Micro-Level Affect Dynamics in Psychopathology Viewed From Complex Dynamical System Theory

NARCIS (Netherlands)

Wichers, M.; Wigman, J. T. W.; Myin-Germeys, I.

2015-01-01

This article discusses the role of moment-to-moment affect dynamics in mental disorder and aims to integrate recent literature on this topic in the context of complex dynamical system theory. First, we will review the relevance of temporal and contextual aspects of affect dynamics in relation to

Data based identification and prediction of nonlinear and complex dynamical systems

Science.gov (United States)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

Data based identification and prediction of nonlinear and complex dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

2016-07-12

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

Data based identification and prediction of nonlinear and complex dynamical systems

International Nuclear Information System (INIS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-01-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

Advances in dynamic network modeling in complex transportation systems

CERN Document Server

Ukkusuri, Satish V

2013-01-01

This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2013-01-01

Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

System crash as dynamics of complex networks.

Science.gov (United States)

Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

2016-10-18

Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

The self as a complex dynamic system

Directory of Open Access Journals (Sweden)

Sarah Mercer

2011-04-01

Full Text Available 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 perspective that may inform future studies into the self and possibly other individual learner differences. The article concludes by critically considering the merits of a complexity perspective but also reflecting on the challenges it poses for research.

Note on transmitted complexity for quantum dynamical systems

Science.gov (United States)

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'.

Understanding Learner Agency as a Complex Dynamic System

Science.gov (United States)

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…

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

Science.gov (United States)

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…

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

Science.gov (United States)

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

2016-01-01

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

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2015-01-01

This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

Nonlinear dynamics and complexity

CERN Document Server

Luo, Albert; Fu, Xilin

2014-01-01

This important collection presents recent advances in nonlinear dynamics including analytical solutions, chaos in Hamiltonian systems, time-delay, uncertainty, and bio-network dynamics. Nonlinear Dynamics and Complexity equips readers to appreciate this increasingly main-stream approach to understanding complex phenomena in nonlinear systems as they are examined in a broad array of disciplines. The book facilitates a better understanding of the mechanisms and phenomena in nonlinear dynamics and develops the corresponding mathematical theory to apply nonlinear design to practical engineering.

Software complex for developing dynamically packed program system for experiment automation

International Nuclear Information System (INIS)

Baluka, G.; Salamatin, I.M.

1985-01-01

Software complex for developing dynamically packed program system for experiment automation is considered. The complex includes general-purpose programming systems represented as the RT-11 standard operating system and specially developed problem-oriented moduli providing execution of certain jobs. The described complex is realized in the PASKAL' and MAKRO-2 languages and it is rather flexible to variations of the technique of the experiment

Controlling collective dynamics in complex minority-game resource-allocation systems

Science.gov (United States)

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

2013-05-01

Resource allocation takes place in various kinds of real-world complex systems, such as traffic systems, social services institutions or organizations, or even ecosystems. The fundamental principle underlying complex resource-allocation dynamics is Boolean interactions associated with minority games, as resources are generally limited and agents tend to choose the least used resource based on available information. A common but harmful dynamical behavior in resource-allocation systems is herding, where there are time intervals during which a large majority of the agents compete for a few resources, leaving many other resources unused. Accompanying the herd behavior is thus strong fluctuations with time in the number of resources being used. In this paper, we articulate and establish that an intuitive control strategy, namely pinning control, is effective at harnessing the herding dynamics. In particular, by fixing the choices of resources for a few agents while leaving the majority of the agents free, herding can be eliminated completely. Our investigation is systematic in that we consider random and targeted pinning and a variety of network topologies, and we carry out a comprehensive analysis in the framework of mean-field theory to understand the working of control. The basic philosophy is then that, when a few agents waive their freedom to choose resources by receiving sufficient incentives, the majority of the agents benefit in that they will make fair, efficient, and effective use of the available resources. Our work represents a basic and general framework to address the fundamental issue of fluctuations in complex dynamical systems with significant applications to social, economical, and political systems.

Conceptualizing Teacher Identity as a Complex Dynamic System: The Inner Dynamics of Transformations during a Practicum

Science.gov (United States)

Henry, Alastair

2016-01-01

Currently, the inner dynamics of teacher identity transformations remain a "black box." Conceptualizing preservice teacher identity as a complex dynamic system, and the notion of "being someone who teaches" in dialogical terms as involving shifts between different teacher voices, the study investigates the dynamical processes…

Small System dynamics models for big issues : Triple jump towards real-world complexity

NARCIS (Netherlands)

Pruyt, E.

2013-01-01

System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and analysis facilitates the (re)design of systems and design of

Modularity and the spread of perturbations in complex dynamical systems.

Science.gov (United States)

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

2015-12-01

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

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

Science.gov (United States)

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.

Logic-based hierarchies for modeling behavior of complex dynamic systems with applications

International Nuclear Information System (INIS)

Hu, Y.S.; Modarres, M.

2000-01-01

Most complex systems are best represented in the form of a hierarchy. The Goal Tree Success Tree and Master Logic Diagram (GTST-MLD) are proven powerful hierarchic methods to represent complex snap-shot of plant knowledge. To represent dynamic behaviors of complex systems, fuzzy logic is applied to replace binary logic to extend the power of GTST-MLD. Such a fuzzy-logic-based hierarchy is called Dynamic Master Logic Diagram (DMLD). This chapter discusses comparison of the use of GTST-DMLD when applied as a modeling tool for systems whose relationships are modeled by either physical, binary logical or fuzzy logical relationships. This is shown by applying GTST-DMLD to the Direct Containment Heating (DCH) phenomenon at pressurized water reactors which is an important safety issue being addressed by the nuclear industry. (orig.)

Identification of Complex Dynamical Systems with Neural Networks (2/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Identification of Complex Dynamical Systems with Neural Networks (1/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Return-to-Work Within a Complex and Dynamic Organizational Work Disability System

OpenAIRE

Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J.

2015-01-01

Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, an...

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

Science.gov (United States)

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.

An introduction to complex systems society, ecology, and nonlinear dynamics

CERN Document Server

Fieguth, Paul

2017-01-01

This undergraduate text explores a variety of large-scale phenomena - global warming, ice ages, water, poverty - and uses these case studies as a motivation to explore nonlinear dynamics, power-law statistics, and complex systems. Although the detailed mathematical descriptions of these topics can be challenging, the consequences of a system being nonlinear, power-law, or complex are in fact quite accessible. This book blends a tutorial approach to the mathematical aspects of complex systems together with a complementary narrative on the global/ecological/societal implications of such systems. Nearly all engineering undergraduate courses focus on mathematics and systems which are small scale, linear, and Gaussian. Unfortunately there is not a single large-scale ecological or social phenomenon that is scalar, linear, and Gaussian. This book offers students insights to better understand the large-scale problems facing the world and to realize that these cannot be solved by a single, narrow academic field or per...

Dynamical systems examples of complex behaviour

CERN Document Server

Jost, Jürgen

2005-01-01

Our aim is to introduce, explain, and discuss the fundamental problems, ideas, concepts, results, and methods of the theory of dynamical systems and to show how they can be used in speci?c examples. We do not intend to give a comprehensive overview of the present state of research in the theory of dynamical systems, nor a detailed historical account of its development. We try to explain the important results, often neglecting technical re?nements 1 and, usually, we do not provide proofs. One of the basic questions in studying dynamical systems, i.e. systems that evolve in time, is the construction of invariants that allow us to classify qualitative types of dynamical evolution, to distinguish between qualitatively di?erent dynamics, and to studytransitions between di?erent types. Itis also important to ?nd out when a certain dynamic behavior is stable under small perturbations, as well as to understand the various scenarios of instability. Finally, an essential aspect of a dynamic evolution is the transformat...

Complex dynamics in Duffing system with two external forcings

International Nuclear Information System (INIS)

Jing Zhujun; Wang Ruiqi

2005-01-01

Duffing's equation with two external forcing terms have been discussed. The threshold values of chaotic motion under the periodic and quasi-periodic perturbations are obtained by using second-order averaging method and Melnikov's method. Numerical simulations not only show the consistence with the theoretical analysis but also exhibit the interesting bifurcation diagrams and the more new complex dynamical behaviors, including period-n (n=2,3,6,8) orbits, cascades of period-doubling and reverse period doubling bifurcations, quasi-periodic orbit, period windows, bubble from period-one to period-two, onset of chaos, hopping behavior of chaos, transient chaos, chaotic attractors and strange non-chaotic attractor, crisis which depends on the frequencies, amplitudes and damping. In particular, the second frequency plays a very important role for dynamics of the system, and the system can leave chaotic region to periodic motions by adjusting some parameter which can be considered as an control strategy of chaos. The computation of Lyapunov exponents confirm the dynamical behaviors

On the Computational Complexity of the Languages of General Symbolic Dynamical Systems and Beta-Shifts

DEFF Research Database (Denmark)

Simonsen, Jakob Grue

2009-01-01

We consider the computational complexity of languages of symbolic dynamical systems. In particular, we study complexity hierarchies and membership of the non-uniform class P/poly. We prove: 1.For every time-constructible, non-decreasing function t(n)=@w(n), there is a symbolic dynamical system...... with language decidable in deterministic time O(n^2t(n)), but not in deterministic time o(t(n)). 2.For every space-constructible, non-decreasing function s(n)=@w(n), there is a symbolic dynamical system with language decidable in deterministic space O(s(n)), but not in deterministic space o(s(n)). 3.There...... are symbolic dynamical systems having hard and complete languages under @?"m^l^o^g^s- and @?"m^p-reduction for every complexity class above LOGSPACE in the backbone hierarchy (hence, P-complete, NP-complete, coNP-complete, PSPACE-complete, and EXPTIME-complete sets). 4.There are decidable languages of symbolic...

Control of complex dynamics and chaos in distributed parameter systems

Energy Technology Data Exchange (ETDEWEB)

Chakravarti, S.; Marek, M.; Ray, W.H. [Univ. of Wisconsin, Madison, WI (United States)

1995-12-31

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

Improving the Complexity of the Lorenz Dynamics

Directory of Open Access Journals (Sweden)

María Pilar Mareca

2017-01-01

Full Text Available A new four-dimensional, hyperchaotic dynamic system, based on Lorenz dynamics, is presented. Besides, the most representative dynamics which may be found in this new system are located in the phase space and are analyzed here. The new system is especially designed to improve the complexity of Lorenz dynamics, which, despite being a paradigm to understand the chaotic dissipative flows, is a very simple example and shows great vulnerability when used in secure communications. Here, we demonstrate the vulnerability of the Lorenz system in a general way. The proposed 4D system increases the complexity of the Lorenz dynamics. The trajectories of the novel system include structures going from chaos to hyperchaos and chaotic-transient solutions. The symmetry and the stability of the proposed system are also studied. First return maps, Poincaré sections, and bifurcation diagrams allow characterizing the global system behavior and locating some coexisting structures. Numerical results about the first return maps, Poincaré cross sections, Lyapunov spectrum, and Kaplan-Yorke dimension demonstrate the complexity of the proposed equations.

Bifurcation and complex dynamics of a discrete-time predator-prey system

Directory of Open Access Journals (Sweden)

S. M. Sohel Rana

2015-06-01

Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system of Holling-I type in the closed first quadrant R+2. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. It has been found that the dynamical behavior of the model is very sensitive to the parameter values and the initial conditions. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamic behaviors, including phase portraits, period-9, 10, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. In particular, we observe that when the prey is in chaotic dynamic, the predator can tend to extinction or to a stable equilibrium. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors. The analysis and results in this paper are interesting in mathematics and biology.

Dynamics in Complex Coacervates

Science.gov (United States)

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.

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

Science.gov (United States)

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

2012-08-01

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

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

Science.gov (United States)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Optimal system size for complex dynamics in random neural networks near criticality

Energy Technology Data Exchange (ETDEWEB)

Wainrib, Gilles, E-mail: wainrib@math.univ-paris13.fr [Laboratoire Analyse Géométrie et Applications, Université Paris XIII, Villetaneuse (France); García del Molino, Luis Carlos, E-mail: garciadelmolino@ijm.univ-paris-diderot.fr [Institute Jacques Monod, Université Paris VII, Paris (France)

2013-12-15

In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259–262 (1988)] in the context of random neural networks. When system size is infinite, it is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the sub-critical regime for finite size systems: the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices.

Optimal system size for complex dynamics in random neural networks near criticality

International Nuclear Information System (INIS)

Wainrib, Gilles; García del Molino, Luis Carlos

2013-01-01

In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259–262 (1988)] in the context of random neural networks. When system size is infinite, it is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the sub-critical regime for finite size systems: the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices

Complex Nonlinear Dynamic System of Oligopolies Price Game with Heterogeneous Players Under Noise

Science.gov (United States)

Liu, Feng; Li, Yaguang

A nonlinear four oligopolies price game with heterogeneous players, that are boundedly rational and adaptive, is built using two different special demand costs. Based on the theory of complex discrete dynamical system, the stability and the existing equilibrium point are investigated. The complex dynamic behavior is presented via bifurcation diagrams, the Lyapunov exponents to show equilibrium state, bifurcation and chaos with the variation in parameters. As disturbance is ubiquitous in economic systems, this paper focuses on the analysis of delay feedback control method under noise circumstances. Stable dynamics is confirmed to depend mainly on the low price adjustment speed, and if all four players have limited opportunities to stabilize the market, the new adaptive player facing profits of scale are found to be higher than the incumbents of bounded rational.

Kinetics of the Dynamical Information Shannon Entropy for Complex Systems

International Nuclear Information System (INIS)

Yulmetyev, R.M.; Yulmetyeva, D.G.

1999-01-01

Kinetic behaviour of dynamical information Shannon entropy is discussed for complex systems: physical systems with non-Markovian property and memory in correlation approximation, and biological and physiological systems with sequences of the Markovian and non-Markovian random noises. For the stochastic processes, a description of the information entropy in terms of normalized time correlation functions is given. The influence and important role of two mutually dependent channels of the entropy change, correlation (creation or generation of correlations) and anti-correlation (decay or annihilation of correlation) is discussed. The method developed here is also used in analysis of the density fluctuations in liquid cesium obtained from slow neutron scattering data, fractal kinetics of the long-range fluctuation in the short-time human memory and chaotic dynamics of R-R intervals of human ECG. (author)

Early days in complex dynamics a history of complex dynamics in one variable during 1906-1942

CERN Document Server

Alexander, Daniel S; Rosa, Alessandro

2011-01-01

The theory of complex dynamics, whose roots lie in 19th-century studies of the iteration of complex function conducted by Kœnigs, Schröder, and others, flourished remarkably during the first half of the 20th century, when many of the central ideas and techniques of the subject developed. This book by Alexander, Iavernaro, and Rosa paints a robust picture of the field of complex dynamics between 1906 and 1942 through detailed discussions of the work of Fatou, Julia, Siegel, and several others. A recurrent theme of the authors' treatment is the center problem in complex dynamics. They present its complete history during this period and, in so doing, bring out analogies between complex dynamics and the study of differential equations, in particular, the problem of stability in Hamiltonian systems. Among these analogies are the use of iteration and problems involving small divisors which the authors examine in the work of Poincaré and others, linking them to complex dynamics, principally via the work of Samuel...

A complex, nonlinear dynamic systems perspective on Ayurveda and Ayurvedic research.

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Rioux, Jennifer

2012-07-01

The fields of complexity theory and nonlinear dynamic systems (NDS) are relevant for analyzing the theory and practice of Ayurvedic medicine from a Western scientific perspective. Ayurvedic definitions of health map clearly onto the tenets of both systems and complexity theory and focus primarily on the preservation of organismic equanimity. Health care research informed by NDS and complexity theory would prioritize (1) ascertaining patterns reflected in whole systems as opposed to isolating components; (2) relationships and dynamic interaction rather than static end-points; (3) transitions, change and cumulative effects, consistent with delivery of therapeutic packages in the reality of the clinical setting; and (4) simultaneously exploring both local and global levels of healing phenomena. NDS and complexity theory are useful in examining nonlinear transitions between states of health and illness; the qualitative nature of shifts in health status; and looking at emergent properties and behaviors stemming from interactions between organismic and environmental systems. Complexity and NDS theory also demonstrate promise for enhancing the suitability of research strategies applied to Ayurvedic medicine through utilizing core concepts such as initial conditions, emergent properties, fractal patterns, and critical fluctuations. In the Ayurvedic paradigm, multiple scales and their interactions are addressed simultaneously, necessitating data collection on change patterns that occur on continuums of both time and space, and are viewed as complementary rather than isolated and discrete. Serious consideration of Ayurvedic clinical understandings will necessitate new measurement options that can account for the relevance of both context and environmental factors, in terms of local biology and the processual features of the clinical encounter. Relevant research design issues will need to address clinical tailoring strategies and provide mechanisms for mapping patterns of

Stochastic dynamics of complex systems: from glasses to evolution (series on complexity science)

CERN Document Server

Sibani, Paolo

2013-01-01

Dynamical evolution over long time scales is a prominent feature of all the systems we intuitively think of as complex - for example, ecosystems, the brain or the economy. In physics, the term ageing is used for this type of slow change, occurring over time scales much longer than the patience, or indeed the lifetime, of the observer. The main focus of this book is on the stochastic processes which cause ageing, and the surprising fact that the ageing dynamics of systems which are very different at the microscopic level can be treated in similar ways. The first part of this book provides the necessary mathematical and computational tools and the second part describes the intuition needed to deal with these systems. Some of the first few chapters have been covered in several other books, but the emphasis and selection of the topics reflect both the authors' interests and the overall theme of the book. The second part contains an introduction to the scientific literature and deals in some detail with the desc...

Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.

Science.gov (United States)

Weber, Bruce H

2011-03-01

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. Copyright © 2010 Elsevier Ltd. All rights reserved.

Complex dynamics in three-well duffing system with two external forcings

International Nuclear Information System (INIS)

Jing Zhujun; Huang Jicai; Deng Jin

2007-01-01

Three-well duffing system with two external forcing terms is investigated. The criterion of existence of chaos under the periodic perturbation is given by using Melnikov's method. By using second-order averaging method and Melnikov's method we proved the criterion of existence of chaos in averaged systems under quasi-periodic perturbation for ω 2 = nω 1 + εν, n = 1, 3, 5, and cannot prove the criterion of existence of chaos in second-order averaged system under quasi-periodic perturbation for ω 2 = nω 1 + εν, n = 2, 4, 6, 7, 8, 9, 10, 11, 12, where ν is not rational to ω 1 , but can show the occurrence of chaos in original system by numerical simulation. Numerical simulations including heteroclinic and homoclinic bifurcation surfaces, bifurcation diagrams, maximum Lyapunov exponents and Poincare map are given to illustrate the theoretical analysis, and to expose the more new complex dynamical behaviors. We show that cascades of period-doubling bifurcations from period-one to four orbits, cascades of interlocking period-doubling bifurcations from period-two orbits of two sets, from quasi-periodicity leading to chaos, onset of chaos which occurs more than one, interleaving occurrences of chaotic behavior and invariant torus, transient chaos with complex period windows and interior crisis, chaos converting to torus, different kind of chaotic attractors. Our results shows that the dynamical behaviors are different from the dynamics of duffing equation with two-well and two external forcings

Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective

International Nuclear Information System (INIS)

Peng, Weiwen; Li, Yan-Feng; Mi, Jinhua; Yu, Le; Huang, Hong-Zhong

2016-01-01

Degradation analysis is critical to reliability assessment and operational management of complex systems. Two types of assumptions are often adopted for degradation analysis: (1) single degradation indicator and (2) constant external factors. However, modern complex systems are generally characterized as multiple functional and suffered from multiple failure modes due to dynamic operating conditions. In this paper, Bayesian degradation analysis of complex systems with multiple degradation indicators under dynamic conditions is investigated. Three practical engineering-driven issues are addressed: (1) to model various combinations of degradation indicators, a generalized multivariate hybrid degradation process model is proposed, which subsumes both monotonic and non-monotonic degradation processes models as special cases, (2) to study effects of external factors, two types of dynamic covariates are incorporated jointly, which include both environmental conditions and operating profiles, and (3) to facilitate degradation based reliability analysis, a serial of Bayesian strategy is constructed, which covers parameter estimation, factor-related degradation prediction, and unit-specific remaining useful life assessment. Finally, degradation analysis of a type of heavy machine tools is presented to demonstrate the application and performance of the proposed method. A comparison of the proposed model with a traditional model is studied as well in the example. - Highlights: • A generalized multivariate hybrid degradation process model is introduced. • Various types of dependent degradation processes can be modeled coherently. • The effects of environmental conditions and operating profiles are investigated. • Unit-specific RUL assessment is implemented through a two-step Bayesian method.

Complex dynamics in Josephson system with two external forcing terms

International Nuclear Information System (INIS)

Yang Jianping; Feng Wei; Jing Zhujun

2006-01-01

Josephson system with two external forcing terms is investigated. By applying Melnikov method, we prove that criterion of existence of chaos under periodic perturbation. By second-order averaging method and Melnikov method, we obtain the criterion of existence of chaos in averaged system under quasi-periodic perturbation for ω 2 =ω 1 +εν, and cannot prove the criterion of existence of chaos in averaged system under quasi-periodic perturbation for ω 2 =nω 1 +εν (n>=2 and n-bar N), where ν is not rational to ω 1 . We also study the effects of the parameters of system on dynamical behaviors by using numerical simulation. The numerical simulations, including bifurcation diagram of fixed points, bifurcation diagram of system in three- and two-dimensional space, homoclinic and heteroclinic bifurcation surface, Maximum Lyapunov exponent, phase portraits, Poincare map, are also plotted to illustrate theoretical analysis, and to expose the complex dynamical behaviors, including the period-n (n=1,2,5,7) orbits in different chaotic regions, cascades of period-doubling bifurcation from period-1, 2 and 5 orbits, reverse period-doubling bifurcation, onset of chaos which occurs more than once for two given external frequencies and chaos suddenly converting to periodic orbits, transient chaos with complex periodic windows and crisis, reverse period-5 bubble, non-attracting chaotic set and nice attracting chaotic set. In particular, we observe that the system can leave chaotic region to periodic motion by adjusting damping α, amplitude f 1 and frequency ω 2 of external forcing which can be considered as a control strategy

a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems

Science.gov (United States)

Shao, Xiao; Chai, Li H.

As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.

Dynamics of a Simple Quantum System in a Complex Environment

CERN Document Server

Bulgac, A; Kusnezov, D; Bulgac, Aurel; Dang, Gui Do; Kusnezov, Dimitri

1998-01-01

We present a theory for the dynamical evolution of a quantum system coupled to a complex many-body intrinsic system/environment. By modelling the intrinsic many-body system with parametric random matrices, we study the types of effective stochastic models which emerge from random matrix theory. Using the Feynman-Vernon path integral formalism, we derive the influence functional and obtain either analytical or numerical solutions for the time evolution of the entire quantum system. We discuss thoroughly the structure of the solutions for some representative cases and make connections to well known limiting results, particularly to Brownian motion, Kramers classical limit and the Caldeira-Leggett approach.

Nonlinear and Complex Dynamics in Economics

OpenAIRE

William Barnett; Apostolos Serletis; Demitre Serletis

2012-01-01

This paper is an up-to-date survey of the state-of-the-art in dynamical systems theory relevant to high levels of dynamical complexity, characterizing chaos and near chaos, as commonly found in the physical sciences. The paper also surveys applications in economics and �finance. This survey does not include bifurcation analyses at lower levels of dynamical complexity, such as Hopf and transcritical bifurcations, which arise closer to the stable region of the parameter space. We discuss the...

Chaotic, fractional, and complex dynamics new insights and perspectives

CERN Document Server

Macau, Elbert; Sanjuan, Miguel

2018-01-01

The book presents nonlinear, chaotic and fractional dynamics, complex systems and networks, together with cutting-edge research on related topics. The fifteen chapters – written by leading scientists working in the areas of nonlinear, chaotic and fractional dynamics, as well as complex systems and networks – offer an extensive overview of cutting-edge research on a range of topics, including fundamental and applied research. These include but are not limited to aspects of synchronization in complex dynamical systems, universality features in systems with specific fractional dynamics, and chaotic scattering. As such, the book provides an excellent and timely snapshot of the current state of research, blending the insights and experiences of many prominent researchers.

Inferring network topology from complex dynamics

International Nuclear Information System (INIS)

Shandilya, Srinivas Gorur; Timme, Marc

2011-01-01

Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.

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

Science.gov (United States)

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.

Equation-free model reduction for complex dynamical systems

International Nuclear Information System (INIS)

Le Maitre, O. P.; Mathelin, L.; Le Maitre, O. P.

2010-01-01

This paper presents a reduced model strategy for simulation of complex physical systems. A classical reduced basis is first constructed relying on proper orthogonal decomposition of the system. Then, unlike the alternative approaches, such as Galerkin projection schemes for instance, an equation-free reduced model is constructed. It consists in the determination of an explicit transformation, or mapping, for the evolution over a coarse time-step of the projection coefficients of the system state on the reduced basis. The mapping is expressed as an explicit polynomial transformation of the projection coefficients and is computed once and for all in a pre-processing stage using the detailed model equation of the system. The reduced system can then be advanced in time by successive applications of the mapping. The CPU cost of the method lies essentially in the mapping approximation which is performed offline, in a parallel fashion, and only once. Subsequent application of the mapping to perform a time-integration is carried out at a low cost thanks to its explicit character. Application of the method is considered for the 2-D flow around a circular cylinder. We investigate the effectiveness of the reduced model in rendering the dynamics for both asymptotic state and transient stages. It is shown that the method leads to a stable and accurate time-integration for only a fraction of the cost of a detailed simulation, provided that the mapping is properly approximated and the reduced basis remains relevant for the dynamics investigated. (authors)

Bifurcation and complex dynamics of a discrete-time predator-prey system involving group defense

Directory of Open Access Journals (Sweden)

S. M. Sohel Rana

2015-09-01

Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system involving group defense. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamical behaviors, including phase portraits, period-7, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors.

Modeling Networks and Dynamics in Complex Systems: from Nano-Composites to Opinion Formation

Science.gov (United States)

Shi, Feng

Complex networks are ubiquitous in systems of physical, biological, social or technological origin. Components in those systems range from as large as cities in power grids, to as small as molecules in metabolic networks. Since the dawn of network science, significant attention has focused on the implications of dynamics in establishing network structure and the impact of structural properties on dynamics on those networks. The first part of the thesis follows this direction, studying the network formed by conductive nanorods in nano-materials, and focuses on the electrical response of the composite to the structure change of the network. New scaling laws for the shear-induced anisotropic percolation are introduced and a robust exponential tail of the current distribution across the network is identified. These results are relevant especially to "active" composite materials where materials are exposed to mechanical loading and strain deformations. However, in many real-world networks the evolution of the network topology is tied to the states of the vertices and vice versa. Networks that exhibit such a feedback are called adaptive or coevolutionary networks. The second part of the thesis examines two closely related variants of a simple, abstract model for coevolution of a network and the opinions of its members. As a representative model for adaptive networks, it displays the feature of self-organization of the system into a stable configuration due to the interplay between the network topology and the dynamics on the network. This simple model yields interesting dynamics and the slight change in the rewiring strategy results in qualitatively different behaviors of the system. In conclusion, the dissertation aims to develop new network models and tools which enable insights into the structure and dynamics of various systems, and seeks to advance network algorithms which provide approaches to coherently articulated questions in real-world complex systems such as

Introduction to turbulent dynamical systems in complex systems

CERN Document Server

Majda, Andrew J

2016-01-01

This volume is a research expository article on the applied mathematics of turbulent dynamical systems through the paradigm of modern applied mathematics. It involves the blending of rigorous mathematical theory, qualitative and quantitative modeling, and novel numerical procedures driven by the goal of understanding physical phenomena which are of central importance to the field. The contents cover general framework, concrete examples, and instructive qualitative models. Accessible open problems are mentioned throughout. Topics covered include: · Geophysical flows with rotation, topography, deterministic and random forcing · New statistical energy principles for general turbulent dynamical systems, with applications · Linear statistical response theory combined with information theory to cope with model errors · Reduced low order models · Recent mathematical strategies for online data assimilation of turbulent dynamical systems as well as rigorous results for finite ensemble Kalman filters The volume wi...

Dynamic complexity of a two-prey one-predator system with impulsive effect

International Nuclear Information System (INIS)

Zhang Yujuan; Xiu Zhilong; Chen Lansun

2005-01-01

In this paper, we investigate the dynamic complexity of a two-prey one-predator system with impulsive perturbation on predator at fixed moments. With the increase of the predation rate for the super competitor, the system displays complicated phenomena including a sequence of direct and inverse cascade of periodic-doubling, chaos, and symmetry breaking bifurcation. Moreover, we discuss the effect of the period of releasing predator on the dynamical behaviors of the unforced continuous system, and find that periodically releasing predator at fixed moments change the properties of the unforced continuous system. We suggest a highly effective method in pest control. The target pest population can be driven to extinction and the non-target pest (or harmless insect) can be permanent by choosing impulsive period, while classical method cannot emulate

Managing Complex Dynamical Systems

Science.gov (United States)

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

2011-01-01

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

The Modeling and Complexity of Dynamical Systems by Means of Computation and Information Theories

Directory of Open Access Journals (Sweden)

Robert Logozar

2011-12-01

Full Text Available We present the modeling of dynamical systems and finding of their complexity indicators by the use of concepts from computation and information theories, within the framework of J. P. Crutchfield's theory of  ε-machines. A short formal outline of the  ε-machines is given. In this approach, dynamical systems are analyzed directly from the time series that is received from a properly adjusted measuring instrument. The binary strings are parsed through the parse tree, within which morphologically and probabilistically unique subtrees or morphs are recognized as system states. The outline and precise interrelation of the information-theoretic entropies and complexities emanating from the model is given. The paper serves also as a theoretical foundation for the future presentation of the DSA program that implements the  ε-machines modeling up to the stochastic finite automata level.

Neonatal Feeding Behavior as a Complex Dynamical System.

Science.gov (United States)

Goldfield, Eugene C; Perez, Jennifer; Engstler, Katherine

2017-04-01

The requirements of evidence-based practice in 2017 are motivating new theoretical foundations and methodological tools for characterizing neonatal feeding behavior. Toward that end, this article offers a complex dynamical systems perspective. A set of critical concepts from this perspective frames challenges faced by speech-language pathologists and allied professionals: when to initiate oral feeds, how to determine the robustness of neonatal breathing during feeding and appropriate levels of respiratory support, what instrumental assessments of swallow function to use with preterm neonates, and whether or not to introduce thickened liquids. In the near future, we can expect vast amounts of new data to guide evidence-based practice. But unless practitioners are able to frame these issues in a systems context larger than the individual child, the availability of "big data" will not be effectively translated to clinical practice. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Complexified dynamical systems

International Nuclear Information System (INIS)

Bender, Carl M; Holm, Darryl D; Hook, Daniel W

2007-01-01

Many dynamical systems, such as the Lotka-Volterra predator-prey model and the Euler equations for the free rotation of a rigid body, are PT symmetric. The standard and well-known real solutions to such dynamical systems constitute an infinitessimal subclass of the full set of complex solutions. This paper examines a subset of the complex solutions that contains the real solutions, namely those having PT symmetry. The condition of PT symmetry selects out complex solutions that are periodic. (fast track communication)

Philosophy of complex systems

CERN Document Server

2011-01-01

The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on. Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of comple...

SACS2: Dynamic and Formal Safety Analysis Method for Complex Safety Critical System

International Nuclear Information System (INIS)

Koh, Kwang Yong; Seong, Poong Hyun

2009-01-01

Fault tree analysis (FTA) is one of the most widely used safety analysis technique in the development of safety critical systems. However, over the years, several drawbacks of the conventional FTA have become apparent. One major drawback is that conventional FTA uses only static gates and hence can not capture dynamic behaviors of the complex system precisely. Although several attempts such as dynamic fault tree (DFT), PANDORA, formal fault tree (FFT) and so on, have been made to overcome this problem, they can not still do absolute or actual time modeling because they adapt relative time concept and can capture only sequential behaviors of the system. Second drawback of conventional FTA is its lack of rigorous semantics. Because it is informal in nature, safety analysis results heavily depend on an analyst's ability and are error-prone. Finally reasoning process which is to check whether basic events really cause top events is done manually and hence very labor-intensive and timeconsuming for the complex systems. In this paper, we propose a new safety analysis method for complex safety critical system in qualitative manner. We introduce several temporal gates based on timed computational tree logic (TCTL) which can represent quantitative notion of time. Then, we translate the information of the fault trees into UPPAAL query language and the reasoning process is automatically done by UPPAAL which is the model checker for time critical system

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Science.gov (United States)

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Directory of Open Access Journals (Sweden)

Zhong Yi Wan

Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more

Dynamics of a complex quantum magnet

International Nuclear Information System (INIS)

Landry, James W.; Coppersmith, S. N.

2003-01-01

We have computed the low energy quantum states and low frequency dynamical susceptibility of complex quantum spin systems in the limit of strong interactions, obtaining exact results for system sizes enormously larger than accessible previously. The ground state is a complex superposition of a substantial fraction of all the classical ground states, and yet the dynamical susceptibility exhibits sharp resonances reminiscent of the behavior of single spins. These results show that strongly interacting quantum systems can organize to generate coherent excitations and shed light on recent experiments demonstrating that coherent excitations are present in a disordered spin liquid. The dependence of the energy spectra on system size differs qualitatively from that of the energy spectra of random undirected bipartite graphs with similar statistics, implying that strong interactions are giving rise to these unusual spectral properties

New Approach for Nuclear Safety and Regulation - Application of Complexity Theory and System Dynamics

International Nuclear Information System (INIS)

Choi, Kwang Sik; Choi, Young Sung; Han, Kyu Hyun; Kim, Do Hyoung

2007-01-01

The methodology being used today for assuring nuclear safety is based on analytic approaches. In the 21st century, holistic approaches are increasingly used over traditional analytic method that is based on reductionism. Presently, it leads to interest in complexity theory or system dynamics. In this paper, we review global academic trends, social environments, concept of nuclear safety and regulatory frameworks for nuclear safety. We propose a new safety paradigm and also regulatory approach using holistic approach and system dynamics now in fashion

Emergence of dynamical order synchronization phenomena in complex systems

CERN Document Server

Manrubia, Susanna C; Zanette, Damián H

2004-01-01

Synchronization processes bring about dynamical order and lead tospontaneous development of structural organization in complex systemsof various origins, from chemical oscillators and biological cells tohuman societies and the brain. This book provides a review and adetailed theoretical analysis of synchronization phenomena in complexsystems with different architectures, composed of elements withperiodic or chaotic individual dynamics. Special attention is paid tostatistical concepts, such as nonequilibrium phase transitions, orderparameters and dynamical glasses.

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

OpenAIRE

Reza Kalantari; Javad Gholami

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, McNamara, Louwerse, & Cai, 2004; McNamara & Graesser, 2012), three Lexical Complexity Analyzer indices (Lu, 2010, 2012; Lu & Ai, 2011...

Complexity of Economical Systems

Directory of Open Access Journals (Sweden)

G. P. Pavlos

2015-01-01

Full Text Available In this study new theoretical concepts are described concerning the interpretation of economical complex dynamics. In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24]. In general, Economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. As a result the economic and financial variables such as foreign exchange rates, gross domestic product, interest rates, production, stock market prices and unemployment exhibit large-amplitude and aperiodic fluctuations evident in complex systems. Thus, the Economics can be considered as spatially distributed non-equilibrium complex system, for which new theoretical concepts, such as Tsallis non extensive statistical mechanics and strange dynamics, percolation, nonGaussian, multifractal and multiscale dynamics related to fractional Langevin equations can be used for modeling and understanding of the economical complexity locally or globally.

System dynamics in complex psychiatric treatment organizations.

Science.gov (United States)

Rosenheck, R

1988-05-01

One of the major challenges facing contemporary psychiatry is the coordination of diverse services through organizational integration. With increasing frequency, psychiatric treatment takes place in complex treatment systems composed of multiple inpatient and outpatient programs. Particularly in public health care systems serving the chronically ill, contemporary practice demands a broad spectrum of programs, often geographically dispersed, that include crisis intervention teams, day treatment programs, substance abuse units, social rehabilitation programs and halfway houses (Bachrach 1983; Turner and TenHoor 1978). Individualized treatment planning often requires that a particular patient participate in two or more specialized programs either simultaneously or in a specified sequence. As a consequence of this specialization, treatment fragmentation has emerged as a significant clinical problem, and continuity of care has been highlighted as a valuable but elusive ingredient of optimal treatment. This paper will describe the dynamic interactions that result when several such programs are united under a common organizational roof. Using a large VA Psychiatry Service as an example, I will outline the hierarchical structure characteristic of such an organization, as well as the persistent pulls toward both integration and fragmentation that influence its operation.

Universal dynamics of complex adaptive systems: Gauge theory of things alive

International Nuclear Information System (INIS)

Mack, G.

1994-04-01

A universal dynamics of objects and their relations - a kind of ''universal chemistry'' - is discussed which satisfies general principles of locality and relativity. Einsteins theory of gravitation and the gauge theory of elementary particles are prototypes, but complex adaptive systems - anything that is alive in the widest sense - fall under the same paradigma. Frustration and gauge symmetry arise naturally in this context. Besides a nondissipative deterministic dynamics, which is thought to operate at a fundamental levle, a Thermo-Dynamics in sense of Prigogine is introduced by adding a diffusion process. It introduces irreversibility and entropy production. It equilibrates the chaotic local model of the time development (only) and is designed to be undetectable under continued observation with given finite measuring accuracy. Compositeness and the development of structure can be described in this framework. The existence of a critical equilibrium state may be postulated which is invariant under the dynamics. But it is usually not reached in a finite time from a given starting configuration, because local dynamics suffers from critical slowing down, especially in the presence of frustration. (orig.)

Embracing Connectedness and Change: A Complex Dynamic Systems Perspective for Applied Linguistic Research

Science.gov (United States)

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…

Encyclopedia of Complexity and Systems Science

CERN Document Server

Meyers, Robert A

2009-01-01

Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...

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

Science.gov (United States)

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

2016-03-01

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

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

Science.gov (United States)

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.

Anti-synchronization between different chaotic complex systems

International Nuclear Information System (INIS)

Liu Ping; Liu Shutang

2011-01-01

Many studies on the anti-synchronization of nonlinear real dynamic systems have been carried out, whereas the anti-synchronization of chaotic complex systems has not been studied extensively. In this work, the anti-synchronization between a new chaotic complex system and a complex Lorenz system and that between a new chaotic complex system and a complex Lue system were separately investigated by active control and nonlinear control methods, and explicit expressions were derived for the controllers that are used to achieve the anti-synchronization of chaotic complex systems. These expressions were tested numerically and excellent agreement was found. Concerning the new chaotic complex system, we discuss its dynamical properties including dissipation, chaotic behavior, fixed points, and their stability and invariance.

Complexity characterization in a probabilistic approach to dynamical systems through information geometry and inductive inference

International Nuclear Information System (INIS)

Ali, S A; Kim, D-H; Cafaro, C; Giffin, A

2012-01-01

Information geometric techniques and inductive inference methods hold great promise for solving computational problems of interest in classical and quantum physics, especially with regard to complexity characterization of dynamical systems in terms of their probabilistic description on curved statistical manifolds. In this paper, we investigate the possibility of describing the macroscopic behavior of complex systems in terms of the underlying statistical structure of their microscopic degrees of freedom by the use of statistical inductive inference and information geometry. We review the maximum relative entropy formalism and the theoretical structure of the information geometrodynamical approach to chaos on statistical manifolds M S . Special focus is devoted to a description of the roles played by the sectional curvature K M S , the Jacobi field intensity J M S and the information geometrodynamical entropy S M S . These quantities serve as powerful information-geometric complexity measures of information-constrained dynamics associated with arbitrary chaotic and regular systems defined on M S . Finally, the application of such information-geometric techniques to several theoretical models is presented.

Exponential rise of dynamical complexity in quantum computing through projections.

Science.gov (United States)

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.

Local difference measures between complex networks for dynamical system model evaluation.

Science.gov (United States)

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node

Theoretical foundation for the discrete dynamics of physicochemical systems: Chaos, self-organization, time and space in complex systems

Directory of Open Access Journals (Sweden)

V. Gontar

1997-01-01

Full Text Available A new theoretical foundation for the discrete dynamics of physicochemical systems is presented. Based on the analogy between the π-theorem of the theory of dimensionality, the second law of thermodynamics and the stoichiometry of complex physicochemical reactions, basic dynamic equations and an extreme principle were formulated. The meaning of discrete time and space in the proposed equations is discussed. Some results of numerical calculations are presented to demonstrate the potential of the proposed approach to the mathematical simulation of spatiotemporal physicochemical reaction dynamics.

Dynamical complexity changes during two forms of meditation

Science.gov (United States)

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.

Complex and unexpected dynamics in simple genetic regulatory networks

Science.gov (United States)

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.

Integrated health management and control of complex dynamical systems

Science.gov (United States)

Tolani, Devendra K.

2005-11-01

A comprehensive control and health management strategy for human-engineered complex dynamical systems is formulated for achieving high performance and reliability over a wide range of operation. Results from diverse research areas such as Probabilistic Robust Control (PRC), Damage Mitigating/Life Extending Control (DMC), Discrete Event Supervisory (DES) Control, Symbolic Time Series Analysis (STSA) and Health and Usage Monitoring System (HUMS) have been employed to achieve this goal. Continuous-domain control modules at the lower level are synthesized by PRC and DMC theories, whereas the upper-level supervision is based on DES control theory. In the PRC approach, by allowing different levels of risk under different flight conditions, the control system can achieve the desired trade off between stability robustness and nominal performance. In the DMC approach, component damage is incorporated in the control law to reduce the damage rate for enhanced structural durability. The DES controller monitors the system performance and, based on the mission requirements (e.g., performance metrics and level of damage mitigation), switches among various lower-level controllers. The core idea is to design a framework where the DES controller at the upper-level, mimics human intelligence and makes appropriate decisions to satisfy mission requirements, enhance system performance and structural durability. Recently developed tools in STSA have been used for anomaly detection and failure prognosis. The DMC deals with the usage monitoring or operational control part of health management, where as the issue of health monitoring is addressed by the anomaly detection tools. The proposed decision and control architecture has been validated on two test-beds, simulating the operations of rotorcraft dynamics and aircraft propulsion.

Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm

Directory of Open Access Journals (Sweden)

Hui Li

2017-01-01

Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.

Complex analysis and dynamical systems new trends and open problems

CERN Document Server

Golberg, Anatoly; Jacobzon, Fiana; Shoikhet, David; Zalcman, Lawrence

2018-01-01

This book focuses on developments in complex dynamical systems and geometric function theory over the past decade, showing strong links with other areas of mathematics and the natural sciences. Traditional methods and approaches surface in physics and in the life and engineering sciences with increasing frequency – the Schramm‐Loewner evolution, Laplacian growth, and quadratic differentials are just a few typical examples. This book provides a representative overview of these processes and collects open problems in the various areas, while at the same time showing where and how each particular topic evolves. This volume is dedicated to the memory of Alexander Vasiliev.

Searching for Appropriate Ways to Face the Challenges of Complexity and Dynamics

OpenAIRE

Sommerfeld, Peter; Hollenstein, Lea

2017-01-01

People, as bio-psychological systems, are just as dynamic and complex as the social systems that they create. Social work intervenes in the interplay of these two complex, dynamic systems. How can we capture these complexities and dynamics in social work research and practice? The paper introduces the theoretical grounds on which a mixed-methods design has been developed combining a longitudinal quantitative method called Real Time Monitoring that produces dense time series data with qualitat...

Coarse-graining complex dynamics

DEFF Research Database (Denmark)

Sibani, Paolo

2013-01-01

Continuous Time Random Walks (CTRW) are widely used to coarse-grain the evolution of systems jumping from a metastable sub-set of their configuration space, or trap, to another via rare intermittent events. The multi-scaled behavior typical of complex dynamics is provided by a fat...... macroscopic variables all produce identical long time relaxation behaviors. Hence, CTRW shed no light on the link between microscopic and macroscopic dynamics. We then highlight how a more recent approach, Record Dynamics (RD) provides a viable alternative, based on a very different set of physical ideas......: while CTRW make use of a renewal process involving identical traps of infinite size, RD embodies a dynamical entrenchment into a hierarchy of traps which are finite in size and possess different degrees of meta-stability. We show in particular how RD produces the stretched exponential, power...

Nonlinear and Complex Dynamics in Real Systems

OpenAIRE

William Barnett; Apostolos Serletis; Demitre Serletis

2005-01-01

This paper was produced for the El-Naschie Symposium on Nonlinear Dynamics in Shanghai in December 2005. In this paper we provide a review of the literature with respect to fluctuations in real systems and chaos. In doing so, we contrast the order and organization hypothesis of real systems with nonlinear chaotic dynamics and discuss some techniques used in distinguishing between stochastic and deterministic behavior. Moreover, we look at the issue of where and when the ideas of chaos could p...

Product development projects dynamics and emergent complexity

CERN Document Server

Schlick, Christopher

2016-01-01

This book primarily explores two topics: the representation of simultaneous, cooperative work processes in product development projects with the help of statistical models, and the assessment of their emergent complexity using a metric from theoretical physics (Effective Measure Complexity, EMC). It is intended to promote more effective management of development projects by shifting the focus from the structural complexity of the product being developed to the dynamic complexity of the development processes involved. The book is divided into four main parts, the first of which provides an introduction to vector autoregression models, periodic vector autoregression models and linear dynamical systems for modeling cooperative work in product development projects. The second part presents theoretical approaches for assessing complexity in the product development environment, while the third highlights and explains closed-form solutions for the complexity metric EMC for vector autoregression models and linear dyn...

Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

Science.gov (United States)

Marek, Michael W.; Wu, Wen-Chi Vivian

2014-01-01

This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

Complex economic dynamics: Chaotic saddle, crisis and intermittency

International Nuclear Information System (INIS)

Chian, Abraham C.-L.; Rempel, Erico L.; Rogers, Colin

2006-01-01

Complex economic dynamics is studied by a forced oscillator model of business cycles. The technique of numerical modeling is applied to characterize the fundamental properties of complex economic systems which exhibit multiscale and multistability behaviors, as well as coexistence of order and chaos. In particular, we focus on the dynamics and structure of unstable periodic orbits and chaotic saddles within a periodic window of the bifurcation diagram, at the onset of a saddle-node bifurcation and of an attractor merging crisis, and in the chaotic regions associated with type-I intermittency and crisis-induced intermittency, in non-linear economic cycles. Inside a periodic window, chaotic saddles are responsible for the transient motion preceding convergence to a periodic or a chaotic attractor. The links between chaotic saddles, crisis and intermittency in complex economic dynamics are discussed. We show that a chaotic attractor is composed of chaotic saddles and unstable periodic orbits located in the gap regions of chaotic saddles. Non-linear modeling of economic chaotic saddle, crisis and intermittency can improve our understanding of the dynamics of financial intermittency observed in stock market and foreign exchange market. Characterization of the complex dynamics of economic systems is a powerful tool for pattern recognition and forecasting of business and financial cycles, as well as for optimization of management strategy and decision technology

Modeling Complex Systems

International Nuclear Information System (INIS)

Schreckenberg, M

2004-01-01

This book by Nino Boccara presents a compilation of model systems commonly termed as 'complex'. It starts with a definition of the systems under consideration and how to build up a model to describe the complex dynamics. The subsequent chapters are devoted to various categories of mean-field type models (differential and recurrence equations, chaos) and of agent-based models (cellular automata, networks and power-law distributions). Each chapter is supplemented by a number of exercises and their solutions. The table of contents looks a little arbitrary but the author took the most prominent model systems investigated over the years (and up until now there has been no unified theory covering the various aspects of complex dynamics). The model systems are explained by looking at a number of applications in various fields. The book is written as a textbook for interested students as well as serving as a comprehensive reference for experts. It is an ideal source for topics to be presented in a lecture on dynamics of complex systems. This is the first book on this 'wide' topic and I have long awaited such a book (in fact I planned to write it myself but this is much better than I could ever have written it!). Only section 6 on cellular automata is a little too limited to the author's point of view and one would have expected more about the famous Domany-Kinzel model (and more accurate citation!). In my opinion this is one of the best textbooks published during the last decade and even experts can learn a lot from it. Hopefully there will be an actualization after, say, five years since this field is growing so quickly. The price is too high for students but this, unfortunately, is the normal case today. Nevertheless I think it will be a great success! (book review)

Quantum Dynamical Behaviour in Complex Systems - A Semiclassical Approach

Energy Technology Data Exchange (ETDEWEB)

Ananth, Nandini [Univ. of California, Berkeley, CA (United States)

2008-01-01

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

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

Science.gov (United States)

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.

Transition Manifolds of Complex Metastable Systems

Science.gov (United States)

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.

From System Complexity to Emergent Properties

CERN Document Server

Aziz-Alaoui, M. A

2009-01-01

Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.

Exploring dynamical complexity in diffusion driven predator-prey systems: Effect of toxin producing phytoplankton and spatial heterogeneities

International Nuclear Information System (INIS)

Upadhyay, Ranjit Kumar; Kumari, Nitu; Rai, Vikas

2009-01-01

In this paper, dynamical complexities in two reaction-diffusion (RD) model systems are explored. A spatial heterogeneity in the form of linear spatial gradient in the reproductive growth rate of the phytoplankton is incorporated in both the model systems. Extra mortality of the zooplankton due to toxin production by the phytoplankton is included in the second reaction diffusion model system. Effect of toxin production and spatial heterogeneity in the model systems are studied. Toxin production does not seem to have an appreciable effect on the asymptotic dynamics of the model systems. On the other hand, spatial heterogeneity does influence the dynamics. In particular, it increases the frequency of occurrence of chaos as evident from two dimensional parameter scans. Both these model systems display short term recurrent chaos [Rai V. Chaos in natural populations: edge or wedge? Ecol Complex 2004;1: 127-38] as they reside on 'edges of chaos' (EOC) [Rai V, Upadhyay RK. Evolving to the edge of chaos: chance or necessity? Chaos, Solitons and Fractals 2006;30:1074-87]. This suggests that the ecological systems have a tendency to evolve to EOC. The study corroborates the inferences drawn from an earlier study by Rai and Upadhyay [Rai V, Upadhyay RK. Evolving to the edge of chaos: chance or necessity? Chaos, Solitons and Fractals 2006;30:1074-87]. The system's dynamics is largely unpredictable and admits bursts of short-term predictability.

The emergence of learning-teaching trajectories in education: a complex dynamic systems approach.

Science.gov (United States)

Steenbeek, Henderien; van Geert, Paul

2013-04-01

In this article we shall focus on learning-teaching trajectories ='successful' as well as 'unsuccessful' ones - as emergent and dynamic phenomena resulting from the interactions in the entire educational context, in particular the interaction between students and teachers viewed as processes of intertwining self-, other- and co-regulation. The article provides a review of the educational research literature on action regulation in learning and teaching, and interprets this literature in light of the theory of complex dynamic systems. Based on this reinterpretation of the literature, two dynamic models are proposed, one focusing on the short-term dynamics of learning-teaching interactions as they take place in classrooms, the other focusing on the long-term dynamics of interactions in a network of variables encompassing concerns, evaluations, actions and action effects (such as learning) students and teachers. The aim of presenting these models is to demonstrate, first, the possibility of transforming existing educational theory into dynamic models and, second, to provide some suggestions as to how such models can be used to further educational theory and practice.

From Hamiltonian chaos to complex systems a nonlinear physics approach

CERN Document Server

Leonetti, Marc

2013-01-01

From Hamiltonian Chaos to Complex Systems: A Nonlinear Physics Approach collects contributions on recent developments in non-linear dynamics and statistical physics with an emphasis on complex systems. This book provides a wide range of state-of-the-art research in these fields. The unifying aspect of this book is a demonstration of how similar tools coming from dynamical systems, nonlinear physics, and statistical dynamics can lead to a large panorama of  research in various fields of physics and beyond, most notably with the perspective of application in complex systems. This book also: Illustrates the broad research influence of tools coming from dynamical systems, nonlinear physics, and statistical dynamics Adopts a pedagogic approach to facilitate understanding by non-specialists and students Presents applications in complex systems Includes 150 illustrations From Hamiltonian Chaos to Complex Systems: A Nonlinear Physics Approach is an ideal book for graduate students and researchers working in applied...

Physiological complexity and system adaptability: evidence from postural control dynamics of older adults.

Science.gov (United States)

Manor, Brad; Costa, Madalena D; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C K; Novak, Vera; Lipsitz, Lewis A

2010-12-01

The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.

Topics in Complexity: Dynamical Patterns in the Cyberworld

Science.gov (United States)

Qi, Hong

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

The nonlinear response of the complex structural system in nuclear reactors using dynamic substructure method

International Nuclear Information System (INIS)

Zheng, Z.C.; Xie, G.; Du, Q.H.

1987-01-01

Because of the existence of nonlinear characteristics in practical engineering structures, such as large steam turbine-foundation system and offshore platform, it is necessary to predict nonlinear dynamic responses for these very large and complex structural systems subjected extreme load. Due to the limited storage and high executing cost of computers, there are still some difficulties in the analysis for such systems although the traditional finite element methods provide basic available methods to the problems. The dynamic substructure methods, which were developed as a branch of general structural dynamics in the past more than 20 years and have been widely used from aircraft, space vehicles to other mechanical and civil engineering structures, present a powerful method to the analysis of very large structural systems. The key to success is due to the considerable reduction in the number of degrees of freedom while not changing the physical essence of the problems investigated. The dynamic substructure method has been extended to nonlinear system and applicated to the analysis of nonlinear dynamic response of an offshore platform by Z.C. Zheng, et al. (1983, 1985a, b, c). In this paper, the method is presented to analyze dynamic responses of the systems contained intrinsic nonlinearities and with nonlinear attachments and nonlinear supports of nuclear structural systems. The efficiency of the method becomes more clear for nonlinear dynamic problems due to the adoption of iterating processes. For simplicity, the analysis procedure is demonstrated briefly. The generalized substructure method of nonlinear systems is similar to linear systems, only the nonlinear terms are treated as pseudo-forces. Interface coordinates are classified into two categories, the connecting interface coordinates which connect with each other directly in the global system and the linking interface coordinates which link to each other through attachments. (orig./GL)

Complexity and Control: Towards a Rigorous Behavioral Theory of Complex Dynamical Systems

Science.gov (United States)

Ivancevic, Vladimir G.; Reid, Darryn J.

We introduce our motive for writing this book on complexity and control with a popular "complexity myth," which seems to be quite wide spread among chaos and complexity theory fashionistas: quote>Low-dimensional systems usually exhibit complex behaviours (which we know fromMay's studies of the Logisticmap), while high-dimensional systems usually exhibit simple behaviours (which we know from synchronisation studies of the Kuramoto model)...quote> We admit that this naive view on complex (e.g., human) systems versus simple (e.g., physical) systems might seem compelling to various technocratic managers and politicians; indeed, the idea makes for appealing sound-bites. However, it is enough to see both in the equations and computer simulations of pendula of various degree - (i) a single pendulum, (ii) a double pendulum, and (iii) a triple pendulum - that this popular myth is plain nonsense. The only thing that we can learn from it is what every tyrant already knows: by using force as a strong means of control, it is possible to effectively synchronise even hundreds of millions of people, at least for a while.

Complex systems fractionality, time-delay and synchronization

CERN Document Server

Sun, Jian-Qiao

2012-01-01

"Complex Systems: Fractionality, Time-delay and Synchronization" covers the most recent developments and advances in the theory and application of complex systems in these areas. Each chapter was written by scientists highly active in the field of complex systems. The book discusses a new treatise on fractional dynamics and control, as well as the new methods for differential delay systems and control. Lastly, a theoretical framework for the complexity and synchronization of complex system is presented. The book is intended for researchers in the field of nonlinear dynamics in mathematics, physics and engineering. It can also serve as a reference book for graduate students in physics, applied mathematics and engineering. Dr. Albert C.J. Luo is a Professor at Southern Illinois University Edwardsville, USA. Dr. Jian-Qiao Sun is a Professor at the University of California, Merced, USA.

Synchronization coupled systems to complex networks

CERN Document Server

Boccaletti, Stefano; del Genio, Charo I; Amann, Andreas

2018-01-01

A modern introduction to synchronization phenomena, this text presents recent discoveries and the current state of research in the field, from low-dimensional systems to complex networks. The book describes some of the main mechanisms of collective behaviour in dynamical systems, including simple coupled systems, chaotic systems, and systems of infinite-dimension. After introducing the reader to the basic concepts of nonlinear dynamics, the book explores the main synchronized states of coupled systems and describes the influence of noise and the occurrence of synchronous motion in multistable and spatially-extended systems. Finally, the authors discuss the underlying principles of collective dynamics on complex networks, providing an understanding of how networked systems are able to function as a whole in order to process information, perform coordinated tasks, and respond collectively to external perturbations. The demonstrations, numerous illustrations and application examples will help advanced graduate s...

Atomic switch networks as complex adaptive systems

Science.gov (United States)

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.

Discontinuity and complexity in nonlinear physical systems

CERN Document Server

Baleanu, Dumitru; Luo, Albert

2014-01-01

This unique book explores recent developments in experimental research in this broad field, organized in four distinct sections. Part I introduces the reader to the fractional dynamics and Lie group analysis for nonlinear partial differential equations. Part II covers chaos and complexity in nonlinear Hamiltonian systems, important to understand the resonance interactions in nonlinear dynamical systems, such as Tsunami waves and wildfire propagations; as well as Lev flights in chaotic trajectories, dynamical system synchronization and DNA information complexity analysis. Part III examines chaos and periodic motions in discontinuous dynamical systems, extensively present in a range of systems, including piecewise linear systems, vibro-impact systems and drilling systems in engineering. And in Part IV, engineering and financial nonlinearity are discussed. The mechanism of shock wave with saddle-node bifurcation and rotating disk stability will be presented, and the financial nonlinear models will be discussed....

Entropy for the Complexity of Physiological Signal Dynamics.

Science.gov (United States)

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.

Systems Approach to Tourism: A Methodology for Defining Complex Tourism System

Directory of Open Access Journals (Sweden)

Jere Jakulin Tadeja

2017-08-01

Full Text Available Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.

The sleeping brain as a complex system.

Science.gov (United States)

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.

Self-organization of complex networks as a dynamical system.

Science.gov (United States)

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Reliability assessment of complex electromechanical systems under epistemic uncertainty

International Nuclear Information System (INIS)

Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong

2016-01-01

The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.

Automatic Emergence Detection in Complex Systems

Directory of Open Access Journals (Sweden)

Eugene Santos

2017-01-01

Full Text Available Complex systems consist of multiple interacting subsystems, whose nonlinear interactions can result in unanticipated (emergent system events. Extant systems analysis approaches fail to detect such emergent properties, since they analyze each subsystem separately and arrive at decisions typically through linear aggregations of individual analysis results. In this paper, we propose a quantitative definition of emergence for complex systems. We also propose a framework to detect emergent properties given observations of its subsystems. This framework, based on a probabilistic graphical model called Bayesian Knowledge Bases (BKBs, learns individual subsystem dynamics from data, probabilistically and structurally fuses said dynamics into a single complex system dynamics, and detects emergent properties. Fusion is the central element of our approach to account for situations when a common variable may have different probabilistic distributions in different subsystems. We evaluate our detection performance against a baseline approach (Bayesian Network ensemble on synthetic testbeds from UCI datasets. To do so, we also introduce a method to simulate and a metric to measure discrepancies that occur with shared/common variables. Experiments demonstrate that our framework outperforms the baseline. In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.

Thinking in complexity the complex dynamics of matter, mind, and mankind

CERN Document Server

Mainzer, Klaus

1994-01-01

The theory of nonlinear complex systems has become a successful and widely used problem-solving approach in the natural sciences - from laser physics, quantum chaos and meteorology to molecular modeling in chemistry and computer simulations of cell growth in biology In recent times it has been recognized that many of the social, ecological and political problems of mankind are also of a global, complex and nonlinear nature And one of the most exciting topics of present scientific and public interest is the idea that even the human mind is governed largely by the nonlinear dynamics of complex systems In this wide-ranging but concise treatment Prof Mainzer discusses, in nontechnical language, the common framework behind these endeavours Special emphasis is given to the evolution of new structures in natural and cultural systems and it is seen clearly how the new integrative approach of complexity theory can give new insights that were not available using traditional reductionistic methods

Environmental coupling and population dynamics in the PE545 light-harvesting complex

Energy Technology Data Exchange (ETDEWEB)

Aghtar, Mortaza; Kleinekathöfer, Ulrich, E-mail: u.kleinekathoefer@jacobs-university.de

2016-01-15

Long-lived quantum coherences have been shown experimentally in the Fenna–Matthews–Olson (FMO) complex of green sulfur bacteria as well as in the phycoerythrin 545 (PE545) photosynthetic antenna system of marine algae. A combination of classical molecular dynamics simulations, quantum chemistry and quantum dynamical calculations is employed to determine the excitation transfer dynamics in PE545. One key property of the light-harvesting system concerning the excitation transfer and dephasing phenomena is the spectral density. This quantity is determined from time series of the vertical excitation energies of the aggregate. In the present study we focus on the quantum dynamical simulations using the earlier QM/MM calculations as input. Employing an ensemble-averaged classical path-based wave packet dynamics, the excitation transfer dynamics between the different bilins in the PE545 complex is determined and analyzed. Furthermore, the nature of the environmental fluctuations determining the transfer dynamics is discussed. - Highlights: • Modeling of excitation energy transfer in the light-harvesting system PE545. • Combination of molecular dynamics simulations, quantum chemistry and quantum dynamics. • Spectral densities for bilins in the PE545 complex.

Mathematical Models to Determine Stable Behavior of Complex Systems

Science.gov (United States)

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.

Optimizing Technology-Oriented Constructional Paramour's of complex dynamic systems

International Nuclear Information System (INIS)

Novak, S.M.

1998-01-01

Creating optimal vibro systems requires sequential solving of a few problems: selecting the basic pattern of dynamic actions, synthesizing the dynamic active systems, optimizing technological, technical, economic and design parameters. This approach is illustrated by an example of a high-efficiency vibro system synthesized for forming building structure components. When using only one single source to excite oscillations, resonance oscillations are imparted to the product to be formed in the horizontal and vertical planes. In order to obtain versatile and dynamically optimized parameters, a factor is introduced into the differential equations of the motion, accounting for the relationship between the parameters, which determine the frequency characteristics of the system and the parameter variation range. This results in obtaining non-sophisticated mathematical models of the system under investigation, convenient for optimization and for engineering design and calculations as well

Complex Hamiltonian Dynamics

CERN Document Server

Bountis, Tassos

2012-01-01

This book introduces and explores modern developments in the well established field of Hamiltonian dynamical systems. It focuses on high degree-of-freedom systems and the transitional regimes between regular and chaotic motion. The role of nonlinear normal modes is highlighted and the importance of low-dimensional tori in the resolution of the famous FPU paradox is emphasized. Novel powerful numerical methods are used to study localization phenomena and distinguish order from strongly and weakly chaotic regimes. The emerging hierarchy of complex structures in such regimes gives rise to particularly long-lived patterns and phenomena called quasi-stationary states, which are explored in particular in the concrete setting of one-dimensional Hamiltonian lattices and physical applications in condensed matter systems.  The self-contained and pedagogical approach is blended with a unique balance between mathematical rigor, physics insights and concrete applications. End of chapter exercises and (more demanding) res...

Lyapunov exponents a tool to explore complex dynamics

CERN Document Server

Pikovsky, Arkady

2016-01-01

Lyapunov exponents lie at the heart of chaos theory, and are widely used in studies of complex dynamics. Utilising a pragmatic, physical approach, this self-contained book provides a comprehensive description of the concept. Beginning with the basic properties and numerical methods, it then guides readers through to the most recent advances in applications to complex systems. Practical algorithms are thoroughly reviewed and their performance is discussed, while a broad set of examples illustrate the wide range of potential applications. The description of various numerical and analytical techniques for the computation of Lyapunov exponents offers an extensive array of tools for the characterization of phenomena such as synchronization, weak and global chaos in low and high-dimensional set-ups, and localization. This text equips readers with all the investigative expertise needed to fully explore the dynamical properties of complex systems, making it ideal for both graduate students and experienced researchers...

Dynamics of multiphase systems with complex microstructure. I. Development of the governing equations through nonequilibrium thermodynamics

NARCIS (Netherlands)

Sagis, L.M.C.; Öttinger, H.C.

2013-01-01

In this paper we present a general model for the dynamic behavior of multiphase systems in which the bulk phases and interfaces have a complex microstructure (for example, immiscible polymer blends with added compatibilizers, or polymer stabilized emulsions with thickening agents dispersed in the

Optimal interdependence enhances the dynamical robustness of complex systems

Science.gov (United States)

Singh, Rishu Kumar; Sinha, Sitabhra

2017-08-01

Although interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more likely to survive over long times. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the global dynamics comprising disjoint sets ("islands") of stable activity.

Modeling Complex Systems

CERN Document Server

Boccara, Nino

2010-01-01

Modeling Complex Systems, 2nd Edition, explores the process of modeling complex systems, providing examples from such diverse fields as ecology, epidemiology, sociology, seismology, and economics. It illustrates how models of complex systems are built and provides indispensable mathematical tools for studying their dynamics. This vital introductory text is useful for advanced undergraduate students in various scientific disciplines, and serves as an important reference book for graduate students and young researchers. This enhanced second edition includes: . -recent research results and bibliographic references -extra footnotes which provide biographical information on cited scientists who have made significant contributions to the field -new and improved worked-out examples to aid a student’s comprehension of the content -exercises to challenge the reader and complement the material Nino Boccara is also the author of Essentials of Mathematica: With Applications to Mathematics and Physics (Springer, 2007).

From globally coupled maps to complex-systems biology

Energy Technology Data Exchange (ETDEWEB)

Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp [Research Center for Complex Systems Biology, Graduate School of Arts and Sciences, The University of Tokyo 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902 (Japan)

2015-09-15

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.

Investigating dynamical complexity in the magnetosphere using various entropy measures

Science.gov (United States)

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

Classroom-oriented research from a complex systems perspective

Directory of Open Access Journals (Sweden)

Diane Larsen-Freeman

2016-09-01

Full Text Available Bringing a complex systems perspective to bear on classroom-oriented research challenges researchers to think differently, seeing the classroom ecology as one dynamic system nested in a hierarchy of such systems at different levels of scale, all of which are spatially and temporally situated. This article begins with an introduction to complex dynamic systems theory, in which challenges to traditional ways of conducting classroom research are interwoven. It concludes with suggestions for research methods that are more consistent with the theory. Research does not become easier when approached from a complex systems perspective, but it has the virtue of reflecting the way the world works.

How complex a dynamical network can be?

International Nuclear Information System (INIS)

Baptista, M.S.; Kakmeni, F. Moukam; Del Magno, Gianluigi; Hussein, M.S.

2011-01-01

Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen; (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes.

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Welch, Gregory Francis [UNC-Chapel Hill/University of Central Florida; Zhang, Jinghe [UNC-Chapel Hill/Virginia Tech

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuities caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.

Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation

Science.gov (United States)

Spaiser, Viktoria; Hedström, Peter; Ranganathan, Shyam; Jansson, Kim; Nordvik, Monica K.; Sumpter, David J. T.

2018-01-01

It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena…

Dynamics of complex quantum systems

CERN Document Server

Akulin, Vladimir M

2014-01-01

This book gathers together a range of similar problems that can be encountered in different fields of modern quantum physics and that have common features with regard to multilevel quantum systems. The main motivation was to examine from a uniform standpoint various models and approaches that have been developed in atomic, molecular, condensed matter, chemical, laser and nuclear physics in various contexts. The book should help senior-level undergraduate, graduate students and researchers putting particular problems in these fields into a broader scientific context and thereby taking advantage of well-established techniques used in adjacent fields. This second edition has been expanded to include substantial new material (e.g. new sections on Dynamic Localization and on Euclidean Random Matrices and new chapters on Entanglement, Open Quantum Systems, and Coherence Protection). It is based on the author’s lectures at the Moscow Institute of Physics and Technology, at the CNRS Aimé Cotton Laboratory, and on ...

Sixth International Conference on Complex Systems

CERN Document Server

Minai, Ali; Bar-Yam, Yaneer; Unifying Themes in Complex Systems

2008-01-01

The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore the common themes and applications of complex systems science. In June 2006, 500 participants convened in Boston for the sixth ICCS, exploring an array of topics, including networks, systems biology, evolution and ecology, nonlinear dynamics and pattern formation, as well as neural, psychological, psycho-social, socio-economic, and global systems. This volume selects 77 papers from over 300 presented at the conference. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex systems science.

Introduction to Focus Issue: Complex network perspectives on flow systems.

Science.gov (United States)

Donner, Reik V; Hernández-García, Emilio; Ser-Giacomi, Enrico

2017-03-01

During the last few years, complex network approaches have demonstrated their great potentials as versatile tools for exploring the structural as well as dynamical properties of dynamical systems from a variety of different fields. Among others, recent successful examples include (i) functional (correlation) network approaches to infer hidden statistical interrelationships between macroscopic regions of the human brain or the Earth's climate system, (ii) Lagrangian flow networks allowing to trace dynamically relevant fluid-flow structures in atmosphere, ocean or, more general, the phase space of complex systems, and (iii) time series networks unveiling fundamental organization principles of dynamical systems. In this spirit, complex network approaches have proven useful for data-driven learning of dynamical processes (like those acting within and between sub-components of the Earth's climate system) that are hidden to other analysis techniques. This Focus Issue presents a collection of contributions addressing the description of flows and associated transport processes from the network point of view and its relationship to other approaches which deal with fluid transport and mixing and/or use complex network techniques.

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

Science.gov (United States)

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.

A probabilistic technique for the assessment of complex dynamic system resilience

Science.gov (United States)

Balchanos, Michael Gregory

In the presence of operational uncertainty, one of the greatest challenges in systems engineering is to ensure system effectiveness, mission capability and survivability for large scale, complex system architectures. Historic events such as the 2003 Northeastern Blackout, and the 2005 Hurricane Katrina, have underlined the great importance of system safety, and survivability. With safety management currently applied on a reactive basis to emerging incidents and risk challenges, there is a paradigm shift from passive, reactive and diagnosis-based approaches to the development of architectures that will autonomously manage safety and survivability through active, proactive and prognosis-based engineering solutions. The shift aims to bring safety considerations early in the engineering design process, in order to reduce retrofitting and additional safety certification costs, increase flexibility in risk management, and essentially make safety be "built-in" the design. As a possible enabling research direction, resilience engineering is an emerging discipline, pertinent to safety management, which offers alternative insights on the design of more safe and survivable system architectures. Conceptually, resilience engineering brings new perspectives on the understanding of system safety, accidents, failures, performance degradations and risk. A resilient system can "absorb" the impact of change due to unexpected disturbances, while it "adapts" to change, in order to maintain the system's physical integrity and capability to carry on with its mission. The leading hypothesis advocates that if a complex dynamic system is more resilient, then it would be more survivable, thus more effective, despite the unexpected disturbances that could affect its normal operating conditions. For investigating the impact of more resilient systems on survivability and safety, a framework for theoretical resilience estimations has been formulated. It constitutes the basis for quantitative

Return-to-Work Within a Complex and Dynamic Organizational Work Disability System.

Science.gov (United States)

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

2016-09-01

Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, and frontline supervisors and workers participated in model building sessions. Participants were asked questions that elicited information about the structure of the work disability system and were translated into feedback loops. To parameterize the model, participants were asked to estimate the shape and magnitude of the relationship between key model components. Data from published literature were also accessed to supplement participant estimates. Data were entered into a model created in the software program Vensim. Simulations were conducted to examine how financial incentives and light duty work disability-related policies, utilized by the participating companies, influenced RTW likelihood and preparedness. Results The SDMs were multidimensional, including individual attitudinal characteristics, health factors, and organizational components. Among the causal pathways uncovered, psychosocial components including workplace social support, supervisor and co-worker pressure, and supervisor-frontline worker communication impacted RTW likelihood and preparedness. Interestingly, SDM simulations showed that work disability-related policies in both companies resulted in a diminishing or opposing impact on RTW preparedness and likelihood. Conclusion SDM provides a novel systems view of RTW. Policy and psychosocial component relationships within the system have important implications for RTW, and may contribute to unanticipated outcomes.

Symbolic dynamics and description of complexity

International Nuclear Information System (INIS)

Hao Bailin.

1992-10-01

Symbolic dynamics provides a general framework to describe complexity of dynamical behaviour. After a discussion of the state of the filed special emphasis will be made on the role of transfer matrix (the Stefan matrix) both in deriving the grammar from known symbolic dynamics and in extracting the rules from experimental data. The block structure of the Stefan matrix may serve as another indicator of complexity of the associated dynamics. (author). 33 refs, 6 figs

Nonlinear Dynamics in Complex Systems Theory and Applications for the Life-, Neuro- and Natural Sciences

CERN Document Server

Fuchs, Armin

2013-01-01

With many areas of science reaching across their boundaries and becoming more and more interdisciplinary, students and researchers in these fields are confronted with techniques and tools not covered by their particular education. Especially in the life- and neurosciences quantitative models based on nonlinear dynamics and complex systems are becoming as frequently implemented as traditional statistical analysis. Unfamiliarity with the terminology and rigorous mathematics may discourage many scientists to adopt these methods for their own work, even though such reluctance in most cases is not justified.This book bridges this gap by introducing the procedures and methods used for analyzing nonlinear dynamical systems. In Part I, the concepts of fixed points, phase space, stability and transitions, among others, are discussed in great detail and implemented on the basis of example elementary systems. Part II is devoted to specific, non-trivial applications: coordination of human limb movement (Haken-Kelso-Bunz ...

NATO Advanced Research Workshop on Recent advances in Nonlinear Dynamics and Complex System Physics

CERN Document Server

Casati, Giulio; Complex Phenomena in Nanoscale Systems

2009-01-01

Nanoscale physics has become one of the rapidly developing areas of contemporary physics because of its direct relevance to newly emerging area, nanotechnologies. Nanoscale devices and quantum functional materials are usually constructed based on the results of fundamental studies on nanoscale physics. Therefore studying physical phenomena in nanosized systems is of importance for progressive development of nanotechnologies. In this context study of complex phenomena in such systems and using them for controlling purposes is of great practical importance. Namely, such studies are brought together in this book, which contains 27 papers on various aspects of nanoscale physics and nonlinear dynamics.

Autonomous Collision-Free Navigation of Microvehicles in Complex and Dynamically Changing Environments.

Science.gov (United States)

Li, Tianlong; Chang, Xiaocong; Wu, Zhiguang; Li, Jinxing; Shao, Guangbin; Deng, Xinghong; Qiu, Jianbin; Guo, Bin; Zhang, Guangyu; He, Qiang; Li, Longqiu; Wang, Joseph

2017-09-26

Self-propelled micro- and nanoscale robots represent a rapidly emerging and fascinating robotics research area. However, designing autonomous and adaptive control systems for operating micro/nanorobotics in complex and dynamically changing environments, which is a highly demanding feature, is still an unmet challenge. Here we describe a smart microvehicle for precise autonomous navigation in complicated environments and traffic scenarios. The fully autonomous navigation system of the smart microvehicle is composed of a microscope-coupled CCD camera, an artificial intelligence planner, and a magnetic field generator. The microscope-coupled CCD camera provides real-time localization of the chemically powered Janus microsphere vehicle and environmental detection for path planning to generate optimal collision-free routes, while the moving direction of the microrobot toward a reference position is determined by the external electromagnetic torque. Real-time object detection offers adaptive path planning in response to dynamically changing environments. We demonstrate that the autonomous navigation system can guide the vehicle movement in complex patterns, in the presence of dynamically changing obstacles, and in complex biological environments. Such a navigation system for micro/nanoscale vehicles, relying on vision-based close-loop control and path planning, is highly promising for their autonomous operation in complex dynamic settings and unpredictable scenarios expected in a variety of realistic nanoscale scenarios.

Dynamic complexity: plant receptor complexes at the plasma membrane.

Science.gov (United States)

Burkart, Rebecca C; Stahl, Yvonne

2017-12-01

Plant receptor complexes at the cell surface perceive many different external and internal signalling molecules and relay these signals into the cell to regulate development, growth and immunity. Recent progress in the analyses of receptor complexes using different live cell imaging approaches have shown that receptor complex formation and composition are dynamic and take place at specific microdomains at the plasma membrane. In this review we focus on three prominent examples of Arabidopsis thaliana receptor complexes and how their dynamic spatio-temporal distribution at the PM has been studied recently. We will elaborate on the newly emerging concept of plasma membrane microdomains as potential hubs for specific receptor complex assembly and signalling outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Emergent nested systems a theory of understanding and influencing complex systems as well as case studies in urban systems

CERN Document Server

Walloth, Christian

2016-01-01

This book presents a theory as well as methods to understand and to purposively influence complex systems. It suggests a theory of complex systems as nested systems, i. e. systems that enclose other systems and that are simultaneously enclosed by even other systems. According to the theory presented, each enclosing system emerges through time from the generative activities of the systems they enclose. Systems are nested and often emerge unplanned, and every system of high dynamics is enclosed by a system of slower dynamics. An understanding of systems with faster dynamics, which are always guided by systems of slower dynamics, opens up not only new ways to understanding systems, but also to effectively influence them. The aim and subject of this book is to lay out these thoughts and explain their relevance to the purposive development of complex systems, which are exemplified in case studies from an urban system. The interested reader, who is not required to be familiar with system-theoretical concepts or wit...

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

International Nuclear Information System (INIS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-01-01

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli

2015-06-12

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.

Controller Design of Complex System Based on Nonlinear Strength

Directory of Open Access Journals (Sweden)

Rongjun Mu

2015-01-01

Full Text Available This paper presents a new idea of controller design for complex systems. The nonlinearity index method was first developed for error propagation of nonlinear system. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of the system model. The algorithm of nonlinearity index according to engineering application is first proposed in this paper. Applying this method on nonlinear systems is an effective way to measure the nonlinear strength of dynamics model over the full flight envelope. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of system model. According to the different nonlinear strength of dynamical model, the control system is designed. The simulation time of dynamical complex system is selected by the maximum value of dynamic nonlinearity indices. Take a missile as example; dynamical system and control characteristic of missile are simulated. The simulation results show that the method is correct and appropriate.

Generic features of the dynamics of complex open quantum systems: statistical approach based on averages over the unitary group.

Science.gov (United States)

Gessner, Manuel; Breuer, Heinz-Peter

2013-04-01

We obtain exact analytic expressions for a class of functions expressed as integrals over the Haar measure of the unitary group in d dimensions. Based on these general mathematical results, we investigate generic dynamical properties of complex open quantum systems, employing arguments from ensemble theory. We further generalize these results to arbitrary eigenvalue distributions, allowing a detailed comparison of typical regular and chaotic systems with the help of concepts from random matrix theory. To illustrate the physical relevance and the general applicability of our results we present a series of examples related to the fields of open quantum systems and nonequilibrium quantum thermodynamics. These include the effect of initial correlations, the average quantum dynamical maps, the generic dynamics of system-environment pure state entanglement and, finally, the equilibration of generic open and closed quantum systems.

Complex dynamics

CERN Document Server

Carleson, Lennart

1993-01-01

Complex dynamics is today very much a focus of interest. Though several fine expository articles were available, by P. Blanchard and by M. Yu. Lyubich in particular, until recently there was no single source where students could find the material with proofs. For anyone in our position, gathering and organizing the material required a great deal of work going through preprints and papers and in some cases even finding a proof. We hope that the results of our efforts will be of help to others who plan to learn about complex dynamics and perhaps even lecture. Meanwhile books in the field a. re beginning to appear. The Stony Brook course notes of J. Milnor were particularly welcome and useful. Still we hope that our special emphasis on the analytic side will satisfy a need. This book is a revised and expanded version of notes based on lectures of the first author at UCLA over several \\Vinter Quarters, particularly 1986 and 1990. We owe Chris Bishop a great deal of gratitude for supervising the production of cour...

System dynamics modelling of situation awareness

CSIR Research Space (South Africa)

Oosthuizen, R

2015-11-01

Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...

A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

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Tinggui Chen

2013-01-01

Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

"COUPLED PROCESSES" AS DYNAMIC CAPABILITIES IN SYSTEMS INTEGRATION

OpenAIRE

Chagas Jr, Milton de Freitas; Leite, Dinah Eluze Sales; Jesus, Gabriel Torres de

2017-01-01

ABSTRACT The dynamics of innovation in complex systems industries is becoming an independent research stream. Apart from conventional uncertainties related to commerce and technology, complex-system industries must cope with systemic uncertainty. This paper's objective is to analyze evolving technological paths from one product generation to the next through two case studies in the Brazilian aerospace industry, considering systems integration as an empirical instantiation of dynamic capabilit...

RG-Whitham dynamics and complex Hamiltonian systems

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A. Gorsky

2015-06-01

Full Text Available Inspired by the Seiberg–Witten exact solution, we consider some aspects of the Hamiltonian dynamics with the complexified phase space focusing at the renormalization group (RG-like Whitham behavior. We show that at the Argyres–Douglas (AD point the number of degrees of freedom in Hamiltonian system effectively reduces and argue that anomalous dimensions at AD point coincide with the Berry indexes in classical mechanics. In the framework of Whitham dynamics AD point turns out to be a fixed point. We demonstrate that recently discovered Dunne–Ünsal relation in quantum mechanics relevant for the exact quantization condition exactly coincides with the Whitham equation of motion in the Ω-deformed theory.

Complex dynamics analysis of impulsively coupled Duffing oscillators with ring structure

International Nuclear Information System (INIS)

Jiang Hai-Bo; Zhang Li-Ping; Yu Jian-Jiang

2015-01-01

Impulsively coupled systems are high-dimensional non-smooth systems that can exhibit rich and complex dynamics. This paper studies the complex dynamics of a non-smooth system which is unidirectionally impulsively coupled by three Duffing oscillators in a ring structure. By constructing a proper Poincaré map of the non-smooth system, an analytical expression of the Jacobian matrix of Poincaré map is given. Two-parameter Hopf bifurcation sets are obtained by combining the shooting method and the Runge–Kutta method. When the period is fixed and the coupling strength changes, the system undergoes stable, periodic, quasi-periodic, and hyper-chaotic solutions, etc. Floquet theory is used to study the stability of the periodic solutions of the system and their bifurcations. (paper)

Complex dynamical invariants for two-dimensional complex potentials

Indian Academy of Sciences (India)

Abstract. Complex dynamical invariants are searched out for two-dimensional complex poten- tials using rationalization method within the framework of an extended complex phase space characterized by x = x1 + ip3, y = x2 + ip4, px = p1 + ix3, py = p2 + ix4. It is found that the cubic oscillator and shifted harmonic oscillator ...

An Axiomatic Representation of System Dynamics

CERN Document Server

Baianu, I

2004-01-01

An axiomatic representation of system dynamics is introduced in terms of categories, functors, organismal supercategories, limits and colimits of diagrams. Specific examples are considered in Complex Systems Biology, such as ribosome biogenesis and Hormonal Control in human subjects. "Fuzzy" Relational Structures are also proposed for flexible representations of biological system dynamics and organization.

Intensity approximation of random fluctuation in complex systems

Science.gov (United States)

Yulmetyev, R. M.; Gafarov, F. M.; Yulmetyeva, D. G.; Emeljanova, N. A.

2002-01-01

The Markov and non-Markov processes in complex systems are examined with the help of dynamical information Shannon entropy method. Here we consider the essential role of two mutually independent channels of entropy involving creation of correlation and annihilation of correlation. The developed method has been used to analyze the intensity fluctuation of the complex systems of various nature: in psychology (to analyze numerical and pattern short-time human memory, to study the effect of stress on the parameters of the dynamical taping-test) and in cardiology (to analyze the random dynamics of RR-intervals in human ECG's and to diagnose various diseases of human cardiovascular systems). The received results show that the application of intensity approximation allows to improve essentially the diagnostics of parameters in the evolution of human dynamic states.

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

Science.gov (United States)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

Complex Dynamic Systems View on Conceptual Change: How a Picture of Students' Intuitive Conceptions Accrue from Dynamically Robust Task Dependent Learning Outcomes

Science.gov (United States)

Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji

2017-01-01

We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…

Polyacrylic acids–bovine serum albumin complexation: Structure and dynamics

International Nuclear Information System (INIS)

Othman, Mohamed; Aschi, Adel; Gharbi, Abdelhafidh

2016-01-01

The study of the mixture of BSA with polyacrylic acids at different masses versus pH allowed highlighting the existence of two regimes of weak and strong complexation. These complexes were studied in diluted regime concentration, by turbidimetry, dynamic light scattering (DLS), zeta-potential measurements and nuclear magnetic resonance (NMR). We have followed the pH effect on the structure and properties of the complex. This allowed refining the interpretation of the phase diagram and understanding the observed phenomena. The NMR measurements allowed probing the dynamics of the constituents versus the pH. The computational method was used to precisely determine the electrostatic potential of BSA and how the polyelectrolyte binds to it at different pH. - Highlights: • Influence of physico-chemical parameters on the electrostatic interactions in the complex system (polyelectrolyte/protein). • Stabilization and encapsulation of biological macromolecules solution by mean of polyelectrolyte. • Properties and structure of mixture obtained by screening the charges of globular protein and at different masses of polyacrylic acids. • Dynamic of the constituents formed by complexes particles. • Evaluation of the electrostatic properties of bovine serum albumin versus pH through solution of the Poisson-Boltzmann equation.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

Science.gov (United States)

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.

Topology Detection for Output-Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Directory of Open Access Journals (Sweden)

Xinwei Wang

2017-01-01

Full Text Available Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle’s invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.

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

Science.gov (United States)

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.

Fourth International Conference on Complex Systems

CERN Document Server

Minai, Ali A; Unifying Themes in Complex Systems IV

2008-01-01

In June of 2002, over 500 professors, students and researchers met in Boston, Massachusetts for the Fourth International Conference on Complex Systems. The attendees represented a remarkably diverse collection of fields: biology, ecology, physics, engineering, computer science, economics, psychology and sociology, The goal of the conference was to encourage cross-fertilization between the many disciplines represented and to deepen understanding of the properties common to all complex systems. This volume contains 43 papers selected from the more than 200 presented at the conference. Topics include: cellular automata, neurology, evolution, computer science, network dynamics, and urban planning. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex sys...

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

Science.gov (United States)

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

Complex Time-Delay Systems Theory and Applications

CERN Document Server

Atay, Fatihcan M

2010-01-01

Time delays in dynamical systems arise as an inevitable consequence of finite speeds of information transmission. Realistic models increasingly demand the inclusion of delays in order to properly understand, analyze, design, and control real-life systems. The goal of this book is to present the state-of-the-art in research on time-delay dynamics in the framework of complex systems and networks. While the mathematical theory of delay equations is quite mature, its application to the particular problems of complex systems and complexity is a newly emerging field, and the present volume aims to play a pioneering role in this perspective. The chapters in this volume are authored by renowned experts and cover both theory and applications in a wide range of fields, with examples extending from neuroscience and biology to laser physics and vehicle traffic. Furthermore, all chapters include sufficient introductory material and extensive bibliographies, making the book a self-contained reference for both students and ...

Coupled disease-behavior dynamics on complex networks: A review

Science.gov (United States)

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.

Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

Directory of Open Access Journals (Sweden)

Jose P. Perez

2014-01-01

Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.

Pinning Synchronization of Switched Complex Dynamical Networks

Directory of Open Access Journals (Sweden)

Liming Du

2015-01-01

Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

“Coupled processes” as dynamic capabilities in systems integration

Directory of Open Access Journals (Sweden)

Milton de Freitas Chagas Jr.

2017-05-01

Full Text Available The dynamics of innovation in complex systems industries is becoming an independent research stream. Apart from conventional uncertainties related to commerce and technology, complex-system industries must cope with systemic uncertainty. This paper’s objective is to analyze evolving technological paths from one product generation to the next through two case studies in the Brazilian aerospace indus­try, considering systems integration as an empirical instantiation of dynamic capabilities. A proposed “coupled processes” model intertwines two organizational processes regarded as two levels of dynamic capabilities: new product and technological developments. The model addresses the role of emergent properties in shaping a firm’s technological base. Moreover, it uses a technology readiness level to unveil systems integration business tricks and as a decision-making yardstick. The “coupled processes” model is revealed as a set of dynamic capabilities presenting ambidexterity in complex systems indus­tries, a finding that may be relevant for newly industrialized economies.

Persistent topological features of dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia); Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Rajković, Milan, E-mail: milanr@vinca.rs [Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia)

2016-05-15

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 examined 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.

Symmetric and Asymmetric Tendencies in Stable Complex Systems.

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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.

Dynamic Systems Modeling in Educational System Design & Policy

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Groff, Jennifer Sterling

2013-01-01

Over the last several hundred years, local and national educational systems have evolved from relatively simple systems to incredibly complex, interdependent, policy-laden structures, to which many question their value, effectiveness, and direction they are headed. System Dynamics is a field of analysis used to guide policy and system design in…

Evolution of complex dynamics

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Wilds, Roy; Kauffman, Stuart A.; Glass, Leon

2008-09-01

We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.

Evaluating the effect of smoking cessation treatment on a complex dynamical system.

Science.gov (United States)

Bekiroglu, Korkut; Russell, Michael A; Lagoa, Constantino M; Lanza, Stephanie T; Piper, Megan E

2017-11-01

To understand the dynamic relations among tobacco withdrawal symptoms to inform the development of effective smoking cessation treatments. Dynamical system models from control engineering are introduced and utilized to evaluate complex treatment effects. We demonstrate how dynamical models can be used to examine how distinct withdrawal-related processes are related over time and how treatment influences these relations. Intensive longitudinal data from a randomized placebo-controlled smoking cessation trial (N=1504) are used to estimate a dynamical model of withdrawal-related processes including momentary craving, negative affect, quitting self-efficacy, and cessation fatigue for each of six treatment conditions (nicotine patch, nicotine lozenge, bupropion, patch + lozenge, bupropion + lozenge, and placebo). Estimation and simulation results show that (1) withdrawal measurements are interrelated over time, (2) nicotine patch + nicotine lozenge showed reduced cessation fatigue and enhanced self-efficacy in the long-term while bupropion + nicotine lozenge was more effective at reducing negative affect and craving, and (3) although nicotine patch + nicotine lozenge had a better initial effect on cessation fatigue and self-efficacy, nicotine lozenge had a stronger effect on negative affect and nicotine patch had a stronger impact on craving. This approach can be used to provide new evidence illustrating (a) the total impact of treatment conditions (via steady state values) and (b) the total initial impact (via rate of initial change values) on smoking-related outcomes for separate treatment conditions, noting that the conditions that produce the largest change may be different than the conditions that produce the fastest change. Copyright © 2017 Elsevier B.V. All rights reserved.

Stability of rotor systems: A complex modelling approach

DEFF Research Database (Denmark)

Kliem, Wolfhard; Pommer, Christian; Stoustrup, Jakob

1998-01-01

The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...... approach applying bounds of appropriate Rayleigh quotients. The rotor systems tested are: a simple Laval rotor, a Laval rotor with additional elasticity and damping in the bearings, and a number of rotor systems with complex symmetric 4 x 4 randomly generated matrices.......The dynamics of a large class of rotor systems can be modelled by a linearized complex matrix differential equation of second order, Mz + (D + iG)(z) over dot + (K + iN)z = 0, where the system matrices M, D, G, K and N are real symmetric. Moreover M and K are assumed to be positive definite and D...

Complex Human Dynamics From Mind to Societies

CERN Document Server

Winkowska-Nowak, Katarzyna; Brée, David

2013-01-01

This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".

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

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Reza Kalantari

2017-10-01

Full Text Available 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, McNamara, Louwerse, & Cai, 2004; McNamara & Graesser, 2012, three Lexical Complexity Analyzer indices (Lu, 2010, 2012; Lu & Ai, 2011, and four Vocabprofile indices (Cobb, 2000 were selected to measure different dimensions of LC. Results of repeated measures analysis of variance (RM ANOVA indicated an improvement with regard to only lexical sophistication. Positive and significant relationships were found between time and mean values in Academic Word List and Beyond-2000 as indicators of lexical sophistication. The remaining seven indices of LC, falling short of significance, tended to flatten over the course of this writing program. Correlation analyses among LC indices indicated that lexical density enjoyed positive correlations with lexical sophistication. However, lexical diversity revealed no significant correlations with both lexical density and lexical sophistication. This study suggests that DST perspective specifies a viable foundation for analyzing lexical complexity

Spreading dynamics on complex networks: a general stochastic approach.

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

2014-12-01

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.

ŽAMPA’S SYSTEMS THEORY: A COMPREHENSIVE THEORY OF MEASUREMENT IN DYNAMIC SYSTEMS

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Renata Rychtáriková

2018-04-01

Full Text Available The article outlines in memoriam Prof. Pavel Žampa’s concepts of system theory which enable us to devise a measurement in dynamic systems independently of the particular system behaviour. From the point of view of Žampa’s theory, terms like system time, system attributes, system link, system element, input, output, sub-systems, and state variables are defined. In Conclusions, Žampa’s theory is discussed together with another mathematical approaches of qualitative dynamics known since the 19th century. In Appendices, we present applications of Žampa’s technical approach to measurement of complex dynamical (chemical and biological systems at the Institute of Complex Systems, University of South Bohemia in České Budějovice.

Classification of time series patterns from complex dynamic systems

Energy Technology Data Exchange (ETDEWEB)

Schryver, J.C.; Rao, N.

1998-07-01

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

Random complex dynamics and devil's coliseums

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Sumi, Hiroki

2015-04-01

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

Harm reduction as a complex adaptive system: A dynamic framework for analyzing Tanzanian policies concerning heroin use.

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Ratliff, Eric A; Kaduri, Pamela; Masao, Frank; Mbwambo, Jessie K K; McCurdy, Sheryl A

2016-04-01

Contrary to popular belief, policies on drug use are not always based on scientific evidence or composed in a rational manner. Rather, decisions concerning drug policies reflect the negotiation of actors' ambitions, values, and facts as they organize in different ways around the perceived problems associated with illicit drug use. Drug policy is thus best represented as a complex adaptive system (CAS) that is dynamic, self-organizing, and coevolving. In this analysis, we use a CAS framework to examine how harm reduction emerged around heroin trafficking and use in Tanzania over the past thirty years (1985-present). This account is an organizational ethnography based on of the observant participation of the authors as actors within this system. We review the dynamic history and self-organizing nature of harm reduction, noting how interactions among system actors and components have coevolved with patterns of heroin us, policing, and treatment activities over time. Using a CAS framework, we describe harm reduction as a complex process where ambitions, values, facts, and technologies interact in the Tanzanian sociopolitical environment. We review the dynamic history and self-organizing nature of heroin policies, noting how the interactions within and between competing prohibitionist and harm reduction policies have changed with patterns of heroin use, policing, and treatment activities over time. Actors learn from their experiences to organize with other actors, align their values and facts, and implement new policies. Using a CAS approach provides researchers and policy actors a better understanding of patterns and intricacies in drug policy. This knowledge of how the system works can help improve the policy process through adaptive action to introduce new actors, different ideas, and avenues for communication into the system. Copyright © 2015 Elsevier B.V. All rights reserved.

Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values

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Storey, Brian; Butler, Joy

2013-01-01

Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title "complexity thinking"…

Synchronization criterion for Lur'e type complex dynamical networks with time-varying delay

International Nuclear Information System (INIS)

Ji, D.H.; Park, Ju H.; Yoo, W.J.; Won, S.C.; Lee, S.M.

2010-01-01

In this Letter, the synchronization problem for a class of complex dynamical networks in which every identical node is a Lur'e system with time-varying delay is considered. A delay-dependent synchronization criterion is derived for the synchronization of complex dynamical network that represented by Lur'e system with sector restricted nonlinearities. The derived criterion is a sufficient condition for absolute stability of error dynamics between the each nodes and the isolated node. Using a convex representation of the nonlinearity for error dynamics, the stability condition based on the discretized Lyapunov-Krasovskii functional is obtained via LMI formulation. The proposed delay-dependent synchronization criterion is less conservative than the existing ones. The effectiveness of our work is verified through numerical examples.

Metrical and dynamical aspects in complex analysis

CERN Document Server

2017-01-01

The central theme of this reference book is the metric geometry of complex analysis in several variables. Bridging a gap in the current literature, the text focuses on the fine behavior of the Kobayashi metric of complex manifolds and its relationships to dynamical systems, hyperbolicity in the sense of Gromov and operator theory, all very active areas of research. The modern points of view expressed in these notes, collected here for the first time, will be of interest to academics working in the fields of several complex variables and metric geometry. The different topics are treated coherently and include expository presentations of the relevant tools, techniques and objects, which will be particularly useful for graduate and PhD students specializing in the area.

Application of System Dynamics Methodology in Population Analysis

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August Turina

2009-09-01

Full Text Available The goal of this work is to present the application of system dynamics and system thinking, as well as the advantages and possible defects of this analytic approach, in order to improve the analysis of complex systems such as population and, thereby, to monitor more effectively the underlying causes of migrations. This methodology has long been present in interdisciplinary scientific circles, but its scientific contribution has not been sufficiently applied in analysis practice in Croatia. Namely, the major part of system analysis is focused on detailed complexity rather than on dynamic complexity. Generally, the science of complexity deals with emergence, innovation, learning and adaptation. Complexity is viewed according to the number of system components, or through a number of combinations that must be continually analyzed in order to understand and consequently provide adequate decisions. Simulations containing thousands of variables and complex arrays of details distract overall attention from the basic cause patterns and key inter-relations emerging and prevailing within an analyzed population. Systems thinking offers a holistic and integral perspective for observation of the world.

Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

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Cerbino, Roberto; Cicuta, Pietro

2017-09-01

Differential dynamic microscopy (DDM) is a technique that exploits optical microscopy to obtain local, multi-scale quantitative information about dynamic samples, in most cases without user intervention. It is proving extremely useful in understanding dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of light scattering techniques. Compared to light scattering, DDM offers obvious advantages, principally (a) simplicity of the setup; (b) possibility of removing static contributions along the optical path; (c) power of simultaneous different microscopy contrast mechanisms; and (d) flexibility of choosing an analysis region, analogous to a scattering volume. For many questions, DDM has also advantages compared to segmentation/tracking approaches and to correlation techniques like particle image velocimetry. The very straightforward DDM approach, originally demonstrated with bright field microscopy of aqueous colloids, has lately been used to probe a variety of other complex fluids and biological systems with many different imaging methods, including dark-field, differential interference contrast, wide-field, light-sheet, and confocal microscopy. The number of adopting groups is rapidly increasing and so are the applications. Here, we briefly recall the working principles of DDM, we highlight its advantages and limitations, we outline recent experimental breakthroughs, and we provide a perspective on future challenges and directions. DDM can become a standard primary tool in every laboratory equipped with a microscope, at the very least as a first bias-free automated evaluation of the dynamics in a system.

Workshop on Nonlinear Phenomena in Complex Systems

CERN Document Server

1989-01-01

This book contains a thorough treatment of neural networks, cellular-automata and synergetics, in an attempt to provide three different approaches to nonlinear phenomena in complex systems. These topics are of major interest to physicists active in the fields of statistical mechanics and dynamical systems. They have been developed with a high degree of sophistication and include the refinements necessary to work with the complexity of real systems as well as the more recent research developments in these areas.

From microscopic to macroscopic sports injuries. Applying the complex dynamic systems approach to sports medicine: a narrative review.

Science.gov (United States)

Pol, Rafel; Hristovski, Robert; Medina, Daniel; Balague, Natalia

2018-04-19

A better understanding of how sports injuries occur in order to improve their prevention is needed for medical, economic, scientific and sports success reasons. This narrative review aims to explain the mechanisms that underlie the occurrence of sports injuries, and an innovative approach for their prevention on the basis of complex dynamic systems approach. First, we explain the multilevel organisation of living systems and how function of the musculoskeletal system may be impaired. Second, we use both, a constraints approach and a connectivity hypothesis to explain why and how the susceptibility to sports injuries may suddenly increase. Constraints acting at multiple levels and timescales replace the static and linear concept of risk factors, and the connectivity hypothesis brings an understanding of how the accumulation of microinjuries creates a macroscopic non-linear effect, that is, how a common motor action may trigger a severe injury. Finally, a recap of practical examples and challenges for the future illustrates how the complex dynamic systems standpoint, changing the way of thinking about sports injuries, offers innovative ideas for improving sports injury prevention. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Evaluating system behavior through Dynamic Master Logic Diagram (DMLD) modeling

International Nuclear Information System (INIS)

Hu, Y.-S.; Modarres, Mohammad

1999-01-01

In this paper, the Dynamic Master Logic Diagram (DMLD) is introduced for representing full-scale time-dependent behavior and uncertain behavior of complex physical systems. Conceptually, the DMLD allows one to decompose a complex system hierarchically to model and to represent: (1) partial success/failure of the system, (2) full-scale logical, physical and fuzzy connectivity relations, (3) probabilistic, resolutional or linguistic uncertainty, (4) multiple-state system dynamics, and (5) floating threshold and transition effects. To demonstrate the technique, examples of using DMLD to model, to diagnose and to control dynamic behavior of a system are presented. A DMLD-based expert system building tool, called Dynamic Reliability Expert System (DREXs), is introduced to automate the DMLD modeling process

Dynamic and interacting complex networks

Science.gov (United States)

Dickison, Mark E.

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

Study of spatially extended dynamical systems using probabilistic cellular automata

International Nuclear Information System (INIS)

Vanag, Vladimir K

1999-01-01

Spatially extended dynamical systems are ubiquitous and include such things as insect and animal populations; complex chemical, technological, and geochemical processes; humanity itself, and much more. It is clearly desirable to have a certain universal tool with which the highly complex behaviour of nonlinear dynamical systems can be analyzed and modelled. For this purpose, cellular automata seem to be good candidates. In the present review, emphasis is placed on the possibilities that various types of probabilistic cellular automata (PCA), such as DSMC (direct simulation Monte Carlo) and LGCA (lattice-gas cellular automata), offer. The methods are primarily designed for modelling spatially extended dynamical systems with inner fluctuations accounted for. For the Willamowskii-Roessler and Oregonator models, PCA applications to the following problems are illustrated: the effect of fluctuations on the dynamics of nonlinear systems; Turing structure formation; the effect of hydrodynamic modes on the behaviour of nonlinear chemical systems (stirring effects); bifurcation changes in the dynamical regimes of complex systems with restricted geometry or low spatial dimension; and the description of chemical systems in microemulsions. (reviews of topical problems)

Emergent Properties in Natural and Artificial Dynamical Systems

CERN Document Server

Aziz-Alaoui, M.A

2006-01-01

An important part of the science of complexity is the study of emergent properties arising through dynamical processes in various types of natural and artificial systems. This is the aim of this book, which is the outcome of a discussion meeting within the first European conference on complex systems. It presents multidisciplinary approaches for getting representations of complex systems and using different methods to extract emergent structures. This carefully edited book studies emergent features such as self organization, synchronization, opening on stability and robustness properties. Invariant techniques are presented which can express global emergent properties in dynamical and in temporal evolution systems. This book demonstrates how artificial systems such as a distributed platform can be used for simulation used to search emergent placement during simulation execution.

Complex dynamics in the development of the first tarsal segment of Drosophila melanogaster

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Juan Nicolas Malagon

2016-09-01

Full Text Available Gene, protein and cell interactions are vital for the development of a multicellular organism. As a result, complexity theory can be a fundamental tool to understand how diverse developmental and evolutionary processes occur. However, in most scientific programs these two fields are separated. In an effort to create a connection between the Evo-devo and complexity science, this article shows how the cell dynamics of epithelia can display behaviours with similar features to complex systems. Here, I propose that these cell dynamics, in addition to control cell density in epithelia, can provide high evolvability to this type of tissue. To achieve this goal, I used a as a systems the development of Drosophila melanogaster front legs. First, I provide an example in which order at the tissue level emerge from apparently random cell dynamics. Then, I show that small modifications in epithelial cellular components can produce highly organized or the opposite random cell dynamics. Therefore, this work shows that a developing epithelium displays signs of complex behaviours and I propose that the feedback between tension and cellular processes are key for understanding how multicellular organisms development and evolve. Such studies may reveal the mechanistic basis of complex processes that bridge several levels of organization.

Failure of large transformation projects from the viewpoint of complex adaptive systems: Management principles for dealing with project dynamics

NARCIS (Netherlands)

Janssen, M.; Voort, H. van der; Veenstra, A.F.E. van

2015-01-01

Many large transformation projects do not result in the outcomes desired or envisioned by the stakeholders. This type of project is characterised by dynamics which are both caused by and result of uncertainties and unexpected behaviour. In this paper a complex adaptive system (CAS) view was adopted

Nonlinear dynamical systems for theory and research in ergonomics.

Science.gov (United States)

Guastello, Stephen J

2017-02-01

Nonlinear dynamical systems (NDS) theory offers new constructs, methods and explanations for phenomena that have in turn produced new paradigms of thinking within several disciplines of the behavioural sciences. This article explores the recent developments of NDS as a paradigm in ergonomics. The exposition includes its basic axioms, the primary constructs from elementary dynamics and so-called complexity theory, an overview of its methods, and growing areas of application within ergonomics. The applications considered here include: psychophysics, iconic displays, control theory, cognitive workload and fatigue, occupational accidents, resilience of systems, team coordination and synchronisation in systems. Although these applications make use of different subsets of NDS constructs, several of them share the general principles of the complex adaptive system. Practitioner Summary: Nonlinear dynamical systems theory reframes problems in ergonomics that involve complex systems as they change over time. The leading applications to date include psychophysics, control theory, cognitive workload and fatigue, biomechanics, occupational accidents, resilience of systems, team coordination and synchronisation of system components.

On modulated complex non-linear dynamical systems

International Nuclear Information System (INIS)

Mahmoud, G.M.; Mohamed, A.A.; Rauh, A.

1999-01-01

This paper is concerned with the development of an approximate analytical method to investigate periodic solutions and their stability in the case of modulated non-linear dynamical systems whose equation of motion is describe. Such differential equations appear, for example, in problems of colliding particle beams in high-energy accelerators or one-mass systems with two or more degrees of freedom, e.g. rotors. The significance of periodic solutions lies on the fact that all non-periodic responses, if convergent, would approach to periodic solutions at the steady-state conditions. The example shows a good agreement between numerical and analytical results for small values of ε. The effect of the periodic modulation on the stability of the 2π-periodic solutions is discussed

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

Directory of Open Access Journals (Sweden)

Xianjun Shen

Full Text Available 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.

Thermodynamic aspects of information transfer in complex dynamical systems

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Cafaro, Carlo; Ali, Sean Alan; Giffin, Adom

2016-02-01

From the Horowitz-Esposito stochastic thermodynamical description of information flows in dynamical systems [J. M. Horowitz and M. Esposito, Phys. Rev. X 4, 031015 (2014), 10.1103/PhysRevX.4.031015], it is known that while the second law of thermodynamics is satisfied by a joint system, the entropic balance for the subsystems is adjusted by a term related to the mutual information exchange rate between the two subsystems. In this article, we present a quantitative discussion of the conceptual link between the Horowitz-Esposito analysis and the Liang-Kleeman work on information transfer between dynamical system components [X. S. Liang and R. Kleeman, Phys. Rev. Lett. 95, 244101 (2005), 10.1103/PhysRevLett.95.244101]. In particular, the entropic balance arguments employed in the two approaches are compared. Notwithstanding all differences between the two formalisms, our work strengthens the Liang-Kleeman heuristic balance reasoning by showing its formal analogy with the recent Horowitz-Esposito thermodynamic balance arguments.

Confluence and convergence: team effectiveness in complex systems.

Science.gov (United States)

Porter-OʼGrady, Tim

2015-01-01

Complex adaptive systems require nursing leadership to rethink organizational work and the viability and effectiveness of teams. Much of emergent thinking about complexity and systems and organizations alter the understanding of the nature and function of teamwork and the configuration and leadership of team effort. Reflecting on basic concepts of complexity and their application to team formation, dynamics, and outcomes lays an important foundation for effectively guiding the strategic activity of systems through the focused tactical action of teams. Basic principles of complexity, their impact on teams, and the fundamental elements of team effectiveness are explored.

The impulsive control synchronization of the drive-response complex system

International Nuclear Information System (INIS)

Zhao Yanhong; Yang Yongqing

2008-01-01

This Letter investigates projective synchronization between the drive system and response complex dynamical system. An impulsive control scheme is adapted to synchronize the drive-response dynamical system to a desired scalar factor. By using the stability theory of the impulsive differential equation, the criteria for the projective synchronization are derived. The feasibility of the impulsive control of the projective synchronization is demonstrated in the drive-response dynamical system

The dynamics of general developmental mechanisms : From Piaget and Vygotsky to dynamic systems models

NARCIS (Netherlands)

van Geert, P

Dynamic systems theory conceives of development as a self-organizational process. Both complexity and order emerge as a product of elementary principles of interaction between components involved in the developmental process. This article presents a dynamic systems model based on a general dual

On the characterization of dynamic supramolecular systems: a general mathematical association model for linear supramolecular copolymers and application on a complex two-component hydrogen-bonding system.

Science.gov (United States)

Odille, Fabrice G J; Jónsson, Stefán; Stjernqvist, Susann; Rydén, Tobias; Wärnmark, Kenneth

2007-01-01

A general mathematical model for the characterization of the dynamic (kinetically labile) association of supramolecular assemblies in solution is presented. It is an extension of the equal K (EK) model by the stringent use of linear algebra to allow for the simultaneous presence of an unlimited number of different units in the resulting assemblies. It allows for the analysis of highly complex dynamic equilibrium systems in solution, including both supramolecular homo- and copolymers without the recourse to extensive approximations, in a field in which other analytical methods are difficult. The derived mathematical methodology makes it possible to analyze dynamic systems such as supramolecular copolymers regarding for instance the degree of polymerization, the distribution of a given monomer in different copolymers as well as its position in an aggregate. It is to date the only general means to characterize weak supramolecular systems. The model was fitted to NMR dilution titration data by using the program Matlab, and a detailed algorithm for the optimization of the different parameters has been developed. The methodology is applied to a case study, a hydrogen-bonded supramolecular system, salen 4+porphyrin 5. The system is formally a two-component system but in reality a three-component system. This results in a complex dynamic system in which all monomers are associated to each other by hydrogen bonding with different association constants, resulting in homo- and copolymers 4n5m as well as cyclic structures 6 and 7, in addition to free 4 and 5. The system was analyzed by extensive NMR dilution titrations at variable temperatures. All chemical shifts observed at different temperatures were used in the fitting to obtain the DeltaH degrees and DeltaS degrees values producing the best global fit. From the derived general mathematical expressions, system 4+5 could be characterized with respect to above-mentioned parameters.

Dynamic coherence in excitonic molecular complexes under various excitation conditions

Energy Technology Data Exchange (ETDEWEB)

Chenu, Aurélia; Malý, Pavel; Mančal, Tomáš, E-mail: mancal@karlov.mff.cuni.cz

2014-08-17

Highlights: • Dynamic coherence does not improve energy transfer efficiency in natural conditions. • Photo-induced quantum jumps are discussed in classical context. • Natural time scale of a light excitation event is identified. • Coherence in FMO complex averages out under excitation by neighboring antenna. • This result is valid even in absence of dissipation. - Abstract: We investigate the relevance of dynamic quantum coherence in the energy transfer efficiency of molecular aggregates. We derive the time evolution of the density matrix for an open quantum system excited by light or by a neighboring antenna. Unlike in the classical case, the quantum description does not allow for a formal decomposition of the dynamics into sudden jumps in an observable quantity – an expectation value. Rather, there is a natural finite time-scale associated with the excitation process. We propose a simple experiment to test the influence of this time scale on the yield of photosynthesis. We demonstrate, using typical parameters of the Fenna–Matthews–Olson (FMO) complex and a typical energy transfer rate from the chlorosome baseplate, that dynamic coherences are averaged out in the complex even when the FMO model is completely free of all dissipation and dephasing.

A review of human factors challenges of complex adaptive systems: discovering and understanding chaos in human performance.

Science.gov (United States)

Karwowski, Waldemar

2012-12-01

In this paper, the author explores a need for a greater understanding of the true nature of human-system interactions from the perspective of the theory of complex adaptive systems, including the essence of complexity, emergent properties of system behavior, nonlinear systems dynamics, and deterministic chaos. Human performance, more often than not, constitutes complex adaptive phenomena with emergent properties that exhibit nonlinear dynamical (chaotic) behaviors. The complexity challenges in the design and management of contemporary work systems, including service systems, are explored. Examples of selected applications of the concepts of nonlinear dynamics to the study of human physical performance are provided. Understanding and applications of the concepts of theory of complex adaptive and dynamical systems should significantly improve the effectiveness of human-centered design efforts of a large system of systems. Performance of many contemporary work systems and environments may be sensitive to the initial conditions and may exhibit dynamic nonlinear properties and chaotic system behaviors. Human-centered design of emergent human-system interactions requires application of the theories of nonlinear dynamics and complex adaptive system. The success of future human-systems integration efforts requires the fusion of paradigms, knowledge, design principles, and methodologies of human factors and ergonomics with those of the science of complex adaptive systems as well as modern systems engineering.

Modeling complex and multi-component food systems in molecular dynamics simulations on the example of chocolate conching.

Science.gov (United States)

Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko

2014-02-01

Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively

Comparing dynamical systems concepts and techniques for biomechanical analysis

Institute of Scientific and Technical Information of China (English)

Richard E.A. van Emmerik; Scott W. Ducharme; Avelino C. Amado; Joseph Hamill

2016-01-01

Traditional biomechanical analyses of human movement are generally derived from linear mathematics. While these methods can be useful in many situations, they do not describe behaviors in human systems that are predominately nonlinear. For this reason, nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature. These analysis techniques have provided new insights into how systems (1) maintain pattern stability, (2) transition into new states, and (3) are governed by short-and long-term (fractal) correlational processes at different spatio-temporal scales. These different aspects of system dynamics are typically investigated using concepts related to variability, stability, complexity, and adaptability. The purpose of this paper is to compare and contrast these different concepts and demonstrate that, although related, these terms represent fundamentally different aspects of system dynamics. In particular, we argue that variability should not uniformly be equated with stability or complexity of movement. In addition, current dynamic stability measures based on nonlinear analysis methods (such as the finite maximal Lyapunov exponent) can reveal local instabilities in movement dynamics, but the degree to which these local instabilities relate to global postural and gait stability and the ability to resist external perturbations remains to be explored. Finally, systematic studies are needed to relate observed reductions in complexity with aging and disease to the adaptive capabilities of the movement system and how complexity changes as a function of different task constraints.

Comparing dynamical systems concepts and techniques for biomechanical analysis

Directory of Open Access Journals (Sweden)

Richard E.A. van Emmerik

2016-03-01

Full Text Available Traditional biomechanical analyses of human movement are generally derived from linear mathematics. While these methods can be useful in many situations, they do not describe behaviors in human systems that are predominately nonlinear. For this reason, nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature. These analysis techniques have provided new insights into how systems (1 maintain pattern stability, (2 transition into new states, and (3 are governed by short- and long-term (fractal correlational processes at different spatio-temporal scales. These different aspects of system dynamics are typically investigated using concepts related to variability, stability, complexity, and adaptability. The purpose of this paper is to compare and contrast these different concepts and demonstrate that, although related, these terms represent fundamentally different aspects of system dynamics. In particular, we argue that variability should not uniformly be equated with stability or complexity of movement. In addition, current dynamic stability measures based on nonlinear analysis methods (such as the finite maximal Lyapunov exponent can reveal local instabilities in movement dynamics, but the degree to which these local instabilities relate to global postural and gait stability and the ability to resist external perturbations remains to be explored. Finally, systematic studies are needed to relate observed reductions in complexity with aging and disease to the adaptive capabilities of the movement system and how complexity changes as a function of different task constraints.

Modeling Stochastic Complexity in Complex Adaptive Systems: Non-Kolmogorov Probability and the Process Algebra Approach.

Science.gov (United States)

Sulis, William H

2017-10-01

Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.

Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

Directory of Open Access Journals (Sweden)

Joshua Rodewald

2016-10-01

Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

Complex dynamics of the generic and brand advertising strategies in duopoly

International Nuclear Information System (INIS)

Qi Jie; Ding Yongsheng; Chen Liang

2008-01-01

By using the optimal profit adjusting strategies, a dynamic advertising competition model in duopoly is extended from Krishnamurthy's static model. Both generic and brand effects for advertising are considered. This model can create complex bifurcating and chaotic behavior for the generic advertising efforts, which lead to chaotic dynamics for the brand advertising and even for the whole system. The asymptotic properties of the symmetric system and the asymmetric system are also investigated, which reflect interactions between the two firms' advertising strategies and relationships between the brand and the generic advertising expenditures

Complex dynamics of the generic and brand advertising strategies in duopoly

Energy Technology Data Exchange (ETDEWEB)

Qi Jie [College of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)], E-mail: jieqi@dhu.edu.cn; Ding Yongsheng [College of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)], E-mail: ysding@dhu.edu.cn; Chen Liang [College of Information Sciences and Technology, Donghua University, Shanghai 200051 (China)

2008-04-15

By using the optimal profit adjusting strategies, a dynamic advertising competition model in duopoly is extended from Krishnamurthy's static model. Both generic and brand effects for advertising are considered. This model can create complex bifurcating and chaotic behavior for the generic advertising efforts, which lead to chaotic dynamics for the brand advertising and even for the whole system. The asymptotic properties of the symmetric system and the asymmetric system are also investigated, which reflect interactions between the two firms' advertising strategies and relationships between the brand and the generic advertising expenditures.

A dynamic predictive maintenance policy for complex multi-component systems

International Nuclear Information System (INIS)

Van Horenbeek, Adriaan; Pintelon, Liliane

2013-01-01

The use of prognostic methods in maintenance in order to predict remaining useful life is receiving more attention over the past years. The use of these techniques in maintenance decision making and optimization in multi-component systems is however a still underexplored area. The objective of this paper is to optimally plan maintenance for a multi-component system based on prognostic/predictive information while considering different component dependencies (i.e. economic, structural and stochastic dependence). Consequently, this paper presents a dynamic predictive maintenance policy for multi-component systems that minimizes the long-term mean maintenance cost per unit time. The proposed maintenance policy is a dynamic method as the maintenance schedule is updated when new information on the degradation and remaining useful life of components becomes available. The performance, regarding the objective of minimal long-term mean cost per unit time, of the developed dynamic predictive maintenance policy is compared to five other conventional maintenance policies, these are: block-based maintenance, age-based maintenance, age-based maintenance with grouping, inspection condition-based maintenance and continuous condition-based maintenance. The ability of the predictive maintenance policy to react to changing component deterioration and dependencies within a multi-component system is quantified and the results show significant cost savings

Complex dynamics of a Holling type II prey-predator system with state feedback control

International Nuclear Information System (INIS)

Jiang Guirong; Lu Qishao; Qian Linning

2007-01-01

The complex dynamics of a Holling type II prey-predator system with impulsive state feedback control is studied in both theoretical and numerical ways. The sufficient conditions for the existence and stability of semi-trivial and positive periodic solutions are obtained by using the Poincare map and the analogue of the Poincare criterion. The qualitative analysis shows that the positive periodic solution bifurcates from the semi-trivial solution through a fold bifurcation. The bifurcation diagrams, Lyapunov exponents, and phase portraits are illustrated by an example, in which the chaotic solutions appear via a cascade of period-doubling bifurcations. The superiority of the state feedback control strategy is also discussed

A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

Science.gov (United States)

Koorehdavoudi, Hana; Bogdan, Paul

2016-06-01

Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

Planning and complexity : Engaging with temporal dynamics, uncertainty and complex adaptive systems

NARCIS (Netherlands)

Sengupta, Ulysses; Rauws, Ward S.; de Roo, Gert

2016-01-01

The nature of complex systems as a transdisciplinary collection of concepts from physics and economics to sociology and ecology provides an evolving field of inquiry (Laszlo and Krippner, 1998) for urban planning and urban design. As a result, planning theory has assimilated multiple concepts from

Planning and complexity : Engaging with temporal dynamics, uncertainty and complex adaptive systems

NARCIS (Netherlands)

Sengupta, Ulysses; Rauws, Ward S.; de Roo, Gert

The nature of complex systems as a transdisciplinary collection of concepts from physics and economics to sociology and ecology provides an evolving field of inquiry (Laszlo and Krippner, 1998) for urban planning and urban design. As a result, planning theory has assimilated multiple concepts from

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

Directory of Open Access Journals (Sweden)

Jianhua Xu

2013-01-01

Full Text Available 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.

Complex network synchronization of chaotic systems with delay coupling

International Nuclear Information System (INIS)

Theesar, S. Jeeva Sathya; Ratnavelu, K.

2014-01-01

The study of complex networks enables us to understand the collective behavior of the interconnected elements and provides vast real time applications from biology to laser dynamics. In this paper, synchronization of complex network of chaotic systems has been studied. Every identical node in the complex network is assumed to be in Lur’e system form. In particular, delayed coupling has been assumed along with identical sector bounded nonlinear systems which are interconnected over network topology

Lattice dynamics and molecular dynamics simulation of complex materials

International Nuclear Information System (INIS)

Chaplot, S.L.

1997-01-01

In this article we briefly review the lattice dynamics and molecular dynamics simulation techniques, as used for complex ionic and molecular solids, and demonstrate a number of applications through examples of our work. These computational studies, along with experiments, have provided microscopic insight into the structure and dynamics, phase transitions and thermodynamical properties of a variety of materials including fullerene, high temperature superconducting oxides and geological minerals as a function of pressure and temperature. The computational techniques also allow the study of the structures and dynamics associated with disorder, defects, surfaces, interfaces etc. (author)

Integration of the immune system: a complex adaptive supersystem

Science.gov (United States)

Crisman, Mark V.

2001-10-01

Immunity to pathogenic organisms is a complex process involving interacting factors within the immune system including circulating cells, tissues and soluble chemical mediators. Both the efficiency and adaptive responses of the immune system in a dynamic, often hostile, environment are essential for maintaining our health and homeostasis. This paper will present a brief review of one of nature's most elegant, complex adaptive systems.

Structure identification and adaptive synchronization of uncertain general complex dynamical networks

International Nuclear Information System (INIS)

Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian

2009-01-01

This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

Structure identification and adaptive synchronization of uncertain general complex dynamical networks

Energy Technology Data Exchange (ETDEWEB)

Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)

2009-12-28

This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.

Complex motions and chaos in nonlinear systems

CERN Document Server

Machado, José; Zhang, Jiazhong

2016-01-01

This book brings together 10 chapters on a new stream of research examining complex phenomena in nonlinear systems—including engineering, physics, and social science. Complex Motions and Chaos in Nonlinear Systems provides readers a particular vantage of the nature and nonlinear phenomena in nonlinear dynamics that can develop the corresponding mathematical theory and apply nonlinear design to practical engineering as well as the study of other complex phenomena including those investigated within social science.

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

Science.gov (United States)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Prediction of the dynamic response of complex transmission line systems for unsteady pressure measurements

International Nuclear Information System (INIS)

Antonini, C; Persico, G; Rowe, A L

2008-01-01

Among the measurement and control systems of gas turbine engines, a recent new issue is the possibility of performing unsteady pressure measurements to detect flow anomalies in an engine or to evaluate loads on aerodynamic surfaces. A possible answer to this demand could be extending the use of well known and widely used transmission line systems, which have been applied so far to steady monitoring, to unsteady measurements thanks to proper dynamic modeling and compensation. Despite the huge number of models existing in the literature, a novel method has been developed, which is at the same time easy-to-handle, flexible and capable of reproducing the actual physics of the problem. Furthermore, the new model is able to deal with arbitrary complex networks of lines and cavities, and thus its applicability is not limited to series-connected systems. The main objectives of this paper are to show the derivation of the model, its validation against experimental tests and example of its applicability

Understanding global health governance as a complex adaptive system.

Science.gov (United States)

Hill, Peter S

2011-01-01

The transition from international to global health reflects the rapid growth in the numbers and nature of stakeholders in health, as well as the constant change embodied in the process of globalisation itself. This paper argues that global health governance shares the characteristics of complex adaptive systems, with its multiple and diverse players, and their polyvalent and constantly evolving relationships, and rich and dynamic interactions. The sheer quantum of initiatives, the multiple networks through which stakeholders (re)configure their influence, the range of contexts in which development for health is played out - all compound the complexity of this system. This paper maps out the characteristics of complex adaptive systems as they apply to global health governance, linking them to developments in the past two decades, and the multiple responses to these changes. Examining global health governance through the frame of complexity theory offers insight into the current dynamics of governance, and while providing a framework for making meaning of the whole, opens up ways of accessing this complexity through local points of engagement.

Seeing the System: Dynamics and Complexity of Technology Integration in Secondary Schools

Science.gov (United States)

Howard, Sarah K.; Thompson, Kate

2016-01-01

This paper introduces system dynamics modeling to understand, visualize and explore technology integration in schools, through the development of a theoretical model of technology-related change in teachers' practice. Technology integration is a dynamic social practice, within the social system of education. It is difficult, if not nearly…

Entropy-based generating Markov partitions for complex systems

Science.gov (United States)

Rubido, Nicolás; Grebogi, Celso; Baptista, Murilo S.

2018-03-01

Finding the correct encoding for a generic dynamical system's trajectory is a complicated task: the symbolic sequence needs to preserve the invariant properties from the system's trajectory. In theory, the solution to this problem is found when a Generating Markov Partition (GMP) is obtained, which is only defined once the unstable and stable manifolds are known with infinite precision and for all times. However, these manifolds usually form highly convoluted Euclidean sets, are a priori unknown, and, as it happens in any real-world experiment, measurements are made with finite resolution and over a finite time-span. The task gets even more complicated if the system is a network composed of interacting dynamical units, namely, a high-dimensional complex system. Here, we tackle this task and solve it by defining a method to approximately construct GMPs for any complex system's finite-resolution and finite-time trajectory. We critically test our method on networks of coupled maps, encoding their trajectories into symbolic sequences. We show that these sequences are optimal because they minimise the information loss and also any spurious information added. Consequently, our method allows us to approximately calculate the invariant probability measures of complex systems from the observed data. Thus, we can efficiently define complexity measures that are applicable to a wide range of complex phenomena, such as the characterisation of brain activity from electroencephalogram signals measured at different brain regions or the characterisation of climate variability from temperature anomalies measured at different Earth regions.

A Memristor-Based Hyperchaotic Complex Lü System and Its Adaptive Complex Generalized Synchronization

Directory of Open Access Journals (Sweden)

Shibing Wang

2016-02-01

Full Text Available This paper introduces a new memristor-based hyperchaotic complex Lü system (MHCLS and investigates its adaptive complex generalized synchronization (ACGS. Firstly, the complex system is constructed based on a memristor-based hyperchaotic real Lü system, and its properties are analyzed theoretically. Secondly, its dynamical behaviors, including hyperchaos, chaos, transient phenomena, as well as periodic behaviors, are explored numerically by means of bifurcation diagrams, Lyapunov exponents, phase portraits, and time history diagrams. Thirdly, an adaptive controller and a parameter estimator are proposed to realize complex generalized synchronization and parameter identification of two identical MHCLSs with unknown parameters based on Lyapunov stability theory. Finally, the numerical simulation results of ACGS and its applications to secure communication are presented to verify the feasibility and effectiveness of the proposed method.

System dynamics and control with bond graph modeling

CERN Document Server

Kypuros, Javier

2013-01-01

Part I Dynamic System ModelingIntroduction to System DynamicsIntroductionSystem Decomposition and Model ComplexityMathematical Modeling of Dynamic SystemsAnalysis and Design of Dynamic SystemsControl of Dynamic SystemsDiagrams of Dynamic SystemsA Graph-Centered Approach to ModelingSummaryPracticeExercisesBasic Bond Graph ElementsIntroductionPower and Energy VariablesBasic 1-Port ElementsBasic 2-Ports ElementsJunction ElementsSimple Bond Graph ExamplesSummaryPracticeExercisesBond Graph Synthesis and Equation DerivationIntroductionGeneral GuidelinesMechanical TranslationMechanical RotationElectrical CircuitsHydraulic CircuitsMixed SystemsState Equation DerivationState-Space RepresentationsAlgebraic Loops and Derivative CausalitySummaryPracticeExercisesImpedance Bond GraphsIntroductionLaplace Transform of the State-Space EquationBasic 1-Port ImpedancesImpedance Bond Graph SynthesisJunctions, Transformers, and GyratorsEffort and Flow DividersSign ChangesTransfer Function DerivationAlternative Derivation of Transf...

Complex Physical, Biophysical and Econophysical Systems

Science.gov (United States)

Dewar, Robert L.; Detering, Frank

1. Introduction to complex and econophysics systems: a navigation map / T. Aste and T. Di Matteo -- 2. An introduction to fractional diffusion / B. I. Henry, T.A.M. Langlands and P. Straka -- 3. Space plasmas and fusion plasmas as complex systems / R. O. Dendy -- 4. Bayesian data analysis / M. S. Wheatland -- 5. Inverse problems and complexity in earth system science / I. G. Enting -- 6. Applied fluid chaos: designing advection with periodically reoriented flows for micro to geophysical mixing and transport enhancement / G. Metcalfe -- 7. Approaches to modelling the dynamical activity of brain function based on the electroencephalogram / D. T. J. Liley and F. Frascoli -- 8. Jaynes' maximum entropy principle, Riemannian metrics and generalised least action bound / R. K. Niven and B. Andresen -- 9. Complexity, post-genomic biology and gene expression programs / R. B. H. Williams and O. J.-H. Luo -- 10. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek / M. J. Berryman and S. D. Angus.

The dynamic complexity of a three species food chain model

International Nuclear Information System (INIS)

Lv Songjuan; Zhao Min

2008-01-01

In this paper, a three-species food chain model is analytically investigated on theories of ecology and using numerical simulation. Bifurcation diagrams are obtained for biologically feasible parameters. The results show that the system exhibits rich complexity features such as stable, periodic and chaotic dynamics

Multi-person tracking with overlapping cameras in complex, dynamic environments

NARCIS (Netherlands)

Liem, M.; Gavrila, D.M.

2009-01-01

This paper presents a multi-camera system to track multiple persons in complex, dynamic environments. Position measurements are obtained by carving out the space defined by foreground regions in the overlapping camera views and projecting these onto blobs on the ground plane. Person appearance is

Recovery time after localized perturbations in complex dynamical networks

International Nuclear Information System (INIS)

Mitra, Chiranjit; Kittel, Tim; Kurths, Jürgen; Donner, Reik V; Choudhary, Anshul

2017-01-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed

Recovery time after localized perturbations in complex dynamical networks

Science.gov (United States)

Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed

Reflecting on complexity of biological systems: Kant and beyond?

Science.gov (United States)

Van de Vijver, Gertrudis; Van Speybroeck, Linda; Vandevyvere, Windy

2003-01-01

Living organisms are currently most often seen as complex dynamical systems that develop and evolve in relation to complex environments. Reflections on the meaning of the complex dynamical nature of living systems show an overwhelming multiplicity in approaches, descriptions, definitions and methodologies. Instead of sustaining an epistemic pluralism, which often functions as a philosophical armistice in which tolerance and so-called neutrality discharge proponents of the burden to clarify the sources and conditions of agreement and disagreement, this paper aims at analysing: (i) what has been Kant's original conceptualisation of living organisms as natural purposes; (ii) how the current perspectives are to be related to Kant's viewpoint; (iii) what are the main trends in current complexity thinking. One of the basic ideas is that the attention for structure and its epistemological consequences witness to a great extent of Kant's viewpoint, and that the idea of organisational stratification today constitutes a different breeding ground within which complexity issues are raised. The various approaches of complexity in biological systems are captured in terms of two different styles, universalism and (weak and strong) constructivism, between which hybrid forms exist.

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

Science.gov (United States)

Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

2011-06-01

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

Metric for Calculation of System Complexity based on its Connections

Directory of Open Access Journals (Sweden)

João Ricardo Braga de Paiva

2017-02-01

Full Text Available This paper proposes a methodology based on system connections to calculate its complexity. Two study cases are proposed: the dining Chinese philosophers’ problem and the distribution center. Both studies are modeled using the theory of Discrete Event Systems and simulations in different contexts were performed in order to measure their complexities. The obtained results present i the static complexity as a limiting factor for the dynamic complexity, ii the lowest cost in terms of complexity for each unit of measure of the system performance and iii the output sensitivity to the input parameters. The associated complexity and performance measures aggregate knowledge about the system.

Complex dynamics and switching transients in periodically forced Filippov prey–predator system

International Nuclear Information System (INIS)

Tang, Guangyao; Qin, Wenjie; Tang, Sanyi

2014-01-01

Highlights: •We develop a Filippov prey–predator model with periodic forcing. •The sliding mode dynamics and its domain have been investigated. •The existence and stability of sliding periodic solution have been discussed. •The complex dynamics are addressed through bifurcation analyses. •Switching transients and their biological implications have been discussed. - Abstract: By employing threshold policy control (TPC) in combination with the definition of integrated pest management (IPM), a Filippov prey–predator model with periodic forcing has been proposed and studied, and the periodic forcing is affected by assuming a periodic variation in the intrinsic growth rate of the prey. This study aims to address how the periodic forcing and TPC affect the pest control. To do this, the sliding mode dynamics and sliding mode domain have been addressed firstly by using Utkin’s equivalent control method, and then the existence and stability of sliding periodic solution are investigated. Furthermore, the complex dynamics including multiple attractors coexistence, period adding sequences and chaotic solutions with respect to bifurcation parameters of forcing amplitude and economic threshold (ET) have been investigated numerically in more detail. Finally the switching transients associated with pest outbreaks and their biological implications have been discussed. Our results indicate that the sliding periodic solution could be globally stable, and consequently the prey or pest population can be controlled such that its density falls below the economic injury level (EIL). Moreover, the switching transients have both advantages and disadvantages concerning pest control, and the magnitude and frequency of switching transients depend on the initial values of both populations, forcing amplitude and ET

Rapid Mission Design for Dynamically Complex Environments

Data.gov (United States)

National Aeronautics and Space Administration — Designing trajectories in dynamically complex environments is very challenging and easily becomes an intractable problem. More complex planning implies potentially...

Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling

International Nuclear Information System (INIS)

Wang Lifu; Kong Zhi; Jing Yuanwei

2010-01-01

This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)

Constraint elimination in dynamical systems

Science.gov (United States)

Singh, R. P.; Likins, P. W.

1989-01-01

Large space structures (LSSs) and other dynamical systems of current interest are often extremely complex assemblies of rigid and flexible bodies subjected to kinematical constraints. A formulation is presented for the governing equations of constrained multibody systems via the application of singular value decomposition (SVD). The resulting equations of motion are shown to be of minimum dimension.

Exploring the dynamic and complex integration of sustainability performance measurement into product development

DEFF Research Database (Denmark)

Rodrigues, Vinicius Picanco; Morioka, S.; Pigosso, Daniela Cristina Antelmi

2016-01-01

In order to deal with the complex and dynamic nature of sustainability integration into the product development process, this research explore the use of a qualitative System Dynamics approach by using the causal loop diagram (CLD) tool. A literature analysis was followed by a case study, aiming ...

Practical synchronization on complex dynamical networks via optimal pinning control

Science.gov (United States)

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

2015-07-01

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

The dynamic complexity of a three-species Beddington-type food chain with impulsive control strategy

International Nuclear Information System (INIS)

Wang Weiming; Wang Hailing; Li Zhenqing

2007-01-01

In this paper, by using theories and methods of ecology and ordinary differential equation, the dynamics complexity of a prey-predator system with Beddington-type functional response and impulsive control strategy is established. Conditions for the system to be extinct are given by using the Floquet theory of impulsive equation and small amplitude perturbation skills. Furthermore, by using the method of numerical simulation with the international software Maple, the influence of the impulsive perturbations on the inherent oscillation is investigated, which shows rich dynamics, such as quasi-periodic oscillation, narrow periodic window, wide periodic window, chaotic bands, period doubling bifurcation, symmetry-breaking pitchfork bifurcation, period-halving bifurcation and crises, etc. The numerical results indicate that computer simulation is a useful method for studying the complex dynamic systems

Complex dynamic in ecological time series

Science.gov (United States)

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...

Plant Phenotyping through the Eyes of Complex Systems: Theoretical Considerations

Science.gov (United States)

Kim, J.

2017-12-01

Plant phenotyping is an emerging transdisciplinary research which necessitates not only the communication and collaboration of scientists from different disciplines but also the paradigm shift to a holistic approach. Complex system is defined as a system having a large number of interacting parts (or particles, agents), whose interactions give rise to non-trivial properties like self-organization and emergence. Plant ecosystems are complex systems which are continually morphing dynamical systems, i.e. self-organizing hierarchical open systems. Such systems are composed of many subunits/subsystems with nonlinear interactions and feedback. The throughput such as the flow of energy, matter and information is the key control parameter in complex systems. Information theoretic approaches can be used to understand and identify such interactions, structures and dynamics through reductions in uncertainty (i.e. entropy). The theoretical considerations based on network and thermodynamic thinking and exemplary analyses (e.g. dynamic process network, spectral entropy) of the throughput time series will be presented. These can be used as a framework to develop more discipline-specific fundamental approaches to provide tools for the transferability of traits between measurement scales in plant phenotyping. Acknowledgment: This work was funded by the Weather Information Service Engine Program of the Korea Meteorological Administration under Grant KMIPA-2012-0001.

Noise-induced temporal dynamics in Turing systems

KAUST Repository

Schumacher, Linus J.; Woolley, Thomas E.; Baker, Ruth E.

2013-01-01

We examine the ability of intrinsic noise to produce complex temporal dynamics in Turing pattern formation systems, with particular emphasis on the Schnakenberg kinetics. Using power spectral methods, we characterize the behavior of the system using

Analysis of Social Network Dynamics with Models from the Theory of Complex Adaptive Systems

OpenAIRE

Lymperopoulos , Ilias; Lekakos , George

2013-01-01

Part 4: Protocols, Regulation and Social Networking; International audience; The understanding and modeling of social dynamics in a complex and unpredictable world, emerges as a research target of particular importance. Success in this direction can yield valuable knowledge as to how social phenomena form and evolve in varying socioeconomic contexts comprising economic crises, societal disasters, cultural differences and security threats among others. The study of social dynamics occurring in...

Traffic Dynamics on Complex Networks: A Survey

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available Traffic dynamics on complex networks are intriguing in recent years due to their practical implications in real communication networks. In this survey, we give a brief review of studies on traffic routing dynamics on complex networks. Strategies for improving transport efficiency, including designing efficient routing strategies and making appropriate adjustments to the underlying network structure, are introduced in this survey. Finally, a few open problems are discussed in this survey.

The nonlinear dynamics of a coupled fission system

International Nuclear Information System (INIS)

Bilanovic, Z.; Harms, A.A.

1993-01-01

The dynamic properties of a nonlinear and in situ vibrationally perturbed nuclear-to-thermal coupled neutron multiplying medium are examined. Some unique self-organizational temporal patterns appear in such fission systems and suggest a complex underlying dynamic. (Author)

XXIII International Conference on Nonlinear Dynamics of Electronic Systems

CERN Document Server

Stoop, Ruedi; Stramaglia, Sebastiano

2017-01-01

This book collects contributions to the XXIII international conference “Nonlinear dynamics of electronic systems”. Topics range from non-linearity in electronic circuits to synchronisation effects in complex networks to biological systems, neural dynamics and the complex organisation of the brain. Resting on a solid mathematical basis, these investigations address highly interdisciplinary problems in physics, engineering, biology and biochemistry.

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

Science.gov (United States)

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…

Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale

CERN Document Server

Stanley, H

2014-01-01

Topics of complex system physics and their interdisciplinary applications to different problems in seismology, biology, economy, sociology,  energy and nanotechnology are covered in this new work from renowned experts in their fields.  In  particular, contributed papers contain original results on network science, earthquake dynamics, econophysics, sociophysics, nanoscience and biological physics. Most of the papers use interdisciplinary approaches based on statistical physics, quantum physics and other topics of complex system physics.  Papers on econophysics and sociophysics are focussed on societal aspects of physics such as, opinion dynamics, public debates and financial and economic stability. This work will be of interest to statistical physicists, economists, biologists, seismologists and all scientists working in interdisciplinary topics of complexity.

Complex systems relationships between control, communications and computing

CERN Document Server

2016-01-01

This book gives a wide-ranging description of the many facets of complex dynamic networks and systems within an infrastructure provided by integrated control and supervision: envisioning, design, experimental exploration, and implementation. The theoretical contributions and the case studies presented can reach control goals beyond those of stabilization and output regulation or even of adaptive control. Reporting on work of the Control of Complex Systems (COSY) research program, Complex Systems follows from and expands upon an earlier collection: Control of Complex Systems by introducing novel theoretical techniques for hard-to-control networks and systems. The major common feature of all the superficially diverse contributions encompassed by this book is that of spotting and exploiting possible areas of mutual reinforcement between control, computing and communications. These help readers to achieve not only robust stable plant system operation but also properties such as collective adaptivity, integrity an...

Operationalizing sustainability in urban coastal systems: a system dynamics analysis.

Science.gov (United States)

Mavrommati, Georgia; Bithas, Kostas; Panayiotidis, Panayiotis

2013-12-15

We propose a system dynamics approach for Ecologically Sustainable Development (ESD) in urban coastal systems. A systematic analysis based on theoretical considerations, policy analysis and experts' knowledge is followed in order to define the concept of ESD. The principles underlying ESD feed the development of a System Dynamics Model (SDM) that connects the pollutant loads produced by urban systems' socioeconomic activities with the ecological condition of the coastal ecosystem that it is delineated in operational terms through key biological elements defined by the EU Water Framework Directive. The receiving waters of the Athens Metropolitan area, which bears the elements of typical high population density Mediterranean coastal city but which currently has also new dynamics induced by the ongoing financial crisis, are used as an experimental system for testing a system dynamics approach to apply the concept of ESD. Systems' thinking is employed to represent the complex relationships among the components of the system. Interconnections and dependencies that determine the potentials for achieving ESD are revealed. The proposed system dynamics analysis can facilitate decision makers to define paths of development that comply with the principles of ESD. Copyright © 2013 Elsevier Ltd. All rights reserved.

Complexity in electronic negotiation support systems.

Science.gov (United States)

Griessmair, Michele; Strunk, Guido; Vetschera, Rudolf; Koeszegi, Sabine T

2011-10-01

It is generally acknowledged that the medium influences the way we communicate and negotiation research directs considerable attention to the impact of different electronic communication modes on the negotiation process and outcomes. Complexity theories offer models and methods that allow the investigation of how pattern and temporal sequences unfold over time in negotiation interactions. By focusing on the dynamic and interactive quality of negotiations as well as the information, choice, and uncertainty contained in the negotiation process, the complexity perspective addresses several issues of central interest in classical negotiation research. In the present study we compare the complexity of the negotiation communication process among synchronous and asynchronous negotiations (IM vs. e-mail) as well as an electronic negotiation support system including a decision support system (DSS). For this purpose, transcripts of 145 negotiations have been coded and analyzed with the Shannon entropy and the grammar complexity. Our results show that negotiating asynchronically via e-mail as well as including a DSS significantly reduces the complexity of the negotiation process. Furthermore, a reduction of the complexity increases the probability of reaching an agreement.

Foundations of Complex Systems Nonlinear Dynamics, Statistical Physics, and Prediction

CERN Document Server

Nicolis, Gregoire

2007-01-01

Complexity is emerging as a post-Newtonian paradigm for approaching a large body of phenomena of concern at the crossroads of physical, engineering, environmental, life and human sciences from a unifying point of view. This book outlines the foundations of modern complexity research as it arose from the cross-fertilization of ideas and tools from nonlinear science, statistical physics and numerical simulation. It is shown how these developments lead to an understanding, both qualitative and quantitative, of the complex systems encountered in nature and in everyday experience and, conversely, h

The brain as a dynamic physical system.

Science.gov (United States)

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

1994-06-01

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

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

Science.gov (United States)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

Validating cognitive support for operators of complex human-machine systems

International Nuclear Information System (INIS)

O'Hara, J.; Wachtel, J.

1995-01-01

Modem nuclear power plants (NPPs) are complex systems whose performance is the result of an intricate interaction of human and system control. A complex system may be defined as one which supports a dynamic process involving a large number of elements that interact in many different ways. Safety is addressed through defense-in-depth design and preplanning; i.e., designers consider the types of failures that are most likely to occur and those of high consequence, and design their solutions in advance. However, complex interactions and their failure modes cannot always be anticipated by the designer and may be unfamiliar to plant personnel. These situations may pose cognitive demands on plant personnel, both individually and as a crew. Other factors may contribute to the cognitive challenges of NPP operation as well, including hierarchal processes, dynamic pace, system redundancy and reliability, and conflicting objectives. These factors are discussed in this paper

Collectives and the design of complex systems

CERN Document Server

Wolpert, David

2004-01-01

Increasingly powerful computers are making possible distributed systems comprised of many adaptive and self-motivated computational agents. Such systems, when distinguished by system-level performance criteria, are known as "collectives." Collectives and the Design of Complex Systems lays the foundation for a science of collectives and describes how to design them for optimal performance. An introductory survey chapter is followed by descriptions of information-processing problems that can only be solved by the joint actions of large communities of computers, each running its own complex, decentralized machine-learning algorithm. Subsequent chapters analyze the dynamics and structures of collectives, as well as address economic, model-free, and control-theory approaches to designing complex systems. The work assumes a modest understanding of basic statistics and calculus. Topics and Features: Introduces the burgeoning science of collectives and its practical applications in a single useful volume Combines ap...

Smart modeling and simulation for complex systems practice and theory

CERN Document Server

Ren, Fenghui; Zhang, Minjie; Ito, Takayuki; Tang, Xijin

2015-01-01

This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.

Effects of stressor characteristics on early warning signs of critical transitions and "critical coupling" in complex dynamical systems.

Science.gov (United States)

Blume, Steffen O P; Sansavini, Giovanni

2017-12-01

Complex dynamical systems face abrupt transitions into unstable and catastrophic regimes. These critical transitions are triggered by gradual modifications in stressors, which push the dynamical system towards unstable regimes. Bifurcation analysis can characterize such critical thresholds, beyond which systems become unstable. Moreover, the stochasticity of the external stressors causes small-scale fluctuations in the system response. In some systems, the decomposition of these signal fluctuations into precursor signals can reveal early warning signs prior to the critical transition. Here, we present a dynamical analysis of a power system subjected to an increasing load level and small-scale stochastic load perturbations. We show that the auto- and cross-correlations of bus voltage magnitudes increase, leading up to a Hopf bifurcation point, and further grow until the system collapses. This evidences a gradual transition into a state of "critical coupling," which is complementary to the established concept of "critical slowing down." Furthermore, we analyze the effects of the type of load perturbation and load characteristics on early warning signs and find that gradient changes in the autocorrelation provide early warning signs of the imminent critical transition under white-noise but not for auto-correlated load perturbations. Furthermore, the cross-correlation between all voltage magnitude pairs generally increases prior to and beyond the Hopf bifurcation point, indicating "critical coupling," but cannot provide early warning indications. Finally, we show that the established early warning indicators are oblivious to limit-induced bifurcations and, in the case of the power system model considered here, only react to an approaching Hopf bifurcation.

From complex spatial dynamics to simple Markov chain models: do predators and prey leave footprints?

DEFF Research Database (Denmark)

Nachman, Gøsta Støger; Borregaard, Michael Krabbe

2010-01-01

to another, are then depicted in a state transition diagram, constituting the "footprints" of the underlying population dynamics. We investigate to what extent changes in the population processes modeled in the complex simulation (i.e. the predator's functional response and the dispersal rates of both......In this paper we present a concept for using presence-absence data to recover information on the population dynamics of predator-prey systems. We use a highly complex and spatially explicit simulation model of a predator-prey mite system to generate simple presence-absence data: the number...... of transition probabilities on state variables, and combine this information in a Markov chain transition matrix model. Finally, we use this extended model to predict the long-term dynamics of the system and to reveal its asymptotic steady state properties....

Dynamic complexities in a parasitoid-host-parasitoid ecological model

International Nuclear Information System (INIS)

Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

2009-01-01

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

Dynamic complexities in a parasitoid-host-parasitoid ecological model

Energy Technology Data Exchange (ETDEWEB)

Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

2009-01-15

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

Challenges in the analysis of complex systems: introduction and overview

Science.gov (United States)

Hastings, Harold M.; Davidsen, Jörn; Leung, Henry

2017-12-01

One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.

Dynamics in electron transfer protein complexes

OpenAIRE

Bashir, Qamar

2010-01-01

Recent studies have provided experimental evidence for the existence of an encounter complex, a transient intermediate in the formation of protein complexes. We have used paramagnetic relaxation enhancement NMR spectroscopy in combination with Monte Carlo simulations to characterize and visualize the ensemble of encounter orientations in the short-lived electron transfer complex of yeast Cc and CcP. The complete conformational space sampled by the protein molecules during the dynamic part of ...

A Symbolic and Graphical Computer Representation of Dynamical Systems

Science.gov (United States)

Gould, Laurence I.

2005-04-01

AUTONO is a Macsyma/Maxima program, designed at the University of Hartford, for solving autonomous systems of differential equations as well as for relating Lagrangians and Hamiltonians to their associated dynamical equations. AUTONO can be used in a number of fields to decipher a variety of complex dynamical systems with ease, producing their Lagrangian and Hamiltonian equations in seconds. These equations can then be incorporated into VisSim, a modeling and simulation program, which yields graphical representations of motion in a given system through easily chosen input parameters. The program, along with the VisSim differential-equations graphical package, allows for resolution and easy understanding of complex problems in a relatively short time; thus enabling quicker and more advanced computing of dynamical systems on any number of platforms---from a network of sensors on a space probe, to the behavior of neural networks, to the effects of an electromagnetic field on components in a dynamical system. A flowchart of AUTONO, along with some simple applications and VisSim output, will be shown.

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

Science.gov (United States)

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

Advances in dynamics, patterns, cognition challenges in complexity

CERN Document Server

Pikovsky, Arkady; Rulkov, Nikolai; Tsimring, Lev

2017-01-01

This book focuses on recent progress in complexity research based on the fundamental nonlinear dynamical and statistical theory of oscillations, waves, chaos, and structures far from equilibrium. Celebrating seminal contributions to the field by Prof. M. I. Rabinovich of the University of California at San Diego, this volume brings together perspectives on both the fundamental aspects of complexity studies, as well as in applications in different fields ranging from granular patterns to understanding of the cognitive brain and mind dynamics. The slate of world-class authors review recent achievements that together present a broad and coherent coverage of modern research in complexity greater than the sum of its parts. Presents the most up-to-date developments in the studies of complexity Combines basic and applied aspects Links background nonlinear theory of oscillations and waves with modern approaches Allows readers to recognize general dynamical principles across the applications fields.

Dynamical systems on networks a tutorial

CERN Document Server

Porter, Mason A

2016-01-01

This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Appli...

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

Directory of Open Access Journals (Sweden)

Jian Liu

Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

Science.gov (United States)

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

The diminishing role of hubs in dynamical processes on complex networks.

Science.gov (United States)

Quax, Rick; Apolloni, Andrea; Sloot, Peter M A

2013-11-06

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein-protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature.

What Is a Complex Innovation System?

Science.gov (United States)

Katz, J. Sylvan

2016-01-01

Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too. PMID:27258040

What Is a Complex Innovation System?

Directory of Open Access Journals (Sweden)

J Sylvan Katz

Full Text Available Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.

[Origination of Pareto distribution in complex dynamic systems].

Science.gov (United States)

Chernavskiĭ, D S; Nikitin, A P; Chernavskaia, O D

2008-01-01

The Pareto distribution, whose probability density function can be approximated at sufficiently great chi as rho(chi) - chi(-alpha), where alpha > or = 2, is of crucial importance from both the theoretical and practical point of view. The main reason is its qualitative distinction from the normal (Gaussian) distribution. Namely, the probability of high deviations appears to be significantly higher. The conception of the universal applicability of the Gauss law remains to be widely distributed despite the lack of objective confirmation of this notion in a variety of application areas. The origin of the Pareto distribution in dynamic systems located in the gaussian noise field is considered. A simple one-dimensional model is discussed where the system response in a rather wide interval of the variable can be quite precisely approximated by this distribution.

SUPERCOMPUTER SIMULATION OF CRITICAL PHENOMENA IN COMPLEX SOCIAL SYSTEMS

Directory of Open Access Journals (Sweden)

Petrus M.A. Sloot

2014-09-01

Full Text Available The paper describes a problem of computer simulation of critical phenomena in complex social systems on a petascale computing systems in frames of complex networks approach. The three-layer system of nested models of complex networks is proposed including aggregated analytical model to identify critical phenomena, detailed model of individualized network dynamics and model to adjust a topological structure of a complex network. The scalable parallel algorithm covering all layers of complex networks simulation is proposed. Performance of the algorithm is studied on different supercomputing systems. The issues of software and information infrastructure of complex networks simulation are discussed including organization of distributed calculations, crawling the data in social networks and results visualization. The applications of developed methods and technologies are considered including simulation of criminal networks disruption, fast rumors spreading in social networks, evolution of financial networks and epidemics spreading.

Vibrations and stability of complex beam systems

CERN Document Server

Stojanović, Vladimir

2015-01-01

 This book reports on solved problems concerning vibrations and stability of complex beam systems. The complexity of a system is considered from two points of view: the complexity originating from the nature of the structure, in the case of two or more elastically connected beams; and the complexity derived from the dynamic behavior of the system, in the case of a damaged single beam, resulting from the harm done to its simple structure. Furthermore, the book describes the analytical derivation of equations of two or more elastically connected beams, using four different theories (Euler, Rayleigh, Timoshenko and Reddy-Bickford). It also reports on a new, improved p-version of the finite element method for geometrically nonlinear vibrations. The new method provides more accurate approximations of solutions, while also allowing us to analyze geometrically nonlinear vibrations. The book describes the appearance of longitudinal vibrations of damaged clamped-clamped beams as a result of discontinuity (damage). It...

Inferring the physical connectivity of complex networks from their functional dynamics

Directory of Open Access Journals (Sweden)

Holm Liisa

2010-05-01

background network to the observed change of the functional activities in the system. Conclusions The results presented in this study indicate a strong relationship between the structure and dynamics of complex network systems. As coupling strength increases, synchronization emerges among hub nodes and recruits small-degree nodes. The results show that the onset of global synchronization in the system hinders the reconstruction of an underlying complex structure. Our analysis helps to clarify how the synchronization is achieved in systems of different network topologies.

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

Science.gov (United States)

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

Dependability problems of complex information systems

CERN Document Server

Zamojski, Wojciech

2014-01-01

This monograph presents original research results on selected problems of dependability in contemporary Complex Information Systems (CIS). The ten chapters are concentrated around the following three aspects: methods for modelling of the system and its components, tasks ? or in more generic and more adequate interpretation, functionalities ? accomplished by the system and conditions for their correct realization in the dynamic operational environment. While the main focus is on theoretical advances and roadmaps for implementations of new technologies, a?much needed forum for sharing of the bes

The heterogeneous dynamics of economic complexity.

Science.gov (United States)

Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2015-01-01

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

Dynamic Complexity Study of Nuclear Reactor and Process Heat Application Integration

International Nuclear Information System (INIS)

Taylor, J'Tia Patrice; Shropshire, David E.

2009-01-01

This paper describes the key obstacles and challenges facing the integration of nuclear reactors with process heat applications as they relate to dynamic issues. The paper also presents capabilities of current modeling and analysis tools available to investigate these issues. A pragmatic approach to an analysis is developed with the ultimate objective of improving the viability of nuclear energy as a heat source for process industries. The extension of nuclear energy to process heat industries would improve energy security and aid in reduction of carbon emissions by reducing demands for foreign derived fossil fuels. The paper begins with an overview of nuclear reactors and process application for potential use in an integrated system. Reactors are evaluated against specific characteristics that determine their compatibility with process applications such as heat outlet temperature. The reactor system categories include light water, heavy water, small to medium, near term high-temperature, and far term high temperature reactors. Low temperature process systems include desalination, district heating, and tar sands and shale oil recovery. High temperature processes that support hydrogen production include steam reforming, steam cracking, hydrogen production by electrolysis, and far-term applications such as the sulfur iodine chemical process and high-temperature electrolysis. A simple static matching between complementary systems is performed; however, to gain a true appreciation for system integration complexity, time dependent dynamic analysis is required. The paper identifies critical issues arising from dynamic complexity associated with integration of systems. Operational issues include scheduling conflicts and resource allocation for heat and electricity. Additionally, economic and safety considerations that could impact the successful integration of these systems are considered. Economic issues include the cost differential arising due to an integrated system

The dynamical complexity of optically injected semiconductor lasers

International Nuclear Information System (INIS)

Wieczorek, S.; Krauskopf, B.; Simpson, T.B.; Lenstra, D.

2005-01-01

This report presents a modern approach to the theoretical and experimental study of complex nonlinear behavior of a semiconductor laser with optical injection-an example of a widely applied and technologically relevant forced nonlinear oscillator. We show that the careful bifurcation analysis of a rate equation model yields (i) a deeper understanding of already studied physical phenomena, and (ii) the discovery of new dynamical effects, such as multipulse excitability. Different instabilities, cascades of bifurcations, multistability, and sudden chaotic transitions, which are often viewed as independent, are in fact logically connected into a consistent web of bifurcations via special points called organizing centers. This theoretical bifurcation analysis has predictive power, which manifests itself in good agreement with experimental measurements over a wide range of parameters and diversity of dynamics. While it is dealing with the specific system of an optically injected laser, our work constitutes the state-of-the-art in the understanding and modeling of a nonlinear physical system in general

Complex systems approach to fire dynamics and climate change impacts

Science.gov (United States)

Pueyo, S.

2012-04-01

I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire

Outer synchronization between two different fractional-order general complex dynamical networks

International Nuclear Information System (INIS)

Xiang-Jun, Wu; Hong-Tao, Lu

2010-01-01

Outer synchronization between two different fractional-order general complex dynamical networks is investigated in this paper. Based on the stability theory of the fractional-order system, the sufficient criteria for outer synchronization are derived analytically by applying the nonlinear control and the bidirectional coupling methods. The proposed synchronization method is applicable to almost all kinds of coupled fractional-order general complex dynamical networks. Neither a symmetric nor irreducible coupling configuration matrix is required. In addition, no constraint is imposed on the inner-coupling matrix. Numerical examples are also provided to demonstrate the validity of the presented synchronization scheme. Numeric evidence shows that both the feedback strength k and the fractional order α can be chosen appropriately to adjust the synchronization effect effectively. (general)

Pattern dynamics of the reaction-diffusion immune system.

Science.gov (United States)

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.

Modelling the crop: from system dynamics to systems biology

NARCIS (Netherlands)

Yin, X.; Struik, P.C.

2010-01-01

There is strong interplant competition in a crop stand for various limiting resources, resulting in complex compensation and regulation mechanisms along the developmental cascade of the whole crop. Despite decades-long use of principles in system dynamics (e.g. feedback control), current crop models

Reaction dynamics in polyatomic molecular systems

Energy Technology Data Exchange (ETDEWEB)

Miller, W.H. [Lawrence Berkeley Laboratory, CA (United States)

1993-12-01

The goal of this program is the development of theoretical methods and models for describing the dynamics of chemical reactions, with specific interest for application to polyatomic molecular systems of special interest and relevance. There is interest in developing the most rigorous possible theoretical approaches and also in more approximate treatments that are more readily applicable to complex systems.

Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks.

Science.gov (United States)

Kastrup, Christian J; Runyon, Matthew K; Lucchetta, Elena M; Price, Jessica M; Ismagilov, Rustem F

2008-04-01

Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to

Adaptive, dynamic, and resilient systems

CERN Document Server

Suri, Niranjan

2015-01-01

As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

Message survival and decision dynamics in a class of reactive complex systems subject to external fields

Science.gov (United States)

Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.

2014-07-01

In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.

Adaptive control of structural balance for complex dynamical networks based on dynamic coupling of nodes

Science.gov (United States)

Gao, Zilin; Wang, Yinhe; Zhang, Lili

2018-02-01

In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.

System dynamics

International Nuclear Information System (INIS)

Kim, Do Hun; Mun, Tae Hun; Kim, Dong Hwan

1999-02-01

This book introduces systems thinking and conceptual tool and modeling tool of dynamics system such as tragedy of single thinking, accessible way of system dynamics, feedback structure and causal loop diagram analysis, basic of system dynamics modeling, causal loop diagram and system dynamics modeling, information delay modeling, discovery and application for policy, modeling of crisis of agricultural and stock breeding products, dynamic model and lesson in ecosystem, development and decadence of cites and innovation of education forward system thinking.

Modelling the impact of mining on socio-economic infrastructure development: a system dynamics approach

Directory of Open Access Journals (Sweden)

Maluleke, George

2016-12-01

Full Text Available The contribution of mining activities to social infrastructure and human development is a complex socio-economic development issue in South Africa. Complexity theory has introduced a new approach to solving problems in social systems, recognising them as complex systems. The socio-economic development system in South Africa falls into this category of complex systems. Analysing such a system requires that a number of feedback loops and details about the issues be analysed simultaneously. This level of complexity is above a human’s ability to comprehend without the aid of tools such as systems thinking and system dynamics. The causality between investment in infrastructure capacity and socio-economic development is dynamic. The relationship is influenced by exogenous feedback that, if not managed, is likely to reverse itself. This paper presents the results of a system dynamics modelling of the relationship, based on the principle of relative attractiveness developed in previous system dynamics research. A Monte Carlo analysis is used to determine the sensitivity of the system to changes in feedback. The paper concludes that the limits to growth in a socio-economic environment are determined by more factors than the availability of capital, and also include land capacity constraints and skills shortage.

Complex networks: Dynamics and security

Indian Academy of Sciences (India)

This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. ... Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona 85287, USA; Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil ...

Narrowing the gap between network models and real complex systems

OpenAIRE

Viamontes Esquivel, Alcides

2014-01-01

Simple network models that focus only on graph topology or, at best, basic interactions are often insufficient to capture all the aspects of a dynamic complex system. In this thesis, I explore those limitations, and some concrete methods of resolving them. I argue that, in order to succeed at interpreting and influencing complex systems, we need to take into account  slightly more complex parts, interactions and information flows in our models.This thesis supports that affirmation with five a...

Study of Complexities in Bouncing Ball Dynamical System

Directory of Open Access Journals (Sweden)

Lal Mohan SAHA

2016-04-01

Full Text Available Evolutionary motions in a bouncing ball system consisting of a ball having a free fall in the Earth’s gravitational field have been studied systematically. Because of nonlinear form of the equations of motion, evolutions show chaos for certain set of parameters for certain initial conditions. Bifurcation diagram has been drawn to study regular and chaotic behavior. Numerical calculations have been performed to calculate Lyapunov exponents, topological entropies and correlation dimension as measures of complexity. Numerical results are shown through interesting graphics.

Nostradamus 2014 prediction, modeling and analysis of complex systems

CERN Document Server

Suganthan, Ponnuthurai; Chen, Guanrong; Snasel, Vaclav; Abraham, Ajith; Rössler, Otto

2014-01-01

The prediction of behavior of complex systems, analysis and modeling of its structure is a vitally important problem in engineering, economy and generally in science today. Examples of such systems can be seen in the world around us (including our bodies) and of course in almost every scientific discipline including such “exotic” domains as the earth’s atmosphere, turbulent fluids, economics (exchange rate and stock markets), population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such complex dynamics, which often exhibit strange behavior, and to use it in research or industrial applications, it is paramount to create its models. For this purpose there exists a rich spectrum of methods, from classical such as ARMA models or Box Jenkins method to modern ones like evolutionary computation, neural networks, fuzzy logic, geometry, deterministic chaos amongst others. This proceedings book is a collection of accepted ...

Understanding the dynamics of the Seguro Popular de Salud policy implementation in Mexico from a complex adaptive systems perspective.

Science.gov (United States)

Nigenda, Gustavo; González-Robledo, Luz María; Juárez-Ramírez, Clara; Adam, Taghreed

2016-05-13

In 2003, Mexico's Seguro Popular de Salud (SPS), was launched as an innovative financial mechanism implemented to channel new funds to provide health insurance to 50 million Mexicans and to reduce systemic financial inequities. The objective of this article is to understand the complexity and dynamics that contributed to the adaptation of the policy in the implementation stage, how these changes occurred, and why, from a complex and adaptive systems perspective. A complex adaptive systems (CAS) framework was used to carry out a secondary analysis of data obtained from four SPS's implementation evaluations. We first identified key actors, their roles, incentives and power, and their responses to the policy and guidelines. We then developed a causal loop diagram to disentangle the feedback dynamics associated with the modifications of the policy implementation which we then analyzed using a CAS perspective. Implementation variations were identified in seven core design features during the first 10 years of implementation period, and in each case, the SPS's central coordination introduced modifications in response to the reactions of the different actors. We identified several CAS phenomena associated with these changes including phase transitions, network emergence, resistance to change, history dependence, and feedback loops. Our findings generate valuable lessons to policy implementation processes, especially those involving a monetary component, where the emergence of coping mechanisms and other CAS phenomena inevitably lead to modifications of policies and their interpretation by those who implement them. These include the difficulty of implementing strategies that aim to pool funds through solidarity among beneficiaries where the rich support the poor when there are no incentives for the rich to do so. Also, how resistance to change and history dependence can pose significant challenges to implementing changes, where the local actors use their significant power

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

Science.gov (United States)

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.

Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems

International Nuclear Information System (INIS)

Fang Jinqing

1995-03-01

Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.)

Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems

Energy Technology Data Exchange (ETDEWEB)

Jinqing, Fang [Academia Sinica, Beijing, BJ (China). Inst. of Atomic Energy

1995-03-01

Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.).

Unified Computational Intelligence for Complex Systems

CERN Document Server

Seiffertt, John

2010-01-01

Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e

Dynamic complexities in a seasonal prevention epidemic model with birth pulses

International Nuclear Information System (INIS)

Gao Shujing; Chen Lansun; Sun Lihua

2005-01-01

In most of population dynamics, increases in population due to birth are assumed to be time-dependent, but many species reproduce only during a single period of the year. In this paper, we propose an epidemic model with density-dependent birth pulses and seasonal prevention. Using the discrete dynamical system determined by stroboscopic map, we obtain the local or global stability, numerical simulation shows there is a characteristic sequence of bifurcations, leading to chaotic dynamics, which implies that the dynamical behaviors of the epidemic model with birth pulses and seasonal prevention are very complex, including small amplitude oscillations, large-amplitude multi-annual cycles and chaos. This suggests that birth pulse, in effect, provides a natural period or cyclicity that may lead a period-doubling route to chaos

Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

CERN Document Server

Su, Housheng

2013-01-01

Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

From precision polymers to complex materials and systems

Science.gov (United States)

Lutz, Jean-François; Lehn, Jean-Marie; Meijer, E. W.; Matyjaszewski, Krzysztof

2016-05-01

Complex chemical systems, such as living biological matter, are highly organized structures based on discrete molecules in constant dynamic interactions. These natural materials can evolve and adapt to their environment. By contrast, man-made materials exhibit simpler properties. In this Review, we highlight that most of the necessary elements for the development of more complex synthetic matter are available today. Using modern strategies, such as controlled radical polymerizations, supramolecular polymerizations or stepwise synthesis, polymers with precisely controlled molecular structures can be synthesized. Moreover, such tailored polymers can be folded or self-assembled into defined nanoscale morphologies. These self-organized macromolecular objects can be at thermal equilibrium or can be driven out of equilibrium. Recently, in the latter case, interesting dynamic materials have been developed. However, this is just a start, and more complex adaptive materials are anticipated.

Dynamics of Variable Mass Systems

Science.gov (United States)

Eke, Fidelis O.

1998-01-01

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

From precision polymers to complex materials and systems

NARCIS (Netherlands)

Lutz, J.F.; Lehn, J.M.; Meijer, E.W.; Matyjaszewski, K.

2016-01-01

Complex chemical systems, such as living biological matter, are highly organized structures based on discrete molecules in constant dynamic interactions. These natural materials can evolve and adapt to their environment. By contrast, man-made materials exhibit simpler properties. In this Review, we

Sustainability science: accounting for nonlinear dynamics in policy and social-ecological systems

Science.gov (United States)

Resilience is an emergent property of complex systems. Understanding resilience is critical for sustainability science, as linked social-ecological systems and the policy process that governs them are characterized by non-linear dynamics. Non-linear dynamics in these systems mean...

Complex networks under dynamic repair model

Science.gov (United States)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Statistical physics of complex systems a concise introduction

CERN Document Server

Bertin, Eric

2016-01-01

This course-tested primer provides graduate students and non-specialists with a basic understanding of the concepts and methods of statistical physics and demonstrates their wide range of applications to interdisciplinary topics in the field of complex system sciences, including selected aspects of theoretical modeling in biology and the social sciences. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting units, and on the other to predict the macroscopic, collective behavior of the system considered from the perspective of the microscopic laws governing the dynamics of the individual entities. These two goals are essentially also shared by what is now called 'complex systems science', and as such, systems studied in the framework of statistical physics may be considered to be among the simplest examples of complex systems – while also offering a rather well developed mathematical treatment. The second ...

Network Physiology: How Organ Systems Dynamically Interact

Science.gov (United States)

Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

2015-01-01

We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073

Network Physiology: How Organ Systems Dynamically Interact.

Science.gov (United States)

Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

2015-01-01

We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

How Well Do Students in Secondary School Understand Temporal Development of Dynamical Systems?

Science.gov (United States)

Forjan, Matej; Grubelnik, Vladimir

2015-01-01

Despite difficulties understanding the dynamics of complex systems only simple dynamical systems without feedback connections have been taught in secondary school physics. Consequently, students do not have opportunities to develop intuition of temporal development of systems, whose dynamics are conditioned by the influence of feedback processes.…

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

The System Dynamics Model User Sustainability Explorer (SD-MUSE): a user-friendly tool for interpreting system dynamic models

Science.gov (United States)

System Dynamics (SD) models are useful for holistic integration of data to evaluate indirect and cumulative effects and inform decisions. Complex SD models can provide key insights into how decisions affect the three interconnected pillars of sustainability. However, the complexi...

Household Food Security Policy Analysis A System Dynamics Perspective

Directory of Open Access Journals (Sweden)

Isdore Paterson Guma

2015-08-01

Full Text Available Household food security FS is complex and requires multiple stakeholder intervention. Systemic approach aids stakeholders to understand the mechanisms and feedback between complexities in food security providing effective decision making as global resource consumption continues to grow. The study investigated food security challenges and a system dynamics model was developed for evaluating policies and intervention strategies for better livelihood at household level. Dynamic synthesis methodology questionnaires and interview guide were used to unearth food security challenges faced by households. A causal loop diagram was drawn. The model demonstrates a balance between food stock seeds preserved seeds for sale and consumption from crop harvest throughout the food cycles. This research makes contribution to the literature by evaluating dynamic synthesis methodology and FS policy discussions from a feedback point of view.

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

Science.gov (United States)

Baffy, György; Loscalzo, Joseph

2014-05-28

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

Complexity and network dynamics in physiological adaptation: An integrated view

OpenAIRE

Baffy, Gyorgy; Loscalzo, Joseph

2014-01-01

Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of t...

Making System Dynamics Cool II : New Hot Teaching and Testing Cases of Increasing Complexity

NARCIS (Netherlands)

Pruyt, E.

2010-01-01

This follow-up paper presents several actual cases for testing and teaching System Dynamics. The cases were developed between April 2009 and January 2010 for the Introductory System Dynamics courses at Delft University of Technology in the Netherlands. They can be used for teaching and testing

Charge-Transfer Complexes Studied by Dynamic Force Spectroscopy

Directory of Open Access Journals (Sweden)

Jurriaan Huskens

2013-03-01

Full Text Available In this paper, the strength and kinetics of two charge-transfer complexes, naphthol-methylviologen and pyrene-methylviologen, are studied using dynamic force spectroscopy. The dissociation rates indicate an enhanced stability of the pyrene-methylviologen complex, which agrees with its higher thermodynamic stability compared to naphthol-methylviologen complex.

A paradox for traffic dynamics in complex networks with ATIS

International Nuclear Information System (INIS)

Zheng Jianfeng; Gao Ziyou

2008-01-01

In this work, we study the statistical properties of traffic (e.g., vehicles) dynamics in complex networks, by introducing advanced transportation information systems (ATIS). The ATIS can provide the information of traffic flow pattern throughout the network and have an obvious effect on path routing strategy for such vehicles equipped with ATIS. The ATIS can be described by the understanding of link cost functions. Different indices such as efficiency and system total cost are discussed in depth. It is found that, for random networks (scale-free networks), the efficiency is effectively improved (decreased) if ATIS is properly equipped; however the system total cost is largely increased (decreased). It indicates that there exists a paradox between the efficiency and system total cost in complex networks. Furthermore, we report the simulation results by considering different kinds of link cost functions, and the paradox is recovered. Finally, we extend our traffic model, and also find the existence of the paradox

A self-cognizant dynamic system approach for prognostics and health management

Science.gov (United States)

Bai, Guangxing; Wang, Pingfeng; Hu, Chao

2015-03-01

Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity and invisibility of rules and states of most dynamic systems, developing an effective approach to track evolving system states becomes a major challenge. This paper presents a new self-cognizant dynamic system (SCDS) approach that incorporates artificial intelligence into dynamic system modeling for PHM. A feed-forward neural network (FFNN) is selected to approximate a complex system response which is challenging task in general due to inaccessible system physics. The trained FFNN model is then embedded into a dual extended Kalman filter algorithm to track down system dynamics. A recursive computation technique used to update the FFNN model using online measurements is also derived. To validate the proposed SCDS approach, a battery dynamic system is considered as an experimental application. After modeling the battery system by a FFNN model and a state-space model, the state-of-charge (SoC) and state-of-health (SoH) are estimated by updating the FFNN model using the proposed approach. Experimental results suggest that the proposed approach improves the efficiency and accuracy for battery health management.

Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach

Directory of Open Access Journals (Sweden)

Hongyong Wang

2018-01-01

Full Text Available In order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity research, no simple means is available to integrate airspace and traffic flow characteristics. In this paper, we propose a new approach for the measurement of air traffic situation complexity. This approach considers the effects of both airspace and traffic flow and objectively quantifies air traffic situation complexity. Considering the aircraft, waypoints, and airways as nodes, and the complexity relationships among these nodes as edges, a dynamic weighted network is constructed. Air traffic situation complexity is defined as the sum of the weights of all edges in the network, and the relationships of complexity with some commonly used indices are statistically analyzed. The results indicate that the new complexity index is more accurate than traffic count and reflects the number of trajectory changes as well as the high-risk situations. Additionally, analysis of potential applications reveals that this new index contributes to achieving complexity-based management, which represents an efficient method for increasing airspace system capacity.

Dynamic Complexity Study of Nuclear Reactor and Process Heat Application Integration

Energy Technology Data Exchange (ETDEWEB)

J' Tia Patrice Taylor; David E. Shropshire

2009-09-01

Abstract This paper describes the key obstacles and challenges facing the integration of nuclear reactors with process heat applications as they relate to dynamic issues. The paper also presents capabilities of current modeling and analysis tools available to investigate these issues. A pragmatic approach to an analysis is developed with the ultimate objective of improving the viability of nuclear energy as a heat source for process industries. The extension of nuclear energy to process heat industries would improve energy security and aid in reduction of carbon emissions by reducing demands for foreign derived fossil fuels. The paper begins with an overview of nuclear reactors and process application for potential use in an integrated system. Reactors are evaluated against specific characteristics that determine their compatibility with process applications such as heat outlet temperature. The reactor system categories include light water, heavy water, small to medium, near term high-temperature, and far term high temperature reactors. Low temperature process systems include desalination, district heating, and tar sands and shale oil recovery. High temperature processes that support hydrogen production include steam reforming, steam cracking, hydrogen production by electrolysis, and far-term applications such as the sulfur iodine chemical process and high-temperature electrolysis. A simple static matching between complementary systems is performed; however, to gain a true appreciation for system integration complexity, time dependent dynamic analysis is required. The paper identifies critical issues arising from dynamic complexity associated with integration of systems. Operational issues include scheduling conflicts and resource allocation for heat and electricity. Additionally, economic and safety considerations that could impact the successful integration of these systems are considered. Economic issues include the cost differential arising due to an integrated

Complex fluids in biological systems experiment, theory, and computation

CERN Document Server

2015-01-01

This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application

OpenAIRE

Li, Xiang

2005-01-01

In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...

Stability and Control of Large-Scale Dynamical Systems A Vector Dissipative Systems Approach

CERN Document Server

Haddad, Wassim M

2011-01-01

Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynami

Exponentially asymptotical synchronization in uncertain complex dynamical networks with time delay

Energy Technology Data Exchange (ETDEWEB)

Luo Qun; Yang Han; Li Lixiang; Yang Yixian [Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876 (China); Han Jiangxue, E-mail: luoqun@bupt.edu.c [National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing 100876 (China)

2010-12-10

Over the past decade, complex dynamical network synchronization has attracted more and more attention and important developments have been made. In this paper, we explore the scheme of globally exponentially asymptotical synchronization in complex dynamical networks with time delay. Based on Lyapunov stability theory and through defining the error function between adjacent nodes, four novel adaptive controllers are designed under four situations where the Lipschitz constants of the state function in nodes are known or unknown and the network structure is certain or uncertain, respectively. These controllers could not only globally asymptotically synchronize all nodes in networks, but also ensure that the error functions do not exceed the pre-scheduled exponential function. Finally, simulations of the synchronization among the chaotic system in the small-world and scale-free network structures are presented, which prove the effectiveness and feasibility of our controllers.

Robustness of pinning a general complex dynamical network

International Nuclear Information System (INIS)

Wang Lei; Sun Youxian

2010-01-01

This Letter studies the robustness problem of pinning a general complex dynamical network toward an assigned synchronous evolution. Several synchronization criteria are presented to guarantee the convergence of the pinning process locally and globally by construction of Lyapunov functions. In particular, if a pinning strategy has been designed for synchronization of a given complex dynamical network, then no matter what uncertainties occur among the pinned nodes, synchronization can still be guaranteed through the pinning. The analytical results show that pinning control has a certain robustness against perturbations on network architecture: adding, deleting and changing the weights of edges. Numerical simulations illustrated by scale-free complex networks verify the theoretical results above-acquired.

Dynamical singularities of glassy systems in a quantum quench.

Science.gov (United States)

Obuchi, Tomoyuki; Takahashi, Kazutaka

2012-11-01

We present a prototype of behavior of glassy systems driven by quantum dynamics in a quenching protocol by analyzing the random energy model in a transverse field. We calculate several types of dynamical quantum amplitude and find a freezing transition at some critical time. The behavior is understood by the partition-function zeros in the complex temperature plane. We discuss the properties of the freezing phase as a dynamical chaotic phase, which are contrasted to those of the spin-glass phase in the static system.

Modelling, Estimation and Control of Networked Complex Systems

CERN Document Server

Chiuso, Alessandro; Frasca, Mattia; Rizzo, Alessandro; Schenato, Luca; Zampieri, Sandro

2009-01-01

The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization of different disciplines and approaches. This book is devoted to networked systems which are one of the most promising paradigms of complexity. It is demonstrated that complex, dynamical networks are powerful tools to model, estimate, and control many interesting phenomena, like agent coordination, synchronization, social and economics events, networks of critical infrastructures, resources allocation, information processing, or control over communication networks. Moreover, it is shown how the recent technological advances in wireless communication and decreasing in cost and size of electronic devices are promoting the appearance of large inexpensive interconnected systems, each with computational, sensing and mobile cap...

Analysis of Dynamic Complexity of the Cyber Security Ecosystem of Colombia

Directory of Open Access Journals (Sweden)

Angélica Flórez

2016-07-01

Full Text Available This paper presents two proposals for the analysis of the complexity of the Cyber security Ecosystem of Colombia (CEC. This analysis shows the available knowledge about entities engaged in cyber security in Colombia and the relationships between them, which allow an understanding of the synergy between the different existing components. The complexity of the CEC is detailed from the view of the Influence Diagram of System Dynamics and the Domain Diagram of Software Engineering. The resulting model makes cyber security evident as a strategic component of national security.

Using system dynamics simulation for assessment of hydropower system safety

Science.gov (United States)

King, L. M.; Simonovic, S. P.; Hartford, D. N. D.

2017-08-01

Hydropower infrastructure systems are complex, high consequence structures which must be operated safely to avoid catastrophic impacts to human life, the environment, and the economy. Dam safety practitioners must have an in-depth understanding of how these systems function under various operating conditions in order to ensure the appropriate measures are taken to reduce system vulnerability. Simulation of system operating conditions allows modelers to investigate system performance from the beginning of an undesirable event to full system recovery. System dynamics simulation facilitates the modeling of dynamic interactions among complex arrangements of system components, providing outputs of system performance that can be used to quantify safety. This paper presents the framework for a modeling approach that can be used to simulate a range of potential operating conditions for a hydropower infrastructure system. Details of the generic hydropower infrastructure system simulation model are provided. A case study is used to evaluate system outcomes in response to a particular earthquake scenario, with two system safety performance measures shown. Results indicate that the simulation model is able to estimate potential measures of system safety which relate to flow conveyance and flow retention. A comparison of operational and upgrade strategies is shown to demonstrate the utility of the model for comparing various operational response strategies, capital upgrade alternatives, and maintenance regimes. Results show that seismic upgrades to the spillway gates provide the largest improvement in system performance for the system and scenario of interest.

Dynamical Systems Approaches to Emotional Development

Science.gov (United States)

Camras, Linda A.; Witherington, David C.

2005-01-01

Within the last 20 years, transitions in the conceptualization of emotion and its development have given rise to calls for an explanatory framework that captures emotional development in all its organizational complexity and variability. Recent attempts have been made to couch emotional development in terms of a dynamical systems approach through…

Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems

Directory of Open Access Journals (Sweden)

Sergei A. Soldatenko

2017-01-01

Full Text Available The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.