Surfactant mediated polyelectrolyte self-assembly

DOE PAGES

Goswami, Monojoy; Borreguero Calvo, Jose M.; Pincus, Phillip A.; ...

2015-11-25

Self-assembly and dynamics of polyelectrolyte (PE) surfactant complex (PES) is investigated using molecular dynamics simulations. The complexation is systematically studied for five different PE backbone charge densities. At a fixed surfactant concentration the PES complexation exhibits pearl-necklace to agglomerated double spherical structures with a PE chain decorating the surfactant micelles. The counterions do not condense on the complex, but are released in the medium with a random distribution. The relaxation dynamics for three different length scales, polymer chain, segmental and monomer, show distinct features of the charge and neutral species; the counterions are fastest followed by the PE chain andmore » surfactants. The surfactant heads and tails have the slowest relaxation due to their restricted movement inside the agglomerated structure. At the shortest length scale, all the charge and neutral species show similar relaxation dynamics confirming Rouse behavior at monomer length scales. Overall, the present study highlights the structure-property relationship for polymer-surfactant complexation. These results will help improve the understanding of PES complex and should aid in the design of better materials for future applications.« less

Molecular dynamics study of thermodynamic stability and dynamics of [Li(glyme)]+ complex in lithium-glyme solvate ionic liquids

NASA Astrophysics Data System (ADS)

Shinoda, Wataru; Hatanaka, Yuta; Hirakawa, Masashi; Okazaki, Susumu; Tsuzuki, Seiji; Ueno, Kazuhide; Watanabe, Masayoshi

2018-05-01

Equimolar mixtures of glymes and organic lithium salts are known to produce solvate ionic liquids, in which the stability of the [Li(glyme)]+ complex plays an important role in determining the ionic dynamics. Since these mixtures have attractive physicochemical properties for application as electrolytes, it is important to understand the dependence of the stability of the [Li(glyme)]+ complex on the ion dynamics. A series of microsecond molecular dynamics simulations has been conducted to investigate the dynamic properties of these solvate ionic liquids. Successful solvate ionic liquids with high stability of the [Li(glyme)]+ complex have been shown to have enhanced ion dynamics. Li-glyme pair exchange rarely occurs: its characteristic time is longer than that of ion diffusion by one or two orders of magnitude. Li-glyme pair exchange most likely occurs through cluster formation involving multiple [Li(glyme)]+ pairs. In this process, multiple exchanges likely take place in a concerted manner without the production of energetically unfavorable free glyme or free Li+ ions.

A quantum dynamical study of the rotation of the dihydrogen ligand in the Fe(H)2(H2)(PEtPh2)3 coordination complex.

PubMed

Gonzalez, Megan E; Eckert, Juergen; Aquino, Adelia J A; Poirier, Bill

2018-04-21

Progress in the hydrogen fuel field requires a clear understanding and characterization of how materials of interest interact with hydrogen. Due to the inherently quantum mechanical nature of hydrogen nuclei, any theoretical studies of these systems must be treated quantum dynamically. One class of material that has been examined in this context are dihydrogen complexes. Since their discovery by Kubas in 1984, many such complexes have been studied both experimentally and theoretically. This particular study examines the rotational dynamics of the dihydrogen ligand in the Fe(H) 2 (H 2 )(PEtPh 2 ) 3 complex, allowing for full motion in both the rotational degrees of freedom and treating the quantum dynamics (QD) explicitly. A "gas-phase" global potential energy surface is first constructed using density functional theory with the Becke, 3-parameter, Lee-Yang-Parr functional; this is followed by an exact QD calculation of the corresponding rotation/libration states. The results provide insight into the dynamical correlation of the two rotation angles as well as a comprehensive analysis of both ground- and excited-state librational tunneling splittings. The latter was computed to be 6.914 cm -1 -in excellent agreement with the experimental value of 6.4 cm -1 . This work represents the first full-dimensional ab initio exact QD calculation ever performed for dihydrogen ligand rotation in a coordination complex.

A quantum dynamical study of the rotation of the dihydrogen ligand in the Fe(H)2(H2)(PEtPh2)3 coordination complex

NASA Astrophysics Data System (ADS)

Gonzalez, Megan E.; Eckert, Juergen; Aquino, Adelia J. A.; Poirier, Bill

2018-04-01

Progress in the hydrogen fuel field requires a clear understanding and characterization of how materials of interest interact with hydrogen. Due to the inherently quantum mechanical nature of hydrogen nuclei, any theoretical studies of these systems must be treated quantum dynamically. One class of material that has been examined in this context are dihydrogen complexes. Since their discovery by Kubas in 1984, many such complexes have been studied both experimentally and theoretically. This particular study examines the rotational dynamics of the dihydrogen ligand in the Fe(H)2(H2)(PEtPh2)3 complex, allowing for full motion in both the rotational degrees of freedom and treating the quantum dynamics (QD) explicitly. A "gas-phase" global potential energy surface is first constructed using density functional theory with the Becke, 3-parameter, Lee-Yang-Parr functional; this is followed by an exact QD calculation of the corresponding rotation/libration states. The results provide insight into the dynamical correlation of the two rotation angles as well as a comprehensive analysis of both ground- and excited-state librational tunneling splittings. The latter was computed to be 6.914 cm-1—in excellent agreement with the experimental value of 6.4 cm-1. This work represents the first full-dimensional ab initio exact QD calculation ever performed for dihydrogen ligand rotation in a coordination complex.

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

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…

Modeling and complexity of stochastic interacting Lévy type financial price dynamics

NASA Astrophysics Data System (ADS)

Wang, Yiduan; Zheng, Shenzhou; Zhang, Wei; Wang, Jun; Wang, Guochao

2018-06-01

In attempt to reproduce and investigate nonlinear dynamics of security markets, a novel nonlinear random interacting price dynamics, which is considered as a Lévy type process, is developed and investigated by the combination of lattice oriented percolation and Potts dynamics, which concerns with the instinctive random fluctuation and the fluctuation caused by the spread of the investors' trading attitudes, respectively. To better understand the fluctuation complexity properties of the proposed model, the complexity analyses of random logarithmic price return and corresponding volatility series are preformed, including power-law distribution, Lempel-Ziv complexity and fractional sample entropy. In order to verify the rationality of the proposed model, the corresponding studies of actual security market datasets are also implemented for comparison. The empirical results reveal that this financial price model can reproduce some important complexity features of actual security markets to some extent. The complexity of returns decreases with the increase of parameters γ1 and β respectively, furthermore, the volatility series exhibit lower complexity than the return series

Theorems and application of local activity of CNN with five state variables and one port.

PubMed

Xiong, Gang; Dong, Xisong; Xie, Li; Yang, Thomas

2012-01-01

Coupled nonlinear dynamical systems have been widely studied recently. However, the dynamical properties of these systems are difficult to deal with. The local activity of cellular neural network (CNN) has provided a powerful tool for studying the emergence of complex patterns in a homogeneous lattice, which is composed of coupled cells. In this paper, the analytical criteria for the local activity in reaction-diffusion CNN with five state variables and one port are presented, which consists of four theorems, including a serial of inequalities involving CNN parameters. These theorems can be used for calculating the bifurcation diagram to determine or analyze the emergence of complex dynamic patterns, such as chaos. As a case study, a reaction-diffusion CNN of hepatitis B Virus (HBV) mutation-selection model is analyzed and simulated, the bifurcation diagram is calculated. Using the diagram, numerical simulations of this CNN model provide reasonable explanations of complex mutant phenomena during therapy. Therefore, it is demonstrated that the local activity of CNN provides a practical tool for the complex dynamics study of some coupled nonlinear systems.

Force-Manipulation Single-Molecule Spectroscopy Studies of Enzymatic Dynamics

NASA Astrophysics Data System (ADS)

Lu, H. Peter; He, Yufan; Lu, Maolin; Cao, Jin; Guo, Qing

2014-03-01

Subtle conformational changes play a crucial role in protein functions, especially in enzymatic reactions involving complex substrate-enzyme interactions and chemical reactions. We applied AFM-enhanced and magnetic tweezers-correlated single-molecule spectroscopy to study the mechanisms and dynamics of enzymatic reactions involved with kinase and lysozyme proteins. Enzymatic reaction turnovers and the associated structure changes of individual protein molecules were observed simultaneously in real-time by single-molecule FRET detections. Our single-molecule spectroscopy measurements of enzymatic conformational dynamics have revealed time bunching effect and intermittent coherence in conformational state change dynamics involving in enzymatic reaction cycles. The coherent conformational state dynamics suggests that the enzymatic catalysis involves a multi-step conformational motion along the coordinates of substrate-enzyme complex formation and product releasing. Our results support a multiple-conformational state model, being consistent with a complementary conformation selection and induced-fit enzymatic loop-gated conformational change mechanism in substrate-enzyme active complex formation.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks.

PubMed

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks

NASA Astrophysics Data System (ADS)

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

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

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

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

2014-03-15

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

Complexity theory and physical unification: From microscopic to oscopic level

NASA Astrophysics Data System (ADS)

Pavlos, G. P.; Iliopoulos, A. C.; Karakatsanis, L. P.; Tsoutsouras, V. G.; Pavlos, E. G.

During the last two decades, low dimensional chaotic or self-organized criticality (SOC) processes have been observed by our group in many different physical systems such as space plasmas, the solar or the magnetospheric dynamics, the atmosphere, earthquakes, the brain activity as well as in informational systems. All these systems are complex systems living far from equilibrium with strong self-organization and phase transition character. The theoretical interpretation of these natural phenomena needs a deeper insight into the fundamentals of complexity theory. In this study, we try to give a synoptic description of complexity theory both at the microscopic and at the oscopic level of the physical reality. Also, we propose that the self-organization observed oscopically is a phenomenon that reveals the strong unifying character of the complex dynamics which includes thermodynamical and dynamical characteristics in all levels of the physical reality. From this point of view, oscopical deterministic and stochastic processes are closely related to the microscopical chaos and self-organization. In this study the scientific work of scientists such as Wilson, Nicolis, Prigogine, Hooft, Nottale, El Naschie, Castro, Tsallis, Chang and others is used for the development of a unified physical comprehension of complex dynamics from the microscopic to the oscopic level.

Heterogeneous Intracellular Trafficking Dynamics of Brain-Derived Neurotrophic Factor Complexes in the Neuronal Soma Revealed by Single Quantum Dot Tracking

PubMed Central

Vermehren-Schmaedick, Anke; Krueger, Wesley; Jacob, Thomas; Ramunno-Johnson, Damien; Balkowiec, Agnieszka; Lidke, Keith A.; Vu, Tania Q.

2014-01-01

Accumulating evidence underscores the importance of ligand-receptor dynamics in shaping cellular signaling. In the nervous system, growth factor-activated Trk receptor trafficking serves to convey biochemical signaling that underlies fundamental neural functions. Focus has been placed on axonal trafficking but little is known about growth factor-activated Trk dynamics in the neuronal soma, particularly at the molecular scale, due in large part to technical hurdles in observing individual growth factor-Trk complexes for long periods of time inside live cells. Quantum dots (QDs) are intensely fluorescent nanoparticles that have been used to study the dynamics of ligand-receptor complexes at the plasma membrane but the value of QDs for investigating ligand-receptor intracellular dynamics has not been well exploited. The current study establishes that QD conjugated brain-derived neurotrophic factor (QD-BDNF) binds to TrkB receptors with high specificity, activates TrkB downstream signaling, and allows single QD tracking capability for long recording durations deep within the soma of live neurons. QD-BDNF complexes undergo internalization, recycling, and intracellular trafficking in the neuronal soma. These trafficking events exhibit little time-synchrony and diverse heterogeneity in underlying dynamics that include phases of sustained rapid motor transport without pause as well as immobility of surprisingly long-lasting duration (several minutes). Moreover, the trajectories formed by dynamic individual BDNF complexes show no apparent end destination; BDNF complexes can be found meandering over long distances of several microns throughout the expanse of the neuronal soma in a circuitous fashion. The complex, heterogeneous nature of neuronal soma trafficking dynamics contrasts the reported linear nature of axonal transport data and calls for models that surpass our generally limited notions of nuclear-directed transport in the soma. QD-ligand probes are poised to provide understanding of how the molecular mechanisms underlying intracellular ligand-receptor trafficking shape cell signaling under conditions of both healthy and dysfunctional neurological disease models. PMID:24732948

Lexical Complexity Development from Dynamic Systems Theory Perspective: Lexical Density, Diversity, and Sophistication

ERIC Educational Resources Information Center

Kalantari, Reza; Gholami, Javad

2017-01-01

This longitudinal case study explored Iranian EFL learners' lexical complexity (LC) through the lenses of Dynamic Systems Theory (DST). Fifty independent essays written by five intermediate to advanced female EFL learners in a TOEFL iBT preparation course over six months constituted the corpus of this study. Three Coh-Metrix indices (Graesser,…

Dynamics in Complex Coacervates

NASA Astrophysics Data System (ADS)

Perry, Sarah

Understanding the dynamics of a material provides detailed information about the self-assembly, structure, and intermolecular interactions present in a material. While rheological methods have long been used for the characterization of complex coacervate-based materials, it remains a challenge to predict the dynamics for a new system of materials. Furthermore, most work reports only qualitative trends exist as to how parameters such as charge stoichiometry, ionic strength, and polymer chain length impact self-assembly and material dynamics, and there is little information on the effects of polymer architecture or the organization of charges within a polymer. We seek to link thermodynamic studies of coacervation phase behavior with material dynamics through a carefully-controlled, systematic study of coacervate linear viscoelasticity for different polymer chemistries. We couple various methods of characterizing the dynamics of polymer-based complex coacervates, including the time-salt superposition methods developed first by Spruijt and coworkers to establish a more mechanistic strategy for comparing the material dynamics and linear viscoelasticity of different systems. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support of this research.

Molecular organization and dynamics of micellar phase of polyelectrolyte-surfactant complexes: ESR spin probe study

NASA Astrophysics Data System (ADS)

Wasserman, A. M.; Kasaikin, V. A.; Zakharova, Yu. A.; Aliev, I. I.; Baranovsky, V. Yu.; Doseva, V.; Yasina, L. L.

2002-04-01

Molecular dynamics and organization of the micellar phase of complexes of linear polyelectrolytes with ionogenic and non-ionogenic surfactants was studied by the ESR spin probe method. Complexes of polyacrylic acid (PAA) and sodium polystyrenesulfonate (PSS) with alkyltrimethylammonium bromides (ATAB), as well as complexes of poly- N, N'-dimethyldiallylammonium chloride (PDACL) with sodium dodecylsulfate (SDS) were studied. The micellar phase of such complexes is highly organized molecular system, molecular ordering of which near the polymeric chain is much higher than in the 'center' of the micelle, it depends on the polymer-detergent interaction, flexibility of polymeric chain and length of carbonic part of the detergent molecule. Complexes of polymethacrylic acid (PMAA) with non-ionic detergent (dodecyl-substituted polyethyleneglycol), show that the local mobility of surfactant in such complexes is significantly lower than in 'free' micelles and depends on the number of micellar particles participating in formation of complexes.

Complexity in neuronal noise depends on network interconnectivity.

PubMed

Serletis, Demitre; Zalay, Osbert C; Valiante, Taufik A; Bardakjian, Berj L; Carlen, Peter L

2011-06-01

"Noise," or noise-like activity (NLA), defines background electrical membrane potential fluctuations at the cellular level of the nervous system, comprising an important aspect of brain dynamics. Using whole-cell voltage recordings from fast-spiking stratum oriens interneurons and stratum pyramidale neurons located in the CA3 region of the intact mouse hippocampus, we applied complexity measures from dynamical systems theory (i.e., 1/f(γ) noise and correlation dimension) and found evidence for complexity in neuronal NLA, ranging from high- to low-complexity dynamics. Importantly, these high- and low-complexity signal features were largely dependent on gap junction and chemical synaptic transmission. Progressive neuronal isolation from the surrounding local network via gap junction blockade (abolishing gap junction-dependent spikelets) and then chemical synaptic blockade (abolishing excitatory and inhibitory post-synaptic potentials), or the reverse order of these treatments, resulted in emergence of high-complexity NLA dynamics. Restoring local network interconnectivity via blockade washout resulted in resolution to low-complexity behavior. These results suggest that the observed increase in background NLA complexity is the result of reduced network interconnectivity, thereby highlighting the potential importance of the NLA signal to the study of network state transitions arising in normal and abnormal brain dynamics (such as in epilepsy, for example).

Bursting Transition Dynamics Within the Pre-Bötzinger Complex

NASA Astrophysics Data System (ADS)

Duan, Lixia; Chen, Xi; Tang, Xuhui; Su, Jianzhong

The pre-Bötzinger complex of the mammalian brain stem plays a crucial role in the respiratory rhythms generation. Neurons within the pre-Bötzinger complex have been found experimentally to yield different firing activities. In this paper, we study the spiking and bursting activities related to the respiratory rhythms in the pre-Bötzinger complex based on a mathematical model proposed by Butera. Using the one-dimensional first recurrence map induced by dynamics, we investigate the different bursting patterns and their transition of the pre-Bötzinger complex neurons based on the Butera model, after we derived a one-dimensional map from the dynamical characters of the differential equations, and we obtained conditions for the transition of different bursting patterns. These analytical results were verified through numerical simulations. We conclude that the one-dimensional map contains similar rhythmic patterns as the Butera model and can be used as a simpler modeling tool to study fast-slow models like pre-Bötzinger complex neural circuit.

Brain Dynamics: Methodological Issues and Applications in Psychiatric and Neurologic Diseases

NASA Astrophysics Data System (ADS)

Pezard, Laurent

The human brain is a complex dynamical system generating the EEG signal. Numerical methods developed to study complex physical dynamics have been used to characterize EEG since the mid-eighties. This endeavor raised several issues related to the specificity of EEG. Firstly, theoretical and methodological studies should address the major differences between the dynamics of the human brain and physical systems. Secondly, this approach of EEG signal should prove to be relevant for dealing with physiological or clinical problems. A set of studies performed in our group is presented here within the context of these two problematic aspects. After the discussion of methodological drawbacks, we review numerical simulations related to the high dimension and spatial extension of brain dynamics. Experimental studies in neurologic and psychiatric disease are then presented. We conclude that if it is now clear that brain dynamics changes in relation with clinical situations, methodological problems remain largely unsolved.

Using a Complexity Approach to Study the Interpersonal Dynamics in Teacher-­Student Interactions: A Case Study of Two Teachers

ERIC Educational Resources Information Center

Pennings, Helena J. M.

2017-01-01

In the present study, complex dynamic systems theory and interpersonal theory are combined to describe the teacher-student interactions of two teachers with different interpersonal styles. The aim was to show and explain the added value of looking at different steps in the analysis of behavioral time-series data (i.e., observations of teacher and…

Origin of Complexity in Multicellular Organisms

NASA Astrophysics Data System (ADS)

Furusawa, Chikara; Kaneko, Kunihiko

2000-06-01

Through extensive studies of dynamical system modeling cellular growth and reproduction, we find evidence that complexity arises in multicellular organisms naturally through evolution. Without any elaborate control mechanism, these systems can exhibit complex pattern formation with spontaneous cell differentiation. Such systems employ a ``cooperative'' use of resources and maintain a larger growth speed than simple cell systems, which exist in a homogeneous state and behave ``selfishly.'' The relevance of the diversity of chemicals and reaction dynamics to the growth of a multicellular organism is demonstrated. Chaotic biochemical dynamics are found to provide the multipotency of stem cells.

From globally coupled maps to complex-systems biology

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

Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp

Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.

Dynamical analysis of the global business-cycle synchronization

PubMed Central

2018-01-01

This paper reports the dynamical analysis of the business cycles of 12 (developed and developing) countries over the last 56 years by applying computational techniques used for tackling complex systems. They reveal long-term convergence and country-level interconnections because of close contagion effects caused by bilateral networking exposure. Interconnectivity determines the magnitude of cross-border impacts. Local features and shock propagation complexity also may be true engines for local configuration of cycles. The algorithmic modeling proves to represent a solid approach to study the complex dynamics involved in the world economies. PMID:29408909

Dynamical analysis of the global business-cycle synchronization.

PubMed

Lopes, António M; Tenreiro Machado, J A; Huffstot, John S; Mata, Maria Eugénia

2018-01-01

This paper reports the dynamical analysis of the business cycles of 12 (developed and developing) countries over the last 56 years by applying computational techniques used for tackling complex systems. They reveal long-term convergence and country-level interconnections because of close contagion effects caused by bilateral networking exposure. Interconnectivity determines the magnitude of cross-border impacts. Local features and shock propagation complexity also may be true engines for local configuration of cycles. The algorithmic modeling proves to represent a solid approach to study the complex dynamics involved in the world economies.

The sleeping brain as a complex system.

PubMed

Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas

2011-10-13

'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.

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

Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.

Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less

Impacts of large dams on the complexity of suspended sediment dynamics in the Yangtze River

NASA Astrophysics Data System (ADS)

Wang, Yuankun; Rhoads, Bruce L.; Wang, Dong; Wu, Jichun; Zhang, Xiao

2018-03-01

The Yangtze River is one of the largest and most important rivers in the world. Over the past several decades, the natural sediment regime of the Yangtze River has been altered by the construction of dams. This paper uses multi-scale entropy analysis to ascertain the impacts of large dams on the complexity of high-frequency suspended sediment dynamics in the Yangtze River system, especially after impoundment of the Three Gorges Dam (TGD). In this study, the complexity of sediment dynamics is quantified by framing it within the context of entropy analysis of time series. Data on daily sediment loads for four stations located in the mainstem are analyzed for the past 60 years. The results indicate that dam construction has reduced the complexity of short-term (1-30 days) variation in sediment dynamics near the structures, but that complexity has actually increased farther downstream. This spatial pattern seems to reflect a filtering effect of the dams on the on the temporal pattern of sediment loads as well as decreased longitudinal connectivity of sediment transfer through the river system, resulting in downstream enhancement of the influence of local sediment inputs by tributaries on sediment dynamics. The TGD has had a substantial impact on the complexity of sediment series in the mainstem of the Yangtze River, especially after it became fully operational. This enhanced impact is attributed to the high trapping efficiency of this dam and its associated large reservoir. The sediment dynamics "signal" becomes more spatially variable after dam construction. This study demonstrates the spatial influence of dams on the high-frequency temporal complexity of sediment regimes and provides valuable information that can be used to guide environmental conservation of the Yangtze River.

On Chaotic and Hyperchaotic Complex Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Mahmoud, Gamal M.

Dynamical systems described by real and complex variables are currently one of the most popular areas of scientific research. These systems play an important role in several fields of physics, engineering, and computer sciences, for example, laser systems, control (or chaos suppression), secure communications, and information science. Dynamical basic properties, chaos (hyperchaos) synchronization, chaos control, and generating hyperchaotic behavior of these systems are briefly summarized. The main advantage of introducing complex variables is the reduction of phase space dimensions by a half. They are also used to describe and simulate the physics of detuned laser and thermal convection of liquid flows, where the electric field and the atomic polarization amplitudes are both complex. Clearly, if the variables of the system are complex the equations involve twice as many variables and control parameters, thus making it that much harder for a hostile agent to intercept and decipher the coded message. Chaotic and hyperchaotic complex systems are stated as examples. Finally there are many open problems in the study of chaotic and hyperchaotic complex nonlinear dynamical systems, which need further investigations. Some of these open problems are given.

Effect of Rho-kinase inhibition on complexity of breathing pattern in a guinea pig model of asthma

PubMed Central

Pazhoohan, Saeed; Javan, Mohammad; Hajizadeh, Sohrab

2017-01-01

Asthma represents an episodic and fluctuating behavior characterized with decreased complexity of respiratory dynamics. Several evidence indicate that asthma severity or control is associated with alteration in variability of lung function. The pathophysiological basis of alteration in complexity of breathing pattern in asthma has remained poorly understood. Regarding the point that Rho-kinase is involved in pathophysiology of asthma, in present study we investigated the effect of Rho-kinase inhibition on complexity of respiratory dynamics in a guinea pig model of asthma. Male Dunkin Hartley guinea pigs were exposed to 12 series of inhalations with ovalbumin or saline. Animals were treated by the Rho-kinase inhibitor Y-27632 (1mM aerosols) prior to each allergen challenge. We recorded respiration of conscious animals using whole-body plethysmography. Exposure to ovalbumin induced lung inflammation, airway hyperresponsiveness and remodeling including goblet cell hyperplasia, increase in the thickness of airways smooth muscles and subepithelial collagen deposition. Complexity analysis of respiratory dynamics revealed a dramatic decrease in irregularity of respiratory rhythm representing less complexity in asthmatic guinea pigs. Inhibition of Rho-kinase reduced the airway remodeling and hyperreponsiveness, but had no significant effect on lung inflammation and complexity of respiratory dynamics in asthmatic animals. It seems that airway hyperresponsiveness and remodeling do not significantly affect the complexity of respiratory dynamics. Our results suggest that inflammation might be the probable cause of shift in the respiratory dynamics away from the normal fluctuation in asthma. PMID:29088265

Investigating the Structural Impacts of I64T and P311S Mutations in APE1-DNA Complex: A Molecular Dynamics Approach

PubMed Central

Doss, C. George Priya; NagaSundaram, N.

2012-01-01

Background Elucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA. Principal Findings In this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T) and rs1803120 (P311S) were taken further for structural analysis. Significance Different parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis. PMID:22384055

School Crisis Management: A Model of Dynamic Responsiveness to Crisis Life Cycle

ERIC Educational Resources Information Center

Liou, Yi-Hwa

2015-01-01

Purpose: This study aims to analyze a school's crisis management and explore emerging aspects of its response to a school crisis. Traditional linear modes of analysis often fail to address complex crisis situations. The present study applied a dynamic crisis life cycle model that draws on chaos and complexity theory to a crisis management case,…

Dynamic NMR of Intramolecular Exchange Processes in EDTA Complexes of Sc[superscript 3+], Y[superscript 3+], and La[superscript 3+

ERIC Educational Resources Information Center

Ba, Yong; Han, Steven; Ni, Lily; Su, Tony; Garcia, Andres

2006-01-01

Dynamic NMR makes use of the effect of chemical exchanges on NMR spectra to study kinetics and thermodynamics. An advanced physical chemistry lab experiment was developed to study the intramolecular exchange processes of EDTA (the disodium salt of ethylenediaminetetraacetic acid) metal complexes. EDTA is an important chelating agent, used in…

Hybrid function projective synchronization in complex dynamical networks

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

Wei, Qiang; Wang, Xing-yuan, E-mail: wangxy@dlut.edu.cn; 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.

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity.

PubMed

Frickel, Jens; Theodosiou, Loukas; Becks, Lutz

2017-10-17

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus-host and prey-predator) with a more complex three-species system (virus-host-predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host-virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host-virus coevolution in the complex system and that the virus' effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Part 3 Specialized aspects of GIS and spatial analysis . Garage band science and dynamic spatial models

NASA Astrophysics Data System (ADS)

Box, Paul W.

GIS and spatial analysis is suited mainly for static pictures of the landscape, but many of the processes that need exploring are dynamic in nature. Dynamic processes can be complex when put in a spatial context; our ability to study such processes will probably come with advances in understanding complex systems in general. Cellular automata and agent-based models are two prime candidates for exploring complex spatial systems, but are difficult to implement. Innovative tools that help build complex simulations will create larger user communities, who will probably find novel solutions for understanding complexity. A significant source for such innovations is likely to be from the collective efforts of hobbyists and part-time programmers, who have been dubbed ``garage-band scientists'' in the popular press.

New approaches to the analysis of complex samples using fluorescence lifetime techniques and organized media

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

Hertz, P.R.

Fluorescence spectroscopy is a highly sensitive and selective tool for the analysis of complex systems. In order to investigate the efficacy of several steady state and dynamic techniques for the analysis of complex systems, this work focuses on two types of complex, multicomponent samples: petrolatums and coal liquids. It is shown in these studies dynamic, fluorescence lifetime-based measurements provide enhanced discrimination between complex petrolatum samples. Additionally, improved quantitative analysis of multicomponent systems is demonstrated via incorporation of organized media in coal liquid samples. This research provides the first systematic studies of (1) multifrequency phase-resolved fluorescence spectroscopy for dynamic fluorescence spectralmore » fingerprinting of complex samples, and (2) the incorporation of bile salt micellar media to improve accuracy and sensitivity for characterization of complex systems. In the petroleum studies, phase-resolved fluorescence spectroscopy is used to combine spectral and lifetime information through the measurement of phase-resolved fluorescence intensity. The intensity is collected as a function of excitation and emission wavelengths, angular modulation frequency, and detector phase angle. This multidimensional information enhances the ability to distinguish between complex samples with similar spectral characteristics. Examination of the eigenvalues and eigenvectors from factor analysis of phase-resolved and steady state excitation-emission matrices, using chemometric methods of data analysis, confirms that phase-resolved fluorescence techniques offer improved discrimination between complex samples as compared with conventional steady state methods.« less

Sub-diffusion and trapped dynamics of neutral and charged probes in DNA-protein coacervates

NASA Astrophysics Data System (ADS)

Arfin, Najmul; Yadav, Avinash Chand; Bohidar, H. B.

2013-11-01

The physical mechanism leading to the formation of large intermolecular DNA-protein complexes has been studied. Our study aims to explain the occurrence of fast coacervation dynamics at the charge neutralization point, followed by the appearance of smaller complexes and slower coacervation dynamics as the complex experiences overcharging. Furthermore, the electrostatic potential and probe mobility was investigated to mimic the transport of DNA / DNA-protein complex in a DNA-protein complex coacervate medium [N. Arfin and H. B. Bohidar, J. Phys. Chem. B 116, 13192 (2012)] by assigning neutral, negative, or positive charge to the probe particle. The mobility of the neutral probe was maximal at low matrix concentrations and showed random walk behavior, while its mobility ceased at the jamming concentration of c = 0.6, showing sub-diffusion and trapped dynamics. The positively charged probe showed sub-diffusive random walk followed by trapped dynamics, while the negatively charged probe showed trapping with occasional hopping dynamics at much lower concentrations. Sub-diffusion of the probe was observed in all cases under consideration, where the electrostatic interaction was used exclusively as the dominant force involved in the dynamics. For neutral and positive probes, the mean square displacement ⟨R2⟩ exhibits a scaling with time as ⟨R2⟩ ˜ tα, distinguishing random walk and trapped dynamics at α = 0.64 ± 0.04 at c = 0.12 and c = 0.6, respectively. In addition, the same scaling factors with the exponent β = 0.64 ± 0.04 can be used to distinguish random walk and trapped dynamics for the neutral and positive probes using the relation between the number of distinct sites visited by the probe, S(t), which follows the scaling, S(t) ˜ tβ/ln (t). Our results established the occurrence of a hierarchy of diffusion dynamics experienced by a probe in a dense medium that is either charged or neutral.

Decreased complexity of glucose dynamics in diabetes: evidence from multiscale entropy analysis of continuous glucose monitoring system data.

PubMed

Chen, Jin-Long; Chen, Pin-Fan; Wang, Hung-Ming

2014-07-15

Parameters of glucose dynamics recorded by the continuous glucose monitoring system (CGMS) could help in the control of glycemic fluctuations, which is important in diabetes management. Multiscale entropy (MSE) analysis has recently been developed to measure the complexity of physical and physiological time sequences. A reduced MSE complexity index indicates the increased repetition patterns of the time sequence, and, thus, a decreased complexity in this system. No study has investigated the MSE analysis of glucose dynamics in diabetes. This study was designed to compare the complexity of glucose dynamics between the diabetic patients (n = 17) and the control subjects (n = 13), who were matched for sex, age, and body mass index via MSE analysis using the CGMS data. Compared with the control subjects, the diabetic patients revealed a significant increase (P < 0.001) in the mean (diabetic patients 166.0 ± 10.4 vs. control subjects 93.3 ± 1.5 mg/dl), the standard deviation (51.7 ± 4.3 vs. 11.1 ± 0.5 mg/dl), and the mean amplitude of glycemic excursions (127.0 ± 9.2 vs. 27.7 ± 1.3 mg/dl) of the glucose levels; and a significant decrease (P < 0.001) in the MSE complexity index (5.09 ± 0.23 vs. 7.38 ± 0.28). In conclusion, the complexity of glucose dynamics is decreased in diabetes. This finding implies the reactivity of glucoregulation is impaired in the diabetic patients. Such impairment presenting as an increased regularity of glycemic fluctuating pattern could be detected by MSE analysis. Thus, the MSE complexity index could potentially be used as a biomarker in the monitoring of diabetes.

Persistent topological features of dynamical systems

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

Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn; Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade; Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn

Inspired by an early work of Muldoon et al., Physica D 65, 1–16 (1993), we present a general method for constructing simplicial complex from observed time series of dynamical systems based on the delay coordinate reconstruction procedure. The obtained simplicial complex preserves all pertinent topological features of the reconstructed phase space, and it may be analyzed from topological, combinatorial, and algebraic aspects. In focus of this study is the computation of homology of the invariant set of some well known dynamical systems that display chaotic behavior. Persistent homology of simplicial complex and its relationship with the embedding dimensions are examinedmore » by studying the lifetime of topological features and topological noise. The consistency of topological properties for different dynamic regimes and embedding dimensions is examined. The obtained results shed new light on the topological properties of the reconstructed phase space and open up new possibilities for application of advanced topological methods. The method presented here may be used as a generic method for constructing simplicial complex from a scalar time series that has a number of advantages compared to the mapping of the same time series to a complex network.« less

Complex groundwater flow systems as traveling agent models

PubMed Central

Padilla, Pablo; Escolero, Oscar; González, Tomas; Morales-Casique, Eric; Osorio-Olvera, Luis

2014-01-01

Analyzing field data from pumping tests, we show that as with many other natural phenomena, groundwater flow exhibits complex dynamics described by 1/f power spectrum. This result is theoretically studied within an agent perspective. Using a traveling agent model, we prove that this statistical behavior emerges when the medium is complex. Some heuristic reasoning is provided to justify both spatial and dynamic complexity, as the result of the superposition of an infinite number of stochastic processes. Even more, we show that this implies that non-Kolmogorovian probability is needed for its study, and provide a set of new partial differential equations for groundwater flow. PMID:25337455

Studying the Structure and Dynamics of Biomolecules by Using Soluble Paramagnetic Probes

PubMed Central

Hocking, Henry G; Zangger, Klaus; Madl, Tobias

2013-01-01

Characterisation of the structure and dynamics of large biomolecules and biomolecular complexes by NMR spectroscopy is hampered by increasing overlap and severe broadening of NMR signals. As a consequence, the number of available NMR spectroscopy data is often sparse and new approaches to provide complementary NMR spectroscopy data are needed. Paramagnetic relaxation enhancements (PREs) obtained from inert and soluble paramagnetic probes (solvent PREs) provide detailed quantitative information about the solvent accessibility of NMR-active nuclei. Solvent PREs can be easily measured without modification of the biomolecule; are sensitive to molecular structure and dynamics; and are therefore becoming increasingly powerful for the study of biomolecules, such as proteins, nucleic acids, ligands and their complexes in solution. In this Minireview, we give an overview of the available solvent PRE probes and discuss their applications for structural and dynamic characterisation of biomolecules and biomolecular complexes. PMID:23836693

Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

PubMed

Gao, Zhongke; Jin, Ningde

2009-06-01

The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

Dynamic Identification for Control of Large Space Structures

NASA Technical Reports Server (NTRS)

Ibrahim, S. R.

1985-01-01

This is a compilation of reports by the one author on one subject. It consists of the following five journal articles: (1) A Parametric Study of the Ibrahim Time Domain Modal Identification Algorithm; (2) Large Modal Survey Testing Using the Ibrahim Time Domain Identification Technique; (3) Computation of Normal Modes from Identified Complex Modes; (4) Dynamic Modeling of Structural from Measured Complex Modes; and (5) Time Domain Quasi-Linear Identification of Nonlinear Dynamic Systems.

Identification of amino acids that promote specific and rigid TAR RNA-tat protein complex formation.

PubMed

Edwards, Thomas E; Robinson, Bruce H; Sigurdsson, Snorri Th

2005-03-01

The Tat protein and the transactivation responsive (TAR) RNA form an essential complex in the HIV lifecycle, and mutations in the basic region of the Tat protein alter this RNA-protein molecular recognition. Here, EPR spectroscopy was used to identify amino acids, flanking an essential arginine of the Tat protein, which contribute to specific and rigid TAR-Tat complex formation by monitoring changes in the mobility of nitroxide spin-labeled TAR RNA nucleotides upon binding. Arginine to lysine N-terminal mutations did not affect TAR RNA interfacial dynamics. In contrast, C-terminal point mutations, R56 in particular, affected the mobility of nucleotides U23 and U38, which are involved in a base-triple interaction in the complex. This report highlights the role of dynamics in specific molecular complex formation and demonstrates the ability of EPR spectroscopy to study interfacial dynamics of macromolecular complexes.

First principles molecular dynamics study of nitrogen vacancy complexes in boronitrene

NASA Astrophysics Data System (ADS)

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.

Quantifying cadherin mechanotransduction machinery assembly/disassembly dynamics using fluorescence covariance analysis.

PubMed

Vedula, Pavan; Cruz, Lissette A; Gutierrez, Natasha; Davis, Justin; Ayee, Brian; Abramczyk, Rachel; Rodriguez, Alexis J

2016-06-30

Quantifying multi-molecular complex assembly in specific cytoplasmic compartments is crucial to understand how cells use assembly/disassembly of these complexes to control function. Currently, biophysical methods like Fluorescence Resonance Energy Transfer and Fluorescence Correlation Spectroscopy provide quantitative measurements of direct protein-protein interactions, while traditional biochemical approaches such as sub-cellular fractionation and immunoprecipitation remain the main approaches used to study multi-protein complex assembly/disassembly dynamics. In this article, we validate and quantify multi-protein adherens junction complex assembly in situ using light microscopy and Fluorescence Covariance Analysis. Utilizing specific fluorescently-labeled protein pairs, we quantified various stages of adherens junction complex assembly, the multiprotein complex regulating epithelial tissue structure and function following de novo cell-cell contact. We demonstrate: minimal cadherin-catenin complex assembly in the perinuclear cytoplasm and subsequent localization to the cell-cell contact zone, assembly of adherens junction complexes, acto-myosin tension-mediated anchoring, and adherens junction maturation following de novo cell-cell contact. Finally applying Fluorescence Covariance Analysis in live cells expressing fluorescently tagged adherens junction complex proteins, we also quantified adherens junction complex assembly dynamics during epithelial monolayer formation.

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.

Complex Phenomena Understanding in Electricity through Dynamically Linked Concrete and Abstract Representations

ERIC Educational Resources Information Center

Taramopoulos, A.; Psillos, D.

2017-01-01

The present study investigates the impact of utilizing virtual laboratory environments combining dynamically linked concrete and abstract representations in investigative activities on the ability of students to comprehend simple and complex phenomena in the field of electric circuits. Forty-two 16- to 17-year-old high school students participated…

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…

The Effects of Aging and Dual Tasking on Human Gait Complexity During Treadmill Walking: A Comparative Study Using Quantized Dynamical Entropy and Sample Entropy.

PubMed

Ahmadi, Samira; Wu, Christine; Sepehri, Nariman; Kantikar, Anuprita; Nankar, Mayur; Szturm, Tony

2018-01-01

Quantized dynamical entropy (QDE) has recently been proposed as a new measure to quantify the complexity of dynamical systems with the purpose of offering a better computational efficiency. This paper further investigates the viability of this method using five different human gait signals. These signals are recorded while normal walking and while performing secondary tasks among two age groups (young and older age groups). The results are compared with the outcomes of previously established sample entropy (SampEn) measure for the same signals. We also study how analyzing segmented and spatially and temporally normalized signal differs from analyzing whole data. Our findings show that human gait signals become more complex as people age and while they are cognitively loaded. Center of pressure (COP) displacement in mediolateral direction is the best signal for showing the gait changes. Moreover, the results suggest that by segmenting data, more information about intrastride dynamical features are obtained. Most importantly, QDE is shown to be a reliable measure for human gait complexity analysis.

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories

PubMed Central

2014-01-01

Background Molecular Dynamics (MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. Results On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. Conclusions MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes. PMID:25077693

MDcons: Intermolecular contact maps as a tool to analyze the interface of protein complexes from molecular dynamics trajectories.

PubMed

Abdel-Azeim, Safwat; Chermak, Edrisse; Vangone, Anna; Oliva, Romina; Cavallo, Luigi

2014-01-01

Molecular Dynamics (MD) simulations of protein complexes suffer from the lack of specific tools in the analysis step. Analyses of MD trajectories of protein complexes indeed generally rely on classical measures, such as the RMSD, RMSF and gyration radius, conceived and developed for single macromolecules. As a matter of fact, instead, researchers engaged in simulating the dynamics of a protein complex are mainly interested in characterizing the conservation/variation of its biological interface. On these bases, herein we propose a novel approach to the analysis of MD trajectories or other conformational ensembles of protein complexes, MDcons, which uses the conservation of inter-residue contacts at the interface as a measure of the similarity between different snapshots. A "consensus contact map" is also provided, where the conservation of the different contacts is drawn in a grey scale. Finally, the interface area of the complex is monitored during the simulations. To show its utility, we used this novel approach to study two protein-protein complexes with interfaces of comparable size and both dominated by hydrophilic interactions, but having binding affinities at the extremes of the experimental range. MDcons is demonstrated to be extremely useful to analyse the MD trajectories of the investigated complexes, adding important insight into the dynamic behavior of their biological interface. MDcons specifically allows the user to highlight and characterize the dynamics of the interface in protein complexes and can thus be used as a complementary tool for the analysis of MD simulations of both experimental and predicted structures of protein complexes.

Dynamics and computation in functional shifts

NASA Astrophysics Data System (ADS)

Namikawa, Jun; Hashimoto, Takashi

2004-07-01

We introduce a new type of shift dynamics as an extended model of symbolic dynamics, and investigate the characteristics of shift spaces from the viewpoints of both dynamics and computation. This shift dynamics is called a functional shift, which is defined by a set of bi-infinite sequences of some functions on a set of symbols. To analyse the complexity of functional shifts, we measure them in terms of topological entropy, and locate their languages in the Chomsky hierarchy. Through this study, we argue that considering functional shifts from the viewpoints of both dynamics and computation gives us opposite results about the complexity of systems. We also describe a new class of shift spaces whose languages are not recursively enumerable.

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

NASA Astrophysics Data System (ADS)

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

2008-08-01

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

Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity

PubMed Central

Frickel, Jens; Theodosiou, Loukas

2017-01-01

Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus–host and prey–predator) with a more complex three-species system (virus–host–predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host–virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host–virus coevolution in the complex system and that the virus’ effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species. PMID:28973943

Multifractality and heteroscedastic dynamics: An application to time series analysis

NASA Astrophysics Data System (ADS)

Nascimento, C. M.; Júnior, H. B. N.; Jennings, H. D.; Serva, M.; Gleria, Iram; Viswanathan, G. M.

2008-01-01

An increasingly important problem in physics concerns scale invariance symmetry in diverse complex systems, often characterized by heteroscedastic dynamics. We investigate the nature of the relationship between the heteroscedastic and fractal aspects of the dynamics of complex systems, by analyzing the sensitivity to heteroscedasticity of the scaling properties of weakly nonstationary time series. By using multifractal detrended fluctuation analysis, we study the singularity spectra of currency exchange rate fluctuations, after partially or completely eliminating n-point correlations via data shuffling techniques. We conclude that heteroscedasticity can significantly increase multifractality and interpret these findings in the context of self-organizing and adaptive complex systems.

Aging, memory, and nonhierarchical energy landscape of spin jam

NASA Astrophysics Data System (ADS)

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-10-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes.

Extending network approach to language dynamics and human cognition. Comment on "Approaching human language with complex networks" by Cong and Liu

NASA Astrophysics Data System (ADS)

Gong, Tao; Shuai, Lan; Wu, Yicheng

2014-12-01

By analyzing complex networks constructed from authentic language data, Cong and Liu [1] advance linguistics research into the big data era. The network approach has revealed many intrinsic generalities and crucial differences at both the macro and micro scales between human languages. The axiom behind this research is that language is a complex adaptive system [2]. Although many lexical, semantic, or syntactic features have been discovered by means of analyzing the static and dynamic linguistic networks of world languages, available network-based language studies have not explicitly addressed the evolutionary dynamics of language systems and the correlations between language and human cognition. This commentary aims to provide some insights on how to use the network approach to study these issues.

Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics

NASA Astrophysics Data System (ADS)

Zhang, Yali; Wang, Jun

2017-09-01

In an attempt to investigate the nonlinear complex evolution of financial dynamics, a new financial price model - the multitype range-intensity contact (MRIC) financial model, is developed based on the multitype range-intensity interacting contact system, in which the interaction and transmission of different types of investment attitudes in a stock market are simulated by viruses spreading. Two new random visibility graph (VG) based analyses and Lempel-Ziv complexity (LZC) are applied to study the complex behaviors of return time series and the corresponding random sorted series. The VG method is the complex network theory, and the LZC is a non-parametric measure of complexity reflecting the rate of new pattern generation of a series. In this work, the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, the numerical empirical study shows the similar complexity behaviors between the model and the real markets, the research confirms that the financial model is reasonable to some extent.

Dynamical mechanism of atrial fibrillation: A topological approach

NASA Astrophysics Data System (ADS)

Marcotte, Christopher D.; Grigoriev, Roman O.

2017-09-01

While spiral wave breakup has been implicated in the emergence of atrial fibrillation, its role in maintaining this complex type of cardiac arrhythmia is less clear. We used the Karma model of cardiac excitation to investigate the dynamical mechanisms that sustain atrial fibrillation once it has been established. The results of our numerical study show that spatiotemporally chaotic dynamics in this regime can be described as a dynamical equilibrium between topologically distinct types of transitions that increase or decrease the number of wavelets, in general agreement with the multiple wavelets' hypothesis. Surprisingly, we found that the process of continuous excitation waves breaking up into discontinuous pieces plays no role whatsoever in maintaining spatiotemporal complexity. Instead, this complexity is maintained as a dynamical balance between wave coalescence—a unique, previously unidentified, topological process that increases the number of wavelets—and wave collapse—a different topological process that decreases their number.

Down syndrome's brain dynamics: analysis of fractality in resting state.

PubMed

Hemmati, Sahel; Ahmadlou, Mehran; Gharib, Masoud; Vameghi, Roshanak; Sajedi, Firoozeh

2013-08-01

To the best knowledge of the authors there is no study on nonlinear brain dynamics of down syndrome (DS) patients, whereas brain is a highly complex and nonlinear system. In this study, fractal dimension of EEG, as a key characteristic of brain dynamics, showing irregularity and complexity of brain dynamics, was used for evaluation of the dynamical changes in the DS brain. The results showed higher fractality of the DS brain in almost all regions compared to the normal brain, which indicates less centrality and higher irregular or random functioning of the DS brain regions. Also, laterality analysis of the frontal lobe showed that the normal brain had a right frontal laterality of complexity whereas the DS brain had an inverse pattern (left frontal laterality). Furthermore, the high accuracy of 95.8 % obtained by enhanced probabilistic neural network classifier showed the potential of nonlinear dynamic analysis of the brain for diagnosis of DS patients. Moreover, the results showed that the higher EEG fractality in DS is associated with the higher fractality in the low frequencies (delta and theta), in broad regions of the brain, and the high frequencies (beta and gamma), majorly in the frontal regions.

Control of complex networks requires both structure and dynamics

NASA Astrophysics Data System (ADS)

Gates, Alexander J.; Rocha, Luis M.

2016-04-01

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.

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…

A Complex Systems Investigation of Group Work Dynamics in L2 Interactive Tasks

ERIC Educational Resources Information Center

Poupore, Glen

2018-01-01

Working with Korean university-level learners of English, this study provides a detailed analytical comparison of 2 task work groups that were video-recorded, with 1 group scoring very high and the other relatively low based on the results of a Group Work Dynamic (GWD) measuring instrument. Adopting a complexity theory (CT) perspective and…

Dynamic Processes of Speech Development by Seven Adult Learners of Japanese in a Domestic Immersion Context

ERIC Educational Resources Information Center

Fukuda, Makiko

2014-01-01

The present study revealed the dynamic process of speech development in a domestic immersion program by seven adult beginning learners of Japanese. The speech data were analyzed with fluency, accuracy, and complexity measurements at group, interindividual, and intraindividual levels. The results revealed the complex nature of language development…

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

A Simplified Approach to Risk Assessment Based on System Dynamics: An Industrial Case Study.

PubMed

Garbolino, Emmanuel; Chery, Jean-Pierre; Guarnieri, Franck

2016-01-01

Seveso plants are complex sociotechnical systems, which makes it appropriate to support any risk assessment with a model of the system. However, more often than not, this step is only partially addressed, simplified, or avoided in safety reports. At the same time, investigations have shown that the complexity of industrial systems is frequently a factor in accidents, due to interactions between their technical, human, and organizational dimensions. In order to handle both this complexity and changes in the system over time, this article proposes an original and simplified qualitative risk evaluation method based on the system dynamics theory developed by Forrester in the early 1960s. The methodology supports the development of a dynamic risk assessment framework dedicated to industrial activities. It consists of 10 complementary steps grouped into two main activities: system dynamics modeling of the sociotechnical system and risk analysis. This system dynamics risk analysis is applied to a case study of a chemical plant and provides a way to assess the technological and organizational components of safety. © 2016 Society for Risk Analysis.

Projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks.

PubMed

Feng, Cun-Fang; Xu, Xin-Jian; Wang, Sheng-Jun; Wang, Ying-Hai

2008-06-01

We study projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks. We relax some limitations of previous work, where projective-anticipating and projective-lag synchronization can be achieved only on two coupled chaotic systems. In this paper, we realize projective-anticipating and projective-lag synchronization on complex dynamical networks composed of a large number of interconnected components. At the same time, although previous work studied projective synchronization on complex dynamical networks, the dynamics of the nodes are coupled partially linear chaotic systems. In this paper, the dynamics of the nodes of the complex networks are time-delayed chaotic systems without the limitation of the partial linearity. Based on the Lyapunov stability theory, we suggest a generic method to achieve the projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random dynamical networks, and we find both its existence and sufficient stability conditions. The validity of the proposed method is demonstrated and verified by examining specific examples using Ikeda and Mackey-Glass systems on Erdos-Renyi networks.

Dynamically Tunable Cell Culture Platforms for Tissue Engineering and Mechanobiology

PubMed Central

Uto, Koichiro; Tsui, Jonathan H.; DeForest, Cole A.; Kim, Deok-Ho

2016-01-01

Human tissues are sophisticated ensembles of many distinct cell types embedded in the complex, but well-defined, structures of the extracellular matrix (ECM). Dynamic biochemical, physicochemical, and mechano-structural changes in the ECM define and regulate tissue-specific cell behaviors. To recapitulate this complex environment in vitro, dynamic polymer-based biomaterials have emerged as powerful tools to probe and direct active changes in cell function. The rapid evolution of polymerization chemistries, structural modulation, and processing technologies, as well as the incorporation of stimuli-responsiveness, now permit synthetic microenvironments to capture much of the dynamic complexity of native tissue. These platforms are comprised not only of natural polymers chemically and molecularly similar to ECM, but those fully synthetic in origin. Here, we review recent in vitro efforts to mimic the dynamic microenvironment comprising native tissue ECM from the viewpoint of material design. We also discuss how these dynamic polymer-based biomaterials are being used in fundamental cell mechanobiology studies, as well as towards efforts in tissue engineering and regenerative medicine. PMID:28522885

Exploring complex networks.

PubMed

Strogatz, S H

2001-03-08

The study of networks pervades all of science, from neurobiology to statistical physics. The most basic issues are structural: how does one characterize the wiring diagram of a food web or the Internet or the metabolic network of the bacterium Escherichia coli? Are there any unifying principles underlying their topology? From the perspective of nonlinear dynamics, we would also like to understand how an enormous network of interacting dynamical systems-be they neurons, power stations or lasers-will behave collectively, given their individual dynamics and coupling architecture. Researchers are only now beginning to unravel the structure and dynamics of complex networks.

Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations

NASA Technical Reports Server (NTRS)

Newman, Perry A.; Newman, James C., III; Barnwell, Richard W.; Taylor, Arthur C., III; Hou, Gene J.-W.

1998-01-01

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Analytical structure, dynamics, and coarse graining of a kinetic model of an active fluid

NASA Astrophysics Data System (ADS)

Gao, Tong; Betterton, Meredith D.; Jhang, An-Sheng; Shelley, Michael J.

2017-09-01

We analyze one of the simplest active suspensions with complex dynamics: a suspension of immotile "extensor" particles that exert active extensile dipolar stresses on the fluid in which they are immersed. This is relevant to several experimental systems, such as recently studied tripartite rods that create extensile flows by consuming a chemical fuel. We first describe the system through a Doi-Onsager kinetic theory based on microscopic modeling. This theory captures the active stresses produced by the particles that can drive hydrodynamic instabilities, as well as the steric interactions of rodlike particles that lead to nematic alignment. This active nematic system yields complex flows and disclination defect dynamics very similar to phenomenological Landau-deGennes Q -tensor theories for active nematic fluids, as well as by more complex Doi-Onsager theories for polar microtubule-motor-protein systems. We apply the quasiequilibrium Bingham closure, used to study suspensions of passive microscopic rods, to develop a nonstandard Q -tensor theory. We demonstrate through simulation that this B Q -tensor theory gives an excellent analytical and statistical accounting of the suspension's complex dynamics, at a far reduced computational cost. Finally, we apply the B Q -tensor model to study the dynamics of extensor suspensions in circular and biconcave domains. In circular domains, we reproduce previous results for systems with weak nematic alignment, but for strong alignment we find unusual dynamics with activity-controlled defect production and absorption at the boundaries of the domain. In biconcave domains, a Fredericks-like transition occurs as the width of the neck connecting the two disks is varied.

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis

PubMed Central

Awan, Imtiaz; Aziz, Wajid; Habib, Nazneen; Alowibdi, Jalal S.; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features. PMID:29771977

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis.

PubMed

Awan, Imtiaz; Aziz, Wajid; Shah, Imran Hussain; Habib, Nazneen; Alowibdi, Jalal S; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

Dynamics of embedded curves by doubly-nonlocal reaction-diffusion systems

NASA Astrophysics Data System (ADS)

von Brecht, James H.; Blair, Ryan

2017-11-01

We study a class of nonlocal, energy-driven dynamical models that govern the motion of closed, embedded curves from both an energetic and dynamical perspective. Our energetic results provide a variety of ways to understand physically motivated energetic models in terms of more classical, combinatorial measures of complexity for embedded curves. This line of investigation culminates in a family of complexity bounds that relate a rather broad class of models to a generalized, or weighted, variant of the crossing number. Our dynamic results include global well-posedness of the associated partial differential equations, regularity of equilibria for these flows as well as a more detailed investigation of dynamics near such equilibria. Finally, we explore a few global dynamical properties of these models numerically.

Gender- and age-related differences in heart rate dynamics: are women more complex than men?

NASA Technical Reports Server (NTRS)

Ryan, S. M.; Goldberger, A. L.; Pincus, S. M.; Mietus, J.; Lipsitz, L. A.

1994-01-01

OBJECTIVES. This study aimed to quantify the complex dynamics of beat-to-beat sinus rhythm heart rate fluctuations and to determine their differences as a function of gender and age. BACKGROUND. Recently, measures of heart rate variability and the nonlinear "complexity" of heart rate dynamics have been used as indicators of cardiovascular health. Because women have lower cardiovascular risk and greater longevity than men, we postulated that there are important gender-related differences in beat-to-beat heart rate dynamics. METHODS. We analyzed heart rate dynamics during 8-min segments of continuous electrocardiographic recording in healthy young (20 to 39 years old), middle-aged (40 to 64 years old) and elderly (65 to 90 years old) men (n = 40) and women (n = 27) while they performed spontaneous and metronomic (15 breaths/min) breathing. Relatively high (0.15 to 0.40 Hz) and low (0.01 to 0.15 Hz) frequency components of heart rate variability were computed using spectral analysis. The overall "complexity" of each heart rate time series was quantified by its approximate entropy, a measure of regularity derived from nonlinear dynamics ("chaos" theory). RESULTS. Mean heart rate did not differ between the age groups or genders. High frequency heart rate power and the high/low frequency power ratio decreased with age in both men and women (p < 0.05). The high/low frequency power ratio during spontaneous and metronomic breathing was greater in women than men (p < 0.05). Heart rate approximate entropy decreased with age and was higher in women than men (p < 0.05). CONCLUSIONS. High frequency heart rate spectral power (associated with parasympathetic activity) and the overall complexity of heart rate dynamics are higher in women than men. These complementary findings indicate the need to account for gender-as well as age-related differences in heart rate dynamics. Whether these gender differences are related to lower cardiovascular disease risk and greater longevity in women requires further study.

Three-dimensional curved grid finite-difference modelling for non-planar rupture dynamics

NASA Astrophysics Data System (ADS)

Zhang, Zhenguo; Zhang, Wei; Chen, Xiaofei

2014-11-01

In this study, we present a new method for simulating the 3-D dynamic rupture process occurring on a non-planar fault. The method is based on the curved-grid finite-difference method (CG-FDM) proposed by Zhang & Chen and Zhang et al. to simulate the propagation of seismic waves in media with arbitrary irregular surface topography. While keeping the advantages of conventional FDM, that is computational efficiency and easy implementation, the CG-FDM also is flexible in modelling the complex fault model by using general curvilinear grids, and thus is able to model the rupture dynamics of a fault with complex geometry, such as oblique dipping fault, non-planar fault, fault with step-over, fault branching, even if irregular topography exists. The accuracy and robustness of this new method have been validated by comparing with the previous results of Day et al., and benchmarks for rupture dynamics simulations. Finally, two simulations of rupture dynamics with complex fault geometry, that is a non-planar fault and a fault rupturing a free surface with topography, are presented. A very interesting phenomenon was observed that topography can weaken the tendency for supershear transition to occur when rupture breaks out at a free surface. Undoubtedly, this new method provides an effective, at least an alternative, tool to simulate the rupture dynamics of a complex non-planar fault, and can be applied to model the rupture dynamics of a real earthquake with complex geometry.

Grounding explanations in evolving, diagnostic situations

NASA Technical Reports Server (NTRS)

Johannesen, Leila J.; Cook, Richard I.; Woods, David D.

1994-01-01

Certain fields of practice involve the management and control of complex dynamic systems. These include flight deck operations in commercial aviation, control of space systems, anesthetic management during surgery or chemical or nuclear process control. Fault diagnosis of these dynamic systems generally must occur with the monitored process on-line and in conjunction with maintaining system integrity.This research seeks to understand in more detail what it means for an intelligent system to function cooperatively, or as a 'team player' in complex, dynamic environments. The approach taken was to study human practitioners engaged in the management of a complex, dynamic process: anesthesiologists during neurosurgical operations. The investigation focused on understanding how team members cooperate in management and fault diagnosis and comparing this interaction to the situation with an Artificial Intelligence(AI) system that provides diagnoses and explanations. Of particular concern was to study the ways in which practitioners support one another in keeping aware of relevant information concerning the state of the monitored process and of the problem solving process.

Oscillations in interconnected complex networks under intentional attack

NASA Astrophysics Data System (ADS)

Zhang, Wen-Ping; Xia, Yongxiang; Tan, Fei

2016-01-01

Many real-world networks are interconnected with each other. In this paper, we study the traffic dynamics in interconnected complex networks under an intentional attack. We find that with the shortest time delay routing strategy, the traffic dynamics can show the stable state, periodic, quasi-periodic and chaotic oscillations, when the capacity redundancy parameter changes. Moreover, compared with isolated complex networks, oscillations always take place in interconnected networks more easily. Thirdly, in interconnected networks, oscillations are affected strongly by the coupling probability and coupling preference.

On the robustness of complex heterogeneous gene expression networks.

PubMed

Gómez-Gardeñes, Jesús; Moreno, Yamir; Floría, Luis M

2005-04-01

We analyze a continuous gene expression model on the underlying topology of a complex heterogeneous network. Numerical simulations aimed at studying the chaotic and periodic dynamics of the model are performed. The results clearly indicate that there is a region in which the dynamical and structural complexity of the system avoid chaotic attractors. However, contrary to what has been reported for Random Boolean Networks, the chaotic phase cannot be completely suppressed, which has important bearings on network robustness and gene expression modeling.

Unravelling the differences between complexity and frailty in old age: findings from a constructivist grounded theory study.

PubMed

McGeorge, S J

2011-02-01

UK health policy has used the terms 'frailty' and 'complexity' synonymously but there is no common definition for either. Understanding these concepts is important if demand for health care created by the increasing number of older people in society is to be managed effectively. This paper explores some findings from a study into how mental health nurses who work with older people construct and operationalize the concept of 'age-related complexity'. Constructivist grounded theory was used. Audio-taped interviews were undertaken with 13 registered nurses and were analysed using a constant comparative method. This paper addresses the relationship between frailty and complexity, which was identified as a theme within the category 'dynamic complexity'. The findings suggest that nurses understand important differences between the two concepts. Frailty is exclusively used to describe physical states while complexity is a more encompassing term that has resonance and relevance in mental health services. The dynamic nature of complexity means that older people can become both more and less complex and this has implications for nursing practice that require further study. © 2010 Blackwell Publishing.

Single-Molecule Interfacial Electron Transfer

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

Lu, H. Peter

This project is focused on the use of single-molecule high spatial and temporal resolved techniques to study molecular dynamics in condensed phase and at interfaces, especially, the complex reaction dynamics associated with electron and energy transfer rate processes. The complexity and inhomogeneity of the interfacial ET dynamics often present a major challenge for a molecular level comprehension of the intrinsically complex systems, which calls for both higher spatial and temporal resolutions at ultimate single-molecule and single-particle sensitivities. Combined single-molecule spectroscopy and electrochemical atomic force microscopy approaches are unique for heterogeneous and complex interfacial electron transfer systems because the static andmore » dynamic inhomogeneities can be identified and characterized by studying one molecule at a specific nanoscale surface site at a time. The goal of our project is to integrate and apply these spectroscopic imaging and topographic scanning techniques to measure the energy flow and electron flow between molecules and substrate surfaces as a function of surface site geometry and molecular structure. We have been primarily focusing on studying interfacial electron transfer under ambient condition and electrolyte solution involving both single crystal and colloidal TiO 2 and related substrates. The resulting molecular level understanding of the fundamental interfacial electron transfer processes will be important for developing efficient light harvesting systems and broadly applicable to problems in fundamental chemistry and physics. We have made significant advancement on deciphering the underlying mechanism of the complex and inhomogeneous interfacial electron transfer dynamics in dyesensitized TiO 2 nanoparticle systems that strongly involves with and regulated by molecule-surface interactions. We have studied interfacial electron transfer on TiO 2 nanoparticle surfaces by using ultrafast single-molecule spectroscopy and electrochemical AFM metal tip scanning microscopy, focusing on understanding the interfacial electron transfer dynamics at specific nanoscale electron transfer sites with high-spatially and temporally resolved topographic-and-spectroscopic characterization at individual molecule basis, characterizing single-molecule rate processes, reaction driving force, and molecule-substrate electronic coupling. One of the most significant characteristics of our new approach is that we are able to interrogate the complex interfacial electron transfer dynamics by actively pin-point energetic manipulation of the surface interaction and electronic couplings, beyond the conventional excitation and observation.« less

Molecular dynamics simulations of large macromolecular complexes.

PubMed

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

2015-04-01

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Assessing the Dynamic Behavior of Online Q&A Knowledge Markets: A System Dynamics Approach

ERIC Educational Resources Information Center

Jafari, Mostafa; Hesamamiri, Roozbeh; Sadjadi, Jafar; Bourouni, Atieh

2012-01-01

Purpose: The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet-based kind of knowledge market by considering both social and economic interactions. Design/methodology/approach: A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of…

Characterizing complex networks through statistics of Möbius transformations

NASA Astrophysics Data System (ADS)

Jaćimović, Vladimir; Crnkić, Aladin

2017-04-01

It is well-known now that dynamics of large populations of globally (all-to-all) coupled oscillators can be reduced to low-dimensional submanifolds (WS transformation and OA ansatz). Marvel et al. (2009) described an intriguing algebraic structure standing behind this reduction: oscillators evolve by the action of the group of Möbius transformations. Of course, dynamics in complex networks of coupled oscillators is highly complex and not reducible. Still, closer look unveils that even in complex networks some (possibly overlapping) groups of oscillators evolve by Möbius transformations. In this paper, we study properties of the network by identifying Möbius transformations in the dynamics of oscillators. This enables us to introduce some new (statistical) concepts that characterize the network. In particular, the notion of coherence of the network (or subnetwork) is proposed. This conceptual approach is meaningful for the broad class of networks, including those with time-delayed, noisy or mixed interactions. In this paper, several simple (random) graphs are studied illustrating the meaning of the concepts introduced in the paper.

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 complex dynamics (e.g. both short- and long-term changes in conductivity) in response to applied voltage signals. Characterization of these atomic switch networks (ASNs) brought out interesting parallels to biological neural networks, including power-law scaling in the statistics of electrical signal propagation and dynamic self-organization of differentiated subnetworks. A reservoir computing (RC) strategy was employed to utilize measurements of electrical signals dynamically generated in ASNs to perform time-series memory and manipulation tasks including a parity test and arbitrary waveform generation. These results represent the useful integration of a complex network into a dynamic physical RC device.

Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

NASA Astrophysics Data System (ADS)

Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

2017-09-01

In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

Complex structural dynamics of nanocatalysts revealed in Operando conditions by correlated imaging and spectroscopy probes

DOE PAGES

Li, Y.; Zakharov, D.; Zhao, S.; ...

2015-06-29

Understanding how heterogeneous catalysts change size, shape and structure during chemical reactions is limited by the paucity of methods for studying catalytic ensembles in working state, that is, in operando conditions. Here by a correlated use of synchrotron X-ray absorption spectroscopy and scanning transmission electron microscopy in operando conditions, we quantitatively describe the complex structural dynamics of supported Pt catalysts exhibited during an exemplary catalytic reaction—ethylene hydrogenation. This work exploits a microfabricated catalytic reactor compatible with both probes. The results demonstrate dynamic transformations of the ensemble of Pt clusters that spans a broad size range throughout changing reaction conditions. Lastly,more » this method is generalizable to quantitative operando studies of complex systems using a wide variety of X-ray and electron-based experimental probes.« less

Aging, memory, and nonhierarchical energy landscape of spin jam

PubMed Central

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-01-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes. PMID:27698141

Offside Decisions by Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events

ERIC Educational Resources Information Center

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-01-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29)…

Dynamics and regulation of nuclear import and nuclear movements of HIV-1 complexes

PubMed Central

Burdick, Ryan C.; Chen, Jianbo; Sastri, Jaya; Hu, Wei-Shau

2017-01-01

The dynamics and regulation of HIV-1 nuclear import and its intranuclear movements after import have not been studied. To elucidate these essential HIV-1 post-entry events, we labeled viral complexes with two fluorescently tagged virion-incorporated proteins (APOBEC3F or integrase), and analyzed the HIV-1 dynamics of nuclear envelope (NE) docking, nuclear import, and intranuclear movements in living cells. We observed that HIV-1 complexes exhibit unusually long NE residence times (1.5±1.6 hrs) compared to most cellular cargos, which are imported into the nuclei within milliseconds. Furthermore, nuclear import requires HIV-1 capsid (CA) and nuclear pore protein Nup358, and results in significant loss of CA, indicating that one of the viral core uncoating steps occurs during nuclear import. Our results showed that the CA-Cyclophilin A interaction regulates the dynamics of nuclear import by delaying the time of NE docking as well as transport through the nuclear pore, but blocking reverse transcription has no effect on the kinetics of nuclear import. We also visualized the translocation of viral complexes docked at the NE into the nucleus and analyzed their nuclear movements and determined that viral complexes exhibited a brief fast phase (<9 min), followed by a long slow phase lasting several hours. A comparison of the movement of viral complexes to those of proviral transcription sites supports the hypothesis that HIV-1 complexes quickly tether to chromatin at or near their sites of integration in both wild-type cells and cells in which LEDGF/p75 was deleted using CRISPR/cas9, indicating that the tethering interactions do not require LEDGF/p75. These studies provide novel insights into the dynamics of viral complex-NE association, regulation of nuclear import, viral core uncoating, and intranuclear movements that precede integration site selection. PMID:28827840

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

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

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

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

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

Analyzing complex networks evolution through Information Theory quantifiers

NASA Astrophysics Data System (ADS)

Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martín Gómez

2011-01-01

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

Proton transfer reactions and dynamics in CH(3)OH-H(3)O(+)-H(2)O complexes.

PubMed

Sagarik, Kritsana; Chaiwongwattana, Sermsiri; Vchirawongkwin, Viwat; Prueksaaroon, Supakit

2010-01-28

Proton transfer reactions and dynamics in hydrated complexes formed from CH(3)OH, H(3)O(+) and H(2)O were studied using theoretical methods. The investigations began with searching for equilibrium structures at low hydration levels using the DFT method, from which active H-bonds in the gas phase and continuum aqueous solution were characterized and analyzed. Based on the asymmetric stretching coordinates (Deltad(DA)), four H-bond complexes were identified as potential transition states, in which the most active unit is represented by an excess proton nearly equally shared between CH(3)OH and H(2)O. These cannot be definitive due to the lack of asymmetric O-H stretching frequencies (nu(OH)) which are spectral signatures of transferring protons. Born-Oppenheimer molecular dynamics (BOMD) simulations revealed that, when the thermal energy fluctuations and dynamics were included in the model calculations, the spectral signatures at nu(OH) approximately 1000 cm(-1) appeared. In continuum aqueous solution, the H-bond complex with incomplete water coordination at charged species turned out to be the only active transition state. Based on the assumption that the thermal energy fluctuations and dynamics could temporarily break the H-bonds linking the transition state complex and water molecules in the second hydration shell, elementary reactions of proton transfer were proposed. The present study showed that, due to the coupling among various vibrational modes, the discussions on proton transfer reactions cannot be made based solely on static proton transfer potentials. Inclusion of thermal energy fluctuations and dynamics in the model calculations, as in the case of BOMD simulations, together with systematic IR spectral analyses, have been proved to be the most appropriate theoretical approaches.

Investigating dynamical complexity in the magnetosphere using various entropy measures

NASA Astrophysics Data System (ADS)

Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Kalimeri, Maria; Anastasiadis, Anastasios; Eftaxias, Konstantinos

2009-09-01

The complex system of the Earth's magnetosphere corresponds to an open spatially extended nonequilibrium (input-output) dynamical system. The nonextensive Tsallis entropy has been recently introduced as an appropriate information measure to investigate dynamical complexity in the magnetosphere. The method has been employed for analyzing Dst time series and gave promising results, detecting the complexity dissimilarity among different physiological and pathological magnetospheric states (i.e., prestorm activity and intense magnetic storms, respectively). This paper explores the applicability and effectiveness of a variety of computable entropy measures (e.g., block entropy, Kolmogorov entropy, T complexity, and approximate entropy) to the investigation of dynamical complexity in the magnetosphere. We show that as the magnetic storm approaches there is clear evidence of significant lower complexity in the magnetosphere. The observed higher degree of organization of the system agrees with that inferred previously, from an independent linear fractal spectral analysis based on wavelet transforms. This convergence between nonlinear and linear analyses provides a more reliable detection of the transition from the quiet time to the storm time magnetosphere, thus showing evidence that the occurrence of an intense magnetic storm is imminent. More precisely, we claim that our results suggest an important principle: significant complexity decrease and accession of persistency in Dst time series can be confirmed as the magnetic storm approaches, which can be used as diagnostic tools for the magnetospheric injury (global instability). Overall, approximate entropy and Tsallis entropy yield superior results for detecting dynamical complexity changes in the magnetosphere in comparison to the other entropy measures presented herein. Ultimately, the analysis tools developed in the course of this study for the treatment of Dst index can provide convenience for space weather applications.

New insights into sucking, swallowing and breathing central generators: A complexity analysis of rhythmic motor behaviors.

PubMed

Samson, Nathalie; Praud, Jean-Paul; Quenet, Brigitte; Similowski, Thomas; Straus, Christian

2017-01-18

Sucking, swallowing and breathing are dynamic motor behaviors. Breathing displays features of chaos-like dynamics, in particular nonlinearity and complexity, which take their source in the automatic command of breathing. In contrast, buccal/gill ventilation in amphibians is one of the rare motor behaviors that do not display nonlinear complexity. This study aimed at assessing whether sucking and swallowing would also follow nonlinear complex dynamics in the newborn lamb. Breathing movements were recorded before, during and after bottle-feeding. Sucking pressure and the integrated EMG of the thyroartenoid muscle, as an index of swallowing, were recorded during bottle-feeding. Nonlinear complexity of the whole signals was assessed through the calculation of the noise limit value (NL). Breathing and swallowing always exhibited chaos-like dynamics. The NL of breathing did not change significantly before, during or after bottle-feeding. On the other hand, sucking inconsistently and significantly less frequently than breathing exhibited a chaos-like dynamics. Therefore, the central pattern generator (CPG) that drives sucking may be functionally different from the breathing CPG. Furthermore, the analogy between buccal/gill ventilation and sucking suggests that the latter may take its phylogenetic origin in the gill ventilation CPG of the common ancestor of extant amphibians and mammals. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Persistent model order reduction for complex dynamical systems using smooth orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ilbeigi, Shahab; Chelidze, David

2017-11-01

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness.

Instantaneous Transfer Entropy for the Study of Cardiovascular and Cardiorespiratory Nonstationary Dynamics.

PubMed

Valenza, Gaetano; Faes, Luca; Citi, Luca; Orini, Michele; Barbieri, Riccardo

2018-05-01

Measures of transfer entropy (TE) quantify the direction and strength of coupling between two complex systems. Standard approaches assume stationarity of the observations, and therefore are unable to track time-varying changes in nonlinear information transfer with high temporal resolution. In this study, we aim to define and validate novel instantaneous measures of TE to provide an improved assessment of complex nonstationary cardiorespiratory interactions. We here propose a novel instantaneous point-process TE (ipTE) and validate its assessment as applied to cardiovascular and cardiorespiratory dynamics. In particular, heartbeat and respiratory dynamics are characterized through discrete time series, and modeled with probability density functions predicting the time of the next physiological event as a function of the past history. Likewise, nonstationary interactions between heartbeat and blood pressure dynamics are characterized as well. Furthermore, we propose a new measure of information transfer, the instantaneous point-process information transfer (ipInfTr), which is directly derived from point-process-based definitions of the Kolmogorov-Smirnov distance. Analysis on synthetic data, as well as on experimental data gathered from healthy subjects undergoing postural changes confirms that ipTE, as well as ipInfTr measures are able to dynamically track changes in physiological systems coupling. This novel approach opens new avenues in the study of hidden, transient, nonstationary physiological states involving multivariate autonomic dynamics in cardiovascular health and disease. The proposed method can also be tailored for the study of complex multisystem physiology (e.g., brain-heart or, more in general, brain-body interactions).

Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory

NASA Technical Reports Server (NTRS)

Pikkujamsa, S. M.; Makikallio, T. H.; Sourander, L. B.; Raiha, I. J.; Puukka, P.; Skytta, J.; Peng, C. K.; Goldberger, A. L.; Huikuri, H. V.

1999-01-01

BACKGROUND: New methods of R-R interval variability based on fractal scaling and nonlinear dynamics ("chaos theory") may give new insights into heart rate dynamics. The aims of this study were to (1) systematically characterize and quantify the effects of aging from early childhood to advanced age on 24-hour heart rate dynamics in healthy subjects; (2) compare age-related changes in conventional time- and frequency-domain measures with changes in newly derived measures based on fractal scaling and complexity (chaos) theory; and (3) further test the hypothesis that there is loss of complexity and altered fractal scaling of heart rate dynamics with advanced age. METHODS AND RESULTS: The relationship between age and cardiac interbeat (R-R) interval dynamics from childhood to senescence was studied in 114 healthy subjects (age range, 1 to 82 years) by measurement of the slope, beta, of the power-law regression line (log power-log frequency) of R-R interval variability (10(-4) to 10(-2) Hz), approximate entropy (ApEn), short-term (alpha(1)) and intermediate-term (alpha(2)) fractal scaling exponents obtained by detrended fluctuation analysis, and traditional time- and frequency-domain measures from 24-hour ECG recordings. Compared with young adults (<40 years old, n=29), children (<15 years old, n=27) showed similar complexity (ApEn) and fractal correlation properties (alpha(1), alpha(2), beta) of R-R interval dynamics despite lower spectral and time-domain measures. Progressive loss of complexity (decreased ApEn, r=-0.69, P<0.001) and alterations of long-term fractal-like heart rate behavior (increased alpha(2), r=0.63, decreased beta, r=-0.60, P<0.001 for both) were observed thereafter from middle age (40 to 60 years, n=29) to old age (>60 years, n=29). CONCLUSIONS: Cardiac interbeat interval dynamics change markedly from childhood to old age in healthy subjects. Children show complexity and fractal correlation properties of R-R interval time series comparable to those of young adults, despite lower overall heart rate variability. Healthy aging is associated with R-R interval dynamics showing higher regularity and altered fractal scaling consistent with a loss of complex variability.

Characterization of doctor-patient communication using heartbeat nonlinear dynamics: A preliminary study using Lagged Poincaré Plots.

PubMed

Nardelli, M; Del Piccolo, L; Danzi, Op; Perlini, C; Tedeschi, F; Greco, A; Scilingo, Ep; Valenza, G

2017-07-01

Emphatic doctor-patient communication has been associated with an improved psycho-physiological well-being involving cardiovascular and neuroendocrine responses. Nevertheless, a comprehensive assessment of heartbeat linear and nonlinear/complex dynamics throughout the communication of a life-threatening disease has not been performed yet. To this extent, we here study heart rate variability (HRV) series gathered from 17 subjects while watching a video where an oncologist discloses the diagnosis of a cancer metastasis to a patient. Further 17 subjects watched the same video including additional affective emphatic contents. For the assessment of the two groups, linear heartbeat dynamics was quantified through measures defined in the time and frequency domains, whereas nonlinear/complex dynamics referred to measures of entropy, and combined Lagged Poincare Plots (LPP) and symbolic analyses. Considering differences between the beginning and the end of the video, results from non-parametric statistical tests demonstrated that the group watching emphatic contents showed HRV changes in the LF/HF ratio exclusively. Conversely, the group watching the purely informative video showed changes in vagal activity (i.e., HF power), LF/HF ratio, as well as LPP measures. Additionally, a Support Vector Machine algorithm including HRV nonlinear/complex information was able to automatically discern between groups with an accuracy of 76.47%. We therefore propose the use of heartbeat nonlinear/complex dynamics to objectively assess the empathy level of healthy women.

Dissociation of a Dynamic Protein Complex Studied by All-Atom Molecular Simulations.

PubMed

Zhang, Liqun; Borthakur, Susmita; Buck, Matthias

2016-02-23

The process of protein complex dissociation remains to be understood at the atomic level of detail. Computers now allow microsecond timescale molecular-dynamics simulations, which make the visualization of such processes possible. Here, we investigated the dissociation process of the EphA2-SHIP2 SAM-SAM domain heterodimer complex using unrestrained all-atom molecular-dynamics simulations. Previous studies on this system have shown that alternate configurations are sampled, that their interconversion can be fast, and that the complex is dynamic by nature. Starting from different NMR-derived structures, mutants were designed to stabilize a subset of configurations by swapping ion pairs across the protein-protein interface. We focused on two mutants, K956D/D1235K and R957D/D1223R, with attenuated binding affinity compared with the wild-type proteins. In contrast to calculations on the wild-type complexes, the majority of simulations of these mutants showed protein dissociation within 2.4 μs. During the separation process, we observed domain rotation and pivoting as well as a translation and simultaneous rolling, typically to alternate and weaker binding interfaces. Several unsuccessful recapturing attempts occurred once the domains were moderately separated. An analysis of protein solvation suggests that the dissociation process correlates with a progressive loss of protein-protein contacts. Furthermore, an evaluation of internal protein dynamics using quasi-harmonic and order parameter analyses indicates that changes in protein internal motions are expected to contribute significantly to the thermodynamics of protein dissociation. Considering protein association as the reverse of the separation process, the initial role of charged/polar interactions is emphasized, followed by changes in protein and solvent dynamics. The trajectories show that protein separation does not follow a single distinct pathway, but suggest that the mechanism of dissociation is common in that it initially involves transitions to surfaces with fewer, less favorable contacts compared with those seen in the fully formed complex. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Formation of the acrosome complex in the bush cricket Gampsocleis gratiosa (Orthoptera: Tettigoniidae).

PubMed

Su, Cai Xia; Chen, Jie; Shi, Fu Ming; Guo, Ming Shen; Chang, Yan Lin

2017-07-01

The acrosome complex plays an indispensable role in the normal function of mature spermatozoa. However, the dynamic process of acrosome complex formation in insect remains poorly understood. Gampsocleis gratiosa Brunner von Wattenwyl possesses the typical characteristic of insect sperms, which is tractable in terms of size, and therefore was selected for the acrosome formation study in this report. The results show that acrosome formation can be divided into six phases: round, rotating, rhombic, cylindrical, transforming and mature phase, based on the morphological dynamics of acrosome complex and nucleus. In addition, the cytoskeleton plays a critical role in the process of acrosome formation. The results from this study indicate that: (1) glycoprotein is the major component of the acrosome proper; (2) the microfilament is one element of the acrosome complex, and may mediate the morphologic change of the acrosome complex; (3) the microtubules might also shape the nucleus and acrosome complex during the acrosome formation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Heart Rate Dynamics after Combined Strength and Endurance Training in Middle-Aged Women: Heterogeneity of Responses

PubMed Central

Goldberger, Ary L.; Tulppo, Mikko P.; Laaksonen, David E.; Nyman, Kai; Keskitalo, Marko; Häkkinen, Arja; Häkkinen, Keijo

2013-01-01

The loss of complexity in physiological systems may be a dynamical biomarker of aging and disease. In this study the effects of combined strength and endurance training compared with those of endurance training or strength training alone on heart rate (HR) complexity and traditional HR variability indices were examined in middle-aged women. 90 previously untrained female volunteers between the age of 40 and 65 years completed a 21 week progressive training period of either strength training, endurance training or their combination, or served as controls. Continuous HR time series were obtained during supine rest and submaximal steady state exercise. The complexity of HR dynamics was assessed using multiscale entropy analysis. In addition, standard time and frequency domain measures were also computed. Endurance training led to increases in HR complexity and selected time and frequency domain measures of HR variability (P<0.01) when measured during exercise. Combined strength and endurance training or strength training alone did not produce significant changes in HR dynamics. Inter-subject heterogeneity of responses was particularly noticeable in the combined training group. At supine rest, no training-induced changes in HR parameters were observed in any of the groups. The present findings emphasize the potential utility of endurance training in increasing the complex variability of HR in middle-aged women. Further studies are needed to explore the combined endurance and strength training adaptations and possible gender and age related factors, as well as other mechanisms, that may mediate the effects of different training regimens on HR dynamics. PMID:24013586

Backbone dynamics in an intramolecular prolylpeptide-SH3 complex from the diphtheria toxin repressor, DtxR

PubMed Central

Bhattacharya, Nilakshee; Yi, Myunggi; Zhou, Huan-Xiang; Logan, Timothy M.

2008-01-01

Summary The diphtheria toxin repressor contains an SH3-like domain that forms an intramolecular complex with a proline-rich (Pr) peptide segment and stabilizes the inactive state of the repressor. Upon activation of DtxR by transition metals, this intramolecular complex must dissociate as the SH3 domain and Pr segment form different interactions in the active repressor. In this study we investigate the dynamics of this intramolecular complex using backbone amide nuclear spin relaxation rates determined using NMR spectroscopy and molecular dynamics trajectories. The SH3 domain in the unbound and bound states showed typical dynamics in that the secondary structures were fairly ordered with high generalized order parameters and low effective correlation times while residues in the loops connecting β-strands exhibited reduced generalized order parameters and required additional motional terms to adequately model the relaxation rates. Residues forming the Pr segment exhibited low order parameters with internal rotational correlation times on the order of 0.6 – 1 ns. Further analysis showed that the SH3 domain was rich in millisecond timescale motions while the Pr segment was rich in motions on the 100s μs timescale. Molecular dynamics simultations indicated structural rearrangements that may contribute to the observed relaxation rates and, together with the observed relaxation rate data, suggested that the Pr segment exhibits a binding ↔ unbinding equilibrium. The results of this study provide new insights into the nature of the intramolecular complex and provide a better understanding of the biological role of the SH3 domain in regulating DtxR activity. PMID:17976643

Fluctuation-driven price dynamics and investment strategies

PubMed Central

Li, Yan; Zheng, Bo; Chen, Ting-Ting; Jiang, Xiong-Fei

2017-01-01

Investigation of the driven mechanism of the price dynamics in complex financial systems is important and challenging. In this paper, we propose an investment strategy to study how dynamic fluctuations drive the price movements. The strategy is successfully applied to different stock markets in the world, and the result indicates that the driving effect of the dynamic fluctuations is rather robust. We investigate how the strategy performance is influenced by the market states and optimize the strategy performance by introducing two parameters. The strategy is also compared with several typical technical trading rules. Our findings not only provide an investment strategy which extends investors’ profits, but also offer a useful method to look into the dynamic properties of complex financial systems. PMID:29240783

Fluctuation-driven price dynamics and investment strategies.

PubMed

Li, Yan; Zheng, Bo; Chen, Ting-Ting; Jiang, Xiong-Fei

2017-01-01

Investigation of the driven mechanism of the price dynamics in complex financial systems is important and challenging. In this paper, we propose an investment strategy to study how dynamic fluctuations drive the price movements. The strategy is successfully applied to different stock markets in the world, and the result indicates that the driving effect of the dynamic fluctuations is rather robust. We investigate how the strategy performance is influenced by the market states and optimize the strategy performance by introducing two parameters. The strategy is also compared with several typical technical trading rules. Our findings not only provide an investment strategy which extends investors' profits, but also offer a useful method to look into the dynamic properties of complex financial systems.

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

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

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

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

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

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

Complexity, fractal dynamics and determinism in treadmill ambulation: Implications for clinical biomechanists.

PubMed

Hollman, John H; Watkins, Molly K; Imhoff, Angela C; Braun, Carly E; Akervik, Kristen A; Ness, Debra K

2016-08-01

Reduced inter-stride complexity during ambulation may represent a pathologic state. Evidence is emerging that treadmill training for rehabilitative purposes may constrain the locomotor system and alter gait dynamics in a way that mimics pathological states. The purpose of this study was to examine the dynamical system components of gait complexity, fractal dynamics and determinism during treadmill ambulation. Twenty healthy participants aged 23.8 (1.2) years walked at preferred walking speeds for 6min on a motorized treadmill and overground while wearing APDM 6 Opal inertial monitors. Stride times, stride lengths and peak sagittal plane trunk velocities were measured. Mean values and estimates of complexity, fractal dynamics and determinism were calculated for each parameter. Data were compared between overground and treadmill walking conditions. Mean values for each gait parameter were statistically equivalent between overground and treadmill ambulation (P>0.05). Through nonlinear analyses, however, we found that complexity in stride time signals (P<0.001), and long-range correlations in stride time and stride length signals (P=0.005 and P=0.024, respectively), were reduced on the treadmill. Treadmill ambulation induces more predictable inter-stride time dynamics and constrains fluctuations in stride times and stride lengths, which may alter feedback from destabilizing perturbations normally experienced by the locomotor control system during overground ambulation. Treadmill ambulation, therefore, may provide less opportunity for experiencing the adaptability necessary to successfully ambulate overground. Investigators and clinicians should be aware that treadmill ambulation will alter dynamic gait characteristics. Copyright © 2016 Elsevier Ltd. All rights reserved.

What does the structure of its visibility graph tell us about the nature of the time series?

NASA Astrophysics Data System (ADS)

Franke, Jasper G.; Donner, Reik V.

2017-04-01

Visibility graphs are a recently introduced method to construct complex network representations based upon univariate time series in order to study their dynamical characteristics [1]. In the last years, this approach has been successfully applied to studying a considerable variety of geoscientific research questions and data sets, including non-trivial temporal patterns in complex earthquake catalogs [2] or time-reversibility in climate time series [3]. It has been shown that several characteristic features of the thus constructed networks differ between stochastic and deterministic (possibly chaotic) processes, which is, however, relatively hard to exploit in the case of real-world applications. In this study, we propose studying two new measures related with the network complexity of visibility graphs constructed from time series, one being a special type of network entropy [4] and the other a recently introduced measure of the heterogeneity of the network's degree distribution [5]. For paradigmatic model systems exhibiting bifurcation sequences between regular and chaotic dynamics, both properties clearly trace the transitions between both types of regimes and exhibit marked quantitative differences for regular and chaotic dynamics. Moreover, for dynamical systems with a small amount of additive noise, the considered properties demonstrate gradual changes prior to the bifurcation point. This finding appears closely related to the subsequent loss of stability of the current state known to lead to a critical slowing down as the transition point is approaches. In this spirit, both considered visibility graph characteristics provide alternative tracers of dynamical early warning signals consistent with classical indicators. Our results demonstrate that measures of visibility graph complexity (i) provide a potentially useful means to tracing changes in the dynamical patterns encoded in a univariate time series that originate from increasing autocorrelation and (ii) allow to systematically distinguish regular from deterministic-chaotic dynamics. We demonstrate the application of our method for different model systems as well as selected paleoclimate time series from the North Atlantic region. Notably, visibility graph based methods are particularly suited for studying the latter type of geoscientific data, since they do not impose intrinsic restrictions or assumptions on the nature of the time series under investigation in terms of noise process, linearity and sampling homogeneity. [1] Lacasa, Lucas, et al. "From time series to complex networks: The visibility graph." Proceedings of the National Academy of Sciences 105.13 (2008): 4972-4975. [2] Telesca, Luciano, and Michele Lovallo. "Analysis of seismic sequences by using the method of visibility graph." EPL (Europhysics Letters) 97.5 (2012): 50002. [3] Donges, Jonathan F., Reik V. Donner, and Jürgen Kurths. "Testing time series irreversibility using complex network methods." EPL (Europhysics Letters) 102.1 (2013): 10004. [4] Small, Michael. "Complex networks from time series: capturing dynamics." 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), Beijing (2013): 2509-2512. [5] Jacob, Rinku, K.P. Harikrishnan, Ranjeev Misra, and G. Ambika. "Measure for degree heterogeneity in complex networks and its application to recurrence network analysis." arXiv preprint 1605.06607 (2016).

Study of base pair mutations in proline-rich homeodomain (PRH)-DNA complexes using molecular dynamics.

PubMed

Jalili, Seifollah; Karami, Leila; Schofield, Jeremy

2013-06-01

Proline-rich homeodomain (PRH) is a regulatory protein controlling transcription and gene expression processes by binding to the specific sequence of DNA, especially to the sequence 5'-TAATNN-3'. The impact of base pair mutations on the binding between the PRH protein and DNA is investigated using molecular dynamics and free energy simulations to identify DNA sequences that form stable complexes with PRH. Three 20-ns molecular dynamics simulations (PRH-TAATTG, PRH-TAATTA and PRH-TAATGG complexes) in explicit solvent water were performed to investigate three complexes structurally. Structural analysis shows that the native TAATTG sequence forms a complex that is more stable than complexes with base pair mutations. It is also observed that upon mutation, the number and occupancy of the direct and water-mediated hydrogen bonds decrease. Free energy calculations performed with the thermodynamic integration method predict relative binding free energies of 0.64 and 2 kcal/mol for GC to AT and TA to GC mutations, respectively, suggesting that among the three DNA sequences, the PRH-TAATTG complex is more stable than the two mutated complexes. In addition, it is demonstrated that the stability of the PRH-TAATTA complex is greater than that of the PRH-TAATGG complex.

Linking dynamics of the inhibitory network to the input structure

PubMed Central

Komarov, Maxim

2017-01-01

Networks of inhibitory interneurons are found in many distinct classes of biological systems. Inhibitory interneurons govern the dynamics of principal cells and are likely to be critically involved in the coding of information. In this theoretical study, we describe the dynamics of a generic inhibitory network in terms of low-dimensional, simplified rate models. We study the relationship between the structure of external input applied to the network and the patterns of activity arising in response to that stimulation. We found that even a minimal inhibitory network can generate a great diversity of spatio-temporal patterning including complex bursting regimes with non-trivial ratios of burst firing. Despite the complexity of these dynamics, the network’s response patterns can be predicted from the rankings of the magnitudes of external inputs to the inhibitory neurons. This type of invariant dynamics is robust to noise and stable in densely connected networks with strong inhibitory coupling. Our study predicts that the response dynamics generated by an inhibitory network may provide critical insights about the temporal structure of the sensory input it receives. PMID:27650865

Relationship between femtosecond-picosecond dynamics to enzyme catalyzed H-transfer

PubMed Central

Cheatum, Christopher M.; Kohen, Amnon

2015-01-01

At physiological temperatures, enzymes exhibit a broad spectrum of conformations, which interchange via thermally activated dynamics. These conformations are sampled differently in different complexes of the protein and its ligands, and the dynamics of exchange between these conformers depends on the mass of the group that is moving and the length scale of the motion, as well as restrictions imposed by the globular fold of the enzymatic complex. Many of these motions have been examined and their role in the enzyme function illuminated, yet most experimental tools applied so far have identified dynamics at time scales of seconds to nanoseconds, which are much slower than the time scale for H-transfer between two heavy atoms. This chemical conversion and other processes involving cleavage of covalent bonds occur on picosecond to femtosecond time scales, where slower processes mask both the kinetics and dynamics. Here we present a combination of kinetic and spectroscopic methods that may enable closer examination of the relationship between enzymatic C-H→C transfer and the dynamics of the active site environment at the chemically relevant time scale. These methods include kinetic isotope effects and their temperature dependence, which are used to study the kinetic nature of the H-transfer, and 2D IR spectroscopy, which is used to study the dynamics of transition-state- and ground-state-analog complexes. The combination of these tools is likely to provide a new approach to examine the protein dynamics that directly influence the chemical conversion catalyzed by enzymes. PMID:23539379

Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

Perc, Matjaž; Gómez-Gardeñes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir

2013-01-01

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223

Dynamics of harpooning studied by transition state spectroscopy. II. LiṡṡFH

NASA Astrophysics Data System (ADS)

Hudson, A. J.; Oh, H. B.; Polanyi, J. C.; Piecuch, P.

2000-12-01

The van der Waals complex LiṡṡFH was formed in crossed beams and the transition state of the excited-state reaction, Li*(2p 2P)+HF→LiF+H, was accessed by photoexcitation of this complex. The dynamics of the excited-state reaction were probed by varying the excitation wavelength over the range 570-970 nm while recording the photodepletion of the complex. The findings were interpreted using high-level ab initio calculations of the ground and lowest excited-state potential-energy surfaces.

MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*

PubMed Central

CHAHINE, Georges L.; HSIAO, Chao-Tsung

2012-01-01

Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696

Nonphotochemical Hole-Burning Studies of Energy Transfer Dynamics in Antenna Complexes of Photosynthetic Bacteria

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

Matsuzaki, Satoshi

2001-01-01

This thesis contains the candidate's original work on excitonic structure and energy transfer dynamics of two bacterial antenna complexes as studied using spectral hole-burning spectroscopy. The general introduction is divided into two chapters (1 and 2). Chapter 1 provides background material on photosynthesis and bacterial antenna complexes with emphasis on the two bacterial antenna systems related to the thesis research. Chapter 2 reviews the underlying principles and mechanism of persistent nonphotochemical hole-burning (NPHB) spectroscopy. Relevant energy transfer theories are also discussed. Chapters 3 and 4 are papers by the candidate that have been published. Chapter 3 describes the application ofmore » NPHB spectroscopy to the Fenna-Matthews-Olson (FMO) complex from the green sulfur bacterium Prosthecochloris aestuarii; emphasis is on determination of the low energy vibrational structure that is important for understanding the energy transfer process associated within three lowest energy Q y-states of the complex. The results are compared with those obtained earlier on the FMO complex from Chlorobium tepidum. In Chapter 4, the energy transfer dynamics of the B800 molecules of intact LH2 and B800-deficient LH2 complexes of the purple bacterium Rhodopseudomonas acidophila are compared. New insights on the additional decay channel of the B800 ring of bacteriochlorophyll a (BChl a) molecules are provided. General conclusions are given in Chapter 5. A version of the hole spectrum simulation program written by the candidate for the FMO complex study (Chapter 3) is included as an appendix. The references for each chapter are given at the end of each chapter.« less

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

PubMed

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

2015-12-01

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

Characterization of Combustion Dynamics, Detection, and Prevention of an Unstable Combustion State Based on a Complex-Network Theory

NASA Astrophysics Data System (ADS)

Gotoda, Hiroshi; Kinugawa, Hikaru; Tsujimoto, Ryosuke; Domen, Shohei; Okuno, Yuta

2017-04-01

Complex-network theory has attracted considerable attention for nearly a decade, and it enables us to encompass our understanding of nonlinear dynamics in complex systems in a wide range of fields, including applied physics and mechanical, chemical, and electrical engineering. We conduct an experimental study using a pragmatic online detection methodology based on complex-network theory to prevent a limiting unstable state such as blowout in a confined turbulent combustion system. This study introduces a modified version of the natural visibility algorithm based on the idea of a visibility limit to serve as a pragmatic online detector. The average degree of the modified version of the natural visibility graph allows us to detect the onset of blowout, resulting in online prevention.

Dynamic Frequency Shifts of Complexed Ligands: An NMR Study of D-[1- 13C,1- 2H]Glucose Complexed to the Escherichia coliPeriplasmic Glucose/Galactose Receptor

NASA Astrophysics Data System (ADS)

Gabel, Scott A.; Luck, Linda A.; Werbelow, Lawrence G.; London, Robert E.

1997-10-01

The13C multiplet structure ofD-[1-13C,1-2H]glucose complexed to theEscherichia coliperiplasmic glucose/galactose receptor has been studied as a function of temperature. Asymmetric multiplet patterns observed are shown to arise from dynamic frequency shifts. Multiplet asymmetry contributions resulting from shift anisotropy-dipolar cross correlations were found to be small, with optimal fits of the data corresponding to small, negative values of the correlation factor, χCD-CSA. Additional broadening at higher temperatures most probably results from ligand exchange between free and complexed states. Effects of internal motion are also considered theoretically, and indicate that the order parameter for the bound glucose is ≥0.9.

Turbulent complex (dusty) plasma

NASA Astrophysics Data System (ADS)

Zhdanov, Sergey; Schwabe, Mierk

2017-04-01

As a paradigm of complex system dynamics, solid particles immersed into a weakly ionized plasma, so called complex (dusty) plasmas, were (and continue to be) a subject of many detailed studies. Special types of dynamical activity have been registered, in particular, spontaneous pairing, entanglement and cooperative action of a great number of particles resulting in formation of vortices, self-propelling, tunneling, and turbulent movements. In the size domain of 1-10 mkm normally used in experiments with complex plasmas, the characteristic dynamic time-scale is of the order of 0.01-0.1 s, and these particles can be visualized individually in real time, providing an atomistic (kinetic) level of investigations. The low-R turbulent flow induced either by the instability in a complex plasma cloud or formed behind a projectile passing through the cloud is a typical scenario. Our simulations showed formation of a fully developed system of vortices and demonstrated that the velocity structure functions scale very close to the theoretical predictions. As an important element of self-organization, cooperative and turbulent particle motions are present in many physical, astrophysical, and biological systems. Therefore, experiments with turbulent wakes and turbulent complex plasma oscillations are a promising mean to observe and study in detail the anomalous transport on the level of individual particles.

Unraveling dynamics of human physical activity patterns in chronic pain conditions

NASA Astrophysics Data System (ADS)

Paraschiv-Ionescu, Anisoara; Buchser, Eric; Aminian, Kamiar

2013-06-01

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a `signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

Dynamic resource allocation in a hierarchical multiprocessor system: A preliminary study

NASA Technical Reports Server (NTRS)

Ngai, Tin-Fook

1986-01-01

An integrated system approach to dynamic resource allocation is proposed. Some of the problems in dynamic resource allocation and the relationship of these problems to system structures are examined. A general dynamic resource allocation scheme is presented. A hierarchial system architecture which dynamically maps between processor structure and programs at multiple levels of instantiations is described. Simulation experiments were conducted to study dynamic resource allocation on the proposed system. Preliminary evaluation based on simple dynamic resource allocation algorithms indicates that with the proposed system approach, the complexity of dynamic resource management could be significantly reduced while achieving reasonable effective dynamic resource allocation.

How proteins bind to DNA: target discrimination and dynamic sequence search by the telomeric protein TRF1

PubMed Central

2017-01-01

Abstract Target search as performed by DNA-binding proteins is a complex process, in which multiple factors contribute to both thermodynamic discrimination of the target sequence from overwhelmingly abundant off-target sites and kinetic acceleration of dynamic sequence interrogation. TRF1, the protein that binds to telomeric tandem repeats, faces an intriguing variant of the search problem where target sites are clustered within short fragments of chromosomal DNA. In this study, we use extensive (>0.5 ms in total) MD simulations to study the dynamical aspects of sequence-specific binding of TRF1 at both telomeric and non-cognate DNA. For the first time, we describe the spontaneous formation of a sequence-specific native protein–DNA complex in atomistic detail, and study the mechanism by which proteins avoid off-target binding while retaining high affinity for target sites. Our calculated free energy landscapes reproduce the thermodynamics of sequence-specific binding, while statistical approaches allow for a comprehensive description of intermediate stages of complex formation. PMID:28633355

Evidence of complex contagion of information in social media: An experiment using Twitter bots.

PubMed

Mønsted, Bjarke; Sapieżyński, Piotr; Ferrara, Emilio; Lehmann, Sune

2017-01-01

It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using 'social bots' deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques.

The RNA polymerase clamp interconverts dynamically among three states and is stabilized in a partly closed state by ppGpp.

PubMed

Duchi, Diego; Mazumder, Abhishek; Malinen, Anssi M; Ebright, Richard H; Kapanidis, Achillefs N

2018-06-06

RNA polymerase (RNAP) contains a mobile structural module, the 'clamp,' that forms one wall of the RNAP active-center cleft and that has been linked to crucial aspects of the transcription cycle, including promoter melting, transcription elongation complex stability, transcription pausing, and transcription termination. Using single-molecule FRET on surface-immobilized RNAP molecules, we show that the clamp in RNAP holoenzyme populates three distinct conformational states and interconvert between these states on the 0.1-1 s time-scale. Similar studies confirm that the RNAP clamp is closed in open complex (RPO) and in initial transcribing complexes (RPITC), including paused initial transcribing complexes, and show that, in these complexes, the clamp does not exhibit dynamic behaviour. We also show that, the stringent-response alarmone ppGpp, which reprograms transcription during amino acid starvation stress, selectively stabilizes the partly-closed-clamp state and prevents clamp opening; these results raise the possibility that ppGpp controls promoter opening by modulating clamp dynamics.

Double symbolic joint entropy in nonlinear dynamic complexity analysis

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-07-01

Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

PubMed Central

Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

2013-01-01

Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform. PMID:23843732

The electronically excited states of LH2 complexes from Rhodopseudomonas acidophila strain 10050 studied by time-resolved spectroscopy and dynamic Monte Carlo simulations. I. Isolated, non-interacting LH2 complexes.

PubMed

Pflock, Tobias J; Oellerich, Silke; Southall, June; Cogdell, Richard J; Ullmann, G Matthias; Köhler, Jürgen

2011-07-21

We have employed time-resolved spectroscopy on the picosecond time scale in combination with dynamic Monte Carlo simulations to investigate the photophysical properties of light-harvesting 2 (LH2) complexes from the purple photosynthetic bacterium Rhodopseudomonas acidophila. The variations of the fluorescence transients were studied as a function of the excitation fluence, the repetition rate of the excitation and the sample preparation conditions. Here we present the results obtained on detergent solubilized LH2 complexes, i.e., avoiding intercomplex interactions, and show that a simple four-state model is sufficient to grasp the experimental observations quantitatively without the need for any free parameters. This approach allows us to obtain a quantitative measure for the singlet-triplet annihilation rate in isolated, noninteracting LH2 complexes.

A Framework for Simulating Turbine-Based Combined-Cycle Inlet Mode-Transition

NASA Technical Reports Server (NTRS)

Le, Dzu K.; Vrnak, Daniel R.; Slater, John W.; Hessel, Emil O.

2012-01-01

A simulation framework based on the Memory-Mapped-Files technique was created to operate multiple numerical processes in locked time-steps and send I/O data synchronously across to one-another to simulate system-dynamics. This simulation scheme is currently used to study the complex interactions between inlet flow-dynamics, variable-geometry actuation mechanisms, and flow-controls in the transition from the supersonic to hypersonic conditions and vice-versa. A study of Mode-Transition Control for a high-speed inlet wind-tunnel model with this MMF-based framework is presented to illustrate this scheme and demonstrate its usefulness in simulating supersonic and hypersonic inlet dynamics and controls or other types of complex systems.

The MYO6 interactome reveals adaptor complexes coordinating early endosome and cytoskeletal dynamics.

PubMed

O'Loughlin, Thomas; Masters, Thomas A; Buss, Folma

2018-04-01

The intracellular functions of myosin motors requires a number of adaptor molecules, which control cargo attachment, but also fine-tune motor activity in time and space. These motor-adaptor-cargo interactions are often weak, transient or highly regulated. To overcome these problems, we use a proximity labelling-based proteomics strategy to map the interactome of the unique minus end-directed actin motor MYO6. Detailed biochemical and functional analysis identified several distinct MYO6-adaptor modules including two complexes containing RhoGEFs: the LIFT (LARG-Induced F-actin for Tethering) complex that controls endosome positioning and motility through RHO-driven actin polymerisation; and the DISP (DOCK7-Induced Septin disPlacement) complex, a novel regulator of the septin cytoskeleton. These complexes emphasise the role of MYO6 in coordinating endosome dynamics and cytoskeletal architecture. This study provides the first in vivo interactome of a myosin motor protein and highlights the power of this approach in uncovering dynamic and functionally diverse myosin motor complexes. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Dynamic torsional motion of a diruthenium complex with four homo-catecholates and first synthesis of a diruthenium complex with mixed-catecholates

NASA Astrophysics Data System (ADS)

Chang, Ho-Chol; Mochizuki, Katsunori; Kitagawa, Susumu

2008-11-01

Dynamic properties of a diruthenium complex with ligand-unsupported Ru-Ru triple bonds, Na 2[Ru 2(3,6-DTBCat) 4] ( 1), were studied using variable-temperature 1H NMR. Structural freedom derived from the ligand-unsupported structure leads to torsional motion about the Ru-Ru bonds in THF and in DMF. The observed solvent dependency corresponds to the electrostatic interactions between the diruthenium complex and Na + counter cations, which are sensitive to the polarity of solvents. In addition, a new diruthenium complex, [{Na(THF) 2(H 2O)}{Na(THF) 0.5(H 2O)}{Ru 2(3,6-DTBCat) 2(H 4Cat) 2}] ( 2·2.5THF·2H 2O), with a ligand-unsupported Ru-Ru bond surrounded by two different kinds of catecholate derivatives, has been synthesized and crystallographically characterized. The complex, which was characterized by single-crystal structural analysis, will provide an opportunity to investigate not only static molecular structures but also dynamic physicochemical properties in comparison with analogues containing four identical catecholate derivatives.

Characterization of local complex structures in a recurrence plot to improve nonlinear dynamic discriminant analysis.

PubMed

Ding, Hang

2014-01-01

Structures in recurrence plots (RPs), preserving the rich information of nonlinear invariants and trajectory characteristics, have been increasingly analyzed in dynamic discrimination studies. The conventional analysis of RPs is mainly focused on quantifying the overall diagonal and vertical line structures through a method, called recurrence quantification analysis (RQA). This study extensively explores the information in RPs by quantifying local complex RP structures. To do this, an approach was developed to analyze the combination of three major RQA variables: determinism, laminarity, and recurrence rate (DLR) in a metawindow moving over a RP. It was then evaluated in two experiments discriminating (1) ideal nonlinear dynamic series emulated from the Lorenz system with different control parameters and (2) data sets of human heart rate regulations with normal sinus rhythms (n = 18) and congestive heart failure (n = 29). Finally, the DLR was compared with seven major RQA variables in terms of discriminatory power, measured by standardized mean difference (DSMD). In the two experiments, DLR resulted in the highest discriminatory power with DSMD = 2.53 and 0.98, respectively, which were 7.41 and 2.09 times the best performance from RQA. The study also revealed that the optimal RP structures for the discriminations were neither typical diagonal structures nor vertical structures. These findings indicate that local complex RP structures contain some rich information unexploited by RQA. Therefore, future research to extensively analyze complex RP structures would potentially improve the effectiveness of the RP analysis in dynamic discrimination studies.

Dynamic Development of Complexity and Accuracy: A Case Study in Second Language Academic Writing

ERIC Educational Resources Information Center

Rosmawati

2014-01-01

This paper reports on the development of complexity and accuracy in English as a Second Language (ESL) academic writing. Although research into complexity and accuracy development in second language (L2) writing has been well established, few studies have assumed the multidimensionality of these two constructs (Norris & Ortega, 2009) or…

Preictal dynamics of EEG complexity in intracranially recorded epileptic seizure: a case report.

PubMed

Bob, Petr; Roman, Robert; Svetlak, Miroslav; Kukleta, Miloslav; Chladek, Jan; Brazdil, Milan

2014-11-01

Recent findings suggest that neural complexity reflecting a number of independent processes in the brain may characterize typical changes during epileptic seizures and may enable to describe preictal dynamics. With respect to previously reported findings suggesting specific changes in neural complexity during preictal period, we have used measure of pointwise correlation dimension (PD2) as a sensitive indicator of nonstationary changes in complexity of the electroencephalogram (EEG) signal. Although this measure of complexity in epileptic patients was previously reported by Feucht et al (Applications of correlation dimension and pointwise dimension for non-linear topographical analysis of focal onset seizures. Med Biol Comput. 1999;37:208-217), it was not used to study changes in preictal dynamics. With this aim to study preictal changes of EEG complexity, we have examined signals from 11 multicontact depth (intracerebral) EEG electrodes located in 108 cortical and subcortical brain sites, and from 3 scalp EEG electrodes in a patient with intractable epilepsy, who underwent preoperative evaluation before epilepsy surgery. From those 108 EEG contacts, records related to 44 electrode contacts implanted into lesional structures and white matter were not included into the experimental analysis.The results show that in comparison to interictal period (at about 8-6 minutes before seizure onset), there was a statistically significant decrease in PD2 complexity in the preictal period at about 2 minutes before seizure onset in all 64 intracranial channels localized in various brain sites that were included into the analysis and in 3 scalp EEG channels as well. Presented results suggest that using PD2 in EEG analysis may have significant implications for research of preictal dynamics and prediction of epileptic seizures.

Complex quantum Hamilton-Jacobi equation with Bohmian trajectories: Application to the photodissociation dynamics of NOCl

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

Chou, Chia-Chun, E-mail: ccchou@mx.nthu.edu.tw

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 simultaneouslymore » 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.« less

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

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

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 motifmore » 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.« less

Dynamic Skin Patterns in Cephalopods

PubMed Central

How, Martin J.; Norman, Mark D.; Finn, Julian; Chung, Wen-Sung; Marshall, N. Justin

2017-01-01

Cephalopods are unrivaled in the natural world in their ability to alter their visual appearance. These mollusks have evolved a complex system of dermal units under neural, hormonal, and muscular control to produce an astonishing variety of body patterns. With parallels to the pixels on a television screen, cephalopod chromatophores can be coordinated to produce dramatic, dynamic, and rhythmic displays, defined collectively here as “dynamic patterns.” This study examines the nature, context, and potential functions of dynamic patterns across diverse cephalopod taxa. Examples are presented for 21 species, including 11 previously unreported in the scientific literature. These range from simple flashing or flickering patterns, to highly complex passing wave patterns involving multiple skin fields. PMID:28674500

Molecular dynamic simulation of weakly magnetized complex plasmas

NASA Astrophysics Data System (ADS)

Funk, Dylan; Konopka, Uwe; Thomas, Edward

2017-10-01

A complex plasma consists of the usual plasma components (electrons, ions and neutrals), as well as a heavier component made of solid, micrometer-sized particles. The particles are in general highly charged as a result of the interaction with the other plasma components. The static and dynamic properties of a complex plasma such as its crystal structure or wave properties are influenced by many forces acting on the individual particles such as the dust particle interaction (a screened Coulomb interaction), neutral (Epstein) drag, the particle inertia and various plasma drag or thermophoretic forces. To study the behavior of complex plasmas we setup an experiment accompanying molecular dynamic simulation. We will present the approach taken in our simulation and give an overview of experimental situations that we want to cover with our simulation such as the particle charge under microgravity condition as performed on the PK-4 space experiment, or to study the detailed influences of high magnetic fields. This work was supported by the US Dept. of Energy (DE-SC0016330), NSF (PHY-1613087) and JPL/NASA (JPL-RSA 1571699).

Cooperative particle motion in complex (dusty) plasmas

NASA Astrophysics Data System (ADS)

Zhdanov, Sergey; Morfill, Gregor

2014-05-01

Strongly coupled complex (dusty) plasmas give us a unique opportunity to go beyond the limits of continuous media and study various generic processes occurring in liquids or solids at the kinetic level. A particularly interesting and challenging topic is to study dynamic cooperativity at local and intermediate scales. As an important element of self-organization, cooperative particle motion is present in many physical, astrophysical and biological systems. As a rule, cooperative dynamics, bringing to life 'abnormal' effects like enhanced diffusion, self-dragging, or self-propelling of particles, hold aspects of 'strange' kinetics. The synergy effects are also important. Such kind of cooperative behavior was evidenced for string-like formations of colloidal rods, dynamics of mono- and di-vacancies in 2d colloidal crystals. Externally manipulated 'dust molecules' and self-assembled strings in driven 3d particle clusters were other noticeable examples. There is a certain advantage to experiment with complex plasmas merely because these systems are easy to manipulate in a controllable way. We report on the first direct observation of microparticle cooperative movements occurring under natural conditions in a 2d complex plasma.

Observing Consistency in Online Communication Patterns for User Re-Identification.

PubMed

Adeyemi, Ikuesan Richard; Razak, Shukor Abd; Salleh, Mazleena; Venter, Hein S

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

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

PubMed

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

2017-01-02

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

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade

NASA Astrophysics Data System (ADS)

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-01

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade.

PubMed

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-28

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

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

Beverton-Holt discrete pest management models with pulsed chemical control and evolution of pesticide resistance

NASA Astrophysics Data System (ADS)

Liang, Juhua; Tang, Sanyi; Cheke, Robert A.

2016-07-01

Pest resistance to pesticides is usually managed by switching between different types of pesticides. The optimal switching time, which depends on the dynamics of the pest population and on the evolution of the pesticide resistance, is critical. Here we address how the dynamic complexity of the pest population, the development of resistance and the spraying frequency of pulsed chemical control affect optimal switching strategies given different control aims. To do this, we developed novel discrete pest population growth models with both impulsive chemical control and the evolution of pesticide resistance. Strong and weak threshold conditions which guarantee the extinction of the pest population, based on the threshold values of the analytical formula for the optimal switching time, were derived. Further, we addressed switching strategies in the light of chosen economic injury levels. Moreover, the effects of the complex dynamical behaviour of the pest population on the pesticide switching times were also studied. The pesticide application period, the evolution of pesticide resistance and the dynamic complexity of the pest population may result in complex outbreak patterns, with consequent effects on the pesticide switching strategies.

Drop formation, pinch-off dynamics and liquid transfer of simple and complex fluids

NASA Astrophysics Data System (ADS)

Dinic, Jelena; Sharma, Vivek

Liquid transfer and drop formation processes underlying jetting, spraying, coating, and printing - inkjet, screen, roller-coating, gravure, nanoimprint hot embossing, 3D - often involve formation of unstable columnar necks. Capillary-driven thinning of such necks and their pinchoff dynamics are determined by a complex interplay of inertial, viscous and capillary stresses for simple, Newtonian fluids. Micro-structural changes in response to extensional flow field that arises within the thinning neck give rise to additional viscoelastic stresses in complex, non- Newtonian fluids. Using FLOW-3D, we simulate flows realized in prototypical geometries (dripping and liquid bridge stretched between two parallel plates) used for studying pinch-off dynamics and influence of microstructure and viscoelasticity. In contrast with often-used 1D or 2D models, FLOW-3D allows a robust evaluation of the magnitude of the underlying stresses and extensional flow field (both uniformity and magnitude). We find that the simulated radius evolution profiles match the pinch-off dynamics that are experimentally-observed and theoretically-predicted for model Newtonian fluids and complex fluids.

Theoretical and Experimental Study of Inclusion Complexes of β-Cyclodextrins with Chalcone and 2',4'-Dihydroxychalcone.

PubMed

Sancho, Matias I; Andujar, Sebastian; Porasso, Rodolfo D; Enriz, Ricardo D

2016-03-31

The inclusion complexes formed by chalcone and 2',4'-dihydroxychalcone with β-cyclodextrin have been studied combining experimental (phase solubility diagrams, Fourier transform infrared spectroscopy) and molecular modeling (molecular dynamics, quantum mechanics/molecular mechanics calculations) techniques. The formation constants of the complexes were determined at different temperatures, and the thermodynamic parameters of the process were obtained. The inclusion of chalcone in β-cyclodextrin is an exothermic process, while the inclusion of 2',4'-dihydroxychalcone is endothermic. Free energy profiles, derived from umbrella sampling using molecular dynamics simulations, were constructed to analyze the binding affinity and the complexation reaction at a molecular level. Hybrid QM/MM calculations were also employed to obtain a better description of the energetic and structural aspects of the complexes. The intermolecular interactions that stabilize both inclusion complexes were characterized by means of quantum atoms in molecules theory and reduce density gradient method. The calculated interactions were experimentally observed using FTIR.

Single-Molecule Spectroscopy and Imaging Studies of Protein Dynamics

NASA Astrophysics Data System (ADS)

Lu, H. Peter

2012-04-01

Enzymatic reactions and protein-protein interactions are traditionally studied at the ensemble level, despite significant static and dynamic inhomogeneities. Subtle conformational changes play a crucial role in protein functions, and these protein conformations are highly dynamic rather than being static. We applied AFM-enhanced single-molecule spectroscopy to study the mechanisms and dynamics of enzymatic reactions involved with kinase and lysozyme proteins. Enzymatic reaction turnovers and the associated structure changes of individual protein molecules were observed simultaneously in real-time by single-molecule FRET detections. Our single-molecule spectroscopy measurements of T4 lysozyme and HPPK enzymatic conformational dynamics have revealed time bunching effect and intermittent coherence in conformational state change dynamics involving in enzymatic reaction cycles. The coherent conformational state dynamics suggests that the enzymatic catalysis involves a multi-step conformational motion along the coordinates of substrate-enzyme complex formation and product releasing, presenting as an extreme dynamic behavior intrinsically related to the time bunching effect that we have reported previously. Our results of HPPK interaction with substrate support a multiple-conformational state model, being consistent with a complementary conformation selection and induced-fit enzymatic loop-gated conformational change mechanism in substrate-enzyme active complex formation. Our new approach is applicable to a wide range of single-molecule FRET measurements for protein conformational changes under enzymatic reactions.

Complex systems: physics beyond physics

NASA Astrophysics Data System (ADS)

Holovatch, Yurij; Kenna, Ralph; Thurner, Stefan

2017-03-01

Complex systems are characterised by specific time-dependent interactions among their many constituents. As a consequence they often manifest rich, non-trivial and unexpected behaviour. Examples arise both in the physical and non-physical worlds. The study of complex systems forms a new interdisciplinary research area that cuts across physics, biology, ecology, economics, sociology, and the humanities. In this paper we review the essence of complex systems from a physicists' point of view, and try to clarify what makes them conceptually different from systems that are traditionally studied in physics. Our goal is to demonstrate how the dynamics of such systems may be conceptualised in quantitative and predictive terms by extending notions from statistical physics and how they can often be captured in a framework of co-evolving multiplex network structures. We mention three areas of complex-systems science that are currently studied extensively, the science of cities, dynamics of societies, and the representation of texts as evolutionary objects. We discuss why these areas form complex systems in the above sense. We argue that there exists plenty of new ground for physicists to explore and that methodical and conceptual progress is needed most.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

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

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

Rundle, John B.; Klein, William

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.

Synchronization and Causality Across Time-scales: Complex Dynamics and Extremes in El Niño/Southern Oscillation

NASA Astrophysics Data System (ADS)

Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.

2017-12-01

A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.

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.

Synchronization and chaotic dynamics of coupled mechanical metronomes

NASA Astrophysics Data System (ADS)

Ulrichs, Henning; Mann, Andreas; Parlitz, Ulrich

2009-12-01

Synchronization scenarios of coupled mechanical metronomes are studied by means of numerical simulations showing the onset of synchronization for two, three, and 100 globally coupled metronomes in terms of Arnol'd tongues in parameter space and a Kuramoto transition as a function of coupling strength. Furthermore, we study the dynamics of metronomes where overturning is possible. In this case hyperchaotic dynamics associated with some diffusion process in configuration space is observed, indicating the potential complexity of metronome dynamics.

Emotional effects of dynamic textures

PubMed Central

Toet, Alexander; Henselmans, Menno; Lucassen, Marcel P; Gevers, Theo

2011-01-01

This study explores the effects of various spatiotemporal dynamic texture characteristics on human emotions. The emotional experience of auditory (eg, music) and haptic repetitive patterns has been studied extensively. In contrast, the emotional experience of visual dynamic textures is still largely unknown, despite their natural ubiquity and increasing use in digital media. Participants watched a set of dynamic textures, representing either water or various different media, and self-reported their emotional experience. Motion complexity was found to have mildly relaxing and nondominant effects. In contrast, motion change complexity was found to be arousing and dominant. The speed of dynamics had arousing, dominant, and unpleasant effects. The amplitude of dynamics was also regarded as unpleasant. The regularity of the dynamics over the textures' area was found to be uninteresting, nondominant, mildly relaxing, and mildly pleasant. The spatial scale of the dynamics had an unpleasant, arousing, and dominant effect, which was larger for textures with diverse content than for water textures. For water textures, the effects of spatial contrast were arousing, dominant, interesting, and mildly unpleasant. None of these effects were observed for textures of diverse content. The current findings are relevant for the design and synthesis of affective multimedia content and for affective scene indexing and retrieval. PMID:23145257

Exponential rise of dynamical complexity in quantum computing through projections.

PubMed

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

2014-10-10

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.

Management of complex dynamical systems

NASA Astrophysics Data System (ADS)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

Probing Biomolecular Structures and Dynamics of Single Molecules Using In-Gel Alternating-Laser Excitation

PubMed Central

Santoso, Yusdi; Kapanidis, Achillefs N.

2009-01-01

Gel electrophoresis is a standard biochemical technique used for separating biomolecules on the basis of size and charge. Despite the use of gels in early single-molecule experiments, gel electrophoresis has not been widely adopted for single-molecule fluorescence spectroscopy. We present a novel method that combines gel electrophoresis and single-molecule fluorescence spectroscopy to simultaneously purify and analyze biomolecules in a gel matrix. Our method, in-gel ALEX, uses non-denaturing gels to purify biomolecular complexes of interest from free components, aggregates, and non-specific complexes. The gel matrix also slows down translational diffusion of molecules, giving rise to long, high-resolution time traces without surface immobilization, which allow extended observations of conformational dynamics in a biologically friendly environment. We demonstrated the compatibility of this method with different types of single molecule spectroscopy techniques, including confocal detection and fluorescence-correlation spectroscopy. We demonstrated that in-gel ALEX can be used to study conformational dynamics at the millisecond timescale; by studying a DNA hairpin in gels, we directly observed fluorescence fluctuations due to conformational interconversion between folded and unfolded states. Our method is amenable to the addition of small molecules that can alter the equilibrium and dynamic properties of the system. In-gel ALEX will be a versatile tool for studying structures and dynamics of complex biomolecules and their assemblies. PMID:19863108

Epidemic threshold of the susceptible-infected-susceptible model on complex networks

NASA Astrophysics Data System (ADS)

Lee, Hyun Keun; Shim, Pyoung-Seop; Noh, Jae Dong

2013-06-01

We demonstrate that the susceptible-infected-susceptible (SIS) model on complex networks can have an inactive Griffiths phase characterized by a slow relaxation dynamics. It contrasts with the mean-field theoretical prediction that the SIS model on complex networks is active at any nonzero infection rate. The dynamic fluctuation of infected nodes, ignored in the mean field approach, is responsible for the inactive phase. It is proposed that the question whether the epidemic threshold of the SIS model on complex networks is zero or not can be resolved by the percolation threshold in a model where nodes are occupied in degree-descending order. Our arguments are supported by the numerical studies on scale-free network models.

Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems

NASA Astrophysics Data System (ADS)

Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.

2018-01-01

The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.

Comparison of Laminar and Linear Eddy Model Closures for Combustion Instability Simulations

DTIC Science & Technology

2015-07-01

14. ABSTRACT Unstable liquid rocket engines can produce highly complex dynamic flowfields with features such as rapid changes in temperature and...applicability. In the present study, the linear eddy model (LEM) is applied to an unstable single element liquid rocket engine to assess its performance and to...Sankaran‡ Air Force Research Laboratory, Edwards AFB, CA, 93524 Unstable liquid rocket engines can produce highly complex dynamic flowfields with features

Linear and non-linear contributions to oxygen transport and utilization during moderate random exercise in humans.

PubMed

Beltrame, T; Hughson, R L

2017-05-01

What is the central question of this study? The pulmonary oxygen uptake (pV̇O2) data used to study the muscle aerobic system dynamics during moderate-exercise transitions is classically described as a mono-exponential function controlled by a complex interaction of the oxygen delivery-utilization balance. This elevated complexity complicates the acquisition of relevant information regarding aerobic system dynamics based on pV̇O2 data during a varying exercise stimulus. What is the main finding and its importance? The elevated complexity of pV̇O2 dynamics is a consequence of a multiple-order interaction between muscle oxygen uptake and circulatory distortion. Our findings challenge the use of a first-order function to study the influences of the oxygen delivery-utilization balance over the pV̇O2 dynamics. The assumption of aerobic system linearity implies that the pulmonary oxygen uptake (pV̇O2) dynamics during exercise transitions present a first-order characteristic. The main objective of this study was to test the linearity of the oxygen delivery-utilization balance during random moderate exercise. The cardiac output (Q̇) and deoxygenated haemoglobin concentration ([HHb]) were measured to infer the central and local O 2 availability, respectively. Thirteen healthy men performed two consecutive pseudorandom binary sequence cycling exercises followed by an incremental protocol. The system input and the outputs pV̇O2, [HHb] and Q̇ were submitted to frequency-domain analysis. The linearity of the variables was tested by computing the ability of the response at a specific frequency to predict the response at another frequency. The predictability levels were assessed by the coefficient of determination. In a first-order system, a participant who presents faster dynamics at a specific frequency should also present faster dynamics at any other frequency. All experimentally obtained variables (pV̇O2, [HHb] and Q̇) presented a certainly degree of non-linearity. The local O 2 availability, evaluated by the ratio pV̇O2/[HHb], presented the most irregular behaviour. The overall [HHb] kinetics were faster than pV̇O2 and Q̇ kinetics. In conclusion, the oxygen delivery-utilization balance behaved as a non-linear phenomenon. Therefore, the elevated complexity of the pulmonary oxygen uptake dynamics is governed by a complex multiple-order interaction between the oxygen delivery and utilization systems. © 2017 The Authors. Experimental Physiology © 2017 The Physiological Society.

Using activity theory to study cultural complexity in medical education.

PubMed

Frambach, Janneke M; Driessen, Erik W; van der Vleuten, Cees P M

2014-06-01

There is a growing need for research on culture, cultural differences and cultural effects of globalization in medical education, but these are complex phenomena to investigate. Socio-cultural activity theory seems a useful framework to study cultural complexity, because it matches current views on culture as a dynamic process situated in a social context, and has been valued in diverse fields for yielding rich understandings of complex issues and key factors involved. This paper explains how activity theory can be used in (cross-)cultural medical education research. We discuss activity theory's theoretical background and principles, and we show how these can be applied to the cultural research practice by discussing the steps involved in a cross-cultural study that we conducted, from formulating research questions to drawing conclusions. We describe how the activity system, the unit of analysis in activity theory, can serve as an organizing principle to grasp cultural complexity. We end with reflections on the theoretical and practical use of activity theory for cultural research and note that it is not a shortcut to capture cultural complexity: it is a challenge for researchers to determine the boundaries of their study and to analyze and interpret the dynamics of the activity system.

[Dynamic paradigm in psychopathology: "chaos theory", from physics to psychiatry].

PubMed

Pezard, L; Nandrino, J L

2001-01-01

For the last thirty years, progress in the field of physics, known as "Chaos theory"--or more precisely: non-linear dynamical systems theory--has increased our understanding of complex systems dynamics. This framework's formalism is general enough to be applied in other domains, such as biology or psychology, where complex systems are the rule rather than the exception. Our goal is to show here that this framework can become a valuable tool in scientific fields such as neuroscience and psychiatry where objects possess natural time dependency (i.e. dynamical properties) and non-linear characteristics. The application of non-linear dynamics concepts on these topics is more precise than a loose metaphor and can throw a new light on mental functioning and dysfunctioning. A class of neural networks (recurrent neural networks) constitutes an example of the implementation of the dynamical system concept and provides models of cognitive processes (15). The state of activity of the network is represented in its state space and the time evolution of this state is a trajectory in this space. After a period of time those networks settle on an equilibrium (a kind of attractor). The strength of connections between neurons define the number and relations between those attractors. The attractors of the network are usually interpreted as "mental representations". When an initial condition is imposed to the network, the evolution towards an attractor is considered as a model of information processing (27). This information processing is not defined in a symbolic manner but is a result of the interaction between distributed elements. Several properties of dynamical models can be used to define a way where the symbolic properties emerge from physical and dynamical properties (28) and thus they can be candidates for the definition of the emergence of mental properties on the basis of neuronal dynamics (42). Nevertheless, mental properties can also be considered as the result of an underlying dynamics without explicit mention of the neuronal one (47). In that case, dynamical tools can be used to elucidate the Freudian psychodynamics (34, 35). Recurrent neuronal networks have been used to propose interpretation of several mental dysfunctions (12). For example in the case of schizophrenia, it has been proposed that troubles in the cortical pruning during development (13) may cause a decrease in neural network storage ability and lead to the creation of spurious attractors. Those attractors do not correspond to stored memories and attract a large amount of initial conditions: they were thus associated to reality distorsion observed in schizophrenia (14). Nevertheless, the behavior of these models are too simple to be directly compared with real physiological data. In fact, equilibrium attractors are hardly met in biological dynamics. More complex behaviors (such as oscillations or chaos) should thus to be taken into account. The study of chaotic behavior have lead to the development of numerical methods devoted to the analysis of complex time series (17). These methods may be used to characterise the dynamical processes at the time-scales of both the cerebral dynamics and the clinical symptoms variations. The application of these methods to physiological signals have shown that complex behaviors are related to healthy states whereas simple dynamics are related to pathology (8). These studies have thus confirmed the notion of "dynamical disease" (20, 21) which denotes pathological conditions characterised by changes in physiological rhythms. Depression has been studied within this framework (25, 32) in order to define possible changes in brain electrical rhythms related to this trouble and its evolution. It has been shown that controls' brain dynamics is more complex than depressive one and that the recovery of a complex brain activity depends on the number of previous episodes. In the case of the symptoms time evolution, several studies have demonstrated that non-linear dynamical process may be involved in the recurrence of symptoms in troubles such as manic-depressive illness (9) or schizophrenia (51). These observations can contribute to more parcimonious interpretation of the time course of these illnesses than usual theories. In the search of a relationship between brain dynamics and mental troubles, it has been shown in three depressed patients an important correlation between the characteristics of brain dynamics and the intensity of depressive mood (49). This preliminary observation is in accordance with the emergence hypothesis according which changes in neuronal dynamics should be related to changes in mental processes. We reviewed here some theoretical and experimental results related to the use of "physical" dynamical theory in the field of psychopathology. It has been argued that these applications go beyond metaphor and that they are empirically founded. Nevertheless, these studies only constitute first steps on the way of a cautious development and definition of a "dynamical paradigm" in psychopathology. The introduction of concepts from dynamics such as complexity and dynamical changes (i.e. bifurcations) permits a new perspective on function and dysfunction of the mind/brain and the time evolution of symptoms. Moreover, it offers a ground for the hypothesis of the emergence of mental properties on the basis of neuronal dynamics (42). Since this theory can help to throw light on classical problems in psychopathology, we consider that a precise examination of both its theoretical and empirical consequences is requested to define its validity on this topic.

Conformational heterogeneity and bubble dynamics in single bacterial transcription initiation complexes

PubMed Central

Duchi, Diego; Gryte, Kristofer; Robb, Nicole C; Morichaud, Zakia; Sheppard, Carol; Wigneshweraraj, Sivaramesh

2018-01-01

Abstract Transcription initiation is a major step in gene regulation for all organisms. In bacteria, the promoter DNA is first recognized by RNA polymerase (RNAP) to yield an initial closed complex. This complex subsequently undergoes conformational changes resulting in DNA strand separation to form a transcription bubble and an RNAP-promoter open complex; however, the series and sequence of conformational changes, and the factors that influence them are unclear. To address the conformational landscape and transitions in transcription initiation, we applied single-molecule Förster resonance energy transfer (smFRET) on immobilized Escherichia coli transcription open complexes. Our results revealed the existence of two stable states within RNAP–DNA complexes in which the promoter DNA appears to adopt closed and partially open conformations, and we observed large-scale transitions in which the transcription bubble fluctuated between open and closed states; these transitions, which occur roughly on the 0.1 s timescale, are distinct from the millisecond-timescale dynamics previously observed within diffusing open complexes. Mutational studies indicated that the σ70 region 3.2 of the RNAP significantly affected the bubble dynamics. Our results have implications for many steps of transcription initiation, and support a bend-load-open model for the sequence of transitions leading to bubble opening during open complex formation. PMID:29177430

Complexity in Dynamical Systems

NASA Astrophysics Data System (ADS)

Moore, Cristopher David

The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

Principal process analysis of biological models.

PubMed

Casagranda, Stefano; Touzeau, Suzanne; Ropers, Delphine; Gouzé, Jean-Luc

2018-06-14

Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms. We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model processes that are always inactive, or inactive on some time interval. Eliminating these processes reduces the complex dynamics of the original model to the much simpler dynamics of the core processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity analysis to test the influence of model parameters on the errors. The results obtained prove the robustness of the method. The analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.

Potent New Small-Molecule Inhibitor of Botulinum Neurotoxin Serotype A Endopeptidase Developed by Synthesis-Based Computer-Aided Molecular Design

DTIC Science & Technology

2009-11-01

dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics

Molecular dynamics studies on troponin (TnI-TnT-TnC) complexes: insight into the regulation of muscle contraction.

PubMed

Varughese, Jayson F; Chalovich, Joseph M; Li, Yumin

2010-10-01

Mutations of any subunit of the troponin complex may lead to serious disorders. Rational approaches to managing these disorders require knowledge of the complex interactions among the three subunits that are required for proper function. Molecular dynamics (MD) simulations were performed for both skeletal (sTn) and cardiac (cTn) troponin. The interactions and correlated motions among the three components of the troponin complex were analyzed using both Molecular Mechanics-Generalized Born Surface Area (MMGBSA) and cross-correlation techniques. The TnTH2 helix was strongly positively correlated with the two long helices of TnI. The C domain of TnC was positively correlated with TnI and TnT. The N domain of TnC was negatively correlated with TnI and TnT in cTn, but not in sTn. The two C-domain calcium-binding sites of TnC were dynamically correlated. The two regulatory N-domain calcium-binding sites of TnC were dynamically correlated, even though the calcium-binding site I is dysfunctional. The strong interaction residue pairs and the strong dynamically correlated residues pairs among the three components of troponin complexes were identified. These correlated motions are consistent with the idea that there is a high degree of cooperativity among the components of the regulatory complex in response to Ca(2+) and other effectors. This approach may give insight into the mechanism by which mutations of troponin cause disease. It is interesting that some observed disease causing mutations fall within regions of troponin that are strongly correlated or interacted.

Complex Dynamics in a Model of Common Fishery Resource Harvested by Multiagents with Heterogeneous Strategy

NASA Astrophysics Data System (ADS)

Gu, En-Guo

In this paper, we formulate a dynamical model of common fishery resource harvested by multiagents with heterogeneous strategy: profit maximizers and gradient learners. Special attention is paid to the problem of heterogeneity of strategic behaviors. We mainly study the existence and the local stability of non-negative equilibria for the model through mathematical analysis. We analyze local bifurcations and complex dynamics such as coexisting attractors by numerical simulations. We also study the local and global dynamics of the exclusive gradient learners as a special case of the model. We discover that when adjusting the speed to be slightly high, the increasing ratio of gradient learners may lead to instability of the fixed point and makes the system sink into complicated dynamics such as quasiperiodic or chaotic attractor. The results reveal that gradient learners with high adjusting speed may ultimately be more harmful to the sustainable use of fish stock than the profit maximizers.

Correlating contact line capillarity and dynamic contact angle hysteresis in surfactant-nanoparticle based complex fluids

NASA Astrophysics Data System (ADS)

Harikrishnan, A. R.; Dhar, Purbarun; Agnihotri, Prabhat K.; Gedupudi, Sateesh; Das, Sarit K.

2018-04-01

Dynamic wettability and contact angle hysteresis can be correlated to shed insight onto any solid-liquid interaction. Complex fluids are capable of altering the expected hysteresis and dynamic wetting behavior due to interfacial interactions. We report the effect of capillary number on the dynamic advancing and receding contact angles of surfactant-based nanocolloidal solutions on hydrophilic, near hydrophobic, and superhydrophobic surfaces by performing forced wetting and de-wetting experiments by employing the embedded needle method. A segregated study is performed to infer the contributing effects of the constituents and effects of particle morphology. The static contact angle hysteresis is found to be a function of particle and surfactant concentrations and greatly depends on the nature of the morphology of the particles. An order of estimate of line energy and a dynamic flow parameter called spreading factor and the transient variations of these parameters are explored which sheds light on the dynamics of contact line movement and response to perturbation of three-phase contact. The Cox-Voinov-Tanner law was found to hold for hydrophilic and a weak dependency on superhydrophobic surfaces with capillary number, and even for the complex fluids, with a varying degree of dependency for different fluids.

Does Leisure Time as a Stress Coping Resource Increase Affective Complexity? Applying the Dynamic Model of Affect (DMA).

PubMed

Qian, Xinyi Lisa; Yarnal, Careen M; Almeida, David M

2013-01-01

Affective complexity, a manifestation of psychological well-being, refers to the relative independence between positive and negative affect (PA, NA). According to the Dynamic Model of Affect (DMA), stressful situations lead to highly inverse PA-NA relationship, reducing affective complexity. Meanwhile, positive events can sustain affective complexity by restoring PA-NA independence. Leisure, a type of positive events, has been identified as a coping resource. This study used the DMA to assess whether leisure time helps restore affective complexity on stressful days. We found that on days with more leisure time than usual, an individual experienced less negative PA-NA relationship after daily stressful events. The finding demonstrates the value of leisure time as a coping resource and the DMA's contribution to coping research.

Symbolic dynamics techniques for complex systems: Application to share price dynamics

NASA Astrophysics Data System (ADS)

Xu, Dan; Beck, Christian

2017-05-01

The symbolic dynamics technique is well known for low-dimensional dynamical systems and chaotic maps, and lies at the roots of the thermodynamic formalism of dynamical systems. Here we show that this technique can also be successfully applied to time series generated by complex systems of much higher dimensionality. Our main example is the investigation of share price returns in a coarse-grained way. A nontrivial spectrum of Rényi entropies is found. We study how the spectrum depends on the time scale of returns, the sector of stocks considered, as well as the number of symbols used for the symbolic description. Overall our analysis confirms that in the symbol space transition probabilities of observed share price returns depend on the entire history of previous symbols, thus emphasizing the need for a modelling based on non-Markovian stochastic processes. Our method allows for quantitative comparisons of entirely different complex systems, for example the statistics of symbol sequences generated by share price returns using 4 symbols can be compared with that of genomic sequences.

Complexity in Higher Education Politics: Bifurcations, Choices and Irreversibility

ERIC Educational Resources Information Center

Kauko, Jaakko

2014-01-01

Taking complexity as an epistemic starting point, this article enhances understanding of dynamics in higher education. It also reviews the relevant literature on path dependency, complexity research, and studies of political change and contingency. These ideas are further developed with reference to the political situation and political…

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

PubMed Central

Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro

2015-01-01

Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045

The Integrin Receptor in Biologically Relevant Bilayers: Insights from Molecular Dynamics Simulations.

PubMed

Kalli, Antreas C; Rog, Tomasz; Vattulainen, Ilpo; Campbell, Iain D; Sansom, Mark S P

2017-08-01

Integrins are heterodimeric (αβ) cell surface receptors that are potential therapeutic targets for a number of diseases. Despite the existence of structural data for all parts of integrins, the structure of the complete integrin receptor is still not available. We have used available structural data to construct a model of the complete integrin receptor in complex with talin F2-F3 domain. It has been shown that the interactions of integrins with their lipid environment are crucial for their function but details of the integrin/lipid interactions remain elusive. In this study an integrin/talin complex was inserted in biologically relevant bilayers that resemble the cell plasma membrane containing zwitterionic and charged phospholipids, cholesterol and sphingolipids to study the dynamics of the integrin receptor and its effect on bilayer structure and dynamics. The results of this study demonstrate the dynamic nature of the integrin receptor and suggest that the presence of the integrin receptor alters the lipid organization between the two leaflets of the bilayer. In particular, our results suggest elevated density of cholesterol and of phosphatidylserine lipids around the integrin/talin complex and a slowing down of lipids in an annulus of ~30 Å around the protein due to interactions between the lipids and the integrin/talin F2-F3 complex. This may in part regulate the interactions of integrins with other related proteins or integrin clustering thus facilitating signal transduction across cell membranes.

A CFD study of complex missile and store configurations in relative motion

NASA Technical Reports Server (NTRS)

Baysal, Oktay

1995-01-01

An investigation was conducted from May 16, 1990 to August 31, 1994 on the development of computational fluid dynamics (CFD) methodologies for complex missiles and the store separation problem. These flowfields involved multiple-component configurations, where at least one of the objects was engaged in relative motion. The two most important issues that had to be addressed were: (1) the unsteadiness of the flowfields (time-accurate and efficient CFD algorithms for the unsteady equations), and (2) the generation of grid systems which would permit multiple and moving bodies in the computational domain (dynamic domain decomposition). The study produced two competing and promising methodologies, and their proof-of-concept cases, which have been reported in the open literature: (1) Unsteady solutions on dynamic, overlapped grids, which may also be perceived as moving, locally-structured grids, and (2) Unsteady solutions on dynamic, unstructured grids.

Active site dynamics of ribonuclease.

PubMed Central

Brünger, A T; Brooks, C L; Karplus, M

1985-01-01

The stochastic boundary molecular dynamics method is used to study the structure, dynamics, and energetics of the solvated active site of bovine pancreatic ribonuclease A. Simulations of the native enzyme and of the enzyme complexed with the dinucleotide substrate CpA and the transition-state analog uridine vanadate are compared. Structural features and dynamical couplings for ribonuclease residues found in the simulation are consistent with experimental data. Water molecules, most of which are not observed in crystallographic studies, are shown to play an important role in the active site. Hydrogen bonding of residues with water molecules in the free enzyme is found to mimic the substrate-enzyme interactions of residues involved in binding. Networks of water stabilize the cluster of positively charged active site residues. Correlated fluctuations between the uridine vanadate complex and the distant lysine residues are mediated through water and may indicate a possible role for these residues in stabilizing the transition state. Images PMID:3866234

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

Is a Universal Science of Complexity Conceivable?

NASA Astrophysics Data System (ADS)

West, Geoffrey B.

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

Complex dynamics and enhanced photosensitivity in a modified Belousov-Zhabotinsky reaction

NASA Astrophysics Data System (ADS)

Li, Nan; Zhao, Jinpei; Wang, Jichang

2008-06-01

This study presents an experimental investigation of nonlinear dynamics in a modified Belousov-Zhabotinsky (BZ) reaction, in which the addition of 1,4-benzoquinone induced various complex behaviors such as mixed-mode oscillations and consecutive period-adding bifurcations. In addition, the presence of 1,4-benzoquinone significantly enhanced the photosensitivity of the ferroin-catalyzed BZ system, in which light-induced transitions between simple and complex oscillations have been achieved. Mechanistic study suggests that the influence of benzoquinone may arise from its interactions with the metal catalyst ferroin/ferriin, where cyclic voltammograms illustrate that the presence of benzoquinone causes an increase in the redox potential of ferroin/ferriin couple, which may consequently alternate the oxidation and reduction paths of the catalyst.

Relationship between microscopic dynamics in traffic flow and complexity in networks.

PubMed

Li, Xin-Gang; Gao, Zi-You; Li, Ke-Ping; Zhao, Xiao-Mei

2007-07-01

Complex networks are constructed in the evolution process of traffic flow, and the states of traffic flow are represented by nodes in the network. The traffic dynamics can then be studied by investigating the statistical properties of those networks. According to Kerner's three-phase theory, there are two different phases in congested traffic, synchronized flow and wide moving jam. In the framework of this theory, we study different properties of synchronized flow and moving jam in relation to complex network. Scale-free network is constructed in stop-and-go traffic, i.e., a sequence of moving jams [Chin. Phys. Lett. 10, 2711 (2005)]. In this work, the networks generated in synchronized flow are investigated in detail. Simulation results show that the degree distribution of the networks constructed in synchronized flow has two power law regions, so the distinction in topological structure can really reflect the different dynamics in traffic flow. Furthermore, the real traffic data are investigated by this method, and the results are consistent with the simulations.

Electron-Transfer Dynamics for a Donor-Bridge-Acceptor Complex in Ionic Liquids.

PubMed

DeVine, Jessalyn A; Labib, Marena; Harries, Megan E; Rached, Rouba Abdel Malak; Issa, Joseph; Wishart, James F; Castner, Edward W

2015-08-27

Intramolecular photoinduced electron transfer from an N,N-dimethyl-p-phenylenediamine donor bridged by a diproline spacer to a coumarin 343 acceptor was studied using time-resolved fluorescence measurements in three ionic liquids and in acetonitrile. The three ionic liquids have the bis[(trifluoromethyl)sulfonyl]amide anion paired with the tributylmethylammonium, 1-butyl-1-methylpyrrolidinium, and 1-decyl-1-methylpyrrolidinium cations. The dynamics in the two-proline donor-bridge-acceptor complex are compared to those observed for the same donor and acceptor connected by a single proline bridge, studied previously by Lee et al. (J. Phys. Chem. C 2012, 116, 5197). The increased conformational freedom afforded by the second bridging proline resulted in multiple energetically accessible conformations. The multiple conformations have significant variations in donor-acceptor electronic coupling, leading to dynamics that include both adiabatic and nonadiabatic contributions. In common with the single-proline bridged complex, the intramolecular electron transfer in the two-proline system was found to be in the Marcus inverted regime.

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

PubMed

Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Optimal dimensionality reduction of complex dynamics: The chess game as diffusion on a free-energy landscape

NASA Astrophysics Data System (ADS)

Krivov, Sergei V.

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game—the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Defect-mediated spatial complexity and chaos in a phase-conjugate resonator

NASA Technical Reports Server (NTRS)

Indebetouw, Guy; Liu, Siuying R.

1992-01-01

We have studied the spatiotemporal dynamics of a phase-conjugate resonator. The cavity Fresnel number is used to vary the degree of transverse confinement of the system. The generation and subsequent motion of the phase defects in the wave front are seen to mediate the system's dynamics. The number of defects and the complexity of their motion increases as the confinement is relaxed, leading the system through a sequence of bifurcations and eventually to chaos.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Games of multicellularity.

PubMed

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coupled binding-bending-folding: The complex conformational dynamics of protein-DNA binding studied by atomistic molecular dynamics simulations.

PubMed

van der Vaart, Arjan

2015-05-01

Protein-DNA binding often involves dramatic conformational changes such as protein folding and DNA bending. While thermodynamic aspects of this behavior are understood, and its biological function is often known, the mechanism by which the conformational changes occur is generally unclear. By providing detailed structural and energetic data, molecular dynamics simulations have been helpful in elucidating and rationalizing protein-DNA binding. This review will summarize recent atomistic molecular dynamics simulations of the conformational dynamics of DNA and protein-DNA binding. A brief overview of recent developments in DNA force fields is given as well. Simulations have been crucial in rationalizing the intrinsic flexibility of DNA, and have been instrumental in identifying the sequence of binding events, the triggers for the conformational motion, and the mechanism of binding for a number of important DNA-binding proteins. Molecular dynamics simulations are an important tool for understanding the complex binding behavior of DNA-binding proteins. With recent advances in force fields and rapid increases in simulation time scales, simulations will become even more important for future studies. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Creating a Safe Space: A Case Study of Complex Trauma and a Call for Proactive Comprehensive Psychoeducational Assessments and Reviews

ERIC Educational Resources Information Center

Mainwaring, Debra J.

2015-01-01

This article advocates for proactive, dynamic and comprehensive psycho-educational assessments for children and young people who have a history of complex trauma, because of its known effects on development and learning. A case study is shared of a young woman with a history of complex trauma because of exposure to parental neglect, multiple…

Lessons from bacterial homolog of tubulin, FtsZ for microtubule dynamics.

PubMed

Battaje, Rachana Rao; Panda, Dulal

2017-09-01

FtsZ, a homolog of tubulin, is found in almost all bacteria and archaea where it has a primary role in cytokinesis. Evidence for structural homology between FtsZ and tubulin came from their crystal structures and identification of the GTP box. Tubulin and FtsZ constitute a distinct family of GTPases and show striking similarities in many of their polymerization properties. The differences between them, more so, the complexities of microtubule dynamic behavior in comparison to that of FtsZ, indicate that the evolution to tubulin is attributable to the incorporation of the complex functionalities in higher organisms. FtsZ and microtubules function as polymers in cell division but their roles differ in the division process. The structural and partial functional homology has made the study of their dynamic properties more interesting. In this review, we focus on the application of the information derived from studies on FtsZ dynamics to study microtubule dynamics and vice versa. The structural and functional aspects that led to the establishment of the homology between the two proteins are explained to emphasize the network of FtsZ and microtubule studies and how they are connected. © 2017 Society for Endocrinology.

Universality of clone dynamics during tissue development

NASA Astrophysics Data System (ADS)

Rulands, Steffen; Lescroart, Fabienne; Chabab, Samira; Hindley, Christopher J.; Prior, Nicole; Sznurkowska, Magdalena K.; Huch, Meritxell; Philpott, Anna; Blanpain, Cedric; Simons, Benjamin D.

2018-05-01

The emergence of complex organs is driven by the coordinated proliferation, migration and differentiation of precursor cells. The fate behaviour of these cells is reflected in the time evolution of their progeny, termed clones, which serve as a key experimental observable. In adult tissues, where cell dynamics is constrained by the condition of homeostasis, clonal tracing studies based on transgenic animal models have advanced our understanding of cell fate behaviour and its dysregulation in disease1,2. But what can be learnt from clonal dynamics in development, where the spatial cohesiveness of clones is impaired by tissue deformations during tissue growth? Drawing on the results of clonal tracing studies, we show that, despite the complexity of organ development, clonal dynamics may converge to a critical state characterized by universal scaling behaviour of clone sizes. By mapping clonal dynamics onto a generalization of the classical theory of aerosols, we elucidate the origin and range of scaling behaviours and show how the identification of universal scaling dependences may allow lineage-specific information to be distilled from experiments. Our study shows the emergence of core concepts of statistical physics in an unexpected context, identifying cellular systems as a laboratory to study non-equilibrium statistical physics.

Structure and function of photosystem I–[FeFe] hydrogenase protein fusions: An all-atom molecular dynamics study

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

Harris, Bradley J.; Cheng, Xiaolin; Frymier, Paul

2015-12-15

All-atom molecular dynamics (MD) simulation was used to study the solution dynamics and protein protein interactions of protein fusions of photosystem I (PSI) from Thermosynechococcus elongatus and an [FeFe]-hydrogenase (FeFe H 2ase) from Clostridium pasteurianum, a unique complex capable of photocatalytic hydrogen production. This study involved fusions of these two proteins via dithiol linkers of different length including decanedithiol, octanedithiol, and hexanedithiol, for which experimental data had previously been obtained. Evaluation of root-mean-squared deviations (RMSDs) relative to the respective crystal structures of PSI and the FeFe H 2ase shows that these fusion complexes approach stable equilibrium conformations during the MDmore » simulations. Investigating protein mobility via root-mean-squared fluctuations (RMSFs) reveals that tethering via the shortest hexanedithiol linker results in increased atomic fluctuations of both PSI and the hydrogenase in these fusion complexes. Furthermore, evaluation of the inter- and intraprotein electron transfer distances in these fusion complexes indicates that the structural changes in the FeFe H 2ase arising from ligation to PSI via the shortest hexanedithiol linker may hinder electron transport in the hydrogenase, thus providing a molecular level explanation for the observation that the medium-length octanedithiol linker gives the highest hydrogen production rate.« less

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

PubMed

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.

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

Improving Ecological Forecasting: Data Assimilation Enhances the Ecological Forecast Horizon of a Complex Food Web

NASA Astrophysics Data System (ADS)

Massoud, E. C.; Huisman, J.; Benincà, E.; Bouten, W.; Vrugt, J. A.

2017-12-01

Species abundances in ecological communities can display chaotic non-equilibrium dynamics. A characteristic feature of chaotic systems is that long-term prediction of the system's trajectory is fundamentally impossible. How then should we make predictions for complex multi-species communities? We explore data assimilation (DA) with the Ensemble Kalman Filter (EnKF) to fuse a two-predator-two-prey model with abundance data from a long term experiment of a plankton community which displays chaotic dynamics. The results show that DA improves substantially the predictability and ecological forecast horizon of complex community dynamics. In addition, we show that DA helps provide guidance on measurement design, for instance on defining the frequency of observations. The study presented here is highly innovative, because DA methods at the current stage are almost unknown in ecology.

Study of Nanocomposites of Amino Acids and Organic Polyethers by Means of Mass Spectrometry and Molecular Dynamics Simulation

NASA Astrophysics Data System (ADS)

Zobnina, V. G.; Kosevich, M. V.; Chagovets, V. V.; Boryak, O. A.

A problem of elucidation of structure of nanomaterials based on combination of proteins and polyether polymers is addressed on the monomeric level of single amino acids and oligomers of PEG-400 and OEG-5 polyethers. Efficiency of application of combined approach involving experimental electrospray mass spectrometry and computer modeling by molecular dynamics simulation is demonstrated. It is shown that oligomers of polyethers form stable complexes with amino acids valine, proline, histidine, glutamic, and aspartic acids. Molecular dynamics simulation has shown that stabilization of amino acid-polyether complexes is achieved due to winding of the polymeric chain around charged groups of amino acids. Structural motives revealed for complexes of single amino acids with polyethers can be realized in structures of protein-polyether nanoparticles currently designed for drug delivery.

Unraveling secrets of telomeres: one molecule at a time

PubMed Central

Lin, Jiangguo; Kaur, Parminder; Countryman, Preston; Opresko, Patricia L.; Wang, Hong

2016-01-01

Telomeres play important roles in maintaining the stability of linear chromosomes. Telomere maintenance involves dynamic actions of multiple proteins interacting with long repetitive sequences and complex dynamic DNA structures, such as G-quadruplexes, T-loops and t-circles. Given the heterogeneity and complexity of telomeres, single-molecule approaches are essential to fully understand the structure-function relationships that govern telomere maintenance. In this review, we present a brief overview of the principles of single-molecule imaging and manipulation techniques. We then highlight results obtained from applying these single-molecule techniques for studying structure, dynamics and functions of G-quadruplexes, telomerase, and shelterin proteins. PMID:24569170

A Comparative Study of [CaEDTA](2-) and [MgEDTA](2-): Structural and Dynamical Insights from Quantum Mechanical Charge Field Molecular Dynamics.

PubMed

Tirler, Andreas O; Hofer, Thomas S

2015-07-09

Structure and dynamics of [MgEDTA](2-) and [CaEDTA](2-) complexes in aqueous solution have been investigated via quantum mechanical/molecular mechanical (QM/MM) simulations. While for the first a 6-fold octahedral complex has been observed, the presence of an additional coordinating water ligand has been observed in the latter case. Because of rapidly exchanging water molecules, this 7-fold coordination complex was found to form pentagonal bipyramidal as well as capped trigonal prismatic configurations along the simulation interchanging on the picosecond time scale. Also in the case of [MgEDTA](2-) a trigonal prismatic configuration has been observed for a very short time period of approximately 1 ps. This work reports for the first time the presence of trigonal prismatic structures observed in the coordination sphere of [MgEDTA](2-) and [CaEDTA](2-) complexes in aqueous solution. In addition to the detailed characterization of structure and dynamics of the systems, the prediction of the associated infrared spectra indicates that the ion-water vibrational mode found at approximately 250 cm(-1) provides a distinctive measure to experimentally detect the presence of the coordinating water molecule via low-frequency IR setups.

Recurrence quantity analysis based on matrix eigenvalues

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian

2018-06-01

Recurrence plots is a powerful tool for visualization and analysis of dynamical systems. Recurrence quantification analysis (RQA), based on point density and diagonal and vertical line structures in the recurrence plots, is considered to be alternative measures to quantify the complexity of dynamical systems. In this paper, we present a new measure based on recurrence matrix to quantify the dynamical properties of a given system. Matrix eigenvalues can reflect the basic characteristics of the complex systems, so we show the properties of the system by exploring the eigenvalues of the recurrence matrix. Considering that Shannon entropy has been defined as a complexity measure, we propose the definition of entropy of matrix eigenvalues (EOME) as a new RQA measure. We confirm that EOME can be used as a metric to quantify the behavior changes of the system. As a given dynamical system changes from a non-chaotic to a chaotic regime, the EOME will increase as well. The bigger EOME values imply higher complexity and lower predictability. We also study the effect of some factors on EOME,including data length, recurrence threshold, the embedding dimension, and additional noise. Finally, we demonstrate an application in physiology. The advantage of this measure lies in a high sensitivity and simple computation.

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. PMID:27918593

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

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.

Evidence for ProTα-TLR4/MD-2 binding: molecular dynamics and gravimetric assay studies.

PubMed

Omotuyi, Olaposi; Matsunaga, Hayato; Ueda, Hiroshi

2015-01-01

During preconditioning, lipopolysaccharide (LPS) selectively activates TLR4/MD-2/Toll/IL-1 receptor-domain-containing adaptor inducing IFN-β (TRIF) pathway instead of pro-inflammatory myeloid differentiation protein-88 (MyD88)/MyD88-adaptor-like protein (MAL) pathway. Extracellular prothymosin alpha (ProTα) is also known to selectively activate the TLR4/MD2/TRIF-IRF3 pathway in certain diseased conditions. In the current study, biophysical evidence for ProTα/TLR4/MD-2 complex formation and its interaction dynamics have been studied. Gravimetric assay was used to investigate ProTα/TLR4/MD-2 complex formation while molecular dynamics (MD) simulation was used to study its interaction dynamics. Through electrostatic interaction, full-length ProTα (F-ProTα) C-terminal peptide (aa 91 - 111) superficially interacts with similar TLR4/MD-2 (KD = 273.36 nm vs 16.07 μg/ml [LPS]) conformation with LPS at an overlapping three-dimensional space while F-ProTα is hinged to the TLR4 scaffold by one-amino acid shift-Mosoian domain (aa-51 - 90). Comparatively, F-ProTα better stabilizes MD-2 metastable states transition and mediates higher TLR4/MD-2 interaction than LPS. ProTα via its C-terminal peptide (aa 91 - 111) exhibits in vitro biophysical contact with TLR4/MD-2 complex conformation recognized by LPS at overlapping LPS-binding positions.

Dynamical complexity of short and noisy time series. Compression-Complexity vs. Shannon entropy

NASA Astrophysics Data System (ADS)

Nagaraj, Nithin; Balasubramanian, Karthi

2017-07-01

Shannon entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity (LZ) and Effort-To-Compress (ETC) on short time series from chaotic dynamical systems in the presence of noise. Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series.

A Dynamic Finite Element Analysis of Human Foot Complex in the Sagittal Plane during Level Walking

PubMed Central

Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R.; Ren, Luquan

2013-01-01

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%–33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning. PMID:24244500

A dynamic finite element analysis of human foot complex in the sagittal plane during level walking.

PubMed

Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R; Ren, Luquan

2013-01-01

The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%-33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning.

Study of intermolecular contacts in the proline-rich homeodomain (PRH)-DNA complex using molecular dynamics simulations.

PubMed

Jalili, Seifollah; Karami, Leila

2012-03-01

The proline-rich homeodomain (PRH)-DNA complex consists of a protein with 60 residues and a 13-base-pair DNA. The PRH protein is a transcription factor that plays a key role in the regulation of gene expression. PRH is a significant member of the Q50 class of homeodomain proteins. The homeodomain section of PRH is essential for binding to DNA and mediates sequence-specific DNA binding. Three 20-ns molecular dynamics (MD) simulations (free protein, free DNA and protein-DNA complex) in explicit solvent water were performed to elucidate the intermolecular contacts in the PRH-DNA complex and the role of dynamics of water molecules forming water-mediated contacts. The simulation provides a detailed explanation of the trajectory of hydration water molecules. The simulations show that some water molecules in the protein-DNA interface exchange with bulk waters. The simulation identifies that most of the contacts consisted of direct interactions between the protein and DNA including specific and non-specific contacts, but several water-mediated polar contacts were also observed. The specific interaction between Gln50 and C18 and water-mediated hydrogen bond between Gln50 and T7 were found to be present during almost the entire time of the simulation. These results show good consistency with experimental and previous computational studies. Structural properties such as root-mean-square deviations (RMSD), root-mean-square fluctuations (RMSF) and secondary structure were also analyzed as a function of time. Analyses of the trajectories showed that the dynamic fluctuations of both the protein and the DNA were lowered by the complex formation.

Multilevel Dynamic Systems Affecting Introduction of HIV/STI Prevention Innovations among Chinese Women in Sex Work Establishments

ERIC Educational Resources Information Center

Weeks, Margaret R.; Li, Jianghong; Liao, Susu; Zhang, Qingning; Dunn, Jennifer; Wang, Yanhong; Jiang, Jingmei

2013-01-01

Social and public health scientists are increasingly interested in applying system dynamics theory to improve understanding and to harness the forces of change within complex, multilevel systems that affect community intervention implementation, effects, and sustainability. Building a system dynamics model based on ethnographic case study has the…

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

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

NASA Astrophysics Data System (ADS)

Takagi, Kazushi; Gotoda, Hiroshi

2016-11-01

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

Studying the dynamics of SLP-76, Nck, and Vav1 multimolecular complex formation in live human cells with triple-color FRET.

PubMed

Pauker, Maor H; Hassan, Nirit; Noy, Elad; Reicher, Barak; Barda-Saad, Mira

2012-04-24

Protein-protein interactions regulate and control many cellular functions. A multimolecular complex consisting of the adaptor proteins SLP-76 (Src homology 2 domain-containing leukocyte protein of 76 kD), Nck, and the guanine nucleotide exchange factor Vav1 is recruited to the T cell side of the interface with an antigen-presenting cell during initial T cell activation. This complex is crucial for regulation of the actin machinery, antigen recognition, and signaling in T cells. We studied the interactions between these proteins as well as the dynamics of their recruitment into a complex that governs cytoskeletal reorganization. We developed a triple-color Förster resonance energy transfer (3FRET) system to observe the dynamics of the formation of this trimolecular signaling complex in live human T cells and to follow the three molecular interactions in parallel. Using the 3FRET system, we demonstrated that dimers of Nck and Vav1 were constitutively formed independently of both T cell activation and the association between SLP-76 and Nck. After T cell receptor stimulation, SLP-76 was phosphorylated, which enabled the binding of Nck. A point mutation in the proline-rich site of Vav1, which abolishes its binding to Nck, impaired actin rearrangement, suggesting that Nck-Vav1 dimers play a critical role in regulation of the actin machinery. We suggest that these findings revise the accepted model of the formation of a complex of SLP-76, Nck, and Vav1 and demonstrate the use of 3FRET as a tool to study signal transduction in live cells.

Catalytic dimer nanomotors: continuum theory and microscopic dynamics.

PubMed

Reigh, Shang Yik; Kapral, Raymond

2015-04-28

Synthetic chemically-powered motors with various geometries have potentially new applications involving dynamics on very small scales. Self-generated concentration and fluid flow fields, which depend on geometry, play essential roles in motor dynamics. Sphere-dimer motors, comprising linked catalytic and noncatalytic spheres, display more complex versions of such fields, compared to the often-studied spherical Janus motors. By making use of analytical continuum theory and particle-based simulations we determine the concentration fields, and both the complex structure of the near-field and point-force dipole nature of the far-field behavior of the solvent velocity field that are important for studies of collective motor motion. We derive the dependence of motor velocity on geometric factors such as sphere size and dimer bond length and, thus, show how to construct motors with specific characteristics.

The threshold algorithm: Description of the methodology and new developments

NASA Astrophysics Data System (ADS)

Neelamraju, Sridhar; Oligschleger, Christina; Schön, J. Christian

2017-10-01

Understanding the dynamics of complex systems requires the investigation of their energy landscape. In particular, the flow of probability on such landscapes is a central feature in visualizing the time evolution of complex systems. To obtain such flows, and the concomitant stable states of the systems and the generalized barriers among them, the threshold algorithm has been developed. Here, we describe the methodology of this approach starting from the fundamental concepts in complex energy landscapes and present recent new developments, the threshold-minimization algorithm and the molecular dynamics threshold algorithm. For applications of these new algorithms, we draw on landscape studies of three disaccharide molecules: lactose, maltose, and sucrose.

Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

Instantons re-examined: dynamical tunneling and resonant tunneling.

PubMed

Le Deunff, Jérémy; Mouchet, Amaury

2010-04-01

Starting from trace formulas for the tunneling splittings (or decay rates) analytically continued in the complex time domain, we obtain explicit semiclassical expansions in terms of complex trajectories that are selected with appropriate complex-time paths. We show how this instantonlike approach, which takes advantage of an incomplete Wick rotation, accurately reproduces tunneling effects not only in the usual double-well potential but also in situations where a pure Wick rotation is insufficient, for instance dynamical tunneling or resonant tunneling. Even though only one-dimensional autonomous Hamiltonian systems are quantitatively studied, we discuss the relevance of our method for multidimensional and/or chaotic tunneling.

Does Leisure Time as a Stress Coping Resource Increase Affective Complexity? Applying the Dynamic Model of Affect (DMA)

PubMed Central

Qian, Xinyi (Lisa); Yarnal, Careen M.; Almeida, David M.

2013-01-01

Affective complexity, a manifestation of psychological well-being, refers to the relative independence between positive and negative affect (PA, NA). According to the Dynamic Model of Affect (DMA), stressful situations lead to highly inverse PA-NA relationship, reducing affective complexity. Meanwhile, positive events can sustain affective complexity by restoring PA-NA independence. Leisure, a type of positive events, has been identified as a coping resource. This study used the DMA to assess whether leisure time helps restore affective complexity on stressful days. We found that on days with more leisure time than usual, an individual experienced less negative PA-NA relationship after daily stressful events. The finding demonstrates the value of leisure time as a coping resource and the DMA’s contribution to coping research. PMID:24659826

The electronically excited states of LH2 complexes from Rhodopseudomonas acidophila strain 10050 studied by time-resolved spectroscopy and dynamic Monte Carlo simulations. II. Homo-arrays of LH2 complexes reconstituted into phospholipid model membranes.

PubMed

Pflock, Tobias J; Oellerich, Silke; Krapf, Lisa; Southall, June; Cogdell, Richard J; Ullmann, G Matthias; Köhler, Jürgen

2011-07-21

We performed time-resolved spectroscopy on homoarrays of LH2 complexes from the photosynthetic purple bacterium Rhodopseudomonas acidophila. Variations of the fluorescence transients were monitored as a function of the excitation fluence and the repetition rate of the excitation. These parameters are directly related to the excitation density within the array and to the number of LH2 complexes that still carry a triplet state prior to the next excitation. Comparison of the experimental observations with results from dynamic Monte Carlo simulations for a model cluster of LH2 complexes yields qualitative agreement without the need for any free parameter and reveals the mutual relationship between energy transfer and annihilation processes.

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.

Dynamism & Detail

ERIC Educational Resources Information Center

Flannery, Maura C.

2004-01-01

New material discovered in the study of cell research is presented for the benefit of biology teachers. Huge amounts of data are being generated in fields like cellular dynamics, and it is felt that people's understanding of the cell is becoming much more complex and detailed.

A study on the anisole-water complex by molecular beam-electronic spectroscopy and molecular mechanics calculations.

PubMed

Becucci, M; Pietraperzia, G; Pasquini, M; Piani, G; Zoppi, A; Chelli, R; Castellucci, E; Demtroeder, W

2004-03-22

An experimental and theoretical study is made on the anisole-water complex. It is the first van der Waals complex studied by high resolution electronic spectroscopy in which the water is seen acting as an acid. Vibronically and rotationally resolved electronic spectroscopy experiments and molecular mechanics calculations are used to elucidate the structure of the complex in the ground and first electronic excited state. Some internal dynamics in the system is revealed by high resolution spectroscopy. (c) 2004 American Institute of Physics

DYNAMICS OF WATER TRANSPORT AND STORAGE IN CONIFERS STUDIED WITH DEUTERIUM AND HEAT TRACING TECHNIQUES

EPA Science Inventory

The volume and complexity of their vascular systems make the dynamics of long-distance water transport difficult to study. We used heat and deuterated water (D2O) as tracers to characterize whole-tree water transport and storage properties in individual trees belonging to the co...

Nonlinear dynamics in the study of birdsong

NASA Astrophysics Data System (ADS)

Mindlin, Gabriel B.

2017-09-01

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

Complexity theory, time series analysis and Tsallis q-entropy principle part one: theoretical aspects

NASA Astrophysics Data System (ADS)

Pavlos, George P.

2017-12-01

In this study, we present the highlights of complexity theory (Part I) and significant experimental verifications (Part II) and we try to give a synoptic description of complexity theory both at the microscopic and at the macroscopic level of the physical reality. Also, we propose that the self-organization observed macroscopically is a phenomenon that reveals the strong unifying character of the complex dynamics which includes thermodynamical and dynamical characteristics in all levels of the physical reality. From this point of view, macroscopical deterministic and stochastic processes are closely related to the microscopical chaos and self-organization. The scientific work of scientists such as Wilson, Nicolis, Prigogine, Hooft, Nottale, El Naschie, Castro, Tsallis, Chang and others is used for the development of a unified physical comprehension of complex dynamics from the microscopic to the macroscopic level. Finally, we provide a comprehensive description of the novel concepts included in the complexity theory from microscopic to macroscopic level. Some of the modern concepts that can be used for a unified description of complex systems and for the understanding of modern complexity theory, as it is manifested at the macroscopic and the microscopic level, are the fractal geometry and fractal space-time, scale invariance and scale relativity, phase transition and self-organization, path integral amplitudes, renormalization group theory, stochastic and chaotic quantization and E-infinite theory, etc.

Modeling social crowds. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Poyato, David; Soler, Juan

2016-09-01

The study of human behavior is a complex task, but modeling some aspects of this behavior is an even more complicated and exciting idea. From crisis management to decision making in evacuation protocols, understanding the complexity of humans in stress situations is more and more demanded in our society by obvious reasons [5,6,8,12]. In this context, [4] deals with crowd dynamics with special attention to evacuation.

Maneuvering in the Complex Path from Genotype to Phenotype

NASA Astrophysics Data System (ADS)

Strohman, Richard

2002-04-01

Human disease phenotypes are controlled not only by genes but by lawful self-organizing networks that display system-wide dynamics. These networks range from metabolic pathways to signaling pathways that regulate hormone action. When perturbed, networks alter their output of matter and energy which, depending on the environmental context, can produce either a pathological or a normal phenotype. Study of the dynamics of these networks by approaches such as metabolic control analysis may provide new insights into the pathogenesis and treatment of complex diseases.

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

Complex collective dynamics of active torque-driven colloids at interfaces

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

Snezhko, Alexey

Modern self-assembly techniques aiming to produce complex structural order or functional diversity often rely on non-equilibrium conditions in the system. Light, electric, or magnetic fields are predominantly used to modify interaction profiles of colloidal particles during self-assembly or induce complex out-of-equilibrium dynamic ordering. The energy injection rate, properties of the environment are important control parameters that influence the outcome of active (dynamic) self-assembly. The current review is focused on a case of collective dynamics and self-assembly of particles with externally driven torques coupled to a liquid or solid interface. The complexity of interactions in such systems is further enriched bymore » strong hydrodynamic coupling between particles. Unconventionally ordered dynamic self-assembled patterns, spontaneous symmetry breaking phenomena, self-propulsion, and collective transport have been reported in torque-driven colloids. Some of the features of the complex collective behavior and dynamic pattern formation in those active systems have been successfully captured in simulations.« less

A Constraint Embedding Approach for Complex Vehicle Suspension Dynamics

DTIC Science & Technology

2015-04-24

Complex Vehicle Suspension Dynamics ECCOMAS Thematic Conference on Multibody Dynamics 2015 Abhinandan Jain∗, Calvin Kuo#, Paramsothy Jayakumar †, Jonathan...Suspension Dynamics ECCOMAS Thematic Conference on Multibody Dynamics 2015 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...13. SUPPLEMENTARY NOTES ECCOMAS Thematic Conference on Multibody Dynamics 2015, June 29-July 2, 2015, Barcelona, Catalonia, Spain 14. ABSTRACT See

Structurally Dynamic Spin Market Networks

NASA Astrophysics Data System (ADS)

Horváth, Denis; Kuscsik, Zoltán

The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

A Tribute to J. C. Sprott

NASA Astrophysics Data System (ADS)

Nazarimehr, Fahimeh; Jafari, Sajad; Chen, Guanrong; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Li, Chunbiao; Wei, Zhouchao

2017-12-01

In honor of his 75th birthday, we review the prominent works of Professor Julien Clinton Sprott in chaos and nonlinear dynamics. We categorize his works into three important groups. The first and most important group is identifying new dynamical systems with special properties. He has proposed different chaotic maps, flows, complex variable systems, nonautonomous systems, partial differential equations, fractional-order systems, delay differential systems, spatiotemporal systems, artificial neural networks, and chaotic electrical circuits. He has also studied dynamical properties of complex systems such as bifurcations and basins of attraction. He has done work on generating fractal art. He has examined models of real-world systems that exhibit chaos. The second group of his works comprise control and synchronization of chaos. Finally, the third group is extracting dynamical properties of systems using time-series analysis. This paper highlights the impact of Sprott’s work on the promotion of nonlinear dynamics.

Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells.

PubMed

Tan, Chris Soon Heng; Go, Ka Diam; Bisteau, Xavier; Dai, Lingyun; Yong, Chern Han; Prabhu, Nayana; Ozturk, Mert Burak; Lim, Yan Ting; Sreekumar, Lekshmy; Lengqvist, Johan; Tergaonkar, Vinay; Kaldis, Philipp; Sobota, Radoslaw M; Nordlund, Pär

2018-03-09

Proteins differentially interact with each other across cellular states and conditions, but an efficient proteome-wide strategy to monitor them is lacking. We report the application of thermal proximity coaggregation (TPCA) for high-throughput intracellular monitoring of protein complex dynamics. Significant TPCA signatures observed among well-validated protein-protein interactions correlate positively with interaction stoichiometry and are statistically observable in more than 350 annotated human protein complexes. Using TPCA, we identified many complexes without detectable differential protein expression, including chromatin-associated complexes, modulated in S phase of the cell cycle. Comparison of six cell lines by TPCA revealed cell-specific interactions even in fundamental cellular processes. TPCA constitutes an approach for system-wide studies of protein complexes in nonengineered cells and tissues and might be used to identify protein complexes that are modulated in diseases. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Self-assembly of polyelectrolyte surfactant complexes using large scale MD simulation

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

Polyelectrolytes (PE) and surfactants are known to form interesting structures with varied properties in aqueous solutions. The morphological details of the PE-surfactant complexes depend on a combination of polymer backbone, electrostatic interactions and hydrophobic interactions. We study the self-assembly of cationic PE and anionic surfactants complexes in dilute condition. The importance of such complexes of PE with oppositely charged surfactants can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate which has applications in industry. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered pearl-necklace structures that have been observed experimentally in biological systems. We investigate many different properties of PE-surfactant complexation for different parameter ranges that are useful for pharmaceutical, engineering and biological applications.

Resolving protein interactions and organization downstream the T cell antigen receptor using single-molecule localization microscopy: a review

NASA Astrophysics Data System (ADS)

Sherman, Eilon

2016-06-01

Signal transduction is mediated by heterogeneous and dynamic protein complexes. Such complexes play a critical role in diverse cell functions, with the important example of T cell activation. Biochemical studies of signalling complexes and their imaging by diffraction limited microscopy have resulted in an intricate network of interactions downstream the T cell antigen receptor (TCR). However, in spite of their crucial roles in T cell activation, much remains to be learned about these signalling complexes, including their heterogeneous contents and size distribution, their complex arrangements in the PM, and the molecular requirements for their formation. Here, we review how recent advancements in single molecule localization microscopy have helped to shed new light on the organization of signalling complexes in single molecule detail in intact T cells. From these studies emerges a picture where cells extensively employ hierarchical and dynamic patterns of nano-scale organization to control the local concentration of interacting molecular species. These patterns are suggested to play a critical role in cell decision making. The combination of SMLM with more traditional techniques is expected to continue and critically contribute to our understanding of multimolecular protein complexes and their significance to cell function.

Discrete Dynamics Lab

NASA Astrophysics Data System (ADS)

Wuensche, Andrew

DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.

Molecular dynamics simulations show altered secondary structure of clawless in binary complex with DNA providing insights into aristaless-clawless-DNA ternary complex formation.

PubMed

Kachhap, Sangita; Priyadarshini, Pragya; Singh, Balvinder

2017-05-01

Aristaless (Al) and clawless (Cll) homeodomains that are involved in leg development in Drosophila melanogaster are known to bind cooperatively to 5'-(T/C)TAATTAA(T/A)(T/A)G-3' DNA sequence, but the mechanism of their binding to DNA is unknown. Molecular dynamics (MD) studies have been carried out on binary, ternary, and reconstructed protein-DNA complexes involving Al, Cll, and DNA along with binding free energy analysis of these complexes. Analysis of MD trajectories of Cll-3A01, binary complex reveals that C-terminal end of helixIII of Cll, unwind in the absence of Al and remains so in reconstructed ternary complex, Cll-3A01-Al. In addition, this change in secondary structure of Cll does not allow it to form protein-protein interactions with Al in the ternary reconstructed complex. However, secondary structure of Cll and its interactions are maintained in other reconstructed ternary complex, Al-3A01-Cll where Cll binds to Al-3A01, binary complex to form ternary complex. These interactions as observed during MD simulations compare well with those observed in ternary crystal structure. Thus, this study highlights the role of helixIII of Cll and protein-protein interactions while proposing likely mechanism of recognition in ternary complex, Al-Cll-DNA.

Memory-induced nonlinear dynamics of excitation in cardiac diseases.

PubMed

Landaw, Julian; Qu, Zhilin

2018-04-01

Excitable cells, such as cardiac myocytes, exhibit short-term memory, i.e., the state of the cell depends on its history of excitation. Memory can originate from slow recovery of membrane ion channels or from accumulation of intracellular ion concentrations, such as calcium ion or sodium ion concentration accumulation. Here we examine the effects of memory on excitation dynamics in cardiac myocytes under two diseased conditions, early repolarization and reduced repolarization reserve, each with memory from two different sources: slow recovery of a potassium ion channel and slow accumulation of the intracellular calcium ion concentration. We first carry out computer simulations of action potential models described by differential equations to demonstrate complex excitation dynamics, such as chaos. We then develop iterated map models that incorporate memory, which accurately capture the complex excitation dynamics and bifurcations of the action potential models. Finally, we carry out theoretical analyses of the iterated map models to reveal the underlying mechanisms of memory-induced nonlinear dynamics. Our study demonstrates that the memory effect can be unmasked or greatly exacerbated under certain diseased conditions, which promotes complex excitation dynamics, such as chaos. The iterated map models reveal that memory converts a monotonic iterated map function into a nonmonotonic one to promote the bifurcations leading to high periodicity and chaos.

Memory-induced nonlinear dynamics of excitation in cardiac diseases

NASA Astrophysics Data System (ADS)

Landaw, Julian; Qu, Zhilin

2018-04-01

Excitable cells, such as cardiac myocytes, exhibit short-term memory, i.e., the state of the cell depends on its history of excitation. Memory can originate from slow recovery of membrane ion channels or from accumulation of intracellular ion concentrations, such as calcium ion or sodium ion concentration accumulation. Here we examine the effects of memory on excitation dynamics in cardiac myocytes under two diseased conditions, early repolarization and reduced repolarization reserve, each with memory from two different sources: slow recovery of a potassium ion channel and slow accumulation of the intracellular calcium ion concentration. We first carry out computer simulations of action potential models described by differential equations to demonstrate complex excitation dynamics, such as chaos. We then develop iterated map models that incorporate memory, which accurately capture the complex excitation dynamics and bifurcations of the action potential models. Finally, we carry out theoretical analyses of the iterated map models to reveal the underlying mechanisms of memory-induced nonlinear dynamics. Our study demonstrates that the memory effect can be unmasked or greatly exacerbated under certain diseased conditions, which promotes complex excitation dynamics, such as chaos. The iterated map models reveal that memory converts a monotonic iterated map function into a nonmonotonic one to promote the bifurcations leading to high periodicity and chaos.

Comment on "A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation": building a model of the mTOR signaling network with a potentially faulty tool.

PubMed

Manning, Brendan D

2012-07-10

In their study published in Science Signaling (Research Article, 27 March 2012, DOI: 10.1126/scisignal.2002469), Dalle Pezze et al. tackle the dynamic and complex wiring of the signaling network involving the protein kinase mTOR, which exists within two distinct protein complexes (mTORC1 and mTORC2) that differ in their regulation and function. The authors use a combination of immunoblotting for specific phosphorylation events and computational modeling. The primary experimental tool employed is to monitor the autophosphorylation of mTOR on Ser(2481) in cell lysates as a surrogate for mTOR activity, which the authors conclude is a specific readout for mTORC2. However, Ser(2481) phosphorylation occurs on both mTORC1 and mTORC2 and will dynamically change as the network through which these two complexes are connected is manipulated. Therefore, models of mTOR network regulation built using this tool are inherently imperfect and open to alternative explanations. Specific issues with the main conclusion made in this study, involving the TSC1-TSC2 (tuberous sclerosis complex 1 and 2) complex and its potential regulation of mTORC2, are discussed here. A broader goal of this Letter is to clarify to other investigators the caveats of using mTOR Ser(2481) phosphorylation in cell lysates as a specific readout for either of the two mTOR complexes.

Engine dynamic analysis with general nonlinear finite element codes

NASA Technical Reports Server (NTRS)

Adams, M. L.; Padovan, J.; Fertis, D. G.

1991-01-01

A general engine dynamic analysis as a standard design study computational tool is described for the prediction and understanding of complex engine dynamic behavior. Improved definition of engine dynamic response provides valuable information and insights leading to reduced maintenance and overhaul costs on existing engine configurations. Application of advanced engine dynamic simulation methods provides a considerable cost reduction in the development of new engine designs by eliminating some of the trial and error process done with engine hardware development.

[Molecular dynamics of immune complex of photoadduct-containing DNA with Fab-Anti-DNA antibody fragment].

PubMed

Akberova, N I; Zhmurov, A A; Nevzorova, T A; Litvinov, R I

2016-01-01

Antibodies to DNA play an important role in the pathogenesis of autoimmune diseases. The elucidation of structural mechanisms of both the antigen recognition and the interaction of anti-DNA antibodies with DNA will help to understand the role of DNA-containing immune complexes in various pathologies and can provide a basis for new treatment modalities. Moreover, the DNA-antibody complex is an analog of specific intracellular DNA-protein interactions. In this work, we used in silico molecular dynamic simulations of bimolecular complexes of the dsDNA segment containing the Fab fragment of an anti-DNA antibody to obtain the detailed thermodynamic and structural characteristics of dynamic intermolecular interactions. Using computationally modified crystal structure of the Fab-DNA complex (PDB ID: 3VW3), we studied the equilibrium molecular dynamics of the 64M-5 antibody Fab fragment associated with the dsDNA fragment containing the thymine dimer, the product of DNA photodamage. Amino acid residues that constitute paratopes and the complementary nucleotide epitopes for the Fab-DNA construct were identified. Stacking and electrostatic interactions were found to play the main role in mediating the most specific antibody-dsDNA contacts, while hydrogen bonds were less significant. These findings may shed light on the formation and properties of pathogenic anti-DNA antibodies in autoimmune diseases, such as systemic lupus erythematosus associated with skin photosensitivity and DNA photodamage.

Impact of an irregular friction formulation on dynamics of a minimal model for brake squeal

NASA Astrophysics Data System (ADS)

Stender, Merten; Tiedemann, Merten; Hoffmann, Norbert; Oberst, Sebastian

2018-07-01

Friction-induced vibrations are of major concern in the design of reliable, efficient and comfortable technical systems. Well-known examples for systems susceptible to self-excitation can be found in fluid structure interaction, disk brake squeal, rotor dynamics, hip implants noise and many more. While damping elements and amplitude reduction are well-understood in linear systems, nonlinear systems and especially self-excited dynamics still constitute a challenge for damping element design. Additionally, complex dynamical systems exhibit deterministic chaotic cores which add severe sensitivity to initial conditions to the system response. Especially the complex friction interface dynamics remain a challenging task for measurements and modeling. Today, mostly simple and regular friction models are investigated in the field of self-excited brake system vibrations. This work aims at investigating the effect of high-frequency irregular interface dynamics on the nonlinear dynamical response of a self-excited structure. Special focus is put on the characterization of the system response time series. A low-dimensional minimal model is studied which features self-excitation, gyroscopic effects and friction-induced damping. Additionally, the employed friction formulation exhibits temperature as inner variable and superposed chaotic fluctuations governed by a Lorenz attractor. The time scale of the irregular fluctuations is chosen one order smaller than the overall system dynamics. The influence of those fluctuations on the structural response is studied in various ways, i.e. in time domain and by means of recurrence analysis. The separate time scales are studied in detail and regimes of dynamic interactions are identified. The results of the irregular friction formulation indicate dynamic interactions on multiple time scales, which trigger larger vibration amplitudes as compared to regular friction formulations conventionally studied in the field of friction-induced vibrations.

Dynamics of nanoparticle-protein corona complex formation: analytical results from population balance equations.

PubMed

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid.

Thinking about complexity in health: A systematic review of the key systems thinking and complexity ideas in health.

PubMed

Rusoja, Evan; Haynie, Deson; Sievers, Jessica; Mustafee, Navonil; Nelson, Fred; Reynolds, Martin; Sarriot, Eric; Swanson, Robert Chad; Williams, Bob

2018-01-30

As the Sustainable Development Goals are rolled out worldwide, development leaders will be looking to the experiences of the past to improve implementation in the future. Systems thinking and complexity science (ST/CS) propose that health and the health system are composed of dynamic actors constantly evolving in response to each other and their context. While offering practical guidance for steering the next development agenda, there is no consensus as to how these important ideas are discussed in relation to health. This systematic review sought to identify and describe some of the key terms, concepts, and methods in recent ST/CS literature. Using the search terms "systems thinkin * AND health OR complexity theor* AND health OR complex adaptive system* AND health," we identified 516 relevant full texts out of 3982 titles across the search period (2002-2015). The peak number of articles were published in 2014 (83) with journals specifically focused on medicine/healthcare (265) and particularly the Journal of Evaluation in Clinical Practice (37) representing the largest number by volume. Dynamic/dynamical systems (n = 332), emergence (n = 294), complex adaptive system(s) (n = 270), and interdependent/interconnected (n = 263) were the most common terms with systems dynamic modelling (58) and agent-based modelling (43) as the most common methods. The review offered several important conclusions. First, while there was no core ST/CS "canon," certain terms appeared frequently across the reviewed texts. Second, even as these ideas are gaining traction in academic and practitioner communities, most are concentrated in a few journals. Finally, articles on ST/CS remain largely theoretical illustrating the need for further study and practical application. Given the challenge posed by the next phase of development, gaining a better understanding of ST/CS ideas and their use may lead to improvements in the implementation and practice of the Sustainable Development Goals. Key messages Systems thinking and complexity science, theories that acknowledge the dynamic, connected, and context-dependent nature of health, are highly relevant to the post-millennium development goal era yet lack consensus on their use in relation to health Although heterogeneous, terms, and concepts like emergence, dynamic/dynamical Systems, nonlinear(ity), and interdependent/interconnected as well as methods like systems dynamic modelling and agent-based modelling that comprise systems thinking and complexity science in the health literature are shared across an increasing number of publications within medical/healthcare disciplines Planners, practitioners, and theorists that can better understand these key systems thinking and complexity science concepts will be better equipped to tackle the challenges of the upcoming development goals. © 2018 John Wiley & Sons, Ltd.

The Rise of China in the International Trade Network: A Community Core Detection Approach

PubMed Central

Zhu, Zhen; Cerina, Federica; Chessa, Alessandro; Caldarelli, Guido; Riccaboni, Massimo

2014-01-01

Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995–2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism. PMID:25136895

The rise of China in the International Trade Network: a community core detection approach.

PubMed

Zhu, Zhen; Cerina, Federica; Chessa, Alessandro; Caldarelli, Guido; Riccaboni, Massimo

2014-01-01

Theory of complex networks proved successful in the description of a variety of complex systems ranging from biology to computer science and to economics and finance. Here we use network models to describe the evolution of a particular economic system, namely the International Trade Network (ITN). Previous studies often assume that globalization and regionalization in international trade are contradictory to each other. We re-examine the relationship between globalization and regionalization by viewing the international trade system as an interdependent complex network. We use the modularity optimization method to detect communities and community cores in the ITN during the years 1995-2011. We find rich dynamics over time both inter- and intra-communities. In particular, the Asia-Oceania community disappeared and reemerged over time along with a switch in leadership from Japan to China. We provide a multilevel description of the evolution of the network where the global dynamics (i.e., communities disappear or reemerge) and the regional dynamics (i.e., community core changes between community members) are related. Moreover, simulation results show that the global dynamics can be generated by a simple dynamic-edge-weight mechanism.

EYE MOVEMENT RECORDING AND NONLINEAR DYNAMICS ANALYSIS – THE CASE OF SACCADES#

PubMed Central

Aştefănoaei, Corina; Pretegiani, Elena; Optican, L.M.; Creangă, Dorina; Rufa, Alessandra

2015-01-01

Evidence of a chaotic behavioral trend in eye movement dynamics was examined in the case of a saccadic temporal series collected from a healthy human subject. Saccades are highvelocity eye movements of very short duration, their recording being relatively accessible, so that the resulting data series could be studied computationally for understanding the neural processing in a motor system. The aim of this study was to assess the complexity degree in the eye movement dynamics. To do this we analyzed the saccadic temporal series recorded with an infrared camera eye tracker from a healthy human subject in a special experimental arrangement which provides continuous records of eye position, both saccades (eye shifting movements) and fixations (focusing over regions of interest, with rapid, small fluctuations). The semi-quantitative approach used in this paper in studying the eye functioning from the viewpoint of non-linear dynamics was accomplished by some computational tests (power spectrum, portrait in the state space and its fractal dimension, Hurst exponent and largest Lyapunov exponent) derived from chaos theory. A high complexity dynamical trend was found. Lyapunov largest exponent test suggested bi-stability of cellular membrane resting potential during saccadic experiment. PMID:25698889

Complementarity of stability patches at the interfaces of protein complexes: Implication for the structural organization of energetic hot spots.

PubMed

Kuttner, Yosef Y; Engel, Stanislav

2018-02-01

A rational design of protein complexes with defined functionalities and of drugs aimed at disrupting protein-protein interactions requires fundamental understanding of the mechanisms underlying the formation of specific protein complexes. Efforts to develop efficient small-molecule or protein-based binders often exploit energetic hot spots on protein surfaces, namely, the interfacial residues that provide most of the binding free energy in the complex. The molecular basis underlying the unusually high energy contribution of the hot spots remains obscure, and its elucidation would facilitate the design of interface-targeted drugs. To study the nature of the energetic hot spots, we analyzed the backbone dynamic properties of contact surfaces in several protein complexes. We demonstrate that, in most complexes, the backbone dynamic landscapes of interacting surfaces form complementary "stability patches," in which static areas from the opposing surfaces superimpose, and that these areas are predominantly located near the geometric center of the interface. We propose that a diminished enthalpy-entropy compensation effect augments the degree to which residues positioned within the complementary stability patches contribute to complex affinity, thereby giving rise to the energetic hot spots. These findings offer new insights into the nature of energetic hot spots and the role that backbone dynamics play in facilitating intermolecular recognition. Mapping the interfacial stability patches may provide guidance for protein engineering approaches aimed at improving the stability of protein complexes and could facilitate the design of ligands that target complex interfaces. © 2017 Wiley Periodicals, Inc.

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.

Sustainability Learning through Gaming: An Exploratory Study

ERIC Educational Resources Information Center

Fabricatore, Carlo; Lopez, Ximena

2012-01-01

This study explored the potential of digital games as learning environments to develop mindsets capable of dealing with complexity in the domain of sustainability. Building sustainable futures requires the ability to deal with the complex dynamics that characterize the world in which we live. As central elements in this system, we must develop the…

Charge-transfer modified embedded atom method dynamic charge potential for Li-Co-O system

NASA Astrophysics Data System (ADS)

Kong, Fantai; Longo, Roberto C.; Liang, Chaoping; Nie, Yifan; Zheng, Yongping; Zhang, Chenxi; Cho, Kyeongjae

2017-11-01

To overcome the limitation of conventional fixed charge potential methods for the study of Li-ion battery cathode materials, a dynamic charge potential method, charge-transfer modified embedded atom method (CT-MEAM), has been developed and applied to the Li-Co-O ternary system. The accuracy of the potential has been tested and validated by reproducing a variety of structural and electrochemical properties of LiCoO2. A detailed analysis on the local charge distribution confirmed the capability of this potential for dynamic charge modeling. The transferability of the potential is also demonstrated by its reliability in describing Li-rich Li2CoO2 and Li-deficient LiCo2O4 compounds, including their phase stability, equilibrium volume, charge states and cathode voltages. These results demonstrate that the CT-MEAM dynamic charge potential could help to overcome the challenge of modeling complex ternary transition metal oxides. This work can promote molecular dynamics studies of Li ion cathode materials and other important transition metal oxides systems that involve complex electrochemical and catalytic reactions.

Charge-transfer modified embedded atom method dynamic charge potential for Li-Co-O system.

PubMed

Kong, Fantai; Longo, Roberto C; Liang, Chaoping; Nie, Yifan; Zheng, Yongping; Zhang, Chenxi; Cho, Kyeongjae

2017-11-29

To overcome the limitation of conventional fixed charge potential methods for the study of Li-ion battery cathode materials, a dynamic charge potential method, charge-transfer modified embedded atom method (CT-MEAM), has been developed and applied to the Li-Co-O ternary system. The accuracy of the potential has been tested and validated by reproducing a variety of structural and electrochemical properties of LiCoO 2 . A detailed analysis on the local charge distribution confirmed the capability of this potential for dynamic charge modeling. The transferability of the potential is also demonstrated by its reliability in describing Li-rich Li 2 CoO 2 and Li-deficient LiCo 2 O 4 compounds, including their phase stability, equilibrium volume, charge states and cathode voltages. These results demonstrate that the CT-MEAM dynamic charge potential could help to overcome the challenge of modeling complex ternary transition metal oxides. This work can promote molecular dynamics studies of Li ion cathode materials and other important transition metal oxides systems that involve complex electrochemical and catalytic reactions.

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

Faes, Luca; Montalto, Alessandro; Stramaglia, Sebastiano; Nollo, Giandomenico; Marinazzo, Daniele

2016-08-01

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

Chua's Circuit and the Qualitative Theory of Dynamical Systems

NASA Astrophysics Data System (ADS)

Mira, Christian

Simple electronic oscillators were at the origin of many studies related to the qualitative theory of dynamical systems. Chua's circuit ([Chua, 1992; Madan, 1993; Chua, 1993; Chua & Pivka, 1995; Wu & Chua, 1996; Pivka et al., 1996]) is now playing an equivalent role for the generation and understanding of complex dynamics. In honour of my friend Leon Chua on his 60th birthday.

Incorporating Social System Dynamics into the Food-Energy-Water System Resilience-Sustainability Modeling Process

NASA Astrophysics Data System (ADS)

Givens, J.; Padowski, J.; Malek, K.; Guzman, C.; Boll, J.; Adam, J. C.; Witinok-Huber, R.

2017-12-01

In the face of climate change and multi-scalar governance objectives, achieving resilience of food-energy-water (FEW) systems requires interdisciplinary approaches. Through coordinated modeling and management efforts, we study "Innovations in the Food-Energy-Water Nexus (INFEWS)" through a case-study in the Columbia River Basin. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic, governance); however, more research is needed to better address social science perspectives. Decisions ultimately taken in this river basin would occur among stakeholders encompassing various institutional power structures including multiple U.S. states, tribal lands, and sovereign nations. The social science lens draws attention to the incompatibility between the engineering definition of resilience (i.e., return to equilibrium or a singular stable state) and the ecological and social system realities, more explicit in the ecological interpretation of resilience (i.e., the ability of a system to move into a different, possibly more resilient state). Social science perspectives include but are not limited to differing views on resilience as normative, system persistence versus transformation, and system boundary issues. To expand understanding of resilience and objectives for complex and dynamic systems, concepts related to inequality, heterogeneity, power, agency, trust, values, culture, history, conflict, and system feedbacks must be more tightly integrated into FEW research. We identify gaps in knowledge and data, and the value and complexity of incorporating social components and processes into systems models. We posit that socio-biophysical system resilience modeling would address important complex, dynamic social relationships, including non-linear dynamics of social interactions, to offer an improved understanding of sustainable management in FEW systems. Conceptual modeling that is presented in our study, represents a starting point for a continued research agenda that incorporates social dynamics into FEW system resilience and management.

Fish Swim, Rocks Sit, and Lungs Breathe: Expert-Novice Understanding of Complex Systems

ERIC Educational Resources Information Center

Hmelo-Silver, Cindy E.; Marathe, Surabhi; Liu, Lei

2007-01-01

Understanding complex systems is fundamental to understanding science. The complexity of such systems makes them very difficult to understand because they are composed of multiple interrelated levels that interact in dynamic ways. The goal of this study was to understand how experts and novices differed in their understanding of two complex…

Evaluating fuel complexes for fire hazard mitigation planning in the southeastern United States

Treesearch

Anne G. Andreu; Dan Shea; Bernard R. Parresol; Roger D. Ottmar

2012-01-01

Fire hazard mitigation planning requires an accurate accounting of fuel complexes to predict potential fire behavior and effects of treatment alternatives. In the southeastern United States, rapid vegetation growth coupled with complex land use history and forest management options requires a dynamic approach to fuel characterization. In this study we assessed...

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.

A bifurcation giving birth to order in an impulsively driven complex system

NASA Astrophysics Data System (ADS)

Seshadri, Akshay; Sujith, R. I.

2016-08-01

Nonlinear oscillations lie at the heart of numerous complex systems. Impulsive forcing arises naturally in many scenarios, and we endeavour to study nonlinear oscillators subject to such forcing. We model these kicked oscillatory systems as a piecewise smooth dynamical system, whereby their dynamics can be investigated. We investigate the problem of pattern formation in a turbulent combustion system and apply this formalism with the aim of explaining the observed dynamics. We identify that the transition of this system from low amplitude chaotic oscillations to large amplitude periodic oscillations is the result of a discontinuity induced bifurcation. Further, we provide an explanation for the occurrence of intermittent oscillations in the system.

A bifurcation giving birth to order in an impulsively driven complex system

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

Seshadri, Akshay, E-mail: akshayseshadri@gmail.com; Sujith, R. I., E-mail: sujith@iitm.ac.in

Nonlinear oscillations lie at the heart of numerous complex systems. Impulsive forcing arises naturally in many scenarios, and we endeavour to study nonlinear oscillators subject to such forcing. We model these kicked oscillatory systems as a piecewise smooth dynamical system, whereby their dynamics can be investigated. We investigate the problem of pattern formation in a turbulent combustion system and apply this formalism with the aim of explaining the observed dynamics. We identify that the transition of this system from low amplitude chaotic oscillations to large amplitude periodic oscillations is the result of a discontinuity induced bifurcation. Further, we provide anmore » explanation for the occurrence of intermittent oscillations in the system.« less

Detection of frequency-mode-shift during thermoacoustic combustion oscillations in a staged aircraft engine model combustor

NASA Astrophysics Data System (ADS)

Kobayashi, Hiroaki; Gotoda, Hiroshi; Tachibana, Shigeru; Yoshida, Seiji

2017-12-01

We conduct an experimental study using time series analysis based on symbolic dynamics to detect a precursor of frequency-mode-shift during thermoacoustic combustion oscillations in a staged aircraft engine model combustor. With increasing amount of the main fuel, a significant shift in the dominant frequency-mode occurs in noisy periodic dynamics, leading to a notable increase in oscillation amplitudes. The sustainment of noisy periodic dynamics during thermoacoustic combustion oscillations is clearly shown by the multiscale complexity-entropy causality plane in terms of statistical complexity. A modified version of the permutation entropy allows us to detect a precursor of the frequency-mode-shift before the amplification of pressure fluctuations.

The stream of experience when watching artistic movies. Dynamic aesthetic effects revealed by the Continuous Evaluation Procedure (CEP).

PubMed

Muth, Claudia; Raab, Marius H; Carbon, Claus-Christian

2015-01-01

Research in perception and appreciation is often focused on snapshots, stills of experience. Static approaches allow for multidimensional assessment, but are unable to catch the crucial dynamics of affective and perceptual processes; for instance, aesthetic phenomena such as the "Aesthetic-Aha" (the increase in liking after the sudden detection of Gestalt), effects of expectation, or Berlyne's idea that "disorientation" with a "promise of success" elicits interest. We conducted empirical studies on indeterminate artistic movies depicting the evolution and metamorphosis of Gestalt and investigated (i) the effects of sudden perceptual insights on liking; that is, "Aesthetic Aha"-effects, (ii) the dynamics of interest before moments of insight, and (iii) the dynamics of complexity before and after moments of insight. Via the so-called Continuous Evaluation Procedure (CEP) enabling analogous evaluation in a continuous way, participants assessed the material on two aesthetic dimensions blockwise either in a gallery or a laboratory. The material's inherent dynamics were described via assessments of liking, interest, determinacy, and surprise along with a computational analysis on the variable complexity. We identified moments of insight as peaks in determinacy and surprise. Statistically significant changes in liking and interest demonstrated that: (i) insights increase liking, (ii) interest already increases 1500 ms before such moments of insight, supporting the idea that it is evoked by an expectation of understanding, and (iii) insights occur during increasing complexity. We propose a preliminary model of dynamics in liking and interest with regard to complexity and perceptual insight and discuss descriptions of participants' experiences of insight. Our results point to the importance of systematic analyses of dynamics in art perception and appreciation.

Experimental study of complex mixed-mode oscillations generated in a Bonhoeffer-van der Pol oscillator under weak periodic perturbation

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

Shimizu, Kuniyasu, E-mail: kuniyasu.shimizu@it-chiba.ac.jp; Sekikawa, Munehisa; Inaba, Naohiko

2015-02-15

Bifurcations of complex mixed-mode oscillations denoted as mixed-mode oscillation-incrementing bifurcations (MMOIBs) have frequently been observed in chemical experiments. In a previous study [K. Shimizu et al., Physica D 241, 1518 (2012)], we discovered an extremely simple dynamical circuit that exhibits MMOIBs. Our model was represented by a slow/fast Bonhoeffer-van der Pol circuit under weak periodic perturbation near a subcritical Andronov-Hopf bifurcation point. In this study, we experimentally and numerically verify that our dynamical circuit captures the essence of the underlying mechanism causing MMOIBs, and we observe MMOIBs and chaos with distinctive waveforms in real circuit experiments.

Digital Signal Processing and Control for the Study of Gene Networks

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun

2016-04-01

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

Digital Signal Processing and Control for the Study of Gene Networks.

PubMed

Shin, Yong-Jun

2016-04-22

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

Digital Signal Processing and Control for the Study of Gene Networks

PubMed Central

Shin, Yong-Jun

2016-01-01

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks. PMID:27102828

Dynamics of water transport and storage in conifers studied with deuterium and heat tracing techniques.

Treesearch

F.C. Meinzer; J.R. Brooks; J.-C. Domec; B.L. Gartner; J.M. Warren; D.R. Woodruff; K. Bible; D.C. Shaw

2006-01-01

The volume and complexity of their vascular systems make the dynamics of tong-distance water transport in large trees difficult to study. We used heat and deuterated water (D20) as tracers to characterize whole-tree water transport and storage properties in individual trees belonging to the coniferous species Pseudotsuga menziesii...

Reasons for Demotivation across Years of Study: Voices from Iranian English Major Students

ERIC Educational Resources Information Center

Hassaskhah, Jaleh; Mahdavi Zafarghandi, Amir; Fazeli, Maryam

2015-01-01

Language learning failure is often directly related to demotivation. The purpose of this study is to examine the process of demotivation and identify its sources within four years of an undergraduate degree programme. To this end, based on the complex dynamic systems perspective of the dynamic systems theories (DSTs), the demotivation test battery…

Femtosecond dynamics of energy transfer in B800-850 light-harvesting complexes of Rhodobacter sphaeroides.

PubMed Central

Trautman, J K; Shreve, A P; Violette, C A; Frank, H A; Owens, T G; Albrecht, A C

1990-01-01

We report femtosecond transient absorption studies of energy transfer dynamics in the B800-850 light-harvesting complex (LHC) of Rhodobacter sphaeroides 2.4.1. For complexes solubilized in lauryldimethylamine-N-oxide (LDAO), the carotenoid to bacteriochlorophyll (Bchl) B800 and carotenoid to Bchl B850 energy transfer times are 0.34 and 0.20 ps, respectively. The B800 to B850 energy transfer time is 2.5 ps. For complexes treated with lithium dodecyl sulfate (LDS), a carotenoid to B850 energy transfer time of less than or equal to 0.2 ps is seen, and a portion of the total carotenoid population is decoupled from Bchl. In both LDAO-solubilized and LDS-treated complexes an intensity-dependent picosecond decay component of the excited B850 population is ascribed to excitation annihilation within minimal units of the LHC. PMID:2404276

Supramolecular reactivity in the gas phase: investigating the intrinsic properties of non-covalent complexes.

PubMed

Cera, Luca; Schalley, Christoph A

2014-03-21

The high vacuum inside a mass spectrometer offers unique conditions to broaden our view on the reactivity of supramolecules. Because dynamic exchange processes between complexes are efficiently suppressed, the intrinsic and intramolecular reactivity of the complexes of interest is observed. Besides this, the significantly higher strength of non-covalent interactions in the absence of competing solvent allows processes to occur that are unable to compete in solution. The present review highlights a series of examples illustrating different aspects of supramolecular gas-phase reactivity ranging from the dissociation and formation of covalent bonds in non-covalent complexes through the reactivity in the restricted inner phase of container molecules and step-by-step mechanistic studies of organocatalytic reaction cycles to cage contraction reactions, processes induced by electron capture, and finally dynamic molecular motion within non-covalent complexes as unravelled by hydrogen-deuterium exchange processes performed in the gas phase.

Proteolytic turnover of the Gal4 transcription factor is not required for function in vivo.

PubMed

Nalley, Kip; Johnston, Stephen Albert; Kodadek, Thomas

2006-08-31

Transactivator-promoter complexes are essential intermediates in the activation of eukaryotic gene expression. Recent studies of these complexes have shown that some are quite dynamic in living cells owing to rapid and reversible disruption of activator-promoter complexes by molecular chaperones, or a slower, ubiquitin-proteasome-pathway-mediated turnover of DNA-bound activator. These mechanisms may act to ensure continued responsiveness of activators to signalling cascades by limiting the lifetime of the active protein-DNA complex. Furthermore, the potency of some activators is compromised by proteasome inhibition, leading to the suggestion that periodic clearance of activators from a promoter is essential for high-level expression. Here we describe a variant of the chromatin immunoprecipitation assay that has allowed direct observation of the kinetic stability of native Gal4-promoter complexes in yeast. Under non-inducing conditions, the complex is dynamic, but on induction the Gal4-promoter complexes 'lock in' and exhibit long half-lives. Inhibition of proteasome-mediated proteolysis had little or no effect on Gal4-mediated gene expression. These studies, combined with earlier data, show that the lifetimes of different transactivator-promoter complexes in vivo can vary widely and that proteasome-mediated turnover is not a general requirement for transactivator function.

A novel simulation methodology merging source-sink dynamics and landscape connectivity

EPA Science Inventory

Source-sink dynamics are an emergent property of complex species-landscape interactions. This study explores the patterns of source and sink behavior that become established across a large landscape, using a simulation model for the northern spotted owl (Strix occidentalis cauri...

Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics

PubMed Central

Bennett, Eric J.; Rush, John; Gygi, Steven P.; Harper, J. Wade

2010-01-01

Dynamic reorganization of signaling systems frequently accompany pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex Absolute Quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules while only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. PMID:21145461

Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics.

PubMed

Bennett, Eric J; Rush, John; Gygi, Steven P; Harper, J Wade

2010-12-10

Dynamic reorganization of signaling systems frequently accompanies pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex absolute quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules, whereas only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. Copyright © 2010 Elsevier Inc. All rights reserved.

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Dynamic Density: An Air Traffic Management Metric

NASA Technical Reports Server (NTRS)

Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

1998-01-01

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

Multiphase Dynamics of Magma Oceans

NASA Astrophysics Data System (ADS)

Boukaré, Charles-Edouard; Ricard, Yanick; Parmentier, Edgar M.

2017-04-01

Since the earliest study of the Apollo lunar samples, the magma ocean hypothesis has received increasing consideration for explaining the early evolution of terrestrial planets. Giant impacts seem to be able to melt significantly large planets at the end of their accretion. The evolution of the resulting magma ocean would set the initial conditions (thermal and compositionnal structure) for subsequent long-term solid-state planet dynamics. However, magma ocean dynamics remains poorly understood. The major challenge relies on understanding interactions between the physical properties of materials (e.g., viscosity (at liquid or solid state), buoyancy) and the complex dynamics of an extremely vigorously convecting system. Such complexities might be neglected in cases where liquidus/adiabat interactions and density stratification leads to stable situations. However, interesting possibilities arise when exploring magma ocean dynamics in other regime. In the case of the Earth, recent studies have shown that the liquidus might intersect the adiabat at mid-mantle depth and/or that solids might be buoyant at deep mantle conditions. These results require the consideration of more sophisticated scenarios. For instance, how does bottom-up crystallization look with buoyant crystals? To understand this complex dynamics, we develop a multiphase phase numerical code that can handle simultaneously phase change, the convection in each phase and in the slurry, as well as the compaction or decompaction of the two phases. Although our code can only run in a limited parameter range (Rayleigh number, viscosity contrast between phases, Prandlt number), it provides a rich dynamics that illustrates what could have happened. For a given liquidus/adiabat configuration and density contrast between melt and solid, we explore magma ocean scenarios by varying the relative timescales of three first order processes: solid-liquid separation, thermo-chemical convective motions and magma ocean cooling.

Dynamical analogy between economical crisis and earthquake dynamics within the nonextensive statistical mechanics framework

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Zitis, Pavlos I.; Eftaxias, Konstantinos

2013-07-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up with these different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes). We show that the populations of: (i) fracto-electromagnetic events rooted in the activation of a single fault, emerging prior to a significant earthquake, (ii) the trade volume events of different shares/economic indices, prior to a collapse, and (iii) the price fluctuation (considered as the difference of maximum minus minimum price within a day) events of different shares/economic indices, prior to a collapse, follow both the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar parameter values. The obtained results imply the existence of a dynamic analogy between earthquakes and economic crises, which moreover follow the dynamics of seizures, magnetic storms and solar flares.

High-amplitude fluctuations and alternative dynamical states of midges in Lake Myvatn.

PubMed

Ives, Anthony R; Einarsson, Arni; Jansen, Vincent A A; Gardarsson, Arnthor

2008-03-06

Complex dynamics are often shown by simple ecological models and have been clearly demonstrated in laboratory and natural systems. Yet many classes of theoretically possible dynamics are still poorly documented in nature. Here we study long-term time-series data of a midge, Tanytarsus gracilentus (Diptera: Chironomidae), in Lake Myvatn, Iceland. The midge undergoes density fluctuations of almost six orders of magnitude. Rather than regular cycles, however, these fluctuations have irregular periods of 4-7 years, indicating complex dynamics. We fit three consumer-resource models capable of qualitatively distinct dynamics to the data. Of these, the best-fitting model shows alternative dynamical states in the absence of environmental variability; depending on the initial midge densities, the model shows either fluctuations around a fixed point or high-amplitude cycles. This explains the observed complex population dynamics: high-amplitude but irregular fluctuations occur because stochastic variability causes the dynamics to switch between domains of attraction to the alternative states. In the model, the amplitude of fluctuations depends strongly on minute resource subsidies into the midge habitat. These resource subsidies may be sensitive to human-caused changes in the hydrology of the lake, with human impacts such as dredging leading to higher-amplitude fluctuations. Tanytarsus gracilentus is a key component of the Myvatn ecosystem, representing two-thirds of the secondary productivity of the lake and providing vital food resources to fish and to breeding bird populations. Therefore the high-amplitude, irregular fluctuations in midge densities generated by alternative dynamical states dominate much of the ecology of the lake.

A Model of Motivation for Extensive Reading in Japanese as a Foreign Language

ERIC Educational Resources Information Center

de Burgh-Hirabe, Ryoko; Feryok, Ann

2013-01-01

Numerous studies have reported that extensive reading (ER) has a positive influence on affect. Recent studies suggest that motivation for ER changes. This is in line with recent developments in second language (L2) motivation research that have highlighted the complex and dynamic nature of L2 motivation. This study presents a model of complex and…

Wigner flow reveals topological order in quantum phase space dynamics.

PubMed

Steuernagel, Ole; Kakofengitis, Dimitris; Ritter, Georg

2013-01-18

The behavior of classical mechanical systems is characterized by their phase portraits, the collections of their trajectories. Heisenberg's uncertainty principle precludes the existence of sharply defined trajectories, which is why traditionally only the time evolution of wave functions is studied in quantum dynamics. These studies are quite insensitive to the underlying structure of quantum phase space dynamics. We identify the flow that is the quantum analog of classical particle flow along phase portrait lines. It reveals hidden features of quantum dynamics and extra complexity. Being constrained by conserved flow winding numbers, it also reveals fundamental topological order in quantum dynamics that has so far gone unnoticed.

Perrhenate complexation by uranyl in traditional solvents and in ionic liquids: a joint molecular dynamics/spectroscopic study.

PubMed

Chaumont, Alain; Klimchuk, Olga; Gaillard, Clotilde; Billard, Isabelle; Ouadi, Ali; Hennig, Christoph; Wipff, Georges

2012-03-15

The complexation of perrhenate (ReO(4)(-)) anions by the uranyl (UO(2)(2+)) cation has been investigated by joint molecular dynamics simulations and spectroscopic (UV-vis, TRLFS, and EXAFS) studies in aqueous solution, acetonitrile, and three ionic liquids (ILs), namely, [Bmi][Tf(2)N], [Me(3)BuN][Tf(2)N], and [Bu(3)MeN][Tf(2)N] that are based on the same Tf(2)N(-) anion (bis(trifluoromethylsulfonyl)imide) and either Bmi(+) (1-butyl,3-methylimidazolium), Me(3)BuN(+), or Bu(3)MeN(+) cations. They show that ReO(4)(-) behaves as a weak ligand in aqueous solution and as a strong ligand in acetonitrile and in the ILs. According to MD simulations in aqueous solution, the UO(2)(ReO(4))(2) complex quickly dissociates to form UO(2)(H(2)O)(5)(2+), while in acetonitrile, a stable UO(2)(ReO(4))(5)(3-) species forms from dissociated ions. In the ILs, the UO(2)(ReO(4))(n)(2-n) complexes (n = 1 to 5) remained stable along the dynamics, and to assess their relative stabilities, we computed the free energy profiles for stepwise ReO(4)(-) complexation to uranyl. In the two studied ILs, complexation is favored, leading to the UO(2)(ReO(4))(5)(3-) species in [Bmi][Tf(2)N] and to UO(2)(ReO(4))(4)(2-) in [Bu(3)MeN][Tf(2)N]. Furthermore, in both acetonitrile and [Bmi][Tf(2)N] solutions, MD and PMF simulations support the formation of dimeric uranyl complexes [UO(2)(ReO(4))(4)](2)(4-) with two bridging ReO(4)(-) ligands. The simulation results are qualitatively consistent with spectroscopic observations in the different solvents, without firmly concluding, however, on the precise composition and structure of the complexes in the solutions. © 2012 American Chemical Society

An evaluation of the performance of two binaural beamformers in complex and dynamic multitalker environments

PubMed Central

Best, Virginia; Mejia, Jorge; Freeston, Katrina; van Hoesel, Richard J.; Dillon, Harvey

2016-01-01

Objective Binaural beamformers are super-directional hearing aids created by combining microphone outputs from each side of the head. While they offer substantial improvements in SNR over conventional directional hearing aids, the benefits (and possible limitations) of these devices in realistic, complex listening situations have not yet been fully explored. In this study we evaluated the performance of two experimental binaural beamformers. Design Testing was carried out using a horizontal loudspeaker array. Background noise was created using recorded conversations. Performance measures included speech intelligibility, localisation in noise, acceptable noise level, subjective ratings, and a novel dynamic speech intelligibility measure. Study sample Participants were 27 listeners with bilateral hearing loss, fitted with BTE prototypes that could be switched between conventional directional or binaural beamformer microphone modes. Results Relative to the conventional directional microphones, both binaural beamformer modes were generally superior for tasks involving fixed frontal targets, but not always for situations involving dynamic target locations. Conclusions Binaural beamformers show promise for enhancing listening in complex situations when the location of the source of interest is predictable. PMID:26140298

Information driven self-organization of complex robotic behaviors.

PubMed

Martius, Georg; Der, Ralf; Ay, Nihat

2013-01-01

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

Complex motion of a vehicle through a series of signals controlled by power-law phase

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

2017-07-01

We study the dynamic motion of a vehicle moving through the series of traffic signals controlled by the position-dependent phase of power law. All signals are controlled by both cycle time and position-dependent phase. The dynamic model of the vehicular motion is described in terms of the nonlinear map. The vehicular motion varies in a complex manner by varying cycle time for various values of the power of the position-dependent phase. The vehicle displays the periodic motion with a long cycle for the integer power of the phase, while the vehicular motion exhibits the very complex behavior for the non-integer power of the phase.

Energy landscape scheme for an intuitive understanding of complex domain dynamics in ferroelectric thin films

NASA Astrophysics Data System (ADS)

Heon Kim, Tae; Yoon, Jong-Gul; Hyub Baek, Seung; Park, Woong-Kyu; Mo Yang, Sang; Yup Jang, Seung; Min, Taeyuun; Chung, Jin-Seok; Eom, Chang-Beom; Won Noh, Tae

2015-07-01

Fundamental understanding of domain dynamics in ferroic materials has been a longstanding issue because of its relevance to many systems and to the design of nanoscale domain-wall devices. Despite many theoretical and experimental studies, a full understanding of domain dynamics still remains incomplete, partly due to complex interactions between domain-walls and disorder. We report domain-shape-preserving deterministic domain-wall motion, which directly confirms microscopic return point memory, by observing domain-wall breathing motion in ferroelectric BiFeO3 thin film using stroboscopic piezoresponse force microscopy. Spatial energy landscape that provides new insights into domain dynamics is also mapped based on the breathing motion of domain walls. The evolution of complex domain structure can be understood by the process of occupying the lowest available energy states of polarization in the energy landscape which is determined by defect-induced internal fields. Our result highlights a pathway for the novel design of ferroelectric domain-wall devices through the engineering of energy landscape using defect-induced internal fields such as flexoelectric fields.

SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks

NASA Astrophysics Data System (ADS)

Li, Jingjing; Zhang, Yumei; Man, Jiayu; Zhou, Yun; Wu, Xiaojun

2017-02-01

Cooperative learning is one of the most effective teaching methods, which has been widely used. Students' mutual contact forms a cooperative learning network in this process. Our previous research demonstrated that the cooperative learning network has complex characteristics. This study aims to investigating the dynamic spreading process of the knowledge in the cooperative learning network and the inspiration of leaders in this process. To this end, complex network transmission dynamics theory is utilized to construct the knowledge dissemination model of a cooperative learning network. Based on the existing epidemic models, we propose a new susceptible-infected-susceptible-leader (SISL) model that considers both students' forgetting and leaders' inspiration, and a susceptible-infected-removed-leader (SIRL) model that considers students' interest in spreading and leaders' inspiration. The spreading threshold λcand its impact factors are analyzed. Then, numerical simulation and analysis are delivered to reveal the dynamic transmission mechanism of knowledge and leaders' role. This work is of great significance to cooperative learning theory and teaching practice. It also enriches the theory of complex network transmission dynamics.

Energy landscape scheme for an intuitive understanding of complex domain dynamics in ferroelectric thin films.

PubMed

Kim, Tae Heon; Yoon, Jong-Gul; Baek, Seung Hyub; Park, Woong-kyu; Yang, Sang Mo; Yup Jang, Seung; Min, Taeyuun; Chung, Jin-Seok; Eom, Chang-Beom; Noh, Tae Won

2015-07-01

Fundamental understanding of domain dynamics in ferroic materials has been a longstanding issue because of its relevance to many systems and to the design of nanoscale domain-wall devices. Despite many theoretical and experimental studies, a full understanding of domain dynamics still remains incomplete, partly due to complex interactions between domain-walls and disorder. We report domain-shape-preserving deterministic domain-wall motion, which directly confirms microscopic return point memory, by observing domain-wall breathing motion in ferroelectric BiFeO3 thin film using stroboscopic piezoresponse force microscopy. Spatial energy landscape that provides new insights into domain dynamics is also mapped based on the breathing motion of domain walls. The evolution of complex domain structure can be understood by the process of occupying the lowest available energy states of polarization in the energy landscape which is determined by defect-induced internal fields. Our result highlights a pathway for the novel design of ferroelectric domain-wall devices through the engineering of energy landscape using defect-induced internal fields such as flexoelectric fields.

Energy landscape scheme for an intuitive understanding of complex domain dynamics in ferroelectric thin films

PubMed Central

Heon Kim, Tae; Yoon, Jong-Gul; Hyub Baek, Seung; Park, Woong-kyu; Mo Yang, Sang; Yup Jang, Seung; Min, Taeyuun; Chung, Jin-Seok; Eom, Chang-Beom; Won Noh, Tae

2015-01-01

Fundamental understanding of domain dynamics in ferroic materials has been a longstanding issue because of its relevance to many systems and to the design of nanoscale domain-wall devices. Despite many theoretical and experimental studies, a full understanding of domain dynamics still remains incomplete, partly due to complex interactions between domain-walls and disorder. We report domain-shape-preserving deterministic domain-wall motion, which directly confirms microscopic return point memory, by observing domain-wall breathing motion in ferroelectric BiFeO3 thin film using stroboscopic piezoresponse force microscopy. Spatial energy landscape that provides new insights into domain dynamics is also mapped based on the breathing motion of domain walls. The evolution of complex domain structure can be understood by the process of occupying the lowest available energy states of polarization in the energy landscape which is determined by defect-induced internal fields. Our result highlights a pathway for the novel design of ferroelectric domain-wall devices through the engineering of energy landscape using defect-induced internal fields such as flexoelectric fields. PMID:26130159

Order reduction, identification and localization studies of dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Xianghong

In this thesis methods are developed for performing order reduction, system identification and induction of nonlinear localization in complex mechanical dynamic systems. General techniques are proposed for constructing low-order models of linear and nonlinear mechanical systems; in addition, novel mechanical designs are considered for inducing nonlinear localization phenomena for the purpose of enhancing their dynamical performance. The thesis is in three major parts. In the first part, the transient dynamics of an impulsively loaded multi-bay truss is numerically computed by employing the Direct Global Matrix (DGM) approach. The approach is applicable to large-scale flexible structures with periodicity. Karhunen-Loeve (K-L) decomposition is used to discretize the dynamics of the truss and to create the low-order models of the truss. The leading order K-L modes are recovered by an experiment, which shows the feasibility of K-L based order reduction technique. In the second part of the thesis, nonlinear localization in dynamical systems is studied through two applications. In the seismic base isolation study, it is shown that the dynamics are sensitive to the presence of nonlinear elements and that passive motion confinement can be induced under proper design. In the coupled rod system, numerical simulation of the transient dynamics shows that a nonlinear backlash spring can induce either nonlinear localization or delocalization in the form of beat phenomena. K-L decomposition and poincare maps are utilized to study the nonlinear effects. The study shows that nonlinear localization can be induced in complex structures through backlash. In the third and final part of the thesis, a new technique based on Green!s function method is proposed to identify the dynamics of practical bolted joints. By modeling the difference between the dynamics of the bolted structure and the corresponding unbolted one, one constructs a nonparametric model for the joint dynamics. Two applications are given with a bolted beam and a truss joint in order to show the applicability of the technique.

Hydrogen exchange mass spectrometry of functional membrane-bound chemotaxis receptor complexes.

PubMed

Koshy, Seena S; Eyles, Stephen J; Weis, Robert M; Thompson, Lynmarie K

2013-12-10

The transmembrane signaling mechanism of bacterial chemotaxis receptors is thought to involve changes in receptor conformation and dynamics. The receptors function in ternary complexes with two other proteins, CheA and CheW, that form extended membrane-bound arrays. Previous studies have shown that attractant binding induces a small (∼2 Å) piston displacement of one helix of the periplasmic and transmembrane domains toward the cytoplasm, but it is not clear how this signal propagates through the cytoplasmic domain to control the kinase activity of the CheA bound at the membrane-distal tip, nearly 200 Å away. The cytoplasmic domain has been shown to be highly dynamic, which raises the question of how a small piston motion could propagate through a dynamic domain to control CheA kinase activity. To address this, we have developed a method for measuring dynamics of the receptor cytoplasmic fragment (CF) in functional complexes with CheA and CheW. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) measurements of global exchange of the CF demonstrate that the CF exhibits significantly slower exchange in functional complexes than in solution. Because the exchange rates in functional complexes are comparable to those of other proteins with similar structures, the CF appears to be a well-structured protein within these complexes, which is compatible with its role in propagating a signal that appears to be a tiny conformational change in the periplasmic and transmembrane domains of the receptor. We also demonstrate the feasibility of this protocol for local exchange measurements by incorporating a pepsin digest step to produce peptides with 87% sequence coverage and only 20% back exchange. This method extends HDX-MS to membrane-bound functional complexes without detergents that may perturb the stability or structure of the system.

Hydrogen Exchange Mass Spectrometry of Functional Membrane-bound Chemotaxis Receptor Complexes

PubMed Central

Koshy, Seena S.; Eyles, Stephen J.; Weis, Robert M.; Thompson, Lynmarie K.

2014-01-01

The transmembrane signaling mechanism of bacterial chemotaxis receptors is thought to involve changes in receptor conformation and dynamics. The receptors function in ternary complexes with two other proteins, CheA and CheW, that form extended membrane-bound arrays. Previous studies have shown that attractant binding induces a small (~2 Å) piston displacement of one helix of the periplasmic and transmembrane domains towards the cytoplasm, but it is not clear how this signal propagates through the cytoplasmic domain to control the kinase activity of the CheA bound at the membrane-distal tip, nearly 200 Å away. The cytoplasmic domain has been shown to be highly dynamic, which raises the question of how a small piston motion could propagate through a dynamic domain to control CheA kinase activity. To address this, we have developed a method for measuring dynamics of the receptor cytoplasmic fragment (CF) in functional complexes with CheA and CheW. Hydrogen exchange mass spectrometry (HDX-MS) measurements of global exchange of CF demonstrate that CF exhibits significantly slower exchange in functional complexes than in solution. Since the exchange rates in functional complexes are comparable to that of other proteins of similar structure, the CF appears to be a well-structured protein within these complexes, which is compatible with its role in propagating a signal that appears to be a tiny conformational change in the periplasmic and transmembrane domains of the receptor. We also demonstrate the feasibility of this protocol for local exchange measurements, by incorporating a pepsin digest step to produce peptides with 87% sequence coverage and only 20% back exchange. This method extends HDX-MS to membrane-bound functional complexes without detergents that may perturb the stability or structure of the system. PMID:24274333

The spatiotemporal system dynamics of acquired resistance in an engineered microecology.

PubMed

Datla, Udaya Sree; Mather, William H; Chen, Sheng; Shoultz, Isaac W; Täuber, Uwe C; Jones, Caroline N; Butzin, Nicholas C

2017-11-22

Great strides have been made in the understanding of complex networks; however, our understanding of natural microecologies is limited. Modelling of complex natural ecological systems has allowed for new findings, but these models typically ignore the constant evolution of species. Due to the complexity of natural systems, unanticipated interactions may lead to erroneous conclusions concerning the role of specific molecular components. To address this, we use a synthetic system to understand the spatiotemporal dynamics of growth and to study acquired resistance in vivo. Our system differs from earlier synthetic systems in that it focuses on the evolution of a microecology from a killer-prey relationship to coexistence using two different non-motile Escherichia coli strains. Using empirical data, we developed the first ecological model emphasising the concept of the constant evolution of species, where the survival of the prey species is dependent on location (distance from the killer) or the evolution of resistance. Our simple model, when expanded to complex microecological association studies under varied spatial and nutrient backgrounds may help to understand the complex relationships between multiple species in intricate natural ecological networks. This type of microecological study has become increasingly important, especially with the emergence of antibiotic-resistant pathogens.

Maximizing information exchange between complex networks

NASA Astrophysics Data System (ADS)

West, Bruce J.; Geneston, Elvis L.; Grigolini, Paolo

2008-10-01

Science is not merely the smooth progressive interaction of hypothesis, experiment and theory, although it sometimes has that form. More realistically the scientific study of any given complex phenomenon generates a number of explanations, from a variety of perspectives, that eventually requires synthesis to achieve a deep level of insight and understanding. One such synthesis has created the field of out-of-equilibrium statistical physics as applied to the understanding of complex dynamic networks. Over the past forty years the concept of complexity has undergone a metamorphosis. Complexity was originally seen as a consequence of memory in individual particle trajectories, in full agreement with a Hamiltonian picture of microscopic dynamics and, in principle, macroscopic dynamics could be derived from the microscopic Hamiltonian picture. The main difficulty in deriving macroscopic dynamics from microscopic dynamics is the need to take into account the actions of a very large number of components. The existence of events such as abrupt jumps, considered by the conventional continuous time random walk approach to describing complexity was never perceived as conflicting with the Hamiltonian view. Herein we review many of the reasons why this traditional Hamiltonian view of complexity is unsatisfactory. We show that as a result of technological advances, which make the observation of single elementary events possible, the definition of complexity has shifted from the conventional memory concept towards the action of non-Poisson renewal events. We show that the observation of crucial processes, such as the intermittent fluorescence of blinking quantum dots as well as the brain’s response to music, as monitored by a set of electrodes attached to the scalp, has forced investigators to go beyond the traditional concept of complexity and to establish closer contact with the nascent field of complex networks. Complex networks form one of the most challenging areas of modern research overarching all of the traditional scientific disciplines. The transportation networks of planes, highways and railroads; the economic networks of global finance and stock markets; the social networks of terrorism, governments, businesses and churches; the physical networks of telephones, the Internet, earthquakes and global warming and the biological networks of gene regulation, the human body, clusters of neurons and food webs, share a number of apparently universal properties as the networks become increasingly complex. Ubiquitous aspects of such complex networks are the appearance of non-stationary and non-ergodic statistical processes and inverse power-law statistical distributions. Herein we review the traditional dynamical and phase-space methods for modeling such networks as their complexity increases and focus on the limitations of these procedures in explaining complex networks. Of course we will not be able to review the entire nascent field of network science, so we limit ourselves to a review of how certain complexity barriers have been surmounted using newly applied theoretical concepts such as aging, renewal, non-ergodic statistics and the fractional calculus. One emphasis of this review is information transport between complex networks, which requires a fundamental change in perception that we express as a transition from the familiar stochastic resonance to the new concept of complexity matching.

Dynamics of Nanoparticle-Protein Corona Complex Formation: Analytical Results from Population Balance Equations

PubMed Central

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

Background Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. Method This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. Results The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. Conclusion The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid. PMID:23741371

oGNM: online computation of structural dynamics using the Gaussian Network Model

PubMed Central

Yang, Lee-Wei; Rader, A. J.; Liu, Xiong; Jursa, Cristopher Jon; Chen, Shann Ching; Karimi, Hassan A.; Bahar, Ivet

2006-01-01

An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperative fluctuations accessible under native state conditions, is a first step towards understanding molecular mechanisms relevant to biological function. We present a web-based system, oGNM that enables users to calculate online the shape and dispersion of normal modes of motion for proteins, oligonucleotides and their complexes, or associated biological units, using the Gaussian Network Model (GNM). Computations with the new engine are 5–6 orders of magnitude faster than those using conventional normal mode analyses. Two cases studies illustrate the utility of oGNM. The first shows that the thermal fluctuations predicted for 1250 non-homologous proteins correlate well with X-ray crystallographic data over a broad range [7.3–15 Å] of inter-residue interaction cutoff distances and the correlations improve with increasing observation temperatures. The second study, focused on 64 oligonucleotides and oligonucleotide–protein complexes, shows that good agreement with experiments is achieved by representing each nucleotide by three GNM nodes (as opposed to one-node-per-residue in proteins) along with uniform interaction ranges for all components of the complexes. These results open the way to a rapid assessment of the dynamics of DNA/RNA-containing complexes. The server can be accessed at . PMID:16845002

Islands of spatially discordant APD alternans underlie arrhythmogenesis by promoting electrotonic dyssynchrony in models of fibrotic rat ventricular myocardium

NASA Astrophysics Data System (ADS)

Majumder, Rupamanjari; Engels, Marc C.; de Vries, Antoine A. F.; Panfilov, Alexander V.; Pijnappels, Daniël A.

2016-04-01

Fibrosis and altered gap junctional coupling are key features of ventricular remodelling and are associated with abnormal electrical impulse generation and propagation. Such abnormalities predispose to reentrant electrical activity in the heart. In the absence of tissue heterogeneity, high-frequency impulse generation can also induce dynamic electrical instabilities leading to reentrant arrhythmias. However, because of the complexity and stochastic nature of such arrhythmias, the combined effects of tissue heterogeneity and dynamical instabilities in these arrhythmias have not been explored in detail. Here, arrhythmogenesis was studied using in vitro and in silico monolayer models of neonatal rat ventricular tissue with 30% randomly distributed cardiac myofibroblasts and systematically lowered intercellular coupling achieved in vitro through graded knockdown of connexin43 expression. Arrhythmia incidence and complexity increased with decreasing intercellular coupling efficiency. This coincided with the onset of a specialized type of spatially discordant action potential duration alternans characterized by island-like areas of opposite alternans phase, which positively correlated with the degree of connexinx43 knockdown and arrhythmia complexity. At higher myofibroblast densities, more of these islands were formed and reentrant arrhythmias were more easily induced. This is the first study exploring the combinatorial effects of myocardial fibrosis and dynamic electrical instabilities on reentrant arrhythmia initiation and complexity.

Influence of the size and charge of gold nanoclusters on complexation with siRNA: a molecular dynamics simulation study.

PubMed

Mudedla, Sathish Kumar; Azhagiya Singam, Ettayapuram Ramaprasad; Balamurugan, Kanagasabai; Subramanian, Venkatesan

2015-11-11

The complexation of small interfering RNA (siRNA) with positively charged gold nanoclusters has been studied in the present investigation with the help of classical molecular dynamics and steered molecular dynamics simulations accompanied by free energy calculations. The results show that gold nanoclusters form a stable complex with siRNA. The wrapping of siRNA around the gold nanocluster depends on the size and charge on the surface of the gold cluster. The binding pattern of the gold nanocluster with siRNA is also influenced by the presence of another cluster. The interaction between the positively charged amines in the gold nanocluster and the negatively charged phosphate group in the siRNA is responsible for the formation of complexes. The binding free energy value increases with the size of the gold cluster and the number of positive charges present on the surface of the gold nanocluster. The results reveal that the binding energy of small gold nanoclusters increases in the presence of another gold nanocluster while the binding of large gold nanoclusters decreases due to the introduction of another gold nanocluster. Overall, the findings have clearly demonstrated the effect of size and charge of gold nanoclusters on their interaction pattern with siRNA.

Efficient calculation of open quantum system dynamics and time-resolved spectroscopy with distributed memory HEOM (DM-HEOM).

PubMed

Kramer, Tobias; Noack, Matthias; Reinefeld, Alexander; Rodríguez, Mirta; Zelinskyy, Yaroslav

2018-06-11

Time- and frequency-resolved optical signals provide insights into the properties of light-harvesting molecular complexes, including excitation energies, dipole strengths and orientations, as well as in the exciton energy flow through the complex. The hierarchical equations of motion (HEOM) provide a unifying theory, which allows one to study the combined effects of system-environment dissipation and non-Markovian memory without making restrictive assumptions about weak or strong couplings or separability of vibrational and electronic degrees of freedom. With increasing system size the exact solution of the open quantum system dynamics requires memory and compute resources beyond a single compute node. To overcome this barrier, we developed a scalable variant of HEOM. Our distributed memory HEOM, DM-HEOM, is a universal tool for open quantum system dynamics. It is used to accurately compute all experimentally accessible time- and frequency-resolved processes in light-harvesting molecular complexes with arbitrary system-environment couplings for a wide range of temperatures and complex sizes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Ionization dynamics of the water trimer: A direct ab initio MD study

NASA Astrophysics Data System (ADS)

Tachikawa, Hiroto; Takada, Tomoya

2013-03-01

Ionization dynamics of the cyclic water trimer (H2O)3 have been investigated by means of direct ab initio molecular dynamics (AIMD) method. Two reaction channels, complex formation and OH dissociation, were found following the ionization of (H2O)3. In both channels, first, a proton was rapidly transferred from H2O+ to H2O (time scale is ˜15 fs after the ionization). In complex channel, an ion-radical contact pair (H3O+-OH) solvated by the third water molecule was formed as a long-lived H3O+(OH)H2O complex. In OH dissociation channel, the second proton transfer further takes place from H3O+(OH) to H2O (time scale is 50-100 fs) and the OH radical is separated from the H3O+. At the same time, the OH dissociation takes place when the excess energy is efficiently transferred into the kinetic energy of OH radical. The OH dissociation channel is significantly minor, and almost all product channels were the complex formation. The reaction mechanism was discussed on the basis of theoretical results.

Development of nanoscale structure in LAT-based signaling complexes

PubMed Central

2016-01-01

ABSTRACT The adapter molecule linker for activation of T cells (LAT) plays a crucial role in forming signaling complexes induced by stimulation of the T cell receptor (TCR). These multi-molecular complexes are dynamic structures that activate highly regulated signaling pathways. Previously, we have demonstrated nanoscale structure in LAT-based complexes where the adapter SLP-76 (also known as LCP2) localizes to the periphery of LAT clusters. In this study, we show that initially LAT and SLP-76 are randomly dispersed throughout the clusters that form upon TCR engagement. The segregation of LAT and SLP-76 develops near the end of the spreading process. The local concentration of LAT also increases at the same time. Both changes require TCR activation and an intact actin cytoskeleton. These results demonstrate that the nanoscale organization of LAT-based signaling complexes is dynamic and indicates that different kinds of LAT-based complexes appear at different times during T cell activation. PMID:27875277

Unraveling the CHIP:Hsp70 complex as an information processor for protein quality control.

PubMed

VanPelt, Jamie; Page, Richard C

2017-02-01

The CHIP:Hsp70 complex stands at the crossroads of the cellular protein quality control system. Hsp70 facilitates active refolding of misfolded client proteins, while CHIP directs ubiquitination of misfolded client proteins bound to Hsp70. The direct competition between CHIP and Hsp70 for the fate of misfolded proteins leads to the question: how does the CHIP:Hsp70 complex execute triage decisions that direct misfolded proteins for either refolding or degradation? The current body of literature points toward action of the CHIP:Hsp70 complex as an information processor that takes inputs in the form of client folding state, dynamics, and posttranslational modifications, then outputs either refolded or ubiquitinated client proteins. Herein we examine the CHIP:Hsp70 complex beginning with the structure and function of CHIP and Hsp70, followed by an examination of recent studies of the interactions and dynamics of the CHIP:Hsp70 complex. Copyright © 2016 Elsevier B.V. All rights reserved.

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

Dynamic Modeling as a Cognitive Regulation Scaffold for Developing Complex Problem-Solving Skills in an Educational Massively Multiplayer Online Game Environment

ERIC Educational Resources Information Center

Eseryel, Deniz; Ge, Xun; Ifenthaler, Dirk; Law, Victor

2011-01-01

Following a design-based research framework, this article reports two empirical studies with an educational MMOG, called "McLarin's Adventures," on facilitating 9th-grade students' complex problem-solving skill acquisition in interdisciplinary STEM education. The article discusses the nature of complex and ill-structured problem solving…

Accomplishment Summary 1968-1969. Biological Computer Laboratory.

ERIC Educational Resources Information Center

Von Foerster, Heinz; And Others

This report summarizes theoretical, applied, and experimental studies in the areas of computational principles in complex intelligent systems, cybernetics, multivalued logic, and the mechanization of cognitive processes. This work is summarized under the following topic headings: properties of complex dynamic systems; computers and the language…

Smad Signaling Dynamics: Insights from a Parsimonious Model

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

Wiley, H. S.; Shankaran, Harish

2008-09-09

The molecular mechanisms that transmit information from cell surface receptors to the nucleus are exceedingly complex; thus, much effort has been expended in developing computational models to understand these processes. A recent study on modeling the nuclear-cytoplasmic shuttling of Smad2-Smad4 complexes in response to transforming growth factor β (TGF-β) receptor activation has provided substantial insight into how this signaling network translates the degree of TGF-β receptor activation (input) into the amount of nuclear Smad2-Smad4 complexes (output). The study addressed this question by combining a simple, mechanistic model with targeted experiments, an approach that proved particularly powerful for exploring the fundamentalmore » properties of a complex signaling network. The mathematical model revealed that Smad nuclear-cytoplasmic dynamics enables a proportional, but time-delayed coupling between the input and the output. As a result, the output can faithfully track gradual changes in the input, while the rapid input fluctuations that constitute signaling noise are dampened out.« less

Regimes of Flow over Complex Structures of Endothelial Glycocalyx: A Molecular Dynamics Simulation Study.

PubMed

Jiang, Xi Zhuo; Feng, Muye; Ventikos, Yiannis; Luo, Kai H

2018-04-10

Flow patterns on surfaces grafted with complex structures play a pivotal role in many engineering and biomedical applications. In this research, large-scale molecular dynamics (MD) simulations are conducted to study the flow over complex surface structures of an endothelial glycocalyx layer. A detailed structure of glycocalyx has been adopted and the flow/glycocalyx system comprises about 5,800,000 atoms. Four cases involving varying external forces and modified glycocalyx configurations are constructed to reveal intricate fluid behaviour. Flow profiles including temporal evolutions and spatial distributions of velocity are illustrated. Moreover, streamline length and vorticity distributions under the four scenarios are compared and discussed to elucidate the effects of external forces and glycocalyx configurations on flow patterns. Results show that sugar chain configurations affect streamline length distributions but their impact on vorticity distributions is statistically insignificant, whilst the influence of the external forces on both streamline length and vorticity distributions are trivial. Finally, a regime diagram for flow over complex surface structures is proposed to categorise flow patterns.

Complexity in the Chinese stock market and its relationships with monetary policy intensity

NASA Astrophysics Data System (ADS)

Ying, Shangjun; Fan, Ying

2014-01-01

This paper introduces how to formulate the CSI300 evolving stock index using the Paasche compiling technique of weighed indexes after giving the GCA model. It studies dynamics characteristics of the Chinese stock market and its relationships with monetary policy intensity, based on the evolving stock index. It concludes by saying that it is possible to construct a dynamics equation of the Chinese stock market using three variables, and that it is useless to regular market-complexity according to changing intensity of external factors from a chaos point of view.

Nonlinear Dynamics on Interconnected Networks

NASA Astrophysics Data System (ADS)

Arenas, Alex; De Domenico, Manlio

2016-06-01

Networks of dynamical interacting units can represent many complex systems, from the human brain to transportation systems and societies. The study of these complex networks, when accounting for different types of interactions has become a subject of interest in the last few years, especially because its representational power in the description of users' interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.) [1], or in representing different transportation modes in urban networks [2,3]. The general name coined for these networks is multilayer networks, where each layer accounts for a type of interaction (see Fig. 1).

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)…

The Spatial Structure of Planform Migration - Curvature Relation of Meandering Rivers

NASA Astrophysics Data System (ADS)

Guneralp, I.; Rhoads, B. L.

2005-12-01

Planform dynamics of meandering rivers have been of fundamental interest to fluvial geomorphologists and engineers because of the intriguing complexity of these dynamics, the role of planform change in floodplain development and landscape evolution, and the economic and social consequences of bank erosion and channel migration. Improved understanding of the complex spatial structure of planform change and capacity to predict these changes are important for effective stream management, engineering and restoration. The planform characteristics of a meandering river channel are integral to its planform dynamics. Active meandering rivers continually change their positions and shapes as a consequence of hydraulic forces exerted on the channel banks and bed, but as the banks and bed change through sediment transport, so do the hydraulic forces. Thus far, this complex feedback between form and process is incompletely understood, despite the fact that the characteristics and the dynamics of meandering rivers have been studied extensively. Current theoretical models aimed at predicting planform dynamics relate rates of meander migration to local and upstream planform curvature where weighting of the influence of curvature on migration rate decays exponentially over distance. This theoretical relation, however, has not been rigorously evaluated empirically. Furthermore, although models based on exponential-weighting of curvature effects yield fairly realistic predictions of meander migration, such models are incapable of reproducing complex forms of bend development, such as double heading or compound looping. This study presents the development of a new methodology based on parametric cubic spline interpolation for the characterization of channel planform and the planform curvature of meandering rivers. The use of continuous mathematical functions overcomes the reliance on bend-averaged values or piece-wise discrete approximations of planform curvature - a major limitation of previous studies. Continuous curvature series can be related to measured rates of lateral migration to explore empirically the relationship between spatially extended curvature and local bend migration. The methodology is applied to a study reach along a highly sinuous section of the Embarras River in Illinois, USA, which contains double-headed asymmetrical loops. To identify patterns of channel planform and rates of lateral migration for a study reach along Embarrass River in central Illinois, geographical information systems analysis of historical aerial photography over a period from 1936 to 1998 was conducted. Results indicate that parametric cubic spline interpolation provides excellent characterization of the complex planforms and planform curvatures of meandering rivers. The findings also indicate that the spatial structure of migration rate-curvature relation may be more complex than a simple exponential distance-decay function. The study represents a first step toward unraveling the spatial structure of planform evolution of meandering rivers and for developing models of planform dynamics that accurately relate spatially extended patterns of channel curvature to local rates of lateral migration. Such knowledge is vital for improving the capacity to accurately predict planform change of meandering rivers.

Computer Simulations and Theoretical Studies of Complex Systems: from complex fluids to frustrated magnets

NASA Astrophysics Data System (ADS)

Choi, Eunsong

Computer simulations are an integral part of research in modern condensed matter physics; they serve as a direct bridge between theory and experiment by systemactically applying a microscopic model to a collection of particles that effectively imitate a macroscopic system. In this thesis, we study two very differnt condensed systems, namely complex fluids and frustrated magnets, primarily by simulating classical dynamics of each system. In the first part of the thesis, we focus on ionic liquids (ILs) and polymers--the two complementary classes of materials that can be combined to provide various unique properties. The properties of polymers/ILs systems, such as conductivity, viscosity, and miscibility, can be fine tuned by choosing an appropriate combination of cations, anions, and polymers. However, designing a system that meets a specific need requires a concrete understanding of physics and chemistry that dictates a complex interplay between polymers and ionic liquids. In this regard, molecular dynamics (MD) simulation is an efficient tool that provides a molecular level picture of such complex systems. We study the behavior of Poly (ethylene oxide) (PEO) and the imidazolium based ionic liquids, using MD simulations and statistical mechanics. We also discuss our efforts to develop reliable and efficient classical force-fields for PEO and the ionic liquids. The second part is devoted to studies on geometrically frustrated magnets. In particular, a microscopic model, which gives rise to an incommensurate spiral magnetic ordering observed in a pyrochlore antiferromagnet is investigated. The validation of the model is made via a comparison of the spin-wave spectra with the neutron scattering data. Since the standard Holstein-Primakoff method is difficult to employ in such a complex ground state structure with a large unit cell, we carry out classical spin dynamics simulations to compute spin-wave spectra directly from the Fourier transform of spin trajectories. We conclude the study by showing an excellent agreement between the simulation and the experiment.

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Numerical investigations with WRF about atmospheric features leading to heavy precipitation and flood events over the Central Andes' complex topography

NASA Astrophysics Data System (ADS)

Zamuriano, Marcelo; Brönnimann, Stefan

2017-04-01

It's known that some extremes such as heavy rainfalls, flood events, heatwaves and droughts depend largely on the atmospheric circulation and local features. Bolivia is no exception and while the large scale dynamics over the Amazon has been largely investigated, the local features driven by the Andes Cordillera and the Altiplano is still poorly documented. New insights on the regional atmospheric dynamics preceding heavy precipitation and flood events over the complex topography of the Andes-Amazon interface are added through numerical investigations of several case events: flash flood episodes over La Paz city and the extreme 2014 flood in south-western Amazon basin. Large scale atmospheric water transport is dynamically downscaled in order to take into account the complex topography forcing and local features as modulators of these events. For this purpose, a series of high resolution numerical experiments with the WRF-ARW model is conducted using various global datasets and parameterizations. While several mechanisms have been suggested to explain the dynamics of these episodes, they have not been tested yet through numerical modelling experiments. The simulations captures realistically the local water transport and the terrain influence over atmospheric circulation, even though the precipitation intensity is in general unrealistic. Nevertheless, the results show that Dynamical Downscaling over the tropical Andes' complex terrain provides useful meteorological data for a variety of studies and contributes to a better understanding of physical processes involved in the configuration of these events.

Dynamics of Fos-Jun-NFAT1 complexes

PubMed Central

Ramirez-Carrozzi, Vladimir R.; Kerppola, Tom K.

2001-01-01

Transcription initiation in eukaryotes is controlled by nucleoprotein complexes formed through cooperative interactions among multiple transcription regulatory proteins. These complexes may be assembled via stochastic collisions or defined pathways. We investigated the dynamics of Fos-Jun-NFAT1 complexes by using a multicolor fluorescence resonance energy transfer assay. Fos-Jun heterodimers can bind to AP-1 sites in two opposite orientations, only one of which is populated in mature Fos-Jun-NFAT1 complexes. We studied the reversal of Fos-Jun binding orientation in response to NFAT1 by measuring the efficiencies of energy transfer from donor fluorophores linked to opposite ends of an oligonucleotide to an acceptor fluorophore linked to one subunit of the heterodimer. The reorientation of Fos-Jun by NFAT1 was not inhibited by competitor oligonucleotides or heterodimers. The rate of Fos-Jun reorientation was faster than the rate of heterodimer dissociation at some binding sites. The facilitated reorientation of Fos-Jun heterodimers therefore can enhance the efficiency of Fos-Jun-NFAT1 complex formation. We also examined the influence of the preferred orientation of Fos-Jun binding on the stability and transcriptional activity of Fos-Jun-NFAT1 complexes. Complexes formed at sites where Fos-Jun favored the same binding orientation in the presence and absence of NFAT1 exhibited an 8-fold slower dissociation rate than complexes formed at sites where Fos-Jun favored the opposite binding orientation. Fos-Jun-NFAT1 complexes also exhibited greater transcription activation at promoter elements that favored the same orientation of Fos-Jun binding in the presence and absence of NFAT1. Thus, the orientation of heterodimer binding can influence both the dynamics and promoter selectivity of multiprotein transcription regulatory complexes. PMID:11320240

Dynamics of Fos-Jun-NFAT1 complexes.

PubMed

Ramirez-Carrozzi, V R; Kerppola, T K

2001-04-24

Transcription initiation in eukaryotes is controlled by nucleoprotein complexes formed through cooperative interactions among multiple transcription regulatory proteins. These complexes may be assembled via stochastic collisions or defined pathways. We investigated the dynamics of Fos-Jun-NFAT1 complexes by using a multicolor fluorescence resonance energy transfer assay. Fos-Jun heterodimers can bind to AP-1 sites in two opposite orientations, only one of which is populated in mature Fos-Jun-NFAT1 complexes. We studied the reversal of Fos-Jun binding orientation in response to NFAT1 by measuring the efficiencies of energy transfer from donor fluorophores linked to opposite ends of an oligonucleotide to an acceptor fluorophore linked to one subunit of the heterodimer. The reorientation of Fos-Jun by NFAT1 was not inhibited by competitor oligonucleotides or heterodimers. The rate of Fos-Jun reorientation was faster than the rate of heterodimer dissociation at some binding sites. The facilitated reorientation of Fos-Jun heterodimers therefore can enhance the efficiency of Fos-Jun-NFAT1 complex formation. We also examined the influence of the preferred orientation of Fos-Jun binding on the stability and transcriptional activity of Fos-Jun-NFAT1 complexes. Complexes formed at sites where Fos-Jun favored the same binding orientation in the presence and absence of NFAT1 exhibited an 8-fold slower dissociation rate than complexes formed at sites where Fos-Jun favored the opposite binding orientation. Fos-Jun-NFAT1 complexes also exhibited greater transcription activation at promoter elements that favored the same orientation of Fos-Jun binding in the presence and absence of NFAT1. Thus, the orientation of heterodimer binding can influence both the dynamics and promoter selectivity of multiprotein transcription regulatory complexes.

Exploring the Active Center of the LSD1/CoREST Complex by Molecular Dynamics Simulation Utilizing Its Co-crystallized Co-factor Tetrahydrofolate as a Probe.

PubMed

Zalloum, Waleed A; Zalloum, Hiba M

2017-12-26

Epigenetic targeting of cancer is a recent effort to manipulate the gene without destroying the genetic material. Lysine-specific demethylase 1 (LSD1) is one of the enzymes associated with the chromatin for post-translational modifications, where it demethylates lysine amino acid in the chromatin H3 tail. Many studies showed that inhibiting LSD1 could potentially be used to treat cancer epigenetically. LSD1 is associated with its corepressor protein CoREST, and it uses tetrahydrofolate as a co-factor to accept CH 2 from the demethylation process. In this study, the co-crystallized co-factor tetrahydrofolate was utilized to determine possible binding regions in the active center of the LSD1/CoREST complex. Also, the flexibility of the complex has been investigated by molecular dynamics simulation and subsequent analysis by clustering and principal component analysis. This research supported other studies and showed that LSD1/CoREST complex exists in two main conformational structures: open and closed. Furthermore, this study showed that tetrahydrofolate stably binds to the LSD1/CoREST complex, in its open conformation, at its entrance. It then binds to the core of the complex, inducing the closed conformation. Furthermore, the interactions of tetrahydrofolate to these two binding regions and the corresponding binding mode of tetrahydrofolate were investigated to be used in structure-based drug design.

All-atomistic molecular dynamics (AA-MD) studies and pharmacokinetic performance of PAMAM-dendrimer-furosemide delivery systems.

PubMed

Otto, Daniel P; de Villiers, Melgardt M

2018-06-13

Improvement of problematic dissolution and solubility properties of a model drug, furosemide, was investigated for poly(amidoamine) (PAMAM) dendrimer complexes of the drug. Full and half generation dendrimers with amino and ester terminals respectively, were studied. In vitro release performance of these complexes was investigated at drug loads ranging 5-60% using simulated gastric fluids. Full generation dendrimers accommodated higher drug loads, outperformed half-generation complexes, and free drug. Pharmacokinetic studies in rats indicated that the dendrimer complexes markedly improved in the bioavailability of the drug compared to the unformulated drug. The G3.0-PAMAM dendrimer complex showed a two-fold increase in C max and a 1.75-fold increase in AUC over the free drug. Additionally, T max was shortened from approximately 25 to 20 min. One of the first all-atomistic molecular dynamics (AA-MD) simulation studies was performed to evaluate low-generation dendrimer-drug complexes as well as its pharmacokinetic performance. AA-MD provided insight into the intermolecular interactions that take place between the dendrimer and drug. It is suggested that the dendrimer not only encapsulates the drug, but can also orientate the drug in stabilized dispersion to prevent drug clustering which could impact release and bioavailability negatively. AA-MD can be a useful tool to develop dendrimer-based drug delivery systems. Copyright © 2018. Published by Elsevier B.V.

Molecular dynamics study of HIV-1 RT-DNA-nevirapine complexes explains NNRTI inhibition and resistance by connection mutations.

PubMed

Vijayan, R S K; Arnold, Eddy; Das, Kalyan

2014-05-01

HIV-1 reverse transcriptase (RT) is a multifunctional enzyme that is targeted by nucleoside analogs (NRTIs) and non-nucleoside RT inhibitors (NNRTIs). NNRTIs are allosteric inhibitors of RT, and constitute an integral part of several highly active antiretroviral therapy regimens. Under selective pressure, HIV-1 acquires resistance against NNRTIs primarily by selecting mutations around the NNRTI pocket. Complete RT sequencing of clinical isolates revealed that spatially distal mutations arising in connection and the RNase H domain also confer NNRTI resistance and contribute to NRTI resistance. However, the precise structural mechanism by which the connection domain mutations confer NNRTI resistance is poorly understood. We performed 50-ns molecular dynamics (MD) simulations, followed by essential dynamics, free-energy landscape analyses, and network analyses of RT-DNA, RT-DNA-nevirapine (NVP), and N348I/T369I mutant RT-DNA-NVP complexes. MD simulation studies revealed altered global motions and restricted conformational landscape of RT upon NVP binding. Analysis of protein structure network parameters demonstrated a dissortative hub pattern in the RT-DNA complex and an assortative hub pattern in the RT-DNA-NVP complex suggesting enhanced rigidity of RT upon NVP binding. The connection subdomain mutations N348I/T369I did not induce any significant structural change; rather, these mutations modulate the conformational dynamics and alter the long-range allosteric communication network between the connection subdomain and NNRTI pocket. Insights from the present study provide a structural basis for the biochemical and clinical findings on drug resistance caused by the connection and RNase H mutations. Copyright © 2013 Wiley Periodicals, Inc.

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

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

Soner Yorgun, M.; Rood, Richard B.

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

PubMed

Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2015-12-01

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

DOE PAGES

Soner Yorgun, M.; Rood, Richard B.

2016-11-11

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smoothmore » topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.« less

Mathematical Models to Determine Stable Behavior of Complex Systems

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

PubMed

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

2018-01-01

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

Novel Framework for Reduced Order Modeling of Aero-engine Components

NASA Astrophysics Data System (ADS)

Safi, Ali

The present study focuses on the popular dynamic reduction methods used in design of complex assemblies (millions of Degrees of Freedom) where numerous iterations are involved to achieve the final design. Aerospace manufacturers such as Rolls Royce and Pratt & Whitney are actively seeking techniques that reduce computational time while maintaining accuracy of the models. This involves modal analysis of components with complex geometries to determine the dynamic behavior due to non-linearity and complicated loading conditions. In such a case the sub-structuring and dynamic reduction techniques prove to be an efficient tool to reduce design cycle time. The components whose designs are finalized can be dynamically reduced to mass and stiffness matrices at the boundary nodes in the assembly. These matrices conserve the dynamics of the component in the assembly, and thus avoid repeated calculations during the analysis runs for design modification of other components. This thesis presents a novel framework in terms of modeling and meshing of any complex structure, in this case an aero-engine casing. In this study the affect of meshing techniques on the run time are highlighted. The modal analysis is carried out using an extremely fine mesh to ensure all minor details in the structure are captured correctly in the Finite Element (FE) model. This is used as the reference model, to compare against the results of the reduced model. The study also shows the conditions/criteria under which dynamic reduction can be implemented effectively, proving the accuracy of Criag-Bampton (C.B.) method and limitations of Static Condensation. The study highlights the longer runtime needed to produce the reduced matrices of components compared to the overall runtime of the complete unreduced model. Although once the components are reduced, the assembly run is significantly. Hence the decision to use Component Mode Synthesis (CMS) is to be taken judiciously considering the number of iterations that may be required during the design cycle.

Effects of Dynamical Evolution on Globular Clusters’ Internal Kinematics

NASA Astrophysics Data System (ADS)

Tiongco, Maria; Vesperini, Enrico; Varri, Anna Lisa

2018-01-01

The synergy between recent photometric, spectroscopic, and astrometric studies is revealing that globular clusters deviate from the traditional picture of dynamically simple and single stellar population systems. Complex kinematical features such as velocity anisotropy and rotation, and the existence of multiple stellar populations are some of the key observational findings. My thesis work has aimed to build a theoretical framework to interpret these new observational results and to understand their link with a globular cluster’s dynamical history.I have focused on the study of the evolution of globular clusters' internal kinematics, as driven by two-body relaxation, and the interplay between internal angular momentum and the external Galactic tidal field. With a specifically-designed, large survey of direct N-body simulations, I have explored the three-dimensional structure of the velocity space of tidally-perturbed clusters, by characterizing their degree of anisotropy and their rotational properties. These studies have proved that a cluster's kinematical properties contain a distinct imprints of the cluster’s initial structural properties, dynamical history, and tidal environment. By relaxing a number of simplifying assumptions that are traditionally imposed, I have also showed how the interplay between a cluster's internal evolution and the interaction with the host galaxy can produce complex morphological and kinematical properties, such as a counter-rotating core and a twisting of the projected isodensity contours.Building on this fundamental understanding, I have then studied the dynamics of multiple stellar populations in globular clusters, with attention to the largely unexplored role of angular momentum. I have analyzed the evolution of clusters with stellar populations characterized by different initial structural and kinematical properties to determine how long these differences are preserved, and in what cases they could still be observable in present-day systems.This body of results provides essential guidance for a meaningful interpretation of the emerging dynamical complexity of globular clusters in the era of Gaia and other upcoming large spectroscopic surveys.

The Dynamics of the Human Leukocyte Antigen Head Domain Modulates Its Recognition by the T-Cell Receptor.

PubMed

García-Guerrero, Estefanía; Pérez-Simón, José Antonio; Sánchez-Abarca, Luis Ignacio; Díaz-Moreno, Irene; De la Rosa, Miguel A; Díaz-Quintana, Antonio

2016-01-01

Generating the immune response requires the discrimination of peptides presented by the human leukocyte antigen complex (HLA) through the T-cell receptor (TCR). However, how a single amino acid substitution in the antigen bonded to HLA affects the response of T cells remains uncertain. Hence, we used molecular dynamics computations to analyze the molecular interactions between peptides, HLA and TCR. We compared immunologically reactive complexes with non-reactive and weakly reactive complexes. MD trajectories were produced to simulate the behavior of isolated components of the various p-HLA-TCR complexes. Analysis of the fluctuations showed that p-HLA binding barely restrains TCR motions, and mainly affects the CDR3 loops. Conversely, inactive p-HLA complexes displayed significant drop in their dynamics when compared with its free versus ternary forms (p-HLA-TCR). In agreement, the free non-reactive p-HLA complexes showed a lower amount of salt bridges than the responsive ones. This resulted in differences between the electrostatic potentials of reactive and inactive p-HLA species and larger vibrational entropies in non-elicitor complexes. Analysis of the ternary p-HLA-TCR complexes also revealed a larger number of salt bridges in the responsive complexes. To summarize, our computations indicate that the affinity of each p-HLA complex towards TCR is intimately linked to both, the dynamics of its free species and its ability to form specific intermolecular salt-bridges in the ternary complexes. Of outstanding interest is the emerging concept of antigen reactivity involving its interplay with the HLA head sidechain dynamics by rearranging its salt-bridges.

Off-fault plasticity in three-dimensional dynamic rupture simulations using a modal Discontinuous Galerkin method on unstructured meshes: Implementation, verification, and application

NASA Astrophysics Data System (ADS)

Wollherr, Stephanie; Gabriel, Alice-Agnes; Uphoff, Carsten

2018-05-01

The dynamics and potential size of earthquakes depend crucially on rupture transfers between adjacent fault segments. To accurately describe earthquake source dynamics, numerical models can account for realistic fault geometries and rheologies such as nonlinear inelastic processes off the slip interface. We present implementation, verification, and application of off-fault Drucker-Prager plasticity in the open source software SeisSol (www.seissol.org). SeisSol is based on an arbitrary high-order derivative modal Discontinuous Galerkin (ADER-DG) method using unstructured, tetrahedral meshes specifically suited for complex geometries. Two implementation approaches are detailed, modelling plastic failure either employing sub-elemental quadrature points or switching to nodal basis coefficients. At fine fault discretizations the nodal basis approach is up to 6 times more efficient in terms of computational costs while yielding comparable accuracy. Both methods are verified in community benchmark problems and by three dimensional numerical h- and p-refinement studies with heterogeneous initial stresses. We observe no spectral convergence for on-fault quantities with respect to a given reference solution, but rather discuss a limitation to low-order convergence for heterogeneous 3D dynamic rupture problems. For simulations including plasticity, a high fault resolution may be less crucial than commonly assumed, due to the regularization of peak slip rate and an increase of the minimum cohesive zone width. In large-scale dynamic rupture simulations based on the 1992 Landers earthquake, we observe high rupture complexity including reverse slip, direct branching, and dynamic triggering. The spatio-temporal distribution of rupture transfers are altered distinctively by plastic energy absorption, correlated with locations of geometrical fault complexity. Computational cost increases by 7% when accounting for off-fault plasticity in the demonstrating application. Our results imply that the combination of fully 3D dynamic modelling, complex fault geometries, and off-fault plastic yielding is important to realistically capture dynamic rupture transfers in natural fault systems.

Overview of the GRC Stirling Convertor System Dynamic Model

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Regan, Timothy F.

2004-01-01

A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.

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.

Determination of the formation of dark state via depleted spontaneous emission in a complex solvated molecule.

PubMed

Guo, Xunmin; Wang, Sufan; Xia, Andong; Su, Hongmei

2007-07-05

We present a general two-color two-pulse femtosecond pump-dump approach to study the specific population transfer along the reaction coordinate through the higher vibrational energy levels of excited states of a complex solvated molecule via the depleted spontaneous emission. The time-dependent fluorescence depletion provides the correlated dynamical information between the monitored fluorescence state and the SEP "dumped" dark states, and therefore allow us to obtain the dynamics of the formation of the dark states corresponding to the ultrafast photoisomerization processes. The excited-state dynamics of LDS 751 have been investigated as a function of solvent viscosity and solvent polarity, where a cooperative two-step isomerization process is clearly identified within LDS 751 upon excitation.

Oscillations and Multiple Equilibria in Microvascular Blood Flow.

PubMed

Karst, Nathaniel J; Storey, Brian D; Geddes, John B

2015-07-01

We investigate the existence of oscillatory dynamics and multiple steady-state flow rates in a network with a simple topology and in vivo microvascular blood flow constitutive laws. Unlike many previous analytic studies, we employ the most biologically relevant models of the physical properties of whole blood. Through a combination of analytic and numeric techniques, we predict in a series of two-parameter bifurcation diagrams a range of dynamical behaviors, including multiple equilibria flow configurations, simple oscillations in volumetric flow rate, and multiple coexistent limit cycles at physically realizable parameters. We show that complexity in network topology is not necessary for complex behaviors to arise and that nonlinear rheology, in particular the plasma skimming effect, is sufficient to support oscillatory dynamics similar to those observed in vivo.

Pattern dynamics of the reaction-diffusion immune system.

PubMed

Zheng, Qianqian; Shen, Jianwei; Wang, Zhijie

2018-01-01

In this paper, we will investigate the effect of diffusion, which is ubiquitous in nature, on the immune system using a reaction-diffusion model in order to understand the dynamical behavior of complex patterns and control the dynamics of different patterns. Through control theory and linear stability analysis of local equilibrium, we obtain the optimal condition under which the system loses stability and a Turing pattern occurs. By combining mathematical analysis and numerical simulation, we show the possible patterns and how these patterns evolve. In addition, we establish a bridge between the complex patterns and the biological mechanism using the results from a previous study in Nature Cell Biology. The results in this paper can help us better understand the biological significance of the immune system.

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

PubMed

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

2015-04-01

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.

Solution-state structure and affinities of cyclodextrin: Fentanyl complexes by nuclear magnetic resonance spectroscopy and molecular dynamics simulation

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

Mayer, Brian P.; Kennedy, Daniel J.; Lau, Edmond Y.

Cyclodextrins (CDs) are investigated for their ability to form inclusion complexes with the analgesic fentanyl and three similar molecules: acetylfentanyl, thiofentanyl, and acetylthiofentanyl. Stoichiometry, binding strength, and complex structure are revealed through nuclear magnetic resonance (NMR) techniques and discussed in terms of molecular dynamics (MD) simulations. It was found that β-cyclodextrin is generally capable of forming the strongest complexes with the fentanyl panel. Two-dimensional NMR data and computational chemical calculations are used to derive solution-state structures of the complexes. Binding of the fentanyls to the CDs occurs at the amide phenyl ring, leaving the majority of the molecule solvated bymore » water, an observation common to all four fentanyls. This finding suggests a universal binding behavior, as the vast majority of previously synthesized fentanyl analogues contain this structural moiety. Furthermore, this baseline study serves as the most complete work on CD:fentanyl complexes to date and provides the insights into strategies for producing future generations of designer cyclodextrins capable of stronger and more selective complexation of fentanyl and its analogues.« less

Solution-state structure and affinities of cyclodextrin: Fentanyl complexes by nuclear magnetic resonance spectroscopy and molecular dynamics simulation

DOE PAGES

Mayer, Brian P.; Kennedy, Daniel J.; Lau, Edmond Y.; ...

2016-02-04

Cyclodextrins (CDs) are investigated for their ability to form inclusion complexes with the analgesic fentanyl and three similar molecules: acetylfentanyl, thiofentanyl, and acetylthiofentanyl. Stoichiometry, binding strength, and complex structure are revealed through nuclear magnetic resonance (NMR) techniques and discussed in terms of molecular dynamics (MD) simulations. It was found that β-cyclodextrin is generally capable of forming the strongest complexes with the fentanyl panel. Two-dimensional NMR data and computational chemical calculations are used to derive solution-state structures of the complexes. Binding of the fentanyls to the CDs occurs at the amide phenyl ring, leaving the majority of the molecule solvated bymore » water, an observation common to all four fentanyls. This finding suggests a universal binding behavior, as the vast majority of previously synthesized fentanyl analogues contain this structural moiety. Furthermore, this baseline study serves as the most complete work on CD:fentanyl complexes to date and provides the insights into strategies for producing future generations of designer cyclodextrins capable of stronger and more selective complexation of fentanyl and its analogues.« less

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Epidemics Modelings: Some New Challenges

NASA Astrophysics Data System (ADS)

Boatto, Stefanella; Khouri, Renata Stella; Solerman, Lucas; Codeço, Claudia; Bonnet, Catherine

2010-09-01

Epidemics modeling has been particularly growing in the past years. In epidemics studies, mathematical modeling is used in particular to reach a better understanding of some neglected diseases (dengue, malaria, …) and of new emerging ones (SARS, influenza A,….) of big agglomerates. Such studies offer new challenges both from the modeling point of view (searching for simple models which capture the main characteristics of the disease spreading), data analysis and mathematical complexity. We are facing often with complex networks especially when modeling the city dynamics. Such networks can be static (in first approximation) and homogeneous, static and not homogeneous and/or not static (when taking into account the city structure, micro-climates, people circulation, etc.). The objective being studying epidemics dynamics and being able to predict its spreading.

Stability and dynamical properties of material flow systems on random networks

NASA Astrophysics Data System (ADS)

Anand, K.; Galla, T.

2009-04-01

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

Noise and poise: Enhancement of postural complexity in the elderly with a stochastic-resonance based therapy

NASA Astrophysics Data System (ADS)

Costa, M.; Priplata, A. A.; Lipsitz, L. A.; Wu, Z.; Huang, N. E.; Goldberger, A. L.; Peng, C.-K.

2007-03-01

Pathologic states are associated with a loss of dynamical complexity. Therefore, therapeutic interventions that increase physiologic complexity may enhance health status. Using multiscale entropy analysis, we show that the postural sway dynamics of healthy young and healthy elderly subjects are more complex than that of elderly subjects with a history of falls. Application of subsensory noise to the feet has been demonstrated to improve postural stability in the elderly. We next show that this therapy significantly increases the multiscale complexity of sway fluctuations in healthy elderly subjects. Quantification of changes in dynamical complexity of biologic variability may be the basis of a new approach to assessing risk and to predicting the efficacy of clinical interventions, including noise-based therapies.

A framework for stochastic simulations and visualization of biological electron-transfer dynamics

NASA Astrophysics Data System (ADS)

Nakano, C. Masato; Byun, Hye Suk; Ma, Heng; Wei, Tao; El-Naggar, Mohamed Y.

2015-08-01

Electron transfer (ET) dictates a wide variety of energy-conversion processes in biological systems. Visualizing ET dynamics could provide key insight into understanding and possibly controlling these processes. We present a computational framework named VizBET to visualize biological ET dynamics, using an outer-membrane Mtr-Omc cytochrome complex in Shewanella oneidensis MR-1 as an example. Starting from X-ray crystal structures of the constituent cytochromes, molecular dynamics simulations are combined with homology modeling, protein docking, and binding free energy computations to sample the configuration of the complex as well as the change of the free energy associated with ET. This information, along with quantum-mechanical calculations of the electronic coupling, provides inputs to kinetic Monte Carlo (KMC) simulations of ET dynamics in a network of heme groups within the complex. Visualization of the KMC simulation results has been implemented as a plugin to the Visual Molecular Dynamics (VMD) software. VizBET has been used to reveal the nature of ET dynamics associated with novel nonequilibrium phase transitions in a candidate configuration of the Mtr-Omc complex due to electron-electron interactions.

Complex nonlinear dynamics in the limit of weak coupling of a system of microcantilevers connected by a geometrically nonlinear tunable nanomembrane.

PubMed

Jeong, Bongwon; Cho, Hanna; Keum, Hohyun; Kim, Seok; Michael McFarland, D; Bergman, Lawrence A; King, William P; Vakakis, Alexander F

2014-11-21

Intentional utilization of geometric nonlinearity in micro/nanomechanical resonators provides a breakthrough to overcome the narrow bandwidth limitation of linear dynamic systems. In past works, implementation of intentional geometric nonlinearity to an otherwise linear nano/micromechanical resonator has been successfully achieved by local modification of the system through nonlinear attachments of nanoscale size, such as nanotubes and nanowires. However, the conventional fabrication method involving manual integration of nanoscale components produced a low yield rate in these systems. In the present work, we employed a transfer-printing assembly technique to reliably integrate a silicon nanomembrane as a nonlinear coupling component onto a linear dynamic system with two discrete microcantilevers. The dynamics of the developed system was modeled analytically and investigated experimentally as the coupling strength was finely tuned via FIB post-processing. The transition from the linear to the nonlinear dynamic regime with gradual change in the coupling strength was experimentally studied. In addition, we observed for the weakly coupled system that oscillation was asynchronous in the vicinity of the resonance, thus exhibiting a nonlinear complex mode. We conjectured that the emergence of this nonlinear complex mode could be attributed to the nonlinear damping arising from the attached nanomembrane.

αE-catenin regulates actin dynamics independently of cadherin-mediated cell–cell adhesion

PubMed Central

Benjamin, Jacqueline M.; Kwiatkowski, Adam V.; Yang, Changsong; Korobova, Farida; Pokutta, Sabine; Svitkina, Tatyana

2010-01-01

αE-catenin binds the cell–cell adhesion complex of E-cadherin and β-catenin (β-cat) and regulates filamentous actin (F-actin) dynamics. In vitro, binding of αE-catenin to the E-cadherin–β-cat complex lowers αE-catenin affinity for F-actin, and αE-catenin alone can bind F-actin and inhibit Arp2/3 complex–mediated actin polymerization. In cells, to test whether αE-catenin regulates actin dynamics independently of the cadherin complex, the cytosolic αE-catenin pool was sequestered to mitochondria without affecting overall levels of αE-catenin or the cadherin–catenin complex. Sequestering cytosolic αE-catenin to mitochondria alters lamellipodia architecture and increases membrane dynamics and cell migration without affecting cell–cell adhesion. In contrast, sequestration of cytosolic αE-catenin to the plasma membrane reduces membrane dynamics. These results demonstrate that the cytosolic pool of αE-catenin regulates actin dynamics independently of cell–cell adhesion. PMID:20404114

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Complex Sequencing Rules of Birdsong Can be Explained by Simple Hidden Markov Processes

PubMed Central

Katahira, Kentaro; Suzuki, Kenta; Okanoya, Kazuo; Okada, Masato

2011-01-01

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors such as human speech and musical performance, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical properties of the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable labeles, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model; GMM), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex behavioral sequences with higher-order dependencies. PMID:21915345

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues.

PubMed

Hawkins, Jared B; Jones, Mark T; Plassmann, Paul E; Thorley-Lawson, David A

2011-01-01

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.

A Role for the Juxtamembrane Cytoplasm in the Molecular Dynamics of Focal Adhesions

PubMed Central

Wolfenson, Haguy; Lubelski, Ariel; Regev, Tamar; Klafter, Joseph; Henis, Yoav I.; Geiger, Benjamin

2009-01-01

Focal adhesions (FAs) are specialized membrane-associated multi-protein complexes that link the cell to the extracellular matrix and play crucial roles in cell-matrix sensing. Considerable information is available on the complex molecular composition of these sites, yet the regulation of FA dynamics is largely unknown. Based on a combination of FRAP studies in live cells, with in silico simulations and mathematical modeling, we show that the FA plaque proteins paxillin and vinculin exist in four dynamic states: an immobile FA-bound fraction, an FA-associated fraction undergoing exchange, a juxtamembrane fraction experiencing attenuated diffusion, and a fast-diffusing cytoplasmic pool. The juxtamembrane region surrounding FAs displays a gradient of FA plaque proteins with respect to both concentration and dynamics. Based on these findings, we propose a new model for the regulation of FA dynamics in which this juxtamembrane domain acts as an intermediary layer, enabling an efficient regulation of FA formation and reorganization. PMID:19172999

Real-time full-field characterization of transient dissipative soliton dynamics in a mode-locked laser

NASA Astrophysics Data System (ADS)

Ryczkowski, P.; Närhi, M.; Billet, C.; Merolla, J.-M.; Genty, G.; Dudley, J. M.

2018-04-01

Dissipative solitons are remarkably localized states of a physical system that arise from the dynamical balance between nonlinearity, dispersion and environmental energy exchange. They are the most universal form of soliton that can exist, and are seen in far-from-equilibrium systems in many fields, including chemistry, biology and physics. There has been particular interest in studying their properties in mode-locked lasers, but experiments have been limited by the inability to track the dynamical soliton evolution in real time. Here, we use simultaneous dispersive Fourier transform and time-lens measurements to completely characterize the spectral and temporal evolution of ultrashort dissipative solitons as their dynamics pass through a transient unstable regime with complex break-up and collisions before stabilization. Further insight is obtained from reconstruction of the soliton amplitude and phase and calculation of the corresponding complex-valued eigenvalue spectrum. These findings show how real-time measurements provide new insights into ultrafast transient dynamics in optics.

Role of lake-wide prey fish survey in understanding ecosystem dynamics and managing fisheries of Lake Michigan

USGS Publications Warehouse

Madenjian, Charles P.; Edsall, T.; Munawar, M.

2005-01-01

With this study, the role of this lake-wide prey fish survey in both understanding the dynamics of the Lake Michigan ecosystem and managing Lake Michigan fisheries was documented. The complexity of ecosystems is such that long-term study is required before the dynamics of the ecosystem can be understoond. Furthermore, long-term observation is needed before important or meaningful questions about ecosystem dynamics can be asked. My approach is to first illustrate, by example, the usefulness of the survey results in providing insights into the dynamics of the Lake Michigan ecosystem. Then, examples of direct application of the survey results toward Lake Michigan fisheries management are presented.

A framework to observe and evaluate the sustainability of human-natural systems in a complex dynamic context.

PubMed

Satanarachchi, Niranji; Mino, Takashi

2014-01-01

This paper aims to explore the prominent implications of the process of observing complex dynamics linked to sustainability in human-natural systems and to propose a framework for sustainability evaluation by introducing the concept of sustainability boundaries. Arguing that both observing and evaluating sustainability should engage awareness of complex dynamics from the outset, we try to embody this idea in the framework by two complementary methods, namely, the layer view- and dimensional view-based methods, which support the understanding of a reflexive and iterative sustainability process. The framework enables the observation of complex dynamic sustainability contexts, which we call observation metastructures, and enable us to map the contexts to sustainability boundaries.

Code Samples Used for Complexity and Control

NASA Astrophysics Data System (ADS)

Ivancevic, Vladimir G.; Reid, Darryn J.

2015-11-01

The following sections are included: * MathematicaⓇ Code * Generic Chaotic Simulator * Vector Differential Operators * NLS Explorer * 2C++ Code * C++ Lambda Functions for Real Calculus * Accelerometer Data Processor * Simple Predictor-Corrector Integrator * Solving the BVP with the Shooting Method * Linear Hyperbolic PDE Solver * Linear Elliptic PDE Solver * Method of Lines for a Set of the NLS Equations * C# Code * Iterative Equation Solver * Simulated Annealing: A Function Minimum * Simple Nonlinear Dynamics * Nonlinear Pendulum Simulator * Lagrangian Dynamics Simulator * Complex-Valued Crowd Attractor Dynamics * Freeform Fortran Code * Lorenz Attractor Simulator * Complex Lorenz Attractor * Simple SGE Soliton * Complex Signal Presentation * Gaussian Wave Packet * Hermitian Matrices * Euclidean L2-Norm * Vector/Matrix Operations * Plain C-Code: Levenberg-Marquardt Optimizer * Free Basic Code: 2D Crowd Dynamics with 3000 Agents

Dynamic Parameter Identification of Subject-Specific Body Segment Parameters Using Robotics Formalism: Case Study Head Complex.

PubMed

Díaz-Rodríguez, Miguel; Valera, Angel; Page, Alvaro; Besa, Antonio; Mata, Vicente

2016-05-01

Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.

A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks

PubMed Central

Schaffer, Evan S.; Ostojic, Srdjan; Abbott, L. F.

2013-01-01

Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons. PMID:24204236

Brownian Dynamics and Molecular Dynamics Study of the Association between Hydrogenase and Ferredoxin from Chlamydomonas reinhardtii

PubMed Central

Long, Hai; Chang, Christopher H.; King, Paul W.; Ghirardi, Maria L.; Kim, Kwiseon

2008-01-01

The [FeFe] hydrogenase from the green alga Chlamydomonas reinhardtii can catalyze the reduction of protons to hydrogen gas using electrons supplied from photosystem I and transferred via ferredoxin. To better understand the association of the hydrogenase and the ferredoxin, we have simulated the process over multiple timescales. A Brownian dynamics simulation method gave an initial thorough sampling of the rigid-body translational and rotational phase spaces, and the resulting trajectories were used to compute the occupancy and free-energy landscapes. Several important hydrogenase-ferredoxin encounter complexes were identified from this analysis, which were then individually simulated using atomistic molecular dynamics to provide more details of the hydrogenase and ferredoxin interaction. The ferredoxin appeared to form reasonable complexes with the hydrogenase in multiple orientations, some of which were good candidates for inclusion in a transition state ensemble of configurations for electron transfer. PMID:18621810

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics.

PubMed

Hou, Yue; Konen, Jessica; Brat, Daniel J; Marcus, Adam I; Cooper, Lee A D

2018-05-08

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

Identifying partial topology of complex dynamical networks via a pinning mechanism

NASA Astrophysics Data System (ADS)

Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an

2018-04-01

In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.

The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

PubMed

Blower, Sally; Go, Myong-Hyun

2011-07-19

Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability.

Inertial particle dynamics in large artery flows - Implications for modeling arterial embolisms.

PubMed

Mukherjee, Debanjan; Shadden, Shawn C

2017-02-08

The complexity of inertial particle dynamics through swirling chaotic flow structures characteristic of pulsatile large-artery hemodynamics renders significant challenges in predictive understanding of transport of such particles. This is specifically crucial for arterial embolisms, where knowledge of embolus transport to major vascular beds helps in disease diagnosis and surgical planning. Using a computational framework built upon image-based CFD and discrete particle dynamics modeling, a multi-parameter sampling-based study was conducted on embolic particle dynamics and transport. The results highlighted the strong influence of material properties, embolus size, release instance, and embolus source on embolus distribution to the cerebral, renal and mesenteric, and ilio-femoral vasculature beds. The study also isolated the importance of shear-gradient lift, and elastohydrodynamic contact, in affecting embolic particle transport. Near-wall particle re-suspension due to lift alters aortogenic embolic particle dynamics significantly as compared to cardiogenic. The observations collectively indicated the complex interplay of particle inertia, fluid-particle density ratio, and wall collisions, with chaotic flow structures, which render the overall motion of the particles to be non-trivially dispersive in nature. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamical footprint of cross-reactivity in a human autoimmune T-cell receptor

NASA Astrophysics Data System (ADS)

Kumar, Amit; Delogu, Francesco

2017-02-01

The present work focuses on the dynamical aspects of cross-reactivity between myelin based protein (MBP) self-peptide and two microbial peptides (UL15, PMM) for Hy.1B11 T-cell receptor (TCR). This same TCR was isolated from a patient suffering from multiple sclerosis (MS). The study aims at highlighting the chemical interactions underlying recognition mechanisms between TCR and the peptides presented by Major Histocompatibility Complex (MHC) proteins, which form a crucial component in adaptive immune response against foreign antigens. Since the ability of a TCR to recognize different peptide antigens presented by MHC depends on its cross-reactivity, we used molecular dynamics methods to obtain atomistic detail on TCR-peptide-MHC complexes. Our results show how the dynamical basis of Hy.1B11 TCR’s cross-reactivity is rooted in a similar bridging interaction pattern across the TCR-peptide-MHC interface. Our simulations confirm the importance of TCR CDR3α E98 residue interaction with MHC and a predominant role of P6 peptide residue in MHC binding affinity. Altogether, our study provides energetic and dynamical insights into factors governing peptide recognition by the cross-reactive Hy.1B11 TCR, found in MS patient.

A Renormalization-Group Interpretation of the Connection between Criticality and Multifractals

NASA Astrophysics Data System (ADS)

Chang, Tom

2014-05-01

Turbulent fluctuations in space plasmas beget phenomena of dynamic complexity. It is known that dynamic renormalization group (DRG) may be employed to understand the concept of forced and/or self-organized criticality (FSOC), which seems to describe certain scaling features of space plasma turbulence. But, it may be argued that dynamic complexity is not just a phenomenon of criticality. It is therefore of interest to inquire if DRG may be employed to study complexity phenomena that are distinctly more complicated than dynamic criticality. Power law scaling generally comes about when the DRG trajectory is attracted to the vicinity of a fixed point in the phase space of the relevant dynamic plasma parameters. What happens if the trajectory lies within a domain influenced by more than one single fixed point or more generally if the transformation underlying the DRG is fully nonlinear? The global invariants of the group under such situations (if they exist) are generally not power laws. Nevertheless, as we shall argue, it may still be possible to talk about local invariants that are power laws with the nonlinearity of transformation prescribing a specific phenomenon as crossovers. It is with such concept in mind that we may provide a connection between the properties of dynamic criticality and multifractals from the point of view of DRG (T. Chang, Chapter VII, "An Introduction to Space Plasma Complexity", Cambridge University Press, 2014). An example in terms of the concepts of finite-size scaling (FSS) and rank-ordered multifractal analysis (ROMA) of a toy model shall be provided. Research partially supported by the US National Science Foundation and the European Community's Seventh Framework Programme (FP7/ 2007-2013) under Grant agreement no. 313038/STORM.

Single-molecule FRET studies of the cooperative and non-cooperative binding kinetics of the bacteriophage T4 single-stranded DNA binding protein (gp32) to ssDNA lattices at replication fork junctions

PubMed Central

Lee, Wonbae; Gillies, John P.; Jose, Davis; Israels, Brett A.; von Hippel, Peter H.; Marcus, Andrew H.

2016-01-01

Gene 32 protein (gp32) is the single-stranded (ss) DNA binding protein of the bacteriophage T4. It binds transiently and cooperatively to ssDNA sequences exposed during the DNA replication process and regulates the interactions of the other sub-assemblies of the replication complex during the replication cycle. We here use single-molecule FRET techniques to build on previous thermodynamic studies of gp32 binding to initiate studies of the dynamics of the isolated and cooperative binding of gp32 molecules within the replication complex. DNA primer/template (p/t) constructs are used as models to determine the effects of ssDNA lattice length, gp32 concentration, salt concentration, binding cooperativity and binding polarity at p/t junctions. Hidden Markov models (HMMs) and transition density plots (TDPs) are used to characterize the dynamics of the multi-step assembly pathway of gp32 at p/t junctions of differing polarity, and show that isolated gp32 molecules bind to their ssDNA targets weakly and dissociate quickly, while cooperatively bound dimeric or trimeric clusters of gp32 bind much more tightly, can ‘slide’ on ssDNA sequences, and exhibit binding dynamics that depend on p/t junction polarities. The potential relationships of these binding dynamics to interactions with other components of the T4 DNA replication complex are discussed. PMID:27694621

Complex dynamic in ecological time series

Treesearch

Peter Turchin; Andrew D. Taylor

1992-01-01

Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a methodology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting...

Investigation of the Dynamics of Coherent Structure, BBF, and Intermittent Turbulence in Earth's Magnetotail: A Study of Complexity in Nonlinear Space Plasmas

NASA Technical Reports Server (NTRS)

Chang, Tom

2005-01-01

We have achieved all the goals stated in our grant proposal. Specifically, these include: 1. The understanding of the complexity induced nonlinear spatiotemporal coherent structures and the coexisting propagating modes. 2. The understanding of the intermittent turbulence and energization process of the observed Bursty Bulk Flows (BBF's) in the Earth s magnetotail. 3. The development of "anisotropic three-dimensional complexity" in the plasma sheet due to localized merging and interactions of the magnetic coherent structures. 4. The study of fluctuation-induced nonlinear instabilities and their role in the reconfiguration of magnetic topologies in the magnetotail based on the concepts of the dynamic renormalization group. 5. The acceleration of ions due to the intermittent turbulence of propagating and nonpropagating fluctuations. In the following, we include lists of our published papers, invited talks, and professional activities. A detailed description of our accomplished research results is given..

Logical Interactions in AN Expanded Space

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka

Understanding the emergent behavior in many complex systems in the physical world and society requires a detailed study of dynamical phenomena occurring and mutually coupled at different scales. The brain processes underlying the social conduct of each, and the emergent social behavior of interacting individuals on a larger scale, represent striking examples of the multiscale complexity. Studies of the human brain, a paradigm of a complex functional system, are enabled by a wealth of brain imaging data that provide clues of how we comprehend space, time, languages, numbers, and differentiate normal from diseased individuals, for example. The social brain, a neural basis for social cognition, represents a dynamically organized part of the brain which is involved in the inference of thoughts, feelings, and intentions going on in the brains of others. Research in this currently unexplored area opens a new perspective on the genesis of the societal organization at different levels and the associated social values...

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

NASA Astrophysics Data System (ADS)

Chouzouris, Teresa; Omelchenko, Iryna; Zakharova, Anna; Hlinka, Jaroslav; Jiruska, Premysl; Schöll, Eckehard

2018-04-01

Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

Patterns of Negotiation

NASA Astrophysics Data System (ADS)

Sood, Suresh; Pattinson, Hugh

Traditionally, face-to-face negotiations in the real world have not been looked at as a complex systems interaction of actors resulting in a dynamic and potentially emergent system. If indeed negotiations are an outcome of a dynamic interaction of simpler behavior just as with a complex system, we should be able to see the patterns contributing to the complexities of a negotiation under study. This paper and the supporting research sets out to show B2B (business-to-business) negotiations as complex systems of interacting actors exhibiting dynamic and emergent behavior. This paper discusses the exploratory research based on negotiation simulations in which a large number of business students participate as buyers and sellers. The student interactions are captured on video and a purpose built research method attempts to look for patterns of interactions between actors using visualization techniques traditionally reserved to observe the algorithmic complexity of complex systems. Students are videoed negotiating with partners. Each video is tagged according to a recognized classification and coding scheme for negotiations. The classification relates to the phases through which any particular negotiation might pass, such as laughter, aggression, compromise, and so forth — through some 30 possible categories. Were negotiations more or less successful if they progressed through the categories in different ways? Furthermore, does the data depict emergent pathway segments considered to be more or less successful? This focus on emergence within the data provides further strong support for face-to-face (F2F) negotiations to be construed as complex systems.

Professor Daniel M Segal and studies of collision and `half-collision' complexes at Imperial College London and Oxford University

NASA Astrophysics Data System (ADS)

Burnett, Keith

2018-03-01

We discuss Danny Segal's key roles in the development of the spectroscopy of collision complexes at Imperial College and Oxford. We explain how his work lead to a number of new insights into collision dynamics in external fields.

Rapid and Specific Method for Evaluating Streptomyces Competitive Dynamics in Complex Soil Communities

USDA-ARS?s Scientific Manuscript database

Quantifying target microbial populations in complex communities remains a barrier to studying species interactions in soil environments. Quantitative real-time PCR (qPCR) offers a rapid and specific means to assess populations of target microorganisms. SYBR Green and TaqMan-based qPCR assays were de...

Using LANDIS II to study the effects of global change in Siberia

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly Z. Shvidenko; Robert M. Scheller

2010-01-01

Landscape dynamics are characterized by complex interactions among multiple disturbance regimes, anthropogenic use and management, and the mosaic of diverse ecological conditions. LANDIS-IT is a landscape forest succession and disturbance model that independently simulates multiple ecological and disturbance processes, accounting for complex interactions to predict...

Using measures of information content and complexity of time series as hydrologic metrics

USDA-ARS?s Scientific Manuscript database

The information theory has been previously used to develop metrics that allowed to characterize temporal patterns in soil moisture dynamics, and to evaluate and to compare performance of soil water flow models. The objective of this study was to apply information and complexity measures to characte...

Enhanced electric dipole transition in lanthanide complex with organometallic ruthenocene units.

PubMed

Hasegawa, Yasuchika; Sato, Nao; Hirai, Yuichi; Nakanishi, Takayuki; Kitagawa, Yuichi; Kobayashi, Atsushi; Kato, Masako; Seki, Tomohiro; Ito, Hajime; Fushimi, Koji

2015-05-21

Enhanced luminescence of a lanthanide complex with dynamic polarization of the excited state and molecular motion is introduced. The luminescent lanthanide complex is composed of one Eu(hfa)3 (hfa, hexafluoroacetylacetonate) and two phosphine oxide ligands with ruthenocenyl units Rc, [Eu(hfa)3(RcPO)2] (RcPO = diphenylphosphorylruthenocene). The ruthenocenyl units in the phosphine oxide ligands play an important role of switching for dynamic molecular polarization and motion in liquid media. The oxidation states of the ruthenocenyl unit (Rc(1+)/Rc(1+)) are controlled by potentiostatic polarization. Eu(III) complexes attached with bidentate phosphine oxide ligands containing ruthenocenyl units, [Eu(hfa)3(RcBPO)] (RcBPO = 1,1'-bis(diphenylphosphoryl)ruthenocene), and with bidentate phosphine oxide ligands, [Eu(hfa)3(BIPHEPO)] (BIPHEPO =1,1'-biphenyl-2,2'-diylbis(diphenylphosphine oxide), were also prepared as references. The coordination structures and electrochemical properties were analyzed using single crystal X-ray analysis, cyclic voltammetry, and absorption spectroscopy measurements. The luminescence properties were estimated using an optoelectrochemical cell. Under potentiostatic polarization, a significant enhancement of luminescence was successfully observed for [Eu(hfa)3(RcPO)2], while no spectral change was observed for [Eu(hfa)3(RcBPO)]. In this study, the remarkable enhanced luminescence phenomena of Eu(III) complex based on the dynamic molecular motion under potentiostatic polarization have been performed.

The Use of Electrospray Mass Spectrometry to Determine Speciation in a Dynamic Combinatorial Library for Anion Recognition

PubMed Central

Phillips, Hazel I A; Chernikov, Aleksey V; Fletcher, Nicholas C; Ashcroft, Alison E; Ault, James R; Filby, Maria H; Wilson, Andrew J

2012-01-01

The composition of a dynamic mixture of similar 2,2′-bipyridine complexes of iron(II) bearing either an amide (5-benzylamido-2,2′-bipyridine and 5-(2-methoxyethane)amido-2,2′-bipyridine) or an ester (2,2′-bipyridine-5-carboxylic acid benzylester and 2,2′-bipyridine-5-carboxylic acid 2-methoxyethane ester) side chain have been evaluated by electrospray mass spectroscopy in acetonitrile. The time taken for the complexes to come to equilibrium appears to be dependent on the counteranion, with chloride causing a rapid redistribution of two preformed heteroleptic complexes (of the order of 1 hour), whereas the time it takes in the presence of tetrafluoroborate salts is in excess of 24 h. Similarly the final distribution of products is dependent on the anion present, with the presence of chloride, and to a lesser extent bromide, preferring three amide-functionalized ligands, and a slight preference for an appended benzyl over a methoxyethyl group. Furthermore, for the first time, this study shows that the distribution of a dynamic library of metal complexes monitored by ESI-MS can adapt following the introduction of a different anion, in this case tetrabutylammonium chloride to give the most favoured heteroleptic complex despite the increasing ionic strength of the solution. PMID:22996943

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Decrypting the structural, dynamic, and energetic basis of a monomeric kinesin interacting with a tubulin dimer in three ATPase states by all-atom molecular dynamics simulation.

PubMed

Chakraborty, Srirupa; Zheng, Wenjun

2015-01-27

We have employed molecular dynamics (MD) simulation to investigate, with atomic details, the structural dynamics and energetics of three major ATPase states (ADP, APO, and ATP state) of a human kinesin-1 monomer in complex with a tubulin dimer. Starting from a recently solved crystal structure of ATP-like kinesin-tubulin complex by the Knossow lab, we have used flexible fitting of cryo-electron-microscopy maps to construct new structural models of the kinesin-tubulin complex in APO and ATP state, and then conducted extensive MD simulations (total 400 ns for each state), followed by flexibility analysis, principal component analysis, hydrogen bond analysis, and binding free energy analysis. Our modeling and simulation have revealed key nucleotide-dependent changes in the structure and flexibility of the nucleotide-binding pocket (featuring a highly flexible and open switch I in APO state) and the tubulin-binding site, and allosterically coupled motions driving the APO to ATP transition. In addition, our binding free energy analysis has identified a set of key residues involved in kinesin-tubulin binding. On the basis of our simulation, we have attempted to address several outstanding issues in kinesin study, including the possible roles of β-sheet twist and neck linker docking in regulating nucleotide release and binding, the structural mechanism of ADP release, and possible extension and shortening of α4 helix during the ATPase cycle. This study has provided a comprehensive structural and dynamic picture of kinesin's major ATPase states, and offered promising targets for future mutational and functional studies to investigate the molecular mechanism of kinesin motors.

All-atomic Molecular Dynamic Studies of Human CDK8: Insight into the A-loop, Point Mutations and Binding with Its Partner CycC

PubMed Central

Xu, Wu; Amire-Brahimi, Benjamin; Xie, Xiao-Jun; Huang, Liying; Ji, Jun-Yuan

2014-01-01

The Mediator, a conserved multisubunit protein complex in eukaryotic organisms, regulates gene expression by bridging sequence-specific DNA-binding transcription factors to the general RNA polymerase II machinery. In yeast, Mediator complex is organized in three core modules (head, middle and tail) and a separable ‘CDK8 submodule’ consisting of four subunits including Cyclin-dependent kinase CDK8 (CDK8), Cyclin C (CycC), MED12, and MED13. The 3-D structure of human CDK8-CycC complex has been recently experimentally determined. To take advantage of this structure and the improved theoretical calculation methods, we have performed molecular dynamic simulations to study dynamics of CDK8 and two CDK8 point mutations (D173A and D189N), which have been identified in human cancers, with and without full length of the A-loop as well as the binding between CDK8 and CycC. We found that CDK8 structure gradually loses two helical structures during the 50-ns molecular dynamic simulation, likely due to the presence of the full-length A-loop. In addition, our studies showed the hydrogen bond occupation of the CDK8 A-loop increases during the first 20-ns MD simulation and stays stable during the later 30-ns MD simulation. Four residues in the A-loop of CDK8 have high hydrogen bond occupation, while the rest residues have low or no hydrogen bond occupation. The hydrogen bond dynamic study of the A-loop residues exhibits three types of changes: increasing, decreasing, and stable. Furthermore, the 3-D structures of CDK8 point mutations D173A, D189N, T196A and T196D have been built by molecular modeling and further investigated by 50-ns molecular dynamic simulations. D173A has the highest average potential energy, while T196D has the lowest average potential energy, indicating that T196D is the most stable structure. Finally, we calculated theoretical binding energy of CDK8 and CycC by MM/PBSA and MM/GBSA methods, and the negative values obtained from both methods demonstrate stability of CDK8-CycC complex. Taken together, these analyses will improve our understanding of the exact functions of CDK8 and the interaction with its partner CycC. PMID:24754906

Stochastic tools hidden behind the empirical dielectric relaxation laws

NASA Astrophysics Data System (ADS)

Stanislavsky, Aleksander; Weron, Karina

2017-03-01

The paper is devoted to recent advances in stochastic modeling of anomalous kinetic processes observed in dielectric materials which are prominent examples of disordered (complex) systems. Theoretical studies of dynamical properties of ‘structures with variations’ (Goldenfield and Kadanoff 1999 Science 284 87-9) require application of such mathematical tools—by means of which their random nature can be analyzed and, independently of the details distinguishing various systems (dipolar materials, glasses, semiconductors, liquid crystals, polymers, etc), the empirical universal kinetic patterns can be derived. We begin with a brief survey of the historical background of the dielectric relaxation study. After a short outline of the theoretical ideas providing the random tools applicable to modeling of relaxation phenomena, we present probabilistic implications for the study of the relaxation-rate distribution models. In the framework of the probability distribution of relaxation rates we consider description of complex systems, in which relaxing entities form random clusters interacting with each other and single entities. Then we focus on stochastic mechanisms of the relaxation phenomenon. We discuss the diffusion approach and its usefulness for understanding of anomalous dynamics of relaxing systems. We also discuss extensions of the diffusive approach to systems under tempered random processes. Useful relationships among different stochastic approaches to the anomalous dynamics of complex systems allow us to get a fresh look at this subject. The paper closes with a final discussion on achievements of stochastic tools describing the anomalous time evolution of complex systems.

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

Transition Manifolds of Complex Metastable Systems

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Hydrogen exchange differences between chemoreceptor signaling complexes localize to functionally important subdomains.

PubMed

Koshy, Seena S; Li, Xuni; Eyles, Stephen J; Weis, Robert M; Thompson, Lynmarie K

2014-12-16

The goal of understanding mechanisms of transmembrane signaling, one of many key life processes mediated by membrane proteins, has motivated numerous studies of bacterial chemotaxis receptors. Ligand binding to the receptor causes a piston motion of an α helix in the periplasmic and transmembrane domains, but it is unclear how the signal is then propagated through the cytoplasmic domain to control the activity of the associated kinase CheA. Recent proposals suggest that signaling in the cytoplasmic domain involves opposing changes in dynamics in different subdomains. However, it has been difficult to measure dynamics within the functional system, consisting of extended arrays of receptor complexes with two other proteins, CheA and CheW. We have combined hydrogen exchange mass spectrometry with vesicle template assembly of functional complexes of the receptor cytoplasmic domain to reveal that there are significant signaling-associated changes in exchange, and these changes localize to key regions of the receptor involved in the excitation and adaptation responses. The methylation subdomain exhibits complex changes that include slower hydrogen exchange in complexes in a kinase-activating state, which may be partially consistent with proposals that this subdomain is stabilized in this state. The signaling subdomain exhibits significant protection from hydrogen exchange in complexes in a kinase-activating state, suggesting a tighter and/or larger interaction interface with CheA and CheW in this state. These first measurements of the stability of protein subdomains within functional signaling complexes demonstrate the promise of this approach for measuring functionally important protein dynamics within the various physiologically relevant states of multiprotein complexes.

Hydrogen Exchange Differences between Chemoreceptor Signaling Complexes Localize to Functionally Important Subdomains

PubMed Central

2015-01-01

The goal of understanding mechanisms of transmembrane signaling, one of many key life processes mediated by membrane proteins, has motivated numerous studies of bacterial chemotaxis receptors. Ligand binding to the receptor causes a piston motion of an α helix in the periplasmic and transmembrane domains, but it is unclear how the signal is then propagated through the cytoplasmic domain to control the activity of the associated kinase CheA. Recent proposals suggest that signaling in the cytoplasmic domain involves opposing changes in dynamics in different subdomains. However, it has been difficult to measure dynamics within the functional system, consisting of extended arrays of receptor complexes with two other proteins, CheA and CheW. We have combined hydrogen exchange mass spectrometry with vesicle template assembly of functional complexes of the receptor cytoplasmic domain to reveal that there are significant signaling-associated changes in exchange, and these changes localize to key regions of the receptor involved in the excitation and adaptation responses. The methylation subdomain exhibits complex changes that include slower hydrogen exchange in complexes in a kinase-activating state, which may be partially consistent with proposals that this subdomain is stabilized in this state. The signaling subdomain exhibits significant protection from hydrogen exchange in complexes in a kinase-activating state, suggesting a tighter and/or larger interaction interface with CheA and CheW in this state. These first measurements of the stability of protein subdomains within functional signaling complexes demonstrate the promise of this approach for measuring functionally important protein dynamics within the various physiologically relevant states of multiprotein complexes. PMID:25420045

A Dynamic Ensemble for Second Language Research: Putting Complexity Theory into Practice

ERIC Educational Resources Information Center

Hiver, Phil; Al-Hoorie, Ali H.

2016-01-01

In this article, we introduce a template of methodological considerations, termed "the dynamic ensemble," for scholars doing or evaluating empirical second language development (SLD) research within a complexity/dynamic systems theory (CDST) framework. Given that CDST principles have yielded significant insight into SLD and have become…

Spatial operator algebra for flexible multibody dynamics

NASA Technical Reports Server (NTRS)

Jain, A.; Rodriguez, G.

1993-01-01

This paper presents an approach to modeling the dynamics of flexible multibody systems such as flexible spacecraft and limber space robotic systems. A large number of degrees of freedom and complex dynamic interactions are typical in these systems. This paper uses spatial operators to develop efficient recursive algorithms for the dynamics of these systems. This approach very efficiently manages complexity by means of a hierarchy of mathematical operations.

Complexity and time asymmetry of heart rate variability are altered in acute mental stress.

PubMed

Visnovcova, Z; Mestanik, M; Javorka, M; Mokra, D; Gala, M; Jurko, A; Calkovska, A; Tonhajzerova, I

2014-07-01

We aimed to study the complexity and time asymmetry of short-term heart rate variability (HRV) as an index of complex neurocardiac control in response to stress using symbolic dynamics and time irreversibility methods. ECG was recorded at rest and during and after two stressors (Stroop, arithmetic test) in 70 healthy students. Symbolic dynamics parameters (NUPI, NCI, 0V%, 1V%, 2LV%, 2UV%), and time irreversibility indices (P%, G%, E) were evaluated. Additionally, HRV magnitude was quantified by linear parameters: spectral powers in low (LF) and high frequency (HF) bands. Our results showed a reduction of HRV complexity in stress (lower NUPI with both stressors, lower NCI with Stroop). Pattern classification analysis revealed significantly higher 0V% and lower 2LV% with both stressors, indicating a shift in sympathovagal balance, and significantly higher 1V% and lower 2UV% with Stroop. An unexpected result was found in time irreversibility: significantly lower G% and E with both stressors, P% index significantly declined only with arithmetic test. Linear HRV analysis confirmed vagal withdrawal (lower HF) with both stressors; LF significantly increased with Stroop and decreased with arithmetic test. Correlation analysis revealed no significant associations between symbolic dynamics and time irreversibility. Concluding, symbolic dynamics and time irreversibility could provide independent information related to alterations of neurocardiac control integrity in stress-related disease.

Analysis of the interactions between GMF and Arp2/3 complex in two binding sites by molecular dynamics simulation.

PubMed

Popinako, A; Antonov, M; Dibrova, D; Chemeris, A; Sokolova, O S

2018-02-05

The Arp2/3 complex plays a key role in nucleating actin filaments branching. The glia maturation factor (GMF) competes with activators for interacting with the Arp2/3 complex and initiates the debranching of actin filaments. In this study, we performed a comparative analysis of interactions between GMF and the Arp2/3 complex and identified new amino acid residues involved in GMF binding to the Arp2/3 complex at two separate sites, revealed by X-ray and single particle EM techniques. Using molecular dynamics simulations we demonstrated the quantitative and qualitative changes in hydrogen bonds upon binding with GMF. We identified the specific amino acid residues in GMF and Arp2/3 complex that stabilize the interactions and estimated the mean force profile for the GMF using umbrella sampling. Phylogenetic and structural analyses of the recently defined GMF binding site on the Arp3 subunit indicate a new mechanism for Arp2/3 complex inactivation that involves interactions between the Arp2/3 complex and GMF at two binding sites. Copyright © 2018 Elsevier Inc. All rights reserved.

Global sensitivity and uncertainty analysis of the nitrate leaching and crop yield simulation under different water and nitrogen management practices

USDA-ARS?s Scientific Manuscript database

Agricultural system models have become important tools in studying water and nitrogen (N) dynamics, as well as crop growth, under different management practices. Complexity in input parameters often leads to significant uncertainty when simulating dynamic processes such as nitrate leaching or crop y...

Mapping sources, sinks, and connectivity using a simulation model of northern spotted owls- 5/20/2014

EPA Science Inventory

Source-sink dynamics are an emergent property of complex species- landscape interactions. A better understanding of how human activities affect source-sink dynamics has the potential to inform and improve the management of species of conservation concern. Here we use a study of t...

Dynamic Development in Speaking versus Writing in Identical Twins

ERIC Educational Resources Information Center

Chan, HuiPing; Verspoor, Marjolijn; Vahtrick, Louisa

2015-01-01

Taking a dynamic usage-based perspective, this longitudinal case study compares the development of sentence complexity in speaking versus writing in two beginner Taiwanese learners of English (identical twins) in an extensive corpus consisting of 100 oral and 100 written texts of approximately 200 words produced by each twin over 8 months. Three…

Molecular dynamics simulations and statistical coupling analysis reveal functional coevolution network of oncogenic mutations in the CDKN2A-CDK6 complex.

PubMed

Wang, Jingwen; Zhao, Yuqi; Wang, Yanjie; Huang, Jingfei

2013-01-16

Coevolution between proteins is crucial for understanding protein-protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural-functional integrity. In this study, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on the CDK6-CDKN2A protein complex to evaluate coevolution between proteins. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37 interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in the CDK6-CDKN2A complex can be helpful for designing protein engineering experiments. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Symmetric and Asymmetric Tendencies in Stable Complex Systems

PubMed Central

Tan, James P. L.

2016-01-01

A commonly used approach to study stability in a complex system is by analyzing the Jacobian matrix at an equilibrium point of a dynamical system. The equilibrium point is stable if all eigenvalues have negative real parts. Here, by obtaining eigenvalue bounds of the Jacobian, we show that stable complex systems will favor mutualistic and competitive relationships that are asymmetrical (non-reciprocative) and trophic relationships that are symmetrical (reciprocative). Additionally, we define a measure called the interdependence diversity that quantifies how distributed the dependencies are between the dynamical variables in the system. We find that increasing interdependence diversity has a destabilizing effect on the equilibrium point, and the effect is greater for trophic relationships than for mutualistic and competitive relationships. These predictions are consistent with empirical observations in ecology. More importantly, our findings suggest stabilization algorithms that can apply very generally to a variety of complex systems. PMID:27545722

Symmetric and Asymmetric Tendencies in Stable Complex Systems.

PubMed

Tan, James P L

2016-08-22

A commonly used approach to study stability in a complex system is by analyzing the Jacobian matrix at an equilibrium point of a dynamical system. The equilibrium point is stable if all eigenvalues have negative real parts. Here, by obtaining eigenvalue bounds of the Jacobian, we show that stable complex systems will favor mutualistic and competitive relationships that are asymmetrical (non-reciprocative) and trophic relationships that are symmetrical (reciprocative). Additionally, we define a measure called the interdependence diversity that quantifies how distributed the dependencies are between the dynamical variables in the system. We find that increasing interdependence diversity has a destabilizing effect on the equilibrium point, and the effect is greater for trophic relationships than for mutualistic and competitive relationships. These predictions are consistent with empirical observations in ecology. More importantly, our findings suggest stabilization algorithms that can apply very generally to a variety of complex systems.

Insights into cellulosome assembly and dynamics: from dissection to reconstruction of the supramolecular enzyme complex.

PubMed

Smith, Steven P; Bayer, Edward A

2013-10-01

Cellulosomes are multi-enzyme complexes produced by anaerobic bacteria for the efficient deconstruction of plant cell wall polysaccharides. The assembly of enzymatic subunits onto a central non-catalytic scaffoldin subunit is mediated by a highly specific interaction between the enzyme-bearing dockerin modules and the resident cohesin modules of the scaffoldin, which affords their catalytic activities to work synergistically. The scaffoldin also imparts substrate-binding and bacterial-anchoring properties, the latter of which involves a second cohesin-dockerin interaction. Recent structure-function studies reveal an ever-growing array of unique and increasingly complex cohesin-dockerin complexes and cellulosomal enzymes with novel activities. A 'build' approach involving multimodular cellulosomal segments has provided a structural model of an organized yet conformationally dynamic supramolecular assembly with the potential to form higher order structures. Copyright © 2013. Published by Elsevier Ltd.

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

Heartbeat Complexity Modulation in Bipolar Disorder during Daytime and Nighttime.

PubMed

Nardelli, Mimma; Lanata, Antonio; Bertschy, Gilles; Scilingo, Enzo Pasquale; Valenza, Gaetano

2017-12-20

This study reports on the complexity modulation of heartbeat dynamics in patients affected by bipolar disorder. In particular, a multiscale entropy analysis was applied to the R-R interval series, that were derived from electrocardiographic (ECG) signals for a group of nineteen subjects comprised of eight patients and eleven healthy control subjects. They were monitored using a textile-based sensorized t-shirt during the day and overnight for a total of 47 diurnal and 27 nocturnal recordings. Patients showed three different mood states: depression, hypomania and euthymia. Results show a clear loss of complexity during depressive and hypomanic states as compared to euthymic and healthy control states. In addition, we observed that a more significant complexity modulation among healthy and pathological mood states occurs during the night. These findings suggest that bipolar disorder is associated with an enhanced sleep-related dysregulation of the Autonomic Nervous System (ANS) activity, and that heartbeat complex dynamics may serve as a viable marker of pathological conditions in mental health.

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes.

PubMed

Kürten, Charlotte; Syrén, Per-Olof

2016-01-16

Enzyme catalysis evolved in an aqueous environment. The influence of solvent dynamics on catalysis is, however, currently poorly understood and usually neglected. The study of water dynamics in enzymes and the associated thermodynamical consequences is highly complex and has involved computer simulations, nuclear magnetic resonance (NMR) experiments, and calorimetry. Water tunnels that connect the active site with the surrounding solvent are key to solvent displacement and dynamics. The protocol herein allows for the engineering of these motifs for water transport, which affects specificity, activity and thermodynamics. By providing a biophysical framework founded on theory and experiments, the method presented herein can be used by researchers without previous expertise in computer modeling or biophysical chemistry. The method will advance our understanding of enzyme catalysis on the molecular level by measuring the enthalpic and entropic changes associated with catalysis by enzyme variants with obstructed water tunnels. The protocol can be used for the study of membrane-bound enzymes and other complex systems. This will enhance our understanding of the importance of solvent reorganization in catalysis as well as provide new catalytic strategies in protein design and engineering.

Microphysics of liquid complex plasmas in equilibrium and non-equilibrium systems

NASA Astrophysics Data System (ADS)

Piel, Alexander; Block, Dietmar; Melzer, André; Mulsow, Matthias; Schablinski, Jan; Schella, André; Wieben, Frank; Wilms, Jochen

2018-05-01

The dynamic evolution of the microscopic structure of solid and liquid phases of complex plasmas is studied experimentally and by means of molecular dynamics (MD) simulations. In small finite systems, the cooperative motion can be described in terms of discrete modes. These modes are studied with different experimental approaches. Using diffuse scattered laser light, applying laser tweezer forces to individual particles, and periodic laser pulses, the excitation of modes is investigated. The instantaneous normal mode analysis of experimental data from two-dimensional liquid clusters gives access to the local dynamics of the liquid phase. Our investigations shed light on the role of compressional and shear modes as well as the determination of diffusion constants and melting temperatures in finite systems. Special attention is paid to hydrodynamic situations with a stationary inhomogeneous dust flow. MD simulations allow to study the collective motion in the shell of nearest neighbors, which can be linked to smooth and sudden changes of the macroscopic flow. Finally, the observed micro-motion in all situations above allows to shed light on the preference of shear-like over compressional motion in terms of a minimized potential energy and a dynamic incompressibility.

The allosteric communication pathways in KIX domain of CBP.

PubMed

Palazzesi, Ferruccio; Barducci, Alessandro; Tollinger, Martin; Parrinello, Michele

2013-08-27

Allosteric regulation plays an important role in a myriad of biomacromolecular processes. Specifically, in a protein, the process of allostery refers to the transmission of a local perturbation, such as ligand binding, to a distant site. Decades after the discovery of this phenomenon, models built on static images of proteins are being reconsidered with the knowledge that protein dynamics plays an important role in its function. Molecular dynamics simulations are a valuable tool for studying complex biomolecular systems, providing an atomistic description of their structure and dynamics. Unfortunately, their predictive power has been limited by the complexity of the biomolecule free-energy surface and by the length of the allosteric timescale (in the order of milliseconds). In this work, we are able to probe the origins of the allosteric changes that transcription factor mixed lineage leukemia (MLL) causes to the interactions of KIX domain of CREB-binding protein (CBP) with phosphorylated kinase inducible domain (pKID), by combing all-atom molecular dynamics with enhanced sampling methods recently developed in our group. We discuss our results in relation to previous NMR studies. We also develop a general simulations protocol to study allosteric phenomena and many other biological processes that occur in the micro/milliseconds timescale.

Market Orientation within University Schools of Business: Can a Dynamical Systems Viewpoint Applied to a Non-Temporal Data Set Yield Valuable Insights for University Managers?

ERIC Educational Resources Information Center

Cox, John C.; Webster, Robert L.; Hammond, Kevin L.

2009-01-01

This study investigates the use of using complexity theory--the study of nonlinear dynamical systems of which chaos and catastrophe theory are subsets--in the analysis of a non temporal data set to derive valuable insights into the functioning of university schools of business. The approach is unusual in that studies of nonlinearity in complex…

Conformational analysis of GT1B ganglioside and its interaction with botulinum neurotoxin type B: a study by molecular modeling and molecular dynamics.

PubMed

Venkateshwari, Sureshkumar; Veluraja, Kasinadar

2012-01-01

The conformational property of oligosaccharide GT1B in aqueous environment was studied by molecular dynamics (MD) simulation using all-atom model. Based on the trajectory analysis, three prominent conformational models were proposed for GT1B. Direct and water-mediated hydrogen bonding interactions stabilize these structures. The molecular modeling and 15 ns MD simulation of the Botulinum Neuro Toxin/B (BoNT/B) - GT1B complex revealed that BoNT/B can accommodate the GT1B in the single binding mode. Least mobility was seen for oligo-GT1B in the binding pocket. The bound conformation of GT1B obtained from the MD simulation of the BoNT/B-GT1B complex bear a close conformational similarity with the crystal structure of BoNT/A-GT1B complex. The mobility noticed for Arg 1268 in the dynamics was accounted for its favorable interaction with terminal NeuNAc. The internal NeuNAc1 tends to form 10 hydrogen bonds with BoNT/B, hence specifying this particular site as a crucial space for the therapeutic design that can restrict the pathogenic activity of BoNT/B.

An empirical comparison of a dynamic software testability metric to static cyclomatic complexity

NASA Technical Reports Server (NTRS)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffrey E.

1993-01-01

This paper compares the dynamic testability prediction technique termed 'sensitivity analysis' to the static testability technique termed cyclomatic complexity. The application that we chose in this empirical study is a CASE generated version of a B-737 autoland system. For the B-737 system we analyzed, we isolated those functions that we predict are more prone to hide errors during system/reliability testing. We also analyzed the code with several other well-known static metrics. This paper compares and contrasts the results of sensitivity analysis to the results of the static metrics.

[Brownian dynamics simulations of protein-protein interactions in photosynthetic electron transport chain].

PubMed

Khruschev, S S; Abaturova, A M; Diakonova, A N; Fedorov, V A; Ustinin, D M; Kovalenko, I B; Riznichenko, G Yu; Rubin, A B

2015-01-01

The application of Brownian dynamics for simulation of transient protein-protein interactions is reviewed. The review focuses on theoretical basics of Brownian dynamics method, its particular implementations, advantages and drawbacks of the method. The outlook for future development of Brownian dynamics-based simulation techniques is discussed. Special attention is given to analysis of Brownian dynamics trajectories. The second part of the review is dedicated to the role of Brownian dynamics simulations in studying photosynthetic electron transport. Interactions of mobile electron carriers (plastocyanin, cytochrome c6, and ferredoxin) with their reaction partners (cytochrome b6f complex, photosystem I, ferredoxin:NADP-reductase, and hydrogenase) are considered.

Structural Dynamics Investigation of Human Family 1 & 2 Cystatin-Cathepsin L1 Interaction: A Comparison of Binding Modes.

PubMed

Nandy, Suman Kumar; Seal, Alpana

2016-01-01

Cystatin superfamily is a large group of evolutionarily related proteins involved in numerous physiological activities through their inhibitory activity towards cysteine proteases. Despite sharing the same cystatin fold, and inhibiting cysteine proteases through the same tripartite edge involving highly conserved N-terminal region, L1 and L2 loop; cystatins differ widely in their inhibitory affinity towards C1 family of cysteine proteases and molecular details of these interactions are still elusive. In this study, inhibitory interactions of human family 1 & 2 cystatins with cathepsin L1 are predicted and their stability and viability are verified through protein docking & comparative molecular dynamics. An overall stabilization effect is observed in all cystatins on complex formation. Complexes are mostly dominated by van der Waals interaction but the relative participation of the conserved regions varied extensively. While van der Waals contacts prevail in L1 and L2 loop, N-terminal segment chiefly acts as electrostatic interaction site. In fact the comparative dynamics study points towards the instrumental role of L1 loop in directing the total interaction profile of the complex either towards electrostatic or van der Waals contacts. The key amino acid residues surfaced via interaction energy, hydrogen bonding and solvent accessible surface area analysis for each cystatin-cathepsin L1 complex influence the mode of binding and thus control the diverse inhibitory affinity of cystatins towards cysteine proteases.

Magnetic storms and solar flares: can be analysed within similar mathematical framework with other extreme events?

NASA Astrophysics Data System (ADS)

Balasis, Georgios; Potirakis, Stelios M.; Papadimitriou, Constantinos; Zitis, Pavlos I.; Eftaxias, Konstantinos

2015-04-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to different extreme events, in order to support the suggestion that a dynamical analogy characterizes the generation of a single magnetic storm, solar flare, earthquake (in terms of pre-seismic electromagnetic signals) , epileptic seizure, and economic crisis. The analysis reveals that all the above mentioned different extreme events can be analyzed within similar mathematical framework. More precisely, we show that the populations of magnitudes of fluctuations included in all the above mentioned pulse-like-type time series follow the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar nonextensive q-parameter values. Moreover, based on a multidisciplinary statistical analysis we show that the extreme events are characterized by crucial common symptoms, namely: (i) high organization, high compressibility, low complexity, high information content; (ii) strong persistency; and (iii) existence of clear preferred direction of emerged activities. These symptoms clearly discriminate the appearance of the extreme events under study from the corresponding background noise.

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…

The Self as a Complex Dynamic System

ERIC Educational Resources Information Center

Mercer, Sarah

2011-01-01

This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…

The application of system dynamics modelling to environmental health decision-making and policy - a scoping review.

PubMed

Currie, Danielle J; Smith, Carl; Jagals, Paul

2018-03-27

Policy and decision-making processes are routinely challenged by the complex and dynamic nature of environmental health problems. System dynamics modelling has demonstrated considerable value across a number of different fields to help decision-makers understand and predict the dynamic behaviour of complex systems in support the development of effective policy actions. In this scoping review we investigate if, and in what contexts, system dynamics modelling is being used to inform policy or decision-making processes related to environmental health. Four electronic databases and the grey literature were systematically searched to identify studies that intersect the areas environmental health, system dynamics modelling, and decision-making. Studies identified in the initial screening were further screened for their contextual, methodological and application-related relevancy. Studies deemed 'relevant' or 'highly relevant' according to all three criteria were included in this review. Key themes related to the rationale, impact and limitation of using system dynamics in the context of environmental health decision-making and policy were analysed. We identified a limited number of relevant studies (n = 15), two-thirds of which were conducted between 2011 and 2016. The majority of applications occurred in non-health related sectors (n = 9) including transportation, public utilities, water, housing, food, agriculture, and urban and regional planning. Applications were primarily targeted at micro-level (local, community or grassroots) decision-making processes (n = 9), with macro-level (national or international) decision-making to a lesser degree. There was significant heterogeneity in the stated rationales for using system dynamics and the intended impact of the system dynamics model on decision-making processes. A series of user-related, technical and application-related limitations and challenges were identified. None of the reported limitations or challenges appeared unique to the application of system dynamics within the context of environmental health problems, but rather to the use of system dynamics in general. This review reveals that while system dynamics modelling is increasingly being used to inform decision-making related to environmental health, applications are currently limited. Greater application of system dynamics within this context is needed before its benefits and limitations can be fully understood.

Traditional Chinese medicine: potential approaches from modern dynamical complexity theories.

PubMed

Ma, Yan; Zhou, Kehua; Fan, Jing; Sun, Shuchen

2016-03-01

Despite the widespread use of traditional Chinese medicine (TCM) in clinical settings, proving its effectiveness via scientific trials is still a challenge. TCM views the human body as a complex dynamical system, and focuses on the balance of the human body, both internally and with its external environment. Such fundamental concepts require investigations using system-level quantification approaches, which are beyond conventional reductionism. Only methods that quantify dynamical complexity can bring new insights into the evaluation of TCM. In a previous article, we briefly introduced the potential value of Multiscale Entropy (MSE) analysis in TCM. This article aims to explain the existing challenges in TCM quantification, to introduce the consistency of dynamical complexity theories and TCM theories, and to inspire future system-level research on health and disease.

Topics in geophysical fluid dynamics: Atmospheric dynamics, dynamo theory, and climate dynamics

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

Ghil, M.; Childress, S.

1987-01-01

This text is the first study to apply systematically the successive bifurcations approach to complex time-dependent processes in large scale atmospheric dynamics, geomagnetism, and theoretical climate dynamics. The presentation of recent results on planetary-scale phenomena in the earth's atmosphere, ocean, cryosphere, mantle and core provides an integral account of mathematical theory and methods together with physical phenomena and processes. The authors address a number of problems in rapidly developing areas of geophysics, bringing into closer contact the modern tools of nonlinear mathematics and the novel problems of global change in the environment.

Effects of a hydrotherapy programme on symbolic and complexity dynamics of heart rate variability and aerobic capacity in fibromyalgia patients.

PubMed

Zamunér, Antonio Roberto; Andrade, Carolina P; Forti, Meire; Marchi, Andrea; Milan, Juliana; Avila, Mariana Arias; Catai, Aparecida Maria; Porta, Alberto; Silva, Ester

2015-01-01

To evaluate the effects of a hydrotherapy programme on aerobic capacity and linear and non-linear dynamics of heart rate variability (HRV) in women with fibromyalgia syndrome (FMS). 20 women with FMS and 20 healthy controls (HC) took part in the study. The FMS group was evaluated at baseline and after a 16-week hydrotherapy programme. All participants underwent cardiopulmonary exercise testing on a cycle ergometer and RR intervals recording in supine and standing positions. The HRV was analysed by linear and non-linear methods. The current level of pain, the tender points, the pressure pain threshold and the impact of FMS on quality of life were assessed. The FMS patients presented higher cardiac sympathetic modulation, lower vagal modulation and lower complexity of HRV in supine position than the HC. Only the HC decreased the complexity indices of HRV during orthostatic stimulus. After a 16-week hydrotherapy programme, the FMS patients increased aerobic capacity, decreased cardiac sympathetic modulation and increased vagal modulation and complexity dynamics of HRV in supine. The FMS patients also improved their cardiac autonomic adjustments to the orthostatic stimulus. Associations between improvements in non-linear dynamics of HRV and improvements in pain and in the impact of FMS on quality of life were found. A 16-week hydrotherapy programme proved to be effective in ameliorating symptoms, aerobic functional capacity and cardiac autonomic control in FMS patients. Improvements in the non-linear dynamics of HRV were related to improvements in pain and in the impact of FMS on quality of life.

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.

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

PubMed

Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

2017-04-15

Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain arrangements and dynamics. Principles of protein-RNA recognition and current approaches are reviewed and illustrated with recent studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Nearside-farside, local angular momentum and resummation theories: Useful tools for understanding the dynamics of complex-mode reactions

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

Hankel, Marlies, E-mail: m.hankel@uq.edu.au, E-mail: j.n.l.connor@manchester.ac.uk; Connor, J. N. L., E-mail: m.hankel@uq.edu.au, E-mail: j.n.l.connor@manchester.ac.uk

2015-07-15

A valuable tool for understanding the dynamics of direct reactions is Nearside-Farside (NF) scattering theory. It makes a decomposition of the (resummed) partial wave series for the scattering amplitude, both for the differential cross section (DCS) and the Local Angular Momentum (LAM). This paper makes the first combined application of these techniques to complex-mode reactions. We ask if NF theory is a useful tool for their identification, in particular, can it distinguish complex-mode from direct-mode reactions? We also ask whether NF theory can identify NF interference oscillations in the full DCSs of complex-mode reactions. Our investigation exploits the fact thatmore » accurate quantum scattering matrix elements have recently become available for complex-mode reactions. We first apply NF theory to two simple models for the scattering amplitude of a complex-mode reaction: One involves a single Legendre polynomial; the other involves a single Legendre function of the first kind, whose form is suggested by complex angular momentum theory. We then study, at fixed translational energies, four state-to-state complex-mode reactions. They are: S({sup 1}D) + HD → SH + D, S({sup 1}D) + DH → SD + H, N({sup 2}D) +H{sub 2} → NH + H, and H{sup +} + D{sub 2} → HD + D{sup +}. We compare the NF results for the DCSs and LAMs with those for a state-to-state direct reaction, namely, F + H{sub 2} → FH + H. We demonstrate that NF theory is a valuable tool for identifying and analyzing the dynamics of complex-mode reactions.« less

Cryo-EM of dynamic protein complexes in eukaryotic DNA replication.

PubMed

Sun, Jingchuan; Yuan, Zuanning; Bai, Lin; Li, Huilin

2017-01-01

DNA replication in Eukaryotes is a highly dynamic process that involves several dozens of proteins. Some of these proteins form stable complexes that are amenable to high-resolution structure determination by cryo-EM, thanks to the recent advent of the direct electron detector and powerful image analysis algorithm. But many of these proteins associate only transiently and flexibly, precluding traditional biochemical purification. We found that direct mixing of the component proteins followed by 2D and 3D image sorting can capture some very weakly interacting complexes. Even at 2D average level and at low resolution, EM images of these flexible complexes can provide important biological insights. It is often necessary to positively identify the feature-of-interest in a low resolution EM structure. We found that systematically fusing or inserting maltose binding protein (MBP) to selected proteins is highly effective in these situations. In this chapter, we describe the EM studies of several protein complexes involved in the eukaryotic DNA replication over the past decade or so. We suggest that some of the approaches used in these studies may be applicable to structural analysis of other biological systems. © 2016 The Protein Society.

Complexity and health professions education: a basic glossary.

PubMed

Mennin, Stewart

2010-08-01

The study of health professions education in the context of complexity science and complex adaptive systems involves different concepts and terminology that are likely to be unfamiliar to many health professions educators. A list of selected key terms and definitions from the literature of complexity science is provided to assist readers to navigate familiar territory from a different perspective. include agent, attractor, bifurcation, chaos, co-evolution, collective variable, complex adaptive systems, complexity science, deterministic systems, dynamical system, edge of chaos, emergence, equilibrium, far from equilibrium, fuzzy boundaries, linear system, non-linear system, random, self-organization and self-similarity.

A comparative study of magnetization dynamics in dinuclear dysprosium complexes featuring bridging chloride or trifluoromethanesulfonate ligands.

PubMed

Burns, Corey P; Wilkins, Branford O; Dickie, Courtney M; Latendresse, Trevor P; Vernier, Larry; Vignesh, Kuduva R; Bhuvanesh, Nattamai S; Nippe, Michael

2017-07-25

We utilized a rigid ligand platform PyCp 2 2- (PyCp 2 2- = [2,6-(CH 2 C 5 H 3 ) 2 C 5 H 3 N] 2- ) to isolate dinuclear Dy 3+ complexes [(PyCp 2 )Dy-(μ-O 2 SOCF 3 )] 2 (1) and [(PyCp 2 )Dy-(μ-Cl)] 2 (3) as well as the mononuclear complex (PyCp 2 )Dy(OSO 2 CF 3 )(thf) (2). Compounds 1 and 2 are the first examples of organometallic Dy 3+ complexes featuring triflate binding. The isolation of compounds 1 and 3 allows us to comparatively evaluate the effects of the bridging anions on the magnetization dynamics of the dinuclear systems. Our investigations show that although the exchange coupling interactions differ for 1 and 3, the dynamic magnetic properties are dominated by relaxation via the first excited state Kramers doublet of the individual Dy sites. Compounds 1 and 3 exhibit barriers to magnetization reversal (U eff = 49 cm -1 ) that can be favorably compared to those of the previously reported examples of [Cp 2 Dy(μ-Cl)] 2 (U eff = 26 cm -1 ) and [Cp 2 Dy(thf)(μ-Cl)] 2 (U eff = 34 cm -1 ).

Singular spectrum and singular entropy used in signal processing of NC table

NASA Astrophysics Data System (ADS)

Wang, Linhong; He, Yiwen

2011-12-01

NC (numerical control) table is a complex dynamic system. The dynamic characteristics caused by backlash, friction and elastic deformation among each component are so complex that they have become the bottleneck of enhancing the positioning accuracy, tracking accuracy and dynamic behavior of NC table. This paper collects vibration acceleration signals from NC table, analyzes the signals with SVD (singular value decomposition) method, acquires the singular spectrum and calculates the singular entropy of the signals. The signal characteristics and their regulations of NC table are revealed via the characteristic quantities such as singular spectrum, singular entropy etc. The steep degrees of singular spectrums can be used to discriminate complex degrees of signals. The results show that the signals in direction of driving axes are the simplest and the signals in perpendicular direction are the most complex. The singular entropy values can be used to study the indetermination of signals. The results show that the signals of NC table are not simple signal nor white noise, the entropy values in direction of driving axe are lower, the entropy values increase along with the increment of driving speed and the entropy values at the abnormal working conditions such as resonance or creeping etc decrease obviously.

Advances in the Theory of Complex Networks

NASA Astrophysics Data System (ADS)

Peruani, Fernando

An exhaustive and comprehensive review on the theory of complex networks would imply nowadays a titanic task, and it would result in a lengthy work containing plenty of technical details of arguable relevance. Instead, this chapter addresses very briefly the ABC of complex network theory, visiting only the hallmarks of the theoretical founding, to finally focus on two of the most interesting and promising current research problems: the study of dynamical processes on transportation networks and the identification of communities in complex networks.

A photo-cross-linking approach to monitor folding and assembly of newly synthesized proteins in a living cell.

PubMed

Miyazaki, Ryoji; Myougo, Naomi; Mori, Hiroyuki; Akiyama, Yoshinori

2018-01-12

Many proteins form multimeric complexes that play crucial roles in various cellular processes. Studying how proteins are correctly folded and assembled into such complexes in a living cell is important for understanding the physiological roles and the qualitative and quantitative regulation of the complex. However, few methods are suitable for analyzing these rapidly occurring processes. Site-directed in vivo photo-cross-linking is an elegant technique that enables analysis of protein-protein interactions in living cells with high spatial resolution. However, the conventional site-directed in vivo photo-cross-linking method is unsuitable for analyzing dynamic processes. Here, by combining an improved site-directed in vivo photo-cross-linking technique with a pulse-chase approach, we developed a new method that can analyze the folding and assembly of a newly synthesized protein with high spatiotemporal resolution. We demonstrate that this method, named the pulse-chase and in vivo photo-cross-linking experiment (PiXie), enables the kinetic analysis of the formation of an Escherichia coli periplasmic (soluble) protein complex (PhoA). We also used our new technique to investigate assembly/folding processes of two membrane complexes (SecD-SecF in the inner membrane and LptD-LptE in the outer membrane), which provided new insights into the biogenesis of these complexes. Our PiXie method permits analysis of the dynamic behavior of various proteins and enables examination of protein-protein interactions at the level of individual amino acid residues. We anticipate that our new technique will have valuable utility for studies of protein dynamics in many organisms. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

A molecular mechanism of P-loop pliability of Rho-kinase investigated by molecular dynamic simulation

NASA Astrophysics Data System (ADS)

Gohda, Keigo; Hakoshima, Toshio

2008-11-01

Rho-kinase is a leading player in the regulation of cytoskeletal events involving smooth muscle contraction and neurite growth-cone collapse and retraction, and is a promising drug target in the treatment of both vascular and neurological disorders. Recent crystal structure of Rho-kinase complexed with a small-molecule inhibitor fasudil has revealed structural details of the ATP-binding site, which represents the target site for the inhibitor, and showed that the conserved phenylalanine on the P-loop occupies the pocket, resulting in an increase of protein-ligand contacts. Thus, the P-loop pliability is considered to play an important role in inhibitor binding affinity and specificity. In this study, we carried out a molecular dynamic simulation for Rho-kinase-fasudil complexes with two different P-loop conformations, i.e., the extended and folded conformations, in order to understand the P-loop pliability and dynamics at atomic level. A PKA-fasudil complex was also used for comparison. In the MD simulation, the flip-flop movement of the P-loop conformation starting either from the extended or folded conformation was not able to be observed. However, a significant conformational change in a long loop region covering over the P-loop, and also alteration of ionic interaction-manner of fasudil with acidic residues in the ATP binding site were shown only in the Rho-kinase-fasudil complex with the extended P-loop conformation, while Rho-kinase with the folded P-loop conformation and PKA complexes did not show large fluctuations, suggesting that the Rho-kinase-fasudil complex with the extended P-loop conformation represents a meta-stable state. The information of the P-loop pliability at atomic level obtained in this study could provide valuable clues to designing potent and/or selective inhibitors for Rho-kinase.

Creating Time: Social Collaboration in Music Improvisation.

PubMed

Walton, Ashley E; Washburn, Auriel; Langland-Hassan, Peter; Chemero, Anthony; Kloos, Heidi; Richardson, Michael J

2018-01-01

Musical collaboration emerges from the complex interaction of environmental and informational constraints, including those of the instruments and the performance context. Music improvisation in particular is more like everyday interaction in that dynamics emerge spontaneously without a rehearsed score or script. We examined how the structure of the musical context affords and shapes interactions between improvising musicians. Six pairs of professional piano players improvised with two different backing tracks while we recorded both the music produced and the movements of their heads, left arms, and right arms. The backing tracks varied in rhythmic and harmonic information, from a chord progression to a continuous drone. Differences in movement coordination and playing behavior were evaluated using the mathematical tools of complex dynamical systems, with the aim of uncovering the multiscale dynamics that characterize musical collaboration. Collectively, the findings indicated that each backing track afforded the emergence of different patterns of coordination with respect to how the musicians played together, how they moved together, as well as their experience collaborating with each other. Additionally, listeners' experiences of the music when rating audio recordings of the improvised performances were related to the way the musicians coordinated both their playing behavior and their bodily movements. Accordingly, the study revealed how complex dynamical systems methods (namely recurrence analysis) can capture the turn-taking dynamics that characterized both the social exchange of the music improvisation and the sounds of collaboration more generally. The study also demonstrated how musical improvisation provides a way of understanding how social interaction emerges from the structure of the behavioral task context. Copyright © 2017 Cognitive Science Society, Inc.

Structure and dynamics of aqueous solutions from PBE-based first-principles molecular dynamics simulations.

PubMed

Pham, Tuan Anh; Ogitsu, Tadashi; Lau, Edmond Y; Schwegler, Eric

2016-10-21

Establishing an accurate and predictive computational framework for the description of complex aqueous solutions is an ongoing challenge for density functional theory based first-principles molecular dynamics (FPMD) simulations. In this context, important advances have been made in recent years, including the development of sophisticated exchange-correlation functionals. On the other hand, simulations based on simple generalized gradient approximation (GGA) functionals remain an active field, particularly in the study of complex aqueous solutions due to a good balance between the accuracy, computational expense, and the applicability to a wide range of systems. Such simulations are often performed at elevated temperatures to artificially "correct" for GGA inaccuracies in the description of liquid water; however, a detailed understanding of how the choice of temperature affects the structure and dynamics of other components, such as solvated ions, is largely unknown. To address this question, we carried out a series of FPMD simulations at temperatures ranging from 300 to 460 K for liquid water and three representative aqueous solutions containing solvated Na + , K + , and Cl - ions. We show that simulations at 390-400 K with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional yield water structure and dynamics in good agreement with experiments at ambient conditions. Simultaneously, this computational setup provides ion solvation structures and ion effects on water dynamics consistent with experiments. Our results suggest that an elevated temperature around 390-400 K with the PBE functional can be used for the description of structural and dynamical properties of liquid water and complex solutions with solvated ions at ambient conditions.

Universality in the dynamical properties of seismic vibrations

NASA Astrophysics Data System (ADS)

Chatterjee, Soumya; Barat, P.; Mukherjee, Indranil

2018-02-01

We have studied the statistical properties of the observed magnitudes of seismic vibration data in discrete time in an attempt to understand the underlying complex dynamical processes. The observed magnitude data are taken from six different geographical locations. All possible magnitudes are considered in the analysis including catastrophic vibrations, foreshocks, aftershocks and commonplace daily vibrations. The probability distribution functions of these data sets obey scaling law and display a certain universality characteristic. To investigate the universality features in the observed data generated by a complex process, we applied Random Matrix Theory (RMT) in the framework of Gaussian Orthogonal Ensemble (GOE). For all these six places the observed data show a close fit with the predictions of RMT. This reinforces the idea of universality in the dynamical processes generating seismic vibrations.

Instantaneous nonlinear assessment of complex cardiovascular dynamics by Laguerre-Volterra point process models.

PubMed

Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

2013-01-01

We report an exemplary study of instantaneous assessment of cardiovascular dynamics performed using point-process nonlinear models based on Laguerre expansion of the linear and nonlinear Wiener-Volterra kernels. As quantifiers, instantaneous measures such as high order spectral features and Lyapunov exponents can be estimated from a quadratic and cubic autoregressive formulation of the model first order moment, respectively. Here, these measures are evaluated on heartbeat series coming from 16 healthy subjects and 14 patients with Congestive Hearth Failure (CHF). Data were gathered from the on-line repository PhysioBank, which has been taken as landmark for testing nonlinear indices. Results show that the proposed nonlinear Laguerre-Volterra point-process methods are able to track the nonlinear and complex cardiovascular dynamics, distinguishing significantly between CHF and healthy heartbeat series.

Dynamical analysis of uterine cell electrical activity model.

PubMed

Rihana, S; Santos, J; Mondie, S; Marque, C

2006-01-01

The uterus is a physiological system consisting of a large number of interacting smooth muscle cells. The uterine excitability changes remarkably with time, generally quiescent during pregnancy, the uterus exhibits forceful synchronized contractions at term leading to fetus expulsion. These changes characterize thus a dynamical system susceptible of being studied through formal mathematical tools. Multiple physiological factors are involved in the regulation process of this complex system. Our aim is to relate the physiological factors to the uterine cell dynamic behaviors. Taking into account a previous work presented, in which the electrical activity of a uterine cell is described by a set of ordinary differential equations, we analyze the impact of physiological parameters on the response of the model, and identify the main subsystems generating the complex uterine electrical activity, with respect to physiological data.

Dissipative structure in the photo-induced phase under steady light irradiation in the spin crossover complex.

PubMed

Nishihara, Taishi; Bousseksou, Azzdine; Tanaka, Koichiro

2013-12-16

We report the spatial and temporal dynamics of the photo-induced phase in the iron (II) spin crossover complex Fe(ptz)(6)(BF(4))(2) studied by image measurement under steady light irradiation and transient absorption measurement. The dynamic factors are derived from the spatial and temporal fluctuation of the image in the steady state under light irradiation between 65 and 100 K. The dynamic factors clearly indicate that the fluctuation has a resonant frequency that strongly depends on the temperature, and is proportional to the relaxation rate of the photo-induced phase. This oscillation of the speckle pattern under steady light irradiation is ascribed to the nonlinear interaction between the spin state and the lattice volume at the surface.

Nephrin Regulates Lamellipodia Formation by Assembling a Protein Complex That Includes Ship2, Filamin and Lamellipodin

PubMed Central

Venkatareddy, Madhusudan; Cook, Leslie; Abuarquob, Kamal; Verma, Rakesh; Garg, Puneet

2011-01-01

Actin dynamics has emerged at the forefront of podocyte biology. Slit diaphragm junctional adhesion protein Nephrin is necessary for development of the podocyte morphology and transduces phosphorylation-dependent signals that regulate cytoskeletal dynamics. The present study extends our understanding of Nephrin function by showing in cultured podocytes that Nephrin activation induced actin dynamics is necessary for lamellipodia formation. Upon activation Nephrin recruits and regulates a protein complex that includes Ship2 (SH2 domain containing 5′ inositol phosphatase), Filamin and Lamellipodin, proteins important in regulation of actin and focal adhesion dynamics, as well as lamellipodia formation. Using the previously described CD16-Nephrin clustering system, Nephrin ligation or activation resulted in phosphorylation of the actin crosslinking protein Filamin in a p21 activated kinase dependent manner. Nephrin activation in cell culture results in formation of lamellipodia, a process that requires specialized actin dynamics at the leading edge of the cell along with focal adhesion turnover. In the CD16-Nephrin clustering model, Nephrin ligation resulted in abnormal morphology of actin tails in human podocytes when Ship2, Filamin or Lamellipodin were individually knocked down. We also observed decreased lamellipodia formation and cell migration in these knock down cells. These data provide evidence that Nephrin not only initiates actin polymerization but also assembles a protein complex that is necessary to regulate the architecture of the generated actin filament network and focal adhesion dynamics. PMID:22194892

Framework based on communicability and flow to analyze complex network dynamics

NASA Astrophysics Data System (ADS)

Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.

2018-05-01

Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.

Ontology of Earth's nonlinear dynamic complex systems

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Davarpanah, Armita

2017-04-01

As a complex system, Earth and its major integrated and dynamically interacting subsystems (e.g., hydrosphere, atmosphere) display nonlinear behavior in response to internal and external influences. The Earth Nonlinear Dynamic Complex Systems (ENDCS) ontology formally represents the semantics of the knowledge about the nonlinear system element (agent) behavior, function, and structure, inter-agent and agent-environment feedback loops, and the emergent collective properties of the whole complex system as the result of interaction of the agents with other agents and their environment. It also models nonlinear concepts such as aperiodic, random chaotic behavior, sensitivity to initial conditions, bifurcation of dynamic processes, levels of organization, self-organization, aggregated and isolated functionality, and emergence of collective complex behavior at the system level. By incorporating several existing ontologies, the ENDCS ontology represents the dynamic system variables and the rules of transformation of their state, emergent state, and other features of complex systems such as the trajectories in state (phase) space (attractor and strange attractor), basins of attractions, basin divide (separatrix), fractal dimension, and system's interface to its environment. The ontology also defines different object properties that change the system behavior, function, and structure and trigger instability. ENDCS will help to integrate the data and knowledge related to the five complex subsystems of Earth by annotating common data types, unifying the semantics of shared terminology, and facilitating interoperability among different fields of Earth science.

Cyclodextrin-complexation effects on the low-frequency vibrational dynamics of ibuprofen by combined inelastic light and neutron scattering experiments.

PubMed

Crupi, Vincenza; Fontana, Aldo; Giarola, Marco; Guella, Graziano; Majolino, Domenico; Mancini, Ines; Mariotto, Gino; Paciaroni, Alessandro; Rossi, Barbara; Venuti, Valentina

2013-04-11

The effect of the inclusion into cyclodextrins (CD) cavity on the low-frequency vibrational dynamics of the anti-inflammatory drug ibuprofen (IBP) is here investigated by using Raman and inelastic neutron scattering (INS) experiments. The differences observed in the frequency regime 0-100 cm(-1) between the vibrational modes of uncomplexed racemic and enantiomeric IBP are discussed on the basis of comparison with the quantum chemical computation results, taking into account the distinct symmetry properties of the molecules involved in the formation of the host-guest complex. Subsequently, the inspection of the same frequency range in the spectra of pure host methyl-β-CD and its IBP-inclusion complexes allows one to identify significant modifications in the vibrational dynamics of the guest molecule after their confinement into CD cavity. The experimental Raman and neutron spectra and the derived Raman coupling function C(R)(ω) show that the complexation process gives rise to a complete amorphization of the drug, as well as to a partial hindering, in the vibrational dynamics of complexes, of the modes between 50 and 150 cm(-1) attributed to CD molecule. The comparison between the Raman and neutron spectra of free and complexed IBP in the energy range of the Boson peak (BP) gives evidence that the dynamics related to this specific vibrational feature is sensitive to complexation phenomena.

Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.

PubMed

Peng, Huan-Kai; Marculescu, Radu

2015-01-01

Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different time scales, and (2) the way in which these signatures interact and form higher-level meanings. In this paper, we propose the Recursive Convolutional Bayesian Model (RCBM) to address both of these fundamental questions. The key idea behind our approach consists of constructing a deep-learning framework using specialized convolution operators that are designed to exploit the inherent heterogeneity of social dynamics. RCBM's runtime and convergence properties are guaranteed by formal analyses. Experimental results show that the proposed method outperforms the state-of-the-art approaches both in terms of solution quality and computational efficiency. Indeed, by applying the proposed method on two social network datasets, Twitter and Yelp, we are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. Finally, our analysis offers new insights on understanding and engineering social media dynamics, with direct applications to opinion spreading and online content promotion.

Metrics for comparing dynamic earthquake rupture simulations

USGS Publications Warehouse

Barall, Michael; Harris, Ruth A.

2014-01-01

Earthquakes are complex events that involve a myriad of interactions among multiple geologic features and processes. One of the tools that is available to assist with their study is computer simulation, particularly dynamic rupture simulation. A dynamic rupture simulation is a numerical model of the physical processes that occur during an earthquake. Starting with the fault geometry, friction constitutive law, initial stress conditions, and assumptions about the condition and response of the near‐fault rocks, a dynamic earthquake rupture simulation calculates the evolution of fault slip and stress over time as part of the elastodynamic numerical solution (Ⓔ see the simulation description in the electronic supplement to this article). The complexity of the computations in a dynamic rupture simulation make it challenging to verify that the computer code is operating as intended, because there are no exact analytic solutions against which these codes’ results can be directly compared. One approach for checking if dynamic rupture computer codes are working satisfactorily is to compare each code’s results with the results of other dynamic rupture codes running the same earthquake simulation benchmark. To perform such a comparison consistently, it is necessary to have quantitative metrics. In this paper, we present a new method for quantitatively comparing the results of dynamic earthquake rupture computer simulation codes.

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

PubMed

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

2016-01-01

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

Multi-Scale Compositionality: Identifying the Compositional Structures of Social Dynamics Using Deep Learning

PubMed Central

Peng, Huan-Kai; Marculescu, Radu

2015-01-01

Objective Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different time scales, and (2) the way in which these signatures interact and form higher-level meanings. Method In this paper, we propose the Recursive Convolutional Bayesian Model (RCBM) to address both of these fundamental questions. The key idea behind our approach consists of constructing a deep-learning framework using specialized convolution operators that are designed to exploit the inherent heterogeneity of social dynamics. RCBM’s runtime and convergence properties are guaranteed by formal analyses. Results Experimental results show that the proposed method outperforms the state-of-the-art approaches both in terms of solution quality and computational efficiency. Indeed, by applying the proposed method on two social network datasets, Twitter and Yelp, we are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. Finally, our analysis offers new insights on understanding and engineering social media dynamics, with direct applications to opinion spreading and online content promotion. PMID:25830775

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.

The interplay between interpersonal dynamics, treatment barriers, and larger social forces: an exploratory study of drug-using couples in Hartford, CT

PubMed Central

Simmons, Janie

2006-01-01

Background The drug treatment field tends to place emphasis on the individual rather than the individual in social context. While there are a growing number of studies indicating that drug-using intimate partners are likely to play an important role in determining treatment options, little attention has been given to the experience and complex treatment needs of illicit drug-using (heroin, cocaine, crack) couples. Methods This exploratory study used in-depth interviews and ethnographic engagement to better understand the relationship between interpersonal dynamics and the treatment experience of ten relatively stable drug-using couples in Hartford, CT. Semi-structured and open-ended qualitative interviews were conducted with each couple and separately with each partner. Whenever possible, the day-to-day realities and contexts of risk were also observed via participant and non-participant observation of these couples in the community. A grounded theory approach was used to inductively code and analyze nearly 40 transcripts of 60–90 minute interviews as well as fieldnotes. Results This study builds on a concept of complex interpersonal dynamics among drug users. Interpersonal dynamics of care and collusion were identified: couples cared for each other and colluded to acquire and use drugs. Care and collusion operate at the micro level of the risk environment. Treatment barriers and inadequacies were identified as part of the risk environment at the meso or intermediate level of analysis, and larger social forces such as gender dynamics, poverty and the "War on Drugs" were identified at the macro level. Interpersonal dynamics posed problems for couples when one or both partners were interested in accessing treatment. Structural barriers presented additional obstacles with the denial of admittance of both partners to treatment programs which had a sole focus on the individual and avoided treating couples. Conclusion Detoxification and treatment facilities need to recognize the complex interplay between interpersonal dynamics which shape the treatment experience of couples, and which are also shaped by larger structural dynamics, including barriers in the treatment system. Improvements to the treatment system in general will go a long way in improving treatment for couples. Couples-specific programming also needs to be developed. PMID:16722545

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A network dynamics approach to chemical reaction networks

NASA Astrophysics Data System (ADS)

van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

2016-04-01

A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

An Evolutionary Approach to Harnessing Complex Systems Thinking in the Science and Technology Classroom

ERIC Educational Resources Information Center

Yoon, Susan A.

2008-01-01

Educational efforts to incorporate ethical decision-making in science classrooms about current science and technology issues have met with great challenges. Some research suggests that the inherent complexity in both the subject matter content and the structure and dynamics of classrooms contribute to this challenge. This study seeks to…

An Information Theoretic Investigation Of Complex Adaptive Supply Networks With Organizational Topologies

DTIC Science & Technology

2016-12-22

assumptions of behavior. This research proposes an information theoretic methodology to discover such complex network structures and dynamics while overcoming...the difficulties historically associated with their study. Indeed, this was the first application of an information theoretic methodology as a tool...1 Research Objectives and Questions..............................................................................2 Methodology

A Complex Systems Framework for Research on Leadership and Organizational Dynamics in Academic Libraries

ERIC Educational Resources Information Center

Gilstrap, Donald L.

2009-01-01

This article provides a historiographical analysis of major leadership and organizational development theories that have shaped our thinking about how we lead and administrate academic libraries. Drawing from behavioral, cognitive, systems, and complexity theories, this article discusses major theorists and research studies appearing over the past…

Organizational Agility and Complex Enterprise System Innovations: A Mixed Methods Study of the Effects of Enterprise Systems on Organizational Agility

ERIC Educational Resources Information Center

Kharabe, Amol T.

2012-01-01

Over the last two decades, firms have operated in "increasingly" accelerated "high-velocity" dynamic markets, which require them to become "agile." During the same time frame, firms have increasingly deployed complex enterprise systems--large-scale packaged software "innovations" that integrate and automate…

Complex Systems and Educational Change: Towards a New Research Agenda

ERIC Educational Resources Information Center

Lemke, Jay L.; Sabelli, Nora H.

2008-01-01

How might we usefully apply concepts and procedures derived from the study of other complex dynamical systems to analyzing systemic change in education? In this article, we begin to define possible agendas for research toward developing systematic frameworks and shared terminology for such a project. We illustrate the plausibility of defining such…

Toward a Common Structure in Demographic Educational Modeling and Simulation: A Complex Systems Approach

ERIC Educational Resources Information Center

Guevara, Porfirio

2014-01-01

This article identifies elements and connections that seem to be relevant to explain persistent aggregate behavioral patterns in educational systems when using complex dynamical systems modeling and simulation approaches. Several studies have shown what factors are at play in educational fields, but confusion still remains about the underlying…

Systems Thinking Tools as Applied to Community-Based Participatory Research: A Case Study

ERIC Educational Resources Information Center

BeLue, Rhonda; Carmack, Chakema; Myers, Kyle R.; Weinreb-Welch, Laurie; Lengerich, Eugene J.

2012-01-01

Community-based participatory research (CBPR) is being used increasingly to address health disparities and complex health issues. The authors propose that CBPR can benefit from a systems science framework to represent the complex and dynamic characteristics of a community and identify intervention points and potential "tipping points."…

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

The Helioseismic and Magnetic Imager (HMI) Investigation for the Solar Dynamics Observatory (SDO)

NASA Technical Reports Server (NTRS)

Scherrer, Philip Hanby; Schou, Jesper; Bush, R. I.; Kosovichev, A. G.; Bogart, R. S.; Hoeksema, J. T.; Liu, Y.; Duvall, T. L., Jr.; Zhao, J.; Title, A. M.;

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.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system.

PubMed

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system

NASA Astrophysics Data System (ADS)

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

Transcription closed and open complex dynamics studies reveal balance between genetic determinants and co-factors

NASA Astrophysics Data System (ADS)

Sala, Adrien; Shoaib, Muhammad; Anufrieva, Olga; Mutharasu, Gnanavel; Jahan Hoque, Rawnak; Yli-Harja, Olli; Kandhavelu, Meenakshisundaram

2015-05-01

In E. coli, promoter closed and open complexes are key steps in transcription initiation, where magnesium-dependent RNA polymerase catalyzes RNA synthesis. However, the exact mechanism of initiation remains to be fully elucidated. Here, using single mRNA detection and dual reporter studies, we show that increased intracellular magnesium concentration affects Plac initiation complex formation resulting in a highly dynamic process over the cell growth phases. Mg2+ regulates transcription transition, which modulates bimodality of mRNA distribution in the exponential phase. We reveal that Mg2+ regulates the size and frequency of the mRNA burst by changing the open complex duration. Moreover, increasing magnesium concentration leads to higher intrinsic and extrinsic noise in the exponential phase. RNAP-Mg2+ interaction simulation reveals critical movements creating a shorter contact distance between aspartic acid residues and Nucleotide Triphosphate residues and increasing electrostatic charges in the active site. Our findings provide unique biophysical insights into the balanced mechanism of genetic determinants and magnesium ion in transcription initiation regulation during cell growth.

A theoretical and experimental study of calcium, iron, zinc, cadmium, and sodium ions absorption by aspartame.

PubMed

Mahnam, Karim; Raisi, Fatame

2017-03-01

Aspartame (L-Aspartyl-L-phenylalanine methyl ester) is a sweet dipeptide used in some foods and beverages. Experimental studies show that aspartame causes osteoporosis and some illnesses, which are similar to those of copper and calcium deficiency. This raises the issue that aspartame in food may interact with cations and excrete them from the body. This study aimed to study aspartame interaction with calcium, zinc, iron, sodium, and cadmium ions via molecular dynamics simulation (MD) and spectroscopy. Following a 480-ns molecular dynamics simulation, it became clear that the aspartame is able to sequester Fe 2+ , Ca 2+ , Cd 2+ , and Zn 2+ ions for a long time. Complexation led to increasing UV-Vis absorption spectra and emission spectra of the complexes. This study suggests a potential risk of cationic absorption of aspartame. This study suggests that purification of cadmium-polluted water by aspartame needs a more general risk assessment.

Development of an experimental approach to study coupled soil-plant-atmosphere processes using plant analogs

NASA Astrophysics Data System (ADS)

Trautz, Andrew C.; Illangasekare, Tissa H.; Rodriguez-Iturbe, Ignacio; Heck, Katharina; Helmig, Rainer

2017-04-01

The atmosphere, soils, and vegetation near the land-atmosphere interface are in a state of continuous dynamic interaction via a myriad of complex interrelated feedback processes which collectively, remain poorly understood. Studying the fundamental nature and dynamics of such processes in atmospheric, ecological, and/or hydrological contexts in the field setting presents many challenges; current experimental approaches are an important factor given a general lack of control and high measurement uncertainty. In an effort to address these issues and reduce overall complexity, new experimental design considerations (two-dimensional intermediate-scale coupled wind tunnel-synthetic aquifer testing using synthetic plants) for studying soil-plant-atmosphere continuum soil moisture dynamics are introduced and tested in this study. Validation of these experimental considerations, particularly the adoption of synthetic plants, is required prior to their application in future research. A comparison of three experiments with bare soil surfaces or transplanted with a Stargazer lily/limestone block was used to evaluate the feasibility of the proposed approaches. Results demonstrate that coupled wind tunnel-porous media experimentation, used to simulate field conditions, reduces complexity, and enhances control while allowing fine spatial-temporal resolution measurements to be made using state-of-the-art technologies. Synthetic plants further help reduce system complexity (e.g., airflow) while preserving the basic hydrodynamic functions of plants (e.g., water uptake and transpiration). The trends and distributions of key measured atmospheric and subsurface spatial and temporal variables (e.g., soil moisture, relative humidity, temperature, air velocity) were comparable, showing that synthetic plants can be used as simple, idealized, nonbiological analogs for living vegetation in fundamental hydrodynamic studies.

Developing a Multiplexed Quantitative Cross-Linking Mass Spectrometry Platform for Comparative Structural Analysis of Protein Complexes.

PubMed

Yu, Clinton; Huszagh, Alexander; Viner, Rosa; Novitsky, Eric J; Rychnovsky, Scott D; Huang, Lan

2016-10-18

Cross-linking mass spectrometry (XL-MS) represents a recently popularized hybrid methodology for defining protein-protein interactions (PPIs) and analyzing structures of large protein assemblies. In particular, XL-MS strategies have been demonstrated to be effective in elucidating molecular details of PPIs at the peptide resolution, providing a complementary set of structural data that can be utilized to refine existing complex structures or direct de novo modeling of unknown protein structures. To study structural and interaction dynamics of protein complexes, quantitative cross-linking mass spectrometry (QXL-MS) strategies based on isotope-labeled cross-linkers have been developed. Although successful, these approaches are mostly limited to pairwise comparisons. In order to establish a robust workflow enabling comparative analysis of multiple cross-linked samples simultaneously, we have developed a multiplexed QXL-MS strategy, namely, QMIX (Quantitation of Multiplexed, Isobaric-labeled cross (X)-linked peptides) by integrating MS-cleavable cross-linkers with isobaric labeling reagents. This study has established a new analytical platform for quantitative analysis of cross-linked peptides, which can be directly applied for multiplexed comparisons of the conformational dynamics of protein complexes and PPIs at the proteome scale in future studies.

Decay of Complex-Time Determinantal and Pfaffian Correlation Functionals in Lattices

NASA Astrophysics Data System (ADS)

Aza, N. J. B.; Bru, J.-B.; de Siqueira Pedra, W.

2018-04-01

We supplement the determinantal and Pfaffian bounds of Sims and Warzel (Commun Math Phys 347:903-931, 2016) for many-body localization of quasi-free fermions, by considering the high dimensional case and complex-time correlations. Our proof uses the analyticity of correlation functions via the Hadamard three-line theorem. We show that the dynamical localization for the one-particle system yields the dynamical localization for the many-point fermionic correlation functions, with respect to the Hausdorff distance in the determinantal case. In Sims and Warzel (2016), a stronger notion of decay for many-particle configurations was used but only at dimension one and for real times. Considering determinantal and Pfaffian correlation functionals for complex times is important in the study of weakly interacting fermions.

Decay of Complex-Time Determinantal and Pfaffian Correlation Functionals in Lattices

NASA Astrophysics Data System (ADS)

Aza, N. J. B.; Bru, J.-B.; de Siqueira Pedra, W.

2018-06-01

We supplement the determinantal and Pfaffian bounds of Sims and Warzel (Commun Math Phys 347:903-931, 2016) for many-body localization of quasi-free fermions, by considering the high dimensional case and complex-time correlations. Our proof uses the analyticity of correlation functions via the Hadamard three-line theorem. We show that the dynamical localization for the one-particle system yields the dynamical localization for the many-point fermionic correlation functions, with respect to the Hausdorff distance in the determinantal case. In Sims and Warzel (2016), a stronger notion of decay for many-particle configurations was used but only at dimension one and for real times. Considering determinantal and Pfaffian correlation functionals for complex times is important in the study of weakly interacting fermions.

Note on transmitted complexity for quantum dynamical systems

NASA Astrophysics Data System (ADS)

Watanabe, Noboru; Muto, Masahiro

2017-10-01

Transmitted complexity (mutual entropy) is one of the important measures for quantum information theory developed recently in several ways. We will review the fundamental concepts of the Kossakowski, Ohya and Watanabe entropy and define a transmitted complexity for quantum dynamical systems. This article is part of the themed issue `Second quantum revolution: foundational questions'.

An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks

PubMed Central

Cabessa, Jérémie; Villa, Alessandro E. P.

2014-01-01

We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866

Investigating chaotic wake dynamics past a flapping airfoil and the role of vortex interactions behind the chaotic transition

NASA Astrophysics Data System (ADS)

Bose, Chandan; Sarkar, Sunetra

2018-04-01

The present study investigates the complex vortex interactions in two-dimensional flow-field behind a symmetric NACA0012 airfoil undergoing a prescribed periodic pitching-plunging motion in low Reynolds number regime. The flow-field transitions from periodic to chaotic through a quasi-periodic route as the plunge amplitude is gradually increased. This study unravels the role of the complex interactions that take place among the main vortex structures in making the unsteady flow-field transition from periodicity to chaos. The leading-edge separation plays a key role in providing the very first trigger for aperiodicity. Subsequent mechanisms like shredding, merging, splitting, and collision of vortices in the near-field that propagate and sustain the disturbance have also been followed and presented. These fundamental mechanisms are seen to give rise to spontaneous and irregular formation of new vortex couples at arbitrary locations, which are the primary agencies for sustaining chaos in the flow-field. The interactions have been studied for each dynamical state to understand the course of transition in the flow-field. The qualitative changes observed in the flow-field are manifestation of changes in the underlying dynamical system. The overall dynamics are established in the present study by means of robust quantitative measures derived from classical and non-classical tools from the dynamical system theory. As the present analysis involves a high fidelity multi-unknown system, non-classical dynamical tools such as recurrence-based time series methods are seen to be very efficient. Moreover, their application is novel in the context of pitch-plunge flapping flight.

(A)biotic processes control soil carbon dynamics: quantitative assessment of model complexity, stability and response to perturbations for improving ESMs

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Harte, J.; Riley, W. J.; Torn, M. S.

2016-12-01

As global temperatures and atmospheric CO2 concentrations continue to increase, soil microbial activity and decomposition of soil organic matter (SOM) are expected to follow suit, potentially limiting soil carbon storage. Traditional global- and ecosystem-scale models simulate SOM decomposition using linear kinetics, which are inherently unable to reproduce carbon-concentration feedbacks, such as priming of native SOM at elevated CO2 concentrations. Recent studies using nonlinear microbial models of SOM decomposition seek to capture these interactions, and several groups are currently integrating these microbial models into Earth System Models (ESMs). However, despite their widespread ability to exhibit nonlinear responses, these models vary tremendously in complexity and, consequently, dynamics. In this study, we explore, both analytically and numerically, the emergent oscillatory behavior and insensitivity of SOM stocks to carbon inputs that have been deemed `unrealistic' in recent microbial models. We discuss the sources of instability in four models of varying complexity, by sequentially reducing complexity of a detailed model that includes microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We also present an alternative representation of microbial turnover that limits population sizes and, thus, reduces oscillations. We compare these models to several long-term carbon input manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that traditional linear and nonlinear models cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures, and that modifying microbial turnover results in more realistic predictions. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in ESMs.

Nonlinear dynamics behavior analysis of the spatial configuration of a tendril-bearing plant

NASA Astrophysics Data System (ADS)

Feng, Jingjing; Zhang, Qichang; Wang, Wei; Hao, Shuying

2017-03-01

Tendril-bearing plants appear to have a spiraling shape when tendrils climb along a support during growth. The growth characteristics of a tendril-bearer can be simplified to a model of a thin elastic rod with a cylindrical constraint. In this paper, the connection between some typical configuration characteristics of tendrils and complex nonlinear dynamic behavior are qualitatively analyzed. The space configuration problem of tendrils can be explained through the study of the nonlinear dynamic behavior of the thin elastic rod system equation. In this study, the complex non-Z2 symmetric critical orbits in the system equation under critical parameters were presented. A new function transformation method that can effectively maintain the critical orbit properties was proposed, and a new nonlinear differential equations system containing complex nonlinear terms can been obtained to describe the cross section position and direction of a rod during climbing. Numerical simulation revealed that the new system can describe the configuration of a rod with reasonable accuracy. To adequately explain the growing regulation of the rod shape, the critical orbit and configuration of rod are connected in a direct way. The high precision analytical expressions of these complex non-Z2 symmetric critical orbits are obtained by introducing a suitable analytical method, and then these expressions are used to draw the corresponding three-dimensional configuration figures of an elastic thin rod. Combined with actual tendrils on a live plant, the space configuration of the winding knots of tendril is explained by the concept of heteroclinic orbit from the perspective of nonlinear dynamics, and correctness of the theoretical analysis was verified. This theoretical analysis method could also be effectively applied to other similar slender structures.

Potential of mean force for human lysozyme camelid vhh hl6 antibody interaction studies

NASA Astrophysics Data System (ADS)

Wang, Yeng-Tseng; Liao, Jun-Min; Chen, Cheng-Lung; Su, Zhi-Yuan; Chen, Chang-Hung; Hu, Jeu-Jiun

2008-04-01

Calculating antigen-antibody interaction energies is crucial for understanding antigen-antibody associations in immunology. To shed further light into this equation, we study a separation of human lysozyme-camelid vhh hl6 antibody (cAb-HuL6) complex. The c-terminal end-to-end stretching of the lysozyme-antibody complex structures have been studied using potential of mean force (PMF) calculations based on molecular dynamics (MD) and explicit water model. For the lysozyme-antibody complex, there are six important intermediates in the c-terminal extensions process. Inclusion of our simulations may help to understand the binding mechanics of lysozyme-cAb-HuL6 antibody complex.

Spontaneous Tl(I)-to-Tl(III) oxidation in dynamic heterobimetallic Hg(II)/Tl(I) porphyrin complexes.

PubMed

Ndoyom, Victoria; Fusaro, Luca; Roisnel, Thierry; Le Gac, Stéphane; Boitrel, Bernard

2016-01-11

Strapped heterobimetallic Hg(II)/Tl(I) porphyrin complexes, with both metal ions bridged by the N-core in a dynamic way, undergo spontaneous Tl(I)-to-Tl(III) oxidation leading to a mono-Tl(III) complex and a mixed valence Tl(I)/Tl(III) bimetallic complex. It provides a new opportunity to tune metal ion translocations in bimetallic porphyrin systems.

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling.

PubMed

Li, Shan; Dong, Xia; Su, Zhengchang

2013-07-30

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads. To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases. As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

PubMed Central

2013-01-01

Background Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads. Results To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases. Conclusions As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads. PMID:23899370

Garter snake population dynamics from a 16-year study: considerations for ecological monitoring

Treesearch

Amy J. Lind; Hartwell H. Welsh Jr; David A. Tallmon

2005-01-01

Snakes have recently been proposed as model organisms for addressing both evolutionary and ecological questions. Because of their middle position in many food webs they may be useful indicators of trophic complexity and dynamics. However, reliable data on snake populations are rare due to the challenges of sampling these patchily distributed, cryptic, and often...

Critical Moments in the Process of Educational Change: Understanding the Dynamics of Change among Teacher Educators

ERIC Educational Resources Information Center

Brody, David L.; Hadar, Linor Lea

2018-01-01

This study examines the complex process of change among teacher educators who have chosen to improve their practice in a professional development community. Storyline methodology was used to reveal the dynamic process which teacher educators undergo when they consider adopting innovative pedagogy. Findings reveal critical moments in professional…

Pondering Motivational Ups and Downs throughout a Two-Month Period: A Complex Dynamic System Perspective

ERIC Educational Resources Information Center

Lasagabaster, David

2017-01-01

This paper describes a two-month longitudinal study in which five secondary education students learning English as a foreign language at school will be interviewed in order to analyse how their motivation varies during this period and what variables affect their motivational changes. The emphasis will thus be on motivation's dynamicity and…