a variety of scales, from intracellular (e.g. gene expression) to ecological (plankton aggregation). The most common ways of simulating such systems involve drawing sample paths from either the Reaction Diffusion Master Equation (RDME) or the Smoluchowski Equation, using methods such as Gillespie's Simulation Algorithm, Green's Function Reaction Dynamics and Single Particle Tracking. The simulation times of such techniques scale with the number of simulated particles, leading to much computational expense when considering large systems. The Spatial Chemical Langevin Equation (SCLE) can be simulated with fixed time intervals, independent of the number of particles, and can thus provide significant computational savings. However, very little work has been done to investigate the behavior of the SCLE. In this talk we summarize our findings on comparing the SCLE to the well-studied RDME. We use both analytical and numerical procedures to show when one should expect the moments of the SCLE to be close to the RDME, and also when they should differ.

  15. COMBINED DELAY AND GRAPH EMBEDDING OF EPILEPTIC DISCHARGES IN EEG REVEALS COMPLEX AND RECURRENT NONLINEAR DYNAMICS

    PubMed Central

    Erem, B.; Hyde, D.E.; Peters, J.M.; Duffy, F.H.; Brooks, D.H.; Warfield, S.K.

    2015-01-01

    The dynamical structure of the brain’s electrical signals contains valuable information about its physiology. Here we combine techniques for nonlinear dynamical analysis and manifold identification to reveal complex and recurrent dynamics in interictal epileptiform discharges (IEDs). Our results suggest that recurrent IEDs exhibit some consistent dynamics, which may only last briefly, and so individual IED dynamics may need to be considered in order to understand their genesis. This could potentially serve to constrain the dynamics of the inverse source localization problem. PMID:26366250

  16. Analysis of screw pitch effects on the performance of bolt-clamped Langevin-type transducers

    NASA Astrophysics Data System (ADS)

    Adachi, Kazunari; Takahashi, Toru; Hasegawa, Hiroshi

    2004-09-01

    Bolt-clamped Langevin-type transducers (BLTs) are common vibration sources in high-power ultrasonic applications such as ultrasonic plastic joining. In this paper, the authors propose a low-aspect-ratio BLT shape based on numerical solutions of a complex elastic contact problem concerning the bearing stress (prestress) imposed on the interfaces between the parts by clamping with the screw bolt. The prestress distribution at the interface has significant influence on the mechanical quality factor (Q) of the BLT. It is found that the screw pitch of the clamping bolt heavily affects the prestress distribution in the simulation using the finite element method. The newly developed BLTs with a high resonance frequency of approximately 80 kHz has a relatively wide radiating face and sufficient volume ratio of the piezoelectric elements that convert electrical energy into mechanical energy. The average of their measured Q values exceeds 1000 despite their high resonance frequency when they are driven at a voltage higher than 17 V rms.

  17. Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes.

    PubMed

    Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon

    2015-09-14

    Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area. PMID:25913176

  18. The Influence of Information Acquisition on the Complex Dynamics of Market Competition

    NASA Astrophysics Data System (ADS)

    Guo, Zhanbing; Ma, Junhai

    In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

  19. Structural dynamics in complex liquids studied with multidimensional vibrational spectroscopy

    SciTech Connect

    Tokmakoff, Andrei

    2013-08-31

    The development of new sustainable energy sources is linked to our understanding of the molecular properties of water and aqueous solutions. Energy conversion, storage, and transduction processes, particularly those that occur in biology, fuel cells, and batteries, make use of water for the purpose of moving energy in the form of charges and mediating the redox chemistry that allows this energy to be stored as and released from chemical bonds. To build our fundamental knowledge in this area, this project supports work in the Tokmakoff group to investigate the molecular dynamics of water’s hydrogen bond network, and how these dynamics influence its solutes and the mechanism of proton transport in water. To reach the goals of this grant, we developed experiments to observe molecular dynamics in water as directly as possible, using ultrafast multidimensional vibrational spectroscopy. We excite and probe broad vibrational resonances of water, molecular solutes, and protons in water. By correlating how molecules evolve from an initial excitation frequency to a final frequency, we can describe the underlying molecular dynamics. Theoretical modeling of the data with the help of computational spectroscopy coupled with molecular dynamics simulations provided the atomistic insight in these studies.

  20. Langevin equation with fluctuating diffusivity: A two-state model

    NASA Astrophysics Data System (ADS)

    Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

    2016-07-01

    Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool.

  1. Langevin equation with fluctuating diffusivity: A two-state model.

    PubMed

    Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

    2016-07-01

    Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool. PMID:27575079

  2. Patchy environment as a factor of complex plankton dynamics

    NASA Astrophysics Data System (ADS)

    Medvinsky, Alexander B.; Tikhonova, Irene A.; Aliev, Rubin R.; Li, Bai-Lian; Lin, Zhen-Shan; Malchow, Horst

    2001-08-01

    We study the role of the diffusive interaction in plankton dynamics in a patchy environment. We use a minimal reaction-diffusion model of the nutrient-plankton-fish food chain to simulate the diffusive interaction between fish-populated and fish-free habitats. We show that such interaction can give rise to spatiotemporal plankton patterns. The plankton dynamics depend on the fish predation rate and can exhibit both regular and chaotic behavior. We show that limit cycle and chaotic attractor coexist in the system. The entire basin of attraction of the limit cycles is found to be riddled with ``holes'' leading to the competitive chaotic attractors. The chaotic dynamics is typical of a wide range of the fish predation rates.

  3. Unraveling the complexity of mitochondrial complex I assembly: A dynamic process.

    PubMed

    Sánchez-Caballero, Laura; Guerrero-Castillo, Sergio; Nijtmans, Leo

    2016-07-01

    Mammalian complex I is composed of 44 different subunits and its assembly requires at least 13 specific assembly factors. Proper function of the mitochondrial respiratory chain enzyme is of crucial importance for cell survival due to its major participation in energy production and cell signaling. Complex I assembly depends on the coordination of several crucial processes that need to be tightly interconnected and orchestrated by a number of assembly factors. The understanding of complex I assembly evolved from simple sequential concept to the more sophisticated modular assembly model describing a convoluted process. According to this model, the different modules assemble independently and associate afterwards with each other to form the final enzyme. In this review, we aim to unravel the complexity of complex I assembly and provide the latest insights in this fundamental and fascinating process. This article is part of a Special Issue entitled Respiratory complex I, edited by Volker Zickermann and Ulrich Brandt. PMID:27040506

  4. A dynamic [1]catenane with pH-responsiveness formed via threading-followed-by-complexation.

    PubMed

    Yan, Xuzhou; Wei, Peifa; Li, Zhengtao; Zheng, Bo; Dong, Shengyi; Huang, Feihe; Zhou, Qizhong

    2013-03-28

    Driven by orthogonal pillar[5]arene-based and crown ether-based molecular recognitions, a dynamic [1]catenane with pH-responsiveness was constructed via threading-followed-by-complexation. PMID:23423220

  5. Positive Affect and the Complex Dynamics of Human Flourishing

    ERIC Educational Resources Information Center

    Fredrickson, Barbara L.; Losada, Marcial F.

    2005-01-01

    Extending B. L. Fredrickson's (1998) broaden-and-build theory of positive emotions and M. Losada's (1999) nonlinear dynamics model of team performance, the authors predict that a ratio of positive to negative affect at or above 2.9 will characterize individuals in flourishing mental health. Participants (N=188) completed an initial survey to…

  6. Evolution and selection of river networks: statics, dynamics, and complexity.

    PubMed

    Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R; Maritan, Amos; Rodriguez-Iturbe, Ignacio

    2014-02-18

    Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics--every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept. PMID:24550264

  7. Small shape deviations causes complex dynamics in large electric generators

    NASA Astrophysics Data System (ADS)

    Lundström, Niklas L. P.; Grafström, Anton; Aidanpää, Jan-Olov

    2014-05-01

    We prove that combinations of small eccentricity, ovality and/or triangularity in the rotor and stator can produce complex whirling motions of an unbalanced rotor in large synchronous generators. It is concluded which structures of shape deviations that are more harmful, in the sense of producing complex whirling motions, than others. For each such structure, we derive simplified equations of motions from which we conclude analytically the relation between shape deviations and mass unbalance that yield non-smooth whirling motions. Finally we discuss validity of our results in the sense of modeling of the unbalanced magnetic pull force.

  8. The Nuclear Pore Complex as a Flexible and Dynamic Gate.

    PubMed

    Knockenhauer, Kevin E; Schwartz, Thomas U

    2016-03-10

    Nuclear pore complexes (NPCs) perforate the nuclear envelope and serve as the primary transport gates for molecular exchange between nucleus and cytoplasm. Stripping the megadalton complex down to its most essential organizational elements, one can divide the NPC into scaffold components and the disordered elements attached to them that generate a selective barrier between compartments. These structural elements exhibit flexibility, which may hold a clue in understanding NPC assembly and function. Here we review the current status of NPC research with a focus on the functional implications of its structural and compositional heterogeneity. PMID:26967283

  9. Ultraprecision XY stage using a hybrid bolt-clamped Langevin-type ultrasonic linear motor for continuous motion

    SciTech Connect

    Lee, Dong-Jin; Lee, Sun-Kyu

    2015-01-15

    This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.

  10. Ultraprecision XY stage using a hybrid bolt-clamped Langevin-type ultrasonic linear motor for continuous motion

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Jin; Lee, Sun-Kyu

    2015-01-01

    This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.

  11. Microbial Bebop: Creating Music from Complex Dynamics in Microbial Ecology

    PubMed Central

    Larsen, Peter; Gilbert, Jack

    2013-01-01

    In order for society to make effective policy decisions on complex and far-reaching subjects, such as appropriate responses to global climate change, scientists must effectively communicate complex results to the non-scientifically specialized public. However, there are few ways however to transform highly complicated scientific data into formats that are engaging to the general community. Taking inspiration from patterns observed in nature and from some of the principles of jazz bebop improvisation, we have generated Microbial Bebop, a method by which microbial environmental data are transformed into music. Microbial Bebop uses meter, pitch, duration, and harmony to highlight the relationships between multiple data types in complex biological datasets. We use a comprehensive microbial ecology, time course dataset collected at the L4 marine monitoring station in the Western English Channel as an example of microbial ecological data that can be transformed into music. Four compositions were generated (www.bio.anl.gov/MicrobialBebop.htm.) from L4 Station data using Microbial Bebop. Each composition, though deriving from the same dataset, is created to highlight different relationships between environmental conditions and microbial community structure. The approach presented here can be applied to a wide variety of complex biological datasets. PMID:23483981

  12. Microbial bebop: creating music from complex dynamics in microbial ecology.

    PubMed

    Larsen, Peter; Gilbert, Jack

    2013-01-01

    In order for society to make effective policy decisions on complex and far-reaching subjects, such as appropriate responses to global climate change, scientists must effectively communicate complex results to the non-scientifically specialized public. However, there are few ways however to transform highly complicated scientific data into formats that are engaging to the general community. Taking inspiration from patterns observed in nature and from some of the principles of jazz bebop improvisation, we have generated Microbial Bebop, a method by which microbial environmental data are transformed into music. Microbial Bebop uses meter, pitch, duration, and harmony to highlight the relationships between multiple data types in complex biological datasets. We use a comprehensive microbial ecology, time course dataset collected at the L4 marine monitoring station in the Western English Channel as an example of microbial ecological data that can be transformed into music. Four compositions were generated (www.bio.anl.gov/MicrobialBebop.htm.) from L4 Station data using Microbial Bebop. Each composition, though deriving from the same dataset, is created to highlight different relationships between environmental conditions and microbial community structure. The approach presented here can be applied to a wide variety of complex biological datasets. PMID:23483981

  13. Cationic Dihydrogen/Dihydride Complexes of Osmium: Structure and Dynamics

    SciTech Connect

    Egbert, Jonathan D.; Bullock, R. Morris; Heinekey, D. M.

    2007-03-22

    Reaction of Cp*Os(CO)2Cl with (Et3Si )(BArF4) under hydrogen gas affords the cationic hydrogen complex [Cp*Os(CO)2(H2)][BArF4] (1), (Cp* = C5Me5; ArF = C6F5). When this reaction is carried out with HD gas, complex 1-d1 results, with JHD = 24.5 Hz. When solutions of complex 1 are monitored by 1H NMR spectroscopy over several days, the gradual formation of a trans dihydride species is observed. Similarly, reaction of CpOs(dppm)Br with NaBArF*4 (ArF* = 3,5-(CF3)2C6H3) under hydrogen affords the cationic dihydride complex [CpOs(dppm)H2]BArF*4 (2). At 295 K, complex 2 exists as a 10:1 mixture of cis and trans isomers. The 1H NMR spectrum of the cis form in the hydride region exhibits a triplet with JHP = 6.5 Hz, due to rapid exchange of the hydrogen atoms. At low temperature, static spectra of the HH'PP' spin system can be obtained, revealing quantum mechanical exchange coupling between the two hydride ligands. The observed JHH' is temperature dependent, varying from 133 Hz at 141 K to 176 Hz at 198 K. This is the first report of detectable exchange coupling between pairs of chemically equivalent hydrogen atoms. Research at the University of Washington was supported by the National Science Foundation. Research at Brookhaven National Laboratory was carried out under contract DE-AC02-98CH10886 with the U.S. Department of Energy and was supported by its Division of Chemical Sciences, Office of Basic Energy Sciences. Research at Pacific Northwest National Laboratory (PNNL) was funded by LDRD funds. PNNL is operated by Battelle for the US Department of Energy.

  14. Eco-evolutionary dynamics of complex social strategies in microbial communities

    PubMed Central

    Harrington, Kyle I; Sanchez, Alvaro

    2014-01-01

    Microbial communities abound with examples of complex social interactions that shape microbial ecosystems. One particularly striking example is microbial cooperation via the secretion of public goods. It has been suggested by theory, and recently demonstrated experimentally, that microbial population dynamics and the evolutionary dynamics of cooperative social genes take place with similar timescales, and are linked to each other via an eco-evolutionary feedback loop. We overview this recent evidence, and discuss the possibility that a third process may be also part of this loop: phenotypic dynamics. Complex social strategies may be implemented at the single-cell level by means of gene regulatory networks. Thus gene expression plasticity or stochastic gene expression, both of which may occur with a timescale of one to a few generations, can potentially lead to a three-way coupling between behavioral dynamics, population dynamics, and evolutionary dynamics PMID:24778764

  15. Dynamics in hybrid complex systems of switches and oscillators

    NASA Astrophysics Data System (ADS)

    Taylor, Dane; Fertig, Elana J.; Restrepo, Juan G.

    2013-09-01

    While considerable progress has been made in the analysis of large systems containing a single type of coupled dynamical component (e.g., coupled oscillators or coupled switches), systems containing diverse components (e.g., both oscillators and switches) have received much less attention. We analyze large, hybrid systems of interconnected Kuramoto oscillators and Hopfield switches with positive feedback. In this system, oscillator synchronization promotes switches to turn on. In turn, when switches turn on, they enhance the synchrony of the oscillators to which they are coupled. Depending on the choice of parameters, we find theoretically coexisting stable solutions with either (i) incoherent oscillators and all switches permanently off, (ii) synchronized oscillators and all switches permanently on, or (iii) synchronized oscillators and switches that periodically alternate between the on and off states. Numerical experiments confirm these predictions. We discuss how transitions between these steady state solutions can be onset deterministically through dynamic bifurcations or spontaneously due to finite-size fluctuations.

  16. Thermodynamic aspects of information transfer in complex dynamical systems.

    PubMed

    Cafaro, Carlo; Ali, Sean Alan; Giffin, Adom

    2016-02-01

    From the Horowitz-Esposito stochastic thermodynamical description of information flows in dynamical systems [J. M. Horowitz and M. Esposito, Phys. Rev. X 4, 031015 (2014)], it is known that while the second law of thermodynamics is satisfied by a joint system, the entropic balance for the subsystems is adjusted by a term related to the mutual information exchange rate between the two subsystems. In this article, we present a quantitative discussion of the conceptual link between the Horowitz-Esposito analysis and the Liang-Kleeman work on information transfer between dynamical system components [X. S. Liang and R. Kleeman, Phys. Rev. Lett. 95, 244101 (2005)]. In particular, the entropic balance arguments employed in the two approaches are compared. Notwithstanding all differences between the two formalisms, our work strengthens the Liang-Kleeman heuristic balance reasoning by showing its formal analogy with the recent Horowitz-Esposito thermodynamic balance arguments. PMID:26986295

  17. Efficient modelling of droplet dynamics on complex surfaces.

    PubMed

    Karapetsas, George; Chamakos, Nikolaos T; Papathanasiou, Athanasios G

    2016-03-01

    This work investigates the dynamics of droplet interaction with smooth or structured solid surfaces using a novel sharp-interface scheme which allows the efficient modelling of multiple dynamic contact lines. The liquid-gas and liquid-solid interfaces are treated in a unified context and the dynamic contact angle emerges simply due to the combined action of the disjoining and capillary pressure, and viscous stresses without the need of an explicit boundary condition or any requirement for the predefinition of the number and position of the contact lines. The latter, as it is shown, renders the model able to handle interfacial flows with topological changes, e.g. in the case of an impinging droplet on a structured surface. Then it is possible to predict, depending on the impact velocity, whether the droplet will fully or partially impregnate the structures of the solid, or will result in a 'fakir', i.e. suspended, state. In the case of a droplet sliding on an inclined substrate, we also demonstrate the built-in capability of our model to provide a prediction for either static or dynamic contact angle hysteresis. We focus our study on hydrophobic surfaces and examine the effect of the geometrical characteristics of the solid surface. It is shown that the presence of air inclusions trapped in the micro-structure of a hydrophobic substrate (Cassie-Baxter state) result in the decrease of contact angle hysteresis and in the increase of the droplet migration velocity in agreement with experimental observations for super-hydrophobic surfaces. Moreover, we perform 3D simulations which are in line with the 2D ones regarding the droplet mobility and also indicate that the contact angle hysteresis may be significantly affected by the directionality of the structures with respect to the droplet motion. PMID:26828706

  18. Rhythmic Manipulation of Objects with Complex Dynamics: Predictability over Chaos

    PubMed Central

    Nasseroleslami, Bahman; Hasson, Christopher J.; Sternad, Dagmar

    2014-01-01

    The study of object manipulation has been largely confined to discrete tasks, where accuracy, mechanical effort, or smoothness were examined to explain subjects' preferred movements. This study investigated a rhythmic manipulation task, which involved continuous interaction with a nonlinear object that led to unpredictable object behavior. Using a simplified virtual version of the task of carrying a cup of coffee, we studied how this unpredictable object behavior affected the selected strategies. The experiment was conducted in a virtual set-up, where subjects moved a cup with a ball inside, modeled by cart-and-pendulum dynamics. Inverse dynamics calculations of the system showed that performing the task with different amplitudes and relative phases required different force profiles and rendered the object's dynamics with different degrees of predictability (quantified by Mutual Information between the applied force and the cup kinematics and its sensitivity). Subjects (n = 8) oscillated the virtual cup between two targets via a robotic manipulandum, paced by a metronome at 1 Hz for 50 trials, each lasting 45 s. They were free to choose their movement amplitude and relative phase between the ball and cup. Experimental results showed that subjects increased their movement amplitudes, which rendered the interactions with the object more predictable and with lower sensitivity to the execution variables. These solutions were associated with higher average exerted force and lower object smoothness, contradicting common expectations from studies on discrete object manipulation and unrestrained movements. Instead, the findings showed that humans selected strategies with higher predictability of interaction dynamics. This finding expressed that humans seek movement strategies where force and kinematics synchronize to repeatable patterns that may require less sensorimotor information processing. PMID:25340581

  19. Efficient modelling of droplet dynamics on complex surfaces

    NASA Astrophysics Data System (ADS)

    Karapetsas, George; Chamakos, Nikolaos T.; Papathanasiou, Athanasios G.

    2016-03-01

    This work investigates the dynamics of droplet interaction with smooth or structured solid surfaces using a novel sharp-interface scheme which allows the efficient modelling of multiple dynamic contact lines. The liquid-gas and liquid-solid interfaces are treated in a unified context and the dynamic contact angle emerges simply due to the combined action of the disjoining and capillary pressure, and viscous stresses without the need of an explicit boundary condition or any requirement for the predefinition of the number and position of the contact lines. The latter, as it is shown, renders the model able to handle interfacial flows with topological changes, e.g. in the case of an impinging droplet on a structured surface. Then it is possible to predict, depending on the impact velocity, whether the droplet will fully or partially impregnate the structures of the solid, or will result in a ‘fakir’, i.e. suspended, state. In the case of a droplet sliding on an inclined substrate, we also demonstrate the built-in capability of our model to provide a prediction for either static or dynamic contact angle hysteresis. We focus our study on hydrophobic surfaces and examine the effect of the geometrical characteristics of the solid surface. It is shown that the presence of air inclusions trapped in the micro-structure of a hydrophobic substrate (Cassie-Baxter state) result in the decrease of contact angle hysteresis and in the increase of the droplet migration velocity in agreement with experimental observations for super-hydrophobic surfaces. Moreover, we perform 3D simulations which are in line with the 2D ones regarding the droplet mobility and also indicate that the contact angle hysteresis may be significantly affected by the directionality of the structures with respect to the droplet motion.

  20. Dynamical symmetries in Kondo tunneling through complex quantum dots.

    PubMed

    Kuzmenko, T; Kikoin, K; Avishai, Y

    2002-10-01

    Kondo tunneling reveals hidden SO(n) dynamical symmetries of evenly occupied quantum dots. As is exemplified for an experimentally realizable triple quantum dot in parallel geometry, the possible values n=3,4,5,7 can be easily tuned by gate voltages. Following construction of the corresponding o(n) algebras, scaling equations are derived and Kondo temperatures are calculated. The symmetry group for a magnetic field induced anisotropic Kondo tunneling is SU(2) or SO(4). PMID:12366008

  1. Plenary Speech: Researching Complex Dynamic Systems--"Retrodictive Qualitative Modelling" in the Language Classroom

    ERIC Educational Resources Information Center

    Dörnyei, Zoltán

    2014-01-01

    While approaching second language acquisition from a complex dynamic systems perspective makes a lot of intuitive sense, it is difficult for a number of reasons to operationalise such a dynamic approach in research terms. For example, the most common research paradigms in the social sciences tend to examine variables in relative isolation rather…

  2. Complex dynamics of synergistic coinfections on realistically clustered networks

    PubMed Central

    Hébert-Dufresne, Laurent; Althouse, Benjamin M.

    2015-01-01

    We investigate the impact of contact structure clustering on the dynamics of multiple diseases interacting through coinfection of a single individual, two problems typically studied independently. We highlight how clustering, which is well known to hinder propagation of diseases, can actually speed up epidemic propagation in the context of synergistic coinfections if the strength of the coupling matches that of the clustering. We also show that such dynamics lead to a first-order transition in endemic states, where small changes in transmissibility of the diseases can lead to explosive outbreaks and regions where these explosive outbreaks can only happen on clustered networks. We develop a mean-field model of coinfection of two diseases following susceptible-infectious-susceptible dynamics, which is allowed to interact on a general class of modular networks. We also introduce a criterion based on tertiary infections that yields precise analytical estimates of when clustering will lead to faster propagation than nonclustered networks. Our results carry importance for epidemiology, mathematical modeling, and the propagation of interacting phenomena in general. We make a call for more detailed epidemiological data of interacting coinfections. PMID:26195773

  3. Dynamical interplay between epidemics and cascades in complex networks

    NASA Astrophysics Data System (ADS)

    Ouyang, Bo; Jin, Xinyu; Xia, Yongxiang; Jiang, Lurong; Wu, Duanpo

    2014-04-01

    Epidemics and cascading failure are extensively investigated. Traditionally, they are independently studied, but in practice, there are many cases where these two dynamics interact with each other and neither of their effects can be ignored. For example, consider that a digital virus is spreading in a communication network, which is transferring data in the meantime. We build a model based on the epidemiological SIR model and a local load sharing cascading failure model to study the interplay between these two dynamics. In this model, when the dynamical process stops at equilibrium, the nodes both uninfected and unfailed form several clusters. We consider the relative size of the largest one, i.e. the giant component. A phenomenon is observed in both Erdős-Rényi (ER) random networks and Barabási-Albert (BA) scale-free networks that when the infection probability is over some critical value, a giant component forms only if the tolerance parameter α is within some interval (\\alpha_l,\\alpha_u) . In this interval, the size of the remained giant component first increases and then decreases. After analyzing the cause of this phenomenon, we then present in ER random networks a theoretical solution of the key values of \\alpha_l and \\alpha_u , which are very important when we evaluate the robustness of the network. Finally, our theory is verified by numerical simulations.

  4. Cellular automata and complex dynamics of driven elastic media

    SciTech Connect

    Coppersmith, S.N.; Littlewodd, P.B.; Sibani, P.

    1995-12-01

    Several systems of importance in condensed matter physics can be modelled as an elastic medium in a disordered environment and driven by an external force. In the simplest cases, the equation of motion involves competition between a local non-linear potential (fluctuating in space) and elastic coupling, as well as relaxational (inertialess) dynamics. Despite a simple mathematical description, the interactions between many degrees of freedom lead to the emergence of time and length scales much longer than those set by the microscopic dynamics. Extensive computations have improved the understanding of the behavior of such models, but full solutions of the equations of motion for very large systems are time-consuming and may obscure important physical principles in a massive volume of output. The development of cellular automata models has been crucial, both in conceptual simplification and in allowing the collection of data on many replicas of very large systems. We will discuss how the marriage of cellular automata models and parallel computation on a MasPar MP-1216 computer has helped to elucidate the dynamical properties of these many-degree-of-freedom systems.

  5. Excited state dynamics and isomerization in ruthenium sulfoxide complexes.

    PubMed

    King, Albert W; Wang, Lei; Rack, Jeffrey J

    2015-04-21

    Molecular photochromic compounds are those that interconvert between two isomeric forms with light. The two isomeric forms display distinct electronic and molecular structures and must not be in equilibrium with one another. These light-activated molecular switch compounds have found wide application in areas of study ranging from chemical biology to materials science, where conversion from one isomeric form to another by light prompts a response in the environment (e.g., protein or polymeric material). Certain ruthenium and osmium polypyridine sulfoxide complexes are photochromic. The mode of action is a phototriggered isomerization of the sulfoxide from S- to O-bonded. The change in ligation drastically alters both the spectroscopic and electrochemical properties of the metal complex. Our laboratory has pioneered the preparation and study of these complexes. In particular, we have applied femtosecond pump-probe spectroscopy to reveal excited state details of the isomerization mechanism. The data from numerous complexes allowed us to predict that the isomerization was nonadiabatic in nature, defined as occurring from a S-bonded triplet excited state (primarily metal-to-ligand charge transfer in character) to an O-bonded singlet ground state potential energy surface. This prediction was corroborated by high-level density functional theory calculations. An intriguing aspect of this reactivity is the coupling of nuclear motion to the electronic wave function and how this coupling affects motions productive for isomerization. In an effort to learn more about this coupling, we designed a project to examine phototriggered isomerization in bis-sulfoxide complexes. The goal of these studies was to determine whether certain complexes could be designed in which a single photon excitation event would prompt two sulfoxide isomerizations. We employed chelating sulfoxides in this study and found that both the nature of the chelate ring and the R group on the sulfoxide affect

  6. High Dynamic Range Complex Impedance Measurement System for Petrophysical Usage

    NASA Astrophysics Data System (ADS)

    Chen, R.; He, X.; Yao, H.; Tan, S.; Shi, H.; Shen, R.; Yan, C.; Zeng, P.; He, L.; Qiao, N.; Xi, F.; Zhang, H.; Xie, J.

    2015-12-01

    Spectral induced polarization method (SIP) or complex resistivity method is increasing its application in metalliferous ore exploration, hydrocarbon exploration, underground water exploration, monitoring of environment pollution, and the evaluation of environment remediation. And the measurement of complex resistivity or complex impedance of rock/ore sample and polluted water plays a fundamental role in improving the application effect of SIP and the application scope of SIP. However, current instruments can't guaranty the accuracy of measurement when the resistance of sample is less than 10Ω or great than 100kΩ. A lot of samples, such as liquid, polluted sea water, igneous rock, limestone, and sandstone, can't be measured with reliable complex resistivity result. Therefore, this problem projects a shadow in the basic research and application research of SIP. We design a high precision measurement system from the study of measurement principle, sample holder, and measurement instrument. We design input buffers in a single board. We adopt operation amplifier AD549 in this system because of its ultra-high input impedance and ultra-low current noise. This buffer is good in acquiring potential signal across high impedance sample. By analyzing the sources of measurement error and errors generated by the measurement system, we propose a correction method to remove the error in order to achieve high quality complex impedance measurement for rock and ore samples. This measurement system can improve the measurement range of the complex impedance to 0.1 Ω ~ 10 GΩ with amplitude error less than 0.1% and phase error less than 0.1mrad when frequency ranges as 0.01 Hz ~ 1 kHz. We tested our system on resistors with resistance as 0.1Ω ~ 10 GΩ in frequency range as 1 Hz ~ 1000 Hz, and the measurement error is less than 0.1 mrad. We also compared the result with LCR bridge and SCIP, we can find that the bridge's measuring range only reaches 100 MΩ, SCIP's measuring range

  7. Dynamics and recognition within a protein–DNA complex: a molecular dynamics study of the SKN-1/DNA interaction

    PubMed Central

    Etheve, Loïc; Martin, Juliette; Lavery, Richard

    2016-01-01

    Molecular dynamics simulations of the Caenorhabditis elegans transcription factor SKN-1 bound to its cognate DNA site show that the protein–DNA interface undergoes significant dynamics on the microsecond timescale. A detailed analysis of the simulation shows that movements of two key arginine side chains between the major groove and the backbone of DNA generate distinct conformational sub-states that each recognize only part of the consensus binding sequence of SKN-1, while the experimentally observed binding specificity results from a time-averaged view of the dynamic recognition occurring within this complex. PMID:26721385

  8. Molecular dynamics simulation strategies for protein-micelle complexes.

    PubMed

    Cheng, Xi; Kim, Jin-Kyoung; Kim, Yangmee; Bowie, James U; Im, Wonpil

    2016-07-01

    The structure and stability of membrane proteins can vary widely in different detergents and this variability has great practical consequences for working with membrane proteins. Nevertheless, the mechanisms that operate to alter the behavior of proteins in micelles are poorly understood and not predictable. Atomic simulations could provide considerable insight into these mechanisms. Building protein-micelle complexes for simulation is fraught with uncertainty, however, in part because it is often unknown how many detergent molecules are present in the complex. Here, we describe several convenient ways to employ Micelle Builder in CHARMM-GUI to rapidly construct protein-micelle complexes and performed simulations of the isolated voltage-sensor domain of voltage-dependent potassium-selective channel and an antimicrobial peptide papiliocin with varying numbers of detergents. We found that once the detergent number exceeds a threshold, protein-detergent interactions change very little and remain very consistent with experimental observations. Our results provide a platform for future studies of the interplays between protein structure and detergent properties at the atomic level. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov. PMID:26679426

  9. A Fisher-gradient complexity in systems with spatio-temporal dynamics

    NASA Astrophysics Data System (ADS)

    Arbona, A.; Bona, C.; Massó, J.; Miñano, B.; Plastino, A.

    2016-04-01

    We define a benchmark for definitions of complexity in systems with spatio-temporal dynamics and employ it in the study of Collective Motion. We show that LMC's complexity displays interesting properties in such systems, while a statistical complexity model (SCM) based on autocorrelation reasonably meets our perception of complexity. However this SCM is not as general as desirable, as it does not merely depend on the system's Probability Distribution Function. Inspired by the notion of Fisher information, we develop a SCM candidate, which we call the Fisher-gradient complexity, which exhibits nice properties from the viewpoint of our benchmark.

  10. The Graph Laplacian and the Dynamics of Complex Networks

    SciTech Connect

    Thulasidasan, Sunil

    2012-06-11

    In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

  11. Violent gas dynamics in galactic cosmogony: spiral shocks and rotation of star complexes.

    NASA Astrophysics Data System (ADS)

    Chernin, A. D.

    Star complexes are huge aggregates of stars and gas which are considered as the largest cells of star formation in spiral galaxies (Efremov 1988). Basic observational data on star complexes are presented with a special emphasis on their rotational properties. A possible model of the formation of star complexes and the origin of their spin momentum is discussed based on the physics of nonlinear supersonic gas dynamics effects in the interstellar medium.

  12. Collisionally induced stochastic dynamics of fast ions in solids

    SciTech Connect

    Burgdoerfer, J.

    1989-01-01

    Recent developments in the theory of excited state formation in collisions of fast highly charged ions with solids are reviewed. We discuss a classical transport theory employing Monte-Carlo sampling of solutions of a microscopic Langevin equation. Dynamical screening by the dielectric medium as well as multiple collisions are incorporated through the drift and stochastic forces in the Langevin equation. The close relationship between the extrinsically stochastic dynamics described by the Langevin and the intrinsic stochasticity in chaotic nonlinear dynamical systems is stressed. Comparison with experimental data and possible modification by quantum corrections are discussed. 49 refs., 11 figs.

  13. Thermodynamic aspects of information transfer in complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Cafaro, Carlo; Ali, Sean Alan; Giffin, Adom

    2016-02-01

    From the Horowitz-Esposito stochastic thermodynamical description of information flows in dynamical systems [J. M. Horowitz and M. Esposito, Phys. Rev. X 4, 031015 (2014), 10.1103/PhysRevX.4.031015], it is known that while the second law of thermodynamics is satisfied by a joint system, the entropic balance for the subsystems is adjusted by a term related to the mutual information exchange rate between the two subsystems. In this article, we present a quantitative discussion of the conceptual link between the Horowitz-Esposito analysis and the Liang-Kleeman work on information transfer between dynamical system components [X. S. Liang and R. Kleeman, Phys. Rev. Lett. 95, 244101 (2005), 10.1103/PhysRevLett.95.244101]. In particular, the entropic balance arguments employed in the two approaches are compared. Notwithstanding all differences between the two formalisms, our work strengthens the Liang-Kleeman heuristic balance reasoning by showing its formal analogy with the recent Horowitz-Esposito thermodynamic balance arguments.

  14. Control of Complex Dynamic Systems by Neural Networks

    NASA Technical Reports Server (NTRS)

    Spall, James C.; Cristion, John A.

    1993-01-01

    This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations.

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

    SciTech Connect

    Walker, David M.; Tordesillas, Antoinette; Small, Michael; Behringer, Robert P.; Tse, Chi K.

    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, constructed 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.

  16. Safety assessment document for the dynamic test complex (Building 836)

    SciTech Connect

    Odell, B.N.; Pfeifer, H.E.

    1981-11-24

    A safety assessment was performed to determine if potential accidents at the 836 Complex at Site 300 could present undue hazards to the general public, personnel at Site 300, or have an adverse effect on the environment. The credible accidents that might have an effect on these facilities or have off-site consequences were considered. These were earthquake, extreme wind (including missiles), lightning, flood, criticality, high explosive (H) detonation that disperses uranium and beryllium, spontaneous oxidation of plutonium, explosions due to finely divided particles, and a fire.

  17. Two-Proton Phototautomerization Dynamics of 7-AZAINDOLE Complexes

    NASA Astrophysics Data System (ADS)

    Chakraborty, T.; Mukherjee, M.; Karmakar, S.

    2013-06-01

    Light-induced tautomerization of 7-azaindole in doubly hydrogen-bonded dimeric complexes is one of the extensively investigated photoisomerization processes in recent years. The reaction, in the case of homodimer, takes place with equal ease in non-polar liquids at room temperature as well as in a cold supersonic jet expansion. A lot of studies were devoted arguing whether the double proton transfer occurs sequentially or in a concerted manner. Over the past three decades it has been assumed, on the basis of the observations of some low-temperature photophysical measurements, the double proton exchange barrier of the dimer is ˜ 2 kcal/mol. However, we notice that such measurements are flawed by artifact; the apparent barrier depends on sample concentration in the solutions. The tautomerization of the isolated dimer is found stopped at 10 K in an argon matrix, and we propose that the double proton exchange is coupled with the large amplitude hydrogen bond vibrations. Furthermore, the process in several 1:1 complexes of the molecule with pyrazole and amides displays remarkable contrasts with that of the homodimer. While the tautomerization in the former cases occurs extremely efficiently in hydrocarbon solutions, is hindered fully in supersonic jet expansion condition.The observations also imply that the effective barrier of phototautomerization in the 1:1 complexes is intimately correlated with the details of double proton transfer mechanism. The details of our findings along with the predictions of some electronic structure calculations will be presented in the talk. References: ``Ultraviolet and infrared spectroscopy of matrix-isolated 7-azaindole dimer: Matrix effect on excited state tautomerization", M. Mukherjee, B. Bandyopadhyay and T. Chakraborty, Chem. Phys. Lett. 546, 74-79 (2012). ``Excited State Tautomerization of 7-Azaindole in a 1:1 Complex with δ-Valerolactam: A Comparative Study with the Homodimer", M. Mukherjee, S. Karmakar and T. Chakraborty, J

  18. Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

    PubMed Central

    Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

    2015-01-01

    Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

  19. Dynamical properties and complexity in fractional-order diffusionless Lorenz system

    NASA Astrophysics Data System (ADS)

    He, Shaobo; Sun, Kehui; Banerjee, Santo

    2016-08-01

    In this paper, dynamics and complexity of the fractional-order diffusionless Lorenz system which is solved by the developed discrete Adomian decomposition method are investigated numerically. Dynamical properties of the fractional-order diffusionless Lorenz system with the control parameter and derivative order varying is analyzed by using bifurcation diagrams, and period-doubling route to chaos in different cases is observed. The complexity of the system is investigated by means of Lyapunov characteristic exponents, multi-scale spectral entropy algorithm and multiscale Renyi permutation entropy algorithm. It can be observed that the three methods illustrate consistent results and the system has rich complex dynamics. Interestingly, complexity decreases with the increase of derivative order. It shows that the fractional-order diffusionless Lorenz system is a good model for real applications such as information encryption and secure communication.

  20. Multiagent model and mean field theory of complex auction dynamics

    NASA Astrophysics Data System (ADS)

    Chen, Qinghua; Huang, Zi-Gang; Wang, Yougui; Lai, Ying-Cheng

    2015-09-01

    Recent years have witnessed a growing interest in analyzing a variety of socio-economic phenomena using methods from statistical and nonlinear physics. We study a class of complex systems arising from economics, the lowest unique bid auction (LUBA) systems, which is a recently emerged class of online auction game systems. Through analyzing large, empirical data sets of LUBA, we identify a general feature of the bid price distribution: an inverted J-shaped function with exponential decay in the large bid price region. To account for the distribution, we propose a multi-agent model in which each agent bids stochastically in the field of winner’s attractiveness, and develop a theoretical framework to obtain analytic solutions of the model based on mean field analysis. The theory produces bid-price distributions that are in excellent agreement with those from the real data. Our model and theory capture the essential features of human behaviors in the competitive environment as exemplified by LUBA, and may provide significant quantitative insights into complex socio-economic phenomena.

  1. Adaptive representation for dynamic environment, vehicle, and mission complexity

    NASA Astrophysics Data System (ADS)

    Collier, Jack A.; Ricard, Benoit; Digney, Bruce L.; Cheng, David; Trentini, Michael; Beckman, Blake

    2004-09-01

    In order for an Unmanned Ground Vehicle (UGV) to operate effectively it must be able to perceive its environment in an accurate, robust and effective manner. This is done by creating a world representation which encompasses all the perceptual information necessary for the UGV to understand its surroundings. These perceptual needs are a function of the robots mobility characteristics, the complexity of the environment in which it operates, and the mission with which the UGV has been tasked. Most perceptual systems are designed with predefined vehicle, environmental, and mission complexity in mind. This can lead the robot to fail when it encounters a situation which it was not designed for since its internal representation is insufficient for effective navigation. This paper presents a research framework currently being investigated by Defence R&D Canada (DRDC), which will ultimately relieve robotic vehicles of this problem by allowing the UGV to recognize representational deficiencies, and change its perceptual strategy to alleviate these deficiencies. This will allow the UGV to move in and out of a wide variety of environments, such as outdoor rural to indoor urban, at run time without reprogramming. We present sensor and perception work currently being done and outline our research in this area for the future.

  2. Dealing with the complex dynamics of teaching hospitals.

    PubMed

    van Rossum, Tiuri R; Scheele, Fedde; Scherpbier, Albert J J A; Sluiter, Henk E; Heyligers, Ide C

    2016-01-01

    Innovation and change in postgraduate medical education programs affects teaching hospital organizations, since medical education and clinical service are interrelated.Recent trends towards flexible, time-independent and individualized educational programs put pressure on this relationship. This pressure may lead to organizational uncertainty, unbalance and friction making it an important issue to analyze.The last decade was marked by a transition towards outcome-based postgraduate medical education. During this transition competency-based programs made their appearance. Although competency-based medical education has the potential to make medical education more efficient, the effects are still under debate. And while this debate continues, the field of medical education is already introducing next level innovations: flexible and individualized training programs. Major organizational change, like the transition to flexible education programs, can easily lead to friction and conflict in teaching hospital organizations.This article analyses the organizational impact of postgraduate medical education innovations, with a particular focus on flexible training and competency based medical education. The characteristics of teaching hospital organizations are compared with elements of innovation and complexity theory.With this comparison the article argues that teaching hospital organizations have complex characteristics and behave in a non-linear way. This perspective forms the basis for further discussion and analysis of this unexplored aspect of flexible and competency based education. PMID:27048264

  3. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    PubMed Central

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity. PMID:27297496

  4. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions.

    PubMed

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-01-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity. PMID:27297496

  5. Complexity and Control: Towards a Rigorous Behavioral Theory of Complex Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    We introduce our motive for writing this book on complexity and control with a popular "complexity myth," which seems to be quite wide spread among chaos and complexity theory fashionistas: Low-dimensional systems usually exhibit complex behaviours (which we know fromMay's studies of the Logisticmap), while high-dimensional systems usually exhibit simple behaviours (which we know from synchronisation studies of the Kuramoto model)... We admit that this naive view on complex (e.g., human) systems versus simple (e.g., physical) systems might seem compelling to various technocratic managers and politicians; indeed, the idea makes for appealing sound-bites. However, it is enough to see both in the equations and computer simulations of pendula of various degree - (i) a single pendulum, (ii) a double pendulum, and (iii) a triple pendulum - that this popular myth is plain nonsense. The only thing that we can learn from it is what every tyrant already knows: by using force as a strong means of control, it is possible to effectively synchronise even hundreds of millions of people, at least for a while.

  6. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    NASA Astrophysics Data System (ADS)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

  7. BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes.

    PubMed

    Lakizadeh, Amir; Jalili, Saeed

    2016-01-01

    Considering the roles of protein complexes in many biological processes in the cell, detection of protein complexes from available protein-protein interaction (PPI) networks is a key challenge in the post genome era. Despite high dynamicity of cellular systems and dynamic interaction between proteins in a cell, most computational methods have focused on static networks which cannot represent the inherent dynamicity of protein interactions. Recently, some researchers try to exploit the dynamicity of PPI networks by constructing a set of dynamic PPI subnetworks correspondent to each time-point (column) in a gene expression data. However, many genes can participate in multiple biological processes and cellular processes are not necessarily related to every sample, but they might be relevant only for a subset of samples. So, it is more interesting to explore each subnetwork based on a subset of genes and conditions (i.e., biclusters) in a gene expression data. Here, we present a new method, called BiCAMWI to employ dynamicity in detecting protein complexes. The preprocessing phase of the proposed method is based on a novel genetic algorithm that extracts some sets of genes that are co-regulated under some conditions from input gene expression data. Each extracted gene set is called bicluster. In the detection phase of the proposed method, then, based on the biclusters, some dynamic PPI subnetworks are extracted from input static PPI network. Protein complexes are identified by applying a detection method on each dynamic PPI subnetwork and aggregating the results. Experimental results confirm that BiCAMWI effectively models the dynamicity inherent in static PPI networks and achieves significantly better results than state-of-the-art methods. So, we suggest BiCAMWI as a more reliable method for protein complex detection. PMID:27462706

  8. BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes

    PubMed Central

    Lakizadeh, Amir; Jalili, Saeed

    2016-01-01

    Considering the roles of protein complexes in many biological processes in the cell, detection of protein complexes from available protein-protein interaction (PPI) networks is a key challenge in the post genome era. Despite high dynamicity of cellular systems and dynamic interaction between proteins in a cell, most computational methods have focused on static networks which cannot represent the inherent dynamicity of protein interactions. Recently, some researchers try to exploit the dynamicity of PPI networks by constructing a set of dynamic PPI subnetworks correspondent to each time-point (column) in a gene expression data. However, many genes can participate in multiple biological processes and cellular processes are not necessarily related to every sample, but they might be relevant only for a subset of samples. So, it is more interesting to explore each subnetwork based on a subset of genes and conditions (i.e., biclusters) in a gene expression data. Here, we present a new method, called BiCAMWI to employ dynamicity in detecting protein complexes. The preprocessing phase of the proposed method is based on a novel genetic algorithm that extracts some sets of genes that are co-regulated under some conditions from input gene expression data. Each extracted gene set is called bicluster. In the detection phase of the proposed method, then, based on the biclusters, some dynamic PPI subnetworks are extracted from input static PPI network. Protein complexes are identified by applying a detection method on each dynamic PPI subnetwork and aggregating the results. Experimental results confirm that BiCAMWI effectively models the dynamicity inherent in static PPI networks and achieves significantly better results than state-of-the-art methods. So, we suggest BiCAMWI as a more reliable method for protein complex detection. PMID:27462706

  9. Positive Affect and the Complex Dynamics of Human Flourishing

    PubMed Central

    Fredrickson, Barbara L.; Losada, Marcial F.

    2011-01-01

    Extending B. L. Fredrickson’s (1998) broaden-and-build theory of positive emotions and M. Losada’s (1999) nonlinear dynamics model of team performance, the authors predict that a ratio of positive to negative affect at or above 2.9 will characterize individuals in flourishing mental health. Participants (N = 188) completed an initial survey to identify flourishing mental health and then provided daily reports of experienced positive and negative emotions over 28 days. Results showed that the mean ratio of positive to negative affect was above 2.9 for individuals classified as flourishing and below that threshold for those not flourishing. Together with other evidence, these findings suggest that a set of general mathematical principles may describe the relations between positive affect and human flourishing. PMID:16221001

  10. Positive affect and the complex dynamics of human flourishing.

    PubMed

    Fredrickson, Barbara L; Losada, Marcial F

    2005-10-01

    Extending B. L. Fredrickson's (1998) broaden-and-build theory of positive emotions and M. Losada's (1999) nonlinear dynamics model of team performance, the authors predict that a ratio of positive to negative affect at or above 2.9 will characterize individuals in flourishing mental health. Participants (N=188) completed an initial survey to identify flourishing mental health and then provided daily reports of experienced positive and negative emotions over 28 days. Results showed that the mean ratio of positive to negative affect was above 2.9 for individuals classified as flourishing and below that threshold for those not flourishing. Together with other evidence, these findings suggest that a set of general mathematical principles may describe the relations between positive affect and human flourishing. PMID:16221001

  11. Distribution of directional change as a signature of complex dynamics.

    PubMed

    Burov, Stanislav; Tabei, S M Ali; Huynh, Toan; Murrell, Michael P; Philipson, Louis H; Rice, Stuart A; Gardel, Margaret L; Scherer, Norbert F; Dinner, Aaron R

    2013-12-01

    Analyses of random walks traditionally use the mean square displacement (MSD) as an order parameter characterizing dynamics. We show that the distribution of relative angles of motion between successive time intervals of random walks in two or more dimensions provides information about stochastic processes beyond the MSD. We illustrate the behavior of this measure for common models and apply it to experimental particle tracking data. For a colloidal system, the distribution of relative angles reports sensitively on caging as the density varies. For transport mediated by molecular motors on filament networks in vitro and in vivo, we discover self-similar properties that cannot be described by existing models and discuss possible scenarios that can lead to the elucidated statistical features. PMID:24248363

  12. Distribution of directional change as a signature of complex dynamics

    PubMed Central

    Burov, Stanislav; Tabei, S. M. Ali; Huynh, Toan; Murrell, Michael P.; Philipson, Louis H.; Rice, Stuart A.; Gardel, Margaret L.; Scherer, Norbert F.; Dinner, Aaron R.

    2013-01-01

    Analyses of random walks traditionally use the mean square displacement (MSD) as an order parameter characterizing dynamics. We show that the distribution of relative angles of motion between successive time intervals of random walks in two or more dimensions provides information about stochastic processes beyond the MSD. We illustrate the behavior of this measure for common models and apply it to experimental particle tracking data. For a colloidal system, the distribution of relative angles reports sensitively on caging as the density varies. For transport mediated by molecular motors on filament networks in vitro and in vivo, we discover self-similar properties that cannot be described by existing models and discuss possible scenarios that can lead to the elucidated statistical features. PMID:24248363

  13. Momentum conserving Brownian dynamics propagator for complex soft matter fluids

    SciTech Connect

    Padding, J. T.; Briels, W. J.

    2014-12-28

    We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution. We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics.

  14. Dynamically­ Reconfigurable Complex Emulsions via Tunable Interfacial Tensions

    NASA Astrophysics Data System (ADS)

    Swager, Timothy

    This lecture will focus on the design of systems wherein a reconfiguration of the materials can be triggered chemically of mechanically. The utility of these methods is to generate transduction mechanisms by which chemical and biological sensors can be developed. Three different types of systems will be discussed. (1) Particles wherein a protease enzyme releases strain in the particle by breaking crosslinks. (2) Assemblies of polymers at air water interfaces and the demonstration of a luminescence strain response upon compression. (3) Dynamic colloids produced from immiscible fluorocarbon/hydrocarbon mixtures and ability to convert the core and shell layers of the particles as well as the conversion to Janus particles. The latter system's morphology changes can be triggered chemically or optically.

  15. 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.

  16. Galectin-9: From cell biology to complex disease dynamics.

    PubMed

    John, Sebastian; Mishra, Rashmi

    2016-09-01

    Galectins is a family of non-classically secreted, beta-galactoside-binding proteins that has recently received considerable attention in the spatio-temporal regulation of surface 'signal lattice' organization, membrane dynamics, cell-adhesion and disease therapeutics. Galectin-9 is a unique member of this family, with two non-homologous carbohydrate recognition domains joined by a linker peptide sequence of variable lengths, generating isoforms with distinct properties and functions in both physiological and pathological settings, such as during development, immune reaction, neoplastic transformations and metastasis. In this review, we summarize the latest knowledge on the structure, receptors, cellular targets, trafficking pathways and functional properties of galectin-9 and discuss how galectin-9-mediated signalling cascades can be exploited in cancers and immunotherapies. PMID:27581941

  17. Spectroscopy and reaction dynamics of collision complexes containing hydroxyl radicals

    SciTech Connect

    Lester, M.I.

    1993-12-01

    The DOE supported work in this laboratory has focused on the spectroscopic characterization of the interaction potential between an argon atom and a hydroxyl radical in the ground X{sup 2}II and excited A {sup 2}{summation}{sup +} electronic states. The OH-Ar system has proven to be a test case for examining the interaction potential in an open-shell system since it is amenable to experimental investigation and theoretically tractable from first principles. Experimental identification of the bound states supported by the Ar + OH (X {sup 2}II) and Ar + OH(A {sup 2}{summation}{sup +}) potentials makes it feasible to derive realistic potential energy surfaces for these systems. The experimentally derived intermolecular potentials provide a rigorous test of ab initio theory and a basis for understanding the dramatically different collision dynamics taking place on the ground and excited electronic state surfaces.

  18. Railway faults spreading model based on dynamics of complex network

    NASA Astrophysics Data System (ADS)

    Zhou, Jin; Xu, Weixiang; Guo, Xin; Ma, Xin

    2015-12-01

    In this paper, we propose a railway faults spreading model which improved the SIR model and made it suitable for analyzing the dynamic process of faults spreading. To apply our model into a real network, the accident causation network of "7.23" China Yongwen high-speed railway accident is employed. This network is improved into a directed network, which more clearly reflects the causation relationships among the accident factors and provides help for our studies. Simulation results quantitatively show that the influence of failures can be diminished via choosing the appropriate initial recovery factors, reducing the time of the failure detected, decreasing the transmission rate of faults and increasing the propagating rate of corrected information. The model is useful to simulate the railway faults spreading and quantitatively analyze the influence of failures.

  19. Momentum conserving Brownian dynamics propagator for complex soft matter fluids.

    PubMed

    Padding, J T; Briels, W J

    2014-12-28

    We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution. We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics. PMID:25554134

  20. Dynamic Simulation of VEGA SRM Bench Firing By Using Propellant Complex Characterization

    NASA Astrophysics Data System (ADS)

    Di Trapani, C. D.; Mastrella, E.; Bartoccini, D.; Squeo, E. A.; Mastroddi, F.; Coppotelli, G.; Linari, M.

    2012-07-01

    During the VEGA launcher development, from the 2004 up to now, 8 firing tests have been performed at Salto di Quirra (Sardinia, Italy) and Kourou (Guyana, Fr) with the objective to characterize and qualify of the Zefiros and P80 Solid Rocket Motors (SRM). In fact the VEGA launcher configuration foreseen 3 solid stages based on P80, Z23 and Z9 Solid Rocket Motors respectively. One of the primary objectives of the firing test is to correctly characterize the dynamic response of the SRM in order to apply such a characterization to the predictions and simulations of the VEGA launch dynamic environment. Considering that the solid propellant is around 90% of the SRM mass, it is very important to dynamically characterize it, and to increase the confidence in the simulation of the dynamic levels transmitted to the LV upper part from the SRMs. The activity is articulated in three parts: • consolidation of an experimental method for the dynamic characterization of the complex dynamic elasticity modulus of elasticity of visco-elastic materials applicable to the SRM propellant operative conditions • introduction of the complex dynamic elasticity modulus in a numerical FEM benchmark based on MSC NASTRAN solver • analysis of the effect of the introduction of the complex dynamic elasticity modulus in the Zefiros FEM focusing on experimental firing test data reproduction with numerical approach.

  1. Epidemic spreading model of complex dynamical network with the heterogeneity of nodes

    NASA Astrophysics Data System (ADS)

    Hong, Sheng; Yang, Hongqi; Zhao, Tingdi; Ma, Xiaomin

    2016-08-01

    In this paper, we model epidemic spreading by considering the mobility of nodes in complex dynamical network based on mean field theory using differential equations. Moreover, a resistance factor which can characterise the impact of individual's difference on the propagation dynamics in complex dynamical network is proposed by considering the influence of total number of connections and the continuous time to remain in contact. The effect of heterogeneity on the evolution process of propagation dynamics is explored by simulation. Extensive simulations are conducted to study the key influence parameters and the influence of them on the spreading dynamics, which are helpful to the understanding of epidemic spreading mechanism and the designing of effective control strategies.

  2. Linear Superposition and Prediction of Bacterial Promoter Activity Dynamics in Complex Conditions

    PubMed Central

    Rothschild, Daphna; Dekel, Erez; Hausser, Jean; Bren, Anat; Aidelberg, Guy; Szekely, Pablo; Alon, Uri

    2014-01-01

    Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments. PMID:24809350

  3. Fractal and complex network analyses of protein molecular dynamics

    NASA Astrophysics Data System (ADS)

    Zhou, Yuan-Wu; Liu, Jin-Long; Yu, Zu-Guo; Zhao, Zhi-Qin; Anh, Vo

    2014-12-01

    Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2) of MF-DFA on the time series, exponent λ of the exponential degree distribution and fractal dimension dB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between (from MF-DFA on time series) and of the converted HVGs for different energy, pressure and volume.

  4. Preferential attachment and growth dynamics in complex systems

    NASA Astrophysics Data System (ADS)

    Yamasaki, Kazuko; Matia, Kaushik; Buldyrev, Sergey V.; Fu, Dongfeng; Pammolli, Fabio; Riccaboni, Massimo; Stanley, H. Eugene

    2006-09-01

    Complex systems can be characterized by classes of equivalency of their elements defined according to system specific rules. We propose a generalized preferential attachment model to describe the class size distribution. The model postulates preferential growth of the existing classes and the steady influx of new classes. According to the model, the distribution changes from a pure exponential form for zero influx of new classes to a power law with an exponential cut-off form when the influx of new classes is substantial. Predictions of the model are tested through the analysis of a unique industrial database, which covers both elementary units (products) and classes (markets, firms) in a given industry (pharmaceuticals), covering the entire size distribution. The model’s predictions are in good agreement with the data. The paper sheds light on the emergence of the exponent τ≈2 observed as a universal feature of many biological, social and economic problems.

  5. Distributed parameter approach to the dynamics of complex biological processes

    SciTech Connect

    Lee, T.T.; Wang, F.Y.; Newell, R.B.

    1999-10-01

    Modeling and simulation of a complex biological process for the removal of nutrients (nitrogen and phosphorus) from municipal wastewater are addressed. The model developed in this work employs a distributed-parameter approach to describe the behavior of components within three different bioreaction zones and the behavior of sludge in the anaerobic zone and soluble phosphate in the aerobic zone in two experiments. Good results are achieved despite the apparent plant-model mismatch, such as uncertainties with the behavior of phosphorus-accumulating organisms. Validation of the proposed secondary-settler model shows that it is superior to two state-of-the-art models in terms of the sum of the square relative errors.

  6. Characterization and dynamic properties for the solid inclusion complexes of β-cyclodextrin and perfluorooctanoic acid.

    PubMed

    Karoyo, Abdalla H; Sidhu, Paul; Wilson, Lee D; Hazendonk, Paul

    2013-07-11

    The structural characterization and dynamic properties of solid-state inclusion complexes (ICs) formed between β-cyclodextrin (β-CD; host) and perfluorooctanoic acid (PFOA; guest) were investigated using (13)C NMR spectroscopy. The 1:1 and 2:1 host/guest solid-state complexes were prepared using a modified dissolution method to obtain complexes with high phase purity. These complexes were further characterized using differential scanning calorimetry (DSC), FT-IR spectroscopy, powder X-ray diffraction (PXRD), (19)F directpolarization (DP), and (13)C cross-polarization (CP) with magic-angle spinning (MAS) NMR spectroscopy. The (19)F → (13)C CP results provided unequivocal support for the formation of well-defined inclusion compounds. The phase purity of the complexes formed between β-CD and PFOA were assessed using the (19)F DP NMR technique at variable temperature (VT) and MAS at 20 kHz. The complexes were found to be of high phase purity when prepared in accordance with the modified dissolution method. The motional dynamics of the guest in the solid complexes were assessed using T1/T2/T1ρ relaxation NMR methods at ambient and VT conditions. The relaxation data revealed reliable and variable guest dynamics for the 1:1 versus 2:1 complexes at the VTs investigated. The motional dynamics of the guest molecules involve an ensemble of axial motions of the whole chain and 120° rotational jumps of the methyl (CF3) group at the termini of the perfluorocarbon chain. The axial and rotational dynamics of the guest in the 1:1 and 2:1 complexes differ in distribution and magnitude in accordance with the binding geometry of the guest within the host. PMID:23713518

  7. Non-Gaussian statistics, classical field theory, and realizable Langevin models

    SciTech Connect

    Krommes, J.A.

    1996-05-01

    The direct-interaction approximation (DIA) to the fourth-order statistic {ital Z}{approximately}{l_angle}({lambda}{psi}{sup 2}){sup 2}{r_angle}, where {lambda} is a specified operator and {psi} is a random field, is discussed from several points of view distinct from that of Chen {ital et} {ital al}. [Phys. Fluids A {bold 1}, 1844 (1989)]. It is shown that the formula for {ital Z}{sub DIA} already appeared in the seminal work of Martin, Siggia, and Rose [Phys. Rev. A {bold 8}, 423 (1973)] on the functional approach to classical statistical dynamics. It does not follow from the original generalized Langevin equation (GLE) of Leith [J. Atmos. Sci. {bold 28}, 145 (1971)] and Kraichnan [J. Fluid Mech. {bold 41}, 189 (1970)] (frequently described as an amplitude representation for the DIA), in which the random forcing is realized by a particular superposition of products of random variables. The relationship of that GLE to renormalized field theories with non-Gaussian corrections ({open_quote}{open_quote}spurious vertices{close_quote}{close_quote}) is described. It is shown how to derive an improved representation, which realizes cumulants through {ital O}({psi}{sup 4}), by adding to the GLE a particular non-Gaussian correction. A Markovian approximation {ital Z}{sub DIA}{sup {ital M}} to {ital Z}{sub DIA} is derived. Both {ital Z}{sub DIA} and {ital Z}{sub DIA}{sup {ital M}} incorrectly predict a Gaussian kurtosis for the steady state of a solvable three-mode example. {copyright} {ital 1996 The American Physical Society.}

  8. Assessing small-worldness of dynamic functional brain connectivity during complex tasks.

    PubMed

    Shen Ren; Taya, Fumihiko; Yu Sun; deSouza, Joshua; Thakor, Nitish V; Bezerianos, Anastasios

    2015-08-01

    The development of network theory has introduced new approaches to understand the brain as a complex system. Currently the time-variant functional connectivity of brain networks under complex tasks is still being investigated. To explore connectivity during complex cognitive and motor tasks, this study focused on the relevance of small-worldness to human workloads using EEG signals from a dynamic analytic approach. Experiments were designed to investigate the small-worldness under two types of flight simulation tasks at two levels of difficulty - easy and hard. The results demonstrated a consistent small-world architecture of brain connectivity with time-based variance during complex tasks. We noticed an increased small-world effect especially at the alpha band when performing hard tasks compared to easy tasks, which relate to high and low workload respectively. Our results show the potential of dynamic brain network analysis in exploring time-variant and task-dependent brain connectivity during complex tasks. PMID:26736899

  9. First principles molecular dynamics study of nitrogen vacancy complexes in boronitrene.

    PubMed

    Ukpong, A M; Chetty, N

    2012-07-01

    We present the results of first principles molecular dynamics simulations of nitrogen vacancy complexes in monolayer hexagonal boron nitride. The threshold for local structure reconstruction is found to be sensitive to the presence of a substitutional carbon impurity. We show that activated nitrogen dynamics triggers the annihilation of defects in the layer through formation of Stone-Wales-type structures. The lowest energy state of nitrogen vacancy complexes is negatively charged and spin polarized. Using the divacancy complex, we show that their formation induces spontaneous magnetic moments, which is tunable by electron or hole injection. The Fermi level s-resonant defect state is identified as a unique signature of the ground state of the divacancy complex. Due to their ability to enhance structural cohesion, only the divacancy and the nitrogen vacancy carbon-antisite complexes are able to suppress the Fermi level resonant defect state to open a gap between the conduction and valence bands. PMID:22677800

  10. Restricted dynamics of water around a protein-carbohydrate complex: Computer simulation studies

    NASA Astrophysics Data System (ADS)

    Jana, Madhurima; Bandyopadhyay, Sanjoy

    2012-08-01

    Water-mediated protein-carbohydrate interaction is a complex phenomenon responsible for different biological processes in cellular environment. One of the unexplored but important issues in this area is the role played by water during the recognition process and also in controlling the microscopic properties of the complex. In this study, we have carried out atomistic molecular dynamics simulations of a protein-carbohydrate complex formed between the hyaluronan binding domain of the murine Cd44 protein and the octasaccharide hyaluronan in explicit water. Efforts have been made to explore the heterogeneous influence of the complex on the dynamic properties of water present in different regions around it. It is revealed from our analyses that the heterogeneous dynamics of water around the complex are coupled with differential time scales of formation and breaking of hydrogen bonds at the interface. Presence of a highly rigid thin layer of motionally restricted water molecules bridging the protein and the carbohydrate in the common region of the complex has been identified. Such water molecules are expected to play a crucial role in controlling properties of the complex. Importantly, it is demonstrated that the formation of the protein-carbohydrate complex affects the transverse and longitudinal degrees of freedom of the interfacial water molecules in a heterogeneous manner.

  11. Gaussian Process Model for Collision Dynamics of Complex Molecules

    NASA Astrophysics Data System (ADS)

    Cui, Jie; Krems, Roman V.

    2015-08-01

    We show that a Gaussian process model can be combined with a small number (of order 100) of scattering calculations to provide a multidimensional dependence of scattering observables on the experimentally controllable parameters (such as the collision energy or temperature) as well as the potential energy surface (PES) parameters. For the case of Ar -C6H6 collisions, we show that 200 classical trajectory calculations are sufficient to provide a ten-dimensional hypersurface, giving the dependence of the collision lifetimes on the collision energy, internal temperature, and eight PES parameters. This can be used for solving the inverse scattering problem, for the efficient calculation of thermally averaged observables, for reducing the error of the molecular dynamics calculations by averaging over the PES variations, and for the analysis of the sensitivity of the observables to individual parameters determining the PES. Trained by a combination of classical and quantum calculations, the model provides an accurate description of the quantum scattering cross sections, even near scattering resonances.

  12. Dynamics and complexity of the Schelling segregation model

    NASA Astrophysics Data System (ADS)

    Domic, Nicolás Goles; Goles, Eric; Rica, Sergio

    2011-05-01

    In this paper we consider the Schelling social segregation model for two different populations. In Schelling’s model, segregation appears as a consequence of discrimination, measured by the local difference between two populations. For that, the model defines a tolerance criterion on the neighborhood of an individual, indicating wether the individual is able to move to a new place or not. Next, the model chooses which of the available unhappy individuals really moves. In our work, we study the patterns generated by the dynamical evolution of the Schelling model in terms of various parameters or the initial condition, such as the size of the neighborhood of an inhabitant, the tolerance, and the initial number of individuals. As a general rule we observe that segregation patterns minimize the interface of zones of different people. In this context we introduce an energy functional associated with the configuration which is a strictly decreasing function for the tolerant people case. Moreover, as far as we know, we are the first to notice that in the case of a non-strictly-decreasing energy functional, the system may segregate very efficiently.

  13. Complexity Science Applications to Dynamic Trajectory Management: Research Strategies

    NASA Technical Reports Server (NTRS)

    Sawhill, Bruce; Herriot, James; Holmes, Bruce J.; Alexandrov, Natalia

    2009-01-01

    The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.

  14. Dynamical Theory of Charge Transfer Between Complex Atoms and Surfaces

    NASA Astrophysics Data System (ADS)

    Chaudhuri, Basudev; Marston, Brad

    2000-03-01

    An existing dynamical quantum many-body theory of charge transfer(A. V. Onufriev and J. B. Marston, Phys. Rev. B 53), 13340 (1996); J. Merino and J. B. Marston, Phys. Rev. B 58, 6982 (1998). describes atoms with simple s-orbitals, such as alkalis and alkaline-earths, interacting with metal surfaces. The many-body equations of motion (EOM) are developed systematically as an expansion in the number of surface particle-hole excitations. Here we generalize this theory to describe atoms with richer orbital structures, such as atomic oxygen. In the simplest version of the model, only the single-particle p_z-orbitals of the atom, the ones oriented perpendicular to the surface, participate directly in resonant charge transfer as they have the largest overlap with the metallic wavefunctions. However, as the several-electron Russell-Saunders eigenstates, labeled by total angular momenta quantum numbers J, L, and S, are built out of products of single-particle orbitals, non-trivial matrix elements must be incorporated into the many-body EOM's. Comparison to recent experimental results(A. C. Lavery, C. E. Sosolik, and B. H. Cooper, Nucl. Instrum. Meth. B 157), 42 (1999); A. C. Lavery et al. to appear in Phys. Rev. B. on the scattering of low-energy oxygen ions off Cu(001) surfaces is made.

  15. Approximate method for stochastic chemical kinetics with two-time scales by chemical Langevin equations.

    PubMed

    Wu, Fuke; Tian, Tianhai; Rawlings, James B; Yin, George

    2016-05-01

    The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766-1793 (1996); ibid. 56, 1794-1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence. PMID:27155630

  16. Approximate method for stochastic chemical kinetics with two-time scales by chemical Langevin equations

    NASA Astrophysics Data System (ADS)

    Wu, Fuke; Tian, Tianhai; Rawlings, James B.; Yin, George

    2016-05-01

    The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766-1793 (1996); ibid. 56, 1794-1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.

  17. Complex zeros of the 2 d Ising model on dynamical random lattices

    NASA Astrophysics Data System (ADS)

    Ambjørn, J.; Anagnostopoulos, K. N.; Magnea, U.

    1998-04-01

    We study the zeros in the complex plane of the partition function for the Ising model coupled to 2 d quantum gravity for complex magnetic field and for complex temperature. We compute the zeros by using the exact solution coming from a two matrix model and by Monte Carlo simulations of Ising spins on dynamical triangulations. We present evidence that the zeros form simple one-dimensional patterns in the complex plane, and that the critical behaviour of the system is governed by the scaling of the distribution of singularities near the critical point.

  18. Complex amplitude correlations of dynamic laser speckle in complex ABCD optical systems.

    PubMed

    Wang, Wei; Hanson, Steen G; Takeda, Mitsuo

    2006-09-01

    Within the framework of complex ABCD-matrix theory, exact theoretical expressions are derived for the space-time-lagged cross-covariance functions of the fields valid for arbitrary (complex) ABCD-optical systems, i.e., systems that include Gaussian-shaped apertures and partially developed speckle. Specifically, we show and discuss the results for the three generic systems, i.e., free-space propagation, Fourier transform configuration, and imaging. To cope with various surface structures of varying rms surface heights, we apply two models in addition to employing the usual model for surfaces giving rise to fully developed speckle. The theoretical results found for free-space propagation are supported by interferometrically obtained data. PMID:16912746

  19. Safety assessment document for the Dynamic Test Complex B854

    SciTech Connect

    Odell, B.N.; Pfeifer, H.E.

    1981-12-11

    A safety assessment was performed to determine if potential accidents at the 854 Complex at Site 300 could present undue hazards to the general public, personnel at Site 300, or have an adverse effect on the environment. The credible accidents that might have an effect on these facilities or have off-site consequences were considered. These were earthquake, extreme wind (including missiles), lightning, flood, criticality, high explosive (HE) detonation that disperses uranium and beryllium, spontaneous oxidation of plutonium, explosions due to finely divided particles, and a fire. Seismic and extreme wind (including missiles) analyses indicate that the buildings are basically sound. The lightning protection system is in the process of being upgraded to meet AMCR 385-100. These buildings are located high above the dry creek bed so that a flood is improbable. The probability of high explosive detonation involving plutonium is very remote since the radioactive materials are encased and plutonium and HE are not permitted concurrently in the same area at Site 300. (The exception to this policy is that explosive actuating devices are sometimes located in assemblies containing fissile materials. However, an accidental actuation will not affect the safe containment of the plutonium within the assembly.) There is a remote possibility of an HE explosion involving uranium and beryllium since these are permitted in the same area.The possibility of a criticality accident is very remote since the fissile materials are doubly encased in stout metal containers. All operations involving these materials are independently reviewed and inspected by the Criticality Safety Office. It was determined that a fire was unlikely due to the low fire loading and the absence of ignition sources. It was also determined that the consequences of any accidents were reduced by the remote location of these facilities, their design, and by administrative controls.

  20. Ecological dynamics and complex interactions of Agrobacterium megaplasmids

    PubMed Central

    Platt, Thomas G.; Morton, Elise R.; Barton, Ian S.; Bever, James D.; Fuqua, Clay

    2014-01-01

    As with many pathogenic bacteria, agrobacterial plant pathogens carry most of their virulence functions on a horizontally transmissible genetic element. The tumor-inducing (Ti) plasmid encodes the majority of virulence functions for the crown gall agent Agrobacterium tumefaciens. This includes the vir genes which drive genetic transformation of host cells and the catabolic genes needed to utilize the opines produced by infected plants. The Ti plasmid also encodes, an opine-dependent quorum sensing system that tightly regulates Ti plasmid copy number and its conjugal transfer to other agrobacteria. Many natural agrobacteria are avirulent, lacking the Ti plasmid. The burden of harboring the Ti plasmid depends on the environmental context. Away from diseased hosts, plasmid costs are low but the benefit of the plasmid is also absent. Consequently, plasmidless genotypes are favored. On infected plants the costs of the Ti plasmid can be very high, but balanced by the opine benefits, locally favoring plasmid bearing cells. Cheating derivatives which do not incur virulence costs but can benefit from opines are favored on infected plants and in most other environments, and these are frequently isolated from nature. Many agrobacteria also harbor an At plasmid which can stably coexist with a Ti plasmid. At plasmid genes are less well characterized but in general facilitate metabolic activities in the rhizosphere and bulk soil, such as the ability to breakdown plant exudates. Examination of A. tumefaciens C58, revealed that harboring its At plasmid is much more costly than harboring it’s Ti plasmid, but conversely the At plasmid is extremely difficult to cure. The interactions between these co-resident plasmids are complex, and depend on environmental context. However, the presence of a Ti plasmid appears to mitigate At plasmid costs, consistent with the high frequency with which they are found together. PMID:25452760

  1. Dynamical complexity of multipoint geospace observations related to magnetosphere-ionosphere coupling

    NASA Astrophysics Data System (ADS)

    Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Donner, Reik; Runge, Jakob

    2016-07-01

    We explore, evaluate and compare the applicability, effectiveness and interdisciplinary character of a variety of modern and sophisticated methods, from complex systems sciences, for the investigation of dynamical complexity of the near-Earth electromagnetic environment. We identify and inter-compare complementary analysis concepts, allowing for a systematic study of geospace magnetic storms and magnetospheric substorms and regime shifts between normal and abnormal states of the Earth's magnetic field, based on observational data from both ground and space. We expect these concepts to allow identifying previously unrecognized precursory structures in the dynamical complexity and, thus, contribute to a better understanding of dynamical processes manifested in observable magnetic field fluctuations prior to possible space weather-related hazards.

  2. Understanding Life : The Evolutionary Dynamics of Complexity and Semiosis

    NASA Astrophysics Data System (ADS)

    Loeckenhoff, Helmut K.

    2010-11-01

    Post-Renaissance sciences created different cultures. To establish an epistemological base, Physics were separated from the Mental domain. Consciousness was excluded from science. Life Sciences were left in between e.g. LaMettrie's `man—machine' (1748) and 'vitalism' [e.g. Bergson 4]. Causative thinking versus intuitive arguing limited strictly comprehensive concepts. First ethology established a potential shared base for science, proclaiming the `biology paradigm' in the middle of the 20th century. Initially procured by Cybernetics and Systems sciences, `constructivist' models prepared a new view on human perception and thus also of scientific `objectivity when introducing the `observer'. In sequel Computer sciences triggered the ICT revolution. In turn ICT helped to develop Chaos and Complexity sciences, Non-linear Mathematics and its spin-offs in the formal sciences [Spencer-Brown 49] as e.g. (proto-)logics. Models of life systems, as e.g. Anticipatory Systems, integrated epistemology with mathematics and Anticipatory Computing [Dubois 11, 12, 13, 14] connecting them with Semiotics. Seminal ideas laid in the turn of the 19th to the 20th century [J. v. Uexküll 53] detected the co-action and co-evolvement of environments and life systems. Bio-Semiotics ascribed purpose, intent and meaning as essential qualities of life. The concepts of Systems Biology and Qualitative Research enriched and develop also anthropologies and humanities. Brain research added models of (higher) consciousness. An avant-garde is contemplating a science including consciousness as one additional base. New insights from the extended qualitative approach led to re-conciliation of basic assumptions of scientific inquiry, creating the `epistemological turn'. Paradigmatically, resting on macro- micro- and recently on nano-biology, evolution biology sired fresh scripts of evolution [W. Wieser 60,61]. Its results tie to hypotheses describing the emergence of language, of the human mind and of

  3. Data based identification and prediction of nonlinear and complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  4. The solar-wind driven magnetosphere{endash}ionosphere as a complex dynamical system

    SciTech Connect

    Horton, W.; Smith, J.P.; Weigel, R.; Crabtree, C.; Doxas, I.; Goode, B.; Cary, J.

    1999-11-01

    The solar-wind driven magnetosphere{endash}ionosphere system is a classic example of a complex dynamical system (CDS). The defining properties of a CDS are (1) sensitivity to initial conditions; (2) multiple space-time scales; (3) bifurcation sequences with hysteresis in transitions between attractors; and (4) noncompositionality. Noncompositionality means that the behavior of the system as a whole is different from the dynamics of its subcomponents taken with passive or no couplings. In particular the dynamics of the geomagnetic tail plasma depends on its coupling to the dissipative ionospheric plasma and on the nature of the solar-wind driving electric field over a suitably long (many hours) previous time interval. These complex dynamical system features are shown here in detail using the known WINDMI model for the solar-wind driven magnetosphere{endash}ionosphere (MI) system. Numerous features in the bifurcation sequence are identified with known substorm and storm characteristics. {copyright} {ital 1999 American Institute of Physics.}

  5. Markov and non-Markov processes in complex systems by the dynamical information entropy

    NASA Astrophysics Data System (ADS)

    Yulmetyev, R. M.; Gafarov, F. M.

    1999-12-01

    We consider the Markov and non-Markov processes in complex systems by the dynamical information Shannon entropy (DISE) method. The influence and important role of the two mutually dependent channels of entropy alternation (creation or generation of correlation) and anti-correlation (destroying or annihilation of correlation) have been discussed. The developed method has been used for the analysis of the complex systems of various natures: slow neutron scattering in liquid cesium, psychology (short-time numeral and pattern human memory and effect of stress on the dynamical taping-test), random dynamics of RR-intervals in human ECG (problem of diagnosis of various disease of the human cardio-vascular systems), chaotic dynamics of the parameters of financial markets and ecological systems.

  6. Asymmetric collapse in biomimetic complex coacervates revealed by local polymer and water dynamics.

    PubMed

    Ortony, Julia H; Hwang, Dong Soo; Franck, John M; Waite, J Herbert; Han, Songi

    2013-05-13

    Complex coacervation is a phenomenon characterized by the association of oppositely charged polyelectrolytes into micrometer-scale liquid condensates. This process is the purported first step in the formation of underwater adhesives by sessile marine organisms, as well as the process harnessed for the formation of new synthetic and protein-based contemporary materials. Efforts to understand the physical nature of complex coacervates are important for developing robust adhesives, injectable materials, or novel drug delivery vehicles for biomedical applications; however, their internal fluidity necessitates the use of in situ characterization strategies of their local dynamic properties, capabilities not offered by conventional techniques such as X-ray scattering, microscopy, or bulk rheological measurements. Herein, we employ the novel magnetic resonance technique Overhauser dynamic nuclear polarization enhanced nuclear magnetic resonance (DNP), together with electron paramagnetic resonance (EPR) line shape analysis, to concurrently quantify local molecular and hydration dynamics, with species- and site-specificity. We observe striking differences in the structure and dynamics of the protein-based biomimetic complex coacervates from their synthetic analogues, which is an asymmetric collapse of the polyelectrolyte constituents. From this study we suggest charge heterogeneity within a given polyelectrolyte chain to be an important parameter by which the internal structure of complex coacervates may be tuned. Acquiring molecular-level insight to the internal structure and dynamics of dynamic polymer complexes in water through the in situ characterization of site- and species-specific local polymer and hydration dynamics should be a promising general approach that has not been widely employed for materials characterization. PMID:23540713

  7. Langevin equation with stochastic damping - Possible application to critical binary fluid

    NASA Technical Reports Server (NTRS)

    Jasnow, D.; Gerjuoy, E.

    1975-01-01

    We solve the familiar Langevin equation with stochastic damping to represent the motion of a Brownian particle in a fluctuating medium. A connection between the damping and the random driving forces is proposed which preserves quite generally the Einstein relation between the diffusion and mobility coefficients. We present an application to the case of a Brownian particle in a critical binary mixture.

  8. Critical comparison of Kramers' fission width with the stationary width from the Langevin equation

    SciTech Connect

    Sadhukhan, Jhilam; Pal, Santanu

    2009-06-15

    It is shown that Kramers' fission width, originally derived for a system with constant inertia, can be extended to systems with a deformation-dependent collective inertia, which is the case for nuclear fission. The predictions of Kramers' width for systems with variable inertia are found to be in very good agreement with the stationary fission widths obtained by solving the corresponding Langevin equations.

  9. Cilium transition zone proteome reveals compartmentalization and differential dynamics of ciliopathy complexes.

    PubMed

    Dean, Samuel; Moreira-Leite, Flavia; Varga, Vladimir; Gull, Keith

    2016-08-30

    The transition zone (TZ) of eukaryotic cilia and flagella is a structural intermediate between the basal body and the axoneme that regulates ciliary traffic. Mutations in genes encoding TZ proteins (TZPs) cause human inherited diseases (ciliopathies). Here, we use the trypanosome to identify TZ components and localize them to TZ subdomains, showing that the Bardet-Biedl syndrome complex (BBSome) is more distal in the TZ than the Meckel syndrome (MKS) complex. Several of the TZPs identified here have human orthologs. Functional analysis shows essential roles for TZPs in motility, in building the axoneme central pair apparatus and in flagellum biogenesis. Analysis using RNAi and HaloTag fusion protein approaches reveals that most TZPs (including the MKS ciliopathy complex) show long-term stable association with the TZ, whereas the BBSome is dynamic. We propose that some Bardet-Biedl syndrome and MKS pleiotropy may be caused by mutations that impact TZP complex dynamics. PMID:27519801

  10. A Langevin model of physical forces in cell volume fluctuations.

    PubMed

    Zehnder, Steven M; Zegers, Federico M; Angelini, Thomas E

    2016-05-24

    Cells interact mechanically with their physical surroundings by attaching to the extracellular matrix or other cells and contracting the cytoskeleton. Cells do so dynamically, exhibiting fluctuating contractile motion in time. In monolayers, these dynamic contractions manifest as volume fluctuations, which involve the transport of fluid in and out of the cell. An integrated understanding of cell elasticity, actively generated stresses, and fluid transport has not yet been developed. Here we apply a minimal model of these forces to cell volume fluctuation data, elucidating the dynamic behavior of cells within monolayers. PMID:26787009

  11. Molecular dynamics of protein kinase-inhibitor complexes: a valid structural information.

    PubMed

    Caballero, Julio; Alzate-Morales, Jans H

    2012-01-01

    Protein kinases (PKs) are key components of protein phosphorylation based signaling networks in eukaryotic cells. They have been identified as being implicated in many diseases. High-resolution X-ray crystallographic data exist for many PKs and, in many cases, these structures are co-complexed with inhibitors. Although this valuable information confirms the precise structure of PKs and their complexes, it ignores the dynamic movements of the structures which are relevant to explain the affinities and selectivity of the ligands, to characterize the thermodynamics of the solvated complexes, and to derive predictive models. Atomistic molecular dynamics (MD) simulations present a convenient way to study PK-inhibitor complexes and have been increasingly used in recent years in structure-based drug design. MD is a very useful computational method and a great counterpart for experimentalists, which helps them to derive important additional molecular information. That enables them to follow and understand structure and dynamics of protein-ligand systems with extreme molecular detail on scales where motion of individual atoms can be tracked. MD can be used to sample dynamic molecular processes, and can be complemented with more advanced computational methods (e.g., free energy calculations, structure-activity relationship analysis). This review focuses on the most commonly applications to study PK-inhibitor complexes using MD simulations. Our aim is that researchers working in the design of PK inhibitors be aware of the benefits of this powerful tool in the design of potent and selective PK inhibitors. PMID:22571663

  12. Complex dynamics in a cross-catalytic self-replication mechanism

    NASA Astrophysics Data System (ADS)

    Beutel, Kathleen M.; Peacock-López, Enrique

    2007-03-01

    The authors consider a minimal cross-catalytic self-replicating system of only two cross-catalytic templates that mimics the R3C ligase ribozyme system of Dong-Eu and Joyce [Chem. Biol. 11, 1505 (2004)]. This system displays considerably more complex dynamics than its self-replicating counterpart. In particular, the authors discuss the Poincaré-Andronov-Hopf bifurcation, canard transitions, excitability, and hysteresis that yield birhythmicity between simple and complex oscillations.

  13. Mathematical Physics of Complex Coevolutionary Systems: Theoretical Advances and Applications to Multiscale Hydroclimate Dynamics

    NASA Astrophysics Data System (ADS)

    Perdigão, Rui A. P.

    2016-04-01

    The fundamental stochastic-dynamic coevolution laws governing complex coevolutionary systems are introduced in a mathematical physics framework formally unifying nonlinear stochastic physics with fundamental deterministic interaction laws among spatiotemporally distributed processes. The methodological developments are then used to shed light onto fundamental interactions underlying complex spatiotemporal behaviour and emergence in multiscale hydroclimate dynamics. For this purpose, a mathematical physics framework is presented predicting evolving distributions of hydrologic quantities under nonlinearly coevolving geophysical processes. The functional formulation is grounded on first principles regulating the dynamics of each system constituent and their interactions, therefore its applicability is general and data-independent, not requiring local calibrations. Moreover, it enables the dynamical estimation of hydroclimatic variations in space and time from knowledge at different spatiotemporal conditions, along with the associated uncertainties. This paves the way for a robust physically based prediction of hydroclimatic changes in unsupervised areas (e.g. ungauged basins). Validation is achieved by producing, with the mathematical physics framework, a comprehensive spatiotemporal legacy consistent with the observed distributions along with their statistic-dynamic relations. The similarity between simulated and observed distributions is further assessed with novel robust nonlinear information-theoretic diagnostics. The present study brings to light emerging signatures of structural change in hydroclimate dynamics arising from nonlinear synergies across multiple spatiotemporal scales, and contributes to a better dynamical understanding and prediction of spatiotemporal regimes, transitions, structural changes and extremes in complex coevolutionary systems. This study further sheds light onto a diversity of emerging properties from harmonic to hyper-chaotic in general

  14. Complex quantum Hamilton-Jacobi equation with Bohmian trajectories: Application to the photodissociation dynamics of NOCl

    SciTech Connect

    Chou, Chia-Chun

    2014-03-14

    The complex quantum Hamilton-Jacobi equation-Bohmian trajectories (CQHJE-BT) method is introduced as a synthetic trajectory method for integrating the complex quantum Hamilton-Jacobi equation for the complex action function by propagating an ensemble of real-valued correlated Bohmian trajectories. Substituting the wave function expressed in exponential form in terms of the complex action into the time-dependent Schrödinger equation yields the complex quantum Hamilton-Jacobi equation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation describing the rate of change in the complex action transported along Bohmian trajectories is simultaneously integrated with the guidance equation for Bohmian trajectories, and the time-dependent wave function is readily synthesized. The spatial derivatives of the complex action required for the integration scheme are obtained by solving one moving least squares matrix equation. In addition, the method is applied to the photodissociation of NOCl. The photodissociation dynamics of NOCl can be accurately described by propagating a small ensemble of trajectories. This study demonstrates that the CQHJE-BT method combines the considerable advantages of both the real and the complex quantum trajectory methods previously developed for wave packet dynamics.

  15. Complex quantum Hamilton-Jacobi equation with Bohmian trajectories: application to the photodissociation dynamics of NOCl.

    PubMed

    Chou, Chia-Chun

    2014-03-14

    The complex quantum Hamilton-Jacobi equation-Bohmian trajectories (CQHJE-BT) method is introduced as a synthetic trajectory method for integrating the complex quantum Hamilton-Jacobi equation for the complex action function by propagating an ensemble of real-valued correlated Bohmian trajectories. Substituting the wave function expressed in exponential form in terms of the complex action into the time-dependent Schrödinger equation yields the complex quantum Hamilton-Jacobi equation. We transform this equation into the arbitrary Lagrangian-Eulerian version with the grid velocity matching the flow velocity of the probability fluid. The resulting equation describing the rate of change in the complex action transported along Bohmian trajectories is simultaneously integrated with the guidance equation for Bohmian trajectories, and the time-dependent wave function is readily synthesized. The spatial derivatives of the complex action required for the integration scheme are obtained by solving one moving least squares matrix equation. In addition, the method is applied to the photodissociation of NOCl. The photodissociation dynamics of NOCl can be accurately described by propagating a small ensemble of trajectories. This study demonstrates that the CQHJE-BT method combines the considerable advantages of both the real and the complex quantum trajectory methods previously developed for wave packet dynamics. PMID:24628169

  16. Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

    PubMed Central

    Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

    2015-01-01

    Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

  17. Fundamental properties of soils for complex dynamic loadings: Dynamic constitutive modeling of sandy soils

    NASA Astrophysics Data System (ADS)

    Dass, W.; Merkle, D. H.; Bratton, J. L.

    1983-04-01

    Constitutive modeling of cohesionless soil for both standard static test conditions and insitu impulsive dynamic load conditions is discussed in this annual report. Predicted laboratory response for several different types of models is evaluated using data from a coordinated testing program. The modeling of insitu soil response to explosive events (CIST and DISC Test) is considered, and the laboratory-derived models are tested for their convenience and accuracy in predicting ground motions. Several important laboratory and insitu phenomena which were not reflected by the model exercises are discussed. Based on the conclusions from this study, testing and modeling requirements for dynamic loading situations are proposed.

  18. Data based identification and prediction of nonlinear and complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  19. Clustering of time-evolving scaling dynamics in a complex signal.

    PubMed

    Saghir, Hamidreza; Chau, Tom; Kushki, Azadeh

    2016-07-01

    Complex time series are widespread in physics and physiology. Multifractal analysis provides a tool to study the scaling dynamics of such time series. However, the temporal evolution of scaling dynamics has been ignored by traditional tools such as the multifractal spectrum. We present scaling maps that add the time dimension to the study of scaling dynamics. This is particularly important in cases in which the dynamics of the underlying processes change in time or in applications that necessitate real-time detection of scaling dynamics. In addition, we present a methodology for automatic clustering of existing scaling regimes in a signal. We demonstrate the methodology on time-evolving correlated and uncorrelated noise and the output of a physiological control system (i.e., cardiac interbeat intervals) in healthy and pathological states. PMID:27575136

  20. Clustering of time-evolving scaling dynamics in a complex signal

    NASA Astrophysics Data System (ADS)

    Saghir, Hamidreza; Chau, Tom; Kushki, Azadeh

    2016-07-01

    Complex time series are widespread in physics and physiology. Multifractal analysis provides a tool to study the scaling dynamics of such time series. However, the temporal evolution of scaling dynamics has been ignored by traditional tools such as the multifractal spectrum. We present scaling maps that add the time dimension to the study of scaling dynamics. This is particularly important in cases in which the dynamics of the underlying processes change in time or in applications that necessitate real-time detection of scaling dynamics. In addition, we present a methodology for automatic clustering of existing scaling regimes in a signal. We demonstrate the methodology on time-evolving correlated and uncorrelated noise and the output of a physiological control system (i.e., cardiac interbeat intervals) in healthy and pathological states.

  1. Balance between noise and information flow maximizes set complexity of network dynamics.

    PubMed

    Mäki-Marttunen, Tuomo; Kesseli, Juha; Nykter, Matti

    2013-01-01

    Boolean networks have been used as a discrete model for several biological systems, including metabolic and genetic regulatory networks. Due to their simplicity they offer a firm foundation for generic studies of physical systems. In this work we show, using a measure of context-dependent information, set complexity, that prior to reaching an attractor, random Boolean networks pass through a transient state characterized by high complexity. We justify this finding with a use of another measure of complexity, namely, the statistical complexity. We show that the networks can be tuned to the regime of maximal complexity by adding a suitable amount of noise to the deterministic Boolean dynamics. In fact, we show that for networks with Poisson degree distributions, all networks ranging from subcritical to slightly supercritical can be tuned with noise to reach maximal set complexity in their dynamics. For networks with a fixed number of inputs this is true for near-to-critical networks. This increase in complexity is obtained at the expense of disruption in information flow. For a large ensemble of networks showing maximal complexity, there exists a balance between noise and contracting dynamics in the state space. In networks that are close to critical the intrinsic noise required for the tuning is smaller and thus also has the smallest effect in terms of the information processing in the system. Our results suggest that the maximization of complexity near to the state transition might be a more general phenomenon in physical systems, and that noise present in a system may in fact be useful in retaining the system in a state with high information content. PMID:23516395

  2. Molecular Basis for the Dissociation Dynamics of Protein A-Immunoglobulin G1 Complex

    PubMed Central

    Liu, Fu-Feng; Huang, Bo; Dong, Xiao-Yan; Sun, Yan

    2013-01-01

    Staphylococcus aureus protein A (SpA) is the most popular affinity ligand for immunoglobulin G1 (IgG1). However, the molecular basis for the dissociation dynamics of SpA-IgG1 complex is unclear. Herein, coarse-grained (CG) molecular dynamics (MD) simulations with the Martini force field were used to study the dissociation dynamics of the complex. The CG-MD simulations were first verified by the agreement in the structural and interactional properties of SpA and human IgG1 (hIgG1) in the association process between the CG-MD and all-atom MD at different NaCl concentrations. Then, the CG-MD simulation studies focused on the molecular insight into the dissociation dynamics of SpA-hIgG1 complex at pH 3.0. It is found that there are four steps in the dissociation process of the complex. First, there is a slight conformational adjustment of helix II in SpA. This is followed by the phenomena that the electrostatic interactions provided by the three hot spots (Glu143, Arg146 and Lys154) of helix II of SpA break up, leading to the dissociation of helix II from the binding site of hIgG1. Subsequently, breakup of the hydrophobic interactions between helix I (Phe132, Tyr133 and His137) in SpA and hIgG1 occurs, resulting in the disengagement of helix I from its binding site of hIgG1. Finally, the non-specific interactions between SpA and hIgG1 decrease slowly till disappearance, leading to the complete dissociation of the SpA-hIgG1 complex. This work has revealed that CG-MD coupled with the Martini force field is an effective method for studying the dissociation dynamics of protein-protein complex. PMID:23776704

  3. Molecular dynamics of the P450cam-Pdx complex reveals complex stability and novel interface contacts.

    PubMed

    Hollingsworth, Scott A; Poulos, Thomas L

    2015-01-01

    Cytochrome P450cam catalyzes the stereo and regiospecific hydroxylation of camphor to 5-exo-hydroxylcamphor. The two electrons for the oxidation of camphor are provided by putidaredoxin (Pdx), a Fe2 S2 containing protein. Two recent crystal structures of the P450cam-Pdx complex, one solved with the aid of covalent cross-linking and one without, have provided a structural picture of the redox partner interaction. To study the stability of the complex structure and the minor differences between the recent crystal structures, a 100 nanosecond molecular dynamics (MD) simulation of the cross-linked structure, mutated in silico to wild type and the linker molecule removed, was performed. The complex was stable over the course of the simulation though conformational changes including the movement of the C helix of P450cam further toward Pdx allowed for the formation of a number of new contacts at the complex interface that remained stable throughout the simulation. While several minor crystal contacts were lost in the simulation, all major contacts that had been experimentally studied previously were maintained. The equilibrated MD structure contained a mixture of contacts resembling both the cross-linked and noncovalent structures and the newly identified interactions. Finally, the reformation of the P450cam Asp251-Arg186 ion pair in the MD simulation mirrors the ion pair observed in the more promiscuous CYP101D1 and suggests that the Asp251-Arg186 ion pair may be important. PMID:25307478

  4. Mood states modulate complexity in heartbeat dynamics: A multiscale entropy analysis

    NASA Astrophysics Data System (ADS)

    Valenza, G.; Nardelli, M.; Bertschy, G.; Lanata, A.; Scilingo, E. P.

    2014-07-01

    This paper demonstrates that heartbeat complex dynamics is modulated by different pathological mental states. Multiscale entropy analysis was performed on R-R interval series gathered from the electrocardiogram of eight bipolar patients who exhibited mood states among depression, hypomania, and euthymia, i.e., good affective balance. Three different methodologies for the choice of the sample entropy radius value were also compared. We show that the complexity level can be used as a marker of mental states being able to discriminate among the three pathological mood states, suggesting to use heartbeat complexity as a more objective clinical biomarker for mental disorders.

  5. Hydration shell effects in the relaxation dynamics of photoexcited Fe-II complexes in water

    SciTech Connect

    Nalbach, P.; Achner, A. J. A.; Frey, M.; Grosser, M.; Thorwart, M.; Bressler, C.

    2014-07-28

    We study the relaxation dynamics of photoexcited Fe-II complexes dissolved in water and identify the relaxation pathway which the molecular complex follows in presence of a hydration shell of bound water at the interface between the complex and the solvent. Starting from a low-spin state, the photoexcited complex can reach the high-spin state via a cascade of different possible transitions involving electronic as well as vibrational relaxation processes. By numerically exact path integral calculations for the relaxational dynamics of a continuous solvent model, we find that the vibrational life times of the intermittent states are of the order of a few ps. Since the electronic rearrangement in the complex occurs on the time scale of about 100 fs, we find that the complex first rearranges itself in a high-spin and highly excited vibrational state, before it relaxes its energy to the solvent via vibrational relaxation transitions. By this, the relaxation pathway can be clearly identified. We find that the life time of the vibrational states increases with the size of the complex (within a spherical model), but decreases with the thickness of the hydration shell, indicating that the hydration shell acts as an additional source of fluctuations.

  6. Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

    ERIC Educational Resources Information Center

    Marek, Michael W.; Wu, Wen-Chi Vivian

    2014-01-01

    This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

  7. Revisiting geometrical shock dynamics for blast wave propagation in complex environment

    NASA Astrophysics Data System (ADS)

    Ridoux, J.; Lardjane, N.; Gomez, T.; Coulouvrat, F.

    2015-10-01

    A new fast-running model for blast wave propagation in air is described. This model is an extension of Whitham's Geometrical Shock Dynamics with specific closure to non sustained shock waves. The numerical procedure relies on a Cartesian fast-marching like algorithm with immersed boundary method for complex boundaries. Comparison to academic results underline the capacity of this model.

  8. Modelling Complex Systems by Integration of Agent-Based and Dynamical Systems Models

    NASA Astrophysics Data System (ADS)

    Bosse, Tibor; Sharpanskykh, Alexei; Treur, Jan

    Existing models for complex systems are often based on quantitative, numerical methods such as Dynamical Systems Theory (DST) [Port and Gelder 1995]. Such approaches often use numerical variables to describe global aspects and specify how they affect each other over time. An advantage of such approaches is that numerical approximation methods and software are available for simulation.

  9. Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments

    ERIC Educational Resources Information Center

    Osman, Magda

    2010-01-01

    Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research…

  10. Embracing Connectedness and Change: A Complex Dynamic Systems Perspective for Applied Linguistic Research

    ERIC Educational Resources Information Center

    Cameron, Lynne

    2015-01-01

    Complex dynamic systems (CDS) theory offers a powerful metaphorical model of applied linguistic processes, allowing holistic descriptions of situated phenomena, and addressing the connectedness and change that often characterise issues in our field. A recent study of Kenyan conflict transformation illustrates application of a CDS perspective. Key…

  11. Detection of NAD(P)H-dependent enzyme activity with dynamic luminescence quenching of terbium complexes.

    PubMed

    Ito, Hiroki; Terai, Takuya; Hanaoka, Kenjiro; Ueno, Tasuku; Komatsu, Toru; Nagano, Tetsuo; Urano, Yasuteru

    2015-05-14

    We discovered that positively charged terbium complexes bearing 1,4,7,10-tetraazacyclododecane functionalized with amide ligands are highly sensitive to dynamic luminescence quenching by NAD(P)H. We exploited this phenomenon to establish a general time-resolved luminescence-based assay platform for sensitive detection of NAD(P)H-dependent enzyme activities. PMID:25879812

  12. Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

    SciTech Connect

    Jin, R; McCallen, S; Almaas, E

    2007-05-28

    Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motif mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.

  13. Phase Transitions in Development of Writing Fluency from a Complex Dynamic Systems Perspective

    ERIC Educational Resources Information Center

    Baba, Kyoko; Nitta, Ryo

    2014-01-01

    This study explored patterns in L2 writing development by focusing on one of the linguistic features of texts (fluency) from a complex dynamic systems perspective. It investigated whether two English-as-a-foreign-language university students would experience discontinuous change (phase transition) in their writing fluency through repetition of a…

  14. Focusing on the Complexity of Emotion Issues in Academic Learning: A Dynamical Component Systems Approach

    ERIC Educational Resources Information Center

    Eynde, Peter Op 't; Turner, Jeannine E.

    2006-01-01

    Understanding the interrelations among students' cognitive, emotional, motivational, and volitional processes is an emergening focus in educational psychology. A dynamical, component systems theory of emotions is presented as a promising framework to further unravel these complex interrelations. This framework considers emotions to be a process…

  15. Fundamental properties of soils for complex dynamic loadings. Development of a three invariant constitutive model

    NASA Astrophysics Data System (ADS)

    Merkle, D. H.; Dass, W. C.

    1985-04-01

    This study sought to develop a general soil stress-strain model which can be used to solve a wide range of soil dynamics problems. The approach used was to review existing soil constitutive models used to predict the response of soil masses to complex dynamic loads, and then formulate a new model for that purpose. Eight existing soil dynamic stress-strain models were studied. The Lade model was selected as the best point of departure for developing a new soil stress-strain model for complex dynamic loading, because of its accuracy and flexibility in representing soil stress-strain behavior, ease of parameter determination, and ease of developing intuition for parameter physical significance and accuracy. The new conic model is so called because its principal mathematical surfaces are conic sections. The computer code used to exercise all nine soil constitutive models under eleven stress and strain paths is called the Soil Element Model (SEM). It can be incorporated in large finite difference or finite element codes for analyzing the response of soil masses to complex dynamic loads. The conic model performs well over a wide range of loading conditions. The parameters are determined in a straightforward manner, and the model reflects the influence of the intermediate principal stress on shear strength through a shear failure surface involving three independent stress invariants: the first total stress invariant and the second and third deviator stress invariants.

  16. Coarse-Grained Molecular Dynamics: Dissipation Due to Internal Modes

    SciTech Connect

    Rudd, R E

    2001-12-21

    We describe progress on the issue of pathological elastic wave reflection in atomistic and multiscale simulation. First we briefly review Coarse-Grained Molecular Dynamics (CGMD). Originally CGMD was formulated as a Hamiltonian system in which energy is conserved. This formulation is useful for many applications, but recently CGMD has been extended to include generalized Langevin forces. Here we describe how Langevin dynamics arise naturally in CGMD, and we examine the implication for elastic wave scattering.

  17. Morphological study of dynamic culture of thermosensitive collagen hydrogel in constructing tissue engineering complex.

    PubMed

    Huang, Lanfeng; Xu, Feixiang; Guo, Bin; Ma, Jianchao; Zhao, Jinsong

    2016-07-01

    ABSTACT The purpose of this study is to research the morphologies and functional characteristics of the cell-scaffold complex in vitro constructed under dynamic culture conditions. BMSCs were isolated from the long bones of Fischer344 rats, and performed in vitro amplification to the third generation as seed cells, together with thermosensitive collagen hydrogel (TCH) as cell adhesion matrix, and poly-L-lactic acid (PLLA) as scaffold, to construct cell-scaffold complex. The cell-scaffold complexes in the experiment group and the control group were then performed dynamic culture and static culture. After 7 d of in vitro culture, the complexes in the 2 groups were performed gross observation and SEM; meanwhile, the total DNA content in the complex was detected on D0,1,3, and 7 of culture. After cultured using these 2 ways, collagen could both wrap the PLLA scaffold, forming dense film-like structures on the PLLA surface. The total DNA contents in the cell-scaffold complex of the experiment group on D1,3, and 7 were significantly higher than the control group (P < 0.05). Compared with D0, the total DNA contents on D1,3, and 7 in both groups were gradually increased, but only the total DNA contents on D7 showed statistically significant difference than D0 (P < 0.05). TCH -PLLA fiber joint-constructed complex extracellular matrix had good biocompatibility, and dynamic culture could promote the distribution of BMSCs on the surface and inside the structure, thus promoting cell proliferation, so it could be used for the in vitro construction of tissue engineering complex. PMID:27459597

  18. Game Theory and Extremal Optimization for Community Detection in Complex Dynamic Networks

    PubMed Central

    Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

    2014-01-01

    The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach. PMID:24586257

  19. Molecular basis of the dynamic structure of the TIM23 complex in the mitochondrial intermembrane space.

    PubMed

    Bajaj, Rakhi; Jaremko, Łukasz; Jaremko, Mariusz; Becker, Stefan; Zweckstetter, Markus

    2014-10-01

    The presequence translocase TIM23 is a highly dynamic complex in which its subunits can adopt multiple conformations and undergo association-dissociation to facilitate import of proteins into mitochondria. Despite the importance of protein-protein interactions in TIM23, little is known about the molecular details of these processes. Using nuclear magnetic resonance spectroscopy, we characterized the dynamic interaction network of the intermembrane space domains of Tim23, Tim21, Tim50, and Tom22 at single-residue level. We show that Tim23(IMS) contains multiple sites to efficiently interact with the intermembrane space domain of Tim21 and to bind to Tim21, Tim50, and Tom22. In addition, we reveal the atomic details of the dynamic Tim23(IMS)-Tim21(IMS) complex. The combined data support a central role of the intermembrane space domain of Tim23 in the formation and regulation of the presequence translocase. PMID:25263020

  20. Probing excited state charge transfer dynamics in a heteroleptic ruthenium complex.

    PubMed

    Ghosh, Rajib; Palit, Dipak K

    2014-01-01

    Dynamics of metal to ligand charge transfer in the excited states of ruthenium polypyridyl complexes, which have shown promise as materials for artificial solar energy harvesting, has been of immense interest recently. Mixed ligand complexes are especially important for broader absorption in the visible region. Dynamics of ultrafast vibrational energy relaxation and inter-ligand charge transfer processes in the excited states of a heteroleptic ruthenium complex, [Ru(bpy)2(pap)](ClO4)2 (where bpy is 2,2'-bipyridine and pap is 2-(phenylazo)pyridine) have been investigated using femtosecond to nanosecond time-resolved transient absorption spectroscopic techniques. A good agreement between the TA spectrum of the lowest excited (3)MLCT state of [Ru(bpy)2(pap)](ClO4)2 complex and the anion radical spectrum of the pap ligand, which has been generated using the pulse radiolysis technique, confirmed the charge localization at the pap ligand. While the lifetime of the inter-ligand charge transfer from the bpy to the pap ligand in the (3)MLCT state is about 2.5 ps, vibrational cooling of the pap-localized(3)MLCT state occurs over a much longer time scale with a lifetime of about 35 ps. Ultrafast charge localization dynamics observed here may have important consequences in artificial solar energy harvesting systems, which employ heteroleptic ruthenium complexes. PMID:24247908