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dynamical network

Po-Jen Hsu, Kun-Lin Ho, Sheng-Hsien Lin, Jer-Lai Kuo
The potential energy surface (PES), structures and thermal properties of methanol clusters (MeOH)n with n = 8-15 were explored by replica-exchange molecular dynamics (REMD) simulations with an empirical model and refined using density functional theory (DFT) methods. For a given size, local minima structures were sampled from REMD trajectories and archived by a newly developed molecular database via a two-stage clustering algorithm (TSCA). Our TSCA utilizes both the topology of O-HO hydrogen bonding networks and the similarity of the shapes to filter out duplicates...
December 2, 2016: Physical Chemistry Chemical Physics: PCCP
Shmma Quraishe, Megan Sealey, Louise Cranfield, Amritpal Mudher
The microtubule cytoskeleton is a highly dynamic, filamentous network underpinning cellular structure and function. In Alzheimer's disease, the microtubule cytoskeleton is compromised, leading to neuronal dysfunction and eventually cell death. There are currently no disease-modifying therapies to slow down or halt disease progression. However, microtubule stabilisation is a promising therapeutic strategy that is being explored. We previously investigated the disease-modifying potential of a microtubule-stabilising peptide NAP (NAPVSIPQ) in a well-established Drosophila model of tauopathy characterised by microtubule breakdown and axonal transport deficits...
December 2, 2016: Scientific Reports
Lei Gao, Wei Wang, Liming Pan, Ming Tang, Hai-Feng Zhang
Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets...
December 2, 2016: Scientific Reports
Yanan Yu, Zhong Wang, Yongyan Wang
Advances in identifying architecture of modules and elucidating their modes of action are gradually improving the decoding of complex relationships between phenotypic robustness and genotypic networks. However, approaches to detecting modules have largely focused on identifying modules in static graphs. In this review, we attempt to reveal the mechanism of polyphyletic architectural transformation based on modular boundary evolutions and different oscillating factors. With the rapid progress in probing into the detailed structural model of modular networks, flexible modular organization manifests a key adaptive balancing ability of allosterically regulating or reconstructing intermodular and intramodular states to uncover the novel biological alterations beyond engineering properties...
2016: Critical Reviews in Eukaryotic Gene Expression
Horacio G Rotstein
The generation of intrinsic subthreshold (membrane potential) oscillations (STOs) in neuronal models requires the interaction between two processes: a relatively fast positive feedback that favors changes in voltage and a slower negative feedback that opposes these changes. These are provided by the so-called resonant and amplifying gating variables associated to the participating ionic currents. We investigate both the biophysical and dynamic mechanisms of generation of STOs and how their attributes (frequency and amplitude) depend on the model parameters for biophysical (conductance-based) models having qualitatively different types of resonant currents (activating and inactivating) and an amplifying current...
December 1, 2016: Journal of Computational Neuroscience
Yanmei Wang, Yan Ding, Jin-Yuan Liu
Plant microRNAs (miRNAs) have been shown to play essential roles in the regulation of gene expression. In this study, small RNA deep sequencing was applied to explore novel miRNAs expressed in elongating cotton fibers. A total of 46 novel and 96 known miRNAs, primarily derived from the corresponding specific loci in genome of Gossypium arboreum, were identified. 64 miRNAs were shown to be differentially expressed during the fiber elongation process; 16 were predicted to be novel miRNAs while the remaining 48 belong to known miRNA families...
2016: Frontiers in Plant Science
Emil Rindom, Kristian Vissing
Loss of skeletal muscle myofibrillar protein with disease and/or inactivity can severely deteriorate muscle strength and function. Strategies to counteract wasting of muscle myofibrillar protein are therefore desirable and invite for considerations on the potential superiority of specific modes of resistance exercise and/or the adequacy of low load resistance exercise regimens as well as underlying mechanisms. In this regard, delineation of the potentially mechanosensitive molecular mechanisms underlying muscle protein synthesis (MPS), may contribute to an understanding on how differentiated resistance exercise can transduce a mechanical signal into stimulation of muscle accretion...
2016: Frontiers in Physiology
Christian Jarvers, Tobias Brosch, André Brechmann, Marie L Woldeit, Andreas L Schulz, Frank W Ohl, Marcel Lommerzheim, Heiko Neumann
Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears...
2016: Frontiers in Neuroscience
Per Sebastian Skardal, Dane Taylor, Jie Sun, Alex Arenas
We study the dynamics of network-coupled phase oscillators in the presence of coupling frustration. It was recently demonstrated that in heterogeneous network topologies, the presence of coupling frustration causes perfect phase synchronization to become unattainable even in the limit of infinite coupling strength. Here, we consider the important case of heterogeneous coupling functions and extend previous results by deriving analytical predictions for the total erosion of synchronization. Our analytical results are given in terms of basic quantities related to the network structure and coupling frustration...
June 1, 2016: Physica D. Nonlinear Phenomena
Christina B Young, Gal Raz, Daphne Everaerd, Christian F Beckmann, Indira Tendolkar, Talma Hendler, Guillén Fernández, Erno J Hermans
: The ability to temporarily prioritize rapid and vigilant reactions over slower higher-order cognitive functions is essential for adaptive responding to threat. This reprioritization is believed to reflect shifts in resource allocation between large-scale brain networks that support these cognitive functions, including the salience and executive control networks. How changes in communication within and between such networks dynamically unfold as a function of threat-related arousal, however, remains unknown...
December 1, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Y Zhang, R Ashcraft, M I Mendelev, C Z Wang, K F Kelton
The state-of-the-art experimental and atomistic simulation techniques were utilized to study the structure of the liquid and amorphous Ni62Nb38 alloy. First, the ab initio molecular dynamics (AIMD) simulation was performed at rather high temperature where the time limitations of the AIMD do not prevent to reach the equilibrium liquid structure. A semi-empirical potential of the Finnis-Sinclair (FS) type was developed to almost exactly reproduce the AIMD partial pair correlation functions (PPCFs) in a classical molecular dynamics simulation...
November 28, 2016: Journal of Chemical Physics
Prithwish K Nandi, Zdenek Futera, Niall J English
Given the fundamental role of water in governing the biochemistry of enzymes, and in regulating their wider biological activity (e.g., by local water concentration surrounding biomolecules), the influence of extraneous electric and electromagnetic (e/m) fields thereon is of central relevance to biophysics and, more widely, biology. With the increase in levels of local and atmospheric microwave-frequency radiation present in modern life, as well as other electric-field exposure, the impact upon hydration-water layers surrounding proteins, and biomolecules generally, becomes a particularly pertinent issue...
November 28, 2016: Journal of Chemical Physics
Martin Cenek, Spencer K Dahl
Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution...
November 2016: Chaos
Igor V Belykh, Maurizio Porfiri
This focus issue presents a collection of research papers from a broad spectrum of topics related to the modeling, analysis, and control of mechanical oscillators and beyond. Examples covered in this focus issue range from bridges and mechanical pendula to self-organizing networks of dynamic agents, with application to robotics and animal grouping. This focus issue brings together applied mathematicians, physicists, and engineers to address open questions on various theoretical and experimental aspects of collective dynamics phenomena and their control...
November 2016: Chaos
Murielle Vanessa Tchakui, Paul Woafo
This work deals with the dynamics of three unidirectionally coupled Duffing oscillators and that of three coupled piezoelectric actuators, considering the special case of inchworm motors. Two configurations of the network are studied: ring configuration and chain configuration. The effects of the coupling coefficient and the time delay are analyzed through different bifurcation diagrams and phase difference variation. It is shown that varying the coupling coefficient and the time delay leads to the appearance of different dynamical behaviors: steady states, periodic and quasiperiodic oscillations, chaos, and phase synchronization...
November 2016: Chaos
Dawid Dudkowski, Yuri Maistrenko, Tomasz Kapitaniak
We studied the phenomenon of chimera states in networks of non-locally coupled externally excited oscillators. Units of the considered networks are bi-stable, having two co-existing attractors of different types (chaotic and periodic). The occurrence of chimeras is discussed, and the influence of coupling radius and coupling strength on their co-existence is analyzed (including typical bifurcation scenarios). We present a statistical analysis and investigate sensitivity of the probability of observing chimeras to the initial conditions and parameter values...
November 2016: Chaos
M Hyong Koh, Rifat Sipahi
Dynamics of many multi-agent systems is influenced by communication/activation delays τ. In the presence of delays, there exists a certain margin called the delay margin τ(*), less than which system stability holds. This margin depends strongly on agents' dynamics and the agent network. In this article, three key elements, namely, the delay margin, network graph, and a distance threshold conditioning two agents' connectivity are considered in a multi-agent consensus dynamics under delay τ. We report that when the dynamics is unstable under this delay, its states can be naturally bounded, even for arbitrarily large threshold values, preventing agents to disperse indefinitely...
November 2016: Chaos
Arturo Buscarino, Luigi Fortuna, Mattia Frasca, Salvatore Frisenna
In this paper, we study synchronization in time-varying networks inherited by the Vicsek's model of self-propelled particles. In our model, each particle/agent moves in a two dimensional space according to the Vicsek's rules and is associated to a chaotic system. The dynamics of two oscillators are coupled with each other only when agents are at a distance less than an interaction radius. We investigate the system behavior with respect to some fundamental parameters, and, in particular, to the noise level, which for increasing intensity drives the system from an ordered motion to a disordered one...
November 2016: Chaos
Subhradeep Roy, Nicole Abaid
In this work, we study leader-follower consensus and synchronization protocols over a stochastically switching network. The agents representing the followers can communicate with any other agent, whereas the agents serving as leaders are restricted to interact only with the other leaders. The model incorporates the phenomenon of numerosity, which limits the perceptual capacity of the agents while allowing for shuffling with whom each individual interacts at each time step. We derive closed form expressions for necessary and sufficient conditions for consensus, the rate of convergence to consensus, and conditions for stochastic synchronization in terms of the asymptotic convergence factor...
November 2016: Chaos
Daniel Alberto Burbano Lombana, Mario di Bernardo
In this paper, we address the problem of achieving synchronization in networks of nonlinear units coupled by dynamic diffusive terms. We present two types of couplings consisting of a static linear term, corresponding to the diffusive coupling, and a dynamic term which can be either the integral or the derivative of the sum of the mismatches between the states of neighbouring agents. The resulting dynamic coupling strategy is a distributed proportional-integral (PI) or a proportional-derivative (PD) law that is shown to be effective in improving the network synchronization performance, for example, when the dynamics at nodes are nonidentical...
November 2016: Chaos
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